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Section 1 Document Inf ormation

D~ate

Revision F01 2011-00105 Freedom of Information Act Request (POI 201100105) 12/16/2010

Originator

Riehie 1)

Recipient

Hackett 5

References

10-CFR-1004.8, HG-i

Keywords Projects

OCE, FOIA, Sensitive, Gonzaga University

Document # Title

Other Information

Originator Co. Recipient Co.

iDOE-RL Other

__________________________

( *1

Department of Energy

V

Richland Operations Office ~x

Box 550

XZ~vP.O.

Richland, Washington 99352 December 16. 20 10

CERTIFIED MAIL Mr. Sean Hackett Gonz7a(ta UnfiVerSiix P.O. 13ox 3528 Spokane., Washington 99220-352-8 Dear NIr. I lackett:. FREEDOMI OF INFORMATION ACT RE-QUEST (FOl 2011-00105) You requested, pursuant to the Freedom of informiation Act (FOIA), the following records on behalf of I leart of America Northwest relating to the U.S. Department of Energy' s (DOE) 2004 Final H-anford Solid Waste Environmental Impact Statement (EIS)-. i) The adequacy of DOE's 2004 FIS including: a. All correspondence between DOE and Battelle (the prim ary contractor for the Final EIS) in 2004 and 2005 relating to the adequacy of analysis, quality assurance, monitoring, and/or compliance with NEPA in preparing the final EIS. b. All corr-esponcence between DOE and the State of Washington between 2004 and 2005 relating, to the above-referenced conclusion including any records relating to the adequacy of analysis, quality assurance, monitoring, and/or compliance with NEPA in preparing the [i S. c, information pertaining to DOE' s July 2005 conclusion that the information in the groundwater cumulative impact analysis published in Appendix L of DOE's 2004 EIS was different than certain input parameters em ployed in the System Assessment Capability (SAC) computer model files that vvere used to prepare that analysis. d. Any correspondence or analysis during the 2004 to August 2005 time p~eriod between IBattelle/Pacific Northwest National Laboratory for information (PNNL,) pertaining to any inadeqjuacies of the final EIS (not just on groundwater analysis i.e. quality assurance issues including but not limited to groundwater analysis). A partial response was provided to yon on Decemnber 2, 2010. Included as Enclosure I are documents responsive to item lc of youir request. Included as Enclosure II are documents of ""ourrequest. responsive to item I1(I

Mr. Scan Hackett

_December

16. 2010

In a letter to vou dated November'3, 2010, we notified you that requests for records generated or in the possession of the Pacific Northwest National Laboratory and/or Battelle fall under the jurisdiction of DOE's Pacific Northwest Site Office (PN-SO). Therefore, a copy of your request was forwarded to the DOE Oakridge Office (PNSO's FOIA Service Center) by this office on October 2 1 20l10, and its FOLA Officer will respond directly to you. We have conducted a thorougih search and no other documents were located. This search was conducted by those within the agency who are most familiar with the subject matter of your request. in locations where documents would most likely be found including the RL's Office of Chief Counsel, administrati\ve record for the HISW EIS. Waste Managemnent Project, Groundwater Project, Assistant M1vanager for the Central Plateau, River Corridor Closure Project, Environmental Management Division and the Office of River Protection" s Environmental Compliance Division, Offie of the Manager, Office of the Deputy Manager, Chief of Staff Tank Farms Proj ect, WNaste Treatmnent and Imnmobilization. Plant Proj ect, Acquisition Management, Pro lect Adm-inistration. Puiblic, Internal, and Intergovernmental Affairs, and Environmental Safety and Quality. Durin- our search was used the following, keywordls: HSW EIS, H-anford Site Solid Waste Program Environmental Impact Statement, U.S. DOE and Battelle, Quality Assurance.. National Environmental Policy Act (NEPA). U.S. DOE and the State of Washington, and Ground water Cumulative Impact Analysis, In addition, you requested any and all informnation related to your request. TFhe FOIA requires toogh search for documents responsive to a request, not an thtanaecycndc exhaustive search. Wec cannot guarantee that you have been provided all information related to y'our request. as we did not conduct an exhaustive search. A search was conducted, however, by representativecs of the agency who are familiar with the subject areas of your request, in locations where responsive docuIments Would most likely be found. The undersiuned individual is responsible for this determination. You ha-ve the right to appeal to the Office of Hearings and1 Appeals, as provided in 10 CER 1004.8, for the adequacy of our search. Any Such appeal shiall be made in writing to the following address: Director, Office of Hearings and Appeals (HG-I1), U.S. Department of Energy, L'Enfant Plaza. Building-, 1000 independence Avenue SW, Washington, D.C. 20585- 1615, and shall be filed within 30 days after receipt of this letter. Should you choose to appeal. please provide this office with a copy of your letter.

Mr. Sean Hackett

2-December

16, 20 10

This letter completes yourF response dated October 8, 2010. If you have any questions regarding your request, please contact me at our address or on (509) 376-6288. Sincerely-,

ye Ic

OCE:DCR

Enclosures

Freedom of Inftormation Act Officer Office Of Conlinun ications and External Affairs

DOE-01 56 Environmental Impact Statement for Retrieval, Treatment, and Disposal of Tank Waste and Closure of Single-Shell Tanks at the Hanford Site, Richland, WA NEW OR CHANGED, DATA FORM 139 Relevant document, section, and page number: Final HanfordSite Solid (Radioactive and Hazardous) Waste ProgramEnvironmental Impact Statement, Benton County, Washington (DOE/EIS-286F)

Description of new data request or data change notice: Ms Burandt verbally requested an analysis of public comments received on the Hanford Solid Waste EIS to identify those that may be relevant to the TC EIS. Response from CH2M HILL: A team led by Dee Willis of CEES reviewed the public comments documented in Volume 111, "Comment Response Document," against five criteria to identify comments relevant to the Tank Closure EIS. The five criteria were: (1) Cumulative Impacts (shared by both EIS's), (2) Groundwater Impacts, (3) Acceptance of Tank Farm Waste Forms, (4) Long-Term Mitigation, and (5) Other Comments Expected to Be Received Again. Based on the judgment of the team, a listing of 41 "representative" comments were identified.

Distribution: Danny Parker, CH2M HILL Greg McLellan, CH2M HILL Mary Burandt, ORP Charlotte Johnson (2), SAIC Diane Stock, Administrative Record Administrative Record Filing Number: TBD

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PNNL-14760, Rev. 0, Release Data Package for the 2004 Composite Analysis PNNL-14824, River Data Package for the 2004 Composite Analysis PNNL-14753, Rev. 0, Groundwater Data Package for the 2004 Composite Analysis PNNL-14725, Rev. 0, Geographic and Operational Site Parameters List (GOSPL) for the 2004 Composite Analysis PNNL-14702, Rev. 0, Vadose Zone Hydrogeology Data Package for the 2004 Composite Analysis PNNL-1 4618, Rev. 0, A Geostatistical Analysis of Historical Field Data on Tritium, Technetium-99, Iodine-i 29, and Uranium PNNL-14599, Rev. 0, Atmospheric Data Package for the 2004 Composite Analysis

PNNL-14618, Rev. 0

Pacific Northwest

National Laboratory

A Geostatistical Analysis of Historical Field Data on Tritium, Technetium-99, Iodine-129, and Uranium

C. J. Murray Y.-J. Chien P. D. Thorne

April 2004

Prepared for the U.S. Department of Energy under Contract DE-AC06-76RL01 830

DISCLAIMER This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor Battelle Memorial Institute, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

PACIFIC NORTHWEST NATIONAL LABORATORY operatedby BATTELLE for the UNITED STATES DEPARTMENT OF ENERGY under Contract DE-ACO6-76RL0 1830

Printed in the United States of America Available to DOE and DOE contractors from the Office of'Scientific and Technical Information, P.O. Box 62, Oak Ridge, TN 37831-0062; ph: (865) 576-8401 fax: (865) 576-5728 email: reports~ladonis.osti.gov Available to the public from the National Technical Information Service, U.S. Department of Commerce. 5285 Port Royal Rd., Springfield, VA 22161 ph: (800) 553-6847 fax: (703) 605-6900 email: orders(qj>ntis.fedworld.gov online ordering: http://wwwKA.ntis.go%,/ordering.htm

~$This document was printed on recycled paper.

PNNL-14618, Rev. 0

A Gcostatistical Analysis of Historical Field Data on Tritium, Tcchnctium-99, Iodine-129, and Uranium

C. J. Murray Y.-J. Chien P. D. Thorne

April 2004

Prepared for the U.S. Department of Energy under Contract DE-AC06-76RLO0183 0

Pacific Northwest National Laboratory Richland, Washington 99352

Executive Summary Pacific Northwest National Laboratory performed a geostatistical study for the Groundwater Remnediation Project (formerly the Groundwater Protection Program) managed by Fluor Hanford, Inc., and the U.S. Department of Energy (DOE). The objective of the study was to generate history matching data needed to test the performance of the System Assessment Capability (SAC) model that forms the basis for the Hanford Site 2004 Composite Analysis for low-level radioactive waste disposal in the Central Plateau at the Hanford Site. The SAC model is a stochastic model that uses probabilistic descriptions of inventory and transport parameters from the Hanford Site to generate predictions of the expected movement of contaminant plumes at the site. The history matching data generated by the study are based on geostatistical analysis of historical measurement of radionuclide concentrations in groundwater samples at Hanford. The history matching study focused on concentration data for two points in time, fiscal year (FY) 1992 and FY 2001, and considered four radionuclides: tritium, technetium-99, iodine- 129, and uranium. Geostatistical methods were used to analyze and model the spatial distribution of each radionuclide and then use that model to generate a suite of stochastic simulations of the concentrations. The simulations covered the entire Hanford Site in a series of regional grids that had similar properties in aquifer geology and contaminant transport. Each simulation would reproduce the data at the known measuring points; between those points the simulated values would reproduce the global probability distribution and the spatial correlation of the radionuclide data identified in the geostatistical model. The simulated concentrations were used together with estimates of the subsurface geology and the probability distributions for the porosity of each geologic unit to generate Monte Carlo realizations of the mass or activity of each contaminant. The suite of Monte Carlo realizations were used to estimate several metrics for the radionuclides that could be tested against the SAC model. Those metrics included the total mass or activity, the location of the center of mass, the area above the drinking water standard (DWS) for each contaminant, and, where relevant, the length of the Columbia River shoreline above the DWS. These metrics were calculated for several individual plume areas at the Hanford Site for FY 1992 and FY 2001. Each metric was calculated over the suite of realizations so that the average value for the metric could be provided along with a measure of uncertainty for the metric. The history matching data generated by this study can be used to evaluate the ability of the SAC Rev. I model to produce simulated concentration histories over time that match the historical data. In addition, the study provides measures of the uncertainty in each of those metrics that can be used to determine if the predictions from the SAC model fall within the uncertainty bands expected due to spatial uncertainty in the historical contaminant concentration data. This report also discusses several areas of uncertainty in the data and the modeling process that were not addressed by the current study. Several possible improvements or extensions of the approach are recommended for future study. These include: *Generate results for additional time points beyond the two points in time considered in the present study. History matching data should be generated for earlier points in time, although the areas covered might need to be restricted due to the sparse distribution of data for earlier time periods.

111

" Examine the effect of vertical contaminant distribution assumptions on uncertainty bounds for history matching data. " Perform an uncertainty analysis to examine the effect on uncertainty bounds for the various metrics that might arise from uncertainty in geologic structure. This should be done by using the results of work being performed in FY 2004 for the sitewide Groundwater Modeling task to develop stochastic alternative conceptual models of the geologic structure. " Examine the sensitivity of history matching metrics to variation in parameters of the variogram models fit to the experimental variograms. * Produce a set of metrics based on the SAC model runs that accounts for the sparseness of the concentration data available for geostatistical modeling. The suggested approach includes sampling concentration fields from the SAC model runs at historical well locations and over screened intervals that were used to sample groundwater. Geostatistical analysis of the sampled model runs would then be used to generate a set of metrics using the same methods described in this report. The metrics calculated from historical groundwater data and sampled SAC model runs would then be compared to evaluate the ability of the SAC model to reproduce historical groundwater concentration data.

iv

Contents Executive Summary...............................................................................................

iii

1.0

Introduction..............................................................................................

1.1

2.0

Approach.................................................................................................

2.1

Data Compilation...................................................................................

2.1

2.2 Geostatistical Simulation Method for Concentration Distributions..............................

2.2

Post-Processing of Contaminant Concentration Simulations ...........................

2.7

2.1

2.2.1 2.3

3.0

Monte Carlo Simulation Method for Mass and Activity..........................................

2.8

2.3.1

Plume Thickness Scenarios .................................................................

2.3.2

Probability Distributions of the Porosity of Sedimentary Units .......................

2.10

2.3.3

Monte Carlo Calculations of Contaminant Mass.........................................

2.11

2.3.4

Calculation of Metrics......................................................................

2.11

History Matching Data for SAC/CA...................................................................... 3.1

2.8

Definition of Grid Areas for Tritium Analysis ....................................................

3.1 3.1

3.2 Variogramn Analysis and Geostatistical Simulations of Tritium Concentration Data ......... 3.2 3.3

Metrics for Tritium Concentration and Activity in Grid 1 ........................................

3.4 Metrics for Tritium Concentration and Activity in Grid 2 ......................................

3.12

3.5

3.15

Metrics for Tritium Concentration and Activity in Grid 3.......................................

3.6 Discussion of Additional Results.................................................................. 4.0

3.5

3.21

Parameter Uncertainties and Data Gaps..................................................................

4.1

Concentration Uncertainty...........................................................................

4.1

4.1

4.2 Vertical Distribution of Contaminants..............................................................

4.2

4.3 Geologic Structure Uncertainty.....................................................................

4.3

4.4 Uncertainty in Porosity Distributions ..............................................................

4.4

V

4.5 Uncertainty in Geostatistical Modeling ............................................................

4.4

5.0

Summary and Recommendations .........................................................................

5.1

6.0

References ...............................................................................................

6.1

Appendix A

-

Sub-Area Boundary Coordinates for FY 2001 Tritium.......................................

A.1I

Appendix B

-

Figures and Data Tables for FY 1992 Tritium ................................................

B. 1

Appendix C

-

Figures and Data Tables for FY 2001 Technetium-99 .......................................

C.1I

Appendix D

-

Figures and Data Tables for FY 1992 Technetium-99 .......................................

D. I

Appendix E - Figures and Data Tables for FY 2001 Iodine-129.............................................

E.1I

Appendix F

Figures and Data Tables for FY 1992 Iodine- 129..............................................

F.1

Appendix G - Figures and Data Tables for FY 2001 Uranium...............................................

G.1I

Appendix H - Figures and Data Tables for FY 1992 Uranium...............................................

H. 1

-

vi

Figures 1.1

Major Areas at the Hanford Site..........................................................................

2.1

Number of Wells in Each Fiscal Year for Each Contaminant for Which An Annual Average is Available ................................................................................................. 2.2

2.2

The Variogram is a Geostatistical Tool to Measures Average Squared Difference Between Pairs of Data Values Separated by a Given Lag Distance..............................................

2.3

2.3

Subcrop Formation Units at FY 2001 Water Table .....................................................

2.4

2.4

Diagram of Basic Elements of the Sequential Simulation Algorithm.................................

2.6

2.5

Plot of the Average Area Above the Tritium Drinking Water Standard as a Function of the Number of Simulations Generated for One of the FY 2001 Tritium Simulation Grids ............ 2.7

2.6

FY 2001 Tritium Distribution by Hydrogeological Zones .............................................

2.7

Median of Simulations of FY 2001 Tritium in Grid I and Contour of Number of Centers of Mass within the Sub-Areas with the Average Centers of Mass Denoted by Black Stars ......... 2.12

3.1

Subsets of FY 2001 Tritium Data and the Suberop Formnation Units at the FY 2001 Water Table.....................................................................................................

3.1

Subsets of FY 1992 Tritium Data and the Suberop Formnation Units at the FY 1992 Water Table.....................................................................................................

3.3

Variograms and Models of Normal Scores of the Subsets of FY 2001 Tritium Data in the Local Grids 1, 2, and 3...................................................................................

3.4

3.4

Median of Simulations of FY 2001 Tritium Concentrations for Grids 1, 2, and 3 ..................

3.5

3.5

Median of Simulations of FY 1992 Tritium for Grids 1, 2, and 3 .....................................

3.6

3.6

Median of Simulated FY 2001 Tritium Concentrations in Grid 1 .....................................

3.7

3.7

Probability of Exceeding 20,000 pCi/L Based on Simulations of FY 2001 Tritium in Grid I...3.8

3.8

Histograms of Total Activity in Simulations of FY 2001 Tritium Within Sub-Area I of Grid 1, Four Thickness Assumptions ....................................................................

3.2

3.3

3.9

Histograms of Mass of Simulations of FY 2001 Tritium Within Sub-Area 2 of Grid 1, Four Depth Assumptions ................................................................................

vii

1.2

2.9

3.9

3.10

3. 10 Curves Fit to Histograms of the Mass of FY 2001 Tritium at Four Depths within Sub-Areas 1 and 2of GridlI......................................................................................... 3.11 3.11

Median of Simulated FY 2001 Tritium Concentrations in Grid 2....................................

3.12

3.12 Probability of Exceeding 20,000 pCi/L Based on Simulations of FY 2001 Tritium in Grid 2..3.13 3.13 Histogram of the Average Length of Columbia River Shoreline Exceeding 20,000 pCi/L for FY 2001 Tritium in Grid 2...............................................................................

3.14

3.14 Histograms of Total Activity in Simulations of FY 2001 Tritium Within Grid 2, Four Thickness Assumptions.................................................................................

3.14

3.15

3.16

Median of Simulated FY 2001 Tritium Concentrations in Grid 3....................................

3.16 Probability of Exceeding 20,000 pCi/L Based on Simulations of FY 2001 Tritium in Grid 3..3.17 3.17

Histogram of the Average Length of Columbia River Shoreline Exceeding 20,000 pCi/L for FY 2001 Tritium in Grid 3...........................................................................

3.19

3.18 Histograms of Total Activity in Simulations of FY 2001 Tritium Within Sub-Area 1 of Grid 3, Four Thickness Assumptions...................................................................

3.19

3.19 Histograms of Total Activity in Simulations of FY 2001 Tritium Within Sub-Area 2 of Grid, Four Thickness Assumptions.....................................................................

3.20

viii

Ta bles 2.1

Definitions of Aquifer Hydrogeological Zones .........................................................

2.2

Probability Distributions Assumed for Each Unit in the Unconfined Aquifer.....................

2.11

2.3

Drinking Water Standards Used for Radionuclides ...................................................

2.13

3.1

Statistics of Locations of Centers of Mass of Individual Simulations of FY 2001 Tritium Calculated for a Depth of 5 m for Each Sub-Area of Grid I...........................................

3.7

Area Exceeding 20,000 pCiIL for FY 2001 Tritium for Each Simulation Within Two Sub-Areas of Grid 1.....................................................................................

3.8

Statistics of Total Activity of Simulations of FY 2001 Tritium Within Sub-Area I of Grid 1, Four Thickness Assumptions .............................................................................

3.9

3.2

3.3

3.4

3.5

3.6

3.7

3.8

3.9

2.8

Mass of Simulations of FY 2001 Tritium Within the Sub-Area 2 of Grid 1, Four Depth Assumptions ..............................................................................................

3.10

Statistics of the Area Exceeding 20,000 pCi/L and Locations of Centers of Mass for Simulations of FY 2001 Tritium Within Grid 2 .......................................................

3.13

Statistics of Total Activity of Simulations of FY 2001 Tritium Within Grid 2, Four Thickness Assumptions.................................................................................

3.15

Statistics of Locations of Center of Mass for Simulations of FY 2001 Tritium Calculated for a Depth of 5 m for Each Sub-Area of Grid 3.......................................................

3.18

Area Exceeding 20,000 pCi/L for FY 2001 Tritium for Each Simulation Within Two Sub-Areas of Grid 3 ....................................................................................

3.18

Statistics of Total Activity of Simulations of FY 2001 Tritium Within Sub-Area 1 of Grid 3, Four Thickness Assumptions............................................................................

3.20

3.10 Statistics of Total Activity of Simulations of FY 2001 Tritium Within Sub-Area 2 of Grid 3, Four Thickness Assumptions............................................................................ 3.21 3.11

Appendices and Content for Additional Contaminants ...............................................

ix

3.22

1.0

Introduction

A composite analysis is required by U.S. Department of Energy (DOE) to ensure public health and safety through the management of low-level radioactive waste disposal facilities associated with the Hanford Site (DOE Order 435.1). A major component of the Hanford Site 2004 Composite Analysis (Kincaid et al. 2004) will be the use of the System Assessment Capability (SAC). The SAC is a stochastic risk assessment program consisting of several modules that address contaminant inventory, contaminant release, atmospheric transport, vadose zone flow and transport, groundwater flow and transport, the Columbia River shore environment, Columbia River flow and transport, and risk and impact assessment. During application of SAC to the composite analysis, predictions of the concentrations of radioactive contaminants in groundwater will be generated as a function of time. These predictions are based on an assumed release of inventory, and then simulates the migration of contaminants through the various transport modules. The results of these predictions will be evaluated by matching (comparing) them against historical groundwater contaminant data. There is a large amount of historical data on the concentration of contaminants in groundwater at the Hanford Site. The most recent annual report, summarizing the groundwater data collected in 2002, can be found in Hartman et al. (2004) with background informnation on the purposes and methods for the groundwater monitoring effort given in Hartman (2000). The purpose of the study described in this report was to generate maps and statistics that quantify contamination in groundwater, based on historical groundwater concentration data for multiple points in time. The maps and statistics could then be compared to predictions from the SAC model, and used for verification of SAC results that will be incorporated in the 2004 Composite Analysis. The results generated from this study include several quantitative summaries of contaminant distributions (e.g., the location of the center of mass of contaminant plumes and the total mass of contaminants in the plume) and are collectively referred to as history matching data. A primary goal of this study was to use geostatistical and Monte Carlo methods that allow one to provide an estimate of uncertainty in the history matching data generated. This work was conducted as part of the Characterization of Systems Task of the Groundwater Remediation Project (formerly the Groundwater Protection Program) managed by Fluor Hanford, Inc. The scope of the study focused on four radioactive contaminants with a wide distribution at Hanford: tritium, technetium-99, iodine- 129, and uraniumn. All four are current contaminants of concern at Hanford that will be examined in detail by the 2004 Composite Analysis (Kincaid et al. 2004, Table A.4). Results were generated for two time periods, fiscal year (FY) 2001 and FY 1992. To support the geographic scope of the 2004 Composite Analysis, the scope of this study covered the entire Hanford Site including the 200 West and East Areas in the Central Plateau, and the 100 Areas and 300 Area in the Columbia River corridor. Figure 1.1 shows the major features at the Hanford Site. The purpose of this report is to document the source of the groundwater concentration data employed in the history matching data analysis, the geostatistical approach used for analyzing the spatial distribution of the contaminants, the Monte Carlo methods used to convert stochastic simulations of concentration to mass or activity, the approach used to calculate the metrics reported by the study, and the results generated for each of the four contaminants. 1.1

Hanor

Ha

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00(

anmr

RierCoteo

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Mjo Aes

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04

2.0

Approach

This study used a Monte Carlo approach to generate suites of realizations of mass or activity for four radioactive contaminants at the Hanford Site. These realizations were generated on a series of regular grids covering the Hanford Site. The foundation for the approach was geostatistical modeling and simulation of the spatial distribution of the concentrations of contaminants. Mass or activity estimates based on the geostatistical simulations were generated for several plume thickness assumptions using Monte Carlo sampling of porosity distributions for each hydrogeologic unit present in a grid cell. Aggregate metrics were computed for a series of sub-areas of the Hanford Site associated with major contaminant plumes. This section of the report provides detail on the data used in the study and the methods employed.

2.1

Data Compilation

Data for each contaminant were retrieved from the Hanford Environmental Information System (HEIS). All measurements of tritium, technetium-99, and iodine-129 data available at the Hanford Site were retrieved from the database (in pCi/L, along with all measurements of uranium concentration (jig/L). Data were included in this study in accordance with selection criteria generally employed for the Hanford Site Groundwater Monitoring Reports (e.g., Hartman et al. 2004). The data were reviewed for data quality, and only data meeting the qualifications generally accepted for inclusion in the annual monitoring reports ()were included. This involved exclusion of data with "Y" or *"R"review qualifiers, which indicate that the data quality review indicated that the data were invalid, or that the results were suspect with insufficient evidence to show if the results were valid or invalid, respectively. The hydrogeologic zone from which the samples were taken was also examined, and samples were retained that were from the upper portions of the unconfined aquifer, again in accord with criteria used to select groundwater concentration data for inclusion in the annual monitoring reports. (a) The selection criteria for the well zone included samples designated "TU" (Top Unconfined), "UU" (Upper Unconfined), and "U"' (Undifferentiated Unconfined), together with samples for which the zone was not recorded on the assumption that wells that test the lower portions of the unconfined aquifer and/or the confined aquifers have been identified by scientists working for the Groundwater Performance Assessment Project. (a) This selection provides a two-dimensional dataset for the concentrations in the upper portion of the unconfined aquifer. While it would be preferable to map the concentrations in three dimensions, there is insufficient data available with discrete measurements of concentration with depth in the aquifer to make that feasible. As discussed in the following sections, the amount of three dimensional data in the aquifer are insufficient to determnine the total thickness of the contaminant plumes, let alone to map the plumes in three dimensions. Data for each contaminant were summarized on a fiscal year basis, averaging all observations for each well for each fiscal year for which data were available. Because a number of wells at the Hanford Site are not sampled on an annual basis, an algorithm was used to select data from the most recent year in order to represent the concentration at a well for a given fiscal year. The algorithm selects the annual average for a given fiscal year, or if this is not available, the most recent of the annual averages from the

(a) Personal communication from J Rieger to the authors, 2002. 2.1

two preceding fiscal years. This algorithm is also used to select the annual fiscal year average data for inclusion in the annual groundwater monitoring reports. (a) Once the fiscal year annual average concentration data were calculated for each contaminant, the distribution of the number of data points with time was examined to select years for which history matching data would be generated. Figure 2.1 plots the number of wells for which an annual average is available for each fiscal year for the four contaminants. Two years were selected to generate history matching data, FY 1992 and FY 200 1, which are highlighted in Figure 2. 1. At the time this study was initiated, FY 2002 data were not yet available, and FY 2001 was the most recent year with available data. FY 1992 was selected because it represented the earliest date for which a high number of tritium observations (-700) were available. In addition, that year has among the highest number of observations ever recorded for both technetium-99 and uranium (Figure 2. 1).

800 S700 600 500

1992T

co 50 400 -MT_

* Tc-9

~ 30 S200 E z

100

_____________

**

_____1-129

aUran * **

0 1962

*

~

~ -_

1972

_

1982

_

_

1992

2002

Fiscal Year

Figure 2.1.

2.2

Number of Wells in Each Fiscal Year for Each Contaminant for Which An Annual Average is Available

Geostatistical Simulation Method for Concentration Distributions

The geostatistical analysis of the contaminant plume included variogram analysis and modeling to define a mathematical model of the spatial continuity of the contaminant concentration data. The most commonly used tool for describing the spatial continuity of geologic properties is the experimental variogram (Isaaks and Srivastava 1989; Davis 1986; Goovaerts 1997), which is a measure of the average dissimilarity between pairs of points separated by a given vector distance, as a function of that distance. The variogram is calculated as: 2(21

N(h)

;v

() 2Nh

I zL(u, _=1

(a) Personal communication fr-om J Rieger to the authors, 2002. 2.2

z (u, +h)](21

where y(h) is the variogram value for a lag distance of h, and N(h) is the number of pairs of concentration values (z) separated by a lag distance of h. Variables that result from the operation of geologic processes that vary spatially (e.g., contaminant transport by groundwater) often display spatial continuity that can be identified by variogram analysis. If a variable exhibits spatial continuity, then points that are close to one another will have smaller differences, and, therefore, lower variogramn values than pairs of points that are separated by greater distances. In variogram analysis, models are fit to the experimental variograms that quantif~y the spatial continuity of the variable. Variogram models are required for geostatistical estimation (i.e., kriging) or simulation algorithms because it is rare that experimental variogramn values will be available for all lag distances for which estimates or simulations may be desired (Isaaks and Srivastava 1989). Figure 2.2 explains some of the important features of a variogramn model. All but one of the variograms in this study were fit using a spherical model (lsaaks and Srivastava 1989), which is defined as follows:

y (h)

1.5h 0.

h

{(a).~T a

if h:!a

1 otherwise

J

(2.2)

where h is the lag distance and a is the range of the spherical variogram model. The other model used was the Gaussian variogram (Isaaks and Srivastava 1989), which has the following form:

y (h)

E

- a 2j

(2.3)

~1 4
(correlated)

Figure 2.2.

I -exp

*

U Experimental variogram data

*

-

Vaniogram model

(uncorrelated) Lag Distance

The Variogram is a Geostatistical Tool to Measures Average Squared Difference Between Pairs of Data Values Separated by a Given Lag Distance. At distances less than the range, the variogram is a function of distance related to the degree of spatial correlation. Points separated by distances greater than the range are uncorrelated. 2.3

The variogram analysis for each contaminant at the Hanford Site was performed for three separate areas. The three areas were 200 West Area (designated Grid I), 100 Areas (Grid 2), and 200 East Area and the plumes that traveled northwest and southeast from it (Grid 3). Figure 2.3 shows the three grid areas for tritium in 2001. These areas were chosen because of differences in their hydrogeological properties. For example, Figure 2.3 is a map of the geological units exposed at the water table. The map shows that the area of Grid 1, which includes 200 West Area, is predominantly Ringold Formation at the

105000- Green

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rvt(nt

5400\j00950

5600

555000-

+atn Figur 2.3

135000

(in)

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nt a

20

ae

al

water table, while Grid 3 is predominantly Hanford formation. The hydraulic conductivity of the Ringold Formation is much lower than that of the Hanford formation, so the plumes in 200 West Area tend to be smaller and move more slowly than those emanating from 200 East Area. This difference in the plumes was expected to be reflected in the spatial continuity of the plumes measured by variogramn analysis. A multi-Gaussian sequential simulation (Gomez-Hemandez and Journel 1993; Goovaerts 1997) approach was used to simulate the distribution of contaminants at the Hanford Site. Because of the large number of separate geostatistical studies and large numbers of simulations generated for each study, Gaussian simulation was used as the default modeling approach because of the simplicity of the modeling approach and computational speed of the simulation algorithm relative to indicator geostatistical methods. All simulations were performned on square grids with a grid resolution of 50 meters. The multi-Gaussian simulation approach requires that the data exhibit a Gaussian distribution. Because the contaminant data are not normally distributed, the variogram modeling described above and the subsequent simulations were performed on a normal-score transformation of the contaminant data (Goovaerts 1997, p. 268), which transforms the variable so that it fits a univariate normal distribution. The normal score transform is a more general transformation than the lognormal transform often used in hydrogeologic studies and it has the advantage that it avoids most problems associated with back-transformation from the logarithmic space to the original data space (see Goovaerts 1997, p. 17, for a discussion of those problems). Sequential Gaussian simulation is a stochastic simulation method that allows one to generate equally probable realizations of the spatial distribution of a variable that honor both the data and the variogramn model fit to the data. The simulations are generated by taking a random path through the grid cells that are to be simulated (Figure 2.4). At each grid cell in the simulation domain, the surrounding data and the variogramn model are used to estimate the conditional cumulative distribution function (CDF) of the variable at that cell (Figure 2.4) by estimating the conditional mean and variance of the distribution. The estimation of the conditional mean and variance are performed by kriging. Although simple kriging is theoretically the preferred form of kriging to estimate the conditional mean and variance, ordinary kriging can be used when sufficient data are available for local re-estimation of the mean (Deutsch and Journel 1998, p. 174). Ordinary kriging can be used to re-estimate the local mean when a spatial trend is present in the data (Journel and Rossi 1989), rather than using a single unchanging mean as occurs in simple kriging. In the simulations generated for this study, the mean and variance of the conditional distribution at each grid cell was estimated by ordinary kriging, with the conditional mean equal to n(u)

ZQ(U

n(u)

2(u)

Z(u, ) with Z

a=1

K

(2.4)

(U)1

at=1

where ZOK is the ordinary kriging mean at location u. Thus, the ordinary kriging mean at each location u is a weighted linear combination of the nearby data ( Z (u, with the ordinary kriging weights (u) ) constrained to sum to I and found by minimization of the error variance. The variance of the (a0 conditional distribution of the simulated cell was estimated by the ordinary kriging variance

2.5

cY'K

0

0

Sequential Simulation

~ 0 0

_

0 0 Datapoint

0

Grid node to simulate Variogram Model

Conditional CDF 1.0

.7

E E

u50 .

*

C0

025

Lagistnce10

20 3040 50 60 70

Contaminant (pCiIL)

o

0

0 0

Grid node to simulate

--

-

0

-

0

Figure 2.4.

Previously simulated node 0 Data point

Diagram of Basic Elements of the Sequential Simulation Algorithm n(U)

UK=C (O) Z A, (U) C (u, ~U) -P"'(U)

(2.5)

where C(O) is the covariance at zero separation distance, C (u, - u) is the covariance between the data point at location ca and the cell being simulated and p,),K (u) is a Lagrange parameter that accounts for the constraint on the weights in ordinary kriging (see Goovaerts 1997, p. 133 for further detail on ordinary kriging). A uniform random number between 0 and I is then used to draw a value from the conditional distribution, which has been estimated by the ordinary kriging mean and variance (Figure 2.4). The simulated value then becomes a data point for the simulation of the remaining grid cells, and the process is repeated, moving to each cell in the domain until all cells in the grid have been evaluated. The sequential algorithm ensures reproduction of the variogram and histogram of the data through a recursive application of Bayes theorem. Additional simulations can be generated by taking different random paths through the simulation grid. A more detailed discussion of the sequential Gaussian simulation algorithm can be found in Goovaerts (1997, p. 376).

2.6

During the geostatistical modeling of the contaminant distributions, the results for the Gaussian simulations of technetium-99 in 200 East Area for FY 2001 did not agree with those provided by previous geostatistical modeling of that plume. Previous study of the technetium-99 distribution in that area for FY 2001 had been performed using sequential indicator simulation rather than sequential Gaussian simulation (DOE 2003). To be consistent with the results, which were felt to be more representative of the concentrations in the plume, sequential indicator simulation (Goovaerts 1997) was used for geostatistical simulations of technetium-99 in 200 East Area for FY 2001. 2.2.1

Post-Processing of Contaminant Concentration Simulations

The set of simulated values of the contaminant concentration for each 50 meters by 50 meters grid cell can be used as a model of the conditional probability distribution of the concentration in that cell (Joumnel 1987, 1989). The conditional probability distributions can be summarized in several ways. For example, they can be used to estimate the mean or median concentration at each grid cell and the uncertainty in that estimate, e.g., by calculating the variance of the simulated values or the 5th and 9 5th percentiles of the simulated concentration values. The suite of simulations can also be used to estimate the probability that the concentration exceeds some cutoff value, e.g., the drinking water standard (DWS) for a contaminant, by calculating the frequency with which the simulated values at each location exceed that cutoff. Each of these statistics of the local conditional distributions can be mapped, and they provide valuable information about the spatial distribution of the contaminant plume. A large number of simulations, at least several hundred, were generated for each contaminant/grid! year combination. The number of realizations generated for each variable/year combination was determined by plotting the results for one of the mnetrics as a function of the number of simulations generated to determine if there was an obvious break in the curve that would indicate that the space of uncertainty was well-sampled. For example, Figure 2.5 shows a plot of the average of one of the metrics calculated 21

______

_

_

FY01 Tr: Grid no.1

20 C4

< 19 E 18 S17 S16 15 14

--

0

Figure 2.5.

_

_

_

100

_

_

_

_

_

200

__

300

_

_

_

400

_

Number of simulations

_

_

_

500

600

Plot of the Average Area Above the Tritium Drinking Water Standard as a Function of the Number of Simulations Generated for One of the FY 2001 Tritium Simulation Grids

2.7

for FY 2001 tritium (the area above the drinking water standard, see Section 2.2.3 for information on the procedure used to calculate that metric). The average area is relatively unstable early in the process with a large amount of variability, especially for less than 100 simulations, but appears to have stabilized after about 300 simulations have been generated.

2.3

Monte Carlo Simulation Method for Mass and Activity

The simulations of contaminant concentration generated using sequential Gaussian simulation were used as the basis to develop simulations of the mass and activity of contaminants in the study areas for FY 1992 and FY 2001. To convert concentration values to mass or activity estimates, several factors need to be determnined, including the thickness of the plume, vertical distribution of contaminant concentration within the plume, and porosity of the sediment.

2.3.1

Plume Thickness Scenarios

Information on the thickness of contaminant plumes at the Hanford Site is limited. One relatively simple way to address both the plume thickness and vertical distribution of contaminants is to examine the distribution of contaminant concentrations for samples taken from different hydrogeological zones. The hydrogeological zones used in this study were those identified by scientists working for the Groundwater Performance Assessment Project!'a) Table 2.1 gives the definitions of the hydrogeological zone in the unconfined aquifer that are plotted in Figure 2.6. Figure 2.6 is a plot of the median and average tritium concentration during FY 2001 for all samples at the Hanford Site taken within four hydrogeological zones in the unconfined aquifer. Thus, Figure 2.6 gives a rough idea of the distribution of tritium with depth in the unconfined aquifer for FY 2001. The median concentration falls off rapidly with depth in the aquifer, with median UU concentrations that are about one-third of those in the TU. However, the high average concentration for MU samples indicates that there are still some high concentration samples that occur at depths greater than 15.2 meters below the water table.

Table 2.1. [Zone TU (Top Unconfined) UU (Upper Unconfined) MU (Middle Unconfined)

Definitions of Aquifer Hydrogeological Zones

I

Definition

Screened across the water table with less than 9.1 mn of the open interval extending below the water table. Screened across the water table for which the open interval is between 9.1 and 15.2 mn below the water table. Screened below the water table for which the open interval extends less than 15.2 mn below the water table. Open interval begins at greater than 15.2 m below the water table and does not extend below the middle coarse of the Ringold Formation (unit 7) or to within 15.2 mn of the top of basalt.

Open interval begins at greater than 15.2 mn below the water table and below the middle coarse LU (Lower unit of the Ringold Formation (unit 7) or within 15.2 mn of the top of basalt and does not extend Unconined) Unconined)more than 3 mnbelow the top of basalt.

(a) Personal communication from J Rieger to the authors, 2002.

2.8

MedianConcentration (pCi/L) 0

500

1000

1500

2000

2500

AverageConcentration (pQilL) 3000

0

3500 1

1-__*

TU- 1162obs

10000

__

30000 _

2

__

40000 _

_

_

_

_

UU

UU - 66 obs

N

3

o

_

jTU

2-

N

20000 __

--

MU -54 obs

3

MU

S

4

4 LU - 39 obs

5

LU

-~5

Figure 2.6.

FY 2001 Tritium Distribution by Hydrogeollogical Zones

Other data compiled for this study provided insight into the thickness and concentration variations with depth of the contaminant plumes. Data from the tritium plume near the PUREX facility indicate the thickness of the tritium plume is at least 8 meters, but concentrations tend to be low for samples more than 10 meters below the water table: " Data from well 299-E25-28 indicate somne tritium at 18 meters, but the concentration is low at that depth and also at the water table. " Data from well 299-E25-29 show the plume is more than 8 meters thick. " Data from wellIs 699-24-1 S and 699-24-I T show concentration at 10 meters below the water table of 15 to 30% of concentration at water table and none at 30 meters below the water table (note that well 699-24-1lP, Q and R go to basalt). " Data from well 699-28-40 P show a few sporadic high results, but generally does not show any peak in the late 1980s corresponding to that in the earlier well 699-28-40 data. It appears that plume thickness at that location is less than 50 meters. * Data from well 699-26-34B show the plume thickness is greater than 8 meters. Indications from discrete depth sampling conducted in FY 1999 at Waste Management Area S-SX suggest that the maximum concentrations of contaminants occur within the upper 2.5 to 7 meters of the aquifer (Johnson and Chou 2000). Some contaminants were found up to 30 meters deep and even below the Ringold lower mud unit (an aquitard deep in the unconfined aquifer); however, concentrations at these greater depths were low. However, data from well 699-48-77C show that the tritium plume from the State-Approved Land Disposal Site (SALDS, north of 200 West) has gone to depths greater than 25 meters with peak concentrations at depth of about I million pCi/L compared to 2 million pCi/L near the water table. There is a large downward driving force from the discharge at the disposal site and the Ringold mud units are 2.9

missing in this location, which may contribute to the high concentrations with depth. Williams et al. (2002) discuss additional evidence from 200 West Area suggesting that significant concentrations of contaminants may be present at depth within the aquifer, with greater concentrations found at depth than occur at the water table in some locations. The following approach was adopted for this study, based on the available data and the approach used in the history matching study performed for SAC Rev. 0 (Bryce et al. 2002). The concentration within a contaminant plume was assumed to be constant with depth over a finite plume thickness. In mass calculations, the mass of a contaminant within a plume was calculated for four different plume thickness scenarios of 5, 10, 15, and 20 meters. Although all four cases will be presented, the major focus will be on the results generated for the 5 meters plume thickness, because the limited data that are available tend to suggest the majority of contaminant mass is within 5 meters of the top of the aquifer (e.g., Eddy et al. 1978; Johnson and Chou 2000), although Williams et al. (2002) make a case for a deeper distribution of contaminants in the aquifer. Work will be performed within the characterization of systems groundwater task during FY 2004 to examine the vertical contaminant distribution in more detail; the assumptions about the distribution used to generate the history matching data should be revisited when the results of the characterization of systems study are available.

2.3.2

Probability Distributions of the Porosity of Sedimentary Units

The major factors that control the mass of contaminants present within the contaminant plume are contaminant concentrations, which were simulated using the methods discussed in Section 2.1 (and then assumed to be constant with depth over a specified plume thickness), and sediment porosity. The sediment porosity varies between the different geological units and also varies within each unit. The identification of the unit thicknesses that are present in the aquifer were taken from the current sitewide groundwater model (Vermeul et al. 2003). A grid of the thickness of each unit at each grid location was generated from the model using EarthVision and then downloaded as a text table. The table identified the thickness of each hydrogeologic unit below the elevation of the water table that was present in FY 1992 and FY 2001. Using information from several sources, including data from Freeman et al. (2002) and Thorne and Newcomer (2002), a probability distribution was developed for the porosity of each hydrogeologic unit. Table 2.2 shows the probability distributions for each unit, which were assumed to be normal for each unit, with mean and standard deviation as specified. The data on which each probability distribution is based are provided in the last column of the table. No data were available for Unit 3, and the assumption was that the pre-Missoula gravels in that unit (now part of the Cold Creek unit) would have a porosity distribution similar to that of the coarse-grained units of the Ringold Formation (5, 7, and 9). No porosity or specific yield data were available for the fine-grained units of the Ringold Formation (4, 6, and 8), and the porosity of those units was assumed to be similar to that of the fine-grained portions of Unit 2. Although porosity occurs in the fine-grained units of the sequence, the majority of that porosity was assumed to not be effective porosity. That implies only small amounts of contaminants would be transported into and out of the mud units. Therefore, for this study, it was assumed that there would be no mass or activity of contaminants contained within the mud units, so that the thickness of the mud units in

2.10

Table 2.2.

Probability Distributions Assumed for Each Unit in the Unconfined Aquifer

[Unit

Mean I Std Dev

1 2 3 4 5 6 7 8 IL 9

0.27 0.42 0.13 0.42 0.13 0.42 0.13 0.42 0.13

0.087 0.081 0.033 0.081 0.033 0.081 0.033 0.081 10.033

Source Pump tests (3) Khaleel and Freeman (1995) Assume Ringold porosity Assume similar to Unit 2 Pump tests (10) Assume similar to Unit 2 Pump tests (10) Assume similar to Unit 2 IPump tests (10)

a grid cell would have zero concentration. This approach follows that developed for the earlier history matching studies that supported SAC Rev. 0 (Bryce et al. 2002). 2.3.3

Monte Carlo Calculations of Contaminant Mass

Monte Carlo simulations of contaminant mass or activity were produced as follows for each simulation of the concentration of a contaminant generated by the stochastic sequential algorithm described in Section 2. 1. For each concentration simulation, porosity values were drawn from the porosity distributions for each of the non-mud sedimentary units present in the sitewide Groundwater Model (see Section 2.2.2) and were assumed to be constant for that sedimentary unit for all cells in that simulation. For each cell in the grid, the thickness of each unit present below the water table would be retrieved from the table of unit thicknesses described in Section 2.2.2. The total volume of pores within the cell would be determined by adding the products of the unit porosity times the unit thickness for each non-mud unit below the water table and above the base of the assumed plume thickness, then multiplying that sum by the area of the cell (2500 in 2 ) . The total mass or activity in the cell would then be the product of the simulated concentration in the cell and the total porous volume. For each cell, four estimates of the mass or activity would be generated, one for each assumed plume thickness (i.e., 5, 10, 15, or 20 meters). This procedure was followed for each cell in each simulation, yielding a suite of simulated contaminant mass or activity values for each cell. 2.3.4

Calculation of Metrics

Several metrics were identified for use in the history matching effort, each of which would allow a quantitative assessment of the agreement between the SAC model and historical groundwater contamination data. The metrics included: 1. 2. 3. 4.

Total mass/activity Location of center of mass Area above DWS Length of shoreline above DWS

2.11

The metrics were calculated for specific plume areas within the individual simulation grids. For example, Figure 2.7 shows the location of two plume-areas for which separate calculations were made within Grid 1, which covers 200 West Area. An estimate of the spatial moments of a concentration field is found by numerical approximations to integral equations of the form (Rajaramn and Gelhar 1991):

f~~ncx~v~v&§zxcic~z(2.6)

=

where

Mbk n

=

C(x,y,z)

=

=

the Uk~hmoment the porosity the concentration for the cell with coordinates x, y, and z

The moments calculated for the current study were the zero order moment, which is the total mass and first order moments, which corresponds to the center of mass. The total mass or activity was calculated as the sum of the mass in each cell in the grid area for a given simulation, with the mass calculated according to the scheme discussed in Section 2.2.3. By calculating the total mass for each simulation of contaminant concentration, a range of total mass values were calculated that provided informnation on the uncertainty in the total mass. Standard univariate statistics were then reported on that distribution, 1400

200 East Area

138000

Tr (pCi/L) in~

fvcer nf

0000as 100000

CF

-

100000

-~

:50000

1000

1000

560000

562000

564000

566000

568000

570000

572000

574000

Easting (in)

Figure 2.7.

Median of Simulations of FY 2001 Tritium in Grid 1 (200 West Area) and Contour of Number of Centers of Mass within the Sub-Areas with the Average Centers of Mass Denoted by Black Stars 2.12

including the mean and median of the total mass and several uncertainty measures, including the standard deviation and 2.5 1hand 95 thpercentiles of the distribution. The center of mass calculations were based on the cell mass estimates calculated assuming that the plume thickness is 5 meters. Given the two dimensional nature of the grid of mass values calculated in Section 2.2.3, the location of the center of mass of each simulation was calculated using the following approximation to equation 1:

xcmass

=

xM, /,

M, (2.7)

ycmass = ~y'M, /ZM, where xcmass and ycmass I

the = the xi= the y,=the M,= the =

x and y coordinates of the center of mass, respectively cell number, x coordinate of cell y coordinate of cell mass of cell i

Similar to the approach used for the total mass, the center of mass was calculated for each simulation in the suite of geostatistical simulations that were generated, providing a measure of the uncertainty in the location of the center of mass. This uncertainty was captured in two forms, graphically and in tabular form. Graphically, the mean center of mass was represented by a star, and the uncertainty is captured by contouring the number of times the center of mass occurred in each cell of a coarser grid covering the area of interest. The coarse grid for Grid 1 (200 West Area) and Grid 2 (100 Areas) was 200 meters by 200 meters, and for Grid 3 (200 East Area) the coarse grid was 400 meters by 400 meters. Figure 2.7 shows the average center of mass and the contours of the center of mass for two sub-areas of 200 West Area. In addition to the graphical display, the tabular information included the average x and y coordinates of the center of mass and confidence intervals for the location of those coordinates. The remaining two metrics addressed the probability that the concentration within local areas exceeded the DWS. The DWS values used for this study are listed in Table 2.3, which is based on inform-ation listed in Hartman et al. (2004). One metric was the area above the DWS for each simulation, calculated by summing the area of the cells within each realization that exceeded the DWS, with each grid cell having an area of 2,500 in2 . This calculation was performed separately for each sub-area of a grid, Table 2.3.

Drinking Water Standards Used for Radionuclides

IDrinking Water Standard

Constituent TritiumnI

20,000 pCi/L

Technetium-99 Iodine- 129 Uranium

900 pCi/L 1pCi/L 30 pig/L

2.13

where sub-areas were defined. Statistical summaries of the mean and variability of the area above the DWS were reported for the suite of stochastic simulations. Another metric reported for Grid 2 (100 Areas) and Grid 3 (200 East Area plume) was the length of the Columbia River shoreline that exceeded the DWS. For each simulation of a grid that was bounded by the Columbia River, the number of grid cells intersecting the river that had concentrations exceeding the DWS were counted and multiplied by the average length of a cell intersected by the river. The average cell length is assumed to be the average of the edge (50 meters) and diagonal (70.7 meters) lengths of a cell, or 60.4 meters. As with the other metrics, the statistics for the distribution of shoreline lengths above the DWS were reported for the suite of simulations that were generated, providing an estimate of the most likely value as well as a measure of the uncertainty in the length. The procedures used to compare the metrics generated in this study from the historical data and the predictions from the SAC model, as well as the results of the comparison, will be reported by the SAC project in the 2004 Composite Analysis.

2.14

3.0

History Matching Data for SAC/CA

A large number of maps, figures, and tables were prepared for this history matching data package. This chapter presents the results for tritium concentrations as an example of the results provided, focusing in particular on the results obtained for FY 2001. Section 3.6 identifies the appendices containing the results for other years and contaminants.

3.1

Definition of Grid Areas for Tritium Analysis

The Hanford Site was divided into three grids for the geostatistical analysis, with the primary basis for the grids being the differences in the type of sediment present at the top of the water table (Figure 3. 1) Grid I occupied the area in the western portion of the Hanford Site where Ringold Formation sediment occurs at the FY 2001 water table, and the grid includes 200 West Area. Because the Ringold Formation

115000-

105000-Gen

:Cas-ri igl Purple meh~ O+er (i+ 2,+69 Baat(99 Gre

rvl(nt5

+

5500

5500

700

Figure 3.1.or ~ ~SustFooY201T ~lu rimata aunth Suo Wat rebleshGae aiso odCekUi ui 105 00 GrenCors-g ai Rng ldg 3rv l ni.1

5500

omto

950

nisa h

Y20

has relatively low hydraulic conductivity, plumes that occur within Grid 1 are spreading relatively slowly and tend to remain small. Grid 2 contains the contaminated areas along the Columbia River associated with the former nuclear reactors in the 100 Areas. Grid 2 has both Ringold and Hanford formations present at the water table. The plumes in this grid also tend to be small, in large part because they are constrained by their proximity to the Columbia River. In contrast to the first two grids, Grid 3 is dominated by high hydraulic conductivity sediment of the Hanford formation, which allows relatively rapid migration of contaminants and the development of larger plumes. For example the tritium plume in Grid 3 has migrated from its source in 200 East Area to the Columbia River. The differences in plume size in the three grid areas lead to differences in the ranges of the variograms, so the areas were treated separately for the geostatistical analysis. Figure 3.1 shows that there was overlap between the three grids. However, the boundary between Grids I and 3 was irregular, so that the areas on the eastern portion of Grid I where Hanford formation sediment was present were excluded from Grid 1, and the area at the western edge of Grid 3 where Ringold Formation sediment was present was excluded from Grid 3. Similar decisions were made for analysis of FY 1992 tritium concentrations. Figure 3.2 shows the subcrop of different geologic units for the FY 1992 water table, which was at a higher elevation than the FY 2001 water table used to construct the subcrop map in Figure 3. 1. The grid areas that were used for geostatistical analysis of the 1992 concentration data are shown in Figure 3.2. The three grid areas that were used for analysis in FY 1992 are similar to those used in FY 200 1, but they are not identical, principally because of differences between the elevation of the water table in the two different years.

3.2

Variogram Analysis and Geostatistical Simulations of Tritium Concentration Data

The results of the variogram analysis of tritium concentrations for each of the three grid areas in FY 2001 are shown in Figure 3.3. As expected from the previous discussion, the variogram models fit to the experimental variograms are very different for the three areas. The total sill of the models fit to all three variograms are constrained to equal 1.0, as required for the sequential Gaussian simulation algorithm (Deutsch and Journel 1998). The variogram fit to the tritium concentration in Grid 2 has the shortest range, less than 1,000 meters. Grid 1, which contains the 200 West Area plumes, has a longer range of 2,000 meters but also has a short range structure of 200 meters that accounts for 40% of the total variance, indicating significant patchiness or variability of the plume at short distances. The variogram model fit to the data from Grid 3 is more continuous at short distances and has a longer total range of 6,000 meters. Although not explicitly modeled, a hole effect can be seen in Figures 3.3a and 3.3c, which results in lower variogramn values for intermediate distances (e.g., at distances of about 2,500 meters in Figure 3.3a). This occurs in part because most variogram pairs for those distances tend to match low values on either side of the large central plumes emanating from facilities in 200 West and 200 East Areas. The hole effect and other differences between the long- and short-range variogramn structure may also be caused by different variogramn structures close to the source versus farther away from the source. This may have occurred because many local recharge areas associated with discrete waste facilities in the source area probably create complex local groundwater flow directions that affect the short-range variogram structure, whereas farther away from the source, the contaminant distribution and variogram structure associated with it was affected only by the regional groundwater flow.

3.2

155000-

I

145000-

135000 0)0 Cx

11500000

105000-

Gren:Casrin

ino, grvl(ntI

550015500

Figure 3.2.SBe

f FY192 nor rmata

550050000950

aundith Suco Fomto)nt

pariso, Figue 3.5 howspte maph Ofr mediasimuate

Aigre inGrd2.

Thedreset

a hY19

trtu6cnetato9o)F

92 Nt

h

F19Tritium in ocetatioans from FY19o FYato 2001ispiaril cause by99

raioctv 20triuonetrtim,. deca whihr has ahf

lifef1.3mearsim(Hatme

3.3

al.

2004).hreris

0.4 0.2

()4

~

1

1.6

h

0.4

X

p(0

Xp(0)+05

Xx

(b

1.4

0.2 y(h) 0

500

0.41h22 = + 0.58 Sph(9000)

1000 1500 Distance (mn)

2000250303004

0

1.4-

>S>X

X

X

0.460.2 0 0

~~~~~y(h)= 0.0+0.5Sh2200 + 0.58 Sph(6000) 1000 20010000 005000 Distance (mn)

1.3.4

6000

CD

Tr (pCi/L)

135000-500000 100000

Z

1250000 1

+

20000 -5000

1000

555000

565000

5751000

5000

595000

Easting (in)

Figure 3.4.

3.3

Median of Simulations of FY 2001 Tritium Concentrations for Grids 1, 2, and 3

Metrics for Tritium Concentration and Activity in Grid 1

Three hundred simulations of the FY 2001 tritium concentration were used as the basis for calculation of metrics for Grid 1. Grid I contains two distinct tritium plumes associated with 200 West Area (Figure 3.6), one to the southeast located near the REDOX plant and associated facilities and one to the northwest in the area of Waste Management Areas T-TX-TY. The areas containing those plumes are labeled sub-areas I and 2, respectively (Figure 3.6), and metrics were calculated separately for each subarea. The XY coordinates of the digitized outlines of sub-areas 1 and 2 are contained as tables in Appendix A. All XY coordinates are Washington State Plane Coordinates (South, UTM Zone 11), in meters. Figure 3.6 contains a map of the median simulated value for each grid cell, while Table 3.1 presents detailed statistics about the locations of the centers of mass that are contoured in Figure 3.6 for the 300 simulations of tritium for FY 2001. The statistics in Table 3.1 assume that the thickness of the tritium

3.5

Tr (pCi/L)

135000-500000

100000

-~

20000 15000 115000-1000 -

55000

565000

100

575000

Easting

Figure 3.5.

585000

595000

(in)

Median of Simulations of FY 1992 Tritium for Grids 1, 2, and 3

plume is 5 meters. Figure 3.7 shows a map of the probability that the tritium concentration exceeds the DWS within the grid area, based on the proportion of simulated values that exceeded the DWS for each grid cell. Table 3.2 shows statistics for the area exceeding the DWS of 20,000 pCi/L for FY 2001 tritium for each simulation within the two sub-areas of Grid 1 (200 West Area). Figures 3.8 and 3.9 present histograms that show the total activity of tritium in FY 2001 for each simulation in sub-areas I and 2, respectively. There are four histograms for each sub-area, showing the results for each of four different depth assumptions, with thickness varying from 5 to 20 meters. Tables 3.3 and 3.4 show the corresponding statistics for the total activity for the four thickness assumptions for the two sub-areas of Grid 1. For example, Table 3.3 indicates that a 95 percent probability interval for the total activity of tritium in sub-area 1 of Grid I for FY 2001 is 1,104.6 Ci to 4,720.7 Ci, assuming that the tritium plume is 5 meters thick. Predicted total activity from the SAC model, either a single estimate or a range of values from a series of realizations, will be compared with the probability interval based on geostatistical modeling of the historical concentration data to determine if the simulated

3.6

200 East

rea

Tr (pCi/L)

0000

200000

US Ecol

15000 1000

560000

562000

564000

566000

568bO0

5701000

572000

574000

Easting (in)

Figure 3.6.

Median of Simulated FY 2001 Tritium Concentrations in Grid 1 (200 West Area). Contours of the number of times that the center of mass within the sub-areas occurred within each cell of a coarser grid are shown. The average centers of mass are shown by black stars in each sub-area.

Table 3.1.

Statistics of Locations of Centers of Mass of Individual Simulations of FY 2001 Tritium Calculated for a Depth of 5 m for Each Sub-Area of Grid 1 (200 West Area)

Coordinate (in) Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97.StPercentile 2.5tb Percentile Confidence Level of Mean (95.0%)

[

Sub-Area I

Easting

Northing

569569.5 17.0 569575.0 294.0 0.31 -0.37 1776.3 568533.4 570309.6 300 570079.0 568917.6 33.4

134151.3 19.7 134137.5 340.4 0.12 0.10 1967.1 133216.6 135183.7 300 134815.7 133430.9 38.7

3.7

J

Sub-Area 2

Easting 567542.4 29.3 567424.4 507.8 0.58 0.97 2590.7 566662.4 569253.1 300 568741.2 566812.3 57.7

[Northing 137594.2 18.6 137555.8 322.4 -0.28 0.12 1724.7 136752.1 138476.8 300 138207.9 136980.6 36.6

140000-

+

+

200 East Area ++

++

2010West Area+*

138000-

136000

+

++

I

=+

4

0

++

134000-J Ponhd+

-

z

0

B C Cribs

00

U S E col gy

0

1300000,5

+

126000-

04

660000

562000

564000

566000

568000

570000

572000

+

574000

Easting (in)

Figure 3.7.

Probability of Exceeding 20,000 pCiIL Based on Simulations of FY 2001 Tritium in Grid 1 (200 West Area)

Table 3.2.

Area Exceeding 20,000 pCi/L for FY 2001 Tritium for Each Simulation Within Two Sub-Areas of Grid 1 (200 West Area) Area (kin 2) Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5 h Percentile 2 .5 'h Percentile Confidence Level of Mean (95.0%)

1

Sub-Area 1 10.62 0.11 10.62 1.94 -0.04 0.25 10.39 6.20 16.59 300 14.42 7.07 0.22

3.8

Sub-Area 2 2.13 0.03 2.01 0.60 1.12 1.01 3.14 1.06 4.21 300 3.58 1.26 0.07

1

Grid 1 15.91 0.15 15.87 2.67 0.39 0.41 16.50 9.75 26.25 300 21.60 11.05 0.30

j

Nute o Data 3M me- 411 9096"q0 a"19 944199 c1191ot var 036 91491mum10929969 i705 Ver,:eM; 4720 72

0103

0 090.'

Nu,, be of Data 300 919911ea 497 09 SIO Oev 1843 60 -M19 aa 037 Maxine-411 11749 11 97 5 Doe9eooe 9092 71 ur991 9149119 &)42 32

0090

291949019lte 310741 49 19 2041

O0w

~

0

~

~

nea1ai41.7$744

205

007r9

2 5011099119 11C4960 1o11411496 A

~

910991* 2117012 miiu i Wfl0t9 132

C00

00 40

0.000

000,

0 120

300 7224 10 799911%10 69 r 0091of01091 C37 991 7'91 3b2982 e701991 109960DR0 0911 880 92 79 j 06619,1979 60 109a0 ,9111 5231 30 20519WC1111 3341 70

N,91091 &1Da(4

541149'

mean9

~

~

0 9.V

0~

~

014t mean1

30X 9339 30

d., 30004

Vf0e,

0091 of91 0 00 na-,jm149 2294599 991099019c-n~ 1713222 pper1qu41119 11436 99 190499129 t-99 q-d1111 673 39 209910911019 304309

35

04*,

"yj

?W

A,

120002200

Figure 3.8.

Histograms of Total Activity in Simulations of FY 2001 Tritium Within Sub-Area 1 of Grid 1 (200 West Area), Four Thickness Assumptions

Table 3.3.

Statistics of Total Activity of Simulations of FY 2001 Tritium Within Sub-Area 1 of Grid 1 (200 West Area), Four Thickness Assumptions Mass (Ci) in Depth

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97.5'h Percentile 2 .5th Percentile Confidence Level of Mean (95.0%)

5Sm 2,590.69 54.47 2,524.61 943.46 0.18 0.57 5,183.72 744.96 5,928.69 300 4,720.72 1,104.60 107.19

3.9

lOin 4,975.09 106.62 4,787.44 1,846.68 0.18 0.57 10,360.29 1,388.82 11,749.11 300 9,092.70 2,117.02 1 209.82

15m 7,224.10 156.08 6,879.59 2,703.47 0.24 0.59 15,394.15 1,968.67 17,362.82 300 12,996.05 3,041.70 307.16

20 m 9,309.30 202.41 8,812.19 3,505.88 0.33 0.61 20,132.69 2,513.18 22,645.86 300 17,132.18 3,943.58 398.33

rneoo 25' gf ow

221274

5 wcer
73 :a

2'5

754

7e

63iwo 5316.5

557177~~~ 7730'

~~

2(7,

~

~

7 5..771

53

2..wi

32

55 2734542255'

957> t.42

1,69 227

72531577 0

M67

12

371

22

~ ~

~

7122575s~724

~

_________________________ l 905

1'727, 04207,20 279075 15256 551

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_____________I___I____________

27427772

06a9

"7e

5P

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0 In-7

&ow 054

pp."2

2 t,7P 127

7770

T37

53 5e25722 2o4w7 435297755 1567 2577 55

92427255735

7 2

72

o22

77

Figure 3.9.

Histograms of Mass of Simulations of FY 2001 Tritium Within Sub-Area 2 of Grid 1 (200 West Area), Four Depth Assumptions

Table 3.4.

Mass of Simulations of FY 2001 Tritium Within the Sub-Area 2 of Grid 1 (200 West Area), Four Depth Assumptions Mass (Ci) in Depth

5Sm

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97.5 Percentile i 25. -7 Percentile Confidence L evel of Mean (95.0%)_L

261.73 8.21 229.11 142.28 5.81 2.05 883.91 69.47 953.38 300 637.15 98.52 16.17

10, m

3.10

521.61 16.38 456.53 283.72 5.78 2.05 1,759.92 138.92 1,898.84 300 1,274.15 1 193.80 1 32.24

15m 771.32 23.69 678.19 410.33 5.15 1.94 2,528.46 208.32 2,736.78 300 1,910.79 1 290.01 146.62

J

20 m 1,004.86 29.86 887.63 517.16 4.58 1.83 3,119.49 277.66 3,397.15 300 2,544.70 377.38

158.76

_

values from the SAC model fall within the 95 percent probability interval from the geostatistical study. Comparison of Tables 3.3 and 3.4 indicates that there is approximately an order of magnitude more tritium in sub-area 1 than there is in sub-area 2. Figure 3.10 shows smooth curves fit to the histograms for the four thickness assumptions for each sub-area of Grid 1. The figure shows that in addition to the increase in mean total activity for greater thickness, there is also a large increase in the variability in the simulated total activity for increasing thickness assumptions of the plume. 200

I

5m

150-

0 100 1015m

50 20m

0 0

20000 Total Mass (Curie)

3000C

10000

250

I

5m

200150 0

100 15m

50

20m

0

0

Figure 3.10.

3000 2000 Total Mass (Curie)

1000

4000

Curves Fit to Histograms of the Mass of FY 2001 Tritium at Four Depths within SubAreas 1 (upper) and 2 (lower) of Grid 1 (200 West Area)

3.11

3.4

Metrics for Tritium Concentration and Activity in Grid 2

The tritium concentration and activity were also simulated for Grid 2, and metrics were calculated for the entire area together. Sub-areas within Grid 2 were not identified during the study; however, if those areas are identified in the future it would be possible to calculate metrics for them (e.g., the area around one of the reactors). Figure 3.11 shows the median simulated tritium value within the simulation grid based on 400 simulations of the tritium concentration. The central portion of the grid was blanked after simulation because of the sparse data coverage in that area. Figure 3.12 shows the probability that tritium concentration in FY 2001 exceeded the DWS. Table 3.5 contains the statistics for the area exceeding the DWS and the locations of the center of mass based on the suite of simulations generated in Grid 2. Because the simulation grid is bounded on one side by the Columbia River, an additional metric was generated for Grid 2 that was not relevant for Grid 1. That metric is the length of the shoreline for which the tritium concentration exceeded the DWS for each simulation; a histogram and statistics of the distribution of results is given in Figure 3.13. Figure 3.14 and Table 3.6 provide the histograms and statistical summaries of the total tritium activity in the simulation grid for plume thicknesses of 5, 10, 15, and 20 meters. Tr (pCIL) 15400500000 100000

100

-

Are0a

rea

500000

N200000

14000

+

+

10

7144000-

Fiue31.Meino

iAte

d F\ 201Titu0ocetainsi0ri0

10ra) ihnclsofa shwnbyablckstr

ofthnumber -Contours oftiethttecneofmsocurd

-10BC+

cAed grdaesonwt+h u4600

+3.1

rg of mass center

154000-

00H Are a

152000E

1000-

1000D

Q

Are a

++

Aea

+

+ +

++

100 F Area

+++

0.7

++

10

0148000-

Ar

+*

+

.

+

14600

144000- +0.4 564000

569000

579000

674000

Easting (in) Figure 3.12.

Probability of Exceeding 20,000 pCiIL Based on Simulations of FY 2001 Tritium in Grid 2 (100 Areas)

Table 3.5.

Statistics of the Area Exceeding 20,000 pCi/L and Locations of Centers of Mass for Simulations of FY 2001 Tritium Within Grid 2 (100 Areas)

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97.5' Percentile 2 .5 h Percentile Confidence Level (95.0%)

Area (krr2) 6.43 0.06 6.40 1.19 -0.12 0.16 6.75 3.07 9.82 400 8.92 4.14 0.2144.1

3.13

I

Center of Mass (unit: m)

Easting 572143.8 73.3 572245.4 1466.4 0.74 -0.25 9448.0 567631.9 577079.9 400 575177.7 568673.3

J

North ing 148421.2 45.9 148399.7 917.1 0.71 0.30 5894.6 145907.6 151802.2 400 150316.4 146620.1 90.2

Number of Data 400

mean 2102.63

0.100

std. dev. coef. of var maximum percentile upper quartile median quartile 2.5 percentile minimum

0080971lower 0060 :3

-

587,69 0.28 4405.94 3319,54 2474.57 2052.08 1629.59 1146.75 905.33

0.040-

0 020

2L

0.000 900.

2900,

9

3900,

Average Length

Figure 3.13.

(in)

Histogram of the Average Length of Columbia River Shoreline Exceeding 20,000 pCi/L for FY 2001 Tritium in Grid 2 (100 Areas) omtw 01 Cota 4M5 an 111100 415 -o

ooso

2,& 46Dsl

517

(0.1,0

5 120~

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osn ' 01 Data 400 moon57 2 d dam 280415

-1

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x 154 5411

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Figure011 Hitgrm (10

3.14. res)

ofsm12 Total Fou

Aciiyi1imltoso0Y401Tiim Thicknss 7

o1

4otV 1m 17s

D (C ,o 432

2400 2

41

24 10n

ihnGi

Assumptions041110222

45413454122 1

0013.140

4000

Table 3.6.

Statistics of Total Activity of Simulations of FY 2001 Tritium Within Grid 2 (100 Areas), Four Thickness Assumptions Mass (Ci) in Depth

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5 th Percentile

25-7P-ercentile Confidence Level of Mean (95.0%)

3.5

5m

loin

553.63 8.97 536.41 179.33 0.88 0.81 1,013.83 211.24 1,225.07 400 984.96

879.62 14.23 837.57 284.51 0.87 0.81 1,637.72 347.53 1,985.24 400 1,562.88 444.00

276.74 17.63

27.97

[

in

20m

1,071.39 17.55 1,018.86 350.94 1.33 0.92 2,104.27 410.88 2,515.16 400 1,935.89 1 543.39

1

34.50

1,219.11 20.31 1,153.58 406.11 1.83 1.03 2,503.70 451.17 2,954.86 400 2,218.85 594.34

1

39.92

Metrics for Tritium Concentration and Activity in Grid 3

The tritium plumes emanating from 200 East Area and other sources occuff ing within the main plume were simulated as a single unit in Grid 3. Metrics were calculated for two sub-areas based on 400 simulations of the tritium concentration. Sub-area I (Figure 3.15) encompassed the plume that moved southeast from 200 East Area, while sub-area 2 included the northemn portion of 200 East Area and portions of the tritium plume that moved to the north. The digitized boundaries for sub-areas I and 2 are found in a table within Appendix A. Figure 3.15 also shows the average center of mass for each of the sub-areas and contours around the center of mass that indicate the variability in the location of the center

of mass for the suite of simulations. Table 3.7 provides detailed statistics for the distribution of the center of mass locations for the two sub-areas. Figure 3.16 illustrates the probability that the tritium concentration exceeded the DWS within Grid 3, while Table 3.8 provides detailed statistics for the distribution of the area exceeding the DWS for each simulation in the two sub-areas. Sub-area I is bounded on the east by the Columbia River, and the southeastern tritium plume had an impact on a significant length of the shoreline. Figure 3.17 contains a histogram of the distribution of the length of shoreline above the DWS for the suite of simulations, indicating that about 10 km of river shoreline were above the DWS in FY 2001 for sub-area 1. Figures 3.18 and 3.19 present histograms that show the total activity of tritium in FY 2001 for each simulation in sub-areas I and 2, respectively. There are four histogramns for each subarea, showing the results for each of four different depth assumptions, with thickness varying from 5 to 20 meters. Tables 3.9 and 3.10 show the corresponding statistics for the total activity for the four thickness assumptions for the two sub-areas of Grid 3. Figure 3.15 shows the presence of low median concentrations mapped in the area between 200 East

Area and the Central Landfill and stretching to the northeast and southeast from the Central Landfill. The 20,000-pCi/L contour is not as continuous or extensive in those areas as it is in the hand-contoured maps of tritium concentration presented in the Hanford Site groundwater monitoring report for the FY 2001 data (see Figure S-3, Hartman et al. 2002). The low concentrations could lead to under estimating the 3.15

146000-!

ContoTr ofpnumL)

14500000

200

20000

&

Tr

13600-

+

5~0000

0)

0

EDO

~ Easn

Fiur 315.

ein0fSmuae0F-01

1000L

rtu

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(in)

Cocnrions, lin rid3 20

3.160

asAe

145000-

+

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+

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+

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\ +

079

+5 +

+

N

+0+

+

+

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1203017

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40 ~ ~ 3A20ratAraPlms

+

Table 3.7.

Statistics of Locations of Center of Mass for Simulations of FY 2001 Tritium Calculated for a Depth of 5 m for Each Sub-Area of Grid 3 (200 East Area Plumes)

Coordinate

(in)

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97 . 5 h Percentile 2.5'h Percentile Confidence Level of Mean (95.0%)

Table 3.8.

Sub-Area I Lasting Northing 587120.4 131577.5 59.0 62.0 587055.7 131770.2 1180.4 1240.6 -0.01 4.85 0.34 -1.53 7598.6 10098.6 584089.1 123933.2 591687.7 134031.8 400 400 589608.7 133434.5 585064.8 128621.8 116.0 121.9

Sub-Area 2 Lasting Northing 571954.7 142941.6 39.8 37.5 571923.2 142870.2 795.4 749.3 2.08 0.88 -0.25 0.26 5817.5 4999.4 568765.0 140385.3 574582.5 145384.7 400 400 573526.7 144634.3 570222.7 141542.2 78.2 73.7

Area Exceeding 20,000 pCi/L for FY 2001 Tritium for Each Simulation Within Two Sub-Areas of Grid 3 (200 East Area Plumes) Area (kin 2 ) Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5th Percentile 2

ITThP-ercentile

Confidence Level of Mean (95.0%0)

[Sub-Area I 89.12 0.53 88.22 10.60 1.16 0.57 76.36 60.74 137.09 400 112.55 70.66 1.04

3.18

Sub-Area 2 6.48 0.11 6.15 2.27 0.71 0.77 13.81 1.97 15.77 400 11.79 2.93 0.22

Grid 3

1

105.48 0.63 105.02 12.60 0.09 0.32 74.84 74.34 149.18 400 132.39 83.11 1.24

Number of Data 400 10139,70 std- dev. 3492Z59 coef of var 0.34 maximum 21124.3? percentile 17472,93 i upper quartile 12463.39 median 9807,75 lower quartile 7574,60 percentile 4013.63 S minimum 1629.59

010mean

0

8097.5

0.0602.5

0-040

5000.

0

10000,

20000

15000,

Average Length (in)

Figure 3.17. Histogram of the Average Length of Columbia River Shoreline Exceeding 20,000 pCi/L for FY 2001 Tritium in Grid 3 t) I 0

Nume 00'

250 400 fl1541

040 3,,

0120

Numb1er0 of Dat

2605004 11827162

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50

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01" dev 2 1 2o904

Histograms of Total Activity in Simulations of FY 2001 Tritium Within Sub-Area 1 of Grid 3 (200 East Area Plumes), Four Thickness Assumptions

3.19

Table 3.9.

Statistics of Total Activity of Simulations of FY 2001 Tritium Within Sub-Area 1 of Grid 3 (200 East Area Plumes), Four Thickness Assumptions Mass (Ci) in Depth

5Sm

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97.5"' Percentile 2 .5 th Percentile Confidence Level of Mean (95.0%)

28,505.03 592.12 26,786.58 11,842.43 1.22 0.96 72,789.27 8,787.88 81,577.14 400 56,805.41 10,900.02 1, 164.07

4f2at 1t2224 9"D 9245 414W1 4 a [)1 24 mw?474.4 729 4 974544 v-me "22 3221 U22" 1c52

N

J

lOin

50,962.96 1,061.82 47,650.75 21,236.44 1.33 1.00 127,014.81 16,862.52 143,877.33 400 102,342.08 119,731.24 2,087.47

15mm

20 m

69,503.75 1,427.24 65,579.73 28,544.90 1.45 1.01 174,525.53 23,908.89 198,434.43 400 135,976.27 127,472.34 2,805.86

2214

83,725.17 1,702.13 79,337.43 34,042.57 1.97 1.08 229,750.50 29,167.91 258,918.41 400 162,852.93 33,391.60 3362 N414541of Data

1.'ml

I1

jm

11'4'

4~o n';

272 4.1 01 at~ 44e44

,4 11445.8$

3

4',.a

'r

Maw~~rn~u

""e2

514as~uw1a

144",~~~~a

224112

311.211a,

41

2K43

14440141226,.4o,45,,,,

~914 99

id 320 (200 East Are Plues

400 , 92a 17463 430M92

22954.4.194

For5hiknssAsumtin

3.20

444 21 5

168735 101644

Table 3.10.

Statistics of Total Activity of Simulations of FY 2001 Tritium Within Sub-Area 2 of Grid 3 (200 East Area Plumes), Four Thickness Assumptions

Mass (Ci) in Depth Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97 .5 1h Percentile 2.5'h Percentile Confidence Level of Mean (95.0%)

5mi 1,082.24 47.58 798.56 951.64 14.50 3.29 7,159.03 179.93 7,338.96 400 3,877.40 1 294.30 1

93.54

lOin 1,917.64 80.85 1,425.58 1,617.06 12.82 3.15 11,093.71 352.14 11,445.85 400 6,370.49 563.60 158.95

15m i 2,574.50 106.38 1,910.00 2,127.50 12.06 3.09 14,893.20 505.46 15,398.66 400 8,203.01 1 810.07 1

209.13

20mi 3,112.11 126.92 2,334.19 2,538.36 12.04 3.10 17,879.21 628.46 18,507.67 400 10,638.91 1,004.63 249.51

metrics calculated for sub-area 1 of Grid 3 for this study (e.g., total activity in the plume and the area above the DWS). The primary reason for this discrepancy is the sparseness of data distribution in those areas, where the distance between adjacent wells can be several kilometers. In hand-contouring the data, hydrogeologists cover those gaps using their understanding of groundwater flow patterns in the region. This is more difficult to do using a geostatistical model, which is constrained by the variogram model fit to the experimental variogram values calculated from the sparse concentration data. The effects of this problem appear to be greatest for the large 200 East groundwater plume that migrates to the southeast, because of the large area and the sparse distribution of monitoring wells in the down gradient portions of that plume. Several methods are being examined to reduce the impact of this effect on history matching the geostatistical results and the results from the SAC model, as detailed in Section 4.5.

3.6

Discussion of Additional Results

Sections 3.1 through 3.5 present the history matching data generated for tritium using FY 2001 data as an example of the data generated for this project. The results provide a number of metrics that can be used to evaluate the performance of the SAC model. These include estimates of the total activity of tritium within defined areas (e.g., plumes associated with facilities), the center of mass of the tritium activity within those areas, the area above the tritium DWS within the defined boundary, and the length of the Columbia River shoreline above the DWS (where appropriate). Each of those results are based on geostatistical analysis of historical groundwater concentrations. By calculating the metrics on a suite of geostatistical simulations it was also possible to provide uncertainty intervals for each of the metrics. History matching data for other time periods and contaminants are contained in Appendices B through H. Each appendix contains the results for a single contaminant and sampling period. Table 3.1 1 gives the appendices and their contents. The XY coordinates for the sub-areas for which mass calculations were made are in Appendices A through H. All coordinates are Washington State Plane Coordinates (South, UTM Zone 11), in meters. 3.21

Table 3.11.

Appendices and Content for Additional Contaminants Appendix B C D E F G H

Year 1992 2001 1992 2001 1992 2001 1992

Contaminant Tritium Technetium-99 Technetium-99 lodine-129 lodine-129 Uranium Uranium

The procedures used to generate the geostatistical simulations and metrics for those other contaminants are the same as those used for tritium in FY 2001 with the exception of the FY 2001 technetium-99 plume for 200 East Area. As discussed in Section 2. 1, that plume was simulated using sequential indicator simulation, with calculation of the metrics performed using the same methods as those applied to all other contaminant plumes.

3.22

4.0

Parameter Uncertainties and Data Gaps

The approach taken for the current study provides quantitative methods for providing history matching data, including estimates of uncertainty in the metrics that can be used to evaluate the SAC model. However, the approach does not address all possible sources of uncertainty in those metrics. Uncertainty in several factors could lead to additional variability in the range of data presented in this study. Those factors include the true concentration for a contaminant at a given point in time, the thickness of contaminant plumes and vertical distribution of contaminants within them, the geologic structure, the porosity of the geologic units, and assumptions made in the geostatistical modeling used as the basis to calculate the metrics. A brief discussion of each of those sources of uncertainty follows. It might be useful in the future to assess the relative importance of those additional sources of uncertainty and determnine the potential effect on the uncertainty bounds provided for the metrics. The width of those uncertainty bounds could have an impact on whether the results of the SAC model are deemed to be acceptable, i.e., the SAC results fall within the range of values estimated from the historical contaminant concentration data.

4.1

Concentration Uncertainty

The contaminant concentration data used for the current study were selected and processed in the same way as the data used for the Hanford Site groundwater monitoring reports (e.g., Hartman et al. 2004). The average annual concentration was calculated for each well for each fiscal year. A number of wells in areas where concentrations do not change rapidly are not sampled every fiscal year, but are only sampled every second or third year. For that reason, if data were not available for the desired fiscal year for a well, in this case FY 2001 and FY 1992, then the average annual concentration from the most recent of the two previous fiscal years was used. The use of an annual average masks two sources of uncertainty. One source is the measurement error associated with each concentration measurement. The second source of additional uncertainty is the variability in the suite of concentration measurements taken within a fiscal year that are used to calculate an annual average. Although both sources of additional variability exist, it is difficult to quantifyv their magnitude. For most concentration measurements, the total analytical error is reported in HEIS, which should provide an estimate of the measurement error that may have been introduced into the analysis at the laboratory. However, it has recently been discovered that in some instances the laboratories reporting the total analytical error have actually been calculating the analytical error for concentrations near the minimum detection limit and then scaling that err or to other concentrations(') (so the analytical error value reported in HEIS cannot be used to estimate the uncertainty associated with an individual measurement, especially for higher concentrations.

(a) Personal communication from PE Dresel (Pacific Northwest National Laboratory) to the authors, January 2004. 4.1

The reduction in uncertainty caused by the use of an annual average cannot be assessed either, because wells have widely varying sampling schedules. During fiscal years when wells are being sampled, they are usually sampled monthly, quarterly, semi-annually, or annually. The variability between samples within a fiscal year cannot be assessed for wells that are only sampled annually or semi-annually. Although the frequency of well sampling for some wells may be determined by regulatory requirements, if there is no regulatory driver, then wells tend to be sampled more frequently when there is reason to suspect greater temporal variability. Thus, the variability found for wells measured monthly cannot be assumed to be representative of the variability that should be expected for wells that are sampled less frequently. Given the inability to estimate the measurement error or temporal variability in concentration measurements, it does not appear to be possible to quantify the additional uncertainty in estimated contaminant concentrations resulting from measurement error or between sample variability, relative to the uncertainty estimated using data averaged over a fiscal year. There are additional sources of uncertainty in contaminant concentrations that arise due to the varying lengths of the open intervals of the well bore from which samples are drawn and variations in hydraulic conductivity within the open interval. For example, if two wells sample areas of a plume with the same concentration and one has a relatively short open interval that only covers the high concentration zone at the top of the aquifer while the second has a longer open interval that includes deeper zones in the aquifer with high hydraulic conductivity and low concentrations, then the second well would appear to have lower concentrations than the first well due to the effects of well bore mixing, even though the mass of contaminant within a unit area of the aquifer might be identical. Given the lack of detailed data on the vertical distribution of contaminant concentrations and hydraulic conductivity in the aquifer, the uncertainty arising from varying lengths of the open interval and well bore mixing cannot be quantified at this time.

4.2

Vertical Distribution of Contaminants

As discussed in Section 2.2. 1, considerable uncertainty exists in the vertical distribution of contaminants in the aquifer. This leads to uncertainty in the thickness of the plume that should be assumed in converting the simulations of contaminant concentration at the top of the aquifer to mass or activity estimates, which greatly increases the uncertainty in several of the metrics (especially the total mass or activity in a plume). The uncertainty related to the differing thickness assumptions modeled in this study can be seen for several of the FY 2001 tritium plumes (e.g., Figures 3.18 and 3.19). If the plume is assumed to be approximately 5 meters thick, as some of the data seem to suggest, then the vertical gradient of concentrations within that interval can probably be ignored. However, there are data that suggest the plumes may be considerably thicker than 5 meters, at least locally. For thicker plumes, the vertical concentration gradient within the plume would be much more important in assessing the total mass or activity of contaminant present. There appears to be data indicating that concentration decreases rapidly with depth even in the thicker plumes, so the assumption of constant concentration with depth that was made earlier in the history matching performed for SAC Rev. 0 and in the present study should be revisited, especially for the 15- and 20-meter plume-thickness assumptions.

4.2

A study to further examine the vertical distribution of contaminants is planned for FY 2004 by the groundwater task of the characterization of systems project. The results of that study might be used to re-examine the assumptions made for this study regarding the thickness of the contaminant plumes and distribution of concentration within those plumes, and to guide the design of any future efforts to estimate ,the mass and activity of contaminants within the plumes.

4.3

Geologic Structure Uncertainty

Considerable uncertainty exists in the geologic structure of the Hanford Site. The identification of geologic form-ations from borehole data can be difficult, especially in drill cuttings, because of the variability that exists in formations at the site, the inability to observe sedimentary structures that might be diagnostic, and the tendency for Ringold Formation sediments to be eroded and then redeposited in the Hanford formation (Xie et al. 2003). Although Xie et al. (2003) found that mineralogy and geochemistry data can be useful in discriminating between Hanford and Ringold formation sediment, those data are rarely available. Together, these factors cause difficulties in identifying geologic units, and especially in distinguishing between coarse-grained units that have similarities (e.g., gravels belonging to the Hanford, Cold Creek, and Ringold units). Therefore, the identification of the geologic unit present can be highly uncertain, even at the borehole locations. Additional uncertainty in the geologic structure exists between the boreholes where data are not available. To calculate the mass or activity of contaminant present beneath a given grid cell, it was necessary to know the geologic units that were present beneath the water table and its thicknesses. In that way, the thickness of a plume associated with a particular thickness assumption (e.g., 5, 10, 15, or 20 meters), could be partitioned between the different geologic units, and a porosity value assigned. The data on form-ation thicknesses used in the study were based on the geologic model incorporated in the sitewide groundwater model. That geologic model is based on interpolation of geologic formation surfaces between the boreholes using EarthVision. This provides continuous surfaces for the top and bottom of each geologic unit in the model, but one that does not take into account the uncertainty between the boreholes. Currently, the sitewide groundwater modeling group is producing a series of stochastic alternative conceptual models of the geologic structure of the aquifer using geostatistical methods. An early version of this approach can be found in Vermneul et al. (2003). That approach will be used to generate alternative simulations of the aquifer geology that honor the tops at the well bores and capture the spatial uncertainty between the boreholes. In future studies, those alternative realizations could be used to determine the sensitivity of the mass and activity estimates and other metrics of uncertainty in the geologic structure. One major element of the geologic uncertainty described in the preceding paragraph is the spatial distribution of mud units in the Ringold Formation. As discussed in Section 2.2.2, the current study assumed that the mud units would not contribute to the mass and activity of the contaminants. Therefore, improved models of the spatial distribution of the mud units would be an important aspect of any future mass and activity simulations for history matching. An additional aspect that could be examined is the potential for contaminants in the mud units to contribute to the total contaminant load. Based on data from the literature on contaminant transport into and out of mud units, different scenarios for the role of

4.3

the mud units at Hanford could be developed and a sensitivity analysis could be used to assess the potential effects of those scenarios on the uncertainty bounds for history matching metrics.

4.4

Uncertainty in Porosity Distributions

An additional element of geologic uncertainty that could contribute to increased uncertainty in history matching metrics is the porosity distribution within different units. For the current study, a single porosity value was sampled from the probability distributions given for each geologic unit in Table 2.1 and applied throughout the Hanford Site for a given simulation of concentration. This approach does not capture the spatial variability that might be expected in porosity within each of the geologic units caused by spatial variations in grain size, sorting, and cementation. Additional uncertainty could be introduced into the new model in two ways. One would be to simply draw a separate porosity value from the relevant probability distribution for each occurrence of a geologic unit. This would produce independent values of porosity for each unit and would not account for any spatial correlation that might be expected in the porosity within nearby cells. In order to account for spatial correlation, an alternative approach would be to use geostatistics to generate a series of simulations of the porosity of each geologic unit. However, this approach would be problematic because there are insufficient porosity data for inference of variogram models, so the variogram models would need to be developed from other data that are available for a large number of samples, e.g., grain size.

4.5

Uncertainty in Geostatistical Modeling

There are two major elements of uncertainty in the geostatistical modeling that have not been quantified. One is the impact that modifications in the variogram model might have on simulated concentration values, and thereby on the metrics that were developed for history matching. The fitting of variogram models to experimental variogram values is not a well-constrained process, and there is variation possible in the range, nugget, and other parameters selected in fitting the model, especially in cases where the data are few and highly clustered or spatially noisy (i.e., the concentration does not appear to vary smoothly in space). To determine the potential impact of uncertainty in variogram modeling, it would be possible to do sensitivity studies, vary model parameters and then generate alternative sets of stochastic simulations of the concentration that could be used to calculate alternative sets of metrics for a particular plume. Also, as discussed in Section 3.5, metrics calculated from the geostatistical simulations, including the total activity in a plume and the area above the DWS, may underestimate the true values of metrics in areas with sparse data. In the current study, this situation appears to occur in the larger plumes associated with 200 East Area that have undergone rapid transport due to the presence of permeable Hanford formation gravels at the water table. In those areas, the spacing between wells is often beyond the range of the variogram model, and there are only a few high concentration data points within the plume that tend to be overshadowed by a larger number of low values located beyond the edge of the plume. Thus, high concentrations tend to be simulated within limited areas near high concentration data points within the plume, and the plume is not as well connected as it might be in a hand-drawn contour map. Several avenues could be investigated to deal with this situation. One would be to split the plume within sub-area I of Grid 3 into near-field and far-field zones and model the experimental variograms

4.4

separately. As mentioned in Section 3.2, there may be differences between the long- and short-range variogram structures because many local recharge areas associated with discrete waste facilities in the near-field areas create complex local groundwater flow directions that affect the short-range variogram structure, whereas farther away from the source, the contaminant distribution and variogram structure associated with it are affected only by the regional groundwater flow. This suggests that there might be longer variogram ranges in far-field areas of the plume, though it remains to be seen if there is sufficient data to calculate reliable variograms in those areas. An additional complexity is that the direction of maximum continuity varies in the far-field flow system. For example in Figure 3.15, the direction of maximum continuity of tritium concentration data is roughly northwest- southeast between 200 East Area and the Central Landfill. However, the plume bifurcates east of that area, apparently due to the distribution of relatively low permeability sediment of the Cold Creek unit and Ringold Formation in that area. A segment of the plume continues to the southeast, past the 400 Area toward the Columbia River, while a sizeable portion of the contamination has moved toward the northeast. Thus, the maximum continuity of the concentration data changes in that area from northwest-southeast to northeast- southwest. Because of the variability in anisotropy direction, it was necessary to model the variogram with an isotropic model. It might be possible to achieve greater continuity of the contaminant plumes in areas of sparse data if variations in the anisotropy field could be captured. It might be possible to do this by using the groundwater velocity field in Grid 3 to provide an estimate of local variations in the directions of maximum continuity. This would require modification of the sequential Gaussian simulation code used to simulate concentration data. There is a simpler approach that would allow direct comparison of the metrics generated fromn geostatistical simulations of concentration data and SAC model runs. This would involve sampling the concentration output from the SAC model at locations, and over the same depth intervals, where historical concentration measurements were made by the Groundwater Performance Assessment Project. The data sampled from SAC model runs would then be analyzed geostatistically, using methods developed in this report, and the same metrics would be calculated from geostatistical simulations of concentration. Both sets of geostatistical simulations would be performed using the same set of sparse locations, so differences due to the sparse distribution of data would be eliminated.

4.5

5.0

Summary and Recommendations

The approach taken in this study has developed a set of metrics that quantify the spatial distribution of four radionuclide contaminants for two points in time FY 2001 and FY 1992, based on historical groundwater concentration measurements. Approximately 24 separate geostatistical studies were completed for that effort, with metrics developed for numerous individual plume areas. That information can be used to evaluate the ability of the SAC Rev. 1 model to produce simulated concentration histories over time that match historical data. In addition, this study provides measures of the uncertainty in each of those metrics that can be used to determine if predictions from the SAC model fall within the uncertainty bands expected due to spatial uncertainty in historical contaminant concentration data. The approach developed for this study appears to represent a significant improvement over the approach used for history matching evaluation of SAC Rev. 0. Several possible improvements or extensions of the approach appear to be worth consideration and are recommended for future study. These include: " Extend this approach to other contaminants. This is currently underway, with extension of the approach to several chemical contaminants for the same time periods. The contaminants that will be completed in FY 2004 are chromium, nitrate, and carbon tetrachloride. " Generate results for additional time points beyond the two points in time considered in the present study. History matching data should be generated for earlier points in time, although the areas covered might need to be restricted due to the sparse distribution of data for earlier time periods (see Figure 2.1). " Examine the effect of vertical contaminant distribution assumptions on uncertainty bounds for history matching data. As mentioned in Section 4.2, a characterization of systems study will be conducted in FY 2004 to examine the vertical distribution of contaminants. The results of that study should be used to guide a sensitivity or uncertainty analysis of the effect on uncertainty bounds of history matching data related to uncertainty in plume thickness and the vertical distribution of contaminants within the plume. For example, one could examine the difference in uncertainty bounds caused by using an assumption of constant concentration with depth versus models that assume the highest concentration occurs at the water table and then use simple mathematical models to decrease the concentration with increasing depth in the aquifer. " Perform an uncertainty analysis to examine the effect on uncertainty bounds for various metrics that might arise from uncertainty in the geologic structure and porosity distribution. This should be done by using the results of work being performed in FY 2004 for the sitewide groundwater modeling task to develop stochastic altemnative conceptual models of the geologic structure. In addition, it might be useful to examine how sensitive the metrics are to the assumption that the mud units do not store appreciable quantities of contaminants that will later become available to the aquifer again. " Examine the sensitivity of history matching metrics to variation in the parameters of the variogram models fit to experimental variograms. This might include examining smaller grid areas more 5.1

representative of individual plumes, especially in the large plume associated with 200 East Area to examine the relationship between near source and far-field variograms. *Produce a set of metrics based on the SAC model runs that accounts for the sparseness of concentration data available for geostatistical modeling. That set of metrics is more likely to match the metrics presented in this study. The suggested approach includes sampling the concentration fields from the SAC model runs at historical well locations and over the screened intervals that were employed in sampling groundwater. Geostatistical analysis of the sampled model runs would then be used to generate a set of metrics using the same methods described in this report. The metrics calculated from historical groundwater data and sampled SAC model runs would then be compared to evaluate the ability of the SAC model to reproduce historical groundwater concentration data.

5.2

6.0

References

Bryce RW, CT Kincaid, PW Eslinger, and LF Morasch. 2002. An Initial Assessment of Hanford Impact Performed with the System Assessment Capability. PNNL-14027, Pacific Northwest National Laboratory, Richland, Washington. Davis, JC. 1986. Statistics and DataAnalysis in Geology. New York, John Wiley & Sons, Inc. Deutsch CV and AG Journel. 1998. GSLIB: GeostatisticalSoftware Library and User 's Guide. New York, Oxford University Press. DOE Order 43 5.1. 1999. Radioactive Waste Management. U.S. Department of Energy, Washington, D.C. Available on the Internet at http://www.hanford.gov/wastemgt/doe/psg/pdf/doeo435.1.pdf DOE. 2003. GroundwaterSampling and Analysis Planfor the 200-BP-5 Operable Unit. DOE/RL200 1-49, U.S. Department of Energy, Richland Operations Office, Richland, Washington. Eddy PA, DA Myers, and JR Raymond. 1978. Vertical Contaminationin the Unconfined Groundwater at the Hanford Site, Washington. PNL-2724, Pacific Northwest Laboratory, Richland, Washington. Freeman EJ, R Khaleel, and PR Heller. September 2002. A Catalog of Vadose Zone Hydraulic Propertiesfor the Hanford Site. PNNL- 13672, Rev. 1, Pacific Northwest National Laboratory, Richland, Washington. Gomez-Hemnandez JJ and AG Joumnel. 1993. "Joint Sequential Simulation of MultiGaussian Fields." In Geostatistics Troia '92, A. Soares (ed.). Dordrecht, Kluwer Academic Publishers, 1:85-94. Goovaerts P. 1997. Geostatisticsfor Natural Resources Evaluation. New York, Oxford University Press. Hartman MJ (ed.). 2000. Hanford Site GroundwaterMonitoring: Setting, Sources, and Methods. PNNL- 13080, Pacific Northwest National Laboratory, Richland, Washington. Hartman MJ, LF Morasch, and WD Webber (eds.). 2002. Hanford Site GroundwaterMonitoringfor Fiscal Year 200]. PNNL-13788, Pacific Northwest National Laboratory, Richland, Washington. Hartman MJ, LF Morasch, and WD Webber (eds.). 2004. Hanford Site GroundwaterMonitoringfor Fiscal Year 2003. PNNL-14548, Pacific Northwest National Laboratory, Richland, Washington. Isaaks EH and RM Srivastava. 1989. An Introduction to Applied Geostatistics. New York, Oxford University Press. Johnson VG and CJ Chou. 2000. RCRA Groundwater Quality Assessment Report for Waste Management Area S-SX (November 1997 through April 2000). PNNL- 13441, Pacific Northwest National Laboratory, Richland, Washington.

6.1

Journel AG. 1987. Geostatisticsfor the Environmental Sciences. CR 811893, U.S. Environmental Protection Agency, Environmental Monitoring Systems Laboratory, Las Vegas, Nevada. Journel AG. 1989. Fundamentalsof Geostatistics in Five Lessons. Volume 8, Short Courses in Geology, American Geophysical Union, Washington, D.C. Journel AG and M Rossi. 1989. "When do we need a trend model in kriging?" Mathematical Geology 21,715-739. Khaleel R and El Freeman. 1995. Variability and Scaling of Hydraulic Propertiesfor 200 Area Soils, Hanford Site. WHC-EP-0883, Westinghouse Hanford Company, Richland, Washington. Kincaid CT, RW Bryce, and 1W Buck. 2004. Technical Scope andApproach for the 2004 Composite Analysis of Low Level Waste Disposal at the Hanford Site. PNNL-14372 Draft, Pacific Northwest National Laboratory, Richland, Washington. Rajaram H and LW Geihar. 1991. Three-Dimensional Spatial Moments Analysis of the Borden Tracer Test. Water Resources Research, 27(6), 1239-125 1. Thorne PD and DR Newcomer. 2002. Prototype Databaseand User 's Guide of SaturatedZone Hydraulic Propertiesfor the Hanford Site. PNNL-14058, Pacific Northwest National Laboratory, Richland, Washington. Vermeul VR, MP Bergeron, CR Cole, CJ Murray, WE Nichols, TD, Scheibe, PD Thorne, SR Waichier, and Y Xie. 2003. TransientInverse Calibrationof the Site-Wide Groundwater Flow Model (ACM-2): FY03 Progress Report. PNNL-14398, Pacific Northwest National Laboratory, Richland, Washington. Williams BA, BN Bjomrstad, R Schalla, and WD Webber. 2002. Revised Hydrogeology for the Suprabasalt Aquifer System, 200- West Area and Vicinity, Hanford Site, Washington. PNNL- 13 85 8, Pacific Northwest National Laboratory, Richland, Washington. Xie Y, CJ Murray, GV Last, and R Mackley. 2003. Mineralogicaland Bulk-Rock Geochemical Signatures of Ringold and Hanford FormationSediments. PNNL- 14202, Pacific Northwest National Laboratory, Richland, Washington.

6.2

Appendix A Sub-Area Boundary Coordinates for FY 2001 Tritium

Appcndix A Sub-Area Boundary Coordinates for FY 2001 Tritium Table A.1.

Coordinates for Sub-Area Boundaries for Grid 1 (200 West Area) of FY 2001 Tritium Sub-Area I Basting (in) (in) 565400 131400 565400 134250 570515 138320 571060 137034 57i364 136328 572138 135554 572405 134779 572700 134629 572700 131400 565400 131400

Sub-Area 2 Easting (in) (in) 565400 139200 569868 139200 570515 138320 565400 134250 565400 139200

]Northing

[Northing

A.I

Table A.2.

Coordinates for Sub-Area Boundary for Grid 2 (100 Areas) of FY 2001 Tritium

[

]Northing

Basting (in)

Northing (mn)

563900 563900 564206 564778 565610 566373 566915 567588 567905 568736 569056 569597 570361 570967 572118 572754 573070 573965 573996 574315 574379 574635 575910 577761 578239 579740 579962 579962 579706 579582 579706 580124 580985 581463 582227 581941 582516 582897 583216 583250 582450 582205 581992

143800 145566 145277 145277 145502 145754 145882 146172 146522 147033 147447 147959 148692 149392 150987 151785 152199 152744 153030 153828 154144 154500 154500 153410 152710 151371 150987 150573 149806 149614 149200 148787 148211 147764 147350 146902 145724 145118 144129 143800 143800 144140 144441

581522 581309 581053 580882 580455 579944 579390 578834 578407 578067 577766 577682 577766 577980 578193 578193 578193 577938 577511 577171 576573 576061 575508 575123 574441 573971 573544 573033 572606 572179 571839 571454 571027 570474 569876 569109 568426 567702 567061 566508 566123 565951 565600

145250 145590 145975 146188 146531 146444 146318 146360 146444 146871 147469 147893 148408 148789 149304 149815 150410 151051 151436 151775 151863 151733 151436 151093 150326 149728 149216 148789 148236 147809 147382 146871 146486 145891 145506 145250 145208 145208 145036 144994 144823 144182 143800

144910

563900

143800

11 581736

1

A.2

Easting (in)

(mn)

1

Table A.3.

Coordinates for Sub-Area Boundaries for Grid 3 (200 East Area) of FY 2001 Tritium Sub-Area I Easting (in) Northing (mn) 573050 135650 575750 136950 576319 137080 576946 136478 577308 135180 579183 135415 579805 135567 580221 136037 580246 138196 582650 138900 582909 138876 583780 138441 584838 137633 585773 137011 587393 136135 586272 137197 583966 138876 587109 138925 589685 137285 590620 136169 591192 134999 593273 133570 594184 131797 594497 130319 594521 128733 594732 127822 594913 126990 594575 124704 594521 123950 594521 121947 594472 118956 594262 117605 594340 116694 594810 114643 5500 122750 573050 135650

j

A.3

Sub-Area 2 Easting (in) Northing (in) 573050 135650 575750 136950 574816 137442 574009 137599 573749 138015 573568 137809 573230 137858 573230 139004 573827 139939 572657 141966 572501 142068 571487 142019 571409 142279 571722 142460 573593 142538 574557 142563 576868 142538 577416 142093 577910 142122 573600 146150 567400 146150 567400 143800 568291 142460 569250 142044 570263 140693 570498 139782 570239 139758 573050 135650

Appendix B Figures and Data Tables for FY 1992 Tritium

Appcndix B Figures and Data Tables for FY 1992 Tritium

135000 0)0

00

z

Z 105000- Gree

5500

1250

C rsrin o.

6500

l gae (nt

5500

5800

Figure B1.BSues of FY 199 f Trimat and Subro Fomaio Wate Tabesh rve aceso l e i t3

105000m~ ~ ~ ~oreganRn ~~~~~B Gre

dgae it)

950

Unt1tthY19

1.412

X

(a)

-0.8

X

>-0.6-

N

0.4 0.2, y(h) 0

=0.1 +0.15

1000

Sph(250)

+

0.75 Sph(2000)

2000 Distance (in)

3000

4000

2

X Xx

1.8 -(b) 1.6-

1.4-

X

1.2 -X

x

x

1-

0.6 0.4 0.2 -y(h)

=0.18

+ 0.82 Gau(800)

0 0

500

1000 Distance (mn)

1500

2000

1.6(C)

1.41.2

X

-

0.6 0.4 y(h)

X

0

Figure B.2.

1000

2000 Distance

=

0.1

+

0.9 Sph(2800) 3000

4000

(in)

Variograms and Models of Normal Scores of FY 1992 Tritium Data in Local Grid 1 (a), Grid 2 (b), and Grid 3 (c). Experimental variogram values designated by X, with the models fit to the data denoted by solid black lines.

B.2

15500000

1450050000

200000

-5000

100

555000

565000

675000

585,000

595000

Easting (in) Figure B.3.

Median of Simulations of FY 1992 Tritiumn Concentrations for Grids 1, 2, and 3

B.3

14600000

200 Ea20000

100

1360100

5000

Z 3200 00-j

s o

6500

5500

a

o6006700C70000

0 27000

Easting

Fiur .4

Table B.

eda o

imlte F

99

riim

000

ocetaton3n0rd00200es

Coodianae ofo Siu-aea Bounda2riesu foceGridon 1Gid1(200 West Area). 19

Sub-Area I Fasting (in) Northing (in) 565400 131400 565400 134250 570473 138274 571023 136892 571274 136289 571940 135549 572405 134779 572700 134629 572700 131400 565400 131400

Sub-Area 2 Fasting (in) Northing (mn) 565400 139200 569786 139200 570473 138274 565400 134250 565400 139200

B3.4

re)

rtu

Table B.2.

Statistics of Centers of Mass of Individual Simulations of FY 1992 Tritium Calculated for a Depth of 5 m for Each Sub-Area of Grid 1 (200 West Area)

Coordinate (in) Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97.5t' Percentile 2.5th Percentile Confidence Level of Mean (95.0%)

Sub-Area I Easting Northing 569460.4 12.5 569466.3 279.4 1.09 -0.32 2069.4 568277.0 570346.3 500 570007.3 1568913.0 24.5

B.5

134018.9 15.4 134011.0 344.0 0.03 0.02 1905.6 133041.8 134947.3 500 134746.7 1133317.2 30.2

Sub-Area 2 Easting

J~Northing

567523.2 15.3 567458.0 342.1 3.37 1.42 2403.6 566760.1 569163.7 500 568485.9 567007.1 30.1

137113.7 14.3 137061.0 318.8 0.89 0.88 1844.6 136499.3 138343.9 500 137876.5 1136620.6 28.0

+

+

140000-

+

I ++

+

200 East Are

_

+

200 West Area

138000-

1: 2

+

+

-~~+1++--~ +

Contou'r of nuLsmber of tenters of mass

+

+

+R

136000-

+ 1342000-

130000-

128000-

5601000

562 1000

5641000

566000

568'000

5701000

572 1000 '574'000

Easting (in)

Figure B.5.

Probability of Exceeding 20,000 pCiIL Based on Simulations of FY 1992 Tritium in Grid 1 (200 West Area)

Table B.3.

Area Exceeding 20,000 pCi/L for FY 1992 Tritium for Each Simulation within Two Sub-Areas of Grid 1 (200 West Area) Area (kin 2)

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5th Percentile Prcntle9.01 25 t Confidence Level of Mean (95.0%)

Sub-Area I 13.16 0.10 12.99 2.25 0.02 0.17 13.86 6.75 20.61 500 17.76 0.20

B.6

]

Sub-Area 2 1.83 0.02 1.76 0.50 3.21 1.30 3.43 0.82 4.25 500 3.13 1.07 0.04

[

Grid I 20.13 0.17 19.85 3.76 0.30 0.46 22.48 11.40 33.88 500 27.98 13.62 0.33

_

o Data, 677be

300

N4600960 Datta 500 66946 1092207 617 Cie. "9 56 c fofllaf 0,17 t0a.,rrfm 3072361 9705 oo-cer0e ;!3033639q upper oua6171612459407 9 i~rqatl 117 2~5 ,r~f 716 766671 3 144

6694m $524 67 6MI 666 2678 33!

0

~

1,0

co f - 046 94606l. 20833 28 97 5 pe,6er1tl 1195721 uppe7r7324,7e 717597 66630o, 5304 666504 4Ue 70l69r02400 3799 10 Pt'ce.We 20647 176 m, 73044

oo20' 66

030

1(0

00

0

000

20W10

1000

17100D

5w,6 3 70oa91

N3070(0pof 41

.71030

2 300 676

04a 0

Number of D~ata 00 m6646 20309 00 617 4,6, 9742897 00of6a 049 64666606676379824 97 5 79679617742974 03 upper64046129 25131 67

6166461569869

stlde06 poe of7 069 06

7449 97 047

7 120

566646661030 Do

97 0 060(9677633076899 upper1quartil 1026711 rn6a,4 14212 07 I666 Quart76 10260233769

64619063

012

Q

3

22W sA^$ o

Table B.4.

1171

a(

233 12"0

Figure B.6.

41030

10,

06676

300

42MO,

5210D

62002

2000

12000

:20.OW 2203

02576 e

4

'22"3 2000 o

Ma661446{ 67

2008~00

2-

Histograms of Total Activity in Simulations of FY 1992 Tritium within Sub-Area 1 of Grid 1 (200 West Area), Four Thickness Assumptions Statistics of Total Activity of Simulations of FY 1992 Tritium within Sub-Area 1 of Grid 1 (200 West Area), Four Thickness Assumptions

Mass (Ci) in Depth Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5 th Percentile 2.5~ Percentile Confidence Level of Mean (95.0%)

5m 5,824.67 119.90 5,304.89 2,681.01 2.40 1.17 20,102.83 730.44 20,833.28 500 11,956.96 2,068.47 23.5 B.7

loin 10,922.07 228.02 9,930.60 5,098.66 2.75 1.26 38,301.17 1,422.45 39,723.61 500 23,036.35 3,977.16 44.0

15m 15,698.69 333.51 14,213.08 7,457.43 2.95 1.31 56,041.73 2,061.35 58,103.08 500 33,578.76 5,709.88 655.25

20m 20,208.99 436.15 18,206.07 9,752.63 3.13 1.36 73,702.36 2,675.88 76,378.24 500 43,873.50 7,279.3 85.9

N,5s56t1 D Oal 500 955 msean 20022 Mal4464 125835124 COof 1, 063 ma, 1 143344

ase

0 12o, s

4655559

Mass JCsri

----

515.. Sfsmrfmm

~~~~~97 5 49 012

1

111,1722

5D5

cssl ofar1 orasrns 7065 11 75sc~5e pe--W 15799 4t64 45 57515515 rre5 415 2 5 P16111

m46 ass

Nsmber of D5ata 555 mean5 5S7.94 de14 56 7592 coef ol var 063 61446456 4,2646 97,56141( 161022 5556164411(6it55.64 15 n4 51299

146,41

I~ 1504

fPrmbe5 oData man 791864 Sf5 Ole4 49265 55sf of va 062 masrmsm5542 56 97 5 irersosiss 214562 5555 quatw1 624 46 1116416n681,26

0 00

Sf51

2 5pesmrile 21919 122.29

t5 296 5 4

2,6 55Cenitrr 29.1 47 M muma 176550

010

0K5.

Figure B.7.

Table B.5.

of Dal, 555

5.

515)

9

516

555 0160..,

Histograms of Mass of Simulations of FY 1992 Tritium within Sub-Area 2 of Grid 1 (200 West Area), Four Depth Assumptions Mass of Simulations of FY 1992 Tritium within Sub-Area 2 of Grid 1 (200 West Area), Four Depth Assumptions Mass (Ci) in Depth

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97 .5th Percentile I5T P -ercentile Confidence Level of Mean (95.0%0)

5Sm 200.22 5.63 171.22 125.96 21.73 3.44 1,389.16 44.28 1,433.44 500 539.10 73.50 11.07 B.8

[

lOin 399.69 11.26 342.11 251.72 21.75 3.44 2,776.79 88.31 2,865.11 500 1,077.87 146.41 22.12

Irm 15 597.94 16.83 512.99 376.31 21.77 3.44 4,151.77 132.29 4,284.06 500 1,610.13 1 219.19 33.06

20m 791.84 22.06 681.29 493.34 21.22 3.40 5,406.58 176.00 5,582.58 500 2,145.59 1 291.47 43.35

0 H5T00000

154000_77,

Area

-~

a

Are

148000-

5

'41

0000

101000

6600

150 000

0

6700a600600

Areag

in

00 56390056390 56426

14805465140 1456055900540 1527757761

56637

1475

5796

150987fnunp

567588-

1417

57970

149806uttt

1341

71474477100

580124

14878

5690056810 569597n

14795

5898

1421

573965 573996 574315

152744 1453030 1453287

58431 58350 563900

1544129 1543800 15480

57479

14514452

56873

14733

491

57706

4929

50

Table B.7.

Statistics of the Area Exceeding 20,000 pCi/L and Locations of Centers of Mass for Simulations of FY 1992 Tritium within Grid 2 (100 Areas)

Ara(ki) Mean

Center of Mass (in)

M2

ratn Northing

15.05

Standard Error Median Standard Deviation

148368.1

573710.1

0.11

35.7

29.2

14.69

573716.3

148370.0

2.86

944.9

773.7

Kurtosis Skewness

-0.24

Range

16.38

7716.2

Minimum

8.18

570248.0

145859.0

Maximum

24.56

577964.2

150408.5

0.35

Count

700

97.5t" Percentile 2 .5th

Percentile

Confidence Level (95.0%)

0.90

-0.33

0.00

-0.06 4549.5

700

700

21.20

575466.8

149789.9

10.22

571800.9

146891.0

0.21

70.1

57.4

00 H Area

154000p

-1000D

+

+

Area

152000-

+

++

~Area

Area 148000-

104.+ +

Are

++

++

+ +

564000

568000

+

572000

576000

580000

Easting (in) Figure B.9.

Probability of Exceeding 20,000 pCi/L Based on Simulations of FY 1992 Tritium in Grid 2 (100 Areas)

B3.10

0.100-

cos

[97-5

Number of Data mean std. dev. coef. of var maximum

percentile 6035.88

upper quartile median quartile 2.5 percentile minimum

Flower

c 0.060

700 3684.09 1023.14 0,28 6940,86 4345.58 3560.97 2957.41 1991.73 965.68

0.040

800.

1800.

2800

3800.

4800,

5800

6800.

Average Length (in)

Figure B.10.

Histogram of the Average Length of Columbia River Shoreline Exceeding 20,000 pCi/L for FY 1992 Tritium in Grid 2 (100 Areas)

B.1 I

Nu110,I07 of Dal

700

Nomt-71of Data

0

97 5

07

medla.812319710

50101010

0011 010a, '"n"'u"1 710 7

71'7111171820

9770071707171770 000 10

_170,4.. X392

200

121190

170415

cM

10,11 trc

of17 Data000,0

7

Nolll00l 07 81

140171 Co.l

010191a04

0

Daa

V78191 701878

039

ol.

,Oa,MuM14761 72

ma mom411 1010019 C110971"1811 9W0205 .011.1 908M;7 0000 71

Table B.8.

0391 1090384 625~070038

7

MOO7C7 . m~

Figure B.11.

700

987397"087 old 10 !YG2 89

7I 0

70471 223 d1o.~ 02691 e04 9 17 41

1500010071

10011 19

o0p01 9o8170 609793

mW

2T1001804711

-mom

14f 1 774mm

20 0t

p9177171723R4 77

699

Histograms of Total Activity in Simulations of FY 1992 Tritium within Grid 2 (100 Areas), Four Thickness Assumptions Statistics of Total Activity of Simulations of FY 1992 Tritium within Grid 2 (100 Areas), Four Thickness Assumptions

Mass (Ci) in Depth Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97.5'hPercentile .5t Percentfile Confidence Level of Mean (95.0%o)

5m 2,522.31 38.92 2,319.67 1,029.65 1.47 1.08 6,519.65 662.89 7,182.53 700 5,008.89 1,125.96 76.41

B. 12

loin 3,970.87 59.11 3,639.23 1,564.00 1.29 1.04 9,826.09 1,137.75 10,963.84 700 7,825.31 1,794.15 116.06

15 m 4,711.68 68.38 4,328.94 1,809.06 1.09 0.98 11,702.11 1,461.07 13,163.19 700 9,001.98 2,147.98 134.25

20 m 5,228.55 75.19 4,846.75 1,989.31 1.02 0.96 13,065.74 1,695.97 14,761.72 700 10,055.47 2,394.77 147.62

145000-'

1450000

2000

5~0000

+

1000

700

Fiue12

6700

eino0iultd0-92Trtu

6800

660009000900

Enstlng ocnrain

n ahsu-ra shw-y mass~~~~~~~D lestr

B.5013

Noin)es nGi 3(0

atAe

Table B.9.

Coordinates for Sub-Area Boundaries for Grid 3 (200 East Area) of FY 1992 Tritium Sub-Area 1I Easting (in) 573050 575750 579634 579609 579790 580020 580074 580045 582650 582909 583780 584838 585773 587393 586272 583966 587109 589685 590620 591192 593273 594184 594497 594521 594732 594913 594575 594521 594521 594472 594262 594340 594810 582500 573050

]~Northing (mn) J 135650 136950 138020 137657 137403 137657 138044 138152 138900 138876 138441 137633 137011 136135 137197 138876 138925 137285 136169 134999 133570 131797 130319 128733 127822 126990 124704 123950 121947 118956 117605 116694 114643 122750 135650

B.14

Sub-Area 2

JNorthing (in)

asting (mn) 575750 575453 574753 574263 573593 573671 573852 573827 572657 572501 571487 571409 571722 573593 574557 576868 577416 577910 573600 567400 567400 568320 569201 569769 570156 570283 570259 570102 573050 1 575750-

136950 137398 137760 137760 139361 139670 139905 139939 141966 142068 142019 142279 142460 142538 142563 142538 142093 142122 146150 146150 143800 142485 142122 141530 140913 140600 140032 139929 135650 136950

Table B.10.

Statistics of Locations of Center of Mass for Simulations of FY 1992 Tritium Calculated for a Depth of 5 m for Each Sub-Area of Grid 3 (200 East Area Plumes)

Coordinate

(in)

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9. Percentile . Percentile Confidence Level of Mean (95.0%) 2 5 th

Sub-Area I Lasting

JNorthing

586175.0 49.6 586114.3 1052.9 -0.31 0.33 5620.3 583825.0 589445.4 450 588325.4 584377.4 97.5

B. 15

130186.6 49.2 130303.5 1043.0 0.21 -0.50 6467.9 126248.5 132716.4 450 131929.4 127935.5 96.6

Sub-Area 2 Lasting Northing 571322.4 142135.7 36.0 42.3 571393.6 142152.6 763.5 896.7 0.40 -0.16 -0.04 -0.17 4578.5 4990.3 569135.4 139448.3 573713.9 144438.6 450 450 572776.1 143774.2 140339.5 569776.1 70.7 83.1

++

++

+

.

+K4

Z

~

~

Enecxdoghes

U

+

0.5

No00 Area

570000

5700

Grid~~Nrt

5800

5800.9005950

3A20raseAeaPums

8.164

+4

Table B.11.

Area Exceeding 20,000 pCi/L for FY 1992 Tritium for Each Simulation within Two Sub-Areas of Grid 3 (200 East Area Plumes) Area (kin 2 )

Sub-Area I

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5 Ih Percentile 2.5"' Percentile Confidence Level of Mean (95.0%)

117.24 0.60 117.23 12.76 0.09 0.20 78.34 83.01 161.35 450 143.65 94.19 1.18

1 1

-

0.080

0.060upper 0.06median Cr

0.020 L_

2000

6.70 0.09 6.44 1.85 0.19 0.49 11.19 2.66 13.85 450 10.80 3.50 0.17

Number of Data mean std. dev. coef. of var maximum 1 97.5 percentile quartile lower quartile 2.5 percentile

~

__

7000.

Grid 3 133.82 0.63 133.57 13.40 0.21 0.20 85.00 92.84 177.84 450 162.17 108.92 1.24

450 10349.06 3109.24 0.30 20158.68 16748.17 12252.13 10139.70 8208.33 4466.29

________

12000 Average Length

Figure B.14.

[

j__

2? 0.040-

L-

0.

Sub-Area 2

17000,

22000.

(in)

Histogram of Average Length of Columbia River Shoreline Exceeding 20,000 pCi/L for FY 1992 Tritium in Grid 3

B. 17

Nntw09. t

400

Nunrr 01 1241 460 ,sem 8W47 019 de.

197477?21g

0.1211.

Osv. 90092 1! 317 1C

M.ra'O.

ma-uao 20857469 979~e9505Cr09i 14929 71 aetj, 8109739 09 798 132.1191 2 9octtrn 0 5(2. 430399go 21$rC 1972 54

505 349 a M."4

4539..92 ~a0 oi?

W,10

219as,241'7 914

a~~~~~~-u

-a1

r910

11~~ 242 709,

$1C dev

733

10Cr8

=90 3,2

M9 Oft 4477582

92f a 04'00 197-11 83(A 62'

012c.

970 0105'09 M079' 04l119931 C511192 40 0010.209eoe'03 Cr

_

0051 Of2 -a-,m'1

,3

354317788 97 79'e"19 25282003 .Ppe, 0001991 170974 29 1115347 139799l73

221353

90970 091 662.1 32

29 2 5 9'Crit

.34'.

... ......... _ _

5

7464041 61C.,l 0771 00

04G0

_

_

_

__

_

_

_

_

_

_

__

_

_

__

_

__

_

__

_

_

Figure B.15.

Histograms of Total Activity in Simulations of FY 1992 Tritium within Sub-Area 1 of Grid 3 (200 East Area Plumes), Four Thickness Assumptions

Table B.12.

Statistics of Total Activity of Simulations of FY 1992 Tritium within Sub-Area 1 of Grid 3 (200 East Area Plumes), Four Thickness Assumptions Mass (Ci) in Depth

5Sm Mean 47,977.31 Standard Error 710.50 Median 45,395.52 Standard Deviation 15,071.96 Kurtosis 1.42 Skewness 0.88 Range 101,512.70 Minimum 16,814.46 Maximum 118,327.16 Count 450 97.5th Percentile 82,225.62 j 5 h Percentile 24,226.05 Confidence Level of Mean (95.0%1___ 1,396.32

B. 18

lOin 85,457.08 1,241.83 81,087.36 26,343.20 1.33 0.86 176,601.14 31,973.54 208,574.68 450 146,348.71 43,211.51 2,440.52 _L

15mi 11,8242.70 1,699.15 111,826.39 36,044.39 1.24 0.85 238,743.31 46,621.30 285,364.61 450 201,864.90 58,750.83

20m 147,408.47 2,113.10 139,786.68 44,825.67 1.18 0.84 293,546.67 60,771.00 354,317.67 450 252,565.79 74,748.07

3,339.28

4,152.80

11 SW0

ue 0

262685111 659646

02 19 4 7 11144'We 1,1

12k._9

22,3479 $Id

1

2C6

6

ii9795

8r,

2 5 p--t41 49

5N

1.G11

996

O

WNW

1.,

700

.409

e

2746 31111

,d1 9114 164F 6

97 111 151 1079301 1 l9 ,a 6994361 944411 49514 143126276

In"11

9799 4994 "

5~ 911276

99 " ,

1.-14 2976 2 51j CpV1 ,146563

'4

811377

e~,

4

KW,1.3

I960 1499

ma1 14

1

~9 T1 69 994194 1,Ze64CI 1

e91

49e' 91443409

9.

691191 4~~~1 1 54 , "14441 1 51 99 69"

1314943 111 97 5 p11991 4 844605 94'qal9 45421964 111140 292 94

42919414119 0 11

1 11114

62,94

Figure B.16.

Histograms of Total Activity in Simulations of FY 1992 Tritium within Sub-Area 2 of Grid 3 (200 East Area Plumes), Four Thickness Assumptions

Table B.13.

Statistics of Total Activity of Simulations of FY 1992 Tritium within Sub-Area 2 of Grid 3 (200 East Area Plumes), Four Thickness Assumptions Mass (Ci) in Depth

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5 h Percentile 2.5' Percentile Confidence Level of Mean (95.0%)__j

5Sm 1,262.85 30.98 1,090.69 657.19 4.29 1.69 4,622.44 186.27 4,808.71 450 3,065.12 467.39 60.88

B. 19

[

lOin 2,204.79 52.18 1,945.86 1,106.83 4.14 1.63 7,756.59 357.18 8,113.77 450 5,067.22 865.78 102.54

15 m 2,978.32 70.12 2,627.59 1,487.48 4.15 1.63 10,201.32 501.69 10,703.01 450 6,972.57 1,169.19 137.81

20M 3,674.86 87.29 3,252.94 1,851.70 4.20 1.64 12,523.50 625.94 13,149.43 450 8,292.36 1,422.89 1715

Appcndix C Figurcs and Data Tables for FY 2001 Tcchnetium-99

Appendix C Figures and Data Tables for FY 2001 Technctium-99

GreGri

no.s19

5500

6500£5005000

Blue ~ Figure .1.

~

950

~ unt1 Estn (in)dFrato

Subets of FCo201seraneim 9 Dratalaund thc

FY 2001 Water Table

C. I

omtinUisa h

1.6 1.4

X

1.2

X

X

X

1

0.6 0.4 0.2

0 Figure C.2.

y(h)

500

=0.1 +

1000

0.4 Sph(1 50)

1500

+

2000

Distance (in)

0.5 Sph(800)

2500

3000

Variograms and Models of Normal Scores of the FY 2001 Technetium-99 Data in Local Grid 1. Experimental variogram values designated by X, with the models fit to the data denoted by solid black lines.

C.2

1.6 -X

1.6

1.4-

I

X

x

1.4-

1.2 -

1.2-

0.8

E0.8

0.6

0.6-

0.4

X

0.40.2 -(2)

(1) cutoff =50 pCj/L (35%) y(h) = Sph(750)

0.2

0

1.6

200

y(h)

~0

0 400

600 800 Distance (in)

1000

1200

--

1400

0

1.6

------

14 1.2-

X

XX1 XX

x

~X

0.6

0.4

0.4 (3) cutoff

=300

400

600 .800 Distance (in)

200

400

_-- _

1400

_-------

X

cutoff

=900

pCi/L (70%)

y(h) =Sph(250)

________0.1__+__0.9______________

0

1200

-

02(4)

pCi/L (65%/)

1000

--

12

0.6

0.2

200

cutoff =97 pCiIL (50%/) =0.23 + 0.77 Sph(500)

600 800 1000 Distance (mn)

1200

1400

0

200

400

600 800 Distance (in)

1000

1200

1400

21.8 -X X

1.6 1.4 -X 1.2 -X

X

X

X

X

0.8

X

0.6 0.4 0 2

(5) cutoff = 2700 pC ilL(849/)i y(h) = 0.4 + 0.6 Sph(150)

00

Figure C.3.

200

400

600 800 Distance (in)

1000

1200

1400

Indicator Variograms and Models of the FY 2001 Technetium-99 Data in Local Grid 2. Experimental variogram values designated by X, with the models fit to the data denoted by olid black lines.

C.3

155000-

Grid

145000-

o.

2Tc-99

p~ilL

4500

+

150

++

50

0

666000

565000

676000

585000

696000

Easting (in) Figure CA4

Median of Simulations of FY 2001 Technetium-99 Concentrations for Grids I and 2

C.4

'

137500

Tc-99 pQi/L

135040

~665O~

567OO 6~Of

~

E9flO

900O

Eastig (in

Ara.Cnouso0h nube of time th f

th cetroaswthntesbae

5633051380

5665056 00

566300

13800

C.5ig m

5950

600

Table C.2.

Statistics of Centers of Mass of Individual Simulations of FY 2001 Technetium-99 Calculated for a Depth of 5 m for the Sub-Area of Grid 1 (200 West Area)

Coordinate

j

(in)

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5 th Percentile 2.5'h Percentile Confidence Level of Mean (95.0%)

I

Sub-Area asting

567987.9 15.2 567950.0 263.2 -0.29 0.40 1350.0 567371.9 568721.8 300 568570.4 567564.6 29.9

C.6

Northing 134825.7 8.7 134826.9 151.2 -0.14 -0.07 818.5 134398.8 135217.3 300 135117.1 134515.1 17.2

I

West Area

_____200

137500-

+

4;~

+

0

+

~.

21

.

. - ...

S136500-

134600

ED

V +

05

U Pond4 0.4

133500565500

566600

669600

568600

567500

570500

Easting (in)

Figure C.6.

Table C.3.

Probability of Exceeding 900 pCi!L Based on Simulations of FY 2001 Technetium-99 in Grid 1 (200 West Area) Area Exceeding 900 pCi/L for FY 2001 Technetium-99 for Each Simulation within Sub-Area of Grid 1 (200 West Area)

J

Area (kin2) Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5 th Percentile 2 .5 t Percentile Confidence Level of Mean (95.0%)

C.7

Sub-Area

Grid I

0.71 0.01 0.67 0.20 0.16 0.69 1.07 0.33 1.40 300 1.14 0.41 0.02

2.71 0.05 2.55 0.79 0.31 0.74 4.05 1.16 5.21 300 4.57 1.44 0.09

mean~ 3.9( a1111111o20( V14 col10 f fV1V0052 mMlO 141 9 97,0Ocen150 9.90 oo 'Se4.90 0 110111 37

0

moo, 790 Sidde 406 11010 o 05 2 ma10mu,1 27 90 97 9610.011101 1066 iopoo, o30I,1 927 m1edian (172

0 120

2~ pecnil

41,

t00

01

0

, , a1io

1

110

1

uOs~oe

,l1'1t10 o' 0414

00-lwn

103a,1

210

'1.1

00

0110. 11001119

20014300 mon 15 02 SW de, 605 COel of sal 0.52 00111M 54 20 (pecemoe 39a32

NU01100at

41122

117(1oo'C6vlio 2140

12..975

'od~ 10.06 io011 Q011'51 709 2 S .10,11we, 462,

O'ON

median10 1344 0 (20 2 5 96,011011 6 12 011/ was.l1

01W0

100

2, 2

"1,

't0 01,v (10 ooef6 of aeO0(2 0121M

1

0

200

0

400

10 I0

2100

Y)0

41)0

0

Figure C.7.

Histograms of Total Activity in Simulations of FY 2001 Technetium-99 within SubArea of Grid 1 (200 West Area), Four Thickness Assumptions

Table C.4.

Statistics of Total Activity of Simulations of FY 2001 Technetium-99 within Sub-Area of Grid 1 (200 West Area), Four Thickness Assumptions Mass (Ci) in Depth

M~ean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5 In Percentile 2.5tIh Percentile Confidence Level of Mean (95.0%n)

5Sm 3.95 0.12 3.37 2.07 4.74 1.86 13.57 1.21 14.79 300 9.83 1.57 0.23

C.8

loin 7.80 0.23 6.72 4.06 4.49 1.84 25.57 2.38 27.95 300 19.66 1 3.10 0.46

[

5m 11.66 0.35 10.08 6.06 4.41 1.83 37.57 3.55 41.12 300 29.49 4.62 0.69

20 m 15.52 0.47 13.44 8.06 4.38 1.83 49.57 4.71 54.28 300 39.32 6.12 0.92

/

Tc-99

pCi/

. . . . . . . . . . . .

50 0 .... . ....0

56000...

.7000

.7200.7400.5600

.. . . .. E stn (in). ... ~~ . Figure...... C..Mdino.Smlte.Y201Tcheim99Cnenrton.nGrd2(20Es Area...Plume) .otur.fth.ube.ftie.ha.hecnero .as. ihi.h sub-reaithn ccured cels f anupsaledgri areshon.wih.te.avrag cetesofmsssow.y.lu.ta.n.h.sbara

......C.....

.9

Table C.5.

Coordinates for Sub-Area Boundary for Grid 2 (200 East Area) of FY 2001 Technetium-99 Basting (in) 571450 573143 573780 574149 574400 574400 573913 573706 573632 573617 573558 573499 573483 573364 573379 573217 573202 573350 573350 573215 573215 573676 573706 573795 573795 573928 573987 574400 574400 571450 571450

[Northing (mn) 141650 141650 141258 141271 141212 139984 139954 139790 139598 139480 139495 139450 139214 139139 139050 139050 138605 138546 138428 138413 137820 137820 137953 137953 137850 137835 137510 137510 136900 136900 141650

C. 10

Table C.6.

Statistics of Centers of Mass of Individual Simulations of FY 2001 Technetium-99 Calculated for a Depth of 5 m for the Sub-Area of Grid 2 (200 East Area Plume)

Coordinate

Sub-Area Easting Northing 572769.0 139527.1 11.3 15.9 572756.5 139521.3 226.9 318.7 -0.12 0.17 0.44 0.26 1198.3 1930.8 572294.6 138627.4 573492.9 140558.1 400 400 573289.7 140200.6 572373.2 138968.8 22.3 31.3

(in)

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5 h Percentile 2 .5 th Percentile Confidence Level of Mean (95.0%o)

C.1 I

144000-

I ... ... ...... .... ...0

.9.

. . . .. . . . . . ... .... .... ... ...0... .......

..... 000

.

0.5

Ea tn.. .m...

4000..... ...

Figure..... C...roabliyofExeein.90p./LBaedonSmuaton.o.F. in Grid... ..... 2.(200.EastArea.Plume

... ~~ ~ ~ ~ C 12.

. .. . .I... . .

000.

00.Tchetum9

Table C.7.

Area Exceeding 900 pCi/L for FY 2001 Technetium-99 for Each Simulation within Sub-Area of Grid 2 (200 East Area Plume) Area (kin 2 )

Sub-Area

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97.5'h Percentile

2.bPercentile Confidence Level of Mean (95.0%)

C. 13

Grid 2

3.89 0.05 3.89 1.06 -0.21 0.07 5.26 1.34 6.60 400 6.17

10.59 0.16 10.53 3.18 0.05 0.41 18.99 3.27 22.25 400 17.24

1.81

5.09

0.10

0.31

'

124~2211

37 222. 080

3 2

Q143

7

~7244

402 3r

We 4211

~272

f1042"

341

6 E

122..

'22142

21

2042 424K

H73stograms2

22 (2001

47I12ola

3233.

ofTtlAtviyi

Area1 Gr3

2 77 7

2

2'2021244

4

121n42

Y'1A141 ",41 Figure112

C'-

12 444 122

k

VtO402!77

141 2^122O

2

3 273 B 73

C

"O_2

'20 14 4

2

23 rt

S13214*2

042

1222

22223

1'4

22222321

12:2112412

21)

12

144

21

12712

iuatoso4Y2013cntu

ihnSb

East4 4441f AraPum)7ouhcnesAsupin

Mean Meia

12.70

22.23

11.79211

2074

Minmum2.7

04

2.

Maiu

97.5hPrcetil

TbeCon8.dStatistics of Toal Activi%)

.2.4

20.533 27.8

77 14 3 31114.20

.3.469

40.0

7,

26.4

46.4

4

01.4

652

of Siuain of1Y.001 Tec.40u9

of~~~~~~~~~C atAe Grd2(0 lm),Fu4hcns

supin

12.2

785

wihi.Sb-re

Appcndix D Figures and Data Tables for FY 1992 Technetium-99

Appcndix D Figures and Data Tables for FY 1992 Technetium-99

0)

500

Grdno tX 0X

105000- Gre

Unit

Core3anRnodgae

I4

555000~~

no

X

570

6500

Eastn +.1 ~~ Subet of, F019 eheim Figure~~ FY~~~ 192Wte al

5000550 (in)

aaadSbrpFrainUisa

+.+

h

1.4X X

1.2 -X

0.8 -XX

>~ X

S0.6 0.4X 0.2 -e>

(a) y(h) = 0.13 + 0.3 Sph(800) + 0.57 Sph(2600) 0

1000

2000

3000

Distance

4000

(in)

1.61.4 1.2 X

X

0.6 0.4 0.2 0.2 r 0

(b),y(h) = 0.13 + 0.87 Sph(230) 500

1000 Distance (in)

1500

2000

1.8

1.6 -x 1.4-

X

X

X

1.2 -X

0.40.2 (c) y(h) 0

Figure D.2.

=0.22

1000

+ 0.28 Sph(1 200) + 0.5 Sph(2500)

2000 Distance

3000

4000

(mn)

Variograms and Models of Normal Scores of the FY 1992 Technetium-99 Data in Local Grid 1 (a), Grid 2 (b) and Grid 3 (c). Experimental variogram values designated by X, with the models fit to the data denoted by solid black lines.

D.2

155000Grid no. 2

++

145000.......... .......... ........... .......... ........... ..........

Grid no. 3 ....

Tc-99 pCi/L

....... ...... ...... 4500

136000- .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... ..........

90 0

.....

...

. ..................... ...r.....77... .I... ... ....... ............. ..................... 7

Z 125000-

450

........... ........... ........... ............ ............ ............. ........... ........... .......... ............ .... .... .. ... ... ... ... ... ... .. .... ....... . ..... . ....... ................... ................... ...........I ....... .................. ................. ................... .... ............ .................. ... ............ ................. ...... .... ............ ............ ........... ........... .......... .......... ..........

115000-

150

50

go 106000-

555000

565000

575000

585000

595000

Easting (m) Figure D.3.

Median of Simulations of FY 1992 Technetium-99 Concentrations for Grids 1, 2, and 3

D.3

137500Tc-99

pCi/L

1365004500

900 1350

150

134500

50 133500 565500

566500

0 567500

568500

569500

570500

Easting (in)

Figure D.4.

Table DA1.

Median of Simulated FY 1992 Technetium-99 Concentrations in Grid 1 (200 West Area). Contours of the number of times that the center of mass within the sub-area occurred within cells of an upscaled grid are shown with the average centers of mass shown by blue star in the sub-area. Coordinates for Sub-Area Boundary for Grid 1 (200 West Area) of FY 1992 Technetium-99 Easting (in) 566300 569450 569450 566300 566300

JNorthing (in) 133800 133800 135750 135750 13380

DA4

Table D.2.

Statistics of Centers of Mass of Individual Simulations of FY 1992 Technetium-99 Calculated for a Depth of 5 m for the Sub-Area of Grid 1 (200 West Area)

I Coordinate (in) Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5 th Percentile 2 .5 'b Percentile Confidence Level of Mean

Sub-Area

Easting 568227.8 12.8 568231.1 270.9 -0.46 -0.10 1361.2 567534.6 568895.8 450 568723.9 567689.8 25.1

(95.0%o)

D.5

J~Northing 134862.4 8.4 134854.6 179.0 -0.49 -0.08 870.2 134394.6 135264.8 450 135191 .0 134515.2 16.6

West Area

________________200

137500-

136500-

09 S135500-.

0.7

*

{0

134500-.

UPond

~

ED

+

133500 565500

+

+I0.4

566500

567500

558500

Easting

569'500

570'50 0

(in)

Figure D.5.

Probability of Exceeding 900 pCi/L Based on Simulations of FY 1992 Technetium-99 in Grid 1 (200 West Area)

Table D.3.

Area Exceeding 900 pCi/L for FY 1992 Technetium-99 for Each Simulation within Sub-Area of Grid 1 (200 West Area) Area (kM2)

Sub-Area 1.01 0.02 0.95 0.39 -0.25 0.56 1.86 0.27 2.13 450 1.92 0.41 0.04

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5th Percentile 2.5'h Percentile Confidence Level of Mean (95.0%)

D.6

Grid 1 6.55 0.14 5.89 2.92 2.02 1.19 18.28 1.55 19.82 450 13.67 2.64 0.27

I

14201001W. D~ata 400

N,,11bw of Data 40

576

2.47 C '7V4 . 0,60 mmitsun 21 50 0' 0 eoel:!e 14 04

0121

~~~~~~~

.

,sunmm 115Ie

97 0 ve

Moc045 4.89 1046r 40-6 312' 0.00 00p0ec1416

106771

000

019t)0711~

1

0

010

t)71111

10 11 .90 674 c"~ 702 01111Of10410,60

0120.

mc d

0

it0t

'0404

mas C201: 1

Mass(we 04 1

01n

141111011' f D416 4513

N~r,,00oof Datla 40

114 464 Coe,1 C!s4

1Q0N13 000 1141711764 32 0105eoo 4A 96 i'wcua"6 23 28 10ecill

0000

of qaoo 2 51 ,,0

1001 60 3 346

4

0 f)

D 120

ftd1

43 11 29 72

Sidd 14 14 ofv4 0 009 00333 97051114117004 6063 40061'q447716 01 25 trmdda 2027 1011174a41 _06e. 1327 205 vercenhie 600 11)l141 3 71 Cost

11ax'maO

i5 14

9.92 12

71710112 "3

004

014

C 00

110

0

_____________________________________

111

'f Y.._s fco',

01

__________________

O''.

66 0

(t 1

10

0

j

00

30 0

401 0

' 1

60 'q

700

60C

Mass, 11ons) 20m

Figure D.6.

Histograms of Total Activity in Simulations of FY 1992 Technetium-99 within the Sub-Area of Grid 1 (200 West Area), Four Thickness Assumptions

Table D.4.

Statistics of Total Activity of Simulations of FY 1992 Technetium-99 within the SubArea of Grid 1 (200 West Area), Four Thickness Assumptions Mass (Ci) in Depth

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5 h Percentile 2.5th Percentile Confidence Level of Mean (95.0%)

5 mSm 5.75 0.16 4.89 3.48 2.34 1.36 20.71 0.79 21.50 450 14.54 1.62 0.32 D.7

l~nin 11.79 0.33 10.01 7.03 2.45 1.37 41.34 1.76 43.11 450 29.59 3.50 0.65

5 17.85 0.50 15.14 10.59 2.51 1.38 61.99 2.74 64.72 450 44.79 5.12 0.98

20 m 23.90 0.67 20.21 14.16 2.54 1.39 82.63 3.71 86.33 450 60.63 6.92 1.3

Tc-99 00 H(pCi/L)

154000 -

100 D

664000~~10

6700

1410000

140000Ara

F600

Siuae4Y195eheim9Cnetain Fiur D.7.00 Media ofe Cotor of0 th ubro iesta h

Figue D7.redisarn

etr

fms

the rimltd The maximu echnetium-99 neactity

1 nGi ihnth rdocre

000080

0ra)

in Grid 2 o(1992 ires)

only 632 pCi/L. No values over the 900 pCi/L DWS were simulated in the grid, so several of the standard metrics do not apply to this grid, including the area above the drinking water standard and the length of the Columbia River shoreline above the drinking water standard.

D.8

Table D.5.

Coordinates for Sub-Area Boundary for Grid 2 (100 Areas) of FY 1992 Technetium-99 Basting (in) 563900 563900 564206 564778 565610 566373 566915 567588 567905 568736 569056 569597 570361 570967 572118 572754 573070 573965 573996 574315 574379

Table D.6.

[Nor-thing (in) ]

1 1

143800 145566 145277 145277 145502 145754 145882 146172 146522 147033 147447 147959 148692 149392 150987 151785 152199 152744 153030 153828 154144

1 1

E asting (in) 574635 575910 577761 578239 579740 579962 579962 579706 579582 579706 580124 580985 581463 582227 581941 582516 582897 583216 583250 563900

Nor-thing (in) 154500 154500 153410 152710 151371 150987 150573 149806 149614 149200 148787 148211 147764 147350 146902 145724 145118 144129 143800 143800

Statistics of the Locations of Centers of Mass for Simulations of IFY 1992 Technetium-99 within Grid 2 (100 Areas) Coordinate (in) Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97.5"'Percentile 2 .5th Percentile Confidence Level (95.0%)

]

asting 573369.1 35.4 573401.6 613.8 -0.14 -0.24 3427.1 571431.2 574858.3 300 574473.9 572179.8 69.7

D.9

Nor-thing 146967.7 21.3 146950.4 369.4 0.07 0.14 2216.2 145937.8 148154.0 300 147716.8 146234.4 42.0

FY92 Tt,9, Grd no.2

N

be&

a

30FY92

Tc.99Grid nog.2N

mean 4 70 ,t, dev 1 20 a021 mamu 860 9705 rcentie 760

rc9Dt

0100I,

0

mean 734M W1 dev 1 70 oo l na' 024 ma-mum 1333 97 5 "u 811811 02 88la8 pe 1 41 840 median 7 12 iower qoant18 601 2 511"'plorWe 463 mln $75

0 06.0

80168108411118 548

median 468 ItOer duarl,:e 383 Operueol e 26 -M~nmlm2 20 004

4,

8S

I i2c1 F92 701.99:Grid no2

mMOs1ue

Nute

3oe

a300

11

1210 FY2 Tc-99: Grid no.Z

mean 8986 st0 de. 1 98 £081 ofow 022 maxmum 1637 97 5 pero8Shle 13 47 PPIm914111181009 median8 8 72

,11

11)

Nme

wo11

2 5 peoenoe 6 08 min-mum, 476

Table D.7.

0 10 25 220 022 1880, 1524 1t47 1006

2 5 peroeNole 701 minlm 565

1111400

Figure D.8.

fOt

mean Mid deiv c0ef 0f 48 maximum 97 5 percenlile 8Ppe, qu941 median

lAO

Histograms of Total Activity in Simulations of FY 1992 Technetium-99 within Grid 2 (100 Areas), Four Thickness Assumptions Statistics of Total Activity of Simulations of FY 1992 Technetium-99 within Grid 2 (100 Areas), Four Thickness Assumptions Mass (Ci) in Depth

5m 4.70 0.07 4.58 1.21 0.16 0.64 6.35 2.25 8.60 300 7.60

loin 7.34 0.10 7.12 1.73 0.48 0.72 9.58 3.75 13.33 300 11.32

15m 8.96 0.11 8.72 1.98 0.86 0.79 11.61 4.76 16.37 300 13.47

2.5 th Percentile

2.86

4.80

6.05

7.01

Confidence Level of Mean (95.0%)

0.14

0.20

0.23

0.25

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97.5"'Percentile

D. 10

20mi 10.25 0.13 10.06 2.21 1.05 0.81 13.30 5.55 18.85 300 15.24

Tc-99 pOIL

..... .... ..

-

14200-

.... .. ... .... ...4

. . . . . . .. . . . . .

.

.

.

.

.

.

.

.

.

.

.

900 50.

.

. . . . . . . . . . . . .... . .... ....... ....

4500

. .... .5

0

... .. ... ... . ..... .... ... ....... .50 900

... 00....00.57000...000.7600

.. E.s..ng.(in) Figure.. D..MeinofSmuae.F.92.ehntu...onetatosinGid3(00.s ArePlme..Cnouso.tenubroftme.ht.h.cne.o.as.ihi su-ae ocrrdwihi elsofa..sc...rd.r.sow.it.heaerg cetes f as sow.b.rd.ta.i.te.ubara

D.150

h

Table D.8.

Coordinates for Sub-Area Boundary for Grid 3 (200 East Area) of FY 1992 Technetium-99 Easting (in) 571450 574400 574400 574231 573860 573645 573645 573698 573839 573942 574400 574400 574238 574202 574142 574105 573713 573282 573098 571450 571450

Table D.9.

[Northing (in) 136900 136900 137731 137856 138723 139197 139612 139739 139834 139879 139864 141205 141212 141256 141256 141205 141205 141568 141650 141650 136900

Statistics of Centers of Mass of Individual Simulations of FY 1992 Technetium-99 Calculated for a Depth of 5 m for Sub-Area of Grid 3 (200 East Area Plume)

T Coordinate (in)

Sub-Area

Easting 572723.3 10.0 572721.9 243.9 0.45 0.18 1592.2 572059.9 573652.1 600 573217.1 572225.3 19.6

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5 th Percentile 2.5~Percentile Confidence Level of Mean (95.0%)

D. 12

[

Northing 139632.1 14.4 139628.1 351.6 -0.59 -0.01 1732.8 138739.3 140472.1 600 140310.3 138948.4 28.2

144000.....

.......

....... ...... .... .......... ........... ........... .......... ....... ...

142000- .. :...... .............. ........ ... ........ ......... ...... .......... ..... .. . . . .. . . ................ .. ............. ............... ...

........... . .. .................. .................. ......... . ........... .................... ........... ....... ......... ... ............. .......... ...................

................. ....................... .................. ..... ..................... ........... . . . .............. ....................... ............. ......... .. .. ....... ..... ...... ..... . .. .. ... . ............... .......... ....... ...... . .......... . ............... ... ... . . .............. .... .. .. ............. ....................... .... ........................

........... ............. .......

0 .9

...... ...

............. ........ ..................... .................... ..................... .......... tf Z

0.7

140000........... ............. .. ....... ..........

138000-

BYCr

2 rb s

..

.......... ............. ...... ........ ....... ... . +

0 .5

0.4

136000568000

670000

572000

574000

576000

Easting (m) Figure D.10.

Probability of Exceeding 900 pCi/L Based on Simulations of FY 1992 Technetium-99 in Grid 3 (200 East Area Plume)

D.13

Nu mber of Data mean std. dev. coef, of var maximum 97.5 percentile upper quartile median lower quartile 2.5 percentile

0.160 ......

0.120-

~

008

080minimum

600 1140.1119

1030.2948 0.9037 6276.9551 3802.3860 1508.8831 844.9750 422.4870 60,3550 0.0000

0,040

0.000

...

0.

1000.

2000.

3000.

4000.

Average Length

Figure DAL1

Table D.10.

5000

6000.

(in)

Histogram of the Average Length of Columbia River Shoreline Exceeding 900 pCi/L for FY 1992 Technetium-99 in Grid 3 (200 East Area) Area Exceeding 900 pCi/L for FY 1992 Technetium-99 for Each Simulation within Sub-Area of Grid 3 (200 East Area Plume) Area (kin 2 )

[

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5 'h Percentile 2 .5 'h Percentile Confidence Level of Mean (95.0%)

Sub-Area 1.32 0.02 1.25 0.48 1.50 0.98 3.30 0.36 3.66 600 2.48 0.61 0.04

D. 14

Grid 3 13.30 0.17 12.96 4.18 1.04 0.72 28.18 4.34 32.52 600 22.66 6.86 0.33

1344

N or0

3

131

97

fx3.3$3.3

27

Z

r'r 2 234 1C3-

.4~ 13 3413~$ -!:tna

emaxn, 3 70310ce03e

00,e

f~r'1~A1

st3

"Z

3

of 0a 4

l0ed13, 14 2 5 pe3033

1 30

Table DAL1

330 275

4;

0 13 em,33

3072

No

29 03

13 03

o3 t 0

0(71302

60A

237

23(51P3r1c;3058

4 77

704

04

Figure D.12.

20.37003

004b..

'3

03 23 13 333

o D 0

31 3,orn

33

343" 31 02 1033

1-4

o.~3o~2

1

3

Nvvi3b63o Data416003 1re44 12 02

0101...

43

.3

30

.,

07

3

47

2

-

2033

0

13

Histograms of Total Activity in Simulations of FY 1992 Technetium-99 within the Sub-Area of Grid 3 (200 East Area Plume), Four Thickness Assumptions Statistics of Total Activity of Simulations of FY 1992 Technetium-99 within the SubArea of Grid 3 (200 East Area Plume), Four Thickness Assumptions Mass (Ci) in Depth

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97'h Percentile 2.5'h Percentile Confidence Level of Mean (95.0%)

5m 6.91 0.15 6.16 3.79 4.89 1.71 27.61 1.73 29.34 600 17.07 2.24 0.30

D. 15

J

lOin

12.02 0.29 10.38 7.11 5.37 1.80 54.23 2.75 56.98 600 32.07 1 3.58 0.57

[

5m

20 m

16.67 0.42 14.29 10.31 5.64 1.85 80.34 3.51 83.85 600 45.88 4.76 0.83

20.98 0.55 17.84 13.38 5.89 1.89 105.69 4.10 109.79 600 57.37 5.8 1.07

Appendix E Figures and Data Tables for FY 2001 Iodine-129

Appcndix E Figures and Data Tables for FY 2001 Iodine-129

136000-

0

105000-Gen

:Cas-ri

igl

rvl(nt5

Pupl mesh: Ot-Ci9) r (uni 2p

11600

0005

17b0ssbn55 5600

Blue ~Hafrin)ato ~ ~ unt1 Estn Figure

ree Sbetsh:Gaee m.. of

od

rek2 Data aund ucoiFrainUnt3tth

Watper mehtbers(nt2469

E. I

Y20

1.2

l

0.8 260.60.4 0.2

(a) y(h) = 0.2 + 0.3 Sph(220) + 0.5 Sph(2200) 0

500

1000 1500 Distance

2000

2500

3000

(in)

1.61.4 1.2 -X

0.8 -X 0.6 0.4

-/ O

0.2-YX

(b) y(h) = 0.08 + 0.92 Sph(1500) 011 0

Figure E.2.

500

1000 1500 Distance (in)

2000

2500

Variograms and Models of Normal Scores of the FY 2001 Todine-129 Data in Local Grid 1 (a) and Grid 2 (b). Experimental variogram values designated by X, with the models fit to the data denoted by solid black lines.

E.2

155000

1-129

145000-pOi/L

Gri no.

.... . . .. . .. .. . . ..

.

.

.

. .

.

.

.

.

.

.

. . . ..

..

1:1 ........

0..

. . . . . . . . .0 . . .. ... . . . . .

555005..00

..

57000

56000

I

5900

E..ting..in) Figue ofSimlatons P. Mdia f F 201 Tdin-12 Cocentatins or

E.3

rid 1 nd4

Sb-area no 2 1-129 pQi/L

13800

E

4

0

2

0 566000

567000

566000

569000

570000

571000

572 00

Easting (in)

Figure EA4.

Median of Simulated FY 2001 Iodine-129 Concentrations in Grid 1 (200 West Area). Contours of the number of times that the center of mass within the sub-areas occurred within cells of an upscaled grid are shown with the average centers of mass shown by black star in the sub-areas.

Table E.1.

Coordinates for Sub-Area Boundaries for Grid 1 (200 West Area) of FY 2001 Iodine-129 Sub-Area 1I Easting (in) 566000 572300 572300 572146 572146 571261 571261 571113 571102 570963 570952 566000 566000

Northing (in) 132800 132800 135121 135153 135557 136357 136624 136655 137061 137124 137348 1 134700 132800

Sub-Area 2

jEasting (in) 566000 570952 570791 570813 570674 570663 570515 570536 570365 570365 570217 570195 566000 566000

EA4

Not-thing (in) 134700 137348 137400 137667 137699 138104 138167 138424 138456 138573 138615 138700 1 138700 134700

Table E.2.

Statistics of Centers of Mass of Individual Simulations of FY 2001 Iodine-129 Calculated for a Depth of 5 m for the Sub-Areas of Grid 1 (200 West Area)

1 Coordinate (in) Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9. Percentile Y 5 thPercentile

2

Confidence Level of Mean (95.0%)

Sub-Area I

-Easting_LNorthing 569213.8 134344.3 16.2 13.4 569181.8 134340.0 281.2 232.5 0.85 -0.10 0.50 0.30 1812.6 1177.7 568534.8 133824.8 570347.4 135002.5 300 300 569877.8 134866.2 568689.5 133925.9 1 3 1.9 26.4

E.5

Sub-Area 2 Easting 568037.5 27.9 567993.1 483.3 0.27 0.43 2640.7 566905.4 569546.1 300 569178.5 567171.7 54.9

Northing 137220.8 16.4 137222.7 284.6 -0.52 -0.03 1453.4 136451.6 137905.0 300 137716.8 136684.1 32.3

3L~bhe 'ru

2

138000-* 200 West Area.

137000-

0.9

+

0

133000

566000

567000

568000

569000

570000

571000

572000

Areas of Grid 1 (200 West Area) Area (kin2) Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5 " Percentile 2.5"' Percentile Confidence Level of Mean (95.0%/)

[

1

Sub-Area I 8.08 0.08 8.06 1.31 0.22 0.29 7.29 4.74 12.03 300 10.85 5.76 0.15

E.6

Sub-Area 2 2.32 0.04 2.16 0.70 1.14 1.01 3.82 1.16 4.98 300 3.96 1.29 0.08

Grid 1 11.17 0.10 11.02 1.72 -0.10 0.17 8.76 7.13 15.89 300 14.87 7.87 0.20

FY01 4.129.2OOWf4EDOXP1.

F-Y0l1-129, 2$OWREDOX P$*01

2122

rono

5(15

pe,-s noe8o

02

ON1

0on 151

050 3foo .5.5 5173 0so2 0141

51ef dfoa, 535 0o4ron 332 9? .5 p' d. S 283 0o144

5572

2550042 C,222

Mass

FY01 1-129: 20OWRE OX 01-4

0~oe It,

Nos,4 dl D.

212

2Wo5

QIOU

335 0144 219

0 122,

fl0

FY0114-I212004WREDOX Pf..

fon

.1e _for5 361

-fs of

51140401f5442 5 425 ."!4*102414

0 08

.pp.,a~~ 54 0

122112 55241402541

024101

92

5 poerenle 5152 2572

20452

sCU Oa

f 0.o 132 -a~o 5 283

o

~,

15m

o

05342 244 0

_2535

05oool 122 N, 0on 2

O.

Figure E.6.

Histograms of Total Activity in Simulations of FY 2001 Iodine-129 within Sub-Area 1 of Grid 1 (200 West Area), Four Thickness Assumptions

Table E.4.

Statistics of Total Activity of Simulations of FY 2001 Iodine-129 within Sub-Area 1 of Grid 1 (200 West Area), Four Thickness Assumptions Mass (Ci) in Depth

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97.51t Percentile 2.5 t Percentile Confidence Level of Mean (95.0%)

[

Sm 0.0788 0.0016 0.0744 0.0280 0.6636 0.8307 0.1475 0.0255 0.1729 300 0.1457 0.0376 0.0032

E.7

loin 0.1506 0.003 1 0.1443 0.0541 0.7715 0.8590 0.2832 0.0492 0.3324 300 0.2828 1 0.0700 0.0061

-

15m 0.2187 0.0046 0.2096 0.0790 0.8586 0.8854 0.4201 0.0718 0.4920 300 0.4135 0.1022 0.0090

20 m 0.2833 0.0059 0.2732 0.1026 0.9137 0.9032 0.5507 0.0935 0.6442 300 0.5446 0.132 0.0117

FY14-20. 2ow rN..-r

FY01 1-129.200W1fItnt 0

Vddv0010 0 0W6 0127?

W0074

A04oo 04

O

Op11l.n000,-

100

01'

0037

noomm-r

lo111Lr1

151

nnr Orn0036

~ 100

g

o

i,

0107

00

OOOVE11U110 0

010

0.C0-7

0700

G00

0010O0

020

03

0

L040

00000

0 OOZ

03MIX

001

C010

FW 1 -129,20OW TPI~el

FY01 P.129. 200WTPI..r

-f 97 5 00 7~~~~~~~qwd

o

v20

0574 21

0 050

01UK

101411 20 10,elwlt

004C 01100411 2 5 011011e 1 0014

01 0

02

ao rn0.23D3 07 5pen-fif: 5 122

rfoo,0 184 r0 00M

Olllmtmll

1111110011

O

0'I120

0100

0 2C0

000

013

010 I

0.20

131 1014 0 014

020

Figure E.7.

Histograms of Total Activity in Simulations of FY 2001 Iodine-129 within Sub-Area 2 of Grid 1 (200 West Area), Four Thickness Assumptions

Table E.5.

Statistics of Total Activity of Simulations of FY 2001 Iodine-129 within Sub-Area 2 of Grid 1 (200 West Area), Four Thickness Assumptions Mass (Ci) in Depth

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97.5"' Percentile 2. I Percentile Confidence Level of Mean (95.0%)

5m 0.0126 0.0004 0.0106 0.0074 9.5127 2.3911 0.0601 0.0036 0.0637 300 0.03 19 0.0046 0.0008

E.8

lOin 0.0252 0.0008 0.0211 0.0 147 9.5111 2.3902 0.1201 0.0072 0.1272 300 0.0637 0.0093 0.0017

1im 0.0373 0.0012 0.0312 0.02 14 9.0143 2.3233 0.1734 0.0107 0.1841 300 0.0922 0.0 136 0.004

20mi 0.0483 0.0016 0.0407 0.0271 8.1742 2.2051 0.2162 0.0140 0.2302 300 0.1222 0.0179 003

1-129 pQi/L 140000-

0

1

0.5

0 570000

Figure E.8.

'575000

580000

585000

590000

595000

Median of Simulated FY 2001 Iodine-129 Concentrations in Grid 2 (200 East Area Plumes). Contours of the number of times that the center of mass within the subareas occurred within cells of an upscaled grid are shown with the average centers of mass shown by black stars in the sub-areas.

E.9

Table E.6.

Coordinates for Sub-Area Boundaries for Grid 2 (200 East Area) of FY 2001 Iodine-129 ___________Sub-Area

Easting (in) 572700 573684 573684 573779 573793 573970 573970 5842 574887 575601 575651 575920 575920 576316 576664 576714 576858 577098 577130 577270 577288 577396 577396 576750 576555 576510 576542 576960 576960 577112 577112 577256 577288 578287 578350 579033 579078 579526 1 579558 L 579811

Northing (mn) 137050 137815 137971 137971 137812 137826 137540 137540 137365 137365 137207 137207 137781 137826 137826 138079 138509 138572 138414 138427 138287 138287 137844 137225 137225 137066 136777 136447 135764 135714 135289 135289 135127 135127 135289 135289 135440 135440 135574 135606

I

JEasting

________]Sub-Area

Northing (in) 136063 136890 136953 137351 137415 138427 138477 139128 139332 138984 138730 137984 137161 136130 136257 137017 137889 138699 139571 139900 139900 138920 138129 137365 136637 136176 135511 135000 134652 133539 132554 131744 130903 130302 128100 127747 125950 125950 137050

(mn)

580272 580272 580128 580114 580272 580286 580430 580430 581873 582746 583410 584319 585508 587335 587430 586444 585287 584174 583238 585400 585902 587028 588267 589537 590170 590650 591047 591219 591536 593263 593851 594136 594312 594457 594520 594805 594805 579250 572700

E. 10

]Easting

2 (in)

572700 573684 573225 573225 573535 573838 574145 574154 573495 573495 572915 572558 571455 571382 571604 572364 573485 573562 574195 574200 569000 569000 569822 570085 570505 570505 570205 570205 569930 569930 570546 572700

Northing (in) 137050 137815 137815 138979 139485 139938 139942 141260 141260 141425 141805 142015 142015 142253 142505 142505 142565 142655 142664 144200 144200 142212 141466 141226 140209 139775 139775 139924 139924 139006 138346 137050

Table E.7.

Statistics of Centers of Mass of Individual Simulations of FY 2001 Iodine-129 Calculated for a Depth of 5 m for the Sub-Areas of Grid 2 (200 East Area Plumes)

J

Coordinate (in) Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97.5tb Percentile . th Percentile 2 5 Confidence Level of Mean

(95.0%0)

I

Sub-Area I

Easting 583567.1 31.3 583564.1 700.4 0.06 0.06 4406.1 581204.8 585610.9 500 584952.5 582203.1 61.5

E.11

Northing 132677.4 25.0 132701.4 558.5 -0.06 -0.24 3148.6 130762.6 133911.2 500 133743.2 1131489.9 49.1

Sub-Area 2 Easting

Northing

141075.3 571816.0 13.8 19.3 141082.2 571797.6 309.0 430.9 -0.13 -0.02 0.21 0.02 1768.9 2512.2 139849.6 570957.1 572726.1 142361.7 500 500 141906.6 572458.6 1571233.5 1140212.6 37.9 27.2

140000jb-re

no,."ae6ri.

0

+

0

-

z

.

125000-

570 1000

5751000

1

565000

560 000

Easting

590000

595000

(in)

Figure E.9.

Probability of Exceeding 1 pCiIL Based on Simulations of FY 2001 Iodine-129 in Grid 2 (200 East Area Plumes)

Table E.8.

Area Exceeding 1 pCiIL for FY 2001 Iodine-129 for Each Simulation within SubAreas of Grid 2 (200 East Area Plumes) Area (kin 2)

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5 th Percentile 2 .5 'h Percentile Confidence Level of Mean (95.0%)

]

Sub-Area I 71.30 0.55 71.07 12.36 -0.11 0.11 69.70 37.26 106.96 500 95.46 47.50 1.09

E. 12

Sub-Area 2 10.83 0.10 10.78 2.24 -0.06 -0.08 12.65 3.72 16.37 500 15.41 6.27 0.20

Grid 2 114.32 0.670 113.69 15.56 -0.11 0.12 89.93 73.48 163.41 500 144.13 84.41 1.37

Number of Data mean dev, of var maximum upper quartile, median lower quarlte, minimum

000std, 0.080coef. 0.060

500 7563.85 2701.18 036 16658.7 9505 97 7484,06 5613.05 784.62

C

0040-

0.020-

0,000LLr 0.

4000.

8000. Average Length

Figure E.10.

12000.

16000.

(in)

Histogram of the Average Length of Columbia River Shoreline Exceeding 1 pCi/L for FY 2001 Iodine-129 in Grid 2 (200 East Area Plumes)

-E.13

FY0I1.129,200E P1REX PI-t0

FY0I1 -129.200E PUREXPI-r ooooo~04 0_w

ooo0357 .1d do, 0 091 oef of -~ 0209

011 W,3 00951 oof of 0009 0

On00,

pre~~ 0000 0200 3 19 10 01073' 2' 0111

97

9 50001

090PW 00

0

~

~

~

0009

u99ppe 11 D0417 0.1 0 049 quan10 03 0 0291

3o3003q

2045 poooe

t

0409

it1

5

FY 191297 20CEPUREX Pl.nt N=0109

o

3 04

100

of CDoloS00

0

0 171V

1 2%

, c,

0039110 700

FY01 12t 2009 FOO4EXPI.,0 N-b

.0.91. oo

de031040

soof

0100e1

000

of 9000949

091130,0330 010

709

Ooeoolo09

Total30

G090

2020EstAe)040

6

iultoso

07

10

70

7707,70

Median0001

Table E.9. ar

01

094(9100030 100 03 1200

ihnSbAe 0049yi

Y201Idn-19

hckesAsupin

0.197

Erro

0001000719

0299

44

Mea

Standar

m0 0009

1931031

3330133010. 0itgrm 019

00

j10d033 043

10002

0.36

0.004 0.193

vSatsisoToaAcitySmuation

0.34s

of0512001

0470064

00

057 04885

10.007

0

.599

0odne1269 wihi.Sb-re7

Mkeanes

0.4979

0.3569

0.496

0.6145

Median

0.2931

0.345

0.4885

0.525

0.0863 0.3854 500 0.30 16 1 0.1108 0.004

0.1546 0.7092 500 0.5558 0.2098 0.0080

0.2151 0.9948 500 0.7795 0.2876 0.0111

Minimum Maximum Count 9 7 .5 ' Percentile 2 .5 th Percentile Confidence Level of Mean (95.0%)

E. 14

0.2687 1.2212 500 0.9685 0.360 0.0 138

1o

FYO1P102. 200(NW)

FYOI 1129 290 (NM)N,1( 'W4 0042 'I,) "4 1o 0016 aA ofvao 0375 rna mumh0 103 75soooO 0 C79 upw 0uMle 000 26 -du1 0041 1- 1004110*031 0~oor~ 019

('0

oS1 07Wl41 Od C-0 0 029 -40 .01 r0377 o.n.. 0 *90 5 C~t 42, 006 oo0075 I' 00 4-1k' 1 056 3 Ssorol 0000 s O 0 1 f,

0 10"' 0".",0 s:

00

'0

060

0 040

0020

2000

0000,

1041'

.'S'o "'60

FY01 1-129. 200E (NW)N

10

0(0,

o 1..5

C0.0

100

C01510

FyV11.12t 200E (NW

N

11410109

0100"a

0-1

001'-ma

C"

o

0

,D.._) 0133

10

0 539

p11001

t

0200.

010

030

1

00

14 05

-1 d-1~

G455056

021

0020

.00'

'(

C10 0

11j0 0 Nla

(C-)O

0 216

r,200

0

('10

G02003 020.2

411 Ol

1511

2,,k,

Figure E.12.

Histograms of Total Activity in Simulations of FY 2001 Iodine-129 within Sub-Area 2 of Grid 2 (200 East Area), Four Thickness Assumptions

Table E.10.

Statistics of Total Activity of Simulations of FY 2001 Iodine-129 within Sub-Area 2 of Grid 2 (200 East Area), Four Thickness Assumptions Mass (Ci) in Depth

Mean Standard Error Median Standard Deviation

Kurtosis Skewness Range

Minimum Maximum Count 97.5'h Percentile 2 .5 'h Percentile Confidence Level of Mean (95.0%)

[

lOin

im

im 15

20 m

0.0424 0.0007 0.0405 0.0159 0.4067 0.6301 0.0941

0.0778 0.0013 0.0746 0.0289 0.4503 0.6339 0.1741

0.1076 0.0018 0.1030 0.0393 0.4432 0.6221 0.2378

0.1333 0.0021 0.1281 0.0479 0.4278 0.6116 0.2908

0.0084

0.0155

0.1025

0.1896

0.0214 0.2592

0.3174

500

500

0.0786 0.0176

0.1422 10.0321

0.00 14

0.0025

E.1 5

500 1

0.0266

500

0.1988 0.0445

0.2448 0.0557

0.0034

0.0042

Appendix F Figures and Data Tables for FY 1992 Iodine-129

Appcndix F Figures and Data Tables for FY 1992 Iodine-129

105000-

Gre

: Core-ri

Gre

Basal 99

1350000

0F

grave

Gingol 2Ui

1

5800

5900

0

1.4 XX

1.2

X

X

-0.8 -0.6 0.4 0.2 -

(a) y(h)

Sph(i20) + 0.65 Sph(840)

=0.315

0 0

500

1000 1500 Distance (in)

2000

2500

1.6

X

1.41.2 -X

0.6 0.4 0.2 01 0

Figure F.2.

X (b) y(h) 500

=0.28

Sph(650) + 0.72 Sph(2000)

1000 1500 Distance (in)

2000

2500

Variograms and Models of Normal Scores of the FY 1992 Iodine 129 Data in Local Grid 1 (a) and Grid 2 (b). Experimental variogram values designated by x, with the models fit to the data denoted by solid black lines.

F.2

155000-

Gridno.21-129 pOlL

145000-

8

4

E

.. . . .

2.

.

. . . . . . . . . . .1 . . . . .. . . ..

0.5

......... .II

.. .. . . . . . . . . . . . 555000.5.500..7..00.55000.59500

Fiur

0 ....... . .E..st...g.(in) ... Mdin.f. iultinsof..192.oie...Cocetaton.frGrds1.n 2. ra (l oerta hedikn Ther weeo122o5e000aa-nte10 wate stadar 1 piIL..N. pail.tucuewa.etcedi.hedtafomta arasoth gotaisicl nayisan clclain f isor.mthig etic wr not.performed.

... .. . 3. .

1-129

--ub--jrea InO2

pCi/L

-4

2

133000

05 13100-7-0 564000

566000

568000

5701000

574000

6721000

Easting (in)

Figure FA4.

Table F.1.

Median of Simulated FY 1992 Iodine-129 Concentrations in Grid 1 (200 West Area). Contours of the number of times that the center of mass within the sub-areas occurred within cells of an upscaled grid are shown with the average centers of mass shown by red stars in the sub-areas. Coordinates for Sub-Area Boundaries for Grid 1 (200 West Area) of FY 1992 Todine-129 Sub-Area I Easting (mn) 566000 572300 572300 571950 571356 570850 566000 566000

]Northing

(in)

]Sub-Area 2 J asting ]Northing (in)

132800 132800 134916 135569 136148 137280 134700 132800

566000 570850 570500 570348 570151 566000 566000

F.4

(in)

134700 137280 138209 138514 138700 138700 134700

Table F.2.

Statistics of Centers of Mass of Individual Simulations of FY 1992 Iodine-129 Calculated for a Depth of 5 m for Sub-Areas of Grid 1 (200 West Area)

Coordinate (in) Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5 'h Percentile Percentile 2YTh 5 Confidence Level of Mean (95.0%)

Sub-Area I Basting

JNorthing

569301.4 14.2 569267.6 302.0 0.03 0.38 1736.1 568543.8 570279.9 450 569928.6 568775.8 28.0

F.5

134376.4 13.4 134342.5 283.6 -0.15 0.39 1623.1 133653.2 135276.3 450 1134969.3

139. 26.3

j

Sub-Area 2 asting Northing 568181.8 137278.2 24.8 12.2 568168.3 137287.9 526.9 259.7 0.00 -0.20 0.23 -0.12 3119.4 1541.5 566667.1 136360.4 569786.5 137901.8 450 450 569333.4 137778.9 56673 136778.0 48.8

24.1

139000

+

'%b-ae nD 2 200 West Area 137000-

0.9

*~135000IfI

U Pond 133000

+

SiLbae

0.5

rol

1310001__________________________________ 564000

B56600

568000

570000

Easting

Figure F.5.

Probability of Exceeding

1 pCiIL

0.4

672000

574000

(in)

Based on Simulations of FY 1992 Todine-129 in

Grid 1 (200 West Area)

Table F.3.

Area Exceeding 1 pCiIL for FY 1992 Iodine-129 for Each Simulation within SubAreas of Grid 1 (200 West Area) Area (kin2 )

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum

Count Ih Percentile . h Percentile 2 5 9 7 .5

Confidence Level of Mean (95.0%)

J

Sub-Area]1

Sub-Area 2

7.23 0.07 7.13 1.53 -0.34 0.31 8.50 3.52 12.01 450 10.36 4.68 0.14

2.89 0.05 2.77 1.11 0.38 0.69 5.77 0.73 6.50 450 5.56 1.13 0.10

F.6

1

Grid

1

17.08 0.16 16.99

1

3.48 -0.34 0.15 19.52 8.12 27.63 450 24.13 10.62 0.32

FY 21429, 200WRPEO Plant "00

N0404141 d Dat 400 4444t 0103 00 at,, 0027 CC41oloo, 0430 1441744

44'

200144114

0 121

FYO.l12.

k4)OWREDI2XF04

10S4~(0~0

4 6)0 0119 000.1 0 4 01

04410

0

97

0660 00

0644(,

OnoAL 400 V14 day4 00.f, of41a

114414,410

3

00 00

0,040

047 Mass Oulo

0120

.1()

070

0.

40

FY024-12. 2IOW REOOXPlant Nv 4t d 0

01&0

450 0al 3

e4 o1o d., 4

4

044

~

97 0 44144410 0349 4000' 410 01 01101 0004 1

CKo10

rn

00ta 4 04%"

0-e0 p--0111 0400 '004 41,111. 0 7 r'1404 03 00'161440

0080

1204 5

-1o

03

13 Ioo'

FY012 129:200W REDOX Ptant

0uppe

7.10

051

aN

104

01o

0so10

Figure F.6.

Histograms of Total Activity in Simulations of FY 1992 Iodine-129 within Sub-Area 1 of Grid 1 (200 West Area), Four Thickness Assumptions

Table F.4.

Statistics of Total Activity of Simulations of FY 1992 Todine-129 within Sub-Area 1 of Grid 1 (200 West Area), Four Thickness Assumptions Mass (Ci) in Depth

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5 'hPercentile 2.5'h Percentile1 Confidence Level of Mean (95.0%)

5m 0.0633 0.00 13 0.0584 0.0272 0.6970 0.9262 0.1434 0.0 186 0.1620 450 0.1277 0.0253 0.0025

F.7

]

lOin 0.1 190 0.0024 0.1092 0.0511 0.6817 0.9266 0.2610 0.0376 0.2986 450 0.24 19 0.0484 0.0047

15m 0.1708 0.0035 0.1574 0.0732 0.6776 0.9253 0.3754 0.0545 0.4299 450 0.3489 0.0690 0.0068

20 m 0.2195 0.0044 0.2029 0.0941 0.6956 0.9273 0.4814 0.0700 0.5514 450 0.4529 0.0877 0.0087~

FY92 4-129:200W TPliant

FY92 I-

Nwnbw0 d5 Data 450

OO lo

TJIaMt

,fDa

0

Va 0010 * 0010 A vat 074015

0000

0 -f

0o,*n 006 ans 0040 Z14144 0 013srsx Iw q504150 000 205100004e 000

ls0

07 Pp,

0100

40

00C30 0 0000 va 0745

11414 o

ma mor 0?, aorno q-d

017 W0

o.15 0500mxt-

007s 0010 0000

IX

000

00

021

D040

00110

0 0&,

0 100

010

~~-1220WFo

FY92 5-129:20OWT

Ta,0.040 1 0-s 0030 sal sf v., 0744

.10

0000

0tk

010

g

00001n

000f "0

11551 0040 9101 W,, 0040 o~s0730 551155 0,11 40

000

SISO~~nS

rsssso 003 ,-5110115j0100, ua-05mf5000 Ct'

0 15C

G00

002W0.,

0 01 ems 0000

0C010

0 100

Q

~01 ~

00001

00201

000 'IO

0100

0000'

M-;Cut 0516m

M-s

005 .

V300 's,

Figure F.7.

Histograms of Total Activity in Simulations of FY 1992 Iodine-129 within Sub-Area 2 of Grid 1 (200 West Area), Four Thickness Assumptions

Table F.5.

Statistics of Total Activity of Simulations of FY 1992 Iodine-129 within Sub-Area 2 of Grid 1 (200 West Area), Four Thickness Assumptions Mass (Ci) in Depth

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range

Minimum Maximum

Count 9."Percentile I TT Percentile 5 Confidence Level of Mean (95.0%) 2

5m

j

lOin

15 m

20 m

0.0160 0.0006 0.0127

0.0321 0.0011

0.0478 0.0017

0.0255

0.0381

0.0619 0.0022 0.0499

0.0120 7.0938 2.2204 0.0845 0.0021 0.0866

0.0239 7.0938 2.2204 0.1690 0.0042 0.1732 450 0.0959

0.0356 7.1390 2.2226 0.2531 0.0063 0.2593

0.0458 7.2792 2.2300 0.3344 0.0081 0.3425

450 0.1423

450 0.1794

0.0119 0.0033

10.0158 0.0042

450 0.0479 0.0040 0.00 1 1

F.8

0.0080 0.0022

1

145000

... ..... ... ..... ...... ... .. ...

........... .. ......... ........... .. ........... .............. ... ........ ............ ............ ............ ........... ...........

.....

1400OD-

-a t"e a n o.

135000-

1-129 pOIL

D 73 +

4 E

130000-

2 .......... ............ ........ . .. ............... 12 500 0- ................. ................... -................... 11............... ................... ............. ............I ................... ................... ................ ................... -................... .................. ................... ................... ................... ..................... .......... ........ .................... ................... ...I ............. .. ................... ............. ...... ................... ......... ..... .............. .... ...... ..... .............. ............. ............ ............... ............. ... ..... .. ......I ..... .. ......... .... .......... ............... .................... .............. ........ ............ 12 000 0- ............... ........... ... ......... .. . ...... ..... ........... ...... ......... ............ ...... ........... .. .................. .......... .... ............. ..... .. .............. ....... .......... . ............... .............. . ..........I ~ + ...... ............... ...... ..........I .... ............... .............. ............ .... .... .. .............. .... .... .................... ................. ............ ... ... .......... ......... ... ........ .. .... .............. ............. .... ......... .............. .............. ............. .............. I.. ........ .............. 115000 570000

575000

580000

585000

j

0.5

0

590000

595000

Easting (m) Figure F.8.

Median of Simulated FY 2001 Iodine-129 Concentrations in Grid 2 (200 East Area Plumes). Contours of the number of times that the center of mass within the subarea occurred within cells of an upscaled grid are shown with the average centers of mass shown by red stars in the sub-areas.

F.9

Table F.6.

Coordinates for Sub-Area Boundaries for Grid 2 (200 East Area) of FY 1992 Iodine-129

Easting (in) 572700 574100 574114 574285 574417 574665 575466 575565 575542 575163 574733 575113 575556 575764 1 576103 576424 576650 576790 576781 578192 578464 578870 579513 1 579553 579702 579861 580042 580033 579870 579531 L

581865

Sub-Area Nrthing (in) N 137050 138100 138075 137776 137704 137776 137383 137415 137546 137835 138174 138256 137894 137794 137794 137876 138057 138256 138536 138744 138560 138560 138183 137595 137446 137446 137654 138183 138563 1 138975

1

[Easting (in) JNorthing (in)

139345

582746 583410 584319 585508 587335 587430 586444 585287 584174 583238 585400 585902 587028 588267 589537 590170 590650 591047 591219 591536 593263 593851 594136 594312 594457 594520 594805 594805 579250 572700

138984 138730 137984 137161 136130 136257 137017 137889 138699 139571 139900 139900 138920 138129 137365 136637 136176 135511 135000 134652 133539 132554 131744 130903 130302 128100 127747 125950 125950 137050

_____________________________

F.10

Sub-Area 2 Northing (in) 572700 137050 574100 138100 573955 138563 573675 139155 573634 139413 573698 139712 573946 139883 139983 574145 574136 141200 573698 141200 573164 141602 572536 142031 572332 142072 571627 141995 142013 571505 571387 142235 571753 142452 142565 573512 574186 142551 574200 144200 144200 569000 569000 142162 569628 141715 570279 140706 140105 570388 139929 570125 140037 569936 569936 139006 570537 138378 137050 572700 1

jEasting (mn)

Table F.7.

Statistics of Centers of Mass of Individual Simulations of FY 1992 Iodine-129 Calculated for a Depth of 5 m for Sub-Areas of Grid 2 (200 East Area Plumes)

CoriatBm Men583217.2 Standard Error Mein583138.7 Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5 1h Percentile 25EPercentile Confidence Level of Mean (95.0%)

Sub-Area 1I asting

J~Northing

44.3 827.8 0.67 0.44 5607.9 581105.2 586713.2 350 585038.8 581731.7 87.0

F.1I1

132781.1 35.3 132846.0 660.5 -0.35 -0.19 3446.4 130923.3 134369.7 350 134011.8 1131396.6 69.4

j

Sub-Area 2 asting Northing 571787.5 21.5 571801.2 403.0 -0.16 -0.16 2155.3 570606.1 572761.4 350 572543.3 570994.9 42.4

140646.9 34.6 140589.7 647.9 -0.21 0.23 3596.3 138927.2 142523.5 350 141989.9 139469.1 68.1

+

145000-

Sub-area no.2 .............. . . . . . . .. . ............ ............. ............ ............ .......... ........... ...... ...

... ... 1400--

sub-a[ea 110.1

7ij

135000-

+ E L

130000-

+

+ +

0.7

........... .......... ........... ............ ............ ............... ............... ................ ................ ............ ............. ..... 125000- :" ''' ................. .............. - ........... .......... ................... ................... .................... .................... ..................... .................... ..................... ..................... ...................... ...I .................. ...................... ....................... ....... ........ ... .. ........................ ........................

120000-

115000

0 .5

..................... ............... ............ .. ....... .............. ................... ..... . ...... ........... ....................... ... .................. . . . .......... .............................. . .................................... ...................... ............................. ............................... ...................... ............................... .......................... .... ...... .. ........ ................. ............................... .............................. .............................. ..............................

.............................. ........ ..................... .... ......................... ............................. ..................................

0 .4

... . . .......................... ...............I ........ ............. ........... ................................. I ............................. ................................ .............................. .......................... ... ........... .............. .. .......... ............. ....... ... ............. ........... .............

570000

575000

580000

585000

+ 5901000

595000

Easfing (m) Figure F.9.

Probability of Exceeding I pCi/L Based on Simulations of FY 1992 Iodine-129 in Grid 2 (200 East Area Plumes)

F.12

Table F.8.

Area Exceeding 1 pCi/L for FY 1992 Iodine-129 for Each Simulation within SubAreas of Grid 2 (200 East Area Plumes)

[

Area (ki) Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 . 5th Percentile 2 . 5 th Percentile Confidence Level of Mean (95.0%) U.

I

Sub-Area I 88.08 0.65 86.85 12.21 -0.28 0.13 67.47 54.74 122.21 350 111.62 67.15 1.28

1

[

1

7.82 0.19 7.31 3.56 0.07 0.65 17.66 1.29 18.94 350 16.11 2.08 0.37

UVNumber

165.92 1.06 165.11 19.81 -0.23 0.21 119.97 121.58 241.54 350 202.97 131.25 20 of Data 350

std. dev. of var maximum upper quartile median lower quartile

0.80coef.

0,6

Grid 3

Sub-Area 2

0,060-minimum

3296.29 0,29 22753-96 13881.73 11376.98 9234 37 3078.12

C

LL0.040-

0.020-

3000.

8000.

13000,

18000

23000.

Average Length (in)

Figure F.10.

Histogram of the Average Length of Columbia River Shoreline Exceeding 1 pCiIL for FY 1992 Iodine-129 in Grid 2 (200 East Area Plumes)

F. 13

FY921 -12l. 20#7EPUREX Pl.

FY92 129.,M0E PUREX Pf-t

_f at -lo 0'34 rw

PO

rol00,23 9?

M--044

2 102 79a,

0

OK~

1002 WO10

FY202 P010 120., 200E

Man 2 r03 291010

01 10"2 NMfto ofr4Dam 3~c 110c

FY92~~~~~~~~~~ 0EPRX lo

1

129

1210X

191

Y292920

UE

'ar

b 141?

0o,

k-c 2 161

[e'o rooo 2 peoo5

200E

Oi

11029 --

14 :

zooo t'-7

112

, 102

02-7060102 ?29 61

02?4?

40

0

1 00

1 40 Man Iricl

Figure F.11.

2.,

0?

1

1

170 Mlt

22.

21

el 2

Histograms of Total Activity in Simulations of FY 1992 lodine-129 within Sub-Area 1

Table F.9.

19V0 1!111

of Grid 2 (200 East Area), Four Thickness Assumptions

Statistics of Total Activity of Simulations of FY 1992 Iodine-129 within Sub-Area Grid 2 (200 East Area), Four Thickness Assumptions

Mass (Ci) in Depth Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5 "'Percentile 2.5h Percentile Confidence Level of Mean (95.0%)

5Sm 0.4518 0.0057 0.4412 0.1061 0.3687 0.6037 0.6121 0.2570 0.8692 350 0.7033 1 0.2777 0.0112

F. 14

[

lOin 0.8100 0.0100 0.7917 0.1866 0.6081 0.6636 1.1241 0.4520 1.5761 350 1.2459 0.5023 0.0 19

I

15 m 1.1292 0.0139 1.1084 0.2592 0.6523 0.6745 1.5650 0.6157 2.1807 350 1.7181 0.7005 0.0273

]

20m 1.4100 0.0173 1.3718 0.3237 0.6701 0.6759 1.9441 0.7525 2.6966 350 2.1220 0.89 10 0.0340

1

of

921-129 20VE(W

NFY9Ow

5

2 1129; 200E(NM W)

010

1-41 0 053 4011-4 030qda co? C var 094 68 114 n-044 0 4 2.ur 77 O 11.11 0 (I

575

041

0 067 06-7 0442 0 27?

04114C

7u~a q44r711de002,1 22 5 pe-cN.

SOCm,-

5

-.41

___je.

47407.407

'052

LM

e 001

07F

007

.-

'

-

--

.40

374 17.

~.05

70'

'(

('10

FY21192O4 (W.

5 0

('14

Y91201

07

10

200E(NM

-

rv 0 0130 Wd 7e- 07702

cO 01var 070 0120

rralr~r0415

'0-'

lerll 4cerle04

7

010

77 t. w -I:rc1 0 379 ; q PI . 0 107bine 07. ((1314 07 006 1rvmjrvr0774 2

-

W.35 ma,010 114

1141e 044 00

Iner quarl

(74

5 w-,~

0716 075a 7

20&4

0 011

0 0'40

C0 O

Figure F.12.

0'1DD

0 2N. 7

3

0r, C400

C,

061-10

)0

I 01200 27.

1

4

s '< C, Q7

0 6M

0 7vD 0

Histograms of Total Activity in Simulations of FY 1992 Iodine-129 within Sub-Area 2 of Grid 2 (200 East Area), Four Thickness Assumptions

Table F.10.

Statistics of Total Activity of Simulations of FY 1992 Iodine-129 within Sub-Area 2 of Grid 2 (200 East Area), Four Thickness Assumptions

Mass (Ci) in Depth Mean Standard Error Median Standard Deviation

Kurtosis Skewness Range

Minimum Maximum

Count 9 7 .5 1h

Percentile

2 .5 th Percentile

Confidence Level of Mean (95.0%)

5Sm

loin

15m

20 m

0.0534

0.0960

0.1305

0.1595

0.0019 0.0440 0.0364 4.1850 1.6959 0.2373 0.0044 0.2417 350 0.15 14 10.0119 0.0038

0.0036 0.0783 0.0670 4.2031 1.7015 0.4347 0.0071 0.4418 350 0.2781 0.0188 0.0070

0.0049 0.1052 0.0925

0.0061 0.1285 0.1144 4.0238 1.6849 0.7472 0.0110 0.7582 350 0.4614 0.0290 0.0 120

F. 15

4.1345 1.6943 0.6055 0.0091 0.6147 350 0.3790 0.0240 0.0097

Appcndix G Figurcs and Data Tables for FY 2001 Uranium

Appendix G Figures and Data Tables for FY 2001 Uranium

1515000

Gen

Cas-ri GreGri

igl

rvl(nt5 no 3aat9

65013550057011

iniae

tha reial reslt coul no2eotie A 5 -G15

650

nta

550

ra

1.8-X 1.6

1.4-

x

1.2 -

yX

X X

X

~0.6 8X 0.6 0.2-/

(a) y(h) 0

500

1000

=0.15

+ 0.85 Sph(1 300)

1500 2000 Distance (in)

2500

3000

1.6 1.4-

X

1.2 -X

X

1

60.80.6 0.4 0.2

(b) y(h)

011 0

500

1000 Distance

1.6-

Sph (1000) S 1500

(mn)

x

1.41.2 -x

2'0.8 0.6 0.4-/ 0.2

(c) 'Y(h)

=0.3

+ 0.7 S ph(1 80)

0 0

Figure G.2.

100

200 300 Distance (in)

400

500

Variograms and Models of Normal Scores of the FY 2001 Uranium Data in Local Grid 1 (a), Grid 2 (b), and Grid 4 (c). Experimental variogram values designated by X, with the models fit to the data denoted by the solid black lines.

G.2

Grid no.4

166000-

14 500 0-

U (u YQ ........... ........... ........... .......... ..........

....... ...... ...... ...... Gnd

135000-

!E 0 12 50 0 0-

115000-

'Z

.......... .......... ........... ........... ............ ..... ...... ............ ..... ...... ............. ............ ............. ............. ............. ............. ....... .... ..... .......... + .............. .......... ..... .................. . . .. ... .................... ............... . . . . . . . . . . . . . . . ... .................... . ..................... .. ... .. .............. ... ... .. ... ... ... .. .. .. . .. . ... .. . . ........... ... ............ ................. ......... ........ ........ ................... ........ ................ ........ ................... ........ ........ ..... ...... ... ........... ................. ......... ............ . ...... ... ............ ... .......... ...................... ........................... ..... .. ............... .. ...... ..... ...... ...... .. .. ..... ....... . ... .................. ............ ....... ........ ........ ..................... ........... ........ ..... .................. .................. . . . . .............. . . . . . . . . .. . ..... .............. ............. ............. .............. .. ...... ............ ........... ........... ..........

500

150

-

30

15 G rid n o..2

D+ 10 105000-

555000

565000

575000

585000

595000

Easting (m) Figure G.3.

Median of Simulations of FY 2001 Uranium Concentrations for Grids 1, 2, and 4. No spatial structure was detected in the data from the 200 East Area, so the geostatistical analysis and calculation of history matching metrics were not performed.

G.3

U (ug/l)

137000500

150

z

V30

135000

1

5

566500

565500

567500

566500

569500

570500

Easting (in)

Figure G.4.

Median of Simulated FY 2001 Uranium Concentrations in Grid 1 (200 West Area). Contours of the number of times that the center of mass within the sub-areas occurred within cells of an upscaled grid are shown with the average centers of mass shown by pink star in the sub-areas.

Table G.1.

Coordinates for Sub-Area Boundaries for Grid 1 (200 West Area) of FY 2001 Uranium

JSub-Area 2

Sub-Area I Easting (in) 566900 569200 569200 566900 566900

[Northing

(mn)

j

134200 134200 135600 135600 134200

GA4

asting (in) 567250 568000 568000 567250 567250

Northing (in) 136650 136650 1__ 37400 1__ 37400 136650

Table G.2.

Statistics of Centers of Mass of Individual Simulations of FY 2001 Uranium Calculated for a Depth of 5 m for the Sub-Areas of Grid 1 (200 West Area)

Coordinate (in) Men567883.9 StnadErr6.7 Mein567873.2 Standard Deviation Kurtosis Skewness 1Range Minimum Maximum Count 97.5" Percentile 2.5h' Percentile Confidence Level of Mean (95.0%)

Sub-ArealI Basting

[Northing [

171.7 0.24 0.54 1009.9 567470.6 568480.5 650 568258.2 567605.6 13.2

G.5

134892.2 3.9 134888.5 98.7 0.15 0.21 615.3 134606.9 135222.2 650 135096.0 134712.9 7.6

Sub-Area 2 asting Northing

567634.4 2.7 567633.3 69.6 -0.42 0.17 378.0 567454.3 567832.3 650 567777.5 1 567506.9 5.4

137042.3 2.8 137038.4 70.4 -0.24 0.26 424.0 136829.8 137253.8 650 137187.1 136919.2 1 5.4

138000-+

200 West Area

~"'," /b-

ateno.2

1370000.9

T Plant El

SC 136000

~

136000-

+

7 44

EPF+0.8

U Pond +EOP~n

+

134000

+

-0.4 588800

868500

587500

58500

569500

870800

Easting (in)

Figure G.5.

Probability of Exceeding 30 jiglL Based on Simulations of FY 2001 Uranium in Grid 1 (200 West Area)

Table G.3.

Area Exceeding 30 pgf/L for FY 2001 Uranium for Each Simulation within SubAreas of Grid 1 (200 West Area)

Area (kin') Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5 'b Percentile 2 .5 th Percentile Confidence Level of Mean (95.0%)

]

Sub-Area 1 0.834 0.008 0.813 0.2 13 0.316 0.515 1.310 0.358 1.668 650 1.290 0.470 0.016

G.6

Sub-Area 2 0.104 0.002 0.095 0.058 0.340 0.747 0.330 0.010 0.340 650 0.228 0.020 0.004

Grid 1 33.19 0.36 31.70 9.29 0.30 0.65 57.70 13.30 71.00 650 54.25 17.88 0.72

0 &D 01 U: 200W U2Pi-tN.W.1D1

50010

1

.2O

UI~

5

26N. 8204 0439 0

-0

12C0

A6 19

OX,1U1 12414 -8rW d 442 W29 4997 358 77419 254 09 1 99 1 810 k' 9499 141 970 S 90-41k 9V92 7b72

0 12

9V 5

Is

I1c

29 0

029

4&)0

95W

69

1

9'ps.* eo

70

0

FY01 V, 20W U P1.94

42900

1024

40

ols

'9a 4

49179

6662 992 346 2 09 174

1296I2

FY01 U: 200W U PI-tr

~14162999 5A 199

d-13

27946146

719cel.140439

lle9ll2176 633

12c,

29922 ;-.

51641 79 167

70

839 49f9 36214 M A010,402

0441

6

7

9911111 2f3613 1~l71114061177ec11e391

KD

00we

1.

90

101.0

11W,

2100

0,

0ox,

PA- (Kg 1919

f24 g4120n.

Figure G.6.

Histograms of Total Activity in Simulations of FY 2001 Uranium within Sub-Area 1 of Grid 1 (200 West Area), Four Thickness Assumptions

Table G.4.

Statistics of Total Activity of Simulations of FY 2001 Uranium within Sub-Area Grid 1 (200 West Area), Four Thickness Assumptions Mass (kg) in Depth

5Sm

Mean Standard Error Median Standard Deviation

Kurtosis Skewness Range

Minimum Maximum Count 9 7 .5 h Percentile .5T Percentile Confidence Level of Mean

(95.Ooo)

_

loin

1im

20m

209.86 3.61 191.81 92.12 2.63 1.29 678.57 46.90 725.47 650 442.69 87.98

419.72 7.23 383.50 184.24 2.63 1.29 1,357.26 93.79 1,451.05

629.59 10.84 575.19 276.37 2.62 1.29 2,035.96 140.68 2,176.63

2.62 1.29 2,714.65 187.56 2,902.21

650 885.39 175.87

650 1,328.09 263.75

650 1,770.79 351.64

7.09

14.19

21.29

28.38

G.7

839.46 14.45 766.87

368.50

1

of

FYN

U;20OW T pl.rn C,

Nw1154 &4Data 955'

95

Ity0.U" 20OW Tp?.a

Nm

sf Dal., 950 364,, 5*94q le1 34 1 274 sss1 s0s.,1 5947

4,1. ;8474

- 1W5 4 of1 0 8A7

ic

45

.~

,s4s

10K,

299 F35

ssas

FY* U2.20WTP545

0 U

21112

0W

I.

of4

11t 54231 22114~~e

-

-ase

97 5 p.ms,le 120

47645 Q212121 17294 WO59412111

2994191411,173 5W9 -d-1441 41931.

12~~~~~

514

fDt me,,,, 75 509 1144 T35 9 7 offv V9742 al 0947 637 999 259499 qa1. 93__8 1941 97

l1112415,11 72 N49p1o4a

57 7 549

011111

C,59 o259,

Ias 9) 15.U~

1

5~

Figure G.7.

Histograms of Total Mass in Simulations of FY 2001 Uranium within Sub-Area 2 of Grid 1 (200 West Area), Four Thickness Assumptions

Table G.5.

Statistics of Total Mass of Simulations of FY 2001 Uranium within Sub-Area 2 of Grid 1 (200 West Area), Four Thickness Assumptions Mass (kg) in Depth

Men18.47 Standard Error

Sm

[in

Jm

[

20m

0.61

36.95 1.23

55.42 1.84

73.90 2.46

13.89

27.79

41.68

55.58

Standard Deviation

15.65

31.30

46.95

62.61

Kurtosis

11.87

11.87

11.87

11.87

2.41 157.58 1.89 159.47 650 57.56 2.58 1.21

2.41 315.16 3.77 318.93 650 115.13 5.16 2.41

2.41 472.74 5.66 478.40 650 172.69 7.74 3.62

2.41 630.32 7.55 637.87 650 230.25 10.32 4.82

Median

______________

____________

Skewness Range Minimum Maximum Count 97.5"' Percentile 2.5 t Percentile Confidence Level of Mean (95.0%)

G.8

11750

11700

11650

U (ug/L) 11600

500 11550

+

150

S1140 +11

5

11400 ++i

113500 -

ih~ North

r,+

113000592000

592500

5931000

'593500

594000

594'500

Eesting (in) Figure G.8.

Median of Simulated FY 2001 Uranium Concentrations in Grid 2 (300 Area). Contours of the number of times that the center of mass within the grid occurred within cells of an upscaled grid are shown with the average centers of mass shown by pink star in the grid.

G.9

Table G.6.

Coordinates for Sub-Area Boundary for Grid 2 (300 Area) of FY 2001 Uranium Easting (in) 592000 594196 594196 594254 594450 594450 594551 594551 594659 594659 594700 594700 594800 594800 594900 594900 592000 592000

Table G.7.

Northing (in) 117500 117500 116904 116850 116850 116397 116258 116043 115960 115599 115568 115251 115156 112958 112908 112800 112800 117500

Statistics of the Area Exceeding 30 jag/L and Locations of Centers of Mass for Simulations of FY 2001 Uranium within Grid 2 (300 Area)

I

I 2

Area (kin ) Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5th Percentile 2.5 IhPercentile onfidence Level (95.0%0)

C

1

1.426 0.026 1.261 0.652 1.593 1.211 3.928 0.508 4.435 650 3.073

j

Center of Mass (unit: m) Easting Northing 593475.2 9.3 593495.4 237.4 -0.54 -0.33 1156.5 592821.6 593978.1 650 593864.5 592975.2 18.3

0.615 0.050

G.10

115499.7 12.3 115492.9 313.9 0.15 -0.05 1784.0 114557.1 116341.1 650 116123.8 114855.3 24.2

Number of Data mean std. dev. coef. of var maximum upper quartile median lower quartile minimum

0.160

-

0.120-

650 1721.9843 359.1320 0,2086 3319.5439 1931.3710 1689,9490 1448.5280 844.9750

~.0.080LL

0.040-

0.00(i----

800.

1300

1800.

2300.

2800.

3300.

Average Length (in)

Figure G.9.

Histogram of the Average Length of Columbia River Shoreline Exceeding 30 j.±g/L, for FY 2001 Uranium in Grid 2 (300 Area)

G.11I

117500.

117000-

116500

++4

116000-

300 Area

+ +

1165500-

0. L

Cz+

o 115000 -

+

+

7

114500+

114000-

113000592000 -r-5921600

+

593'000

593500

5941000

594'500

Easting (in)

Figure G.10.

Probability of Exceeding 30 jiglL Based on Simulations of FY 2001 Uranium in Grid 2 (300 Area)

G.12

N36166 of Data r3 0 160

0.

N~rrt0e,

1700r 13752 5011dv 67 37 Co~14-'Va1 0 3 r" 5Q1 6630 9.5 7 6 pe3$5 736 14flq"6 311 571

2C

0 12c,

'301167,636

1-01 q

Datao1600

,a 307 IM4 std deV 12 26 0701 4136 0 367 maxnu.~ 677 764 07 0 P.M."t. 6036 44Pw quafl 301 574 m44do 278440

mosmit

766a7621

230057

054W

0 040

0.

150'

2079

300

4M

5N

15CIO 200 (9

37030~~in

050

7

4",5 7

50

7740774D4236 31053 146005 Coel 01o0 0364 4 1 0621,36 7170-,ooo0 516 7p 47710432

12.V 0750

0170~~077~~3~77 0te 000

WO0

070 oroole 533 06 4747765077 434600 lo Q-11 744 437 6078 0 oon 2W 447

3130

05745

'0

700

n77oo7472 6 s711d0. 170637 CoVl 4 0367 maximi127764242

773 0$04 7

155

600

K~)g,10m~

... .Am26%

0550___________________________005 06 D o

11009

500

436

COO M.-s

Wa.os{Kgl 15,,

"00

1.736

1275'

71(47 30

Figure G.11.

Histograms of Total Mass in Simulations of FY 2001 Uranium within Grid 2 (300 Area), Four Thickness Assumptions

Table G.8.

Statistics of Total Mass of Simulations of FY 2001 Uranium within Grid 2 (300 Area), Four Thickness Assumptions

Mass (kg) in Depth Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97.5th Percentile 2.5thPercentile Confidence Level of Mean (95.0%)

5m 183.75 2.62 167.64 66.78 2.65 1.41 422.96 78.70 501.66 650 358.47 97.11 5.14

G.13

j

loin 307.15 4.42 278.44 112.81 2.71 1.45 684.74 133.02 817.76 650 615.93 157.38 8.6

15m 404.24 5.81 368.00 148.20 2.71 1.45 904.58 177.46 1,082.04 650 814.09 210.97 11.41

20 m 472.89 6.70 431.80 170.76 2.76 1.46 1,057.65 206.59 1,264.24 650 928.62 251.01 13.15

..

. .. .. . ..

U

(u gIL)

... ... ... ....

15 00

.. . . . . .. .0..

.. . . . .

50 .. . . ... .. . ....

57760057780057800057820057.40 Easting (in)....

Figue of G.2. imuatedFl! edia 001Uranum

.. . . . .. .

....... .. ...0

oncetratonsin Gid 4(10.H.Aea)

G.150

Table G.9.

Coordinates for Sub-Area Boundary for Grid 4 (100 H Area) of FY 2001 Uranium Northing (i)

asting (i)

577550 578000 578000 578050 578150 578150 578200 578200 578250 578250 578300 578300 578350 578450 578500 578550 578550 578250 577950 577550 577550

Table G.10.

153100 153100 153000 152950 152950 152900 152850 152800 152750 152700 152650 152550 152500 152500 152450 152450 152350 152350 152650 52650 153100

Statistics of the Area Exceeding 30 pgIL and Locations of Centers of Mass for Simulations of FY 2001 Uranium within Grid 4 (100 H Area) Center of Mass (unit: m) 2

Area (kin ) Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 9 7 .5 'h Percentile 2.5 thPercentile Confidence Level (95.0%)

0.062 0.00 1 0.060 0.025 0.097 0.571 0.143 0.010 0.153 700 0.118 0.023 0.002

G.15

Easting

Northing

578005.1 2.6 578004.9 70.1 -0.46 -0.11 366.6 577815.7 578182.3 700 578134.1 577864.8 5.2

152742.3 2.0 152743.3 54.2 -0.16 0.11 308.2 152600.3 152908.4 700 152854.1 152637.6 4.0

153000-

152400-

Grid60 (10 H area)lin

mea std.in

(em)0.04

-

Numer. of vaa 7078

0.200

maximum upper quartile median lower quartile minimum

>,

1119

0.150 -..

482.8430 181.0660 120.7110 60.3550 0.0000

0-

LL

0.100

0.050

000100.

200.

300.

500.

600.

m

100.eLegh

Figure G.14.

400.

Histogram of the Average Length of Columbia River Shoreline Exceeding 30 gg/L for FY 2001 Uranium in Grid 4 (100 H Area)

G. 16

15833 19 3,532

57 5X.ro, 0 54414

-W

s

(k, 4

2 5P-111

28734

945

055C97

C775

26174

14 6359

Pps98 9 ._j14

10 74a, 4225

30

130

90

75 percenwe

C' '16C2 1Th4Th~l1

0

r~n~ ,m2575

75

2,

120

175C

-4;-af

,=

71751

220

14,5,,7 - 007 7

4 oE~~d74 054~24 0 331 24x1~ 4 375 9 7 5 pe.cer44 7720D-

05'

1

4744 4

,s4

3445

-121 of-1

0 33 oax-ml.r 26200 97 5 pe'oeot74e185225 100(0P 7915

4-45

908

704r474111

70434

53

l1

Io414

. -,t50

5 e,

135 C V,-

I5P00

'1

0

3g 15,r

17 Mr

1570

3

(Kg) 2Srn

Figure G.15.

Histograms of Total Mass in Simulations of FY 2001 Uranium within Grid 4 (100 H Area), Four Thickness Assumptions

Table G.11.

Statistics of Total Mass of Simulations of FY 2001 Uranium within Grid 4 (100 H Area), Four Thickness Assumptions

Mass (kg) in Depth Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97.5' Percentile 2.5'7 Percentile Confidence Level of Mean (95.0%)

5Sm 5.633 0.073 5.330 1.926 0.759 0.765 11.731 1.800 13.531 700 9.643 2.6 14 0. 143__

G. 17

J

loin 8.539 0.107 8.204 2.836 0.744 0.768 17.879 2.975 20.853 700 14.639 4.220 0.2 10

15 m 9.964 0.125 9.589 3.296 0.641 0.752 20.622 3.753 24.375 700 17.204 1 4.950 0.245

20m 10.478 0.132 10.009 3.488 0.713 0.771 22.221 3.979 26.200 700 18.229 5.238 0.259

Appcndix H Figures and Data Tables for FY 1992 Uranium

Appcndix H Figures and Data Tables for FY 1992 Uranium

GreGri: Esat9 X

I~

65SOU665l0

6700

14500a0tin Fiur Sbet 1.1 o F

19 UanumDaaan

Wae Table1-+

135000

S6OO

(in)d

+ H+

SbcopFrmtin

5900

o nisatth F

19

1.6 1.4 1.2 -XX

0.2(a)y(h)

= 0.2 + 0.8 Sph(1 300)

0 0

500

1000 1500 Distance

2000

2500

3000

(in)

1.6 1.4 1.2 -X

~-0.8-

X

0.2 (b) y(h)

=0.3 +

0 0

0.7 Sph(950)

I 1000

500 Distance

1500

(mn)

1.2

0.8-XX

X

x

X

60.6 -X 0.4 0.2 (c) y(h) 00

Figure H.2.

500

1000

=0.12

+ 0.88 Sph(2000)j

1500 2000 Distance (in)

2500

3000

Variograms and Models of Normal Scores of the FY 1992 Uranium Data in Local Grid 1 (a), Grid 2 (b), and Grid 3 (c). Experimental variogram values designated by X, with the models fit to the data denoted by the solid black lines.

H.2

155000Grid no.2

145000-"

Grid no.3 .......... ...... ............. ........... ........... ..............

135000-

125000-

U (ug(L)

..... ..... ....... Grid no.1

........ .......... ........... .......... ........... ........... ........... ............ .. ........ ............ ............ ............ .......... . ............. ............. ............. ............. .............. ............ ............. ............... ................ .................. ................... ................ ..... ...................... ... ............................ ......... ........ ............ ........... ............ ............ ........ .... ............. .............. .............. .............. ............... ............... ............... ............. ..... ....... ............ ............ ........... .... ...... ................. ................. ................ .. ............. ...............

500

150

30

15

115000-

go 106000-

555000

565000

575000

5851000

595000

Easting (m) Figure H.3.

Median of Simulations of FY 1992 Uranium Concentrations for Grids 1, 2, and 3

H.3

U (ug/L)

500

P

150

0-3

5

131000-7 664000

566.000

670000

56000

Easting

Figure H.4.

1

5721000

574 10000

(in)

Median of Simulated FY 1992 Uranium Concentrations in Grid 1 (200 West Area)

HA.

Table H.1.

Coordinates for the Boundary of Grid 1 (200 West Area) of FY 1992 Uranium Easting (in) 563750 569750 569850 570350 571350 571950 572250 572800 573050 573650 574000 574000 567450 566650 566400 566350 566000 565950 564950 564900 564200 564150 564000 563950 563750 563750

37Northing (in) 139300 139300 139000 138450 136150 135550 134950 134500 134500 134900 134900 130800 130800 131100 131100 131150 131150 131200 131200 131150 131150 131100 131100 131050 131050 139300

H.5

Table H.2.

Statistics of the Area Exceeding 30 ptg/L and Locations of Centers of Mass for Simulations of FY 1992 Uranium within Grid 1 (200 West Area) Center of Mass (unit: mn) Easting Northing 133900.9 569192.6 28.9 44.0 133900.8 569250.9 1032.3 678.8 -0.39 0.24 0.10 -0.51 3853.1 6057.4 132013.3 565613.5 135866.4 571670.9 550 550 135201.5 570900.2 132681.6 566803.9 56.9 86.5

[

Area (km') 6.98 0.09 6.79 2.18 0.38 0.58 12.89 2.23 15.11 550 11.67 3.55 0.18

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count . th Percentile 97 5 . 2 5th Percentile Confidence Level (95.0%) 139000

+

200 West Area+

~

TPlant

1370005

T

+*

CM~

ERUF

+

Ii

k ~

UPond ++ +

REDOX

+

1330005

-0.5

564 1000

1315550.4 566050

570000

6685,000

5725000

674000

Easting (in)

Figure H.5.

Probability of Exceeding 30 pgg/L Based on Simulations of FY 1992 Uranium in Grid 1 (200 West Area)

H.6

N4400"' d4 Data 650 2M~a 9221 m 1104 112S84 f a' -a D20 50 4140hm 740722 9? 5 Porooo50e 5142 71? 4554540 -5002 J541234 37

120

Nmtw ofDaa 0 r~a 445970 s10 day0 M2792 coO1 of 100050 ro4w 14521 44 pools 10235 IS 4ppe, q-,t150 541251 9 nvl50o 4037 53

0 12,0

04045440100 rn

0

00

400

5--0

6300

723w

5200

7023

MoK 5 5)

D

3 2 5 peoroo1e 149300

4)4)4)0

120 0)1

14520

350118 6omr

47M?

570

200

Nuvwr4,4d4 Data 550 45 01 6&k44 olS de, 2225-15 054 050 2211054 97 5 W,,en~a 15411 75

12,., 12-104r

160

Ma-s (Kg) 101,

2 6W-w

N.u400 ,1 d Dat

550 810, 77459 d-o 44G7594 c100 05 of 0104 50 n4o.m4 --009W72 9? 5 Slooi 3245 11

2440 112?

142058

opo..r44

m4144m11512 385,

2

4

00,

1

2054

0 040

600~ 0'

11005?z

140

2002

1400

Figure 11.6.

Table H.3.

210c0

115N2?

Mazos0'145 15m1

6104$i4,

315c)

2040

Histograms of Total Mass in Simulations of FY 1992 Uranium within Grid 1 (200 West Area), Four Thickness Assumptions Statistics of Total Mass of Simulations of FY 1992 Uranium within Grid 1 (200 West Area), Four Thickness Assumptions Mass (kg) in Depth

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97.5'h Percentile 2 .5 th Percentile Confidence Level of Mean (95.0%o)

5mi 2,262.90 48.05 2,034.37 1,126.88 2.08 1.29 7,019.47 387.75 7,407.22 550 5,187.91 1 763.42 94.39 H.7

lOin 4,489.69 95.51 4,037.93 2,239.96 2.10 1.30 14,047.89 773.56 14,821.44 550 10,338.39 1,483.63 187.61

15m 6,668.01 142.34 5,946.91 3,338.20 2.10 1.30 20,959.56 1,151.38 22,110.94 550 15,440.26 2,232.25 279.60

J

20mi 8,774.60 188.13 7,780.00 4,411.96 2.09 1.31 27,487.17 1,520.56 29,007.72 550 20,406.87 2,967.34 369.54

152000H 100

D500

S148000-3 10015

1480000

57200

57005a0

Easting (in) Figure H.7.

Median of Simulated FY 1992 Uranium Concentrations in Grid 2 (100 Areas)

H.8

Table H.4.

Coordinates for the Boundary of Grid 2 (100 Areas) of FY 1992 Uranium Basting (in) 563900 563900 564206 564778 565610 566373 566915 567588 567905 568736 569056 569597 570361 570967 572118 572754 573070 573965 573996 574315 574379 574635 575910 577761 578239 579740 579962 579962 579706 579582 579706 580124 580985 581463

Northing (in) 143800 145566 145277 145277 145502 145754 145882 146172 146522 147033 147447 147959 148692 149392 150987 151785 152199 152744 153030 153828 154144 154500 154500 153410 152710 151371 150987 150573 149806 149614 149200 148787 __ __

581900

148211 147764

147700

581900

1__ 43800

563900

143800

H.9

Table H.5.

Statistics of the Area Exceeding 30 j.±g/L and Locations of Centers of Mass for Simulations of FY 1992 Uranium within Grid 2 (100 Areas)

Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97.5"' Percentile 2 .5 th Percentile Confidence Level (95.0%)

I

1

Center of Mass (unit: m)

Area (kin') 7.13 0.12 6.64 3.06 1.21 0.99 19.57 0.91 20.48 700 14.27 2.65 0.23

H. 10

Easting

Northing

575292.6 35.4 575312.2 936.3 -0.17 -0.05 5996.8 572180.9 578177.8 700 577016.1 573596.9 69.5

147010.4 20.0 146986.3 529.9 -0.23 0.32 2888.2 145797.1 148685.3 700 148183.8 146065.1 39.3

100 H Are a 1000D Are a

152000-

69 0.9

100 N Are a

0)

100OF

0.

Area

z 148000-

Are a -100 HAD Area

~

0.5

6 -0.4

144000564000

568000

572000

576000

580000

Easting (in) Figure H.8.

Probability of Exceeding 30 jtg/L Based on Simulations of FY 1992 Uranium in Grid 2 (100 Areas) Number of Data 700 mean 1084.67 std. dee. 863.27

0.200-

coef, of var maximum upper quartile median lower quartile minimum

0150

an 0.100-

F

0-80 5914,82 1388-17

844.98 543.20

0.0

U.

0,050-

0~.0.-r 0-

1000.

2000.

3000.

4000.

Average Length

Figure H.9.

5000.

6000.

(in)

Histogram of the Average Length of Columbia River Shoreline Exceeding 30 gig/L for FY 1992 Uranium in Grid 2 (100 Areas)

H.]1I

o

120

NV1,r51 C4 Dal.

7W 12 6 062 372 37 042 1l5J1sl260376 6 ro1l 161966 "500, I$16 16666 661 212 e I26 l

N

13 70D6 ,D1,3 ,Oan 13222 "Vc 516 34 7e co6Va1r1 040 fl6.1l 8l33715 97,5 1. 16076 sp'6s3 3 -165$.n 1220334 1o5 "i."1152561" 2.3, s06 5215

$16 <*v lof a

25

0080

7U705 34rw

0340..

1

0

W22

12

1100, M.-, (KM

2034

2508

40)

245 400

56.

526. 1Kq

Nunbe,so21116 700 -an11115766 t l66s42012 Max1 036 11151h114345 0021111111147 67 5 pseme1Stle3161W1 11551e11C,11151950445

VOID0

C,050

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10m1

010Nv,,6ef

Of Da34 7(00 1001111' 17705 $1464. W6743 malQ6, 0 3aQ6 46 675 65511

5 32

c~c

35400X 161,6 21077 640 16111140 0 0716116 WM111111 6 2 p'66 5

1611114580216011 151661115111166 11"3316 2 551614516 7 C2 875

5

le

M,n -m 504 54

00054.

Mss *Kq) 151,

Figure H.10.

Masa (Kg)520m~

Histograms of Total Mass in Simulations of FY 1992 Uranium within Grid 2 (100 Areas), Four Thickness Assumptions

Table H.6.

Statistics of Total Mass of Simulations of FY 1992 Uranium within Grid 2 (100 Areas), Four Thickness Assumptions

Mass (kg) in Depth Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97.5" Percentile 2.5'bPercentile Confidence Level of Mean (95.0%)

5Sm 890.80 14.08 825.12 372.64 1.10 0.98 2,336.36 267.40 2,603.76 700 1,819.97 347.05 27.65 H.12

loin 1,322.22 20.23 1,220.04 535.16 1.22 1.01 3,430.52 406.63 3,837.15 700 2,667.91 1 533.15 39.71_

15m 1,579.98 23.45 1,458.02 620.56 1.05 0.98 3,840.46 504.54 4,345.00 700 3,180.04 676.75 46.05

[

20Gm

1,775.35 26.00 1,646.08 687.89 0.96 0.96 4,085.82 587.62 4,673.43 700 3,542.94 1 750.56 510

-

200

EaU

(ug/L)

500

00

570000

575000

580000

585000

590000

695000

Easting (in) Figurel-H.11.

Median of Simulated FY 1992 Uranium Concentrations in Grid 3

H.13

Table H.7.

Coordinates for Sub-Area Boundary of Grid 3 of FY 1992 Uranium Basting (in) 592000 594196 594196 594254 594450 594450 594551 594551 594659 594659 594700 594700 594800 594800 594900 594900 592000 592000

Northing (mn) 117500 117500 116904 116850 116850 116397 116258 116043 115960 115599 115568 115251 115156 112958 112908 112800 112800 117500

H. 14

4+ U (ug/L) 116500

150 0100

-30

15

113000

592000

592500

593000

593500

5940000

594500

Easting (in) Figure H.12.

Median of Simulated FY 1992 Uranium Concentrations in Sub-Area (300 Area Plume) of Grid 3. Contours of the number of times that the center of mass within the sub-area occurred within cells of an upscaled grid are shown with the average centers of mass shown by pink star in the sub-area.

H. 15

Table H.8.

Statistics of Centers of Mass of Individual Simulations of FY 1992 Uranium Calculated for a Depth of 5 m for Sub-Area (300 Area Plume) of Grid 3

I Coordinate Mean Standard Error Median Standard Deviation Kurtosis

Sub-Area Fasting 593680.0 6.5 593687.9 138.9

(in)

0.62

____________

Skwes-0.49 Range

Minimum

1.90

-1.26

______________ ____________

900.2

1476.5

593188.8

114557.4

Mxmm594089.0 Count

Northing 115464.8 11.5 115519.9 243.0

116033.9 450

______________

9 7 .5 th Percentile 2 .5 'h Percentile Confidence Level of Mean (95.0%)

593932.7 593360.4 12.9

H. 16

450

115779.4 114807.4 22.5

117506-

1176006

+ +

+

+

+

++

11650++

116000

+

+1

116000-

114500-A

0.5

+~ +

11400

115060

Are

300Are

114500-

1140001

592000

592500

593000

593500

594000

594500

Easting (in) Figure H.13.

Probability of Exceeding 30 gg/L Based on Simulations of FY 1992 Uranium in SubArea (300 Area Plume) of Grid 3

H.1 7

Table H.9.

Statistics of the Area Exceeding 30 pgI/L for Simulations of FY 1992 Uranium within Sub-Area (300 Area Plume) of Grid 3

J

Area (krn')

Sub-Area

Grid 3

0.64

20.95 0.27

Mean________________

StnadErr0.01 0.60

20.46

Standard Deviation

0.19

6.61

Kurtosis

3.19

0.68

1.37 1.31 0.26 1.57 450 1.06 0.38 0.02

0.66 38.90 8.02 46.92 600 35.69 9.99 05

Median

_______________

____________

Skewness Range Minimum Maximum Count 9 7 .5 Ih Percentile 2.5'h Percentile Confidence Level of Mean (95.0%)

Number of Data mean std, dev. met, of var maximum upper quartile median lower q~uartile minimum

0120.

C0

450 3146,52 1391.28 0,44 9958,63 3802,39 2836,70 2112-44 844.98

080_

0.040

0,00oo0

. 500.

2500,

..... 4500.

6500,

8500.

10500.

Average Length (in)

Figure H.14.

Histogram of the Average Length of Columbia River Shoreline Exceeding 30 p~g/L

for FY 1992 Uranium in Grid 3

H. 18

FY02 U, 3W0A,.

4-

Fy42 V 300 A-.

64 14

";Ia

14

01'20

1301413141

1

24 f

320

000

3624

31J01L,

40

30

~

11

4'61

41404.63.

6 09

1W

2 2040

10

21

01

meat~~ 1,

120

FY92

V34

4423

~~

16

1>0)

26C

U 14111334113 340

0-11512

V?1 46

0

145CO1U,

3004

000411

112 3tt

3

17131444 44

41,

N-4

23 4

011"0

1

310

0A-0 01041 324 Ot D. 4134

0014

022ol.35

02 4

42

4o0"122104 1o, 3a 0241

60

.1042

1244

358797o 63

41.1*0

3

D

Grid~ (30 Area Plm)DorTiknsSsupin 3e Ow

Table H.1.

Staisticras of Total Mass f Simulations of FY 1992 Uranium within Sub-Area of Grid 3 (300 Area Plume), Four Thickness Assumptions

Mass (kg) in Depth Mean Standard Error Median Standard Deviation Kurtosis Skewness Range Minimum Maximum Count 97.5"' Percentile 77 5 t Percentile Confidence Level of Mean (95.0%)

[

1

m 84.14 0.99 81.62 21.00 2.12 0.97 148.15 41.59 189.74 450 130.79 51.12 1.95

H.19

[

1

lOin

15 m

20 m

140.29 1.60 137.25 33.97 1.41 0.82 229.77 69.24 299.01 450 218.10 87.24 3.15

184.50 2.09 181.62 44.28 0.82 0.70 275.16 90.55 365.70 450 287.49 114.49 4.10

217.83 2.43 216.05 51.48 0.56 0.64 306.29 107.12 413.41 450 334.90 134.82 4.77

PNNL-14618, Rev. 0

Distribution No. of Copies

No. of Copies

ONSITE

8 Fluor Hanford, Inc.

2

DOE Office of River Protection R. M. Yasek R. W. Lober

9

J. V. Borghese F. M. Coony B. H. Ford T. W. Fogwell R. Jackson V. J. Rohay L. C. Swanson M. E. Todd-Robertson

H6-60 H6-60

DOE Richland Operations Office B. L. Charboneau B. L. Foley J. P. Hanson R. D. Hildebrand J. G. Morse K. M. Thompson S. H. Wisness DOE Public Reading Room (2)

A6-33 A6-3 8 A5-13 A6-38 A6-38 A6-38 A3-04 H2-53

Stoller R. G. McCain

9

R. L. Aaberg C. Arimescu M. P. Bergeron B. N. Bjomstad R. W. Bryce A. L. Bunn K. J. Cantrell Y. J. Chien R. L. Dirkes J. L. Downs D. W. Engle P. W. Eslinger M. J. Fayer E. J. Freeman M. D. Freshley G. W. Gee T. J. Gilmore D. G. Horton C. T. Kincaid G. V. Last (5) C. A. LoPresti W. J. Martin T. B. Miley C. J. Murray B. A. Napier W. E. Nichols

2

H9-01 H9-04 H6-60 HO-23 HO-23

CH2M HILL Hanford Group, Inc. F. J. Anderson A. J. Knepp M. N. Jarayssi F. M. Mann W. J. McMahon C. W. Miller D. A. Myers C. D. Wittreich M. 1. Wood

E6-35 H6-03 H6-03 E6-35 E6-35 H6-62 E6-3 5 H6-62 H8-44

Fluor Federal Services R. Khaleel R. J. Puigh

B2-62

47 Pacific Northwest National Laboratory

5 Bechtel Hanford Inc. P. G. Doctor K. R. Fecht K. A. Gano J. K. Linville S. G. Weiss

E6-35 E6-3 5 E6-3 5 E6-35 E6-35 E6-35 E6-35 E6-35

E6-17 E6-17

Distr.1I

K3-54 K6-04 K9-36 K6-81 E6-3 5 K6-85 K6-81 K6-81 K6-75 K6-85 K5-12 K6-04 K9-33 K9-36 K9-33 K9-33 K6-81 K6-81 K9-33 K6-81 K5-12 K6-81 K6-04 K6-81 K3-54 K9-33

PNNL-14618, Rev. 0 No. of Copies G. W. Patton J. V. Ramsdell, Jr. S. P. Reidel M. C. Richmond R. G. Riley M. L. Rockhold R. J. Serne D. L. Strenge

No. of Copies K6-75 K3-54 K6-81 K9-33 K6-96 K9-3 6 P7-22 K3-54

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Distr.2

K6-04 K9-33 K9-33 K9-3 6 K9-36 K9-36 K9-36 H2-53

PNNL.-14702, Rev. 0

Vadose Zone Hydrogeology Data Package for the 2004 Composite Analysis

G. V. Last E. J. Freeman K. J. Cantrell M. J. Fayer

G. W. Gee W. E. Nichols B. N. Bjornstad D. G. Horton

July 2004

Prepared for the U.S. Department of Energy under Contract DE-AC06-76RL01 830

DISCLAIMER This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor Battelle Memorial Institute, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

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PNNL- 14702, Rev. 0

Vadose Zonc Hydrogeology Data Packagc for the 2004 Composite Analysis

G. V. Last E. J. Freeman K. J. Cantrell M. J. Fayer

G. W. Gee W. E. Nichols B. N. Bjornstad D. G. Horton

July 2004

Prepared for the U.S. Department of Energy under Contract DE-AC06-76RLO01830

Pacific Northwest National Laboratory Richland, Washington 99352

Executive Summary The U.S. Department of Energy is required to conduct a composite analysis of active and planned low-level radioactive waste disposal facilities associated with the Hanford Site. The original composite analysis was completed in 1998; however, it must be revised in 2004 to address a number of revisions to waste site information, updated performance assessments and environmental impact statements (EIS), changes in inventory estimates, and changes in the definition of offsite receptors. This data package documents the technical basis for selecting physical and geochemnical parameters and input values that will be used in vadose zone modeling for the 2004 Composite Analysis. This work was conducted as part of the Characterization of Systems Task of the Groundwater Remediation Project (formnerly the Groundwater Protection Program) managed by Fluor Hanford, Inc., Richland, Washington. This data package describes the geologic framework, the physical, hydrologic, and contaminant transport properties of the geologic materials, and deep drainage (i.e., recharge) estimates, building on the general framework developed for the initial assessment conducted using the System Assessment Capability (SAC). The general approach for this work was to update and provide incremental improvements over the previous SAC data package completed in 2001. As with the previous SAC data package, much of the data and interpreted information were extracted from existing documents and databases. Every attempt was made to provide traceability back to the original source(s) of the data or interpretations. Kincaid et a]. (2004) identified 1,046 waste sites from the Waste Information Data System (WIDS) sites and several existing and future storage sites for inclusion in the 2004 Composite Analysis, with analyses to be conducted on a site-by-site basis whenever inventory and release data perm it.(a) The complexity of this assessment, together with the lack of detailed characterization data and/or understanding of some of the less dominant fine-scale fate and transport processes necessitates simplification of the site features, release events, and the contaminant fate and transport processes to those factors considered most dominant. The dominant factors affecting transport of contaminants through the vadose zone include: 1) waste inventory and release estimates, 2) estimates of deep drainage (recharge), 3) the hydrogeologic profiles and properties of the vadose zone affecting aqueous phase advection and dispersion, and 4) estimates of geochemnical reactions (e.g., sorption) affecting the retardation of contaminants. The last three of these data types are addressed by this data package. The first one, waste inventory and release estimates, is addressed in the inventory and release model data packages. The 2004 Composite Analysis will, in general, use a one-dimensional vadose zone model, configured to account for lateral spreading, and in selected cases, conditioned against multi-dimensional model results (Kincaid et al. 2004). Waste sites were grouped into a number of geographic areas assumed to

(a) Originally 974 of 2,730 Waste Information Data System (WIDS) sites were identified for inclusion in the 2004 Composite Analysis. Further work identified 48 more waste sites bringing the total to 1,022. Subsequent reviews identified an additional 24 sites that have been included, many of which account for offsite transfers of waste and nuclear material. This brings the total to 1,046.

iii

have similar hydrogeologic structure and properties. Hydrogeologic units were identified and their thickness ranges specified for each of these hydrogeologic provinces. To account for uncertainty in the model parameters, a stochastic distribution was developed for each process model parameter for each hydrogeologic unit. The vadose zone hydrostratigraphic profiles and hydrogeochemnical property distributions for the 2004 Composite Analysis are represented by 26 generalized one-dimensional vertical columns representing 17 general geographic areas and 9 site-specific locations. Each hydrostratigraphic profile (template) was configured with the hydraulic and geochemnical parameters necessary to simulate the flow and transport through the vadose zone using the Subsurface Transport Over Multiple Phases (STOMP) code. As many as five variations of a single hydrostratigraphic template were incorporated to more accurately represent the depth of waste release, the thickness of the vadose zone beneath the point of release, and variations in contaminant distribution coefficients (Kd values) associated with different waste chemistry designations. Each template consists of a few major hydrostratigraphic units that are horizontally layered with constant thicknesses, and are homogeneous and isotropic. Hydraulic and geochemnical parameters for each hydrostratigraphic unit are represented by stochastic distributions to facilitate sensitivity and uncertainty analyses. This data package is a compilation of the available data to support a composite analysis of Hanford's impact. As site characterization is completed at waste sites and as investigations into contaminant behavior are completed, the uncertainty in this information will be reduced and, as a result, the uncertainty in future estimates of impact will be reduced.

iv

Acknowledgments The authors would like to acknowledge Thomas W. Fogwell and the Groundwater Remediation Project managed by Fluor Hanford, Inc. for supporting this work. We would like to thank Raziuddin Khaleel (Fluor Federal Services), and Charles T. Kincaid, Christopher J. Murray, Stephen P. Reidel, and Robert W. Bryce for their technical reviews. The authors would also like to thank Anderson L. Ward for his technical support throughout the completion of this work, and Christopher A. Newbill for preparation of the site location map. We would also like to thank Launa F. Morasch for her technical editorial support, and Lila M. Andor and the rest of the Publication Design team for their support in producing this document.

v

Contents Executive Summary ............................................................................................... Acknowledgments................................................................................................ 1.0

2.0

3.0

4.0

Introduction.............................................................................................. 1.1 Purposel.1 1.2 Scope and Approach ................................................................................ Background.............................................................................................. 2.1 Conceptual Model of the Hanford Site Vadose Zone ............................................ 2.1.1 Features................................................................................... 2.1.2 Events ................................................................................... 2.1.3 Processes................................................................................. 2.2 Uncertainty and Unresolved Technical Issues .................................................. Property Representation ................................................................. 2.2.1 2.2.2 Effects of Scale ........................................................................... 2.2.3 Spatial and Temporal Resolution of Site Data......................................... 2.2.4 Preferential Flow ......................................................................... 2.2.5 Temperature and Density Effects ....................................................... 2.2.6 Geochemical Processes.................................................................. 2.3 Technical Basis and Approach for Vadose Zone Modeling.................................... 2.3.1 Features .................................................................................. 2.3.2 Events ................................................................................... 2.3.3 Processes................................................................................. 2.4 Implementation................................................................................... 2.4.1 Hydrogeologic Profiles................................................................... 2.4.2 Deep Drainage Rates..................................................................... 2.4.3 Geochemnical Reactions.................................................................. 2.4.4 Interaction with the Inventory, Release, and Groundwater Modules ............... Data Compilation .......................................................................................... 3.1 HydroStratigraphy ................................................................................. 3.2 Hydrostratigraphic Templates...................................................................... 3.2.1 Waste Site Type (reflecting the depth of waste injection).............................. 3.2.2 Geographic and Site-Specific Areas Designations...................................... 3.2.3 Waste Chemistry Groupings (for assigning Kd ranges)................................. 3.2.4 Hydrostratigraphic Template Designations.............................................. Input Parameters............................................................................................ 4.1 Hydrostratigraphy .................................................................................. 4.2 Hydraulic Properties ................................................................................ 4.2.1 Site-Wide Hydraulic Property Distributions ............................................ 4.2.2 Site-Specific Hydraulic Property Distributions ......................................... 4.2.3 Application to Vadose Zone Simulations................................................ 4.2.4 Transport Parameters.....................................................................

vii

11i

v 1.1 1.1 2.1 2.1 2.4 2.12 2.14 2.18 2.19 2.19 2.20 2.20 2.22 2.23 2.24 2.25 2.26 2.26 2.27 2.28 2.29 2.30 2.30 3.1 3.1 3.3 3.3 3.4 3.4 3.8 4.1 4.1 4.3 4.7 4.9 4.9 4.11

4.3

5.0 6.0

Contaminant Distribution Coefficients........................................................... 4.3.1 Tritium................................................................................... 4.3.2 Carbon- 14................................................................................. 4.3.3 Chlorine-36 (as chloride) ................................................................ 4.3.4 Selenium-79 (as selenate)................................................................ 4.3.5 Strontium-90 .............................................................................. 4.3.6 Technetium-99 (as pertechnetate) ...................................................... Iodine- 129 (as iodide) ................................................................... 4.3.7 4.3.8 Cesium-137............................................................................... 4.3.9 Europium-152............................................................................. 4.3.10 Uranium .................................................................................. 4.3.11 Neptunium-237 ........................................................................... 4.4 Hy drostrat igraphic Templates .................................................................... Assignment of Waste Chemistry Types................................................ 4.4.1 4.4.2 Facility Location, Dimensions, and Wetted Area ..................................... 4.5 Recharge Estimates................................................................................ 4.5.1 Natural and Disturbed Soil .............................................................. 4.5.2 Surface Barriers........................................................................... 4.5.3 Probability Distribution Functions...................................................... 4.5.4 Integrated Drainage Calculations ....................................................... 4.5.5 Recharge Classes ......................................................................... Conclusions and Recommendations ...................................................................... References ...............................................................................................

Appendix A - H-ydrostratigraphic Templates............................................................... Appendix B - Hydraulic Property Distributions............................................................ Appendix C - Resolution of Discrepancies in the System Assessment Capability Vadose Zone Model for the BC Cribs and Trenches...................................................... Appendix D - Surface Barrier Degradation.................................................................

viii

4.12 4.14 4.14 4.16 4.16 4.17 4.17 4.17 4.17 4.18 4.18 4.18 4.18 4.19 4.19 4.21 4.21 4.23 4.26 4.27 4.29 5.1 6.1

A.I B.1I C.1I D.1I

Figures 2.1 2.2 2.3 2.4 2.5 3.1 3.2 4.1 4.2 4.3

General Vadose Zone Conceptual Model Concepts after Caggiano (1996). Note that the geologic nomenclature varies from that used today...................................... 2.2 Process Relationship Diagram of Vadose Zone Flow and Transport .................................. 2.3 Generalized West-to-East Geologic Cross Section Through the Hanford Site (after Hartman 2000).................................................................................... 2.7 Photograph of a Typical Clastic Dike as Found at the U.S. Ecology Site in Central Hanford (after Fecht et al. 1999) ........................................................ 2.8 Schematic of Vadose Zone Implementation Model for the Composite Analysis .................. 2.28 Location of Geographic Areas Represented by a Single Generalized Stratigraphic Column .................................................................................... 3.2 Schematic of One-Dimensional Vadose Zone Simulation.............................................. 3.3 Formation Specific Water Retention Curves for the Site-Wide Distribution ........................ 4.7 Formation Specific Hydraulic Conductivity Curves for the Site-Wide Distribution................ 4.8 Formation Specific Hydraulic Conductivity Curves Versus Saturation for the...................... 4.8

ix

Ta bles

2.1

Options for the Composite Analysis (after the Preliminary Concepts Document)(a)............... 2.25

3.1 3.2 3.3 3.4

Waste Site Type Designations Used in the Hydrostratigraphic Template Codes.................... 3.4 Geographic Area Designations Used in the Hydrostratigraphic Template Codes................... 3.5 Site-Specific Area Designations Used in the Hydrostratigraphic Template Codes ................. 3.5 Waste Stream Designation and Assumed Compositions for Determination of Kd Values................................................................................................ 3.7 Waste Chemistry Designations Used in the Base Template Codes.................................... 3.8 General Hydrostratigraphic Templates for Each Geographic Area.................................... 3.9 Site-Specific Templates Established for a Few Key Facilities........................................ 3.11 Sources of Hydrogeologic Data for the Seventeen Geographic Areas to be Analyzed .................................................................................... 4.2 Hydrostratigraphic Units Used in this Study (after DOE 2002 and Lindsey 1996)...................................................................... 4.3 Description of Hydraulic-Property Soil Classes......................................................... 4.4 Statistical Mean Values for Site-Wide Samples......................................................... 4.6 Statistical Mean Values for BC-Crib Samples........................................................... 4.6 Statistical Mean Values for U I & U2 Samples.......................................................... 4.6 Statistical Mean Values for 200-ZP-1I Samples ......................................................... 4.7 Statistical Mean Values for 200 West Area Samples .................................................. 4.10 List of Contaminants of Concemn to be Included in the 2004 Composite Analysis (Kincaid et al. 2003).............................................................. 4.13 Kd Ranges by Waste Chem istry/Source Category ..................................................... 4.15 Default Surface Areas.................................................................................. 4.20 Estimated Recharge Rates for Predominant Soil Types and Sediment with a Shrub-Steppe Plant Community ................................................................. 4.22 Estimated Recharge Rates for Soil Types and Sediment Without Vegetation...................... 4.22 Estimated Recharge Rates by Soil Type/Sediment and Vegetation Condition in Each Hanford Area. Significant secondary soil types and their associated recharge estimates are shown in parentheses.................................... 4.24 Barrier Design Life and Estimated Recharge Rates for Barrier Tops ................................ 4.25 Initial Side Slope Recharge Rates for Hanford Site Climate Conditions ........................... 4.25 Estimated Recharge Rates for Baseline Soil Conditions .............................................. 4.29 Estimated Recharge Rates for Disturbed Conditions and Sensitivity Tests ........................ 4.30 Estimated Recharge Rates for Surface Barrier Components .......................................... 4.31 Estimated Recharge Rates for Surface Barriers with Side Slopes and rb, = 3.0 mm/yr..................................................................................... 4.31 Estimated Recharge Rates for Surface Barriers with Side Slopes and rb.. = 42.0 mm/yr ................................................................................... 4.32

3.5 3.6 3.7 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 4.9 4.10 4.11 4.12 4.13 4.14

4.15 4.16 4.17 4.18 4.19 4.20 4.21

x

1.0

Introduction

A composite analysis is required by U.S. Department of Energy (DOE) Order 435.1 to ensure public safety through the management of active and planned low-level radioactive waste disposal facilities associated with the Hanford Site (DOE M 435.1 -1). The original composite analysis (Kincaid et a]. 1998) must be revised and submitted to DOE Headquarters (DOE-HQ) in 2004 because of revisions to waste site information in the 100, 200, and 300 Areas, updated performance assessments and environmental impact statements (EIS), changes in inventory estimates for key sites and constituents, and a change in the definition of offsite receptors. Kincaid et al. (2004) describe the technical scope of the 2004 Composite Analysis for the Hanford Site and the approach to perform this analysis. It will be a site-wide analysis, considering final remedial actions for the Columbia River corridor and the Central Plateau and will be a companion to waste-specific and site-specific assessments. The 2004 Composite Analysis also will provide supporting inform-ation on a regional or site-wide basis for use in important Hanford assessments and decisions such as the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) 5-year review in 2005, tank closure decisions, decisions on final groundwater remedies for the 200 Areas, decisions on final groundwater remedies for the 100 Areas, and the Columbia River corridor final record of decision. Beginning in fiscal year (FY) 2003, the DOE Richland Operations Office (DOE-RL) initiated activities, including the development of data packages, to support the 2004 Composite Analysis. This report describes the data compiled in FY 2003 to support vadose zone modeling for the 2004 Composite Analysis. This work was conducted as part of the Characterization of Systems Task of the Groundwater Remediation Project (formerly the Groundwater Protection Program) managed by Fluor Hanford, Inc., Richland, Washington.

Purpose

1.1

The purpose of this data package is to summarize the conceptual understanding of flow and transport through the vadose zone (i.e., the conceptual model), describe how this understanding will be simplified for numerical simulation as part of the 2004 Composite Analysis (i.e., implementation model), and finally to provide the input parameters needed for the vadose zone simulations.

Scope and Approach

1.2

The scope of this data package covers the geologic framework, the physical, hydrologic, and contaminant transport properties of the geologic materials in the vadose zone, and estimates of deep drainage (i.e., recharge). This data package builds on the general framework developed for the initial assessment conducted using the Systern Assessment Capability (SAC) as presented in: *Preliminary System Assessment Capability Concepts for Architecture, Platform, and Data Management - Appendix C, Vadose Zone Conceptual Model (http://www.hanford.gov/cp/gpp/modeling/sacarchive/App%/20C.pdf)

*Draft 2001 SAC Data Package, Appendix C - Vadose Zone Datafor InitialAssessment Performed with System Assessment Capability(Revision 0) (http://www.hanford.gov/cp/gpp/modeling/sacarchive/dp-vadose.pdf). The general approach for this work was to update and provide incremental improvements over the previous 2001 data package. As with the previous SAC data package, much of the data and interpreted information were extracted from existing documents and databases. Every attempt was made to provide traceability back to the original source(s) of the data or interpretations.

1.2

2.0

Background

The vadose zone is the hydrogeologic region that extends from the soil surface to the water table (DOE 1998). At the Hanford Site, the vadose zone ranges in thickness from less than 1 meter along the river in the 100 and 300 Areas to more than 100 meters on the Central Plateau in the center of the Hanford Site. At discrete locations, the vadose zone contains waste inventories from past waste disposal practices (e.g., direct liquid waste disposal to the ground via engineered facilities) and from unplanned releases (e.g., spills and tank leaks). The geologic framework of the vadose zone is very complex with a high degree of heterogeneity and anisotropy in its physical, hydrologic, and geochemnical properties. This complex hydrogeochemnical framework, together with waste water and meteoric water fluxes lead to highly complex threedimensional movement of moisture and contaminants through the vadose zone. Wilson et al. (1995) describe flow within the vadose zone as dynamic and characterized by periods of unsaturated flow at varying degrees of partial saturation punctuated by episodes of preferential, saturated flow in response to hydrologic events or releases of liquids. This section summarizes our conceptual understanding of flow and transport through the Vadose Zone and the technical basis and approach for modeling the Vadose Zone for the Composite Analysis. Conceptual models are evolving hypotheses that identify the important features, events, and processes controlling fluid flow and contaminant transport at a specific field site and in the context of a specific problem. Looney and Falta (2000) further describe a conceptual model as answering the question "How do we believe the system actually operates?"~ The conceptual model is one of the key initial elements in the overall modeling process. Once the site-specific problem has been defined and the important features, events, and processes conceptualized, quantitative descriptions can be prepared and implemented. Field and laboratory data are used to provide the input data, as well as to calibrate and independently test the predictive capabilities of the model. Of particular interest to this data package are the subsurface geologic, hydraulic, and geochemical parameters and the deep drainage estimates that control flow and transport through the vadose zone.

2.1

Conceptual Model of the Hanford Site Vadose Zone

Conceptual models of the vadose zone at the Hanford Site have been developed from information on the geology, geochemistry, and hydrologic regime as well as the distribution and movement of waste in the subsurface. Most of the information has been obtained from borehole drilling through sediment sampling and analysis and geophysical logging. This has provided a considerable amount of information about the lithology and stratigraphy, but a more limited amount of hydrologic and geochemical information has been obtained. These investigations into the vadose zone have traditionally been at or near the waste disposal sites; however, a few areas that represent background conditions or provide representative test sites have also been studied. The integrated knowledge from these previous studies and ongoing work provides a reasonable conceptual understanding of the geologic, hydraulic, and geochemical controls on contarninant movemnent and distribution within the vadose zone of the Hanford Site (DOE 1999). Figure 2.1 illustrates some of these controls. However, there are still many outstanding issues, some of which require additional study and some of which may never be completely resolved. 2.1

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these important features, events, and processes, and identifies those factors that are considered most dominant and have been selected as study sets for numerical representation (modeling) in the 2004 Composite Analysis. 2.1.1

Features

The primary features relevant to the vadose zone flow and transport include the hydrogeologic materials (and their physical, hydraulic, and geochemical properties); subsurface conditions (e.g., fluid statics and thermal conditions); and fluid properties. Other features relevant to the vadose zone conceptual model such as climate and weather statistics, terrestrial ecology, and projected land use are not specifically discussed here. Instead, the reader is referred to (Neitzel et al. 2003) for general discussions of these specific features. Some aspects of the climate and weather phenomena are discussed later as they relate to precipitation, run-off, and infiltration events. There is a significant amount of hydrogeologic data available for the Hanford Site, primarily from borehole drilling in the vicinity of waste disposal operations. Interpretation of the geologic data are presented in numerous reports, including Delaney et al. (1991); Lindsey (1992, 1995); Lindsey et al. 1992a, b; Lindsey and Jager 1993; Hartman and Peterson (1992); Peterson et al. (1996); DOE (I1993a, 1994); Thomne et al. (1993, 1994); Hartman (2000); Williams et al. (2000); Williams et al. (2002); and DOE (2002). The thickness of the vadose zone varies from less than I meter along the river in the 100 and 3 00 Areas to more than 100 meters beneath the Central Plateau. The vadose zone lies mostly within cataclysmic flood deposits of the Hanford formation, but in places such as 200 West Area and portions of the 100 Areas it extends into the underlying Cold Creek unit, and/or the upper portions of the Ringold Formation. The physical structure (e.g., geology, hydrologic properties, and geochemical properties) of the geologic framework and its principal transport pathways is complex with a high degree of heterogeneity and anisotropy. To capture some of the site-wide variability in these features, this discussion is broken into three general physiographic areas (the 100, 200, and 300 Areas). While other selected areas away from these focus areas, such as areas representative of background conditions and areas that have the potential to become contaminated in the future, are also important to the general vadose zone technical element, they are not specifically discussed here. 2.1.1.1

100 Areas

The average thickness of the vadose zone in the reactor areas ranges from 6 meters (1 00-F Area) to over 30 meters (100-B/C Area) with each reactor area being slightly different. During operations, groundwater mounding reduced the thickness of the vadose zone by 6 to 9 meters directly under the retention basins or other liquid-waste disposal facilities.

Hydrogeologic Materials. The hydrogeologic framework of the vadose zone is complex; however, locally within the 100 Areas, it can be divided into two primary hydrostratigraphic units: 1) the graveldominated facies association of the Hanford formation and 2) the conglomeratic member of Wooded Island, Unit E, of the Ringold Formation (DOE 2002; Peterson et al. 1996; H-artman and Lindsey 1993; Lindberg 1993a, b; Lindsey and Jaeger 1993). The Ringold Formation makes up the lower portion of the 2.4

vadose zone at the 100-K, 100-N, and the I00-D Areas. It is only partially present in the 100-B/C Area and not present in the I100-H- and 100-F Areas. The Hanford formation extends from the surface to just above the water table when the Ringold Formation is present. The Hanford formation extends beneath the water table and makes up the unconfined aquifer in the 100-H and 100-F Areas. The Ringold Formation Unit E is a fluvially deposited pebble-to-cobble conglomerate with a sandy matrix. It is characterized by complex interstratified beds and lenses of sand and gravel with variable degrees of cernentation. The gravel]-dominated facies of the Hanford formation occasionally exhibits an open framework texture composed of uncemented, clast-supported pebble, cobble, and boulder gravel with a coarsegrained sandy matrix and minor sand and silt interbeds or stringers. The clast size decreases in the lower portion of the Hanford formation. The Hanford formation is generally less cemented and more poorly sorted than the Ringold Formation and typically contains a higher percentage of angular basaltic detritus. Although clastic dikes have been observed in the vadose zone beneath the 100 Areas (Fecht et al. 1999), because of their limited areal distribution and lack of vertical continuity, they may not represent significant preferential pathways. However, these vertical features could represent natural cutoff walls that confine or limit plumes from spreading horizontally during wetting from a waste site; then later, under unsaturated conditions, be more conductive than the surrounding sediments (Murray et al. 2002). The contact between Ringold Unit E and the Hanford formation is important because the saturated hydraulic conductivity for the gravel-dominated sequence of the Hanford formnation is one to two orders of magnitude higher than the denser and locally cemented Ringold Unit F. Since hydraulic conductivity varies with the formation, different groundwater level responses could occur where channels now filled with the Hanford formation had been scoured into the Ringold Unit E. These buried channels could become preferential pathways for contaminated groundwater during high river stages.

Hydraulic Properties and Conditions. The physical properties of the vadose zone in the 100 Areas are not well characterized. Peterson et al. (1996) reported saturated hydraulic conductivity, moisture content, specific gravity, and bulk density for samples taken fromn the single-pass reactor areas. No scaling of hydraulic conductivity based on particle-size distribution was done for that report. Khaleel and Relyea (1997) published moisture retention data for the Il00-D, 100-F, and 100-H Areas. In the 100 N Area, Connelly et al. (199 1) collected 10 surface samples for moisture retention data and DOE (I1996a) collected four samples each from boreholes 199-N-1I08A and 199-N-1I09A. The measured physical properties for these samples vary widely reflecting the heterogeneity of the vadose zone. These data are recorded on the catalog of vadose zone flow paramneters for the Hanford Site (Freeman et al. 2002). The large volume of liquid discharges during operations created water table mounds 6 to 9 meters above the nominal water table under the retention basins and other liquid disposal facilities. Volumetric moisture content found in sediment under the 100-N Area liquid waste disposal facilities (DOE 1996a) appear to be high for the given sediment type and natural recharge rate. This suggests these soils are still draining.

2.5

Geochemical Properties and Conditions. Results from the geochemnical characterization studies in the 100 Areas show a contaminant zoning (chromatographic) effect in the vadose zone. For radionuclides and inorganic contaminants that are not adsorbed (i.e., tritium, nitrate), the large releases of water to the vadose zone at the retention basin and liquid waste disposal facilities quickly pushed these contaminants through the vadose zone, into the unconfined aquifer, and subsequently out to the Columbia River. Crews and Tillson (1969), using iodine- 131 isotopic analysis, estimated the travel time to the Columbia River from 1301 -N liquid waste disposal facility to be approximately 10 days during active disposal. Contaminants that show moderate adsorption such as strontium-90 show differential distribution (i.e., chromatographic zoning) within the vadose zone. Seine and LeGore (1996) examined characterization data from 12 boreholes within the 100-N Area and found that strontium-90 in the vadose zone is bound to sediment directly underneath the liquid waste disposal facilities in a relatively thin layer at depths that correspond to the elevated water table formed during operations. Seine and LeGore (1996) also reported the average bulk distribution coefficient (Kd) for strontium-90 to be 15 mL/g for these sediments. Contaminants with strong adsorption such as cobalt-60, cesium-137, and plutonium-239/240 remained within 1 meter of the bottom of the disposal facility. Contaminated sediment that is now part of the vadose zone should be considered a source termn for further downward migration to the water table. Further complicating the release of contaminants from the vadose zone in the 100 Areas is the seasonal and diurnal fluctuations of the Columbia River. A high river stage can cause the water table to rise into sediment containing higher concentrations of contaminants. Additionally, the chemistry changes caused by the constant re-wetting of the soil due to diumnal fluctuations could affect how the contaminants are released from the vadose zone (Petersen and Connelly 2001). 2.1.1.2

200 Areas

The 200 East and 200 West Areas are located on the Central Plateau of the Hanford Site. The vadose zone beneath the 200 Areas ranges in thickness from about 50 meters in the western portion of the 200 West Area (beneath the former U Pond) to 104 meters in the southern part of 200 East Area. The stratigraphy of the vadose zone varies significantly across the Cold Creek floodbar making up the Central Plateau. A generalized geologic cross section showing the general stratigraphy through the 200 Areas is shown in Figure 2.3. Hydrostratigraphy. The geology and hydrology of the 200 Areas have been extensively studied because they contain major sources of groundwater contamination (Hartman 2000). The major stratigraphic units making up the vadose zone include 1) glaciofluvial deposits of the Pleistocene-Age Hanford formation, 2) fluvial and/or colian deposits and paleosols of the Pliocene/Pleistocene-Age Cold Creek unit, and 3) the fluvial/lacustrine deposits of the Miocene/Pliocene-Age Ringold Formation. 200 West Area. The vadose zone beneath 200 West Area ranges from 50 to 80 meters thick and can be subdivided into six principal hydrostrati graphic units (Lindsey et al. 1992a; Connelly et al. 1992a; Thorne et al. 1993; Williams et al. 2002; DOE 2002). These units include two facies associations of the Hanford formation (gravel- dominated and the sand-dominated), two lithofacies of the Cold Creek unit (the fine-grained, laminated to massive facies, and the coarse to fine-grained carbonate-cemented facies) 2.6

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Individual polygonal cells are bounded by other polygons to form what is described as a honeycomb pattern when viewed from the air (Fecht et al. 1999). Vertically oriented clay skins within clastic dikes could locally act to form an impediment to lateral flow. Perhaps the most significant feature in the 200 West Area affecting vadose-zone transport is the finegrained and carbonate-cemented facies of the Cold Creek unit (Rohay et al. 1994), which represents an ancient buried calcic paleosol sequence (Slate 1996, 2000). Because of the cemented nature the Cold Creek unit, it is often considered impervious; however, it is also structurally brittle and, therefore, may contain many fractures that have developed during or since soil development. The degree of cementation varies considerably within the Cold Creek unit so that contaminants could breach the unit through discontinuities in cementation or structure. The Cold Creek unit which contains many weathering products (e.g., oxides and carbonates) may also chemically react with transported wastes with which it comes in contact. Immediately overlying the carbonate-cemented facies of the Cold Creek unit is the

2.7

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fine-grained, laminated to massive facies (formerly referred to as the "early Palouse soil") which has a relatively high moisture-retention capacity with a corresponding low permeability and would tend to retard the downward movement of moisture and contaminants. 200 East Area. The vadose zone beneath 200 East Area can be subdivided into six principal hydrostrati graphic units, including three units with in the Hanford formation, a fluvial gravel facies of the Cold Creek unit (equivalent to the Pre-Missoula Gravels), and two units belonging to the Ringold Formation (Lindsey et al. 1992b; Connelly et al. 1992b; Thorne et al. 1993; Williams et al. 2000; DOE 2002). The Hanford formation units include 1) an upper gravel-dominated facies, 2) a sand-dominated facies, and 3) a lower gravel-dominated facies. Over most of the 200 East Area the Hanford sand facies lies between the upper and lower gravel-dominated facies (Lindsey et al 1992b; Connelly et al. 1992b). Based on borehole samples, the upper and lower gravel-dominated facies appear to have similar physical and chemical properties. The Ringold Formation in the 200 East Area is, for the most part, eroded away in the northern half of 200 East Area. Here, the Hanford formation lies directly on top of basalt bedrock. With the dropping water table, basalt outcrops above the water table and, thus, is unsaturated beneath the northeastern portion of 200 East Area. Just south of 200 East Area, the water table lies within the Ringold Formation. Because the physical and chemical characteristics of the Ringold Formation, Member of Wooded Island, Unit A and Unit E gravels are similar, and because only a small portion of the vadose zone lies within Unit A, these units can be combined into a single hydrostratigraphic unit. Clastic dikes have also been observed in the Hanford formation beneath 200 East Area. The vertically oriented clay skins within clastic dikes could locally act to form an impediment to lateral flow. This could then cause ponding (perching) of the water and eventual breakthrough to underlying strata. 2.8

Sublinear to anastamnosing (braid-stream like) channel-cut scour and fill features occur within the Hanford formation and could act as preferential .pathways in the horizontal direction. Other types of heterogeneity are associated with stratigraphic pinch out or offlapping/on lapping of facies. Both the Ringold and the Hanford formations often contain relatively thin fine-grained stringers that can result in lateral spreading of moisture and slow down the vertical movement of contaminants within the vadose zone. Low-permeability layers, where they exist, often occur as single, relatively thick (meters or more) and continuous layers within the Ringold Formation. Low-permneability layers within the Hanford formnation, on the other hand, occur more frequently, yet are relatively thin (0.5 meter or less) and laterally discontinuous. Low-permeability layers within the sand-dominated facies of the Hanford formation are generally thicker and more continuous than those in the gravel1-domninated facies. Paleosols and some facies changes (i.e., the contact between fine grained and coarser grained facies) have been observed to be fairly continuous over the range of at least 100 meters and have been found to promote lateral spreading of crib effluent on that same scale. Hydraulic Properties and Conditions. Accurate predictions of flow and transport in the vadose zone require a detailed characterization of the hydrologic properties and their variability, and estimates of transport parameters such as dispersivity. In particular, data that are essential for quantifying the water storage and flow properties of unsaturated soil include the soil moisture characteristics (i.e., soil moisture content versus pressure head and unsaturated hydraulic conductivity versus pressure head relationships) for sediment in various geologic units. Data on particle-size distribution, moisture retention, and saturated hydraulic conductivity (K,) have been cataloged for over 248 samples from throughout the Hanford Site, including 12 locations in 200 East and West Areas (Khaleel and Freeman 1995; Khaleel et al. 1995; Khaleel and Relyea 1997; and Khaleel and Heller 2003). The soil retention data were corrected for gravel content and the main drying curve. The saturated hydraulic conductivity was measured on intact, undisturbed splitspoon sleeve samples. After the data were corrected and cataloged, hydraulic parameters were determined by fitting the van Genuchten soil-mnoisture retention model to the data. Macrodispersivity estimates for non-reactive species have been estimated using the Gelhar and Axness (1983) equation where the longitudinal macrodispersivity depends on the mean pressure head. Khaleel (1999) estimated a longitudinal macrodispersivity of about 100 centimeters for the sanddominated facies of the Hanford formation in 200 East Area. The transverse dispersivities have been estimated as one-tenth of the longitudinal values (Gelhar et al. 1992). Ward et al.(') obtained dispersivity estimates via field measurements at a location close to the immobilized low-activity waste site, using potassium chloride (Kr.,) as a tracer. Analysis of the data provided dispersivities that ranged from 1.3 to 7.8 centimeters for travel distances ranging from 25 to 125 centimeters. Dispersivity increased with depth to about 0.75 meter, after which it essentially became constant. These estimates are for the Hanford formation, but the transport distance within the vadose

(a) Ward AL, RE Clayton and JS Ritter. 31 December 1998. "~Hanford Low-Activity Tank Waste Performance Assessment Activity: Determination of In Situ Hydraulic Parameters of the Upper Hanford Formation." In Letter to Dr. Fredrick M Mann from AL Ward dated 31 March, 1999. 2.9

zone is indeed of limited extent. Nevertheless, results based on the limited data are consistent with the concept of a scale-dependent dispersivity. Thus, although no data exist on large-scale dispersivities for the vadose zone, It is expected that they will be larger (as is suggested by the longitudinal dispersivity estimate of 100 centimeters) than those based on the small-scale tracer experiment of Ward et al.(') Based on a survey of literature, Gelhar (1993) examined the longitudinal vadose zone dispersivities as a function of the scale of the experiment, and found an increase of dispersivity with an increase in scale. Geochemical Properties and Conditions. The Hanford formation sediment consists of glaciofluvial materials. The mineralogy of this sediment is highly variable depending on grain size. Gravel-dominated sediment tends to have a high degree of rock fragments (mostly basaltic, with some plutonic, metamorphic, and detrital caliche fragments) (DOE 2002). Microprobe analysis of the sand and finer-grained fraction has found it to be dominated by quartz (18 to 67. 1% by weight), plagioclase (5.1 to 41.5%) and Microcline (1.8 to 30. 1%) (Tallman et al. 1979; Seine et al. 1993; Xie et al. 2003). Other dominant minerals include amphiboles up to 36.6%, pyroxenes up to 27.5%, Mica (Biotite/1Ilite) up to 13.1%, and calcite up to 6.5% by weight. Smectite clays represent a few weight percent of the bulk sand fraction (3.3 to 5% [Seine et al. 1993]) and generally dominates in the clay fraction (Tallman et al. 1979). Hanford formation sediment is typified as having low organic carbon content generally <0.1I% by weight (Seine et al. 1993 ) and low-to-moderate cation exchange capacity (2.6 to 7.8 inilliequivalents per 100 grams, Seine et al. 1993). The sediment has a slightly basic pH when wetted (Seine et al. 1993 found that the pH of saturation extract ranging from 7.66 to 8.17). Small amounts of detrital calcium carbonate (calcite) are common and can act as a weak buffer. Much less mineralogy data are available for the Cold Creek unit. Tallman et al. (1979) found that the sediment they referred to as Early "Palouse" Soil are fairly similar in mineralogy (25.3 to 29.4% quartz, 15.1 to 18.2% plagioclase, 15 to 17.8% microcline, 7.9 to 10% amphiboles, 1.3 to 12.5% micas), but generally have higher in calcite (8 to 8.8%), and lack pyroxenes. Bjornstad (1990) found similar results for these fine-grained sediment, but found that the carbonate-rich facies (referred to as the PlioPleistocene unit) consisted predominantly of calcium carbonate and/or sedimentary rock fragments, with lesser amounts of quartz and feldspars. Thin beds of caliche with calcite predominate and variable amounts of ferric oxide exist in the 200 West Area in the Cold Creek unit just above the Ringold Formnation. Xie et al. (2003) found significant differences in electron microprobe and petrographic results between the Hanford and Ringold Formnations. The Ringold Formnation sediment is generally higher in quartz but lower in plagoclase and pyroxene. Deeper within the Ringold Formnation, calcic/ferric oxide cements are often present. The cementing can alter significantly the permeability of the otherwise coarsegrained Ringold sediment.

(a) Ward AL, RE Clayton and JS Ritter. 31 December 1998. "Hanford Low-Activity Tank Waste Performnance Assessment Activity: Determination of In Situ Hydraulic Parameters of the Upper Hanford Formation." In Letter to Dr. Fredrick M Mann from AL Ward dated 31 March, 1999. 2.10

Empirical &~data describing contaminant adsorption for Hanford formation, Cold Creek unit, and Ringold Formation sediments are fairly well characterized for dilute waste solutions and groundwater (Cantrell et al. 2002, 2003a). Fewer Kd data are available for high ionic strength waste solutions with slightly acidic to slightly basic pH- values. A relatively small amount of Kd data exists for the combined high ion ic-stren gth/h igh ly-basic tank liquors for many common radionuclides. These distribution coefficient (Ks) data have been well tabulated by Cantrell et al. (2003a), Kincaid et al. (1998), Seine and Wood (1990), Kaplan and Seine (1995), and Kaplan et al. (1996, 1998). In most instances, adsorption is assumed to be the controlling geochemical process but neutralization of acid waste by the alkaline sediment and neutralization of basic tank waste can cause precipitation of some macro and many minor contaminant species within the sediment pores. Outside the zone of pH neutralization, adsorption is considered to be the dominant contaminant retardation process in the vadose zone. The geochemical processes that affect contaminant migration and mineral alteration within the vadose zone sediment for both 200 East and 200 West Areas are quite similar. Some subtle changes should be considered as the fine-grained sediment and caliche zone above the Ringold are less prevalent in 200 East Area. 2.1.1.3

300 Area

The vadose zone beneath the 300 Area ranges in thickness from about 15 meters to less than I meter along the Columbia River. Hydrostratigraphy. The geology of the vadose zone consists almost entirely of the Pleistocene Hanford form-ation with a thin veneer of Holocene eolian sand. Thin portions of the Ringold Formation may also extend above the water table in portions of the site. Schalla et al. (1988) described the eolian sand deposits as ranging from 0 to nearly 4.6 meters thick. Where missing, these deposits are thought to have been removed by construction activities and often replaced by or covered with construction gravel. The geologic contact with the underlying Hanford fon-nation is quite distinct. Schalla et al. (1988) described the Hanford formation as poorly sorted sandy gravel with some silt and local sand stringers. The upper portion was described as containing pebble to boulder gravel that grows finer with depth. The gravel fraction is described as mainly basaltic in nature with some quartz-rich and mnetamorphic clasts. The thickness of the Hanford formation varies fromn 6.4 to 24.7 meters. Gaylord and Poeter (1991) describe the Hanford formation beneath the 300 Area as consisting predominantly of three lithofacies: gravelly sand, sandy granule to pebble-size gravel, and sandy cobble to boulder-size gravel. They further indicate that finer grained sand facies, comprising only a minor percentage of the 300 Area Hanford formation deposits, are concentrated in the southern part of the area intermixed with the coarse-grained gravel dominated deposits. In an attempt to define the spatial distribution of hydrologic properties (primarily aimed at thle unconfined aquifer) Gaylord and Poeter (199 1) broke the 300 Area sediment into four general hydrofacies. These hydrofacies were defined based on grain size and sorting, recognizing the importance of the fine-grained component to hydraulic behavior.

2.11

Based on the available geologic information for the 300 Area, the hydrostratigraphy of vadose sediment can be broken into five different units: 1) backfill (or surface cover); 2) eolian sands (if still present at the waste site); 3) sand-dominated Hanford sediment; 4) gravel-dominated Hanford sediment; and 5) gravel-dominated Ringold sediment (if present above the water table). Although these sediments are primarily coarse, it must be recognized that some silt stringers and fine-grained rip up clasts (some over 1 meter in diameter) are present, particularly in the Hanford formation. The location and extent of these stringers is uncertain. It must also be recognized that sedimentary structures (e.g., stratification, grading bedding, forset bedding) impart some degree of heterogeneity and anisotropy in each of the units; however, again there is insufficient data to adequately portray these characteristics. Hydraulic Properties and Conditions. Schalla et al. (1988) presented the results of physical (e.g., field moisture content, water retention, particle-size analysis) and bulk geochemnical analyses of selected samples. The field water content ranged from <2 to nearly 5% by weight. Geochemical Properties and Conditions. Gaylord and Poeter (1991) also provided whole rock geochemnical (via x-ray fluorescence) and rare earth/trace element (inductively coupled plasma/mass spectroscopy [ICP/MS]) analyses for the Hanford and Ringold Formations. These data are similar to those for Central Plateau sediment (Xie et al. 2003). Existing sorption data are rather limited for the 300 Area (Cantrell et al. 2003 b), therefore sorption parameters must be derived from an assessment of the waste chemistry and existing sorption values from other Hanford site sediments (similar to the selection process used in the Hanford composite analysis [Kincaid et al. 1998]). Without site-specific geochemical data, values for the geochemnical properties (i.e., Kd values) will have to be estimated from the sediment type (e.g., grain-size data and the presence of secondary mineralization like the Fe oxide coatings often found in the Ringold Formation) and waste type. The mineralogy and contaminant adsorption properties of the Hanford formation sediment in the 300 Area are thought to be quite similar to those in the 200 Areas such that the extensive Kd data base (Cantrell et al. 2003b) should be adequate for the 2004 Composite Analysis. 2.1.2

Events

Various events to be considered in the conceptual model include those that are naturally occurring (e.g., meteoric recharge), those that are manmade (e.g., intentional or unintentional contaminant and water releases), those that occur slowly over a long period of time, and those that represent extreme or unusual occurrences (e.g., 500 year stormns, volcanism). A brief synopsis of some of the important types of events that should be considered are presented in the following sections. 2.1.2.1

Recharge Events

The long-termn natural driving force for flow and transport through the vadose zone is precipitation that has infiltrated below the zone of evaporation and the influence of plant roots. Such water eventually flows to the water table, carrying with it whatever dissolved species may be present. Gee et al. (1992) presented evidence from multiple experiments showing that measurable diffuse natural recharge occurs across the lower elevations of the Hanford Site, with rates ranging from near zero in undisturbed shrubsteppe plant communities to more than 100 mm per year beneath the unvegetated graveled surfaces of tank farmns. 2.12

The arid climate setting, with cool wet winters and dry hot summers at the Hanford Site dictates that recharge potential is greatest in winter (Gee et al. 1992). During winter months at Hanford, precipitation is greatest and evaporation potential lowest; therefore, precipitation has the greatest chance to infiltrate into the ground. This type of recharge can occur as either diffuse or focused recharge. How much each event contributes is site- and event-dependent. Water runoff from the higher elevations occurs intermnittently because of frozen ground and, while infrequent, can be extensive (e.g., Pearce et al. 1969). Cushing and Vaughan (1988) indicate runoff from higher elevations has a 3.8-year return period. Extensive water runoff does not appear prevalent at the Hanford Site between Highway 240 and the Columbia River based on the absence of geomnorphic features such as erosion rills and gullies. For undisturbed (natural) sites in the 100 and 200 Areas at Hanford, there is typically gentle terrain and coarse soil that foster diffuse recharge. In contrast, at disturbed waste sites there can, at times, be localized ponding that gives rise to focused flow particularly under conditions of rapid snowmelt. Observations have revealed that local runoff does occur at waste sites when there is a heavy rain, quick snowmelt, or the ground is frozen (e.g., Gee and Hillel 1988; Jones 1989; Ward et al. 1997). 2.1.2.2

Source/Release Events

Another source of water that transports contaminants originates from industrial activities. Historically, millions of gallons of contaminated water were disposed to subsurface infiltration structures and surface ditches and ponds. Such unregulated disposal ceased several years ago. Currently, two facilities are permitted to discharge to the vadose zone: the State-Approved Liquid Disposal (SALD) Facility and the Treated Effluent Disposal Facility (TEDF). Discharges from these facilities are closely monitored and regulated. Numerous discharges of water, collectively called miscellaneous streams, are also permitted but do not need to be monitored unless they exceed certain discharge rates and annual amounts (DOE 1998). These streams include hydrotesting, maintenance, construction, cooling water and steamn condensate, sanitary wastes, and storm water control. Also unregulated but possible sources of additional recharge water are roads, road shoulders, parking lots, power and fire lines, and all structures that do not have precipitation controls that fall under the miscellaneous streams permit. Source events include accidental or intentional discharges of fluids, gases, and contaminants to the environment. Unintentional releases include spills, tank leaks, and distribution pipe leaks. The quantity, quality, duration, and phases of waste or fluid released are generally unknown. These events also include remediation activities that involve the injection of liquid, chemicals, gases, and heat. 2.1.2.3

Discharge/Exit Events

Discharge or withdrawal events include all actions to remove fluids, gases, and contaminants from the environment. These events must be characterized for quantity, quality, duration, and phases of waste or fluid removed. These events include remediation activities such as groundwater pumnping, vapor extraction, and heat removal (e.g., cryogenic barriers).

2.13

2.1.2.4

Climate Events

A change to a drier and/or warmer climate could result in a sparser plant community, a change in the mix of plant and animal species, increased wind erosion and deposition (e.g., re-activated sand dunes), and changes in natural recharge. The stress of this change could allow non-native plant and animal species to supplant native species. 2.1.2.5

Volcanism

Volcanic activity has the potential to deposit significant quantities of ash. Such deposition could reduce evaporation and plant activity for years, which could increase the natural recharge rate. 2.1.2.6

Seismicity

Earthquakes and other related events, such as fault rupture, landslides, or differential settlement could potential effect the integrity of surface or subsurface structures, potentially impacting recharge and vadose zone transport. 2.1.2.7

Flooding Events

Natural flooding in the Columbia River is predicted to affect low-lying areas along the river but not the 200 Areas. Failure of the upriver dams has the potential to affect the entire Hanford Site. The probable maximum flood in the Cold Creek drainage basin could affect the southwestern portion of the 200 West Area (Skaggs and Walter 198 1). Under this scenario, water from the flood would reach the Yakima River. 2.1.2.8

Human Disturbance Events

Human activities are capable of degrading surface covers over waste sites and exposing the waste to increased recharge and more direct contract with the biosphere. 2.1.3

Processes

The primary processes governing flow and transport through the vadose zone are complex and interrelated. These processes depend on the physical and chemical nature of the geologic materials that make up the vadose zone (described above) as well as the types, amounts, and compositions of the fluids that occupy the pore spaces (Looney and Falta 2000, p. 13). At a high level, one can discuss these processes in terms of the mechanisms, rates, and routes by which contamninants move (or are moved) through the vadose zone to the water table (i.e., fluid flow, physical transport, and the capillary fringe) and the fate of the contaminants (i.e., physical and chemical interactions, decay and decomposition). 2.1.3.1

Transport Mechanisms

For the majority of contamninants, movement through the vadose zone is contingent on being dissolved within flowing water (i.e., aqueous phase drainage). The flow of water through the unsaturated soils depends in complex ways on the rate of water infiltration, moisture content of the soil, textural 2.14

heterogeneity, and soil hydraulic properties. Infiltrating water provides the primary driving force for downward mnigration of contaminants. Perched water zones and lateral spreading may develop when water moving downward through the vadose zone accumulates on top of low-permeability soil lenses, highly cemented horizons, or above the contact between a fine-grained horizon and an underlying coarsegrained horizon. Unsaturated hydraulic conductivities may vary by several orders of magnitude depending on the water content of the soils. Some contaminants (as well as water) are volatile and move in the gas phase. The hulk of this movement is diffusional, but convective flow can occur near the soil surface and near open boreholes in response to barometric changes. Remediation activities (e.g., vapor extraction, thermal treatment) can also affect local convective gas flow. The geothermal gradient has a small but steady impact on the movement of water upward through the vadose zone. Enfield et al. (1973) used field measurements of temperature and matric potential at a site about I km to the south of the 200 East Area to calculate an upward water flux of 0.04 mm per year. 2.1.3.2

Transport Rates

Fluids such as water move through the vadose zone at rates determined by the hydraulic, thermnal, and vapor gradients and the relevant properties of the sediment. For many applications, common assumptions include a static air phase, isothermal conditions, and no density effects. With these assumptions, flow rates are calculated using Richards equation with gravity and capillary potential gradients. When these assumptions are not appropriate (e.g., organic liquids, vapor flow, hot saline tank waste), more sophisticated equations must be used to calculate rates. The rate of recharge at a particular location is influenced by five main factors: climate, soil, vegetation, topography, and springs or streams. Other factors can significantly impact recharge by affecting one or more of the main factors. These other factors include soil development, animal activity, fire, water and wind erosion and deposition, plant community changes, disturbance, and human structures (e.g., roads, buildings). The rate of recharge at each waste site will depend on the design of the surface cover. Plants and animals live within the upper I to 2 meters of soil, and some plant roots can reach depths of 3 meters. Surface covers can be designed to protect against such intrusion by including biobarriers, which are layers that resist biotic intrusion. Coarse gravel layers have been shown to be ineffective at preventing root and insect intrusion, but they appear to deter animal intrusion. For thinner cover designs, the biobarrier may be closer to the surface and more susceptible to degradation. Intrusion of surface covers by plants and animals can create macropores that could become conduits for surface water to flow into the soil much deeper than expected. Inadvertent intrusion by humans can result in surface depressions that could become areas of focused recharge when surface runoff occurs. Some of the liquids that were disposed or leaked to the vadose zone had properties that differed significantly from the properties of pure water. Because their properties differed fromn those of water, their rate and route of movement through the vadose zone may differ fromn those of water. The specific gravity of waste that has leaked from single-shell tanks ranged from 1.1 to 1.65, which could enhance the transport of contaminants. Increased density has been demonstrated to elongate contaminant plumes

2.15

vertically and reduce lateral spreading caused by stratigraphic variations in hydraulic properties (Ward et al. 1997). The properties of these fluids will change as contaminants are diluted, sorbed, or the fluid evaporates into the sediment air space. Organic fluids were also disposed at Hanford. The movement of these fluids through the vadose zone and groundwater aquifer is complex because it involves flow in multiple phases: the organic liquid phase, the dissolved phase in water, and the vapor phase in the vadose zone air space. The movement of organic fluids can be enhanced if their density is much higher than the density of water. That is the case for the primary organic fluid contaminant at Hanford - the dense nonaqueous phase liquid, carbon tetrachloride. Between 1955 and 1973, roughly 577 to 922 metric tons of carbon tetrachloride was disposed to three subsurface infiltration facilities at the Hanford Site (Rohay et al. 1994). The current groundwater plume containing concentrations above 0.5 mg/L covers an area of about I11square kilometers. Soil-vapor extraction and pump-and-treat activities have been employed to prevent further movement of the plume and reduce contaminant mass. Efficiencies of the vapor extraction activities have decreased. The pumpand-treat activities may be having an impact, because the extent of the plume has not increased. The behavior of carbon tetrachloride in the subsurface and in the vadose zone is poorly understood and requires additional characterization and assessment to determine the important processes governing its fate and transport. The rate of gas movement in the vadose zone will be affected by the magnitude of any temperature gradients. The vadose zone across the entire Hanford Site experiences temperature changes that arise from the diurnal and seasonal temperature changes at the soil surface. The magnitude of the temperature changes diminishes with depth; at 10 meters, the seasonal change appears to be less than I 'C. Nearsurface temperatures appear to have a minimal effect on recharge rates if the rates exceed 10 millimeters per year, but they could be important when rates are less. In addition to the near-surface temperature changes, a steady upward geothermnal gradient exists that drives gas (and water vapor) upward. The elevated temperatures of the leaked waste from the single-shell tanks and previous operational discharges could have induced local movement of both liquids and vapor. The formation of colloids and occurrence of colloid-facilitated transport of contaminants were identified by the Expert Panel as a potentially important process for the vadose zone (DOE 1997). For most waste sites at Hanford, the low water contents and simple geochemistry are not conducive to colloid formation or colloid-facilitated transport. However, for the large-volume discharges and waste from leaking tanks, the conditions existed for both colloid form-ation and colloid-facilitated transport. However, insufficient data exist at the Hanford Site to adequately characterize the potential for colloidal transport under these conditions. 2.1.3.3

Transport Pathways

Because gravity is the dominant force that moves liquid downward, the predominant direction for contaminant movement is downward. Variations in the hydraulic properties and the presence of impeding features such as bedding interfaces, caliche layers and disposal facilities can locally alter and redirect the movement laterally. Various preferential pathways such as clastic dikes and fractures are capable of concentrating or contributing to phenomena such as fingering and funnel flow. Preferential flow has been documented along poorly sealed well casings at the Hanford Site (Baker et al. 1988) and transport along 2.16

elastic dikes has been postulated to be potentially important (DOE 1997). Relatively simple stratigraphic layering can give rise to complex water content distributions and enhanced lateral spreading that impedes vertical migration of contaminants. Because of the nature Zone Expert Panel (DOE in the Hanford geology is possible preferential flow

of some waste, local routes of contaminant movement will vary. The Vadose 1997) stated that the likely mode of transport for leaked or disposed tank waste along preferential, vertical, and possibly tortuous pathways. They identified caused by:

* Hot (1 77 0 CQ caustic tank waste leaking into the vadose zone, flashing to steam, fracturing the matrix, and enlarging pores " Hot (I 77'C) caustic tank waste leaking into the vadose zone with a self-healing nature, creating geothermal convection systems that could move contaminants upward and the hot alkaline slurry reacts with Hanford sediment * Dissolution of siliceous sediment by the hot and alkaline tank waste, which could increase porosity in some places (by dissolution) and lower porosity in others (by precipitation) 2.1.3.4

Contaminant Behavior

The fate of contaminants in the vadose zone depends on geochemical conditions, the speciation of the contaminant, residence time, and microbial activity. Sediment has the capacity to sorb most contaminants from solution. The amount of sorption is a function of many factors, including mineral surface area and type, contaminant type (speciation) and concentration, overall solution concentration, pH, Eh, and reaction rates for the controlling adsorption or precipitation, dissolution, and hydrolysis reactions. Some contaminants do not sorb at all (i.e., soluble anions such as nitrate, chromate, and protectonate) and are moved along with the bulk solution. The movement of contaminants through the vadose zone is affected by their sorption in the far-field and sometimes by complex dissolution/precipitation reactions between waste liquids of extreme pH and the slightly alkaline sediment in the near field. The significance of sorption is that it delays downward movement of the contaminant and allows degradation processes to occur (e.g., radioactive decay) and, for some, irreversible incorporation into the sediment. Sorption can be described using a simple linear relationship (i.e., a distribution coefficient or Kd) that is determined empirically. Values of Kd have been measured for a wide range of contaminants and waste types at the Hanford Site (Kincaid et al. 1998). The Kd approach is applicable for conditions at Hanford where the contaminant concentrations are low and the chemistry is relatively constant. However, conditions near some waste sources are so variable due to the strong influence of the waste that the Kd approach may not be applicable. Such is the case for the hot, highly concentrated tank waste in contact with Hanford sediment. The general consensus is that the presence of this waste will likely decrease the sorption of contaminants (e.g., cesium- 13 7). The net effect will be an increase in their mobility until conditions in the sediment (e.g., lower concentrations via waste dilution) become more appropriate for the Kd approach. The complex reactions that occur between the sediment and the highly acidic and (more importantly for 2.17

Hanford) highly basic wastes are currently under study. Future SAC revisions will determine whether more complex chemical reaction processes should be considered to increase the accuracy of transport models used to estimate migration rates of key contaminants of concern. Contaminants that exist in the gas phase (e.g., radon, carbon-14, carbon tetrachloride) are subject to atmospheric venting and remediation activities such as vapor extraction. Carbon-14 as carbon dioxide also reacts strongly with alkaline earth cations to formn insoluble carbonates at neutral to basic pH values. Further it reacts with cement, a common constituent of waste form containers and structures used in many solid waste burial grounds, to form carbonate precipitates (Krupka and Seine 1996; Seine et al. 1992). Contaminants near the soil surface are subject to animal and plant uptake. Plants and animals live within the upper I to 2 meters of soil, and some plant roots reach depths of 3 meters or more. Waste present within this zone is subject to ecological uptake and dispersal above ground. Contaminants that are consumed by microbes are subject to degradation into other compounds that may or may not be considered contaminants. This degradation process depends on the presence of a microbial population that is capable of degrading the contaminant(s) in question and the availability of any additional nutrients that may be required for the microbes to be effective. Sometimes it is the water that is consumed rather than the waste. Waste forms such as the immobilized low-activity waste undergo a corrosion process that consumes water. In a dry disposal, this consumption process will create a water vapor gradient that draws vapor toward the waste form.

2.2

Uncertainty and Unresolved Technical Issues

Unresolved technical issues and sources of uncertainty affect the ability to predict the behavior of contaminants in the vadose zone. These include property representation, scale effects, spatial and temporal resolution of data, preferential flow, funneled flow, colloid transport, density effects, and thermal effects. Many of these issues are not addressed in this data package but may be addressed in later revisions of the composite analysis after resolution of key issues by the science and technology program. Disdussions of outstanding issues are generally focused on performance/risk assessment under future conditions and future releases. However, there are also site characterization and laboratory study needs related to interpreting observations from past tank leaks, spills, and nearby intentional discharges. This information, i.e., interpretation of site characterization data, is important to estimate existing inventories for use as initial conditions and also to demonstrate the validity of our understanding and the predictive ability of the models used for flow and transport of contaminants. Interpreting the mass and distribution of contaminants is difficult because there is much about the history and character of the leaks, spills, and water losses that is difficult to characterize. The resulting uncertainty will always hamper the ability of models to predict observed distributions of contamninants in the vadose zone, even if the distributions are well known.

2.18

2.2.1

Property Representation

The physical, chemical, and hydraulic properties of the various solids, liquids, and gases in the subsurface are typically represented within numerical simulators using mathematical functions. The form of these functions, and their resulting suite of parameters, change as more process knowledge and characterization information becomes available. Good examples are the water retention and hydraulic conductivity properties of the sediments. The parameters for these functions are determined by fitting them directly to data or by inferring them from physical properties. Many functions have been proposed to represent hydraulic properties. One of the most commonly used hydraulic models is the van Genuchten-Mualem model (Kosugi et al. 2002). A standard practice is to fit the van Genuchten retention model to retention data and the saturated conductivity value and use the resulting parameters with the Mualeni conductivity model to predict unsaturated conductivity values. In this standard approach, the Im"parameter is fixed equal to 1-1/In and the pore interaction term is fixed at 0. 5. This approach has been shown to work for a number of soils, but examples exist to show that it is not universally applicable and that, for many soils, it becomes increasingly less applicable as the soil dries out (e.g., Stephens 1992; Khaleel et al. 1995). Predictions of dry-end conductivity can be improved by including one or more measured values of unsaturated conductivity in the fitting process and excluding the saturated conductivity value. Improvements can also be obtained by treating the Im" parameter as independent and fitting both Im"and the pore interaction term. The drawback to increasing the number of finting parameters is the possibility of obtaining a non-unique set of parameter values during the finting process. Some soils have unique structural features such as fractures and macropores that make them less amenable to characterization using a single function like the van Genuchten function. For such cases, Dumner (1992) and others have proposed multiple functions, either linked or combined. The resulting fits to the data are better, but the number of parameters is so large that these techniques are not often used. To date, nearly all analyses at Hanford have used a single van Genuchten-Mualem function to represent hydraulic properties. Many have used the standard approach of finting to retention and saturated conductivity data, but a portion have included an unsaturated conductivity value in the finting process (Khaleel et al. 1995). As more knowledge is gained and the original data evaluated more fully, the parameter values can be revised such that uncertainty in the conductivity predictions can be reduced.

2.2.2

Effects of Scale

One of the greatest challenges facing the composite analysis and similar efforts is adequately understanding the effects of spatial and temporal scale related to processes, observation, modeling, and assessments. Not a lot is known about how vadose zone processes, at various spatial and temporal scales, interact, which ones are dominant, and how these interactions can be related to and interpreted from existing field and/or laboratory observations. It is also difficult to determine what must be measured and modeled to assess both risk and the ability of the models to assess the risk within useful uncertainty bounds (i.e., to determine the validity of the models). In past assessments, the hydrogeologic units were generally assumed to be homogeneous and isotropic in character. In reality, these units display complex inter- and intra-sedimentary structures at various scales. The effects of these complex structures are generally thought to enhance lateral spreading and impede downward migration. However, some of these structures might also promote "'funneled flow"

2.19

and/or the development of "fingered flow." Thus, the effect of these small-scale structures needs to be more thoroughly understood and properly accounted for in the assignment of physical properties (e.g., effective permeability, porosity, moisture retention characteristics, anisotropy, dispersivity) to the larger modeled units. The effects of small-scale structures on large scale flow and transport parameters also needs to be assessed to understand the degree of uncertainty, to make appropriate choices for bounding calculations and to determine the effects of simplification on assessment predictions. Scaling and volume averaging tools are needed that can be used to determine effective values of parameters from small scale (often disturbed) borehole samples in conjunction with soft information on the fine-scale structure of these sediments. Data are lacking for much of the vadose zone where the analysis will be focused, so scale-up and volume averaging will be required. The justification of upscaling and averaging will need to be evaluated either deterministically or by a probabilistic assessment that clearly reflects the uncertainties involved in the analysis. 2.2.3

Spatial and Temporal Resolution of Site Data

The resolution of the nature and extent of various hydrogeologic units beneath a given waste site, based on borehole samples, is generally on the order of 1.5 meters vertically and tens of meters or more horizontally, and the minimum discemnable thickness of fine-grained units is thought to be about 15 centimeters. Also, the intemnal structure of these sedimentary units may have been lost in the drilling and sampling process. Vertical borehole data alone cannot provide the quality and quantity of data needed for accurate analysis of vadose zone transport. Thus, much of our knowledge on the internal structure and heterogeneities of these units comes from extrapolation of qualitative examination of "4representative" outcrops. At the Hanford Site, only a few limited geostatistical studies have been conducted to quantitatively describe the internal structure and heterogeneities in outcrop and core samples. Thus, in many cases there is currently a lack of site specific data to support the development of detailed three dimensional geologic models for a given waste site. 2.2.4

Preferential Flow

Preferential pathways are important for contaminant transport associated with tank-farm releases and/or other low-volume discharges where mobile constituents have not yet been flushed through the vadose zone. However, it is important to differentiate between structurally controlled flow and unstable flow. Structurally controlled flow occurs when the structure of the porous medium or the presence of a buried structure (e.g., tank) routes the water along a "preferential path." Unstable flow or wetting-front instability occurs during infiltration when an instability develops at the fluid-fluid interface (e.g., waterair, dense nonaqucous phase liquid water). 2.2.4.1

Structure Controlled Flow

Preferential flow is greatest when the preferred flow path consists of a series of connected large pore spaces. Because flux is proportional to the fourth power of the pore radius, large pores transmit very large quantities of fluid, but only when the pores are filled. Thus, water content determines the effectiveness of preferred pathways to conduct water. When water contents are high (at or near saturation),

2.20

preferred pathways can conduct copious quantities of water. When water contents are low (dry vadose zone), preferred pathways with large pores do not conduct water because they cannot fill with water. Whenever there are variations in sediment properties, the potential exists for water flow to be affected. The capillary barrier effect is a good example. The arrangement of fine textured material over coarsetextured material temporarily delays the downward migration of water and allows it to be evaporated and transpired back into the atmosphere. The net effect is that deep drainage is reduced. Such textural breaks are used for surface covers, but they also occur naturally throughout the vadose zone. When such "capillary breaks" are sloped, the water that is retained above the break can move laterally. In fact, this feature has been used to improve the performance of waste disposal facilities in the vadose zone (Frind et al. 1977). Clastic dikes and unsealed boreholes may potentially act as preferential flow paths for saturated flow by providing large connected pore spaces. These features are especially effective as preferred pathways when they cross-cut the normally horizontally layered sedimentary sequences. The actual influence of clastic dikes on flow is somewhat uncertain; whereas some portions of clastic dikes have large connected pore spaces, other portions have fine-grained clay skins that may actually limit high rates of lateral flow (Murray et al. 2002). Wood et al. (1995, 1996) and Jacobs (1999) suggested that both clastic dikes and unsealed boreholes are insufficiently large and continuous to be significant with respect to the overall contaminant mass transport through the vadose zone. A recent field study of clastic dikes suggested that dikes are not important preferential flow and transport pathways when the drainage flux was less than 100 mm/yr (Murray et al. 2003). Thus, these potential pathways are not considered dominant enough features to be incorporated into an assessment on the scale of the 2004 Composite Analysis. 2.2.4.2

Unstable Flow

Unstable flow fingering seems to develop when a saturated fine-grained textured soil overlies a coarse-grained soil. Water accumulates in and over the fine-grained unit until the thickness of the perched water provides sufficient driving force to allow the water to "drip" into the large pore spaces of the underlying coarse-grained sediment. This situation results in fingers with inner cores that are saturated surrounded by an unsaturated layer. However, fingers that are clearly caused only by the instability of a wetting front have been primarily observed in the laboratory. There is a commonly held belief that unstable flow or fingering may be an artifact of the uniformn, horizontal, and homogeneous layers (e.g., glass beads) used in the laboratory experiments. The phenomena may or may not occur in natural structured geologic media. If it does, the following questions need to be addressed: " What effect does the fine-scaled structure that typically involves alternating coarse-grained and finegrained layers do to enhance or deter the formation of unstable flow fingers? " How does this fine structure change the scale of fingers and relative speed up of the transport process (i.e., the effect of bypassing)? Experiments by Yao and Hendricks (1996) found that at low infiltration rates wetting fronts stabilize because under these conditions capillarity dominates over gravity; thus, there is no mechanism to cause instability and no fingers form. They further found an increase in the number and a decrease in the size of

2.21

fingers as the infiltration rate increased. Similar studies are needed to address finger formation and its scale when the fluid properties differ from these of water at amnbient temperatures (e.g., high density fluids, hot liquids). 2.2.4.3

Temporal Effects

In dry environments, deep vadose zone flow (i.e., recharge to the aquifer) can be dominated by the extreme transient events (e.g., snowmelt and run-on events) if they result in saturated or nearly saturated conditions in regions with fast preferential pathways. Proper assessment of deep recharge and effects related to enhanced transport down borehole annular space or any near surface preferential pathways and/or man-made structures must be addressed at a higher resolution both spatially and temporally. How spatial and temporal variations (particularly the extreme events) interact with heterogeneity and interfaces (particularly sloping ones with breaks or holes) to change the pathway and rates, needs more investigation. The effects of geologic complexity and the spatial and temporal complexity of adjacent, interacting sources (e.g., water line leaks, fire hydrant flushing, adjacent cribs) have also not been adequately addressed. 2.2.4.4

Funneled Flow Coupled with Colloid Transport

The Tank Waste Remediation System (TWRS) Expert Panel (DOE 1997) hypothesized that structure controlled flow coupled with colloid transport was the most likely mechanism to move large quantities of contaminants (such as cesium- 137). If important to the transport of key contaminants, this combination of processes needs to be investigated. Research is currently underway to investigate the impact of colloids on contaminant transport in Hanford sediment (Zhuang et a]. 2003; Cherrey et al. 2003). 2.2.5

Temperature and Density Effects

Other important issues raised by the TWRS Expert Panel relate to how the hot (I 770CQ caustic waste from tank leaks interacts with the geohydrologic system through time to affect both the fluid movement and contaminant transport processes. Many of the heat effects related to the high temperatures of the tanks, elevated temperatures surrounding the tanks, and self-heating nature of the leaked waste have yet to be investigated and resolved. The high heat load of the single-shell tanks coupled with vapor transfer could potentially set up a systemn whereby soluble briny waste, leaked from the tank, could migrate toward the heat source (e.g., center of the bottom of the tank). The possibility of a heat pipe being created needs to be investigated, as does the nature and scale of the effect. In addition, the possibility that the high heat lowered infiltration rates needs to be investigated. Density effects have only been investigated to a limited degree (e.g., Ward et al. 1997). These studies did not fully investigate the interactions of density with temperature, unstable flow effects, structurally controlled preferential flow (e.g., elastic dikes), colloidal transport, and/or waste-soil chemical and physical effects to determine inter-relationships and importance among the processes.

2.22

2.2.6

Geochemical Processes

As discussed in detail in the Groundwater/Vadose Zone Integration Project Specification (DOE 1998) and Science and Technology Summary Description (DOE 2000), more studies are needed to improve the knowledge and databases for the vadose zone. The vadose zone is not well characterized in a quantitative fashion. Field studies will corroborate lab tests and extend the time to study reactions from months to tens of years. Field studies will allow some key questions to be investigated such as the extent of existing physical, chemical, and mineralogic associations between contaminants and major chemical components in the waste and sediment and identification of the primary processes that produced these associations. Such "forensic" characterization will identify migration profiles (transport distances and concentrations) of key constituents and changes in the mineralogy, sorption capacity, and buffer capacity. Subsequent to characterization and analysis of the resulting data, laboratory testing to quantify the key controlling processes will begin. The goal will be to evaluate the key short- and long-term processes controlling the key risk driving contaminants. Processes to be quantified include adsorption, mineral precipitation and dissolution, biomineralization, matrix diffusion, pore plugging, and colloid formation and transport. In the area of geochemistry, field studies are in progress on representative contaminated sites to improve the conceptual models for waste interactions and on contaminant transport processes and directed laboratory research to clarify details of the chemical processes. Another activity in which geochemnists will contribute is development of a credible reactive transport model. At the present time, SAC will likely rely on the Kd construct to describe all contaminant retardation reactions/processes. More sophisticated descriptions of contaminant/sediment interactions may be required for future iterations of SAC. Field studies to characterize the near-field geochemical environments at representative inactive liquid waste disposal sites and past leaks at single-shell tanks and complementary laboratory studies under more controlled conditions are in progress. The field studies (vadose zone geochemical and hydrologic characterization) will provide the ranges of conditions and field scale observations on contaminant distributions and migration rates versus time or volume discharge. Once the field characterization data bound the conditions and define the nature and extent of the near field, laboratory tests can be chosen to better quantify the physical and chemical processes that control the interaction of contaminants and sediment. Currently at most liquid disposal sites, information is available on the chemistry and volumes disposed, and groundwater monitoring data are available to describe existing contaminants within the upper unconfined aquifer. These efforts are likely to focus on the "extreme-pH" chemical environments such as acidic process liquids and highly alkaline tank liquors. The latter were also high temperature fluids and both are known to have contained organic complexing agents. Our knowledge base is most sparse for these extreme-pH wastes that are far from chemical equilibrium with the sediments. During interactions of these highly reactive solutions with the sediments, large amounts of mineral dissolution and precipitation can occur. Such large changes in mass between phases can significantly influence the pore structure and hydraulics (permeability) of the vadose zone sediments. The formnation and sequestration of colloids may also be most active in this dynamic zone. It is this highly interactive near-field zone that merits detailed study to 2.23

improve current modeling approaches which rely on the simplistic Kd construct. More detailed discussions of the planned field characterization and focused laboratory studies can be found in DOE (1998, 2000) and individual project work plans such the ORP's RFL/CMS Single-Shell Tank Vadose Program Work Plan (DOE/RL 2000b) and the Immobilized Low-Activity Waste Multi- Year Statement of Work (LMHC 1999).

2.3

Technical Basis and Approach for Vadose Zone Modeling

Kincaid et al. (2004) describe the basis and technical approach for the 2004 Composite Analysis, indicating that the SAC (Kincaid et al. 2000; Bryce et al. 2002; Eslinger et al. 2002 a, b) would be used for the analysis. The SAC consists of a set of modules (models and data) that have been assembled since the previous 1998 Composite Analysis was performed to allow the collective impact of all the waste that will remain at the Hanford Site to be estimated. These modules include: Inventory, Release, Air Transport, Vadose Zone Transport, Groundwater Transport, Soil, River. Riparian Zone, and Risk/Impact Modules. These modules have been organized to simulate the transport and fate of contaminants through the environmnent. In general, inventory feeds to release, which feeds to the atmospheric, vadose zone, groundwater, and Columbia River pathways. The atmosphere, groundwater, Columbia River and riparian zone modules provide media-specific concentration estimates used in the risk and impact assessment. Kincaid et al. (2004) identified 1,046 waste sites from the 2,730 Waste Information Data System (WIDS) sites and several existing and future storage sites for inclusion in the 2004 Composite Analysis. Analysis of liquid discharge and unplanned release sites will be conducted on a site-by-site basis whenever inventory and release data permit. This is because the superposition of liquid discharge to a single soil column results in non-representative contaminant migration and release from the vadose zone. Solid waste burial grounds will be simulated at the burial ground scale; for example, individual burial trenches would be aggregated for a single burial ground. The inventory of solid waste disposal will be increased over timne until all burial grounds are closed. Vadose zone flow and transport simulations for the assessment will be based on 1) hydrogeologic profiles and properties for selected areas of the Hanford Site, 2) estimates of deep drainage rates that drive contaminant migration, 3) estimates of geochemnical reactions between contaminants and the soil and sediment of the vadose zone profile, and 4) waste inventory and release projections. The first three of these data types are the focus of this data package. The fourth, waste inventory and release projections, is the subject of other data packages. The behavior of contaminants in the vadose zone can be complex and subject to many unresolved issues and levels of uncertainty. The options for numerically simulating this behavior can be equally as complex. Table 2.1 attempts to summarize some of the important features and processes that can be incorporated into the simulations, depending on the complexity of thle model. On a large scale, and for

2.24

Options for the Composite Analysis (after the Preliminary Concepts Document)(')

Table 2.1.

Model Type Simple

[ 0 * * 0 * 0

Complex

l-D 4-6 Horizontal Layers Homogeneous, Isotropic

____________

Semi-Complex

Dimensions and Hydrogeology

0 0 * * a

Transport Processes Phase Transport Linear Sorption

*Aqueous

..

Isotherm (Kd)

Degradation and Decay1 Processes

Scale and Temporal Factors *Step-Wise

Steady

State *One

*Radioactive *Biological

Site per area per

waste type

2-D .Density and 0 Long Term Climate Up to 10 Sloping Temperature Effects Changes Sorption * Sites on finer grid Layers *Linear Homogeneous, Isotherms (K,, values) Isotropic *Peak Arrivals 2 and 3-D *Multiphase Transport *Episodic, Seasonal Numerous complexly *Colloidal Transport Variations formed layers *Barometric Effects *Long Tenn Climate Heterogeneous and *Reactive Transport Changes * cl nst-pcfc *Wind and Water Anisotropic Preferential Flowpaths i Erosion basis *Near and long term Chemically enhanced permeability

Decay Pseudo-

Decay ___________

*

0

* * *

Radioactive Decay Biological Decay

Radioactive Decay Biological Decay Inorganic Decay (Oxidative/ Reductive)

(a) GrounwaterVadoseZone Integration Project PreliminarySystem Assessment Capability Concepts for Architecture,

(b)

Platform, and Data Monagement. September 30, 1999. http://www.hanford.gov/cp/gpp/modeling/sacarchive/9-30rpt.pdf Shaded area identifies the model type options selected for the Composite Analysis.

the purposes of simulating the release of mobile contaminants from the vadose zone to the groundwater, the vadose zone can be simulated in a fairly simple manner to account for the most dominant features, events, and processes, as highlighted in Table 2.1. 2.3.1

Features

The physical structure (e.g., geology, hydrologic properties, geochemical properties) of the vadose zone and its principal transport pathways varies by location on the Hanford Site. Because the geometry and configuration of various hydrostratigraphic facies and heterogeneities are not well defined, the effects of these features will be captured via sensitivity or uncertainty analyses, within the context of larger hydrostratigraphic units. Not accounttng for small-scale stratifications and variations in texture will likely lead to an under estimation of lateral spreading. The limited quantity of site-specific data requires that values for the hydraulic properties be estimated from existing hydraulic property values provided by Freeman et al. (2002) and Freeman and Last (2003). For the 2004 Composite Analysis, the relationships between moisture content, pressure head, and unsaturated hydraulic conductivity are assumed to be nonhysteretic and representable using the van Genuchten (1980) and Mualem (1976) functions. Predictions of unsaturated conductivity can be markedly improved by simultaneously fitting van Genuchten parameters to retention and unsaturated conductivity data (Kosugi et al. 2002). A subset of the samples tested at Hanford were analyzed for unsaturated hydraulic conductivity. Because unsaturated conductivity data were unavailable for a majority of samples, the parameter database was established 2.25

using only those parameters determined using just retention data, so as to have an intemnally consistent set of parameters. Setting up the database in this manner allowed the generation of statistical distributions that support the Monte Carlo approach to be used for the 2004 CA. For future composite analyses, methods are being developed to incorporate and benefit from actual unsaturated conductivity data. Just as important, methods will also be developed to scale lab-derived parameters to field-scale appropriate parameters as well as develop methods to use field-derived parameters. Again, with only limited site-specific geochemnical data, values for the geochemnical properties (i.e., Kd values) must be estimated from the sediment type (e.g., grain-size data and the presence of secondary mineralization like the iron oxide coatings often found in the Ringold Formation) and waste type, based on data from existing laboratory measurements (Cantrell et al. 2003 a). For most circumstances, the linear sorption model approach is adequate for modeling transport, especially for the far-field and low impact sites where geochemical conditions remain fairly constant and contaminant loading of the adsorption sites is low (Cantrell et al. 2003b). However, in situations where large changes in chemical conditions occur within a small spatial zone (e.g., where highly concentrated, alkaline or acidic wastes have been discharged), a more sophisticated approach to surface adsorption modeling may be warranted. A simplified way to account for changes in mobility is to use a multitude of different Kd values to represent the sorptive capacity of the soil as the waste becomes more diluted and/or buffered by meteoric recharge and waste-sediment interactions (i.e., mimicking the decrease in competing ions along the flowpath) as was done in the previous Composite Analysis (Kincaid et al. 1998) and SAC initial assessment (Bryce et al. 2002).

2.3.2

Events

Various events could be considered in the implementation model for the composite analysis include those that are naturally occurring (e.g., meteoric recharge), those that are manmade (e.g., intentional or unintentional contaminant and water releases), those that are rather normally occurr ing (e.g., occur slowly over a long period of time), and those that represent extreme or unusual occurrences (e.g., 500 year storms, volcanism). Of primary importance to the composite analysis are the source release events, which discharged large volumes of waste water to the vadose zone, and the deep drainage (recharge) of meteoric water. Climate change and other disruptive events such as volcanism, flooding, or human disturbance are believed to be of rather low probability or consequence and are outside the scope of the composite analysis (Kincaid et al. 2004).

2.3.3

Processes

For the majority of contaminants, movement through the vadose zone is contingent on being dissolved within flowing water. The primary long term source of flowing water is precipitation that has infiltrated below the zone of evaporation and the influence of plant roots. Such water eventually flows to the water table, carrying with it whatever dissolved species may be present. Other important transport mechanisms such as: gaseous transport, temperature gradients, and possibly colloidal transport, are not considered significant on the scale and complexity of the composite analysis. The rate of recharge (deep drainage) at a particular location can be influenced by climate, soil, vegetation, topography, springs and streams, animal activity, fire, water and wind erosion and deposition, 2.26

plant community changes, disturbance, and human structures (e.g., roads, buildings). For most applications, flow rates through the vadose zone can be calculated using Richards equation with gravity and capillary potential gradients providing the dominant forces. The formation of colloids and occurrence of colloid-facilitated transport of contaminants have been identified as a potentially important process for the vadose zone (DOE 1997). However, for most waste sites at Hanford, the low water content and simple geochemnistry are not conducive to colloid formation or colloid-facilitated transport. Little or no data exist at the Hanford Site to adequately characterize the potential for colloidal transport. Various preferential pathways such as clastic dikes and fractures are capable of concentrating or contributing to phenomena such as fingering and funnel flow. Because of the nature of some waste, the local routes of contaminant movement will vary. The Vadose Zone Expert Panel (DOE 1997) stated that a likely mode of transport for leaked or disposed tank waste in the Hanford geology is along preferential, vertical, and possibly tortuous pathways. However, detailed analyses of tank farm plumes as well as vadose zone transport field studies suggest that these mechanisms are not significant contributors to groundwater contamination under normal recharge environments (i.e., fluxes <1 00 mm/yr) (Knepp 2002; CH2M HILL Hanford Group 2002; Murray et al. 2003). The fate of contaminants in the vadose zone depends on geochemnical conditions, the speciation of the contaminant, residence time, and microbial activity. Sediment has the capacity to sorb most contaminants from solution. The amount of sorption is a function of many factors. Some contaminants do not sorb at all. Sorption can be described using a simple linear relationship (i.e., a distribution coefficient or Kd) that is determined empirically. The Kd approach is applicable for most analyses at Hanford where contaminant concentrations are low and the chemistry is relatively constant. However, conditions near some waste sources are highly variable due to strong influences from the chemical components in the wastes. The general consensus is that these wastes will likely decrease the sorption of normally sorbed contaminants (e.g., cesium- 137), increasing in their mobility until concentrations in the sediments decrease to the range appropriate for the Kd approach. Contaminants that exist in the gas phase (e.g., radon, carbon-14, carbon tetrachloride) are subject to atmospheric venting and vapor extraction. Carbon-14 as carbon dioxide also reacts strongly with alkaline earth cations to form insoluble carbonates at neutral to basic pH values, and can also react with cement (Krupka and Seine 1996; Seine et al. 1992). Contaminants near the soil surface are subject to animal and plant uptake and dispersal within the aboveground environment. Contaminants can also be consumed by microbes, degrading into other compounds that may or may not be considered contaminants. Sometimes it is the water that is consumed rather than the wastes. Waste forms such as the immobilized low-activity waste undergo a corrosion process that consumes water. In a dry disposal, this consumption process will create a water vapor gradient that draws vapor toward the waste form.

2.4

Implementation

The large scale and complexity of a cumulative effects assessment for the entire Hanford Site together with the lack of detailed characterization data and/or understanding of some of the fate and transport

2.27

processes necessitates simplification of the site features, release events, and the contaminant fate and transport processes to enable timely results. Thus, the model approach shown in Table 2.1 was selected for this analysis. Implementation of this modeling approach is schematically illustrated in Figure 2.5. The primary transport mechanism to be simulated is aqueous phase transport in the porous media of the vadose zone, with radiological decay simulated using first order decay models. Hydrogeologic Profiles

2.4.1

The 2004 Composite Analysis will in general use a one-dimensional vadose zone model, with some analysis performed to explore the use of multidimensional models to explicitly account for structural features within the Hanford Site, and/or to condition the one-dimensional model results (Kincaid et al. 2004). To account for large scale variability in the hydrostratigraphy across the Hanford Site, the

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LEGEND Input Feature

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dormteet.A

Atmosphere

cF

Capillary Fringe

Sail Concentrations

-0

VaporPhase Drainage

Aclu.PhaseDrainage

Schematic of Vadose Zone Implementation Model for the Composite Analysis 2.28

preparation of hydrogeologic profiles and hydraulic and transport property datasets for each site were grouped into a number of geographic areas assumed to have similar hydrogeologic structure and properties. Hydrogeologic units are identified and their thickness ranges specified for each of these hydrogeologic provinces. To account for finer scale variability and uncertainty in the model parameters, probability distribution functions for each process model parameter were developed for each hydrogeologic unit of the hydrogeologic province. Kincaid et al. (2000) identified the Subsurface Transport Over Multiple Phases (STOMP) computer code (White and Oostrom 1996) as the code of choice for the Vadose Zone Flow and Transport Module for the System Assessment Capability. Properties that would be represented include unsaturated hydraulic conductivity, porosity, water retention parameters, dispersivity, and diffusion coefficient. Kincaid et al. (2004) also indicated that care would be taken to develop and apply correlated model parameters, where necessary, to appropriately model properties (for example, parameters of the van Genuchten and Mualemn models - van Genuchten 1980) of unsaturated hydraulics and water retention). Data to support the vadose zone profile and property models would be assembled for each geographic area.

2.4.2

Deep Drainage Rates

Deep drainage rates (also called recharge rates) are critical to the 2004 Composite Analysis because they affect both the release of waste from the disposal zone and the transport of waste to the water table. Deep drainage rates are a function of the climate, surface soil, topography, and vegetation. Kincaid et al. (2004) indicated that estimates of deep drainage and water-table elevation for the 2004 Composite Analysis will be based on the assumption of a continuation of current climate as defined by Hanford Site weather records (Hoitink et al. 2003). Hanford weather data have been collected regularly since 1946 at the Hanford Meteorological Station, which is located between the 200 East and 200 West Areas. For the 2004 Composite Analysis, a set of deep drainage rates will be assigned for specific intervals of time. The first interval, called the pre-Hanfordperiod, is the natural environment that existed prior to the start of Hanford activities. The undisturbed soil profiles and the shrub-steppe plant community determine the rates during this interval. The second interval is called the operations period, during which much of the land surface at waste sites was disturbed (e.g., trenches excavated; cribs constructed; waste disposed and buried) and maintained free of vegetation. The third interval is the rernediation period, during which sites will be covered with a protective surface barrier, remediated by retrieval and/or treatment, or left intact. For sites receiving a surface barrier, the remediation period begins with construction of the barrier and lasts for the period of institutional control followed by the design life of the barrier. For sites being remediated by retrieval, the remediation period encompasses the time to remove the contamination (and inventory) to a prescribed depth, place it in the Environmental Remediation Disposal Facility, and backfill with sediment. For sites being treated in place, the Remediation period encompasses the time to treat the contaminants so that they are altered or destroyed and then restore the site. For both retrieval and treatment activities, the remediation period includes the period of institutional control during which a shrub-steppe plant community is

2.29

re-established. In both cases, the vadose zone simulations will continue to predict the migration and fate of residual contamination in the vadose zone below the cleanup depth. The fourth and final interval is the post-Hanford period, during which long-term changes can occur after the site is no longer under active institutional control. The post-Hanford period represents the longest time interval evaluated. During this period, the design life of surface barriers is exceeded. For a period of time equivalent to the design life of the barrier, the deep drainage rate is changed in stages till it reaches the rate associated with an equivalent natural soil.

2.4.3

Geochemical Reactions

Kincaid et al. (2004) indicated that adsorption of contaminants with vadose zone sediment will be approximated using the linear sorption isotherm model. The mobility of contamination is highly dependent on its speciation and surrounding environment. It is assumed that upon introduction to the vadose zone environment, waste mobility is dominated by waste characteristics. After being in contact with vadose zone sediment and soil water for some distance, it is assumed the waste undergoes a change in its mobility based on buffering of the contaminant solution by the vadose zone hydrogeologic units. Finally, it is assumed once contaminants have migrated a short distance in the Hanford Site unconfined aquifer, another mobility state is defined by the highly buffered, neutralized, and diluted contaminant. Distribution coefficients would be defined for each contaminant in several zones; for example, upper (near field) vadose zone, lower (far field) vadose zone, and unconfined aquifer. Where indicated, Kd dependency on hydrogeologic units would be included. Broad ranges of distribution coefficient may be necessary to represent the suite of waste speciation and surrounding environment conditions that are possible. Data to support the vadose zone and aquifer geochemical reaction model would be assembled.

2.4.4

Interaction with the Inventory, Release, and Groundwater Modules

The inventory and release modeling results for the composite analysis will provide input to the vadose zone module. In addition to curie or kilogram amounts of waste and waste volume, the inventory module provides data on the location and dimensions of each storage or disposal facility. The release module, in concert with the inventory module, provides the contaminant flux to the vadose zone. Large-volume contaminant releases to sites where the vadose zone is thin, such as the cooling water discharges to retention basins in the 100 Areas, are routed directly to the Columbia River, bypassing the vadose zone. The Vadose Zone Module will provide estimates of the mass flux of contaminant as a function of time entering the unconfined aquifer. The estimates will address releases from all operational areas for the radionuclide and chemical contaminants selected for the 2004 Composite Analysis. Released flux to the aquifer will be provided for individual waste sites and/or aggregations of waste sites where available (for example, liquid discharge sites), and for solid waste burial grounds where applicable (for example, the combination of trenches that comprise solid waste burial grounds). The vadose zone releases to the aquifer will be aggregated to groundwater model nodes in order to introduce contaminants into the aquifer model. The Vadose Zone Module will provide estimates of mass flux of contaminants from the vadose zone to groundwater for the period of analysis. 2.30

3.0

Data Compilation

Kincaid et al. (2004) selected a reduced model approach for simulating vadose zone flow and transport for the composite analysis. In this approach, flow and transport are treated as either onedimensional processes or as one-dimensional approximation of two-dimensional processes. Vadose zone simulations will be conducted using the STOMP computer code (White and Gostrom 1996). Needed input parameters include: 1) hydrostratigraphy; 2) physical and hydraulic proper-ties (e.g., unsaturated hydraulic conductivity, porosity, water retention parameters, dispersivity, diffusion coefficients); 3) contaminant distribution coefficients; and 4) estimates of deep drainage rates. Input parameters for the vadose zone model were obtained from existing geologic, soil physics, and geochemnical databases. To facilitate sensitivity and uncertainty analyses, probability distribution functions were developed for each of the primary transport parameters.

3.1

HydroStratigraphy

The vadose zone stratigraphic profiles and hydrogeochemnical property distributions for the composite analysis are represented by 26 generalized one-dimensional vertical columns. These 26 stratigraphic profiles represent 17 general geographic areas and 9 site-specific locations. Each hydrostrati graph ic profile (template) was configured with the hydraulic and geochemnical parameters necessary for STOMP to simulate the flow and transport through the vadose zone. As many as five variations of a single hydrostratigraphic template were necessary to more accurately represent the depth of waste releases and thickness of the vadose zone beneath the point of injection. Additional variations of the hydrostratigraphic templates were necessary to accommodate variations in Kd values associated with different waste chemistry designations. Thus, a series of 63 templates were ultimately identified for application in the 17 geographic areas shown in Figure 3.1. These templates consist of the one-dimensional stratigraphy, hydrologic properties, and geochemnical properties as well as the waste site type (e.g., crib, tank, etc.) and waste chemistry designation. An additional template was added to identify those sites that discharged waste effluents directly to the river. A more complete discussion regarding the development of the templates is provided in Section 3.2 and Last et al. 2004. The preferred approach for modeling contaminant transport through the vadose zone uses these templates to represent the vadose zone beneath each waste site within a given geographic area. The actual simulation of each waste site assigned to a given template is implemented at that site's centroid coordinates. Each temnplate consists of a few major hydrostratigraphic units that are horizontally layered with constant thicknesses and are homnogeneous and isotropic (Figure 3.2). Hydrologic and geochemical parameters for each hydrostrati graph ic unit are represented by stochastic distributions to facilitate sensitivity and uncertainty analyses. Once each site was assigned to a geographic area and representative stratigraphic template, site-specific parameters such as the site location (centroid), and recharge rates (based on surface cover changes) were added. Each site was then assigned a unique alphanumeric identifier (refer to Last et al. 2004).

3.1

100 AreaH

IOOD

~~N

f

I

Area

rF r100 r

r

DOF H

100

.Area

K Area,/,,

N

100 B/C

A

Area~~

~

K

'Butte

and

'

SALDSETF T Are

j ownsite

O

BPon JL B

200 ast

*

Old

Ar%aets.T *

-00

C Cribs

____

S

9

RDFUS Ecology Central Landfill Bural Ground

Energy Northwest 618-10

fis% '"ke

n

i...

Hanford Site BoundaryBuilIGo

-I

400 Area

1.

(Fast

Flux Test Facility)

I)

~

300 Area

__

3 city of

RichlandC

J

_______________________________________________________ Riverst

OR

_____________________________

LBasalt Above Water

Table

Site Areas *Composite Analysis Sites

0 NArea S 0

a

1

2

3

4

5

1

r

. 30W

Are4'

LndfllRichland

North 1100

il

cangI.&tO4Ol March 24, 2004 11:34AM

Figure 3.1.

Location of Geographic Areas Represented by a Single Generalized Stratigraphic Column

3.2

Hydrostratigrahroug coum dependento on numbert anda hydosrotirapiSdtbs

saturate hyralcvodutviy vdo on

Sixty-three h d o ta ir pi c 2)~~~~~~~~~~~ hydosratgrph

repa te were defined on t -e -- pebasis on the types of ratesies foa7slce the geea egrpi A raFgre, and3)che uchmia

ancde alhanumric ws devlopedto ientif eachuniq e drostrairpi epaehscd geogrphic nd anumbe rea, desinatinthewastechemitry r for ainng Klvaue.einsste dig atioale alhdaumic c hractersoth spcfchydrostratigraphic tepaeseecetdb 3.2.1n WasepSieTen

fistdgi

(rflctn the depth ofwasteinjection)

dnttifingathe prtoa

raweete aiiyi

oaeadth

eodadtiddgt

identifying~ th yeo ~ aiiy ~ ~~ o xmltest ~[:a~su o 116 ndiates httefclt

andtha iisaiu

disosa facili t iecrb pfOneDmeditch); the

200ireaanthat it isanundground hig-laev wste teeplesies

mai cthedgies ofbrtarfeth gegrphc re, ndanube dsinain

sit oe 241e idicatttitosn h

tafnk Fothe

were, wastedsigsh:1)ura sites hewatechmitr 3.3sie

i nte10Ae

purpsos )thes of einngte bses facilitiesisuchtasnponds

rop orasigin

d

ales

ditches, retention basins, buildings, unplanned releases; 2) near surface facilities such as cribs, specific retention trenches, French drains, burial grounds; 3) underground storage tanks; 4) reverse (injection) wells; and 5) river outfalls. Each of these site types (except the river outfalls) release waste to the vadose zone at increasingly deeper depths, making the hydrostratigraphic column shorter, and moving the location of high impact versus intermediate impact Kd zones deeper in the soil profile. The waste site designation scheme for implementation in the base template nomenclature is shown in Table 3. 1. 3.2.2

Geographic and Site-Sp~ecific Areas Designations

Seventeen geographic areas (Figure 3.1) were identified that could each be represented by a single generalized hydrostratigraphic column. Each of the six 100 Areas were designated as separate geographic areas because each area is geographically distinct and has distinct hydrogeologic characteristics. The 200 Areas were divided into six aggregate areas based on differences in hydrogeologic characteristics. The 200 West and 200 East Areas were each divided into two geographic areas. Additional geographic areas were designated for the 200 North, Gable Mountain Pond, and the B Pond areas. A single geographic area was designated to encompass waste sites in the 300 Area. Finally, three additional geographic areas were defined for isolated sites in the 400 and 600 Areas. Table 3.2 presents the letter designations and brief descriptions of each geographic area. Nine site-specific designations were created by adding additional alphanumeric characters to two of the geographic area designations (Table 3.3). 3.2.3

Waste Chemistry Groupings (for assigning Kd ranges)

Six waste chemistry types were defined by Kincaid et al. (1998) for use in the 2004 Composite Analysis. These waste chemistry types describe chemically distinct waste streams that impact the sorption of contaminants. These same waste chemistry designations were adapted for use in the initial assessment conducted using SAC to assign Kd values to the vadose zone base templates (Bryce et al. Table 3.1.

Waste Site Type Designations Used in the Hydrostratigraphic Template Codes

Waste Site Type Designation(a) 100, 200, 300, 400

I

116, 216, 217, 316, 616

241 166,266, 276

[

Facility Types (reflecting depth of waste injection) Surface facilities (e.g., process sewers, reactor buildings, laboratory buildings, stacks, ponds, ditches, valve pits, process plants, unplanned releases [except tank leaks]). Near surface, shallow liquid and/or dry waste disposal facilities (e.g., cribs, burial grounds, retention basins, trenches, French drain, storage tunnels, drain/tile fields, pipelines, sewers). High level waste tanks, settling tanks, diversion boxes, catch tanks, tank leak unplanned releases. Deep injection sites (e.g., reverse wells)

River outfalls and associated pipelines Riverlb) (a) First digit represents the area: 1 = 100 Area, 2 = 200 Area, 3 = 300 Area, 4 = 400 Area, 6 = 600 Area. Second and third digits indicate the facility type. (b) River outfall discharged wastes directly to the river; thus, there is no vadose zone flow and transport component for these sites.

3.4

Table 3.2. Designation A

Geographic Area Designations Used in the Hydrostratigraphic Template Codes

3Geographic Area Description

B C D E F G H 1 K M N P

Q R S __________facilities,

T

Southern 200 East Area - encompassing the PUREX (A plant), hot semi-works (C-Plant), associated facilities (including PUREX tunnels), BC cribs, US Ecology, and the A, AN, AP, AW, AX, AY, AZ, C Tank Farms Northwestern 200 East Area - encompassing the B-plant, associated waste disposal facilities, and the B, BX, BY Tank Farms I100-B/C Area 100-D/DR Area East of 200 East - B Pond 100-F Area Gable Mountain Pond Areas 100-H Area 200 North 100-KE/KW Area 600 Area near Energy Northwest and the 618-li burial ground 100-N Area 600 Area southwest of the 400 area near the 618- 10 burial ground 400 Area 300 Area (and a few isolated facilities in and near the 400 Area) Southern 200 West Area - encompassing the REDOX (S-Plant), U-plant, Z-plant associated ERDE, and the S, SX, SY, U Tank Farms Northern 200 West Area - encompassing T Plant, associated facilities, and the T, TX, TY Tank Farms

Table 3.3. Designation A BC W A BC E A BT N A BT S A BT W A ILAW C S UN S US SZ9

Site-Specific Area Designations Used in the Hydrostratigraphic Template Codes

[Site-Specific Area Description Southern Southern Southern Southern Southern Southern Southern Southern Southern

200 200 200 200 200 200 200 200 200

East Area - representing the western portion of the BC cribs area East Area - representing the eastern portion of the BC cribs area East Area - representing the northern portion of the BC trench area East Area - representing the southern portion of the BC trench area East Area - representing the western portion of the BC trench area East Area - representing the central portion of the ILAW site West Area - representing the northern portion of the 216-U-l1&2 crib area West Area - representing the southern portion of the 216-U- 1&2 crib area West Area - representing the 21 6-Z-9 trench area

2002). However, based on the results of a recent compilation of contaminant distribution coefficients (Kd) for Hanford sediment (Cantrell et al. 2002), the six waste stream categories used in these assessments have been reduced to four.(a)

(a) Cantrell KJ, RJ Seine, and GV Last, Pacific Northwest National Laboratory, Richland, Washington. A white paper, Waste Stream Descriptions, Impact Zones and Associated Kd Estimates Including Rationalfor Selections, dated May 16, 2003. 3.5

Kd values used in the 1998 Composite Analysis were initially tabulated for six source term categories (Kincaid et al. 1998, Table E.2) and three impact zone categories (Kincaid et al. 1998, Table E.3). In addition to the three impact zone categories (High Impact, Intermediate Impact and Groundwater), another Kd category (Intermediate Impact Zone - Gravel) was included in the SAC initial assessment to represent very coarse lithologies composed of 90% by weight gravel. Kd measurements are generally conducted on material that is <2 millimeters in size. The first three impact zone categories mentioned assume that the material is sand size and that Kd values measured using <2 millimeter-size material are applicable. For materials that contain significant amounts of gravel, Kd values will be much lower than those determined with <2 millimeter-size material because the surface area and corresponding quantity of adsorption sites is much lower. For the Intermediate Impact Zone - Gravel category it is necessary to make a correction to Kd values due to the high gravel content. For the Intermediate Impact Zone - Gravel case, it was assumed that the material was 90% gravel and the corresponding correction factor was taken to be 0.31 for relatively high Kd contaminants (cesium, strontium, and plutonium) and 0.1 for low Kd contaminants (see Kaplan and Seine 2000, Appendix A). In future versions of the composite analysis, stratigraphic correlations will be used to estimate gravel contents of sediment to make gravel corrections to the Kd values rather than using an assumed gravel content of 90% for gravel rich sediment.

To better justify the selection of the Kd values for each waste stream designation and impact zone, it was determined that quantitative values (chemical concentrations), for each waste stream category should be assigned. This provides for a systematic approach for the assignment of Kd values that is less ambiguous and more technically defensible. Based on review of the six waste stream designations, six designations were reduced to four. The previous six waste stream designations were: I. 2. 3. 4. 5. 6.

High Organic/Very Acidic High Organic/Near Neutral High Salt/Very Basic Chelates/High Salt Low Organic/Low Salt/Acidic Low Organic/Low Salt/Near Neutral These were simplified to the following four:

1. 2. 3. 4.

Very Acidic (simplified from I above) High Salt/Very Basic (samne as 3 above) Chelates/High Salt (same as 4 above) Low Salt/Near Neutral (same 6 above with incorporation of 2 and 5)

The reasons for these simplifications are discussed in the following paragraphs. The high organic designation can be eliminated because waste streams that were termed high organic generally refer to waste streams containing significant concentrations of tributyl phosphate, hexone, kerosene, lard oil, and/or carbon tetrachloride. Except for tributyl phosphate, these organics compounds do not complex metals and radionuclides under normal aqueous environmental conditions and as a result will not enhance

3.6

their transport through chemical mechanisms. However, it is possible that if these materials occur as a free organic phase, they could significantly affect transport through multiphase flow and alteration of the hydrologic properties of the sediments. Tributyl phosphate is a weak complexant and after any dilution will not be capable of significantly mobilizing metals and radionuclides. These organic compounds, if disposed in large quantities and high concentration, could potentially affect radionuclide and metal migration by creating a reducing zone; however, no field evidence for such an occurrence has been found. As a result of this simplification, the High Organic/Very Acidic waste stream was redesignated as the Very Acidic waste stream and the High Organic/Near Neutral waste stream was combined with the Low Salt/Near Neutral waste stream. The Low Organic/Low Salt/Acidic waste stream was combined with the Low Salt/Near Neutral waste stream because mildly acidic waste streams will generally be neutralized relatively quickly near the disposal location by calcite that occurs naturally in most Hanford sediment. Slower reactions with aluminosilicate minerals could also account for some acid neutralization. To better justif~y the selection of Kd values, specific compositions have been assigned to each waste streamn (high impact zone). These compositions are shown in Table 3.4. The compositions are meant to represent a major component that is generic for each waste stream category and not an actual measured component. Only major components that are expected to have a significant influence on adsorption are included. In the case of the Very Acidic waste stream, the assumned comnposition is largely a guess. No actual acid concentration data could be located for this waste stream. The composition of the High Salt/Very Basic waste stream provided in Table 3.4 is meant to represent a generic composite composition of Hanford fuel processing waste that has leaked from single-shell tanks or intentionally discharged to specific retention cribs. Because a large number of leaking single-shell tanks occur in the single-shell waste management areas (S-SX, B-BX-BY, T and TX-TY, and U), estimated compositions available for SX Tanks and Tank T- 106 (Agnew et al. 1996) were used to guide the selected compositions. Similar to the High Salt/Very Basic waste stream, the composition selected to represent the Chelates/High Salt waste stream should be considered to be a generic composite composition and does not represent any single or specific waste streamn. The concentration of ethylenediamine-tetraocietic acid (EDTA) was selected based on measured concentrations of chelating agents in actual tank waste (Campbell et al. 1998a, 1998b). Intermediate impact zone compositions are assumed to be 10% of the concentrations assumed for the high impact zone (Table 3.4), except in the case of the Very Acidic waste stream where it is assumed that all the acid is neutralized in the High Impact zone. The un-impacted zone is assumed to have the composition of typical Hanford groundwater. Several typical compositions of Hanford groundwater (uncontaminated) are tabulated in (Cantrell et al. 2002). In general, Hanford groundwater is a calcium Table 3.4.

Waste Stream Designation and Assumed Compositions for Determination of Kd Values [Waste Stream Very Acidic High Salt/Very Basic Chelates/High Salt Low Salt/Near Neutral

Composition 1.0 M HN0 3 2 M NaOH, 4 M NaNO 3, 2 M NaNO, 1.0 M NaNO3-, 0.05 M EDTA, pH 12 Same as Hanford Groundwater 3.7

bicarbonate dominated water with a pH that typically ranges from approximately 7.5 to 8.5. Other prominent major ions are sodium, chloride, sulfate, and magnesium. A total ion composition of between 4 and 10 meq/L is typical. Table 3.5 presents the waste chemnistry designations used in the hydrostratigraphic templates. 3.2.4

Hydrostratigraphic Template Designations

A total of 63 hydrostratigraphic templates have been identified based on various comnbinations of the geographic areas, site types, and waste chemnistry types. Table 3.6 provides a description of the general hydrostratigraphic templates established for each geographic area. Table 3.7 describes the site-specific templates set up for a number of key facilities within two of these general geographic areas. Table 3.5.

Waste Chemistry Designations Used in the Base Template Codes Wasnthit I_________

2 3 4

Waste Stream Description] Very Acidic

High Salt/Very Basic Chelates/High Salt Low Salt/Near Neutral

3.8

Table 3.6.

General Hydrostratigraphic Templates for Each Geographic Area Geographic Area

[[1Chemistry

Template Designation IOOC-4

11 6C-4 1OOD-4 116D-4 1OOF-4 11 6F-4 1OOH-4 1161--4 IOOK-4 I1I 6K-4 166K-4 1OON-4 11 6N-4 2006-4 2001-4 200E-4 200B-2 2001B-4 21613-3 216B3-4

Area

Designation (a)

100 B/C

C

100 D

D

100 F

F

100 H

H

100 K

K

100 N

N

Gable Mtn. 200N E 200 E (B-Pond) N 200 E (B-Plant)

G I E B

2411B-2

266B-4

Description

S 200 E (PUREX, BC Cribs)

S 200 W (Redox, U-Plant, Z-Plant)

A

S

jDesignation(b)

Waste

Designation (d)

Surface Facilities Near Surface Facilities Surface Facilities Near Surface Facilities Surface Facilities Near Surface Facilities Surface Facilities Near Surface Facilities Surface Facilities Near Surface Facilities Reverse Wells Surface Facilities Near Surface Facilities Surface Facilities Surface Facilities Surface Facilities Surface Facilities

100 116 100 116 100 116 100 116 100 116 166 100 116 200 200 200 200

Near Surface Facilities

216

Tanks Reverse Wells

241 266

4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 2 4 3 4 2 4

267B3-2

200A-2 200A-4 21 6A-2 216A-4 241 A-2 241 A-3 266A-4 200S-2 200S-4

T

Waste Site Types

267c)

2

Surface Facilities

200

Near Surface Facilities

216

Tanks

241

Reverse Wells Surface Facilities

266 200

2 4 2 4 2 3 4 2 4

3.9

Table 3.6. (contd)

Template Designation 2 16S-1 216S-2 216S-4 241S-2 241S-3

Waste Site Types

Geographic Area S 200 W (Redox, U-Plant, Z-Plant)

S

241S-4

266S-4 200T-2 200T-4 216T-2 21 6T-3 21 6T-4 241 T-2 266T-2 266T-4 300R-4 31 6R-4 400Q-4 616M-4 616P-4

Waste Chemistry Designation (d)

Near Surface Facilities

216

Tanks

241

_____________

N 200 W (T-Plant)

T

300 Area (North Richland 400 600 600

R

Q M P

River

-

1 2 4 2 3 ___4

Reverse Wells Surface Facilities

266 200

Near Surface Facilities

216

Tanks Reverse Wells

241 266

Surface Facilities Near Surface Facilities Surface Facilities Near Surface Facilities Near Surface Facilities

300 316 400 616 616

4 2 4 2 3 4 2 2 4 4 4 4 4 4

-

-

River

(a) Assigned letter designation for geographic area. (b) Assigned number designation for waste site type: First number designates traditional Hanford Site area (i.e., 100, 200, 300, 400, 600 Areas); last two numbers designate waste site type (00 surface facilities, 16 = near surface facilities, 41 tanks, 66/67 reverse wells). (c) Two designations are used for reverse wells that have very different depths within a single geographic area. The "67" designation distinguishes the very deep reverse wells from those at a more intermediate depth (66). (d) Assigned number designation for waste chemistry type. =

=

=

3.10

Table 3.7.

Site-Specific Templates Established for a Few Key Facilities Site-Specific Area

Template Designation

Area

Waste Site Types

[Designation~

21 6ABCW-3

Waste

1Chemistry

Description

JDesignation

1b)

Designation dI

S 200 E, BC Cribs, Western ABCW Near Surface 3 216 Portion Facilities 216A BC E-3 S 200 E, BC Cribs, Eastern ABCE Near Surface 216 3 Portion Facilities 216ABTN-3 S 200 E, BC Trenches, ABTN Near Surface 216 3 216ABTN-4 Northern Portion Facilities 4 216ABTS-3 S 200 E, BC Trenches, ABTS Near Surface 216 3 Southern Portion Facilities 216ABTW-3 S 200 E, BC Trenches, ABTW Near Surface 216 3 Western Portion Facilities 216AILAWC-3 S 200 E, ILAW Site, Central AILAWC Near Surface 216 3 Portion Facilities 216SUN-4 S 200 W, 216-U-1&2 Area, SUN Near Surface 216 4 Northern Portion Facilities 216S US-4 S 200 W, 216-U- 1&2 Area, SUS Near Surface 216 4 Northern Portion Facilities 216SZ9-l S 200 W, 216-U- 1&2 Area, S_-Z9 Near Surface 216 1 Northern Portion IFacilities (a) Assigned letter designation for geographic area. (b) Assigned number designation for waste site type: First number designates traditional Hanford Site area (i.e., 100, 200, 300, 400, 600 Areas); last two numbers designate waste site type (00 = surface facilities, 16 = near surface facilities, 41 - tanks, 66/67 = reverse wells). (c) Two designations are used for reverse wells that have very different depths within a single geographic area. The "67" designation distinguishes the very deep reverse wells from those at a more intermediate depth (66). (d) Assigned number designation for waste chemistry type.

3.11

4.0

Input Parameters

This section describes the input data sets assembled for use in vadose zone modeling for the 2004 Composite Analysis.

4.1

Hydrostratigraphy

The geology of the vadose zone forms the framework through which contaminants move. The physical structure of the vadose zone, along with its hydraulic and geochemical properties, controls the migration and distribution of contaminants. Of particular interest are the interrelationships between the coarse- and fine-grained sediments within the vadose zone, and the degree of contrast in their physical and geochemical properties. As described by Kincaid et al. 2004, the large scale and complexity of a cumulative effects assessment for the entire Hanford Site necessitates the use of a simplified modeling approach. In this approach, industrial waste sites were grouped into one of 17 geographic areas that were identified as having unique hydrostratigraphic properties. The vadose zone beneath each geographic area is represented as a single one-dimensional hydrostratigraphic column. The hy drostrati graphic information that described a geographic area was assembled into a common template for all waste sites within that area. These templates were assembled from existing information including: " Driller's logs, geologists' logs, and geophysical logs " Published interpretive depths to the top and bottom surfaces of hydrogeologic units " Surface elevations (to convert hydrogeologic unit depths to elevations) " Elevation of the 1944 water table (to define the bottom of the vadose zone prior to waste disposal) In general, the main hydrostratigraphic units, contact depths, and thicknesses were taken from published maps and cross-sections, where available. The estimated average strata thicknesses were used to assemble the generalized columns extending from the surface to the 1944 water table (Kipp and Mudd 1973). However, because the sumn of the average thicknesses did not always equal the distance from the ground surface to the water table, small adjustments were made to normalize the average strata thicknesses to equal the total thickness of the vadose zone. Table 4.1 lists the published references used to assign hydrogeologic units to each of the hydrostratigraphic templates. Since lithofacies identification and geologic nomenclature has varied over time and by published sources, some translation was necessary to relate the major geologic units to a common classification. Table 4.2 describes the generalized hydrostratigraphic nomenclature used in this study based on that defined by DOE (2002), and Lindsey (1996). Appendix A provides the hydrostrati graphic column for each geographic area, including the layer thicknesses and their hydraulic and geochemnical property designations.

4.1

Table 4.1.

Sources of Hydrogeologic Data for the Seventeen Geographic Areas to be Analyzed

[Geographic Area 100 B/C 100 D 100 F 100 H

[ Designations References C Lindberg 1993a; Lindsey 1992; Peterson et al. 1996 D Lindsey and Jaeger 1993; DOE, 1993b; Lindsey 1992; Peterson et al. 1996 F Raidi 1994; Lindsey 1992; Peterson et al. 1996 H Lindsey and Jaeger 1993; Liikala et al. 1988; Vermuel et al. 1995; DOE 1993b; Peterson et a]. 1996 100 K K Lindsey 1992; Lindberg 1995; Peterson et al. 1996 100 N N Hartman and Lindsey 1993 Gable Mountain Pond G Lindsey et al. 1992b; DOE 1993c; DOE 1993d; Wurstner et al. 1995 Area 200 N I Lindsey et al. 1992b; DOE 1993c; DOE 1993d; Wurstner et al. 1995 E 200 E (B-Pond) E Barnett et al. 2000; Cearlock et al. 2000; Lindsey et al. 1992b; Wurstner et al. 1995 N 200 E (B-Plant) B Lindsey et al. 1992b; Price and Fecht 1976a, b, c; Tallman et al. 1979; Wurstner et al. 1995; Wood et al. 2000 S 200 E (PUREX, BC A Lindsey et al. 1992b; Reidel and Horton 1999; Valenta et al. 2000; Reidel cribs, BC Trenches, ABC et al. 200 1; Reidel and Ho 2002; Tallman et al. 1979; Wurstner et al. 1995 ILAW) ABT A ILAW S 200 W (Redox, U- S Johnson and Chou 1988; Lindsey et al. 1992a; Price and Fecht 1976d; Slate Plant, Z-Plant) S-U 2000; Tallman et al. 1979; Wurstner et al. 1995; Rohay et al. 1994; Connelly S-Z9 et a]. 1992a; Last et al. 1989; Last and Rohay 1993; Swanson et a]. 1999; Well logs for 299-W 19-14, -15, and -16; and borehole data from wells 299-WI15-8, -9, -83, -84, -86, -95, -10 1, and -207. N 200 W (T-Plant) T Lindsey et al. 1992a; Slate 2000; Tallman et a]. 1979; Wurstner et a]. 1995 300 Area (North R Gaylord and Poeter 199 1; Lindberg and Bond 1979; Schalla et a]. 1988; Richland) Swanson et al. 1992 400 Area Q HEDL, 1975; Meier Associates Log Book Project V-749; Well logs from 499-SlI-8J, and 499-S 1-7B3. 600 Area (61 8-10 P Well Logs from 699-S6-E4A Area) 600 Area (618-11 M Well Logs from 699-1 3-3A Area, Energy Northwest) In the simplified modeling approach selected for the composite analysis, the number and thicknesses of the hydrostratigraphic units within each template remain fixed. However, it must be recognized that there is uncertainty associated with the configuration of the hydrostratigraphic columns. The primary sources of uncertainty relate to drilling and sampling techniques, borehole logging, elevation control, and interpretation of the stratigraphy.

4.2

Table 4.2.

Hydrostratigraphic Units Used in this Study (after DOE 2002 and Lindsey 1996)

J

Code [Formation/Unit] Facies/Subunit BakilHDb Holocene Backfillformation

Hanford formation

Medium-grained, Cross-Bedded, Well Sorted Interbedded Sand- to Siltdominated Sand-Dominated, Silty Sand Sand-Dominated, Fine Sand Sand-Dominated, Coarse Sand

HDs

Medium-grained dune sand, moderate to well sorted, and cross laminated to cross-bedded.

HISSD

Rhythimite sequences of slackwater deposits consisting of graded beds of horizontal or climbing ripple laminated sand, to fine sand, to silt (laminated to massively bedded). Silt to fine sand, massively bedded to horizontally laminated or cross laminated. Fine to coarse sand, massively bedded, with or without silt.

HSD(f) HSD-Smn HSD-Sh(c)

San-DmiatdHSD(c) Sand-Dominated Graely Sndstratification GravelDominated GravelDominated, Coarse Cold Creek unit Fine-Grained, Laminated to Massive Coarse to FineGrained, Carbonate

HGD HGD(c)

CCUf(lammsv) CCUfc(calc)

4.2

Medium to coarse sand with minor amounts of pebbly sand, exhibiting horizontal to low-angle cross stratification. Medium to coarse sand to pebbly sand (with up to 30 wt% very fine pebble to cobble), with high angle planar-tabular cross to trough cro ss- strati fi cation Silty sandy pebble to boulder gravel (with 30-60 wt% gravel), massive to cross stratified. Pebble to boulder gravel (with greater than 60 wt% gravel), to silty sandy gravel, massive to cross stratified. Fine sand, silt, and/or clay, with a buff, pale to dark brown color, well sorted to very well sorted, micaceous, and having high natural-gamma activity Calcium-carbonate cemented clay, silt, sand, and/or gravel, white to light gray in color, very poor to moderately sorted, with a massive to platy structure and bioturbated with root casts (rhyzoliths).

__________Cemented

Ringold Formation

Description Poorly sorted gravel, sand, and silt derived from the Hanford and/or Holocene deposits

Fluvial Sand (Member of Taylor Flat) Fluvial Gravel (Member of Wooded Island, subunit E)

Rtf

Interstratified sand and silt deposits

Rwi(e)

Moderate to strongly cemented well rounded gravel and sand deposits, and interstratified finer-grained deposits.

Hydraulic Properties

Hydraulic property data for the vadose zone simulations were derived from the laboratory measurements of 284 soil samples (both repacked and splitspoon samples) taken from the 100 and 200 Areas (Appendix B). These data were selected from a catalog of vadose zone hydraulic properties (Freeman et a]. 2002) and a subsequent prototype database (Freeman and Last 2003). Because the

4.3

hydraulic property data are rather limited in regard to the spatial location of samples and the soil types represented, individual stochastic data sets were developed to represent ten different soil classes. These ten classes build on the six soil classes originally identified by Khaleel and Freeman (1995) based on texture (i.e., particle size), International Society of Soil Science (ISSS) classification, and moisture retention curve characteristics. Four additional soil classes were incorporated to separate out the Cold Creek unit sediment, add additional detail for the Hanford formation sand-dominated sediment, and add a new class for very coarse gravel. The 10 soil hydraulic property classes and their associated hydraulic property distributions were later correlated to the hyd rostrati graphic units used in the 17 geographic area templates. Table 4.3 describes the hydraulic-property soil classes to be used in the composite analysis. The statistical distributions of van Genuchten model (van Genuchten 1980) parameters, saturated hydraulic conductivity, and bulk density data were developed from laboratory data described in a catalog of vadose zone hydraulic properties by Freeman et al. (2001, 2002), and a subsequent prototype database Table 4.3.

Formnation

ISoil

Class

Holocene Deposits Backfill _____________

Fine Sand

Coarse Sand

Gravelly Sand Sandy Gravel

Gravel Silt Dominated

Caliche

Ringold Formation

C~ode 1 Bf

Gravel Dominated ________________________

Description

IUnit

Code(s)

Sand and gravel mixed with finer fraction. Same HDb as the SSG soil category identified by Khaleel and Freeman (1995)

__________

Hanford formation Silty Sand

Cold Creek unit

Description of Hydraulic-Property Soil Classes

Hss

Sand mixed with finer fraction, containing >500% fine sands, silt, and clay, with > 15% silt and clay. Derived from the SS soil category identified by Khaleel and Freeman (1995) H fs Sand, containing 35-70% fine sand, silt, and clay, with <1 5% silt and clay. Derived from the S soil category identified by Khaleel and Freeman (1995) Hcs Sand, containing >60% coarse sand. Derived from the S soil category identified by Khaleel and Freeman (1995) Hgs Gravelly sand. Same as the GS soil category identified by Khaleel and Freeman (1995) Hg Sandy gravel for which gravel content is approximately <60%. Same as the SG I soil category identified by Khaleel and Freeman (1995) Hrg Very high gravel content soils (>60%0 gravel) from the 100 areas (along the river). PPIz Derived from the SS soil category identified by Khaleel and Freeman (1995) but correlated to Cold Creek unit silt. Includes additional samples from borehole B88 14. PPIc Derived from the SS soil category identified by Khaleel and Freeman (1995) but correlated to the Cold Creek unit carbonate. Rg Sandy gravel for which gravel content is approximately >60%0. Same as the 5G2 soil category identified by Khaleel and Freeman (1995).

4.4

H-ISSD/HSD(f)

HSD-Sm

HSD-Sh(c)

H-SD(c) HGD

HGD(c) CCUf(lam-msv)

CCUf-c(calc)

Rwi(e)

(Freeman and Last 2003). Ideally, all parameters in this database should be corrected for gravel content using the same gravelI-correction procedure. Some of the parameters are known to have been corrected using the Gardner method (e.g., Khaleel et al. 1997) However, it is not clear that all samples were treated in a consistent manner. Gravel percentages are included in Tables 4.4 to 4.8 to indicate which soil classes might be affected. Future revisions of this database ought to address any disparity that might exist among samples. Estimates for longitudinal dispersivity were primarily taken from Ho et al. (1999). Values for residual saturation (Sr) were calculated by dividing the raw residual water content (OR) by the raw saturated content ().Effective porosity is assumed to be equal to the saturated water content (0,). The high, low, mean, and standard deviation values were calculated for each soil hydraulic property class. However, it should be noted that most of these soil classes do not have enough data points to qualify as a statistically significant distribution (Warrick et al. 1986). The residual water content (Sr), saturated water content (0.,), bulk density (Ph), gravel content, and fitting parameter n are assumed as normal Gaussian distributions based, in part on the report of Khaleel and Freeman (1995). The saturated hydraulic conductivity (K,) and the fitting parameter a, are treated as lognormal distributions, in accordance with Domenico and Schwartz (1990) and Carsel and Parrish (1988), respectively. In addition to the normal distribution statistics, the statistics for the log-normnal parameters are also included and truncation values are calculated for all parameters. Although Carsel and Parrish (1988) have reported cross-correlations between a number of these parameters, recent examination of the Hanford Site data have not found any statistically significant correlations. (a) In addition to statistical tables for the full suite of samples, subsets of samples were also assembled near specific sites of interest. Site-specific data sets for the 200 West Area, BC cribs and trenches, 200-UP- I (216-U- I and -2 cribs), and the 200-ZP- 1 (21 6-Z-9 trench) were also assembled. The sitespecific data for the 216-U- I and -2 cribs were derived from the S-SX tank farm, 216-U- I and -2 crib, and Environmental Restoration Disposal Facility samples. The 21 6-Z-9 site-specific data consists of samples from T Tank Farms, the 216-ZP-1 area, the 218-W-5 burial grounds, and project C-01 8-H. A composite table consisting of only 200 West Area samples was also created as part of this task. This data set provides a greater sample population that is unique to the unsaturated hydraulic properties found in the 200 West Area plateau sediments. The site-specific data for the BC cribs and trenches are derived from the closest sites to the facility, the immobilized low-activity waste (ILAW) site, the Sission and Lu Injection test site, and U.S. Ecology. A disadvantage to using only those sample sets close to the site of interest is that the population size is greatly diminished resulting in cases where the statistical distribution may not adequately represent the actual formation properties. Methods to increase the sample size (e.g., use an inverse distance weighting)(b) or otherwise incorporate information from large data sets (e.g., Bayesian Updatin g)(b) yet still account for site-specific

(a) Freeman EJ and ML Rockhold. 2003. Estimation of Sile-Specif/ic ProbabilityDistributionFunctionsfor Soil Hydraulic Parametersusing Bayesian Updating. Letter Report, Pacific Northwest National Laboratory, Richland, Washington. (b) Freeman El. May 14, 2003. Revised SAC Statistical Properties Tables of Vadose Hydraulic Properties. Letter Report, Pacific Northwest National Laboratory, Richland, Washington. 4.5

information are being examined. However, for the purposes of the 2004 Composite Analysis, the sitespec ific parameter distributions were based on equally weighted parameter values from samples nearest the site of interest. Tables 4.4 to 4.8 present the hydraulic property distributions for the Hanford site-wide data set as well as the site-specific data sets.

Table 4.4. ________

Soil

Statistical Mean Values for Site-Wide Samples

_________Site-Wide ______

[ al [(1/cm)

_____________________

69

OR

j

J(cm3/cm')

n

(cm3 /cm3 )

l

~

K

J(cm/sec)

jS, I

gravel

J

Bulk Density (g/cm 3 )

Class

Count

Bf

6

3.20E-02

1.400

0.030

0.262

1.50E-02

0.10

----

1.94

Hss

38

7.71 E-03

1.915

0.072

0.445

8.58E-05

0.16

0.18

1.61

H fs

40 82

2.49E-02 5.85E-02

2.107 2.020

0.049 0.031

0.397

2.87E-04

0.11

0.57

Hcs

0.353

2.19E-03

0.08

2.55

1.60 1.66

Hgs Hg

17 29

1.34E-02 1.79E-02

2.111 1.727

0.046 0.023

0.250 0.167

4.73E-04 3.56E-04

0.17 0.14

25.78 51.42

1.92 1.91

Hrg

40

7.40E-03

1.831

0.020

0.102

1.46E-03

0.20

67.63

1.97

PPlz PPIc

9 16

5.52E-03 1.08E-02

2.101 1.727

0.034 0.072

0.420 0.306

5.5713-05 5.OOE-04

0.08 0.21

0.44 16.73

1.68 1.71

Rg

18

7.8 1E-03

1.697T

0.063

0.178

4.13E-04

0O.23

46.08

1.90

Table 4.5. __ _

_

_

Soil

1

Class

jCount I

a

_

Statistical Mean Values for BC-Crib Samples BC-Cribs

__

I I

Bf

6

(I/cm) I 3.20E-02

Hfs BC Hcs BC Hgs

18 46 5

2.08E-02 7.19E-02 3.07E-02

_

_

n

J1.400 j2.507 J2.047 1.872

_

_

Densityl

[0, (1Ma5MBulk KI 3 (cmlsec) (c'/cm cm/cm) OR

[

IS.,

0.030

0.262

1.50E-02

0.10

0.033 0.026 0.040

0.380 0.357 0.271

2.25E-03 5.32E-03 3.02E-03

0.09 0.07 0.15

gravel ----

J(g/cm)J 3

1.94

0.38

1.65 1.67 1.95

[2.68 17.66

Statistical Mean Values for Ul & U2 Samples

Table 4.6.

1

_____

Soil Clas jCount Bf 6

a I n 0 (1c) 3.20E-02 1.400

H-ss U

6.78E-03 1.25E-02

Ul and U2

1 (c

3

1

9, 3 c )J(m/cm

R)

___

__________

K,

(cm/sec)

jS,

%gravel

J

Bulk Density (g/cm3 )

0.030

0.262

1.50E-02

0.10

----

1.94

2.347

0.066

0.437

0.15

0.00

2.451

0.042

0.347

2.49E-05 1.71 E-05

0.12

0.00

1.58 1.72

57.10 0.08

Hfs U

6 4

IHg U PPIZ U

3 5

11. 14E-02 11.845 14.73E-03 2.020

0.029 0.035

0.150 0.398

2.88E-04 7.27E-06

0.20 0.09

IRgU

7

1l.33E-02

1.768

0.144

0.318

7.83E-05

0.38

4.6

F16.49

2.09 1.71 1.82

Table 4.7. ________

Soil Class

a

1I

_______200-ZP-

1

101?

q1

n

j(cm3 /cm 3 )

3.20E-02 2.79E-03 8.33E-03 6.65E-02 l.6-2 6.69E-03

1.400 1.840 1.903 1.692 171 2.203

1.09E-02

1.734

0.030 0.047 0.042 0.021 0.026 0.033 0.075

Count

Bf 6 Hss Z 5 Hfs Z 4 Hcs Z 5 HgZ 9 PPlz Z 4 PPIc ZE 15

4.2.1

_______ ______

Jc

Statistical Mean Values for 200-ZP-1 Samples

(I/cm)

3 1(cm /cm3)

_

_

_

_

_________

I~ Bulk Density

J(cm/sec) JS

0.262 1.50E-02 0.351 6.55E-06 0.366 7.88E-05 0.292 1.4913-03 0.156 3.5 1E-03 0.448 7.1 IE-4 0.1r.4-4

gravel

J~(g/cm') 3

0.10-----------1.94 0.13 0.00 1.80 0.11 0.75 1.68 0.07 0.00 1.56 0.16 153.44 1.79 07 1.00 1.58 02 15.07 1.68

Site-Wide Hydraulic Property Distributions

The site-wide sample distribution (Table 4.4) uses all the data in each of the soil classes to calculate the statistical mean van Genuchten parameters that were then used to generate the hydraulic properties curves shown in Figures 4.1, 4.2, and 4.3. Figure 4.1 shows that the Hanford formnation silty sand and the Cold Creek unit silt attain the highest saturated water content, while the Hanford formation coarse gravels and Hanford formnation sandy gravels have the lowest water content. Table 4.4 illustrates that the finer textured sediments typically have greater saturated water content, lower saturated hydraulic conductivity 0.5

~0.45 ------------------

WRC-bf

E

0.:

WRC-hfs

.~

0.4

WRC-hcs

0.3 0

ca

~0.2 .~0.15

E 0

0.05

10

101

10

10Z

i03

104

Pressure Head (cm) Figure 4.1.

Formation Specific Water Retention Curves for the Site-Wide Distribution

4.7

10-2

0 10--

cond-hcs

~ 10

E

-

N

10

-5

-cond-hss

cond-hgs

.---

~

-

- -- -

.-

z '

\.

-~

cond-hg cond-pplz cond-pplc cond-rg cond-hrg

\

10-7'

'

10-10

104~

103

101

101

Pressure Head (cm) Figure 4.2.

Formation Specific Hydraulic Conductivity Curves for the Site-Wide Distribution 10-2

10-3 U)

10

10-6 0

L, 10)-7

cond-bf cond-hfs cond-hcs

/ 0

n-s

10-8 0--z

0 0

-

0.25

0.5

cond-pplz

-

-..-

-

-cond-pplc

cond-rg cond-hrg

0.75

Effective Saturation (Se) Figure 4.3.

Formation Specific Hydraulic Conductivity Curves Versus Saturation for the Site-Wide Distribution

4.8

and lower bulk density. As the samples become coarser the water content declines, saturated hydraulic conductivity increases and bulk density increases. The properties in Table 4.4 and Figure 4.1 represent matrix characteristics and do not account for preferential flow through cracks (refer to et al. 2002, 2003). Uncertainties arise from the drilling and sampling methods used to collect the samples (e.g., corebarrel, splitspoon), how the samples are handled in the lab (e.g., repacked), subjectivity in assigning the samples to various geologic formations and facies (i.e., soil classes), systematic or measurement errors associated with the laboratory analyses, and scaling issues when using small sample data to represent larger field scale processes. The saturated hydraulic conductivity is highest for the backfill (B) and Hanford coarse gravel (Hcg) and lowest for the silty Cold Creek unit (PPIz) and Hanford formation silty sand (Hss). The hydraulic conductivity does not drop off rapidly as would be expected for the coarse textured sediment. This may indicate a higher fraction of fines than accounted for. 4.2.2

Site-Specific Hydraulic Property Distributions

When evaluating the hydraulic properties at a particular location it is valuable to only use those data that are most representative of the hydraulic properties at that site. Three sites were selected from which to generate site-specific hydraulic properties data sets: I1)the BC cribs and trenches, 2) the 216-U- I and -2 crib area, and 3) the 21 6-Z-9 trench area. A fourth set of hydraulic property data was generated for all 200 West Area samples. Tables 4.5 to 4.8 list the mean hydraulic property data derived for each of these specific areas. Appendix B provides the hydraulic property distributions for the each site-wide and sitespecific soil class. 4.2.3

Application to Vadose Zone Simulations

Each vadose zone hydrostratigraphic template represents a one-dimensional soil column made up of several hydrostratigraphic units. Each hydrostratigraphic unit occupies a number of model nodes depending on the thickness of the hydrostratigraphic unit. The hydraulic properties for each hydrostratigraphic unit are determined by stochastically sampling the probability distribution function for each parameter, for a given simulation (realization). All model nodes within a single hydrogeologic unit are assigned the same hydraulic properties for a single realization. 4.2.3.1

Conditioning of One-Dimensional Flow Simulations Against Detailed Site-Specific Assessments

Several studies were conducted to examine multiple hydrostratigraphic models and two-dimensional vadose zone simulations of selected waste sites where previous one-dimensional simulations failed to provide reasonable results. One of the main areas of interest was the BC cribs and trenches. Here multiple hydrostratigraphic profiles (templates) were developed to generate reasonable two-dimensional representations of the vadose zone. Multiple two-dimensional flow simulations were conducted to provide the basis with which to estimate the wetted column area needed as input for one-dimensional flow

4.9

and transport simulations (Appendix C). Additional work was aimed at trying to incorporate the up scaling techniques developed through the Science and Technology Project (Zhang et al. 2002) to improve hydraulic property estimates for the BC crib and trench area. Table 4.8.

f

Statistical Mean Values for 200 West Area Samples ________

a Cls I Count (Icm Bf 6 0.032 Hss_2W 11 4.53E-03 Hfs_2W 8 1.02E-02 Hcs 2W 7 4.15E-02 7.90E-03 Hgs 2W 2 Hg 2W 12 1.6513-02 PPIz 9 5.52E-03 1.08E-02 IPPIc 16 JRg_2W 18 1l.32E-02 Soil

j

I j cm/cm3

200W

n 0.03 1.4 2.116 0.057 2.177 0.042 1.759 0.026 2.223 0.030 1.745 0.027 2.101 0.034 1.727 0.072 11.753 10.126

j 3

OCM M

ORM3

(c/cm 0.262 0.398 0.356 0.318 0.273 0.154 0.420 0.306 10.297

K

(cm/sec)

___

J

%

_____

Bulk Density

S I gravel S,

1.50E-02 0.102 1.91 E-05 0.141 3.67E-05 0.118 1.09E-03 0.077 2.35E-04 0.133 1.48E-03 0.172 5.57E-05 0.080 5.OOE-04 0.214 l .06E-04 10.334

(gc) 1.94 ---0.00 1.67 0.38 1.70 2.14 1.65 24.00 1.81 54.36 1.89 0.49 1.66 ,16.73 1.71 122.18 1 1.84

Another main area of interest was the 216-U- I and -2 cribs. Here, another approach has been taken to model this site as two separate sites to account for the multiple release mechanisms. Field data indicate this location experienced a fast path release (perhaps due to flow through a borehole annulus or similar mechanism) that allowed a significant quantity of contamination to effectively bypass the vadose zone and travel directly to the surface aquifer. Because the mechanism for this fast path is not characterized, the 216-U- I and -2 site was modeled with an empirical two-site arrangement wherein a duplicate site, "216-U-I and -2-Fast" was defined that uses a special hydrostratigraphic template that immediately releases any waste it receives directly to groundwater. No waste is routed to this "fast" site by the inventory model. However, a remedial action is declared in the overall SAC model input set that declares that a fraction of the waste in the vadose zone in the year of the suspected fast path event (1988) is to be remediated from 216-U- I and -2 site and sent to the 216-U- I and -2-Fast site (which effectively sends it immediately to the surface aquifer). The fraction used for this remediation was determined by dividing the estimated contaminant mass in the aquifer after the fast path event (as determined by history matching data prepared by Murray et al. (2004) by the total mass in the vadose zone at 216-U-lI and -2 in 1988 (as modeled in an initial median-inputs simulation of the 216-U- I and -2 site). Thus, the model is effectively forced to deliver the field-observed mass of contaminant directly from the vadose zone to groundwater in a single event in 1988. Several other sites (e.g., the Integrated Disposal Facility LIDF, formerly the Immobilized Low-Level Activity Waste facility], and the tank farms) are the subject of more detailed site-specific performance assessments. Thus, efforts were made to incorporate the results of these performance assessments more directly into the composite analysis, and/or to scale the composite analysis model results so that the central tendency of the results mimics the deterministic results from these site-specific assessments. None of these more-detailed site-specific performnance assessments are stochastic, so the results are used

4.10

directly in SAC median-inputs runs in place of the embedded STOMP one-dimensional model results. The results are also used to calibrate the STOMP one-dimensional model at these sites so that the stochastic simulations will better mimic the expected behavior of the site-specific assessments where they run stochastically with the SAC data. This is done by comparing the release rates of the median-inputs STOMP model in SAC for these sites to the more-detailed site-specific modeling results for a range of vadose zone wetted area scaling factors, and choosing the factor that results in the best agreement for use in later stochastic simulations. This is similar to the approach used for the BC cribs and trenches in which the one-dimensional model used in SAC was calibrated against idealized two-dimensional models.

4.2.4

Transport Parameters

For the 2004 Composite Analysis, the two key parameters that will govern transport of contaminants in the subsurface are the dispersivity and the species-specific water content dependent diffusion coefficient. The product of dispersivity (X) and pore water velocity yields the mechanical dispersion coefficient, which relates the dispersive solute flux to the solute concentration gradient. Longitudinal dispersivity (i.e., in the direction of flow) is generally larger than dispersivity in the transverse direction and it is also scale dependent (Khaleel et al. 2002). Field measurements of dispersivity are extremely rare and small-scale laboratory measurements have only marginal utility in estimating field values (Meyer et al. 2004). Estimates of longitudinal dispersivity for the compo 'site analysis were primarily taken from Ho et al. (1999). In the absence of data, dispersivity values are often based on simple guidelines related to the size of the computational elements in numerical simulation codes. Dispersion during transport of contaminants can potentially be enhanced when the contaminants react with either the sediments or the fluid or gas constituents. The enhanced macrodispersion phenomenon is not well understood and is therefore a current research topic (e.g., Khaleel et al. 2003). Although not entirely understood, enhanced macrodispersion has been estimated at specific sites at Hanford. For example, the modeling data package for the S-SX FIR (Khaleel et al. 200 1) suggested that dispersion of cesium was enhanced by 10 to 15% for all but the plio-pleistocene layer, for which the enhancement factor was roughly a factor of 2. Enhanced macrodispersion is not addressed in the current version of the Composite Analysis but will be considered for future versions. The diffusion coefficient is the proportionality factor in Fick's law that relates the diffusive transport flux to the gradient in solute concentration (Meyer et al. 2004). According to Meyer et al., the diffusion process results in mass transport from regions of high solute concentration to regions of lower concentration and occurs as a result of the random thermal motion (Brownian motion) of molecules and atoms. The diffusion process will be represented in the 2004 Composite Analysis. Each contaminant species will be assigned a unique free-water diffusion coefficient that applies to diffusion in dilute water solution. In the subsurface environment, porous medium and the water content will affect the diffusion process. Thus, the effective diffusion coefficient will be a function of the tortuosity of the porous medium and the water content. The tortuosity will be represented using the Millington and Quirk tortuosity model. Finally. reactive solutes can affect diffusion. The resulting apparent coefficient will be represented as a function of the water content, bulk density, and sorption coefficient as explained by Meyer et al. (2004).

4.11

4.3

Contaminant Distribution Coefficients

Geochemical properties were assigned to each hydrogeologic unit, in a manner similar to that done for the 1998 Composite Analysis (Kincaid et al. 1998). The waste characteristics were assumed to dominate the near-field mobility of the contaminants in the vadose zone. After being in contact with vadose zone sediments and soil water for some distance, the waste undergoes a change in its mobility based on buffering of the contaminant solution by the vadose zone sediments. Thus, distribution coefficients were defined separately for each contaminant in the upper vadose zone (near-field or high impact zone) and in the lower vadose zone (far-field or intermediate impact zone) (Kincaid et al. 1998). Distribution coefficient zones were defined as either high impact or intermnediate impact depending on the nature of the contamination fluid. Zones in which the organic concentration, pH, or salt concentration in the fluids may have affected the Kd values were designated high-impact. Zones in which the acidic or basic nature of the wastes was estimated to have been neutralized by the natural soil were designated intermediate impact. Kincaid et al. (1998) estimated the depths of this transition zone by examining the peak location of beta/gamma contamination (as presented by Fecht et al. 1977) for 200 Area cribs receiving very acid or high-salt/very basic waste. In general, these transition depths ranged from 10 to 40 meters. Given the limited data available on which to base further interpretations on the depths of transition, and the desire to simplify the numerical simulations, a slightly different approach was used here. Generally, the hydrogeologic unit into which waste streams were introduced was designated as high-impact regardless of waste stream characteristics. If those hydrogeologic units were thin (e.g., <1 meter), then the hydrogeologic unit immediately below that into which the waste stream was introduced was also designated high-impact. All other hydrogeologic units lower in the profile were designated intermediate impact. This approach enables us to keep the numerical simulations relatively simple by using the existing number of hydrogeologic units (i.e., we did not have to add new layers to make the Kd change where it might have occurred within a single hydrogeologic unit). At the same time, the depths of change, corresponding to the thickness of the hydrogeologic units, are still on the same scale (tens of meters) as those used by Kincaid et al. (1998). Appendix A provides the detailed hydrogeologic columns and locations of the various Kd zones, for each base template. As described in Section 3.2.3, several Kd classes were defined for mapping distribution coefficients to high or intermediate impact zones and chemical waste type. These Kd classes were labeled using a two or three digit alpha-numeric code. The first digit represents the waste chemistry type (numbers I through 4) (see Table 3.5). The second digit represents the impact zone (i.e., H for high impact [i.e., near field vadose zone], I for intermediate impact [i.e., far field vadose zone], or G for the zone not impacted [i.e., very far field vadose] and groundwater). For Kd values in the intermediate impact zone, a third digit was added to identify those Kd classes that were adjusted for the gravel-dominated hydrostratigraphic units. To account for the common observation that significant gravel content decreases Kd values (Kaplan and Serne 2000), the intermediate impact zone for each Kd class in the intermediate impact zone was subdivided into gravel rich and gravel poor zones. Kd classes with a third digit of "I" pertain to gravel poor (i.e., sand-dominated) strata and Kd classes ending in a "~2" pertain to gravel rich (i.e., gravel dominated) strata (See Section 3.2.3).

4.12

Kincaid et al. (2004) identified sixteen radionuclides as contaminants of concern to be addressed in the composite analysis, see Table 4.9. However, two of these radionuclides, radium-226 and protatctinium-231 are to be simulated as progeny of uranium-234 and uranium-238, and will not be directly incorporated into the flow and transport simulations for the 2004 Composite Analysis. Thus, Kd estimates were not developed for those contaminants. For all other contaminants of interest, a best estimate Kd value and range (minimum and maximum) were developed for each Kd class. A brief discussion for each contaminant is presented below. Probability distribution functions for these Kd values were generated according to the following set of rules and derived from the minimum, maximum, and best estimate Kd values. Table 4.9.

List of Contaminants of Concern to be Included in the 2004 Composite Analysis (Kincaid et al. 2003)

Tritium Chlorine-36

(a) (b)

(c)

(d) (e)

Contaminants of Concern Carbon-i14 Selenium-79

Strontium-90

Technetium-99

Iodine-I 29 Europium- 152(a)

Radium-22eJ)

Cesium- 137

Uranium-233 Protactinium-231I ) Uranium-235 e) Uranium-234 (d) Neptunium-237 ilranium-23 8 (d) Europium-152 will be simulated using median values in a determninistic simulation. Because of its relatively short decay half-life, the simulation will extend at most two or three hundred years beyond Hanford Site closure. Radium-226 will be simulated as progeny of U-234 and U-238. It will be further evaluated in the 2004 Composite Analysis because the chemical separation for uranium may have placed radium-226 in Hanford wastes at levels not in secular equilibrium with the uranium in the waste. Protactinium-23] will be simulated as progeny of U-238. It will be further evaluated in the 2004 Composite Analysis because the chemical separation for uranium may have placed protactinium-23 I in Hanford wastes at levels not in secular equilibrium with the uranium in the waste. Uranium-238 and uranium-234 will be summed and shown as uranium-238 to represent both in this simulation. It is assumed that these two uranium isotopes are always in secular equilibrium. Uranium-235 is modeled separately to properly generate protactinium-231 through radioactive decay and progeny ingrowth.

Case #1: Where the minimum estimate, best estimate, and maximum estimate were all greater than zero, a lognormnal distribution was assumed. The best estimate was assigned to the median value. The minimum estimate was assigned to the lower 1 %tail of the distribution, and the maximum estimate was not used in defining the distribution. Case #2: Where the minimum estimate was zero, but the best estimate and maximum estimate were greater than zero. A lognormal distribution was used, with the best estimate assigned to the median value, the lower 1% tail of the distribution assigned to the value 0.00 1, and the maximum estimate used to define a probability truncation limit for the upper tail of the distribution (if less than 0.99 probability, otherwise truncation was set to 0.99). Case #3: Where the minimum and best estimates were zero, but the maximum estimate was greater than zero. A composite distribution was used. The value zero was assigned a 50% 4.13

probability. The other portion of the distribution was assigned a triangular distribution where the minimum and mode were both zero and the maximum was assigned to the upper tail estimate. In those cases where a lognormal distribution was assumed, the lognormal distributions were truncated at the 1% and 99% levels, thereby preventing the generation of values that could fall below the minimum estimate. Table 4.10 provides the current compilation of distribution coefficients for each waste stream category and impact zone (derived from the Contaminant Distribution Coefficient Database and Users Guide by Cantrell et al. 2002, 2003a). The hydrostratigraphic templates provided in Appendix A identify the Kd classes assigned to each hydrostrati graphic unit for each geographic and site-specific area. As with the hydraulic parameters, all model nodes within a single hydrogeologic unit are assigned the same Kd values for a given realization.

4.3.1

Tritium

The best estimates for Kd values of tritium are zero, and the ranges were selected to be zero for allI source and impact zone categories. It is assumed that tritium atoms are incorporated into water molecules and, as a result, no adsorption or other significant geochemnical interactions are expected.

4.3.2

Carbon-14

Under typical Hanford conditions, it is assumed that carbon-14 will occur predominately as the

bicarbonate ion (H1' 4C03-), though at high pH bicarbonate will deprotonate to carbonate (14 C03 2-) and at low pH will protonate to formn '4C0 2 (aq). In general, adsorption of any anion (through surface complexation) onto Hanford sediment in the alkaline pH range is expected to be negligible because the pH point of zero charge (pzc) or pHp., for most minerals is below the typical pH of Hanford groundwater. For example, the p~- for montmorillonite and feldspar is approximately 3 (Stumm and Morgan 1996). The pHp,. for calcite (at PCc)2 = 10-" atm) is approximately 8.2 and goes down to 6.5 atp('02 = I atm. This indicates that Hanford sediments will be dominated by negatively charged sites in the alkaline pH range; conditions which are not conducive to adsorption of anions. This is clearly demonstrated with CrO42 - for

example (Cantrell et al. 2002).

Although surface adsorption of H'4 C03 or 14C

2 3 -

is not likely to be significant under Hanford

conditions, two other processes could potentially remove these species from solution. These two mechanisms are isotopic exchange and precipitation. Calcite is common within Hanford sediment (often as caliche or mineral grain coatings) and is the most readily available carbonate phase within Hanford sediment available for solid surface exchange with 14CO 3 2-. Like ion exchange, isotopic exchange can be written as a chemical reaction (Garnier 1985): 12c+/4c=

14c, 14

4.14

12c

(4.1)

Table 4.10.

Kd

Waste Chernistry/Soarce Category 1: Very Acidic hr'Impoact (A) - H KdEstiomate (mLI Min Ma Best Aniale Non-Adsorbing Radionuclides H3 TcllO C 36 Moderately Adsorbing 1129 U238 Se79 Np237 C14 Highly Adsorbing 0(111 Csl137 P29 EuL5? Organic Contaminants CCI4 Inorganic Contaminants CrVI

0

0 I

tI 0I 11

0

0I

0

4 0.2 5, II 0

It 0 3 0 0

15 4 10 2

II0 11000 0.4 211

Ranges by Waste Chemistry/Source Category Intermsediate Impact - Sand (BII III Ed Estimsate(.~L/g) MxBst Mm Best 0 0 0II

0.2

1

2

4

2

2110

0 0 Ot 0

02 018 -1 lB uInsoitable

tO 100010 I 100(

5 21(1) 0. 1

hstnediate Impact -Gravel (B2) - 112 Kd EstsosatelotLfe) Min Ma

0 0.2 3 2 0

22 2000(1 600 200

2 4 II0 30 l1ll

10 2110 200 10

112

11 0 00,1

It0 0

0

0

0

11 0

A1 I

IIt0

(102 (008 115 1 unsuitable

501 I101001 21(00 1000

Grousdsate, (Fl) - IG Kd Estmat -L/1) M$Z Bes Mr

0 00t2 013 0.2 I

(02 (1. t 31 1001

102 (1. 5 t0 onsuitahle

I 11,2 3 2 0

2 4 10 30 1001

68 60 186 62

3A1 62 62 3.1

155 31110 620 310

22 211(11 600 200

10 211 200 10

s0 I 100 2000 1000

1011

01.06

0.2

0.1

0.0

0

0

0.3

0.1

0.0

(1.02

0

03

0

00 1(3

Waste ChensistrylSoarceCategory 2: Very High SaltlVery Basic Higho NnAdsAaI~te NnAsrbing Radionuclides H3 1 T"99 C136 Moderately Adsorbing 1129 U238 Se,79 Np237 C 14 Highly Adsorbing S,-90 CsB37 Pa23-9 Eu -2 Organic Elenments CC14 Inorganic Elements CcVi

aept(D) - 1H

Interstediate Inspact- Sand (El1) -21

(14 Estrotate mLIN)dEtmt Best I'Mro Max II 0 0

0 0 0

0.02 11.8

II 0.2

0I 0 0 01 108

0 0 0

2001 onsuitable

100 0

22 10I 200 200

10 0 711 t0

50 300) 6)01 11(1

22 1001 600 2010

1O 10 2001 II0

0.2

0.1

0.0

0.2

0.1

0I13

01

1

0

0

Arahsle

0 1(2 0

200 usuotable

e 0 01 0

0.2 4 010 5001 100

0

Waste Chemsistry/SourceCategory 3: Chelates[High Snlts HmhIaeat(GI) - 3H (1 soac(.L/e) I Best Mao Mlax ighly Mobile Elements C136 Somewhat Mobile Elements 129 U238 Se?0 Np237 C14 Moderately Immobile Elements Oct10 CsI37

Best

0 (). 1 0

loteossedratelompact- Gravel (E2) - 212

KdEstdEtmteoL MiKMx

(1.2 4 1

11.2

211 5111 10

5 O 2](0) II

211 1(1 20(00 1000

1

2

0.2

0

113

10 200 201 10

30O 10000 201100 10

01103

loteosediate Impaet -Grasel (G2) - 312 Kd Estimate mU 5 M.n Max

0

01II(

0II

22 2(000 6110 200

0.06

I 1 10a3

0

2 4 10 311 1001

0.01

0 0.2

000O

11 0.2 3 2 II

0

0

1

0.2 0.0 5 tO unsuitable

01.02

0.2 10.8 01 5 ussitable

2

0.02 (1.4 0.1 500 100~l

0.

110

a 0 0.1 0

0.6

2 4 1I (5 tOO

es 0 0

15.3 310 60 310

0

211

0 01.112 0 tOO

0. (1

0.!

0.6

0

0.3

Ground-ster (C) - 3G

(1KEsttneimLI c1 d Mn

Bst

a

Ma

0

0

0

11 (0.02 0 0.2 I

0.2 0.4 0.1 3 (1(01

0.2 0.8 5 II0 unsuitable

0 0.2 1 2 0

2 4 II0 30 100

3.1 31 l1ll 62

1.6 3.1 62 3.1

6.2 310 620 3111

22 2(110 600 200

10I 21(1 200 tO

11.6

0.02

0 11

0016

0.2

0.1

0.3

0

II

003

0

2 4 II 1I 3(1 lun 100

0.02 1010 10.5 suitable

]

osO I 0 0

3.1 3.1 62 3.1

II 0 0 I 0

02

0 0

III 0.01 0

6.8 31 190 62

0

CCI4i Elmet Inorganic Elements CcVl

Ma

50 1000 2011(1 1000

11.2 0.2 0 2 unsuitahle

Eul52

Mm

3110 00

Istertediae lImpact- Sand(GI) -311 Kd Estimate ImL/g) *!nl Best IMtn MaIs

10 11 61 2(1

(14 simtd

11.0 0,08 0 2110 u(1 nsuitable

1 100

t

(10 0 0I

Grumd, at, (F 1) - 2G

50 1101110 2000 00 0.6 0I13

Waste Chemistry/Source Category 4: Low Organic/Low Salt/Near Neutral

oaxeBest rHighlyMobile Elements H3 TeSS C136 SomewhbatMohile Elements 1129 U238 Sc79 Np237 C 14 Modecately Immohile Elements Or9() Cs 137 Pu239 Eu152 Organic Elements CC14 Inorganic Elements CcVI

e (Fl) - 4H HahIn KdEsaate (.L/4) Mao Ma 0 1 II

0 0 0

0 1I )l)

0.2 10 5 tO usuitable

I 0.2 3 2 6

2 4 I 31 100

22 2000) 6001 2001

II0 2001 200 10

11.2

0.1

06

0

II

03

511 1000011 2000 10001

lostemusdiatelotpact - Gcasel (F2) - 412 lKd Estimate mLI') Mao s Max

Istesoediate lImpact - Sand (ElI)- 411 Kd Estimate (mL/i') Best L M.o MI 010 0 0 0.2 0,8 5 10 ansaitable 22 20100 6011 2111 11.2

II 1),11.1 I

II II I 0.2 3 2 0 l10 2001 2100 I0 1I

2 4 31 100 S() 1100100 2000 11000 06 (3 0III

4.15

.0

0 01 0

I0 0.02 ()()8 15 0I

Gsoaodssate (FlI - 46 K Estmtedl Best Mi Ma 0

0

0

11

11.2 11

01 0.2 3 2

2 4 10 30 100~l

10 200 2001 I0

50) 1111111 21000 1011

asailable

0.02 0.3 012 0

012 04 1 3 10I

7 620 l19l 62

3 62 62 3 1

16 31101 621 31l0

0.02

01.011

01.06

0.2

113 00(

I

5 10 usuitable 22 200011 6110 2110

0.1

1 0I 01 0

0I6 0.3

where CG and CG, refer to the carbon content in the stationary and mobile phases, respectively. The equilibrium constant can be defined as:

K(' 4C/'2 C) =

f(' 4C/' 2C)/(' 4C/ 2C)

(4.2)

This equilibrium constant is a pure thermodynamic constant. At a given temperature, it leads to a selectivity that is based only on the mass difference. Application of this concept to selection of a Kd value for ' 4C is problematic. Previous work using columns composed of a natural carbonate sand (aragonite and calcite) has demonstrated that the exchange process occurs at the first mono-molecular layer (Gamnier 1985); however, the adsorption process was found to be complicated by kinetic and other factors. Kinetic factors that affected the results included flow rate and sediment aging. Adsorption of other ions such as HP) 4 - was also found to significantly reduce uptake of H1'C03 by the carbonate surfaces.

In addition to isotopic exchange, the migration of H14 C03- or 14 C032 could potentially be retarded through precipitation of sodium/calcium carbonates that could occur during exposure to high pH, high salt concentrations in high level waste within tanks or released from leaking tanks or disposed in trenches. Because of the high pH conditions within the tanks, any CO 2 within the system will be in the form of 2-2 C0 3 As a result of the extremely high sodium concentrations within the tanks, most of the CO-? will precipitate as NaCO3. Initially the 14 C03 2 within the tanks is likely to be at trace concentrations and could be below the solubility limit; however, as C0 2 from the atmosphere enters the system from -.

openings in the tank, Na2 CO3 Will precipitate, removing

14 C03 2

in the process. If a tank leak were to

occur, this process would continue within the vadose zone as CO 2 from the atmosphere diffuses through the vadose zone into the tank leak impact zone. Because of the complex processes described above that impact the mobility of 4C, a simple linear adsorption model will not adequately describe its transport from a tank leak and through groundwater. As

a result of these uncertainties with regard to H1'C03_ or 14C032 - retardation within Hanford sediments, a large range in K& values has been selected. The best estimate was taken to be zero and the minimum and maximum were taken to be zero and 100, respectively.

4.3.3

Chlorine-36 (as chloride)

Chloride K,, value measurements are not available for Hanford sediment. This species is not expected to form complexes in Hanford groundwater, nor is it expected to undergo significant adsorption. Chloride is generally considered to exhibit conservative behavior. Measurements of chloride adsorption on clay, sandstone and granite indicated no adsorption (Stenhouse 1995). In acid soil rich in kaolinite, and iron and aluminum hydrous oxides, some chloride adsorption can occur (Higgo 1988); however, Hanford sediment does not have these characteristics. As a result the minimum, maximum, and best value for the chloride K, value is taken to be 0.0 ml/g.

4.3.4

Selenium-79 (as selenate)

A fair number of Se(VJ) Kd values have been determined using natural Hanford sediment (Cantrell et al. 2002). These results indicate that at trace concentrations, adsorption of Se(V} to Hanford sediment is low to moderate with K,, values ranging from 3 to 10 mL/g. At higher Se(VI) concentrations, the K, 4.16

values are lower (0 to 3 mL/g). Acidic conditions typically increase adsorption for anions such as selenate, but this cannot be confirmed for Hanford sediments with the available data. Basic conditions significantly reduce adsorption.

4.3.5

Strontium-90

The best estimate Kd value for strontium selected for most Hanford impact zones and source categories is 22 mI/g with a range of 10 to 50. In acidic high impact zones the best estimate is reduced to 10 ml/g with a range of 5 to 15. For the chelates/high salts source category, the best estimate for the high impact zone is 0.5 ml/g with an range of 0.2 to 20 and for the intermediate impact zone the best estimate is 10 ml/g with a range of 5 to 20. It is expected that in future work will incorporate ongoing multicomponent ion exchange data to provide a more scientifically defensible approach for estimating Kd values for strontium-90.

4.3.6

Technetium-99 (as pertechnetate)

The best estimates for the Kd values of pertechnetate are zero. The ranges were taken to be from zero to 0. 1 mI/g for all source and impact zone categories (except gravel corrected). When comparing this range to values tabulated in Cantrell et al. (2002), the range may appear to be somewhat narrow; however, in most cases when higher Kd values were measured, the Kd values were not significantly greater than the standard deviation. As a result of this and the fact that it is known that pertechnetate is a very weak adsorbate, this narrow range for the lKd values was selected. It should be noted that in environments where reducing agents are present, significantly higher immobilization of pertechnetate could potentially occur that is not represented by this range of Kd values.

4.3.7

Iodine-129 (as iodide)

The best estimate value selected for the iodide Kd appropriate for most Hanford impact zones and source categories is 0.2 ml/g with a range of 0 to 2. For acidic high impact zones, the best estimate value selected is 4 with a range of 0 to 15. Because pH effects resulting from acidic discharges were assumed to impact only the high impact zone categories, intermediate impact zones Kd values are assumed to be the same as for groundwater. High pH and high salt appear to reduce Kd values. This would result from increasing negative charges on sediment surfaces at high pH and increased competition with other anions at high salt concentrations. As a result, for high pH and high salt in the high impact zone a range of Kd values of 0 to 0.2 was selected with a best estimate of 0.02 ml~g. For the intermediate impact zone, the best estimate is 0. 1 ml/g.

4.3.8

Cesium-137

For cesium the best estimate Kd value selected for most Hanford impact zones and source categories is 2,000 ml/g with a range of 200 to 10,000. For acidic source categories and high impact zones the best estimate is reduced somewhat to 1,000 ml/g. For the high impact zones of the very high salt/very basic and chelates/high salts source categories the best estimate is 10 ml/g with a range of 0 to 500; for the

4.17

intermediate impact zone the best estimate is 100 ml/g with a range of 10 to 1,000. It is expected that in future work will incorporate available multi-component ion exchange data to provide a more scientifically defensible approach for estimating Kd values for cesium- 13 7.

4.3.9

Europium-152

value data are not available for adsorption of Eu3 on Hanford sediments; however, the chemistry of is very similar to AM (Cantrell 1988; Allard 1982), so Kd data available for AM 3~ adsorption onto Hanford sediments has been used as an analog for Eu3 - (Cantrell et al. 2002). Review of this data suggest a best estimate of 200 ml/g with a range of between 10 and 1,000. Kd

Eu3

4.3.10

Uranium

The best estimate Kd value for uranium selected for most Hanford impact zones and source categories is 0.8 mu/g, with a range of 0.2 to 4. For high impact zones with sources that are acidic or contain chelates, the best estimate value is reduced to 0.2 ml/g and with a range of 0 to 4. Although the Kd value for very basic conditions is taken to be the same across each impact zone, no reliable data are available at high pH (one measurement is available at pH 11, but precipitation of the uranium is believed to have occurred in this case).

4.3.11

Neptunium-237

Np(V) Kd values for Hanford sediment compiled in Cantrell et al. (2002) indicate Np(V) adsorption is generally moderate, with Kd values in the general range of 2 to 30 ml/g. Lower values can result at contact times of I day or less, and high calcium or chelate concentrations in solution. High solution pH values can result in very high Kd values; however, this may actually be due to precipitation. These results indicate that Np(V) migration from a tank leak should be minimal except when the tank wastes contain chelates. Moderate migration of Np(V) could occur in the vadose zone and groundwater under natural Hanford conditions. Because precipitation is the most likely removal mechanism for Np(V) retardation at high pH, the same range of high Kd values was used for the High Impact, Intermediate Impact and the Intermediate Impact - Gravel Zones of the Very High Salt/Very Basic waste category.

4.4

Hydrostratigraphic Templates

Of the more than 2,730 waste sites at Hanford and several storage sites, a subset of 1,046 sites has been selected for inclusion in the 2004 Composite Analysis. A unique alphanumeric identification tag (i.e., the site code as given in the Hanford WIDS system), was used to identify each waste site for vadose zone simulation. For example, the 241 -T- 106 tank was identified by its WIDS site code "241 -T- 106." Initially each site was assigned to a hydrostratigraphic template based on its location within one of the 16 geographic areas, its site type (surface, near surface, tank, or injection well), and its waste chemistry designation. Other waste site-specific information (location, facility dimensions, and surface cover) was assigned to define the site-specific parameters needed to perform the vadose zone simulations.

4.18

4.4.1

Assignment of Waste Chemistry Types

As described in Section 3.2.3, a waste chemistry designation was assigned to each facility to be simulated in the 2004 Composite Analysis. This assignment was based on the original waste chemistry designations used in the 1998 Composite Analysis (Kincaid et al. 1998) and translating these six waste chemistry categories to the four categories used in this study (see Section 3.2.3). In assigning waste chemistry designation to facilities not included in the 1998 Composite Analysis, the following approach was taken: " Burial grounds, process sewers, ponds, retention basins, buildings, cooling water, stacks, steam condensate, and sand filters were assigned a "low salt, near neutral" waste type (waste type 4). " All 241 facilities were assigned a "high salt, very basic" waste type (waste type 2). Note that some tank wastes are designated as containing "chelates and high salt" (waste type 3) (Kincaid et al. 1998). This simplifying assumption to group essentially all tank waste into just two waste types on which to assign Kd values does have obvious limitations. * Liquid waste facilities that lacked a waste type designation, were assigned a waste type based on waste descriptions by Maxfield (1979) and/or the various Source Aggregate Area Management Study Reports (e.g., DOE 1992; DOE 1993e). " The WIDS was consulted for all remaining facilities. If the WIDS indicated a source for the effluent discharged to a facility, the facility was given the waste type for the source. In a few instances, WIDS provided no information and a waste type 4 was assigned. " Unplanned releases associated with a facility were assigned the waste type given to the facility. " Unplanned releases of solids (e.g., animal waste, contaminated equipment, particulates), and atmospheric releases were assigned waste type 4. " Unplanned releases with insufficient information were assigned a best guess of waste type 4. " Petroleum spills are obviously high organic but they do not fit the idea of waste type 3. Therefore, petroleum spills were arbitrarily labeled waste type 4. The waste chemistry designations for all facilities represented in the 2004 Composite Analysis are provided in a master spreadsheet of site-specific parameters and model designations (the General Operational Site Parameters List [GOSPL], see Last et al. 2004).

4.4.2

Facility Location, Dimensions, and Wetted Area

The facility location is used to assign geohydrologic properties and specify where waste that is leaving the vadose zone enters the groundwater model. The locations of most waste facilities were obtained from the WIDS. If a facility location was not in WIDS, the location was estimated using other available resources such as the Hanford Site Waste Management Units Report (DOE 2003), the Hanford 4.19

Site Atlas (BHJ 1998) and Maxfield (1979). Facility locations were assumed to be the centroid of the facility (in state-plane coordinates). Long linear facilities (such as ditches) generally do not have center coordinates listed in WIDS, so their coordinates were estimated based on visual inspection of the Hanford Site Atlas and/or other site maps. The facility surface area (also called the facility footprint) was used to estimate the waste release area (e.g., the bottom area of a crib) and the dimensions of the surface barrier (if any). Facility surface areas of many sites were obtained from the WIDS. If the WIDS did not contain the facility surface area, the area was estimated using the facility length and width or the facility diameter. If no data were found to estimate facility area, a default value was assigned. The default values are combinations of three "9"s for easy recognition as default values. Table 4.11 lists the default values used for the four different site types. Table 4.11.

Default Surface Areas

Facility (site) Type Unplanned Release, French Drain Storage Tank, Trench Radioactive Process Sewer, Crib Burial Ground

IDefault Area

(in)

0.999 9.99 99.9 __________

99

The wetted column area (in essence, the wetted vadose zone area) represents the maximum area] extent of the waste as it migrates to the water table. For at least some sites, the facility area in WIDS represents the fenced boundary rather than the actual waste release area, which can be significantly smaller. It is also possible that the waste at some sites could spread laterally and extend beyond the facility boundaries. Until the waste-zone area of each individual waste site is determined, we will continue to assume, as was done for the previous composite analysis, that the waste zone area equals the facility area. The result of this assumption is that, whenever the waste zone area is significantly smaller than the wetted column area, the source term will be dispersed over the larger wetted column and migrate downward more slowly. Conversely, when the waste zone area is larger than the wetted column, the source term will be dispersed over the smaller wetted column area and migrate downward more quickly. In certain simulation cases, the volume of liquid disposed per facility area exceeds the capacity of the vadose zone to transmit it. Either the vadose zone sediments have very low conductivity values or the facility area is inordinately small (e.g., reverse wells listed as having a facility area equivalent to the borehole diameter). In the field, this situation would result in significant lateral spreading beyond the facility footprint. The impact of lateral spreading will be represented in the 2004 Composite Analysis using the Ksdependent approach. In this approach, the wetted vadose zone area A, (M 2) is related to the facility footprint by the scaling factor A (dimensionless), as follows: A = /AA)

K. I u

4.20

IAO A

>1 !

(4.3)

where

Qax

K, A0

maximum artificial liquid discharge rate (m 3/s) minimum hydraulic conductivity (mis) of all layers for the given site and realization the facility area (in 2 ) from the WIDS database

-the

=the

The major assumptions underlying Equation 4.3 are that the vadose zone layer with the lowest K, controls flow, a unit gradient is always present across the controlling layer, and flow is steady. The scaling factor, ;., is constrained by the SAC Environmental Settings Definition keyword file to be equal to or greater than 1.0 so that the effective area is not less than the facility footprint area, unless specified for a specific site. For example, 2 is usually permitted to be less than 1.0 for the underground storage tanks, for which the actual wetted area from leaks is commonly less than the facility footprint. For most sites with little or no artificial discharges, A usually resolves to 1.0 (no scaling) and hence the assigned WIDS area is used. For large-discharge sites, 2I values greater than 1.0 are common.

4.5

Recharge Estimates

This section provides recharge (deep drainage) estimates for use in the 2004 Composite Analysis. The recharge estimates were derived from a suite of available field data and computer simulation results (Fayer and Walters 1995; Murphy et al. 1996; Prych 1998; Fayer et al. 1999; Wittreich et al. 2003). The estimates do not account for overland flow from roadways or roofs, water line leaks, or any other manmade additions of water, the impacts wrought by future climate change or land use alterations, variations within soil types, or dune-sand deposition. The estimates were developed for fairly large geographic areas and may not represent the local recharge rates at specific locations. This section provides recharge estimates for natural and distributed soils and for surface barriers for each of the four intervals: pre-Hanford, operations, remediation, and post-Hanford. The conditions during these periods include natural soil and shrub-steppe plant communities, disturbances that alter the surface soil and vegetation, emplacement of surface barriers, and long-term changes that occur as the waste sites stabilize and return to natural conditions. This section describes the probability distribution of the recharge estimates. These distributions will be used in a Monte Carlo analysis to represent the expected range of recharge rates. This section describes a method to examine the impact of surface barrier side slopes and the terrain surrounding surface barriers, both of which could significantly affect waste release and vadose zone transport. Finally, this section summarizes the recharge estimates for all conditions.

4.5.1

Natural and Disturbed Soil

Prior to the establishment of the Hanford Site in 1943, the undisturbed soil and shrub-steppe plant community generally resulted in very low recharge rates. Those low rates led to the very dry vadose zone conditions that characterized the pre-Hanford period. During the subsequent operations period, the soil and vegetation at many of the waste sites were disturbed, which increased recharge rates; similar conditions will exist during the remediation period. In addition to the recharge that occurs directly in a waste site, recharge in the immediate vicinity of the site could affect transport of contaminants to the groundwater. Examination of the Hanford soil map produced by Hajek (1966) revealed five natural soil types prevalent in and around the waste areas. These soils are nominally I to 2 meters thick (at most) and

4.21

easily disrupted during construction activities. Experience shows that the dominant soil condition following construction is the underlying sediment, i.e., the Hanford sands. The only other soil type that might occur in the waste areas is a silt loam. Such soil does not currently exist in these areas. However, surface barriers will eventually age to the point where they eventually resemnble silt loam soil. Recharge estimates were assigned to the five undisturbed soil types and two sediment types for the following four plant community conditions: 1. Shrub-Steppe P/ant Commnunity. This condition is a mature plant community consisting of shrubs and bunchgrasses and associated fauna and flora. Table 4.12 lists the recharge estimates for the five soil types that dominate the areas being evaluated in the 2004 Composite Analysis. It is assumed that these soils, when undisturbed, will support a shrub-steppe plant community. Table 4.12. Estimated Recharge Rates for Predominant Soil Types and Sediment with a ShrubSteppe Plant Community

[

Recharge Rate Estimate

Soil Type

Ephrata stony loam

(mm/yr)

Description

1.5

No data; used estimate for El, which is a similar soil

15Avg. .5from

of two estimates (1.2: 1.8) from deep (>10 m) chloride data collected the two boreholes B 17 and B 18 (Prych 1998) Avg. of three estimates (0.66. 2.8. 5.5) from deep (>10 m) chloride data from the three boreholes BI10. B 12. and B20 (Prych 1998) Avg. of four estimates (0. 16, 0.58, 1.0, and 1.8) from deep (>1 0 m) chloride data collected from the four boreholes E24-16 1. E24-162, B850 1. B8502

(Eh)

Ephrata sandy loam (E-,) Burbank loamy sand (B,,) Rupert Sand (R,,) in 200 East

30collected 0.9 __________________(Fayer

Rupert Sand (RP) outside of 200 East Hianford-formnation sand Warden silt loam

et at. 1999)

40Estimated 40Barricade 4.0

from chloride data collected from a borehole near the Wye (Murphy et al. 1996) No data, used estimate for Rupert sand outside the 200 East area

0.11

1Ilighest of four values estimated from chloride data collected in silt loam soil (Prych 1998)

2.

No P/ants. This condition describes the case in which vegetation was removed and plants were prevented from re-establishing (e.g., weed control). This condition can be applied to the analysis of fire effects, although the duration without plants will be short (<1 year). Table 4.13 shows the recharge estimates for the case without vegetation.

3.

Sha//ow-Rooted P/ants. This condition describes the case in which a fire or Hantford operations destroys the existing shrub-steppe vegetation and the plants that re-vegetate the site are strictly shallow-rooted (e.g., cheatgrass). Very few recharge data are available for native soils and backfilled sediments with shallow rooted grasses such as cheatgrass (Fayer and Walters 1995). For the purposes of this analysis, it was estimated that a cheatgrass cover will reduce the recharge rates listed in Table 4.13 by 50%. Thus, Ephrata stony loamn will have an expected mean annual recharge of 8.5 millimeters per year and a graveled surface will have a recharge rate of 44.5 millimeters per year if the surface is covered with cheatgrass.

4.22

Table 4.13.

L

Soil Type Ephrata stony loam (Eh) Ephrata sandy loam (E,) (F 1) Burbank loamy sand (B,) (B.) Rupert Sand (Rp) Hanfordformation sand Graveled surface

Estimated Recharge Rates for Soil Types and Sediment Without Vegetation Recharge Rate Estimate

(mm/yr)

Simulation estimate for period 1958 to 1992 (Fayer and Walters 1995)

17

Simulation estimate for period 1958 to 1992 (Fayer and Walters 1995)

53Simulation 44 558-yr

89

4.

[Description

17

estimate for period 1957 to 1997 (Fayer et al. 1999) Simulation estimate for period 1957 to 1997 (Fayer et al. 1999) (July 1984 to June 1993) lysimeter record for Hanford sand (Fayer and Walters 1995) 9-yr (Feb 1990 to Feb 1999) lysimeter record for graveled surface showed 52% of precipitation received became deep drainage (Fayer et al. 1999): drainage rate scaled to precipitation rate of 172 mm/yr

Young Shrub-Sieppe Plain Conmmunity. This condition describes the case in which a young shrubsteppe plant community is developing in an area that had previously been disturbed by an event such as a fire. It was estimated that recharge in such areas will be double the rates estimated for mature shrub-steppe conditions (Table 4.12).

Table 4.14 shows the estimated recharge rates for various surface conditions for the 16 geographic areas, along with a brief description of each setting and major soil type that was identified using the Hajek (1966) soil map. If a significant secondary soil type was present, that soil type and its estimated recharge rate are shown in parentheses. Note that a recharge estimate of 1 millimeter per year was assumed for those sites that discharged directly to the river, and an estimate of 0.1 millimeter per year was assumed for those sites covered by asphalt, concrete, or building. 4.5.2

Surface Barriers

The Hanford Disposition Baseline and Kincaid et al. (2004) determined the schedule and type of engineered surface barriers to be applied to each site for the 2004 Composite Analysis. This section describes the recharge rates to be used for barriers during the institutional control period, their design life, and after their design life. A key assumption of the 2004 Composite Analysis is that deep drainage beneath barrier side slopes and the surrounding terrain does not appreciably affect contaminant release and transport. This assumption is consistent with the previous composite analysis as well as recent and ongoing assessments. To date, the assumption has not been tested. Therefore, estimates of side slope drainage are provided here for possible use in sensitivity tests. 4.5.2.1

Barrier Tops

DOE conducted a focused feasibility study of engineered surface barriers and identified four designs that mnet Hanford needs (DOE 1996). Table 4.1 5 lists the four designs and the expected design life of

4.23

Table 4.14.

Estimated Recharge Rates by Soil Type/Sediment and Vegetation Condition in Each Hanford Area. Significant secondary soil types and their associated recharge estimates are shown in parentheses

T

Major (Secondary)(a)

Area Label C K N D H F R

Q P M G T S A B E --

--

--

Brief Description

{Soil

Type(s)

and Sediments

Reactor along river FEh (na) Reactor along river Eb (Ed) Reactor along river F,, Reactor along river E, Reactor along river B, Reactor along river Rr (Ed) 300 Area R, (Ed) R, (B.) 400 Area 618-10 Area R, (B.) 6 18-11 Area Rp, (B.) 200N Area El (Ba) Northern 200W Area Rp (Ba) Southern 200W Area Rr44 and ERDF Southern 200E Area Rp, (Ba) Northwestern 200E El Area Eastern 200E Area Ba (R~a) All Areas with soils Hanford sand disturbed by excavations All Areas with a Warden silt surface barrier loamnaa0.2.1 All Areas with gravel gravel

surface and no plants Eh Ephrata stony loam El,

{Young Estimated Recharge Rate (mm/yr)

No Vegetation

Cheatgrass

Shrub-Steppe

Shrub-Steppe

17(53) 17(17) 17 17 53 44(17) 44(17) 44 (53) 44 (53) 44 (53) 17(53) 44 (53)

8.5 (26.5) 8.5 (8.5) 8.5 8.5 26.5 22(8.5) 22(8.5) 22 (26.5) 22 (26.5) 22 (26.5) 8.5 (26.5) 22 (26.5)

3.0 (6.0) 3.0(3.0) 3.0 3.0 6.0 8.0(3.0) 8.0(3.0) 8.0 (3.0) 8.0 (3.0) 8.0 (3.0) 3.0 (6.0) 8.0 (3.0)

1.5 (3.0) 1.5(1.5) 1.5 1.5 3.0 4.0(1.5) 4.0(1.5) 4.0 (3.0) 4.0 (3.0) 4.0 (3.0) 1.5 (3.0) 4.0 (3.0)

22

8.0

4.0

44(53) 17

22(26.5)

1.8 (6.0)

0.9 (3.0)

8.5

3.0

1.5

53 (44)

26.5 (22)

6.0 (1.8)

3.0 (0.9)

55

27.5

8.0

4.0

an0.2.1

89 I_______

44.5

an I___I___I

Ephrata sandy loam B, = Burbank loamy sand Rp Area. Rupert sand in 200 East Rp, (a) =Note: Only the major soil types were used to represent each aggregate area.

Rupert sand

each. For the 2004 Composite Analysis analyses, only the Hanford barrier and the modified RCRA C barrier are being evaluated for sites that require protection. Recharge rates for the top portion of the surface barriers were estimated from field studies of surface barrier systems at Hanford (Fayer et al. 1999; Wiltreich et al. 2003) and are shown in Table 4.15. 4.5.2.2

Barrier Side Slopes

This discussion of recharge through barrier side slopes is provided only for completeness and to provide the basis for possible use in sensitivity analyses. A significant number of the surface barriers

4.24

Table 4.15.

Barrier Design Life and Estimated Recharge Rates for Barrier Tops Recharge Rate (mmlyr)

Design Life (yr) ,0000.1 Brrir Hanfrd 10000.1 Hanfrd arrer

FFS Design (DOE/RL 1996)

J

5000.1 5000.1

Modiied CRA Modiied CRA

Standard RCRA C 30 (not evaluated in the 2004 Composite Analysis) Modified RCRA D 100 (not evaluated in the 2004 Composite Analysis)_____________________

Source Based on lysimeter data and simulation results (Fayer et al. 1999; Wittreich et al. 2003) Based on lysimeter data and simulation results (Fayer et al. 1999) No data; recommendation is based on presence of Geomembrane and 2-ft thick clay admix layer _____________________ Based on simulation results using parameters from Fayer et al. (1999)

0.1

0.1

being planned at Hanford will be above-grade structures that require stabilizing side slopes. Two side slope designs are currently being tested at the Prototype Surface Barrier (Wittreich 2003). One design, called "Gravel," is a sandy gravel/gravelly sand mix emplaced at a 10 horizontal (H):1I vertical (V) slope. The second design, called "Basalt," is open-work basalt riprap emplaced at a 2H: IlV slope. Neither design incorporates any plant-promoting features. Since being constructed in November 1994, the sandy gravel side slope has had very few plants established and the basalt side slope has had none. Drainage data have been collected since November 1994. During that period, records show that Hanford received higher-than-normal precipitation. Therefore, the side slope drainage data were scaled to the long-term precipitation average to yield long-term estimates of side slope recharge rates. Hoitink et al. (2003) reported an annual mean precipitation at the Hanford Meteorological Station (HMS) of 172 millimeters per year, based on HMS records from 1946 through 2002. For the 2004 Composite Analysis, we assumed the long-termn precipitation average was 172 millimeters per year and scaled the drainage data accordingly. The full set of drainage data encompassed the period from November 1994 to September 2002. For the estimation process, the drainage data from the first year (up to October 1995) were not included so as to avoid any effects from the initial conditions. Drainage was not measured during the period from October 1998 to September 1999. The remaining data, which spanned a total of six years, were used to estimate recharge rates for the period immediately following barrier construction. Table 4.1 6 shows these estimates for the two side slope materials in the current baseline for above-grade surface barriers.

Table 4.16.

Side Slope Type Gravel (mix of sand and gravel)

Initial Side Slope Recharge Rates for Hanford Site Climate Conditions

1

jSlope

r

Initial Recharge Rate

42

I OH: IV

Source

(mm/yr)

Based on six years of drainage data from the prototype surface barrier (Wittreich et al. 2003) scaled to average of 172 mm/yr.

_______ _______________precipitation

Basat (pen-orkBased 2H:IV Basaltpenwr riprap)precipitation

32

on six years of drainage data from the prototype surface barrier (Wittreich et al. 2003) scaled to average of 172 mm/yr.

4.25

We do not expect the initial recharge rates shown in Table 4.16 to persist forever. During the 100 years of institutional control, we expect the plant community on the side slopes to slowly develop and mature to the point where recharge rates beneath the side slopes resemble Burbank loamy sand and a shrub-steppe plant community. Therefore, we propose representing side slope recharge rates in a timedependent fashion during the period of institutional control. 4.5.2.3

Surface Barriers Post-Hanford

No guidance is available for specifying barrier performnance after the design life. In the previous composite analysis (Kincaid et a]. 1998) barrier performance after the design life was simply assumed to end, after which recharge rates were set equal those of the original soil type at each location. However, there is no basis for assuming the surface barr ier will disappear or evolve to resemble the local soil. What will happen is that the barrier will continue to experience soil and ecological processes that will alter the nature of the barrier and affect it's performance. Appendix D describes processes that could potentially affect barrier performance and outlines several scenarios that could be used to simulate performance after the design life. Fayer et al. (1999) examined two key natural processes (erosion of the silt loam layer and deposition of dune sand on the barrier) that could alter barrier performance. Their results suggested that neither process would significantly alter barrier performance. Thus, after the barrier design life, the barrier would continue to function as designed; the barrier top would most likely resemble a Warden silt loam and the side slope would most likely resemble the Ephrata stony loam. For the 2004 Composite Analysis, the approach chosen to describe barrier performance after the design life was to retain some functioning after the design life but for a limited duration equivalent to the design life. For example, the modified RCRA C barrier top would perform as designed for it's 500-year design life, after which the barrier performance would be changed linearly to the final rate (the recharge rate for the equivalent soil type, which in this case would be Warden silt loam). For simplicity and ease of implementation, the changes in performance after the design life will be represented by five equal stepwise changes in recharge during the degradation period. 4.5.3

Probability Distribution Functions

After reviewing the possible probability distributions, we chose a three-point triangular distribution to represent recharge at all sites. In this distribution, the low value is equal to the mean value minus the standard deviation and the high value is equal to twice the mean value. The number of recharge estimates is too small to calculate adequate statistics, so recharge statistics (mean and standard deviations) were estimated using statistics from winter precipitation. Data from HMS precipitation records from Hoitink et al. (2003) and current Hanford Site weather records (http://hms.rl.gov/products.htm) were used to obtain the mean value and standard deviation of the extended-winter (November through March) precipitation for the period from November 1946 to March 2003 and resulted in a mean value of 101 millimeters per year and standard deviation of 40 millimeters per year. We reasoned that winter precipitation was the primary source of recharge and that recharge would seldom, if ever, exceed winter precipitation; so all recharge values were keyed to the mean extended winter precipitation as the upper limit of recharge. Because the available data were limited, we estimated the standard deviation for all 4.26

surfaces as equal to half the mean value. This appears to be a conservative estimate based on the statistic for the extended winter precipitation. As more data are collected for various surface conditions the actual standard deviations can be substituted.

4.5.4

Integrated Drainage Calculations

A key assumption of the baseline analysis of the 2004 Composite Analysis is that vadose zone waste is only affected by the recharge that occurs beneath the surface barrier tops. The implication of this assumption is that recharge occurring beneath the barrier side slopes (if present) or in the areas immediately surrounding the surface barrier will not affect the mobilization of waste beneath the surface barrier nor the transport of the waste contaminants to the water table. To test the assumption, a method was developed to integrate the drainage rates from the barrier top and side slopes (or surrounding terrain if no side slopes) into a single composite rate that could be used for sensitivity analyses in the 2004 Composite Analysis. In the composite analysis, each waste site is characterized by two drainage estimates defined as follows: Release Model Drainage. This drainage rate directly affects the behavior of the release model. The assumption is that the waste form is directly beneath the intact and functional part of the surface barrier and affected only by recharge through the barrier top. Any recharge through the barrier side slopes or in the areas surrounding the barrier is assumed to have no impact on the waste form. Vadose Zone Model Drainage. This drainage rate directly impacts the transport of contaminants released by the waste form through the vadose zone and to the water table. In the baseline 2004 Composite Analysis, the vadose zone drainage rate is equivalent to the barrier top drainage rate. However, for sensitivity tests of this assumption, the vadose zone drainage rate could be assigned a value that is a composite of recharge through the barrier and recharge through a portion of the barrier side slopes or surrounding terrain. The impact of higher drainage rates around a surface barrier is a function of individual site characteristics such as barrier geomnetry and dimensions, distance to the water table, geology, physicalhydraulic-chemical properties, and contaminant depth and characteristics. Given the diversity of site characteristics and the one-dimensional conceptual model used in the 2004 Composite Analysis, the analysis was simplified for the purpose of demonstrating sensitivity without having to represent the unique features of every site. For this purpose, the recharge rates were integrated by weighting the recharge contributions from the barrier and the contributing portion of the side slope based on their respective areas referenced to the total area. Some of the recharge beneath the side slope will affect contamninant transport beneath the barrier and some will move away from the barrier and have negligible impact on contaminants. This partitioning was represented by assuming that half the side slope area would contribute to contaminant transport. The resulting integrated vadose zone drainage rate (rh) is computed as follows: hh , hi

r., _5.,

4.27

)/h

(4.4)

where rh,

drainage rate of the barrier top drainage rate of the barrier side slope A&h = area of the barrier top Ah, =area of the barrier side slope Ab= total area of the barrier and contributing side slope; sum of Ab, and 0.5 *Ab, =

rh.

The following example illustrates how the integrated recharge rate from a modified RCRA C barrier with side slopes might affect the overall vadose zone drainage rate. Modified RCRA C Barrier " shape =square, 316 m on a side, yielding area AN, = 10 ha " height =5 m above the surrounding terrain " surface barrier drainage rate rb, = 0.1 mm/yr Gravel Side Slope " slope=5H:IV " slope length = 25 mn " contributing area, 0.5 * Ah, = 1.71 ha (equal to one-half of the side slope area) " drainage rate r., = 3.0 mm/yr (assumed mature shrub-steppe plant community) Using Equation 4.4 and the values provided above, the integrated vadose zone drainage rate is rh =[0.lx10+ 3.0 x.71]/11.7 =0.52 mm/yr

(4.5)

If the waste site requires the barrier area to be doubled to 20 hectares, the contributing side slope area would be 2.35 hectares and the integrated vadose zone drainage rate would be rh =

[0.1 x 20 + 3.0 x 2.36]/22.4

=

0.41 mm/yr

(4.6)

The integrated drainage rate for the 10-hectare waste site is 5 times larger than the barrier top drainage rate. For the 20-hectare site, the integrated drainage rate drops to 0.41 millimeter per year, but it is still 4 times larger than the barrier top drainage rate. These examples show that, for surface barriers in the range from 2 to 20 hectares (typical of what might be expected for the Hanford Site), side slope drainage can significantly increase the vadose zone drainage rate. To further dramatize the significance, consider the case where the side slope drainage rate is equal to the rate currently measured beneath the gravel side slope at the prototype barrier. If plants never establish on the side slope and the rate remains at 42 millimeters per year, the integrated vadose drainage rate would be 6.2 millimeters per year for the I 0-hectare barrier and 4.5 millimeters per year for the 20-hectare barrier. To further illustrate the effect of barrier dimensions on drainage, if the barrier were reduced to I ha with a corresponding side slope area of 0.62 hectare, the integrated drainage rate would be increased to 16.2 millimeters per year. The impact of the side slopes on integrated drainage rates decreases as the size of the barrier increases. Plans for surface barriers typically assume that the barrier top will extend 10 meters beyond

4.28

the edge of the waste to provide more protection. The extent of such overbuilding is colloquially referred to as the barrier overhang distance. The overhang will increase the functional area of the surface barrier and somewhat decrease the impact of any side slope. For the 2004 Composite Analysis, however, we assumed no overhang. If surface barriers are built at or near ground level to eliminate side slopes, they will still be prone to the influence of drainage rates in the surrounding soils. The analysis of impacts from such drainage can be evaluated using a similar methodology to that used in evaluating side slope impacts. 4.5.5

Recharge Classes

To facilitate the assignment of recharge rates for individual waste sites, four sets of recharge classes were developed: 1) rates for baseline soil conditions with shrub-steppe plant community; 2) rates for disturbed conditions or for sensitivity tests (e.g., native soils or backfilled soils; with or without vegetation; asphalt, concrete, or gravel covers); 3) rates for surface barr ier components; and 4) integrated rates for surface barriers with side slopes. In all cases, the waste site drainage rates described by Equation 4.4 were assumed to be directly equivalent to recharge rates (i.e., all drainage subsequently becomes recharge). Each recharge class was identified with a unique code based on either the primary native soil and vegetation type or the type and size of the surface barrier. Tables 4.17 through 4.21 provide the estimated recharge rates for each class. Table 4.17.

Estimated Recharge Rates for Baseline Soil Conditions

Best Recharge Class Code Eh-s E,-s

Description Ephrata stony loam (Eb) - with shrubsteppe (s)plant community Ephrata sandy loam (E1 ) - with shrub-

1.5

0.75

3.0

Burbank loamy sand (Ba) - with shrub-

1.5

1.5

6.0

0.45

0.45

1.8

4.0

2.0

2.0

8.0

0.11

0.06

0.06

0.22

3.0 ________

Rupert sand (Rp) in 200 East (e) - with

0.9

shrub-steppe (s) plant community

Rnp-s Wa5s

-(mim/yr)

________

steppe (s) plant community

Rp,-s

Minimum Maximum (mmlyr) 0.75 3.0

0.75

steppe (s) plant community Ba5s

TEstimated Standard

Estimate Deviation (mm/yr)~ (mm/yr) 1.5 0.75

________

Rupert sand (Rp) outside 200 East - with shrub-steppe (s) plant community Warden silt loam (Wa) - with shrubsteppe (s) plant communityII1

4.29

Estimated Recharge Rates for Disturbed Conditions and Sensitivity Tests

Table 4.18.

Recharge

Class Code Eb-ds Eb-dg

Best

Estimated Standard

Estimate

Deviation

(mm/yr)

Description Ephrata stony loam (4j), disturbed (d) -

(mm/yr)

3.0 with young shrub-steppe (s) vegetation_____ 9 Ephrata stony loam (Eb), disturbed (d) -

Minimum

(mmlyr)

1.5

1.5

4.5

4.5

with cheatgrass (g) vegetation

Eb -dn E1-ds Ej-dg E1-dn

B,-dg Ba-dn R,,-ds

(My~a

6.0 18 _____

Ephrata stony loam (Eh), disturbed (d) with no (n) vegetation Ephrata sandy loam (E,), disturbed (d) with young shrub-steppe (s) vegetation Ephrata sandy loam (E1), disturbed (d) with cheatgrass (g) vegetation Ephrata sandy loam (E,), disturbed (d) -

17

8.5

8.5

34

3.0

1.5

1.5

6.0

9

4.5

4.5

18

8.5

8.5

34

6.0

3.0

3.0

12

26

13.0

13.0

52

53

26.5

26.5

101

1.8

0.9

0.9

3.6

22

11

11

44

44

22

22

88

17

with no (n) vegetation

B0-d

Maximum

________

Burbank loamy sand (Ba), disturbed (d) with young shrub-steppe (s) plant community Burbank loamy sand (B,,), disturbed (d) with cheatgrass (g) plant community Burbank loamy sand (B,), disturbed (d) with no (n) vegetation Rupert sand (Rp) in 200 East, disturbed (d) - with young shrub-steppe (s) plant

_________community

Rp,-dg

Rp,-dn

Rupert sand (1?) in 200 East, disturbed (d) - with cheatgrass (g) plant community Rupert sand (R.) in 200 East, disturbed (d)

Rp-ds

Rp-dg

Rp-dn IL-dn G-dn ABC (a) -Note:

-

with no (n) vegetation_____

4.0 16.0 8.0 4.0 Rupert sand (Rp) outside 200 East, disturbed (d) - with young shrub-steppe (s) plant community 44 11 11 22 Rupert sand (Rp) outside 200 East, disturbed (d) - with cheatgrass (g) plant community 22 88 44 22 Rupert sand (I?) outside 200 East, disturbed (d) - with no (n) vegetationI 27.5 101 55 27.5 Hanford Sand (I-h), disturbed (d) - with no (n) vegetation 44.5 101 89 44.5 Gravel surface (G), disturbed - with no (n) vegetation 0.2 0.05 0.1 0.05 Soil Surface covered by Asphalt, Building, or ConcreteI the maximum recharge was truncated at the mean extended winter precipitation value of 10 1 mm/yr.

4.30

Table 4.19.

Estimated Recharge Rates for Surface Barrier Components Best Estimate

Recharge RCRA C Hanford Wa5s

Gr5s

L Gr-n

Im/r

Description

Code

________Class

Modified RCRA C - barrier top during design life Hanford Barrier- barrier top during design life Warden Silt Loam (Wa) - with shrubsteppe (s) plant community (Could be used to represent final degradation of barrier top) Gravel side slope - with shrub-steppe (s) plant community (Could be used to represent final degradation of gravel side slope)422218 Gravel side slope -no vegetation (n)

Table 4.20.

(mmlyr)

Recharge Class Code

[

Maximum (my)

m/r

0.1

0.05

0.05

0.20

0.1

0.05

0.05

0.20

0.11

0.06

0.06

0.22

3.0

1.5

1.5

6.0

422

18

Estimated Recharge Rates for Surface Barriers with Side Slopes and rbS

Barrier Type

Modified RCRA Cor Hanford

Estimated Standard Minimum Deviation

Cover Area, Ab' (M2)

128
= 3.0

]Maximum 1

Best Estimate

Minimum (mm/yr) 1.40 1.34 1.24 1.12 0.97 0.81 0.65 0.51 0.40 0.31 0.24 0.18

5.62 5.36 4.97 4.47 3.86 3.22 2.60 2.05 1.59 1.22 0.95 0.74

J(mm/yr)

j

(mmlyr)

-18 -19 -110 -1ll -112 -113 -114 -115 -116 -117 -118 -119

1
2.81 2.68 2.49 2.23 1.93 1.61 1.30 1.02 0.79 0.61 0.47 0.37

-120

524288
0.29

0.15

0.59

-121 -122

1048576 Abc2O97lS2 2097152
0.24 0.20

0.12 0.10

0.48 0.40

2 4

0 4 8
8 92

4.31

mm/yr

Table 4.21.

Estimated Recharge Rates for Surface Barriers with Side Slopes and rbS

Tlas]Rchage Barie Tpe

Modified RCRA C or Hanford

Code

ove AeaAh1

J(Mn)

-18 -19 -110 -111 -112 -113 -114 -115 -116 -117

12 8
-118 -119 -120 -121 -122

13 1072
25 6

262 44

4.32

=

42.0 mm/yr

] est Estimate [Minimum Maximum J(mmr) (mm/yr) L (mmlyr) 39.2 37.3 34.6 30.9 26.6 21.9 17.4 13.4 10.1 7.5 5.5 4.0 2.9 2.1 1.5

1

19.6 18.7 17.3 15.5 13.3 11.0 8.7 6.7 5.1 3.7 2.7 2.0 1.4 -1.00.8

1

78.5 74.7 69.2 61.8 53.1 43.8 34.9 26.9 20.2 15.0 11.0 8.0 5.8 4.2 3.0

5.0

Conclusions and Recommendations

The 2004 Composite Analysis will include one-dimensional stochastic simulations of flow and transport through the vadose zone for 1,022 of the 1,046 waste sites selected for inclusion in the 2004 Composite Analysis. The remaining 24 sites are just place holders to account for offsite transfers and nuclear materials and thus are not directly simulated. Data and interpreted information needed to define the input parameters for the vadose zone simulations have been extracted from existing documents and databases. This report describes the assumptions and rationale for 1) defining the hydrostratigraphy, hydraulic properties, and distribution coefficients for each site to be simulated; and 2) defining the recharge estimates for each site. To simplify the preparation of input files for the large number of sites, and to improve the computational efficiencies, the Hanford Site was subdivided into 17 geographically similar areas that could each be represented by a single generalized hy drostrati graphic column. The hydrostrati graphic columns for each of the 17 geographic areas were further modified to account for differences in the depth of waste releases, and differences in solid/liquid distribution coefficients (Kd values) affected by different waste chemistries. This resulted in 63 base templates, each with their own unique hydrogeologic stratigraphy, hydraulic parameter distributions, and Kd distributions. Flow and transport parameters are to be stochastically sampled for each hydrogeologic unit for each realization. Thus, each model node within a given hydrogeologic unit has the same set of parameters for a given realization. Recharge estimates are provided for four different conditions: pre-Hanford, operations, remediation, and post-Hanford. The conditions during these periods include natural soil with shrub-steppe plant communities, disturbed soil and vegetation, surface barriers, and degraded surface barriers as the waste sites stabilize and return to natural conditions. Probability distributions have been provided for each recharge estimate to facilitate Monte Carlo analysis in representing the expected range of recharge rates. There are many issues and sources of uncertainty that can affect the ability to predict the behavior of contaminants in the vadose zone. These include scale effects, spatial resolution of data, preferential flow, funneled flow, colloid transport, density effects, and thermal effects. Fogwell et al. 2003 has identified a number of data gaps related to key technical issues and parameter uncertainties. This includes a number of site characterization and laboratory study needs related to interpreting observations from past tank leaks, spills, and deliberate discharges. Adequate site characterization is important to estimate existing inventories, initial conditions, and also to demonstrate the validity of our understanding and the predictive ability of the models used for flow and transport. Estimating inventories and contaminant distributions is difficult because there is much about the history and character of the leaks, spills, and water losses that is difficult to characterize with a reasonable level of uncertainty. This level of uncertainty will always hamper the ability of models to predict observed distributions of contamninants in the vadose zone, even if the distributions were well known.

5.1

Recommendations to reduce uncertainty and improve the site-wide data sets presented in this documnent include the following: * Increase the number of hydrostratigraphic profiles to better represent the site-specific conditions beneath the waste sites. A first step might be to further differentiate the 200 Areas into 24 zones (representative of the regional closure zones) rather than the 6 general geographic areas currently used. Additional site-specific hydrostrati graph ic profiles (or even two or three dimensional representations), should also be developed for those sites found to be high risk drivers and with correspondingly high uncertainty. " Improve our quantitative representation (i.e., through geostatistics) of the geologic structure and heterogeneities associated with the various hydrogeologic facies. " Improve defensibility and traceability of assigning physical and hydrologic properties to the hydrostrati graph ic units. This could entail improving our understanding and semi-quantification of the relationship/correlation between geologic facies and hydraulic properties. * Improve the hydraulic property database to include all the available data. These data include measured values of unsaturated conductivity, parameter estimates from resulting outflow experiments, and data and parameters resulting from field-scale tests. * Address the impacts of gravel on hydraulic and sorption behavior of all samples, in a systematic and consistent manner. * Improve the physical and hydraulic property distribution estimates. This could entail improving the number of sample analyses we have for each of the hydraulic property classes, improving these data via pedotransfer functions tied to particle-size data, using Bayesian updating to improve site-specific property distributions, and incorporating concepts for scaling up sample analytical data to the field and model cell scale. " Improve contaminant distribution coefficient estimates by correcting for gravel content based on particle-size data of the geologic facies and addressing scale-up issues from sample derived &~ values to field and model cell scales. " Improve our recharge estimates, particularly for coarse surface soil and side slope material. * Improve our technical basis and modeling parameters to investigate the effect of side-slope design on deep infiltration rates. " Improve the technical basis and modeling parameters for barrier performance after the design life.

5.2

6.0

References

Agnew SF, J Boyer, RA Corbin, TB Duran, JR Fitzpatrick, KA Jurgensen, TP Ortiz, and BL Young. 1996. Hanford Tank Chemical and Radionuclide Inventories: HDW Model Rev. 3. LA-UR-96-858, Los A larnos National Laboratory, Los Alamos, New Mexico. Allard B. 1982. Actinides in Perspective. NM4 Edenistein (ed.), pp. 553-580, Pergamon Press, Oxford. Bailey LEF and DE Billington. 1998. Overview of the FEPAnalysis Approach to Model Development. NIREX Science Report S/98/009, United Kingdom Nirex Limited, Oxfordshire, United Kingdom. Baker SM, RF Lorang, RP Elmore, Al Rossi, and MD Freshley. 1988. U]/U2 Uranium Plume Characterization,Remedial Action Review and Recommnendationfor FutureAction. WHC-EP-O 133, Westinghouse Hanford Company, Richland, Washington. Bamnett DB, RM Smith, and CJ Chou. 2000. GroundwaterMonitoring Planfor the Hanford Site 216-B-3 Pond RCRA Facility. PNNL-13367, Pacific Northwest National Laboratory, Richland, Washington. BHI. 1998. Hanford Site Atlas. BHI-01 119, Rev. 2, Bechtel Hanford Inc., Richland, Washington. Bjornstad BN. 1990. Geohydrology of the 218- W-5 Burial Ground, 200-West Area, Hanford Site. PNL-7336, Pacific Northwest Laboratory, Richland, Washington. Bryce RW, CT Kincaid, PW Eslinger, and LF Morasch (eds.). 2002. An InitialAssessment of Hanford Impact Performed with the System Assessment Capability. PNNL- 14027, Pacific Northwest National Laboratory, Richland, Washington. Caggiano JA. 1996. Assessment Groundwater Monitoring Planfor Single-Shell Tank Waste ManagementArea S-SX. WHC-SD-EN-AP-191, Westinghouse Hanford Company, Richland, Washington. Campbell JA, AK Sharma, SA Clauss, GM Mong, and D Bellofatto. 1998b. Organic Speciation of AX-i 02, BX-104, C-1 04, C-20], and C-202 Tank Wastes. PNNL-1 1955, Pacific Northwest National Laboratory, Richland, Washington. Campbell JA, SA Clauss, KE Grant, V Hoopes, GM Mong, R Steele, D Bellofatto, and A Sharma. 1998a. Organic Analysis ProgressReport FYI199 7. PNNL-1 1738, Pacific Northwest National Laboratory, Richland, Washington. Cantrell KJ, Ri Seine, and GV Last. 2002. Hanford Contaminant Distribution Coefficient Database and Users Guide. PNNL- 13895, Pacific Northwest National Laboratory, Richland, Washington. Cantrell KI, Ri Seine, and GV Last. 2003a. Hanford ContaminantDistributionCoefficient Database and Users Guide. PNNL-13895, Rev. 1, Pacific Northwest National Laboratory, Richland, Washington. 6.1

Cantrell KJ, RJ Seine, and GV Last. 2003b. Applicability of the Linear Sorption Isotherm Model to Represent Contamninant Transport Processes in Site- Wide Performance Assessments - A While Paper. CP- 17089, Fluor Hanford, Inc., Richland, Washington. Cantrell KJ. 1988. "Actinide(lll) Carbonate Complexation." Polyhedron 7(7):573-574. Carsel RF and RS Parrish. 1988. "Developing Joint Probability Distributions of Soil Water Retention Characteristics." Water Resour. Res. 24(5): 755-769. Cearlock CS, KM Singleton, ME Todd, and DB Barnett. 2000. 200-CW-1 Operable Unit Borehole/Test Pit Summary Report. BHI-01367, Bechtel Hanford, Inc., Richland Washington. CH2M HILL Hanford Group, Inc. 2002. Field Investigation Report for Waste Management Area S-SX; Volume 1, Main Text andAppendices A - C, Volume 2, Appendices D -I. RPP-7884, Rev. 0, CH2M HILL Hanford Group, Inc., Richland, Washington. Cherrey KD, M Flury, and JB Harsh. 2003. "Nitrate and Colloid Transport through Coarse Hanford Sediments under Steady-State, Variably- Saturated Flow." Water Resour. Res. 39, 1165, doi: 10. 1 029/2002WROO 1944. Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA). 1980. Public

Law 96-150, as amended, 94 Stat. 2767, 42 USC 9601 et seq. Connelly MP, JD Davis, and PD Rittman. 1991. Numerical Simulation of Strontium-90 Transporit om the 100-N Area Liquid Waste Disposal Facility. WHC-SD-ER-TA-001, Rev. 0, Westinghouse Hanford Company, Richland, Washington. Connelly MP, BH Ford, and JV Borghese. 1992a. Hydrogeologic Modelfor the 200 West Area GroundwaterAggregate Area. WHC-SD-EN-TI-0 14, Westinghouse Hanford Company, Richland, Washington. Connelly MP, JV Borghese, CD Delaney, BH Ford, JW Lindberg, and SI Trent. 1992b. Hydrogeologic Model for the 200 East GroundwaterAggregate Area. WHC-SD-EN-TI-0 19, Westinghouse Hanford Company, Richland, Washington. Crews WS and DD Tillson. 1969. Analysis of Travel Time of 1-131 from the 1301-N Crib to the Columbia River During July 1969. BNWL-CC-23 26, Pacific Northwest Laboratory, Richland, Washington. Cushing CE and BE Vaughan. 1988. "'Springs and Streamns' in Shrub-Steppe Balance and Change in a Semi-Arid Terrestrial Ecosystem." WH Rickard et al. (ed.), Developments in Agriculturaland ManagedForest Ecology 20, Elsevier Science Publishers, New York. Delaney CD, KA Lindsey, and SP Reidel. 1991. Geology and Hydrology of the Hanford Site: A Standardized Text for Use in Westinghouse Hanford Company Documents and Reports. WHC-SD-ER-TI-003, Westinghouse Hanford Company, Richland, Washington. 6.2

DOE. 1992. Z-Plant Source Aggregate Area Management Study. DOE/RL-9 1-58, U.S. Department of Energy, Richland Operations Office, Richland, Washington. DOE. 1993a. 200 East Groundwater Aggregate Area Management Study Report. DOE/RL-92- 19, Rev. 0, U.S. Department of Energy, Richland Operations Office, Richland, Washington. DOE. 1993b. Lim ited Field Investigation Report for the I100-HR-3 Operable Unit. DOE/RL-93-34, U.S. Department of Energy, Richland Operations Office, Richland, Washington. DOE. 1993c. B Plant Source Aggregate Area Management Study Report. DOE/RL-92-05, U.S. Department of Energy, Richland Operations, Richland, Washington. DOE. 1993d. 200 NorthAggregate Area Source AAMS Report. DOE/RL-92-17, U.S. Department of Energy, Richland Operations, Richland, Washington. DOE. 1993e. PUREX Source Aggregate Area Management Study Report. DOE/R-L-92-04, U.S. Department of Energy, Richland Operations, Richland, Washington. DOE. 1994. Remedial Investigation and Feasibility Study Reportfor the Environmental Restoration DisposalFacility. DOE/RL-93-99, Rev. 1, U.S. Department of Energy, Richland Operations Offices, Richland, Washington. DOE. 1996. Focused FeasibilityStudy qf EngineeredBarriersfor Waste Management Units in the 200 Areas. DOE/RL-93-33, Rev. 0, U.S. Department of Energy, Richland, Washington. DOE. 1996a. 1301-N and 1325-N Liquid Waste DisposalFacilities Limited Field Investigation Report. DOE/RL-96-1 1, Rev. 0, U.S. Department of Energy, Richland Operations Office, Richland, Washington. DOE. 1997. TWRS Vadose Zone ContaminationIssue, Expert PanelStatus Report. DOE/RL-97-49, Rev. 0, U.S. Department of Energy, Richland, Washington. DOE. 1998. Groundwater/Vadose Zone Integration Project Specification. DOE/RL-98-48, Draft C, U.S. Department of Energy, Richland Operations Office, Richland, Washington. DOE. 1999. Groundwvater/Vadose Zone Integration Project BackgroundInformation and State of Knowledge. DOE/RL-98-48, Vol. 11, Rev. 0, U.S. Department of Energy, Richland Operations Office, Richland, Washington. DOE. 2000a. Groundwater/Vadose Zone Integration Project Science and Technology Summnary Description. DOE/RL-98-48, Vol. 111, Rev. 1, U.S. Department of Energy, Richland Operations Office, Richland, Washington. DOE. 2000b. Phase I RCRA FacilityInvestigation/CorrectiveMeasures Study Work Planfor SingleShell Tank Waste Managemnent Areas. DOE/RL-99-3 6, Rev. 1, U.S. Department of Energy, Richland Operations Office, Richland, Washington.

6.3

DOE. 2002. StandardizedStratigraphicNomenclaturefor Post-Ringold-FormnationSediments within the CentralPasco Basin. DOE/RL-2002-39, Rev. 0, U.S. Department of Energy, Richland Operations Office, Richland, Washington. DOE. 2003. Hanford Site Waste Management Units Report. DOE/RL-88-30, Rev. 12, U.S. Department of Energy, Richland Operations Office, Richland, Washington. DOE M 435.1-1. 1999. Radioactive Waste Management Manual. U.S. Department of Energy, Washington, D.C. Available on the Internet at http://www.directives.doe.gov/pdfs/doe/doetext/neword/43 5/m-43 51-1Ic I.html DOE Order 435.1. 1999. Radioactive Waste Management. U.S. Department of Energy, Washington, D.C. Available on the Internet at http://www.hanford.gov/wastemgt/doe/psg/pdf/doeo43)5.1.pdf Domenico PA and FW Schwartz. 1990. Physical and Chemical Hydrogeology. Wiley and Sons, New York, New York. Durner W. 1992. "Predicting the Unsaturated Hydraulic Conductivity using Multi-Porosity Water Retention Curves." Proceedings of the International Workshop on IndirectMethods for Estimating the Hydraulic Properties of UnsaturatedSoils, Riverside, California, October 11I- 13, 1989, MTh van Genuchten, FJ Leij, and LI Lund (eds.), University of California, Riverside, California, p. 185-202. Enfield CG, JJC Hsieh, and AW Warrick. 1973. "Evaluation of Water Flux above a Deep Water Table Using Thermocouple Psychromneters" in Soil Sci. Soc. Amner. Proc. 3 7:968-970. Eslinger PW, C Arimescu, DW Engel, BA Kanyid, and TB3 Miley. 2002b. "User Instructions for the Systems Assessment Capability, Rev. 0," in Computer Codes, Volume 2: Impacts Modules. PNNL13932, Volume 2, Pacific Northwest National Laboratory, Richland, Washington. Eslinger PW, DW Engel, LH Gerhardstein, CA Lo Presti, WE Nichols, and DL Strenge. 2002a. "User Instructions for the Systems Assessment Capability, Rev. 0," in Computer Codes, Volume 1: Inventory, Release, and Transport Modules. PNNL- 13932, Volume 1, Pacific Northwest National Laboratory, Richland, Washington. Fayer MI and TB3 Walters. 1995. EstimnatedRecharge Rates at the Hanford Site. PNL-l 0285, Pacific Northwest Laboratory, Richland, Washington. Fayer MI, EM Murphy, IL Downs, FO Khan, CW Lindenmeier, and BN Bjornstad. 1999. Recharge Data Packagefor the Innmobilized Low-A ctivity Waste 2001 Performance Assessment. PNNL-1 3033,

Pacific Northwest National Laboratory, Richland, Washington. Eecht KR, GV Last, and KR Price. 1977. Evaluation of ScintillationProbe Profilesfrom 200 Area Crib Monitoring Wells, Volutnes IIand III ARI--ST-156, Atlantic Richfield Hanford Company, Richland, Washington.

6.4

Fecht KR, KA Lindsey, DG Horton, GV Last, and SP Reidel. 1999. An Atlas of Clastic Injection Dikes of the Pasco Basin and Vicinity. BHI-01 1103, Rev. 0, Bechtel Hanford, Inc., Richland, Washington. Fogwell TW, GV Last, AL Bunn, KJ Cantrell, FM Coony, JL Downs, MJ Fayer, EJ Freeman, GW Gee, DG Horton, CT Kincaid, CJ Murray, BA Napier, GW Patton, VV Rawhalf, RG Riley, and PD Thorne. 2003. Characterizationof Systenms Task Fiscal Year 2003 Status Report. WMP-1 8045, Fluor Hanford, Inc., Richland, Washington. Freeman EJ and GV Last. 2003. Vadose Zone Hydraulic Property Letter Reports. WMP- 17524, Rev. 0, Fluor Hanford, Richland, Washington. Freeman El, R Khaleel, and PR H-eller. 2001. A Catalog of Vadose Zone Hydraulic Propertiesfor the Hanford Site. PNNL-13672, Pacific Northwest National Laboratory, Richland, Washington. Freeman El, R Khaleel, and PR Heller. 2002. A Catalogof Vadose Zone Hydraulic Propertiesfor the Hanford Site. PNNL-13672, Rev. 1, Pacific Northwest National Laboratory, Richland, Washington. Frind EG, RW Giliham, and I Pickens. 1977. "Application of Unsaturated Flow Properties in the Design of Geologic Environments for Radioactive Waste Storage Facilities" in Finite Elements in Water Resources, pp. 3.144-3.163. WG Gray, GF Pinder, and CA Brebbia (eds.), Pantech, London. Gamnier JM. 1985. "Retardation of Dissolved Radiocarbon through a Carbonated Matrix." Geochim. Cosmnochim. Acta 49:683-693. Gaylord DR and EP Poeter. 1991. Geology and Hydrology of the 300 Area and Vicinity, Hanford Site, South Central Washington. WHC-EP-0500, Westinghouse Hanford Company, Richland, Washington. Gee GW and D Hillel. 1988. "Groundwater Recharge in Arid Regions: Review and Critique of Estimation Methods" in Journalof HydrologicalProcesses 2:255-266. Gee GW, MJ Fayer, ML Rockhold, and MD Campbell. 1992. "Variations in Recharge at the Hanford Site" in Northwest Science 66:23 7-250. Gelhar LW and CL Axness. 1983. "Three- Dimensi onal Analysis of Macrodispersion in a Stratified Aquifer" in Water Resources Research 19:161-180. Gelhar LW, C Welty, and KR Rehfeldt. 1992. "A Critical Review of Data on Field-Scale Dispersion in Aquifers," in Water Resources Research 28:1955-1974. Gelhiar LW. 1993. Stochastic Subsurface Hydrology,.

Prentice Hall, New York.

Hajek BE. 1966. Soil Sun'ey Hanford Projiect in Benton County, Washington. BNWL-243, Pacific Northwest Laboratory, Richland, Washington. Hartman Mi (ed.). 2000. Hanford Site GroundwaterMonitoring: Setting, Sources, and Methods. PNNL- 13080, Pacific Northwest National Laboratory, Richland, Washington. 6.5

Hartman Mi and KA Lindsey. 1993. Hydrogeology of the 100-N Area, Hanford Site, Washington. WI-C-SD-EN-EV-027, Westinghouse Hanford Company, Richland, Washington. Hartman Mi and RE Peterson. 1992. Hydrologic Informiation Sununaryfor the Northern Portion of the Hanford Site. WI-C-SD-EN-TI-023, Westinghouse Hanford Company, Richland, Washington. 1-EDL (Hanford Engineering Development Laboratory). 1975. Site Ivestigation Report for the Fast Flux Test Facility, Richland, Washington. BCL- 170 1, prepared by Hanford Engineering Development Laboratory, Westinghouse Hanford Company, Richland, Washington, for the United States Atomic Energy Commission. Higgo 11W. 1988. Review of Sorption DataApplicable to the Geologic Environment of Interestfor Deep Disposal ofJLWandLLW in the UK. NSS/R-I 62, British Geological Survey, Keyworth, Nottingham, UK. Ho CK, RG Baca, SI- Conrad, GA Smith, L Shyr, and TA Wheeler. 1999. Stochastic Parameter Development for PORFLOWSimulations of the Hanford AX Tank Farmn. SAN D98-2 880, Sandia National Laboratories, Albuquerque, New Mexico. Hoitink DJ, KW Burk, JV Ramsdell, and WJ Shaw. 2003. Hanford Site ClimatologicalDataSummary 2002 with HistoricalData. PNNL-14242, Pacific Northwest National Laboratory, Richland, Washington. Jacobs Engineering Group, Inc. 1999. Retrieval Performance Evaluation Methodology for the AX Tank Farmn. DOE/RL-98-72, prepared by Jacobs Engineering Group Inc. for U.S. Department of Energy, Richland Operations Office, Richland, Washington. Johnson VG and CJ Chou. 1998. Results of Phase 1 Groundwater Quality Assessmnent for Single-Shell Tank Waste Management Areas S-SY at the Hanford Site. PNNL-I 1810, Pacific Northwest National Laboratory, Richland, Washington. Jones TL. 1989. Simulating the Water Balance of an Arid Site. PNL-SA- 17633, Pacific Northwest Laboratory, Richland, Washington. Kaplan DI and RI Seine. 1995. DistributionCoefficient Values Describing Iodine, Neptunium, Selenium Technetium, and UraniuniSorptionto Hanford Sediments. PNL-10379, SUP. 1, Pacific Northwest Laboratory, Richland, Washington. Kaplan DI and RJ Seine. 2000. Geochemnical Data Packagefor the Hanford Immobilized Low-Activity Tank Waste PerformanceAssessmnent (ILA W PA). PNNL- 1303 7, Rev. I, Pacific Northwest National Laboratory, Richland, Washington. Kaplan DI, KE Parker, and IC Ritter. 1998. Effects ofAging a Hanford Sediment and Quartz Sand with Sodiuni Hydroxide on Radiomnuclide Sorption Coefficients and Sediment Physical and Hydrological Properties: Fimnal Reportfor Subtask 2a. PNNL- 11965, Pacific Northwest National Laboratory, Richland, Washington.

6.6

Kaplan DI, Ri Seine, AT Owen, JA Conca, TW Wietsma, and TL Gervais. 1996. RadionuclideAdsorption Distribution Coefficients Measured in Hanford Seditnents for the Low, Level Waste Performance Assessment Project. PNNL-1 1385, Pacific Northwest National Laboratory, Richland, Washington. Khaleel R. 1999. Far-FieldHydrology Data Packagefor Immobilized Low-Activity Tank Waste Performance Assessment. HNF-4769, Rev. 1, Fluor Daniel Northwest, Inc., Richland, Washington. Khaleel R and El Freeman. 1995. Variability and Scaling of Hydraulic Propertiesfor 200 Area Soils, Hanford Site. WHC-EP-0883, Westinghouse Hanford Company, Richland, Washington. Khaleel R and PR Heller. 2003. "On the Hydraulic Properties of Coarse-Textured Sediments at Intermediate Water Contents." Water Resour. Res. 39(9): 1233. Khaleel R and iF Relyea. 1997. "Correcting Laboratory -Measured Moisture Retention Data for Gravel" in Water Resources Research 33(8): 1875-1878. Khaleel R, JF Relyea, and IL Conca. 1995. "Evaluation of van Genuchten-Mualem Relationships to Estimate Unsaturated Hydraulic Conductivity at Low Water Contents." Water Resources Research 31(1 1):2659-2668. Khaleel R, T-CJ Yeh, and Z Lu. 2002. "Upscaled Flow and Transport Properties for Heterogeneous Unsaturated Media." Water Resources Research 3 8(5). Khaleel R, TE Jones, Al Knepp, FM Mann, DA Myers, PM Rogers, RI Seine, and MlI Wood. 200 1. Modeling Data Packagefor S-SX Field Investigation Report (FIR). RPP-6296, Rev. 0, CH2M HILL Hanford Group, Inc., Richland, Washington. Kincaid CT, RW Bryce, and JW Buck. 2004. Technical Scope and Approachfor the 2004 Composite Analysis of Low-Level Waste Disposal at the Hanford Site. PNNL-14372, Pacific Northwest National Laboratory, Richland, Washington. Kincaid CT, PW Eslinger, WE Nichols, AL Bunn, RW Bryce, TB3 Miley, MC Richmond, SF Snyder, and RL Aaberg. 2000. Groundwater/Vadose Zone Integration Project, System Assessment Capability (Revis ion 0)., Assessment Description, Requirements, Software Design, and Test Plan. BHI-01 365, Draft A, Bechtel Hanford, Inc., Richland, Washington. Kincaid CT, MP Bergeron, CR Cole, MD Freshley, NL Hassig, VG Johnson, DI Kaplan, RI Seine, GP Streile, DL Strenge, PD Thorne, LW Vail, GA Whyatt; and SK Wurstner. 1998. Composite Analysis for Low-Level Waste Disposalin the 200 Area Plateauof the Hanford Site. PNNL- 11800, Pacific Northwest National Laboratory, Richland, Washington. Kipp 1(1 and RD Mudd. 1974. Selected Water Table Contour Maps and Well Hydrographsfor the Hanford Reservation, 1944-19 73. BNWL-B-360, Pacific Northwest Laboratory, Richland, Washington.

6.7

Knepp Al. 2002. Field Investigation Report for Waste Management Area B-BX-BY Volume]1, Main Text and Appendices A - C, Volumne 2, Appendices D - T. RPP- 10098, Rev. 0. CH2M HILL Hanford Group, Inc., Richland, Washington. Kosugi K, 1W Hopmans, and JH Dane. 2002. "3.3.4 Parameteric Models" in Methods of Soil Analysis" Part 4 -Physical Methods. Soil Science Society of America, Madison, Wisconsin, p. 739-757. Krupka KM and RI Seine. 1996. PerformanceAssessment of Low-Level Radioactive Waste Disposal Facilities: Effects on Radionuclide Concentrations by Cemient/Ground-Water Interactions. NUREG/CR-6377, U.S. Nuclear, Regulatory Commission, Washington, D.C. Last GV and Vi Rohay. 1993. Refined Conceptual Model for the Volatile Organic Compounds-Arid Integrated Demonstrationand 200 West Area Carbon TetrachlorideExpedited Response Action. PNL-8597, Pacific Northwest Laboratory, Richland, Washington. Last GV, BN Bjomnstad, MP Bergeron, DW Wallace, DR Newcomer, IA Schramke, MA Chamness, CS Cline, SP Airhart, and JS Wilbur. 1989. Hydrogeology of the 200 Areas Low-Level Burial Grounds -An Interim Report. PNL-6820, Vol. 1 and 2, Pacific Northwest Laboratory, Richland, Washington. Last GV, Vi Rohay, El Schelling, and L Soler. 2001. Use of Process Relationship Diagrams in Development of ConceptualModels. PNNL-SA-345 15, Pacific Northwest National Laboratory, Richland, Washington. Last GV, WE Nichols, and CT Kincaid. 2004. Geographicand OperationalSite ParametersList (GOSPLJ for the 2004 Composite Analysis. PNNL- 14702, Rev. 0, Pacific Northwest National Laboratory, Richland, Washington. Last GV, VI Rohay, FJ Schelling, AL Bunn, MA Delamare, RL Dirkes, RD Hildebrand, JG Morse, BA Napier, RG Riley, L Soler, PD Thorne. 2004. "'A Comprehensive and Systematic Approach to Developing and Documenting Conceptual Models of Contaminant Release and Migration at the Hanford Site." Journal of Stochastic Environmental Research and Risk Assessment 18(2): 190-116. LI-MC. 1999. Statements of Work for FY 2000 to FY 2005 for the Hanford Low-Activity Tank Waste Performance Assessment Programn. HNF-SD-WM-PAP-062, Rev. 4, Lockheed Martin Hanford Company, Richland, Washington. Liikala TL, RL Aaberg, NJ Aimo, DJ Bates, TI Gilmore, El Jensen, GV Last, PL Oberlander, KB Olsen, KR Oster, LR Roome, JC Simpson, SS Teel, and El Westergard. 1988. Geohydrologic Characterization of the Area Surrounding the 183-H Solar EvaporationBasin. PNL-6728, Pacific Northwest Laboratory, Richland, Washington. Lindberg JW and FW Bond. 1979. Geohydrology and Ground-Water Quality Beneath the 300 Area, HanfordSite, Washington. PNL-2949, Pacific Northwest Laboratory, Richland, Washington. Lindberg JW. 1993a. Geology of the 100-B/C Area, Hanford Site, South-Central Washington. WHCSD-EN-TI- 13 3, Westinghouse Hanford Company, Richland, Washington. 6.8

Lindberg JW. 1993b. Geology of the 100-K Area, Hanford Site, South-Central Washington. WHC-SD-EN-TI- 155, Westinghouse Hanford Company, Richland, Washington. Lindberg JW. 1995. Hydrogeology of the 100-K Area, Hanford Site, South-Central Washington. WHC-SD-EN-TI-294, Westinghouse Hanford Company, Richland, Washington. Lindsey KA and GK Jaeger. 1993. Geologic Setting of the 100-HR-3 Operable Unit, Hanford Site, South-Central Washington. WHC-SD-EN-TI- 132, Westinghouse Hanford Company, Richland, Washington. Lindsey KA, BN Bjomnstad, JW Lindberg, and KM Hoffmann. I 992b. Geologic Setting of the 200 East Area: An Update. WHC-SD-EN-TI-O 12, Rev. 0, Westinghouse Hanford Company, Richland, Washington. Lindsey KA, MP Connelly, and BN Bjomnstad. 1992a. Geologic Setting of the 200 West Area: An Update. WHC-S D- EN-TI-008, Westinghouse Hanford Company, Richland, Washington. Lindsey KA. 1992. Geology of the Northern Part of the Hanford Site: An Outline of Data Sources and Geologic Setting of the 100 Areas. WHC-SD-EN-TI-01 I, Westinghouse Hanford Company, Richland, Washington. Lindsey KA. 1995. Miocene- to Pliocene-Aged SuprabasaltSediments of the Hanford Site, SouthCentral Washington. BHI-00 184, Rev. 00, Bechtel Hanford, Inc., Richland, Washington. Lindsey KA. 1996. Miocene to Pliocene Ringold Formation and Associated Deposits of the Ancestral Columbia River System, South-Central Washington and North Central Oregon. Open File Report 96-8, Washington State Department of Natural Resources, Olympia, Washington. Looney BB and RW Falta (eds.). 2000. Vadose Zone, Science and Technology Solutions. Two Volumes, Battelle Press, Columbus, Ohio. Maxfield HL. 1979. Handbook - 200 Areas Waste Sites. RHO-CD-673, Volumes 1, 11, and 111. Rockwell Hanford Operations, Richland, Washington. Meyer PD, KP Saripalli, and VL Freedman. 2004. Near-FieldHydrology Data Packagefor the Integrated DisposalFacility 2005 PerformanceAssessment. PNNL- 14700, Pacific Northwest National Laboratory, Richland, Washington. Mualem Y. 1976. "A New Model for Predicting the Hydraulic Conductivity of Unsaturated Porous Media" in Water Resources Research 12:5 13. Murphy EM, TR Ginn, and JL Phillips. 1996. "Geochemical Estimates of Paleorecharge in the Pasco Basin: Evaluation of the Chloride Mass-Balance Technique." Water Resources Research 32(9):2853-2868.

6.9

Murray CJ, Y Chien, and PD Thorne. 2004. A GeostatisticalAnalysis of HistoricalField Data on Tritium, Technetium-99, Iodine-129, and Uranium. PNNL-1461 8, Rev. 0, Pacific Northwest National Laboratory, Richland, Washington. Murray CJ, AL Ward, and IL Wilson. 2003. Influence of Clastic Dikes on Vertical Migration of Contaminants in the Vadose Zone at Hanford. PNNL-1 4224, Pacific Northwest National Laboratory, Richland, Washington. Murray CJ, DG Horton, AL Ward, and GW Gee. 2002. "Hydrogeologic Influence of Clastic Dikes on Vadose Zone Transport," Section 7.3.3 pp. 7.26-7.27, in Hanford Site EnvironmentalReportfor Calendar Year 2001. PNNL-1391 0, Pacific Northwest National Laboratory, Richland, Washington. NEA (Nuclear Energy Agency). 2000. Features, Events and Processes (FEPs)for Geologic Disposal of Radioactive Waste, An InternationalDatabase. Organization For Economic Co-Operation and Development (OECD) Publications, France. Neitzel DA, AL Bunn, KW Burk, SD Cannon, JP Duncan, RA Fowler, BG Fritz, DW Harvey, PL Hendrickson, DG Horton, GV Last, TM Poston, EP Prendergast-Kennedy, SP Reidel, MI Scott, PD Thorne, and DM Woody. 2003. HanfordSite National EnvironmentalPolicy Act (NEPA) Characterization, Revision 15. PNNL-641 5, Rev. 15, Pacific Northwest National Laboratory, Richland, Washington. Pearce GG, RE Brown, and TP O'Farrell. 1969. The Arid Lands Ecology Reserve at Pacific Northwest Laboratory, Richland, Washington. BNWL-SA-2574, Pacific Northwest Laboratory, Richland, Washington. Peterson RE, RF Raidl, and CW Denslow. 1996. Conceptual Site Models for Groundwater Contaminationat the 100-BC-5, 100-KR -4, 100-HR-3, and 100-FR-3 Operable Units. BHI-00917, Bechtel Hanford Company, Richland, Washington. Peterson RE and MP Connelly. 2001. Zone of Interaction Between Hanford Site Groundwaterand Adjacent Columbia River. PNNL-13674, Pacific Northwest National Laboratory, Richland, Washington. Price WH and KR Fecht. 1976a. Geology of the 241-U Tank Farm. ARH-LD- 138, Informal Report, Atlantic Richfield Hanford Company, Richland, Washington. Price WH and KR Fecht. 1976b. Geology of the 241-B Tank Farm. ARH-LD-129, Atlantic Richfield Hanford Company, Richland, Washington. Price WH and KR Fecht. 1976c. Geology of the 241-BX Tank Farm. AR-H-LD- 130, Atlantic Richfield Hanford Company, Richland, Washington. Price WH and KR Fecht. 1976d. Geology of the 241-BY Tank Farm. ARH-LD- 13 1, Atlantic Richfield Hanford Company, Richland, Washington.

6.10

Prych EA. 1998. Using Chloride and Chlorine-S6 as Soil-Water Tracers to Estimate Deep Percolation at Selected Locations on the US. Department'of Energy Hanford Site, Washington. Water-Supply Paper 248 1. U.S. Geological Survey, Tacoma, Washington. Raid] RE. 1994. Geology of the 100-FR-3 Operable Unit, Hanford Site, South-Central Washington. WHC-SD-EN-TI-22 1, Westinghouse Hanford Company, Richland, Washington. Reidel SP and AM Ho. 2002. Geologic and Wireline Summnaries from Fiscal Year 2002 ILA W Boreholes. PNNL-14029, Pacific Northwest National Laboratory, Richland, Washington. Reidel SP and DG Horton. 1999. Geologic Data Packagefor 2001 Immobilized Low-Activity Waste Performance Assessment. PNNL- 12257, Rev. 1, Pacific Northwest National Laboratory, Richland, Washington. Reidel SP, DG Horton, and MM Valenta. 2001. Geologic and Wireline Borehole Summnaryfrom the Second ILA WBorehole (299-E24-21). PNNL-13652, Pacific Northwest National Laboratory, Richland, Washington. Riley RG and C LoPresti. 2004. Release Mlodel DataPackagefor the 2004 Composite A nalysis. PNNL- 14760, Rev. 0, Pacific Northwest National Laboratory, Richland, Washington. Rohay VJ, KJ Swett, and GV Last. 1994. 1994 ConceptualMlodel of the Carbon Tetrachloride Contamination in the 200 West Area at the HanfordSite. WHC-SD-EN-TI-248, Westinghouse Hanford Company, Richland, Washington. Schalla R, RW Wallace, RL Aaberg, SP Airhart, DJ Bastes, JVM Carlile, CS Cline, DI Dennison, MD Freshley, PR Heller, Li Jensen, KB Olsen, RG Parkhurst, JT Rieger, and El Westergard. 1988. Interim CharacterizationReport for the 300 Area Process Trenches. PNL-67 16, Pacific Northwest Laboratory, Richland, Washington. Serne RI and M I Wood. 1990. Hanford Waste-Formi Release and Sediment Interaction: A Status Report with Rationale and Recommendationsfor Additional Studies. PNL-7297, Pacific Northwest Laboratory, Richland, Washington. Seine RI and VL LeGore. 1996. Strontium-90 Adsorption-DesorptionProperties and Sedimlent Characterizationat the 100-N Area. PNNL-1 0899, Pacific Northwest National Laboratory, Richland, Washington. Seine RI, IL Conca, VL LeGore, KI Cantrell, CW Lindenmeier, IA Campbell, IL Amonette, and MI Wood. 1993. Solid- Waste Leach Characteristicsand Contamninant-SedimentInteractions, Volume 1: Batch Leach and Adsorption Tests andSedimient Characterization. PNL-8889, Vol. 1, Pacific Northwest Laboratory, Richland, Washington. Seine RI, RO Lokken, and LI Criscenti. 1992. "~Characterization of Grouted LLW to Support Performance Assessment" in Waste Management 12:27 1-287.

6.11

Skaggs RL and WH Walters. 198 1. FloodRisk Analysis of Cold Creek Near the Hanford Site. RHO-B WI-C- 120, Rockwell Hanford Operations, Richland, Washington. Slate JL. 1996. "Buried Carbonate Paleosols Developed in PT jo-Pleistocene Deposits of the Pasco Basin, South-Central Washington" in QuaternaryInternational34-36:191-196. Slate JL. 2000. Nature and Variabilityof the Plio-PleistoceneUnit in the 200 West Area of the Hanford Site. BHI-0 1203, Bechtel Hanford, Inc., Richland, Washington. Soler L, GV Last, BA Napier, VJ Rohay, and FJ Schielling. 2001. The Application of Features, Events, and Process Methodology at the Hanford Site. BHI-01573, Rev. 0, Bechtel Hanford, Inc., Richland, Washington. Stenhouse MJ. 1994. Sorption Databasesfor Crystalline, Marl and Bentonite for Performance Assessment. NTB 93-06, Nagra, Wettingen, Switzerland. Stephens DB. 1992. "A Comparison of Calculated and Measured Unsaturated Hydraulic Conductivity of Two Uniformn Soils in New Mexico." Proceedingsof the International Workshop on IndirectMethods for Estimating the Hydraulic Propertiesof UnsaturatedSoils, Riverside, California, October 11I- 13, 1989, MTh van Genuchten, FJ Leij, and UJ Lund (eds.), University of California, Riverside, California, p. 249-261. Stumm W and JJ Morgan. 1996. "Aquatic Chemistry," Chemical Equilibriaand Rates in Natural Waters, Pr ed., John Wiley and Sons, Inc., New York. Swanson LC, GG Kelty, KA Lindsey, KR Simpson, RK Price, and SD Consort. 1992. Phase I Hydrogeologic Summary of the 300-FF-5 Operable Unit, 300 Area. WHC-SD-EN-TI-052, Rev. 0, Westinghouse Hanford Company, Richland, Washington. Swanson LD, VJ Rohay, and JM Faurote. 1999. Hydrogeologic Conceptual Model for the Carbon Tetrachlorideand Uranium/Technetium Plumes in the 200 West Area: 1994 through 1999 Update. BHI0 13 11, Bechtel Hanford, Inc., Richland, Washington. Tallman AM, KR Fecht, MC Marratt, and GV Last. 1979. Geology of the SeparationAreas, Hanford Site, South-Central Washington. RH-O-ST-23, Rockwell Hanford Operations, Richland, Washington. Thorne PD, MA Chamness, FA Spane, Jr., VR Vermeul, and WD Webber. 1993. Three-Dimensional ConceptualModel for the Hanford Site UnconfinedAquifer System, FY93 Status Report. PNL-897 1, Pacific Northwest Laboratory, Richland, Washington. Thome PD, MA Chamness, VR Vermeul, QC MacDonald, and SE Schubert. 1994. Three-Dimensional ConceptualModel for the Hanford Site UnconfinedAquifer System, FY 1994 Status Report. PNL- 10195, Pacific Northwest Laboratory, Richland, Washington.

6.12

Valenta MM, MB Martin, JR Moreno, RM Ferri, DG Horton, and SP Reidel. 2000. ParticleSize DistributionDataFrom Existing Boreholes at the Immnobilized Low-Activity Waste Site. PNNL- 13328, Pacific Northwest National Laboratory, Richland, Washington. van Genuchten MTh. 1980. "A Closed-Form Solution for Predicting the Conductivity of Unsaturated Soils." Soil Sci. Soc. Am. J. 44:892- 898. Vermeul VR, SS Teel, JE Amonette, CR Cole, JS Fruchter, YA Gorby, FA Spane, JE Szecsody, MD Williams, and SB Yabusaki. 1995. Geologic, Geochemical, Microbiologic, and Hydrologic Characterizationat the In Situ Redox Manipulation Test Site. PNL- 10633, Pacific Northwest Laboratory, Richland, Washington. Ward AL, GW Gee, and MD White. 1997. A Comprehensive Analysis of Contaminant Transport in the Vadose Zone Beneath Tank SX-]09. PNNL-l 1463, Pacific Northwest National Laboratory, Richland, Washington. Warrick A, DE Myers, and D Nelson. 1986. "Geostatistical Methods Applied to Soil Science, in Methods of Soil Analysis," Part 1, Soil Science Society Amer. 53-82. White MD and M Oostrom. 1996. STOMP Subsurface Transport Over Multiple Phases Theory Guide. PNNL- 11217, Pacific Northwest National Laboratory, Richland, Washington. Williams BA, BN Bjornstad, R Schalla, and WD Webber. 2000. Revised Hydrogeologyfor the SuprabasaltAquifer System, 200-EastArea and Vicinity, Hanford Site, Washington. PNNL- 12261, Pacific Northwest National Laboratory, Richland, Washington. Williams BA, BN Bjomnstad, R Schalla, and WD Webber. 2002. Revised Hydrogeologyfor the SuprabasaltAquifer System, 200-West Area and Vicinity, HanfordSite, Washington. PNNL- 13 858, Pacific Northwest National Laboratory, Richland, Washington. Wilson LG, LG Everett, and SJ Cullen. 1995. Handbook of Vadose Zone Characterizationand Monitoring. CRC Press, Inc., Lewis Publishers, Raton, Florida. Wittreich CD, JK Linville, GW Gee, and AL Ward. 2003. 200-OP-i Prototype Hanford BarrierAnnual Monitoring Reportfor Fiscal Year 2002. CP-14873, Rev. 0, Fluor Hanford, Inc., Richland, Washington. Wood MI, R Khaleel, PD Rittman, AH Lu, SI- Finfrock, RJ Seine, KJ Cantrell, and TH DeLorenzo. 1995. Performance Assessment for the Disposal of Low-Level Waste in the 200- West Area Burial Grounds. WI-C-D-0645, Westinghouse Hanford Company, Richland, Washington. Wood MI, R Khaleel, PD) Rittman, SH Finfrock, TH DeLorenzo, and DY Gorbrick. 1996. Performance Assessment for the Disposalof Low-Level Waste in the 200-East Area Burial Grounds. WHC-SD-WM-TI-730, Westinghouse Hanford Company, Richland, Washington.

6.13

Wood MI, R Schalla, BM Bjomnstad, and SM Narbutovskih. 2000. Subsurface Conditions Descriptionof the B-BX-BY Waste Management Area. HNF-5507, Rev. 0, CH2M HILL Hanford Group, Inc., Richland, Washington. Wurstner SK, PD Thorne, MA Chamness, MD Freshly, and MD Williams. 1995. Development of a Three-DimensionalGround-Water Model of the Hanford Site UnconfinedAquifer System: FY 1995 Status Report. PNL-1 0886, Pacific Northwest Laboratory, Richland, Washington. Xie Y, CJ Murray, GV Last, and R Mackley. 2003. Mineralogicaland Bulk-Rock Geochemical Signatures of Ringold and Hanford FormationSediments. PNNL- 14202, Pacific Northwest National Laboratory, Richland, Washington. Yao T-M and JMH Hendricks. 1996. "Stability of Wetting Forests in Dry Homogeneous Soils Under Low Infiltration Ratios." Soil Science Society ofAmerica Journal,60, 20-28, Madison, Wisconsin: Soil Science Society of America TIC 286692. Zhang ZF, AL Ward, and GW Gee. 2002. Estimating Field-Scale Hydraulic Parameters Using a Combination of ParameterScaling and -InverseMethods. PNNL- 14109, Pacific Northwest National Laboratory, Richland, Washington. Zhang ZF, AL Ward, and GW Gee. 2003. "Estimating Soil Hydraulic Parameters of a Field Drainage Experiment Using Inverse Techniques." Vadose Zone J1 2:201-21 1. Zhuang J, M Flury, and Y Jin. 2003. "Colloid-Facilitated Cs Transport through Water-Saturated Hanford Sediment and Ottawa Sand." Environ. Sci. Technol. 37:4905-4911.

6.14

Appendix A Hydrostratigraphic Templates

VZ Base Templates A South 200 East Area (A Plant, C Plant, U. S. Ecology) Stratigraphic Columns NotesiAssumpine 1Topography range hroer735 PtMSL in southes cornerof 200 East Areato 645 ft MSL in e 241-C area (USG Gable Butte 7 5 mtn Quadrangle Map, Will assume an aueragee nuoton of 090 If MSIL an elevationof 11Gm (300ft in the eastern part of 200 East to 119rn (30 2) The pre-Hanford Walter Table(January 1944) is estimated to rangehroot in~the wetern pant(BNdWeLB-30 W il assume an aueragevater table elesotioc,of 117 in(385 ft) MOL 3) A thin blanket of eol~acsand andsit covuersthe surface ofthe site Mlere notdisturbed outingexcavation aria const-utioc of the ywste disposal sites and tnen incorporated into bacoflI Hce, this matecal yw generally removedo materials Tedeptnof the sites and ths the bacofull over these sties rangehrorn0 rn for ponds aria unplannedreleases to an averageof about 4 5 rn tor for tacks cro and bunialgrounds, and upto 16 4 mn deepl(HanfordWell Assume averagedepth of150 Pt 4) Injectionwel121006-2 is screened hroot15-40 Pf Well 299-E24-11is GOPI

~ta

dispsa dthe g.~ ton fo Adju wtd AverageHyrui Average Elevation Thiokirees Thiokeesow Itt) GeolegicBeit (I) (tt)r Depth (ft) 0 -f-.eo 15 G75eder 15, 15

Tespi. 20l

15

15

30

200

203

233

G21

290

10,

101

3051

395 0nordl raoe E385 WtgoorairtE

3051

38spWrerTac

_____ I____

1

1

Teureelet 2116A-3 toll

______ri I, ______

ob

4

Thickneet

Thicknest

(It)

111)

180

(It)

103

233 90

457 Soasn200oi

2051

TO9ierorouas .-

305

3051R .

3051

. can 3051oler

Depth(It)

3

50

Aveage Eleva on (111)

so

103

NA

4H1

212

4(2

2

NA

I

Type

INA

i;

""'eoei

001. 1

Hg

1

0C32

09

I1

Hdraulic Property Type*

oryo4et

OdKo ,roelrncoh

sara o-1

KdClaw

Kd Clawss

dto

A

1-

NA

A

-

::::

SAC Soil Type INA

Ka Zeeel NA

Bt

8el

S

Hs

H

RGFg

1I

la

NA

211

T314

212

312

2(2

312

ti

2

N2 3

N2

HI2 B

A

Desicriptiont

NA 2iti A3

INA NA

IN

S

tI

O felodcl

It0 Zonre-

1.A rdot

aooho"yt-o-is.to.-resit I "'0 -" aa

.1oi~i E

N

N 21A"

SAC SoilI

Type'

Description

Sar ighty."ned-rncorarno mlcinete toaet vin

0 B

Ka ClawO

2H

R

-7__

GeologicUolt "INA 0 60Sf

457

233

11

H S2 -_I'__1___

I0-NA

tO1

1s

o

G9yOSirc

G21

Averae

Hg

Property

101

200

Ib~i- capiige o -w mie-oo. fire Sty saye Z~d,uilt fe petebre to toiepoi ony -,1 c oe

Geologic belt

0

1

5(01

-KdClawo

iftnihseHrSdirnt2calo1sana

Elevatiee Depth(it

-

Thickness (It)

l Stynceetoerycr eto

___ 200

__

Pat 75onel N HI

I____ Grounds)____

021

TIkoeo (It)

-Sntoau

457 Smir2000lar

G2

S

SAC Soil Type IA Hss

Property Type*

Dellcripbon JNA

G&O nf.,~d .-uil

___

_____2

___________

la

Claat

2H0

3

H

3

41

Kdl NAIN

Iu.i inepr,, ne

10

10

305

395

-1

r

- lt

30c Topll

A-

fnane ad eer~

Aunrag

11iries

Cano .,s

~toNA ~

032

-n.otfep i

~

~

~

N

A

4122

~

nalsus po eile pa-e by K2a11

AlervCoosit

impac klmedilIpc Th ._.nig

BLUE)rnec

S

poith

adofdt thckes

h

ol TT

Dsrpin

nt

uroge strat thckAse to

15 151 675Eola

~e

NA 2S66A4er20

AnalyssiC

Gooi

f)

ootlz

N air

thNoaAncns

rcj. .S

o h

Tp

woe

A.41

d7

"KdCa

NAna

HS

VZ Base Templates - ABC Cribs BC-Cribs (216-B-14 through -19), South 200 East Area Stratigraphic Columns Notes/Assumptions: 1) Topography ranges from 229m (751 ft) MSL northeast of the cribs to 227m (745') ft MSL southeast of the cribs (as taken from the Hanford Site Atlas). 2) The pre-Hanford Water Table (January 1944) is estimated to have been at an elevation of 387 ft (1118m) MSL (based on Kipp and Mud, 1974 BNWL-B-360). 3) The site depth to the crib bottom is reported to be 13 ft (4 m) based on Maxfield, 1979 - RHO-CD-673. Thus, the backfill is assumed to be 13 ft deep. 4) However, the site was interim stabilized in 1981 bycovering with a miniumn of 2 ft (0.61m) of clean soil and revegetated (WIDS). at216A BC E-X for the Eastern corner of the BC crib area based onr 299-E13-1 (N 134404.612, E 673666.723). Hydraulic Adjusted Estimated SAC Soil Property Depth Thickness Thickness Type Type * Description Elevation (ft) Geologic Unit ft (ft)t (f)-

Temp

______ ______

13

13 9

9 9

221

221

112

83

_______________

Temp~t

NA

NA

Baciet

B

B

3H

720HanfordtSand bede orzntlybedd 2 coarse sandlShlc]l

Pebbly very coarse to nmedium sand to coarse to mrediuw sand

S

Hcs_BC

Handtord Sand499 horizontally bedded honesand(Sh~tl)

Coarse to honesand to slightly silty

742 Surface

NA

13

729 earketl

2

2

243 355

387 Ringold Unit E

355

387 Water Tabte

Hantord Sand-

10

23

719 horizontally bedded coarse sand1511

215

215

238

Handfotd Sand504 horizontally bedded sand(Sh~flI hone

98

117

355

387 Ringold Unit E

355

387[Water Tabte

_______

______

KidClass

NA

0

_____

S

HfsB

3H ___________

1

coarse___to__finesand______311

Silty sandy coarse to fine pebble to slightly silty pebbly very ooarse to medium sand NA

SG2

Rig

Pbl eycas omdu Pebbl t coarse to medrandwHsC3 snS o ore omdicsnd Coretfiesntolghysly coarse to hone sandtosihlSit oretohesn Silty sandy coarse tofine pebble to slightly silty pebbly oetycoarse to medium sand INA

S

SG2

216A BC W-3

Kd Class NA 3H

HsC3 Hfs_BC

311

Rg

312

I____

After Khaleel and Freeman (1995), per white paper by Khaleel (September 2000) HI=high impact, ll=lntermediate Impact (After Composite Analysis) Based on Fecht, Last, and Marratt, 1979 - RHO-LD-72. BLUE = Injection/release point t Average thickness adjusted to normalize the average strata thicknesses to equal the total thickness of the vadose zone.

A.2

312

____NA

_____

216A BC W-X for the Western comner of the BC crib area based on 299-E13-6 (N 134341.79 E7356.07 Hydraulic Adjusted Estimated Property SAC Soil Depth Thickness Thickness Type_ Type Description (ftL Elevation (ftt Geologic Unit (ft (ftNA NA NA 742 Sartace ______0 B B Beofifilt 729 B~ackfill 13 13 13 10

216A BC E-3

NA

VZ Base Templates - ABC Trenches BC-Trenches (216-B-20 through -31, -52 through -54, and -58), South 200 East Area Stratigraphic Columns Notes/Assumptions 1) Topography ranges from 228.5m (75001)MSLnearthe 216-B-58trenchto 225m (738')It MSLsouthof the 216-9-28 trench(as takentrom the HanfordSite Atlas). Note however,that the odtewas interimstabilized in 1981 by coverng wth a miniumsf 28I 2) The pro-Hanford Water Table(Januaty 1944)is estimated to havebeenat an elevation of 3878t(118m) MSL(basedon KippandMad, 1974- BNWL-B-360). (2.4-3 m) hased on Maofiold,1979- RHO-CD-673.Thus,the backfill is unnamedto be 108I 3) The site depthto thetrench bottomis reportedto be 8 to t0o9-mmn. deep.

oflthe BCcrib are" based on ,11-034 (N 134341.75?,E67364.0771. 216A 13CTW-Xfor thte Wetstern comfer Temnpitoe Estimated Thickness

Adjusted Thickness (ff19

(ft)13

Depth (ft) Elevation (ft) Geologic Unit 0 742 Ourtave 13 13 729 Backil

10

10

23

215215 238

215 215

98

355

117

355

______________

Hydraulic Property Type

Description

~~~~~~~~~~Handtvrd cvrvi n aai iloySly Cas ofn adt lgtysly

3871WaierTable

ft)

Depth(ft) Elevation(ft)

(ft)

58

27

18

pebbleiv sandyvvars toOnre, Sum 1iabtly nitt pebblyveryvoarseto tediumsand tINA____

295

228

cv0s slinnay

HantordSand728hoiizvntaly bedded

S

Hcs_BC

S

HsB

S

HsB

114 1_____

187

50hrnanybidde sand /5O/f Oine

387

358idinnaldUnitE

3591

387WalerTabte

187

534 Onial beddedB

197

53~~~~42 nvriz znraly bedded

HandividSand-

187 187 87

35

98

871

284

1

_____

NA

________

216A 8CT N-3

216A BCT N-4

KidClans

KdClass

Hs B

3H1

411

HnCs

3H1

4H1

S

HfsBC

31411

SG2

Rg

371

TTepe

S Bit medium

312 _________

One

SinOSY 1ebly vryae

Rg

sdt

ifd n an Caetd tans i ne sand31

it

sandy artofneinOpebble i Siiryad

in slightlysiarypebblyverymoanse mnedivsand NANAN

Tomp toe216AOCT S-X for theta thwo efportion of the BCtrench areabaed on 2$$E$32 (N 34146 3 E67318.661). AdjustedHyrui Esimaited SCoi Thickness ThicknessPrpty Type Type* Descriplion Depth(it) Elevation(ff) Geologic Unit (ft) (ft)187

3H

htl t pebbl tonfintet One snyvasan

Sn]

43

Kd Class

AN

SG2

Description

Geologic Unit

ain

228

______

uvuisetovfOne-ad

73nd Bav1

10

216ABCT W-3

Backfil3 Pebblyverybdaibvtv mediumsandto main i. mediumsand

BCT N-X forthe morttwesterircomer of t BC trenh arebased on 2fl.El-14 (N 134474 32 E57308

Tomptote21l

__

SACSoil Type

A

N

HanfvrvSand719 horizontalyedded vvars snd (Sn/v/i Sand. 504 ho~~~~nrizontally bedded tine sand/50/fli

387 hingeldUnitE

_

fien eanfrSand -~rm 47 1ho~nzorallbeide

387

344 RingeldUnitE

344

38/ lWaterTable

412

412

246ABCT 5-3

216A BOT S-4

KdClass

Kd!Class

4

3

Goa-s toninesn

nnirl

i

n osiitysly

sand ainsetovfOne mSh

S

HsB

1

1

1

1

312

412

Slig tly ebby vey corseto m diu

sandy ase

ine pebble ivcC

sligatlnniltypeby very coarse to

SG2

Rg

NA_____________NA_______

INA

After Khaleeland Freeman (1995).per wit e paperby Khateet(September 2000) HI=highimpact, ll=termediate Impact(AfterCompositeAnalysis) Basedon Focht. Last,and Marraft,1979- RHO-LD-72. BLUE = Injectio/release point t Average thickness adjusted tonormalize the overagestratathicknesses to equal thetotal thickness sf1thevadosezone.

A.3

VZ Base Templates - AILAW South 200 East Area (ILAW) Stratigraphic Columns Notes/Assumptions: 1) Thicknesses, elevation, and water table are averages from wells 299-W17-21, 299-E17-23, and 199-E17-25 for the south template, averages from wells 2992) A thin bl anket of eolian sand and silt covers the surface of tne site where not disturbed This is ignored because ILAWactiv~tieswill remove this unit prior to 3) All data from PNNL-1 1957, PNNL-13652, and PNNL-14029 (north template) 4) Coordinates are for well 299-E17-21 (south template), 299-E24-7 (central template), and299-1124-21 Tempiat

216A _tLAWS-X forthe southern portion of the fLAW site. Nearsu Easting = 574,107 m, Nothing = 134,83 m AdJUSted Hydraulic Average Property Elevation Depth Thickness Average Tye Description Geologic Unit (ft) (it) (ft)+ Thickness (Ift) NA NA 736 Surface a and gravel Sand 736 Backfiff 0 so 50 Hanford formation 686. sand-dominated Sand (S2)

187

187

5t

11

11

237

Hanford formation. 499 gravel-dominated Gravelly sand to sandy gravel (M)(

249

Hanford formation, 498 sand-dominated Sand (S3)

259 334

Hanford formation, 477 gravel-dominated Gravel to sandy gravel (G4) NA 402 Water Table

11 75

11 75

20

164 20

50

SG1

214

33

33

234

Hanford formation, Sand (S3) 484 sand dominated

51

51

267 318

Hanford formation, 451 graveldominated Gravel to sandy gravel(G4) NA 400 Water Table

14

168

14

50

218

Hanford formation, 496 gravel dominated Gravelly sand to sandy gravel (M3)

38

38

232

Hanford formation. Sand (S3) 482 sand dominated

48

48

270 318

Hanford formation, 444 gravel dominated Gravel to sandy gravel (G4) NA 396 WaterTable

4H

I

412

Hfs j,

11

411

I

412 NA

INA

0A ILAW C-4

____

Hydraulic Property TyJES NA B

ld ZoneNA HI

HI

KdlClass ________

4H

4H

Hfs

SG1

Hj

11

412

S

HIs

11

411

11

412 NA__

SG2

Rj* NA

1NA

_____21A

Hydraulic Property Type* NA B

ld Class

HI

4H

I

412

11

411

I 1j

412 NA

jj

SG1

Hfs

S

9G iNA

iNA

ILAW N-4

ld Zone** NA________ HI

Hfs

S

After Khaleel and Freeman (1995), per white paper by Khaleel (September 2000) HI=high impact, ll=lntermediate Impact (After Composite Analysis) Bused on Fecht. Last, and Marrant,1979 - RHO-LD-72. BLUE =Injection/release point Average thickness adjusted to normalize the average strata thicknesses to equal the total thickness of the vadlosezone.

A.4

14H

S

iNA

Hanford formation, Sand (S2) 664 sand dominated

ltd Class ________

HgI1

NA

Templat 21GA4LAW N-X for:th northern portion of the ILAW Site. Surlacr Easling = 574,656 m, Northing- 135.69 m AdJUSted Hydraulic Average Property Elevation Depth Thickness Average Type* Description Geologic Unit ff1) Iff1) (ft)t Thickness (ft) NA NA 714 Surface B Sand and Gravel 714 Backfill 0 so so 168

I

5G2 NA

HI

Hts

S

Hanford formation, Sand (S2) 668 sand dominated Hanford formation, 504 gravel dominated Gravelly sand to sandy gravel (G3)

SAC Soil KdZone Type NA NA HI B

S

m _C-Xfor the central portion of the ILAWsite. Nearsufa Easting = 574,407m, Nortfirma 13,5 Temp t 21GRA-11LAW Adju tea Hydraulic Average Property Elevation Depth Thickness Average Type* Description Geologic Unit (ft) ff9) Mftt Thickness (f9) NA NA 718 Surface 8 Sand-and Gravel 718 Backfili 0 so 50

164

200A ILAWS-4

INA

4H

_

VZ Base Templates B North 200 East Area (B Plant facilities and burial grounds) Stratigraphic Columns Notes/Assumptions. I ) Topography ranges from 700 ht L east of6BPlant to 5906i MSL in the northeast corner of 200 East Area (USGS Gable Butte7 5 mis, Quadrangle Map). Will assume as average elevation ot 6456i MSL part sf 200 East to 116m 2) The pre-Hanford Water Table (January 1944)is estimated to range from an elevation of 116 m (380 ft) in the eastemn (390 tt)in the weetemnpart (BNWL-B-360). Will assume an average water table elevation of 117mn(3856i) MSL. 3) A thin blanket of eslian sand and silt covers the sarface of the site whierenot disturbed. However, this material was generally removed during encavation and construction of the waste disposal sites andthen incorporated into backfill materials. The depth of the sites and thus, the backfull over these cites range from 0 m for ponds and unplanned releases, to an average of about 4.5 m for cribs and burial grounds and up to 16d4mfor tanks. 4) Five reverse wells are located in this area ranging in depth from 15 - 62 m Assume average depth of 50m (1646t).with an average preforated interval of 11.5 mn(38 6t). 5) Injection well 216-B-4 is 108' deep; 216-B-h is perted 252-302': 216-B-6 is perfed 73-75' ____20-2 _____ Teople 20013-Xfor surface cdlspo siates (e~g Buldilngs, Ponds, Ditches, Unplanned Releases) Average Thickness (ft)

AverageHyrui ThicknessPrpty (ft)+ Depth (ft) Elevation (ft) Geologic Unit

2

2

2

60

64

66 249

173 173 183 183

10

249Hantvrd

1

60

643 Enon

Sendandst

576 HantordGrael

slightly s~fypebbiy very coarseto

396

Casu 200East ~~~North Sand mci

85-mntdflr-ae Pleistocene

365 WaterTalusl

______2605

TeO ai

2168-X fo- shallow dis

aslsites (e

-.Cribs.

Description

omdumsn

istvPvces

47

Depth (it) Elevation It) Geologic Unit 0 645 Surface NA _____ 9-am is 630 B-aci 15 66

579 HianfordGrael

17 13

29

36anford Sand

Not 20

at

KdZonei

KdClass

KuClass

KdClass

S

Hss

HI

2H

3H

4H

SGl

Hg

HI

2H

3H

4H

S

Hon

11

211

311

411

NA

NA

NA

INA

NA

NA

26-

)182

Burfi'I Grounds)

51

SCoi Type

2008-4

Pebly~iverycoarse to coarse sand tv sandymediumto fie pebble NA

Average Thickness Average Thickness (11) (ft~n 15

osihl omdu

Type

____

200-3

Description

Siltysandymediumto tinepebbie to sligahtlysillypebblyvery coarseto coarsesand Coarseto mediumsand to slightly pebbly saighy siltycoarse to rmediumt

Hydraulic Property Type. NA

SAC Soil Type NA B

113

K, Zone**

K. Class

KuClass

KuClass

NA NA

NA 2H

NA 3H

NA 4

Hg

HI

2H

3H

4H

S

Hcs

11

211

311

411

NA

NA

NA

NA

INA

SG1

snanee diae

10 11

260

385 Hantot Pleistoonne

20

201

260

385 WatrTlae

Pebblyverycoarse to coarse sand to sandy wediurnto fine pebile

NA

._____241I8-2 241 B-X for tanks Adjusted Average Thickness Average Thickness (Ut) 11111t Depth (it) Elevation (Ut)Geologic Unit NA 0 645 Surface aentut 5958cn 50 50 50

1

Temnplt

12

16

66

579 HanfordGravel

173

183

249

396

10

11

260

385

260

385

_______________

N ___

Description

Shnysandymedium totfne pebile to slightly sitlypebbly o..ry cure to coarse sand

Not 0at carse to medium sand ro slightly pebbly sliightlysilty noameto mni HanfordSane sand UnifltetonoatedPebyvr o se ce~tor to O tb 5nOt riantord/PioPleistocene sandt medium ato ,:neanp0to NA Water Table

A.5

Hydraulic Property Type* NA7 B

SAC Soil Type KuZone" NA NA NA B

~

KuClass NA 2H

SGf

Hg

HI

2H

S

Hcs

I

1

SGl

Hg

I

NA

NA

N

A

____

Tenitt 266B-X for dp

in ctice sites tem. reverse wells

except 216I-9-512).

AverageHyrui ThicknessPrpty Average Description Depth (ft) Elevation(ft) Geologic Unit Mt)1 Thickness (ft) NA 645 Surface ______0 Sendandst 643 Eolran 2 2 2 s0

64

98

183 10 11 10 11

Average Thickness [ft) 2 60

N

KdClass

KdZone** AN NA N

411

NA

412

519onh 200East41 pebblyslightlysilty coarseto oediunn d Hannor San

S

Hcs

INA41

164

481

S____

249 260

396

260

slightlysilty pebblyvery coarseto

519

____________

~~~~Undfifferencaned Pebblyvenycoarseto coars adt ,I:sn t 385 ~Hanfov/l sandymediumto tfn pbl Pleistocne

lion sites (LA.,the 216--

2

64

66

183

249

s

MA

I

S G

g

I

NA

NA

N

G

643 Eotio 579 HanfordGravel 396 HafrdSn

Description Sand and sift lightly silty,peby very coarseto

pebblysllgrtly sftrycoarseto rmediirr

Property Type.

SAC Soil Type

KdZone**

H

HS

1 NA

_________

r___267B-2

reverse wea(a))

AverageHyrui Thickness Mftt Depth (It) Elevation (ft) Geologic Unit 2

SCoi Type

Hg

579 Hanford Gravel

NA 385 WaterTable 260 _______ _______ is parted 73-75' is ported 252-302', 216-13-6 (a) Injection well 216-B-4 is 108'deep; 216-B3-5

Templte 267-X for vr-y deep In

Type.

SG1

66 60 126 60 126

173

____2668B4

_____

_

_

KdClass

S

Hss

NA

211

SG1

Hg

NA

212

S

HEN

NA

211

SG1 NA

Hg NA

sandtneaae mesaane

10

8

260 260

385 385Water Table

savity -Jr-,ee to fn pebble NA

*After Khaleel and Freeman (1995) -HI=hrgh impact, IIlnterroediate Impact (After Composite Analysts) BLUE = Injection/release point Average thickness adjusted to normalize the average strata thicknesses to equal the total thickness of the vadose zone.

A.6

HI NA

2H NA

__________

___

VZ Base Templates C 100-BIC Stratigraphic Columns Notes/Assumptions: 1) Elevation ranges from 500 ft AMSL in the south to about 400 IftAMSL to the north along the rivers edge (USGS Vemita Bridge and Riverland 7.5 win. Quad Maps). Average elevation near retention basins -440 ft and increases to the south (up to 460 ft) away from the river. 2) The water table rangestfrom an elevation of 122wm (400.3 ft) to 123 mn(403.5 ft) (Hatman and Dresel 1998). Assume an average water table elevation of 122.5wm (402 ft) AMSL 3) A thin L<1m) blanket of eolian or fluvial sand or silt may cover the surface of the site where not disturbed. Some backfill may also be present but it is not documented in existing reports. 4) No reverse wells are located in this aggregate area. IOOC-4

Template 100C.X - For surface disposal sites (i.e. reactors) Adjusted Average Average Thickness Thickness (ft)t -Depth (it) Elevation (11) Geologic Unit R~ 460 uface KA __ _ _ 0

Hydraulic Property Type NA

Description

SAC Soil Kd ZoneType NA HI

Kd Class 4H

Siltysandypebbieto bouldergravel

30

30

1

281 1_____

sand

IIcoarse

I 1_____

581

4021

1_____

581

402 1Water Table

INA

I

Description

Depth (ft) Elevation (11)Geologic Unit

(ft)t 15

0 15

460 Surface 445Backill

301

45

415 Hanfordfr gravel withlensesofgravellymediumto

_____

Hg

NA

HI

4H

II

412 A N

I993

IO

Template 116C-X - For shallow dispgosal sftes, (i.e. cribs, trenches, burial grounds, sand flter) Adjusted Average Average Thickness Thickness

....ft)!.....

SGi

430 Hanfordfmntrawl wth lensesof gravellymediumto

SG1 NA

I

jHj NA

1

NA

I

116C-4 Hydraulic Property

SAC Soil

Type*

Type

NA

NA

NA H1I

NA 4H

SG1

Hg

HI

4H

SGi

Hg

11

412

NA

NA

NAA

.5B

Kd! Zone-

Kd Class

Silly sandypebbleto bouldergravel 1coarse sand (00E 19931

13 ________________

58

402

58

402 WalerTable

NA

*AfterKhaleel and Freeman (1995), perwhite paperby Khaleel (September2000) HI=high impact, ll=lntermediate Impact (After Composite Analysis) BLUE = injection/release point t Average thickness adjusted to normalize the average strata thicknesses to equal the total thickness of the vadose zone.

A.7

VZ Base Templates D 100-DIDR Stratigraphic Columns Notes/Assumptions: 1) Surface elevation rsnges from 470 ft MSL along the southern boundary to about 390 ft MSL to the northwest along rivers edge (USGS Coyote Rapids 7.5 min, Quad Map). Will assume an average elevation of 460 ft MSL. 2) Water table ranges from an elevation of 116.5 m (382 ft) along the eastern boundary to 119 m (390.5 ft) to the northwest (DOE 1993, Hartman and Dresel 1998). Will assume an average water table elevation of 118 m (387 ft) MSL. 3) A thin L~1m) blanket of eolian or tluvial sand or sift may cover the surface of the site where not disturbed. Some backfill may also be present but it is not well documented in existing reports. 4) No reverse wells are located in the 100-D/DR aggregate ares. Temnpit 1iOD-X - For surface dis xrsal sites I.a. reactors) Adjusted Average Average Elevation Thickness Thickness Geologic Unit (ft) Depth (ft) (ft)t (ft)... KA 460 Surroc. 0

IOO;T]

Description

Hydraulic Property Type NA

SAC Soil Type NA

SGi

Hg

KidZoneNA

Kd Class NA

Sandygravelandgravellysand,weilh

430 Hanfvrdfm gravel localsandyand siltyinterbeds

30

30

( S231

1

201 1____

1

Tempiate 11 6D-X - Fnor shallow dts Adjusted Average Average Thickness Thickness (ft)

etersvnet a,196

531

4071

731

387IRingvld Unit E

[Sillysandygravel

731

387 1Waler Table

I____________

_____________

HI

G1 SG2 NA

Hj

I

Rg NA

I

I I

11

412

I

412

NA

NA

116D 4

sal sites I I.e. cribs, trenches, burial gronds, sand filter)

Depth [ft) 0 ______ 17 15

Elevation Geologic Unit (ft NA 460 Surtace

Description

443 ackddl

Hydraulic Property Type * NA B

SAC Soil Kd Zone** Kd Class Type NA NA NA 4H Hit 8

Sandygravelandgravelly sand,with

30

47

4131Hantvrd f.s gravel localsandyaedsilty interbeds

_______20 ________________

SG1

Hg

HI

4H

SG1

Hq j RII1 NA NA

11

412 412

et. al., 1996)

___________(Peterson

6

4H

________________

53 73

4071 3871Ringold Unit E

73

3871Water Table

Sillysandygravel I_____________

SG2 NA

I

After Khaleel and Freeman (1995), per white paper by Khaleel (September 2000) HI=high impact, ll=lnterrnediate Impact (After Composite Analysis) BLUE =injection/release point t Average thickness adjusted to normalize the average strata thicknesses to equal the total thickness of the vadose zone.

A.8

NA

VZ Base Templates E East 200 East Area (B-Pond) Stratigraphic Columns Notes/Assumptions: 1) Topography ranges from460 to 650 ft (137 to 198 m) MSL (USGS Gable Butte 7.5 min. Quadrangle Map). Will assume an average elevation of 169 m (555 ft) MSL. 2) The pre-Hanford Water Table (January 1944) is estimated to range from an elevation of 113 m (370 ft) to 116 m (380 ft) MSL (BNWL-B360). Will assume an average water table elevation of 115 m (375 ft) MSL. 3) A thin blanket of eolian sand and silt covers the surface of the site where not disturbed. However, this material was generally removed during excavation and construction of the waste disposal sites and then incorporated into backfill materials. 4) The depth of the sites and thus, the backfull over these sites range from 0 m for ponds and unplanned releases, to an average of about 4.5 m for cribs and burial grounds, and upto 16.4 mfor tanks. Tempi te 200E-X for sudaedsoa Adjusited Average Average Thickness Thickness (ft) Mt

Depth (ft)

___0__

3 12

3 11

____________

62

F

sites (e. 1.Ponds)

58

3

Elevation (fL Geologic Unit Description 555___tace 5S NA 552 Solian Sandand silt

~

14

79

__________

30_____________ 28 _____

_____

151

_________ _______

________

SAC Soil Type

Kd Zone**

Kd Class

NA

NA

HI

4H

S

Has

HI

4H

Silty sandy gravel sand to sandy to gravelly

SG1

Hg

HI

412

483 Hantordsand

Slightly pebbly, slightly silty cvarse to medium sand to coarse to fine sand

S

Hcs

11

411

SG1

Hg

11

412

SS

PPIZ

11

NA

NA

NA

1

85

Hydraulic Property Type

541 HanfordGravel

___________gravel

72

2OOE-4

404 Hantord gravel Sandy gravelto silty sandy __________gravel

179

376 Ringold Lower d

I________

I

180

375 Water Table

INA

I

silt,sandy silt

BLUE =injection/release point t Average thickness adjusted to normalize the average strata thicknesses to equal the total thickness of the vadose zone.

A.9

411 I

NA

VZ Base Templates F 100-F Stratigraphic Columns Notes/Assumptions: 1) Surface elevation ranges from 420 ft MSL within the north-centra 100-F Area to about 380 ft MSL to the northeast along rivers edge (USGS Locke Island 7.5 min. Quad Map). Will assume an aeerage elevation ot 410 ft MSL 2) Water table ranges from an elevation ot 113 5 m (372 ft) in the southeast to 115 m (3770f) to the north (Hartman and Dresel 1998). Will assume an average water table elevation of 114 m (374 ft) MSL 3) A thin L~l m) blanket of eotian or fluvial sand or silt may cover the surface of the site where not disturbed. Some backhtllmay atso be present but it is not well documented in existing reports. 4) No reverse wells are located in the 100-F aggregate area. Tempirns 1OOF-X for sufacedsposa sit(i. Adjusted Average Average Thickness Depth Thickness (ft) t (ft

6!

_____ ______

_____

Temipt te 1 1F-X for shalo

Jft

Geologic Unit

30

380 Hanford Gravel

Sand gravel to siiiy sandy gravel (Peterson et at. 19961. Gravei-domrinaied eath subordinatesanddnominatedfares IRaidi 1994),

361 301

3741

______

3741mater Table

____

1b

21

0 15~ 36

Elevation (ft)

Geologic Unit

410 Srface 395 Eakfil 374 Hanfnrd firngravei Idnrminated

_______

_____

301

s , sand fitter)

374 1Water Tabie

Description NA _________

NA

Kd Zone** NA

Kd Class NA

SGI

Hg

HI

4H

-Type

II NA

______

I

4121

NA

___

NA

.

1lF

Hydraulic Property Typea NA B

SAC Soil Type NA B

KidZone** NA

SGl

Hg

HI

4H

NA

NA

Sandy gravel tn silty sandy gravel (Petersn et al. 19961. Gravel-domineated with subordinatesandtacies(Raid 1994)I. 1NA

After Khaleel and Freeman (1995), per white paper byKhaleet (September 2000) HI=high impact, lt=lntermediate Impact (After Composite Analysis) BLUE = injection/release point t Average thickness adjusted to normalize the average strata thicknesses to equal the total thickness of thevadose zone.

A.10

SAC Soil

NtA

NA

I

1_____ OF.

___

SGl

____________

INA

___

Hydraulic Property Type

Description NA

Depth (ft)

_____

Elevation

di~sposal sites (e.g. cribs, tren c hes,buriat grout

Average Average Thickness Thickness [(fit (tt _____

_____________

41____ Surt~af...

_____

30

reactors)

NA

I

NA

H41

-

KdClass NA 4H4

VZ Base Templates G 200 North Area and Gable Mountain Pond (Aggregate Area G) Stratigraphic Columns Notes/Assumptions: 1) Topography ranges from 435 ft MSL at Gable Mountain Pond to 584 ft MSL in the 200 North Area (DOE/RL-92-17). Will assume an average elevation of 510 ft MSL. 2) The pre-Hanford Water Table (January 1944) is estimated to range from an elevation of 116 m (380 ft) to 11igm (390 ft) (BNWL-B-360). Will assume an average water table elevation of 117 m (385 ft) MSL. 3) A thin blanket of eolian sand and silt covers the surface of the site where not disturbed. However, this material was generally removed during excavation and construction of the waste disposal sites and then incorporated into backfill materials. The depth of the sites and thus, the backfull over these sites range from 0 m for ponds and unplanned releases, to an average of about 4.5 m for cribs and burial grounds. 4) There are no tanks or reverse wells in this aggregate area. Tempia

200,G-X for sufc

Average Thickness (ft)

I sites (e~g Ponds, trenches, buldings)

dso

Average Thickness (ft)t

3 1221

Depth (ft) Elevation (ft) Geologic Unit Description NA 0 51O Srface 3 3 507 Eolian aand andsilt 1241

121,

1___________ 1251

Tempia

____

________

-

386 lUndifferenciated coarse gravel gravelandsandto silty Hanfordformnationsandy 385 lWater Table

1

1NA

___

Hydraulic Property Type* NA S

___

SAC Soil Type IKd ZoneNA NA HI Hss

______0

15 110,

Hg

HI

4H

NA

NA

NA

NA 216G-4

Average Thickness (ft)t

Depth (ft) _Elevaion (ft) Geologic Unit 510 Surface NA 15 15 v495 ffackfill gasket

1091

1241 1____________ 1251

Kd Class NA 4H

SG1

216G-X for shallow disposalI sites (e._____Cribs)_

Average Thickness (ft)

200OG-4

ecito

386 lUndifferenciafed HanfordformnationCoarsegravelandsandto silty sandy gravelI

385]Water Table

_NA7

Hydraulic Property Type* NA B

SAC Soil Type Kd ZoneNA NA B HI

SG1

Hg

NA

NA

After Khaleel and Freeman (1995), per white paper by Khaleel (September 2000) HI=high impact, ll=lntermediate Impact (After Composite Analysis) BLUE = Injection/release point t Average thickness adjusted to normalize the average strata thicknesses to equal the total thickness of the vadlose zone.

A.1 I

I

Kd Class NA 4H

HI

4H

NA

NA

-

VZ Base Templates H 100-H Stratigraphic Columns Notes/Assumptions: 1) Surface elevation ranges from 425 ft MSL in the center of the 100-H Area to about 380 ft MSL along rivers edge to the northeast (USDOE, Hanford Site Topography - Locke Island, Bechtel Job #22192; USGS Locke Island 7.5 min Quad Map). Will assume an average elevation of 415 ft MSL. 2) Water table ranges from an elevation of 116 m (380 ft) to the south to 117 m (384 ft) to the northeast (Hartman and Dresel 1998). Will assume an average water table elevation of 116.5 m (382 ft) MSL. 3) A thin ('ri m) blanket of eolian or tluvial sand or silt may cover the surface of the site where not disturbed. Locally, up to 15 ft of backfill may also be present (Peterson et al. 1998) but it is not well documented in existing reports. 4) There are no reverse (injection wells) in the 100-H Aggregate Area. Tempi te 10OH-X form urc Average Thickness (ft) _

sites (i.e. retention ba ins)

dsoal

Average Thickness (ft)t ___

__

3

_____

Template 116H-X for alo Average Thickness (ft)

3038Hafr 30

Geologic Unit

41 Sutacit

Description NA

rgrvlSandy gravel withsubordinate gravelly 35HnorImgae sand(Petersener. al. 1996) 3821 382 water Table

Depth (ft) 0

__________ _____15

18

Elevation (ft

Geologic Unit

15__

415 Surface 400 Vackft.l

33

32Hnedr

33

382 waterTable

Hydraulic Property Type'

SAC Soil Type

NA

NA

NA

NA

SG1

Hg

HI

4H

1________________ SG1 1

NA

INA

dispoal sites (e.g. cribs, trenc es, burial gro nids)

Average Thickness (ft)t

____________

0__

331 331

____ _31 _____

Depth (ft)

Elevation (ft

____________________10-

_

Description NA

I

____

INA

A.12

!I

11

I

NA

____

____

I

412 NA

116$H-4

SAC Soil Type

Kd Zone"

Kd Class

NA

NA

NA

NA

B___

HI_4H

G

g

I

NA

NA

NA

Khaleel and Freeman (1995), per white paper by Khaleel (September 2000) Hlhigh impact, ll=lntermediate Impact (After Composite Analysis) BLUE = injection/release point t Average thickness adjusted to normalize the average strata thicknesses to equal the total thickness of the vadose zone. -After

q

NA

Kd Class

Hydraulic Property Type* B_______

rvrSandy gravelwith subordivale gravellyI

Kd Zone-

4 N

VZ Base Templates 1 200 North Area (Aggregate Area 1)Stratigraphic Columns Notes/Assumoptions: 1) Topography ranges from 580 IftMSL near 216-N-3in fhe NW portion of fis geographic area, to 540 ft MSL beneaththe old 216-NA Pond in the SE portion ot the area (Gable Butte Quadrangle,7.5 MinuteSeries, 1986). Will assume an aoerage elevation of 565 ft MSL 2) The pre-Hanford Water Table (January 1944) is estimated at an elevationof 395 ft (BNWL-B-360). Will assume an average water table elevation of 395fft MSL. 3) Stratigraphybased on asbuilt drawinogsof 699-hft-60A,ft,aod -51-63. A thio blankretof top soil (eoliaosood and silt) covers theourface of However, this material woo generally removed during excavationaed constuction of the waste disposal sites aod then incorporated into backfill mnaterials, The depth of the sites and thus, the bookfush over these sites range from 0 mnfor ponds and unplanned releases,to an averageof about 4.5 mntot cribs and burial grounds. 4) There are no tanks or reverse wells in this aggregatearea.

TafftPlato200GX

tf

d~~iap- IMee, (n g. Poo___ -_

Average Aeae Thickness Thicns ff1) 4 _____ ______

122

__

__________

175

39 Uard~fna ledt~ G-1

175

390 v.a.- Tas-

tfe.g.~ .0 Cos)

____

NA

NA

________

15

Property Depth (ft) Elevation (ft) Geologic Unit Description 0 565 vra S is fI 550 us.a warts

ttft~o165_____175,

t

STOMP Nofe~ R4t Node Index 0 Nodes Start

Kd Zone** Kd Ctass NA NAHI 4H

Hg

HI

NA

NA

I

_

F

6

NA

2161-4

39 390,Watr 70,0l

Typ NA S

Kd Zone* NA HIE

Kd Class NA 4'H

GI

Hg

HI

4H

NA

NA

annnrso -3 ta.raoma~ -. 10-

INA9

NA

I

NA

After Khaleel and Freeman (1995), per ch56epapet by Khaleel (September 2000) Hlvhigh impact, Illntermediafe Impact (After CompositeAnralysis) BLUE = Injection/release point Average thickness adjusted to normalize the averagestrata thicknesses to equal thetotal thickness ofthe vadose zone.

A.13

I

2004

350 Hss)4H),t.1.l1345,350,

1

344 Hg(4H)fI,1.t,1,344,

I STOMP Node Ratifies

SACSail

Typ NA S

j Node eddea End

345

344

4H

Hydraulic

A rae Thickness 191~

SAC Sail Type NA Hsr

____-

Average Thioes ff

-

SG1

Wavranto1ouln-

s

2604

_

Hydraulic Property Typ NA Si

Depth (ft) I levation [ft) Geotoglo Unit Description 0___ h)rt 3-_ V 3______ 562 1o.1sa. anysl

172

Temypa 21141-for &allwdsl

s,__buidigs

Nnde

(eden

enden

ft Nodes Start 30 320

21

Node

End

321 1

350 t(4H),,1,t,1,321,350, 320 Hg)4H),t'lt,1,'T~320,

VZ Base Templates K 100-K Stratigraphic Columns Notes/Assumptions: 1) Surface elevation ranges from 515 ft MSL in adjacent waste sites south of K Area to about 390 ft MSL to the northwest along rivers edge (USGS Coyote Rapids 7.5 min. Quad Map). Will assume an average elevation of 480 ft MSL, except injection wells which have projected surface elevation of 465 ft MSL. 2) Water table ranges from an elevation of 121 m (397 ft) to the northeast to 121.5 m (39ft) to the south (Hartman and Dresel 1998). Will assume an average water-table elevation of 121.5 m (399 ft) MSL. 3) A thin (<1 m) layer of eolian or fluvial sand or silt may cover the surface of the site where not disturbed (Lindberg 1995). 4) Two injection wells (116-KE-3 and 116-KE-2) extend 10 ft into water table, and approximately l0oft of the perforated casings extend above

Tem pl1a1te I00K-X for urface disposal sites (Le~ ponds and racos Average Average Thickness Thickness (ft) Mftt

10_________IOK-4

Depth (ft) Elevation (ft) Geologic Unit 0t

480t Surface

Description NA

Hydraulic Property Type

SAC Soil Type

NA

NA

Kd ZoneNA

Kd,Class NA

SG1

Hg

HI

4H

Sandy gravel to silty sandy

30

301

450 Hanfordtomgravel gravel intercalated vith gravelil sandto sand(Lindberg 1995, Peterson at. al. 1996)

15

451

36

81

399 RingoldUnitE

Flavialsandy gravelto sitty sandy grave (Lindberg 1995)

811

399, Water Table

N-A

______ ______

435

4412

________Hg__j_11SGj

S2

R

1G NA

Template 1ISK-X for shallow disposal sites le.g cribs, trench1es, burial grou ds) Average Thickness (ft)

Average Thickness (ft)t

Depth (ft) Elevation (ft) Geologic Unit 0 480 Surface NA

15

15

465 Sactshtt

1

Rg NNA

II

41 NA

_____116K-4

Description

Losesadyrl oty sand gravel

Hydraulic Property Type

SAC Soil Type Kit Zone-

Kd Class

NA

NA

NA

NA

B

B

HI

4H

SG1

Hg

HI

4H

1

42

NA

1 NA

Sandy gravelto silty sandy

36

30 45

43 Hnor I gavlgravet intercalated wth gravelly

81

399 RingoldUnit E

sandto sand lLindberg 1995. Peterson et. al. 1996)

399 WtrTbe

________81

Flovia sandy gravetto sitty Isandy gravel (Lindberg 19951

GRg 1G

NA

N

Rg

NA

1

Templte 1661(.X for d eep disposal sites (e.g. r verse wells)_____ Average Average Thickness Thickness (ft) (Ift)t

168K-4

Depth (Ift)Elevation (ft) Geologic Unit 0 465 Surface NA 20

20

445 Backill

Description

Loosesandy gravelto silty grave

___________sandy

Hydraulic Property Type NA BBI B_____

SAC Soil Type K Zone** NA

NA

B__11

Kd Class NA 1 _412_1

Sandy grave to sittysandy

20

401

425 Hanfordfmrgravel sand gravelintercalated with gravelly to sand(Lindberg 1995,

SG1

Hg

11

412

1

I

42 42

Peterson et, al, 19991

______________

16

56

409 RingoldUnit E

10

66

399

66

399 Water Table

Flavialsandy gravel to silty sandy gravel (Lindberg 1995)

INA

GRg GRg

SG2

Rg

HI

4H

NA

NA

NA

NA

After Khaleel and Freeman (1995), per white paper by Khaleel (September 2000) HI=high impact, ll=lntermediate Impact (After Composite Analysis) BLUE = injection/release point Red indicates changes based on e-mails from Cantrel to Last (12/19/01) and Freeman to Last (12/27/01) f Average thickness adjusted to normalize the average strata thicknesses to equal the total thickness of the vadose zone.

A.14

j

VZ Base Templates M 600 Area (M) Stratigraphic Columns (618-11) Notes/Assumptions: 1) Assume an average elevation of 450ft (137.2 m) MVSL.(USGS Topo -Richland, Wash, 15min. Quad. 1951) 2) Assume an average water table elevation of 389 ft (118.5m) MVSL. (Groundwater Monitoring Report, 2002, PNNL-141 87). 3) Lithofacies taken from Well Logs (699-13-3A). In Hanford Well Log Library Sigma V. Temp late 600M-X for surface dis Adjusted Average Average Thickness Thickness J!IL.. (ft t

sall siftes eg. Trenches, pods. unphi ned releases)

Depth Jftt Elevation (ft) 445 6 6 439 12 18 427

____0

221 ______10

405 Hanford Hgs Gravelly Sand

GS

Hgs

395 Hanford Hg

Gravel

SG1

q

387 Ringold Rg

Gravelly Sand (Ringold

SG2

Rg

_________

ribs, burial grounds)

Depth (ft) 0 15 15 3 18 221

______10

_________ _____

____

8

________ ______

________Formation)

__________

Geologic Elevation (ft) Unit 380 Surface 430 3ackfill 427 Hanford Hg

Description NA

Sandy Gravel

Hydraulic Property Type NA B SG1 GS

50

395 Hanford Hg

Gravel

SG1_

387 Ringold Rg

Gravelly Sand (Ringold

_________

411 412

NA

________Formation)

387 Water Table NA

I

NA

SAC Soil Type Kd Zone** Kd Class NA NA NA B HI 4HHg 11 412 Hgs

11

411

Hg

1

412

SG2

Rg

NA

NA

__________

After Khaleel and Freeman (1995), per white paper by Khaleel (September 2000). *HI = high impact, 11= Intermediate Impact, (After Composite Analysis) t Average thickness adjusted to normalize the average strata thicknesses to equal the total thickness of the vadose zone.

A.15

412

11 NA

161111-4

405 Hanford Hgs Gravelly Sand

58

1 111

_______-6________

40

58

1

___

NA

387 Water Table NA

58 all

SAC Soil Kd Zone** Kd Class Type NA NA NA Hcs HI 4H Hg 11 412

50 ________ ______

Termplate BIBM-X for shallow die Adjusted Average Average Thickness Thickness J!L..... (f)

Hydraulic Property Type * NA _ S SG1

40

58

8 _________ ______ _____

Geologic Description Unit Surface NA Hanford Hfs Silty Silty Sand Hanford Hg Sandy Gravel

______655W-4

11

412

NA

NA

___

VZ Base Templates N 100-N Stratigraphic Columns Notes/Assumptions: 1) Surface elevation ranges from 460 ft MSL in the center of the 100-N Area to about 390 ft MSL along the rivers edge to the northwest (UISGS Coyote Rapids 7.5 min. Quad Map). Will assume an average elevation of 455 ft MSIL. 2) Water table ranges from an elevation of 119 m (390 ft) to the east to 120.5 m (395 ft) to the west (Hart man and Dresel 1998). Will assume an average water table elevation of 119.5 m (392 ft) MSL. 3) A thin L~1m) blanket of eolian or fluvial sand or silt may cover the surface of the site where not disturbed. Locally, backfill may also be present but it is not well documented in existing reports. 4) There are no reverse (injection wells) in the 100-N Aggregate Area. TempilIts IOON-X for sa

ce disposal sites (i.e. ponds and eactor)

Average Thickness JL...(ft) ftt

Average Thickness

____

____

_

_________

Elevation Depth (ft) 0 30 3

L

455 Surface 2

afr

NA lacetkrsral sandy pebble to boulder mgae m grvelgravel (Hartman and Lindsey 1993)

30 3

425Hanord

10

40

415

23

63

392 Ringold Uot E

63

3?atrTbe

______ ______

Description

Geologic Unit

sandy pebble to cobble gravel IFluvial, (Hartrnan and Lindsey 1993)

OON-4

_____I

Hydraulic Property Type NA

SAC Soil Type NA

SG1

Hg

SG1

Hq

11

412

SG2

Rg

11

412

A

N

N

NA

NA

KidZoneNA HI

J!ft

Average Thickness (t)

Depth (ft)

_____15

25 23 _____

Description

Geologic Unit

455 Surface

______0

_____

Elevation (itL

NA

15

440 Batrtut

40

fin travel Glacionouvial sandy pebble to souader 4151Hasfordl

Hydraulic Property Type

Hydraulic Property Type

NA

B

NA 8

SG1

H H

gravel (Hartman and Lindsey 1993)

63

392 RrngoldUnitE

63

392 Water Table

4H

[-I__ 116N-4

Template 11 6N-X for salo wdisall sites le.g cribs and trenches) Average Thickness

KidClass NA

sandypebbleto cobbletravel Flonvial,

(Hartwan and Lindsey 1993) NA

SG2

Rg

NA

NA

After Kh aleel an d Freeman (199 5), per wh ite paper by Kh aleel (Septe mber 2000) HI=high impact, Il=lnitermediate Impact (After Composite Analysis) BLUE = injection/release point t Average thickness adjusted to normalize the average strata thicknesses to equal the total thickness of the vadose zone.

A. 16

Kd Zone-1 KdlClass NA

NA

HI I

4H4

I

11 NA7-

4

412 NA

VZ Base Templates P 600 Area (P) Stratigraphic Columns (316-4, 618-10) Notes/Assumptions: 1) Assume an average elevation of 440 ft (134.1 m)MSL. (USGS Topo - Richland, Wash, 15 min. Quad. 1951) 2) Assume an average water table elevation of 375.7 ft (114.5m) MSL. (Groundwater Monitoring Report, 2002, PNNL-14187). 3) Lithofacies taken from Well Logs (699-S6-E4A). In Hanford Well Log Library Sigma V. shte$ (e.g. Trenches, ponds, unplanned releases)

Template 60OP-X for sufc dsal Average Thickness

Average Thickness (it)

-f~

______

35

_______35

35

70 701

____

______

445 Surface

___

___0

Description

Depth (ft) Elevation (it) Geologic Unit* 410 Hanford Hcs 35HnodH afr g 70 37 3751Water Table

NA

Grey to Black Basaltic Sand Gravel with sand and small

amount of clay______

NA

SAC Soil Type

NA

NA

NA

NA

S

Hcs

4H

SG1

Hg

HI 11

NA

NA

N

Description Deth ft) Elevation (ft Geologic Unit NA 0 380 Surface 430 ackll 15 Is 410 Hanford Hcs IGrey to Black Basaltic Sand 35 20 Gravel with sand and small g 35 afr 751 35 amount of clay_____ 70 375 Hanford Hg NA 3751 Water Table 701 1__________

Hydraulic Property Type * NA B S L SG1

SAC Soil Type Kd ZoneNA NA Hf B HI Hcs 11 Hg NA

per white paper by Khaleel (September 2000). After Khaleet and Freeman (199g5), HI = high impact, 11 Intermediate Impact, (After Composite Analysis) tAverage thickness adjusted to normalize the average strata thicknesses to equal the total thickness of the vadose zone.

A. 17

N

412

16P-4

_____6__

Average Thickness (ft)f

1

Kd Zone** Kd Class

_______________

NA

Template 616P-X for shatilo dispos I (e.g. cribs, burial ground) Average Thickness (ft)

600P-4

..

Hydraulic Property Type

A

Kd Class NA 4H 4H 412 N

VZ Base Templates Q 400 Area (Q) Stratigraphic Columns Notes/Assumptions: 1) Assume an average elevation of 540 ft (164.6m) MSL. (USGS Topo - Richland, Wash, 15 min. Quad. 1951) 2) Assume an average water table elevation of 392 ft (119.5m) MSL. (Groundwater Monitoring Report, 2001, PNNL-1 3788). 3) Lithofacies taken from Summary Report, FFTF Well No. 4 (499-S1-BJ) in Project Inspection Log Book Project V-749, Meier Associates, Inc. and well logs for 499-S1-7B. InHanford Well Log Library Sigma V. Template 4000-X for sufc diaspo Average Thickness

.J!ft....

Average Thickness (ft)t

Elevation Description (ft Geologic Unit Depth (ft) NA 0 540 Surface Fine sand to silty medium 54 486 Hanford Hfs sand, with occational lenses of 54 II I Icoarse sand.1 70 124 416 Hanford Hss Silty fine to medium sand. 24

_____

sites (e.g. Trenches, onds,unplanne releases)

_____

148

392 Hanford Hcs

1481

392 Water Table

Interbedded gravelly sand, and silty sand, and silty gravel. INA

f4000-4 Hydraulic Property Type NA i S

SAC Soil Type Kd Zone-~ NA NA Hfs

Average Thickness

... ft)L.....

Mftt

1 S

Hss

S

Hcs

NA

NA

11

I

(Jt)

0 15

380 Surface 525~ 3ackfll

39

54

486 Hanford Hfs I

______70

24 _____

_____

Description

Geologic Unit

15

411

11

411

NA

NA 416Q.4

Elevation

Depth (ft)

4H

HI

Template 416Q-X for shallw disposal (e.g. cribs burisl grounds) Average Thickness

Kd Class NA

NA __________

Fine sand to silty medium sand, with occational lenses of coarse sand.11 Silty fine to medium sand.

124

416 Hanford Hss

148

392 Hanford Hcs

Interbedded gravelly sand,' and silty sand, and silty gravel.

148

392 Waler Table

NA

Hydraulic Property

SAC Soil

Type

Type

Kd Zone-

Kd Class

NA B

NA B

NA HI

NA 4H

S

Hfs

HI

4H

S

Hss

11

411

S

Hcs

11

411

NA

NA

After Khaleel and Freeman (1995), per white paper byKhaleel (September 2000). *HI= high impact, 11= Intermediate Impact, (After Composite Analysis) t Average thickness adjusted to normalize the average strata thicknesses to equal the total thickness of the vadose zone.

A. 18

NA

NA

VZ Base Templates R 300 Area (R) Stratigraphic Columns Notes/Assumptions: 1) Assume an average elevation of 380 ft (115.8m) MSL. (Schalla et. a[, 1988) 2) Assume an average water table elevation of 347 ft (106m) MSL. (Groundwater Monitoring Report, 1999). tWaterievels flucutate daily, weekly and seasonally up to a meter depending on postion relative to the river Water levels have been increasing recently due to irrigation west of 300 Area 3) Lithofacies after Lindsey, 89, 91 and Gaylord Lindsey, g0, Lithofacies are highly varible in thickness and extent because of the fluvial nature of depostion Tempiate 30DR-X for surface dispos at sites (e.11Trenches, ponds, unplannr releases) Adjusted Average Average Thickness Description Thickness (it) *Jtj Depth (ft) Elevation (it) Geologic Unit INA 380Surface 0 2

2 37 71 6

1

2

Hss

HI

4H

SG 1

Hg

HI

4H

SG2

Rg

11

S S

Pz PZ

I1

NA

NA

NA

341 Hanford Hg

71

110

270 Ringold Rg

Fluvialgravel litbolfacies sandy tv pebble-sized gravel

61 61

171

20 Ringold Rm massive toup lanminated _1_17_209 ________ R comprises tv 10%sift;sand 201 Water Table NA

Tempiate 316R-X for surface disos sat sites (e.g Trenches, ponds, unplanne releases) Adjusted Average Average Thickness Description (ft t Det f)Elevation (ft) GogiUnt Thickness (ft) NA ______0 380 Surface 15 15 365 Backfitl 15 37

24 71 1

391

71______

6161 ____________ 70_____

10 11

171 __________ ________ 171

Kd Class NA

S

39

1711

SAC Soil Type Kd ZoneNA NA

band andsilt (absent for trenchesand

37

701

Hydraulic Property Type NA

378 Eolian

Gravel (Cobble/bvulder to afterLindsey, travel/pebble luhotacien 89, 91 andGaylordLindsey,901

_______________________granale-

300R-4

_____

341 Hanford Hg 70 iooldRg 7OinodR

Gravel(Cobble/boulder to afterLindsey, grawl/pebble Idthotacies, 189,91 andGaylordLindsey,901 Fluvial gravel iftbotacies sandy ranoleto pebble-sized gravel

209 Ringold Rm massiveto laminatedsit; sand __________ ___________comprises ap tv 10% 209 Water Table

INA

11 1

NA

_______316R-4

Hydraulic Property Type NA B

SAC Soil Type KZoe NA NA B J-I Hg

SGI -

HI

Kd Class NA 4H 4H

- -

S2

Rg

11

412

SS

PPIZ

11

412

NA

NA

NA

NA

_____________

t Average thickness adjusted to normalize the average strata thicknesses to equal the total thickness of the vadose zone.

A.19

412

VZ Base Templates S South 200 West Area (S, U [except U-1&2], Z Areas [except 216-Z-9]and ERDF) Stratigraphic Columns ions Noftes/Assumpt ofthe S-16 Pond(USGSGableButteandRiveriandT5mm. Quad 1) Topographry rangesfrom730ft MSLeastof ERDFto 625ft MSLsouthwest Maps). W~illassume an averageelevation of 680 f IMSL of f122m (400it) eastof ERIF to f127m (4f17tft)west ofthe isestimatedfto rangefroman elevation 2) The pre-Hanford Water Table (January f1944) S-f6 Pond(DOE-hiS-0i f13,page4 21) Will assume an averagewatertableelevationof 124 m (407ft)MSL 3) A thin blanket of noliansandandsift coversthe surfaceof the sitewherenotdisturbed. of the wastedisposalsitesandthen incorporated info backhil However, this materialwas generally removedduringexcavationannconstruction materials. rangefrom0-2.6mnfor pondsandunplannedreleases,to an averageot about4.5to The depthof the sites andthus,the backfuiioverthese Odtes 5.7 m for cribs andbanialgrounds, and13.7to 16.4mnfortanks. 4) Onlytwo reverse wellsare located in this arearangingin depthfrom23 -46 m. in screenedfrom50-75ft 5) Injectionwelt 216-2- 10 is screened from118-150ft. 216-U-d Template2009-X or surfacedso

(Prt)

____ efts

Ponds)_______ __

Depth(14)Elevation(Ift) Geotogic Unt

Mttt

6O

65

70

610Hnfrioinrd G-e

oiuay ft

30

301

100

580H~ofloooo Sand

Sighlftny -tor

30

301

130

550 HnfoordSilySand

15

20

150

neoceoelEarly 530 Palo-'el

20

20

170

510 Can-r

102

277d 2731

40 40/

Tamplate21654- for shfal low

_____ sites___

Cribs,_ Bu

.urrTae

Type

Description

OGf

urien tonrepeb iv

Shorny .1on -eu-

fin, -od

to -e fire-r

tityv~noeooriofine

so

rt,to reroefirov

su, -d-

to -ayfioeto.

E)oOlothno-rld, NA

Gond)_____1

Type

200S-2

200S.3

200S-4

Kd 0 Ctass 0 Zone** K0 Ctass K0 Class K0 Class K

11

112 1

212 1

312

412

S

Hfs

2W

It

111

211

311

411

S

Hon2W

it

111

211

311

411

SS

PPtz

11

ilt

211

311

4)11

SO

PPIc

IiI

i

1

112

212 NA

-3121 NA

1S2

1S3

502 NA

H2W

Rg_2W NA I

!1 NA

_____________

i

1

412 NA 1S

Hyrali

Averargeoer Aveag

Deph (ft)

Ift) 11M~t

20

r____ 2003-1

_

____

________

20

170

levatio

(11)

Go-lgicro Unit

560Cuich

l

sum crton

adny -yod -.

100 _______________

272 27

3001130

400HaordlSaind 47 wte rule

noonlat

iree

tooe

venfo

B-11n1

..

~

Bv

S NAy

His 2W NAu

K~as

dl

K~ls

)tO

212

311

411

il2 NAy

212 NAZ

312 NA

412 NA

1

1

1

to fineversa to

tor in a

ShO

55Hafod Slt S- to.1t --.

dlss

Type

8odo S

2,0 a

Hs2

It NA

1

i

Tern~p~ 21?S-x for rhalovw dipo

Thc

0es

I sites(e~g Cr-

0es

Thc

_______ receiving______ MAP___ C____

130ert

550

Hafr

it

F____

SAverage sierty tbyndvror~esn

ad

Hyddratoveyuleian

SoiWl

01-antNoNAJN 15

15

20

iplei5tocene

170

62 30

301 10

100

272

~~~

15 200 00~ 30 30

30r

30

BelaBHly1

510,-ir Gauch

ell rdynndren

580 HenfonJSend

SiltySandyMedivnto

400

Sandhy verycoarseto fine , ende iI It ndoatdI,2 -lfn -5

t

15pra

~

)

~

~~~~~~~~ 7 01 100 ~ 500

anrdaal g~l

~

510t

Gealo gic U

610

~nf~rd

65 60

70

30

301 100

100

272

20

lin,150refne

1

00

G.-

i

siopety Dovontertone

y

Sity Savy -edi-

580 Hanfi- Send

Sanvyry

400

findnay

5ee

0

Ringol SorltySn

210Z4 (Sill s~tes

Sirtae

64001

r ie

20

50

65

170.

510

100

5801H-fcnd Sand

100

172

400

Calio

i

W

Hs

2W

--

t

-

I

__

12__

H

3H

_

21

1

21-

H

KdIs 211

H

121

It

211

243

1

I

311as

H

411-

411s

4

!

1

312

412

211_31_41

_

PC

1

_2W

1122

sad

Hg

SG2

Ho PPbl

31

1

Si ss

~

SiltySandyMehiurrto toe - pebbl , toi

nrt,ltynl d

2ill

H1I

SACrs Sovryinelod Tynd Zone-

HP

sandy ,tycoarse t Rinfod 1000 Sed

H0

00

edS

Po-escee Pebblysltorao . very e tnf -ad! to e l Mlyrendyrnooeryfineo

30

W

l

HSS 2waste

002k

Sedyeehntrnd

Poase

20

BLUEd

HgR2W

Poeryty

5

il2

0

_

to meio voarse Psny verdy land nredivnonpbl

11

o2W

aS

-ell fin -d!

NOyr

HntoroUravE)

fn

2W

HI

to fine pebble to

"ntRg

l

0

atye- teaa -, i,(Sam

Thickne~~en~e Thcke 2.5

0G

sand

1

1

Bp

SS

ee

HI

2

SAC P So il

Poet S

n

Hanor Silt Sandedat tanks to

Pli-Piistvn aio

~ ~

yi-

Ho~2W

00i

n

itaoyodrnorpebb In5

170 ft

et

.-

S

b.

pel ine

,

, E)oor~n Slihy~tyoasooertesn

550

20

find

SIyfnW-yfn

Oavtylt

PtlrdnrediorIysiteytne 130

mention 205.

00

d

5100 e

Thebblys

20t

R-fnJldtV n

~ 3 .-~

170,

I NAo-

&_

1

414

HI2W 1

412

!1

wroie peyoer

intS

-,,-ecto IreePeepoin

Formulas for Depth (0) corrected by WE Nichols (04/16/02) tAverage thickness adjusted to normalize the average strata thicknesses to equal the total thickness 01 the vadose zone

A.21

H

2W

It

412

VZ Base Templates - U Cribs U Cribs (216-U-I, -2 and -16) Notes/Assumptions: 1) Surface elevation ranges from 211.0 m (692.3 ft) near 216-U-i 6 to 212.5 mn(697.2 ft) MSL near the 216-U-i and -2 Cribs (as taken from the Hanford Site Atlas). 2) Ground surface and water-table elevations from PNNL HYDRODAT database. 3) The pre-Hanford Water Table (January 1944) is estimated to have been at an elevation of 405 MSL (based on Kipp and Mud, 1974 - BNWL-B-360). 4) The site depth to bottom of the 216-U-i and -2 Cribs is reported to be 24 ft-mmn. (7.3 m) based on Maxfield, 1979 - RHO-CD-673. No bottom is reported for the 216-U-16 Crib. Thus, the backfill is assumed to be 24 deep for all three cribs. Template 2165jUj1-x for the area N-NE of the 216-U-1&2 Cribs, based on well 299-WI19-16 (N 135029.21, E 56727l. 68) located 24 mn(80 f)north of 216-U1 Crib. _ ________216S Estimated Adjusted Bottom Thickness Thickness Bottom Elevation (f)* (ft)t Depth (ift) (ft) Geologic Unit

24

24 67

67 55

5

5

Hydraulic Property Tye

SAC Soil Tp

Kd Class

NA

NA

NA

NA

Description

0

695.157 Surface

24

671 Backfill

Backfill

B

B

4H

91

604 Hanford H1

Interbedded layers of fine to coarse sand and sandy gravel

S

Hcs_2W

4H

514

4

54HafrH2

Interbedded layers of silty toHfU fine, medium, and coarse sand

4

afr2

HfU

19

19

165

530 CCU-upper

Silt and fine sand

SS

2

2

167

528 CCU-lower

Calcium-carbonate cemented sand, silt and clay (caliche)

SSSPI41

83

83

250

445 Ringold Unit E

Sandy gravel

250.59

____________

U N-

444.57 Water Table

NA

SG2 _____

PPIZ U

41 41

411

Pc

41

Rq_

412

_____

NA

Template 2165_UC-x for the central a rea between 216-U-li/2 C ribs and 216-U-1 6 C rib based on well 299-Wl19-15 (N 134975.78, E 567254.25), located about 26 m (85 ft)south of216-U-I 12 Cribs and 56 mn(185 t) north of 216-U-l6 Crib. 216SjJC Estimated Adjusted Thickness Thickness Bottom (ft Mt (if Depth (ft) 0 105

105

Bottom Elevation (ift) Geologic Unit 693.501 Surface

Hydraulic Property Type *

SAC Soil Type

Kd Class

NA

NA

NA

NA

NA NA

Hs241 Hs2

Description

105

589 Hanford Hi

Interbedded of fine to coarse sand layers and sandy gravel

43 43

148

546 Hanford H2

layers of silty to fine, medium, and coarse sand

16

16

164

530 CCU-upper

Silt and fine sand

SS

PPIz U

3

3

167

527 CCU-lower

Calcium-carbonate cemented sand, silt and clay (caliche)

SS

PPIc

411

9 44 30

9 44 30

176 220 250

518 Upper Ringold 474 Ringold Unit E 444 Ringold Unit E

Medium to coarse sand Sandy gravel Medium to coarse sand

Hcs

SG2

411 412 411

43

____________

249.55,

~Interbedded

443.95,Water Table

A.22

NA

SHsU

S S _____

HsU

Rg

Hcs _____

41 4

4

4H

NA

Template 216SUS-x for the southern portion of the 216-U-1& 2 crib area, based on well 299-W1 9-14 (N 134831.14, _ ________216S E 5672 7.99), located 9 m (30 f) fromSE edge of 216-UI-16 Crib. Bottom Estimated Adjusted Elevation Thickness Thickness Bottom Geologic Unit (ft) Depth (ft) (ft)t (ft)***

Description

NA

NA

Backfill

B

B

4H

S

Hs2W

4H

HsU

41

HfU

41

PPIz U

411

86

110

583 Hanford Hi

Interbedded layers of fine to coarse sand and sandy gravel

42

42

152

541 Hanford H2

Interbedded layers of silty to fine, medium, and coarse sand

14

14

166

527 CCU-upper

Silt and fine sand

4

53CUlwr 53CUoer

cemented Calcium-carbonate sand, silt and clay (caliche)

248

445 Ringold Unit E 445-42 Water Table

78

NA

669 ackfill

86

78

Kd Class

NA

24

____________

SAC Soil Type

693.44 Surface

24

4

Hydraulic Property Type

0 24

4

U S-4

1010

248.02

Sandy gravel NA

SS SPC

SG2 _____

PI

1 41

Rg

412

_____

Khaleel and Freeman (1995), per white paper by Khaleel (September 2000) impact, ll=lntermediate Impact (After Composite Analysis) **Based on Fecht, Last, and Marratt, 1979 - RHO-LD-72. BLUE = Injection/release point GREEN = Modifications by Nichols to support air phase modeling t Average thickness adjusted to normalize the average strata thicknesses to equal the total thickness of the vadose zone. *After

*HI=high

A.23

NA

VZ Base Templates 216-Z-9 Trench

-

S_Z9

Notes/Assumptions: 1) Land surface elevations range from 201.1 m (860 ft) near well 299-Wi15-39 to 209.4 m (697 ft)near well 299-Wi16-18. Will assume an average elevation of 205.2 m (673 6t)MSL. 2) The pre-Hanford Water Table (January 1944) is estimated to range from an elevation of 122m (4006f) east of ERDF to 127 m (4176f) west of the S-1 6 Pond (DOE-EIS-01 13, page 4.21). The lowest measured water-level was 440.6 ft in 299-Wi 5-5 on April 18, 1 Will assume a minimum water table elevation of 124 m (4076f) MSL. 3) A thin blanket of eolian sand and silt covers the surface of the site where not disturbed. However, this material was generally removed during excavation and construction of the waste disposal sites and then incorporated into backfill materials. 4) The depth of the 216-Z-9 Trench is about 6.1 m (206f). Note that it has a concrete cover. A building also partially overlies the site.

Temp t217S ZS-Xfrfhe216-9 Tenlch

Geologic UnitI

Description

Surfac~e

Concrete

Bacill

Gravelly Medium

Hartford Gravel (Hi)

Sandy Gravel

2175 ZO-1

j

Ajustd Dpht evfo Hy/ tton Hdraulic Average Average Dpho Depth to Elevation Top of Top Thickness Thickness Bottom of Bottom Property (ft) t Contact (it) Contact (ft) Type Contact (ft) Contact (ift ) NA 673 0 0 0 0

7

20

653

SAC Soil Type

KdZone**

K,,Class

NA

NA

NA 1H

15

2

20

653

B

B

HI

29.2

24

.44

629

SG1

HgZ

HI

Hanford Sand (H2) Coarse to Medium Sand Slightly Muddy Hanford Medium to Fine Hnfrdead and S)andto Sandy antrdd Mud and ud H4( Sandy Mud CCU Sill Calcareous Gravelly, Muddy, CCU Carbonate Sand Semi-indurated Ringold (Unit E) Muddy Sandy

44

62

39.2

39

83

590

S

HfsZ

11

ill

83

590

23.4

23

106

567

5

Hss Z

II

ill

106

567

8.7

9

15

558

SS

PPlz Z

11

ill

115

558

4.0

4

119

54

SS

PPIc Z

11

ill

119

5>4

146.1

147

266

407

SG2

Rg 2W

11

112

26

407

1270

163

429

244

GW

49

244

54.0

190

GW

190 4

450

54 5 45

483

483

528

146

GW _

_____________Gravel

Rinold(Unt 6 -Semi-indurated RiglUi ) Muddy Sandy Saturated GravelI Ringold Lower Muddy Medium to Mud Fine Sand Ringold Unit A Sandy Gravel Elephanit Mountain Baat52 Basalt. I

Hand Entered Unsaturated Zone Geologic Data Taken from 8 wells near Z-9 (Wells 299-Wi 5-8, -9, -83, -84, -86, -95, -101, -217). Unsaturated Property Class Designations taken from SAC Rev. 0 Inputs. Saturated Zone Geologic Data Taken from 299-W15-5. Values

EZZIZZIHand Entered Lull Hand Entered ElCalculated

1H I

I____

t Average thickness adjusted to normalize the average strata thicknesses to equal the total thickness of the vadose zone.

A.24

VZ Base Templates T North 200 West Area (T Areas) Stratigraphic Columns Notes/Assumptions 1) Topography ranges frm 790 ft MSLin the NWcornerof the 216-W-5 banialgroundto about665 ftMSLeast of theTX Tankfarm (USGSGable Butte 7.5min Quad Maps). and Riverdand Will assume an average elevation of 6905fMSL 2) The pre-Hanford Water Table (January 1944)is estimated to rangefrom anetevation of 122m (4006f) eastof 200W to 127m (417li)on thewest page4.21). side ofthe 218-W-5 BanialGroand (KippandMud,1974; DOE-EIS-01t13, Will assame an average matertabteelevationof 124mn(407ft) MSL. 3) A thin btanket of noliansandandsilt coversthe surface ofthe sitewfherenotdisturbed. of the wastedisposal sites andthen incorporated into backhll However, this materialwas generally removedduringexcavation and coestruction materials. The depthof the sitesand thus, the backfnllover these sitesrangefrom0 mifor pondsandmostunplannedreleases,to an averageof about8 m for fortanks. cribs and burialgrounds, and apto 15wm 4) Only two reversewellsare located in thisarearangingin depthfrom22 - 62w., 6) Injection well215-T-2 is 75 It deep. 216-T-3is reportedas 266ft. Screenedintervalis unknow - will assume25 ftscreened interval. Temi ta2lOTXfor tsurface dispo asite (e.g.Pocls Average Thickness (ft)

AverageHyrui Thickness (ItM Depth (ft) 90

35

Etevation (ft)

90

9

32

127

5

Gooi Unit

K,,Zone-

____

_____

KaCtass

aClass

is

I

H4

H_2 PRGc

HI

2H1

4H

211

411

412

i,vn, Peylv

180

103

23

407 omnaiEvd P.1-"

127

Hafod sato slighyilty vwdIeycas 560Graell and.v mediu snGS

183

ver hne sadNt plitoee Sity hn to,, (Erl sigty slty - yetwvrfinebbe( 553 ,agldus~E) sand

25

_____

NAoNAooo

,o,.1 11

251

155

9t

SCSi Type

-tvrdNAoNAi Eh3Sorr

sisocv ityne eyd tire

10

rpry Type*

Description

t.a vsir Piv-igsvci my firypevaio v~ -e -0 535HCo,drvel vd,woeyvsvvaaiv Peby -v y re .. ,!i ojr .. d,..Say ely m.fdGa ,hi fty 563' Sepn~gi .. di

9

_____

______

~

GS

dyc ri

0-2 S

-

Hasz 2W

g 2Wl

1

212

Hon 2W

I

211

31

1

212

34112

P--t ,Pebbly vey corsto me, d iumfft 35

25

10

~

~

~

Tomp

16eag

13

~

~ ~

Crine

19eag Thicknessilt 25

2

10

52

~

R22W

silt coarseto~q sand mn ths PebblyoshIIwds Plitoeejositsmdumtevrdfn 5 P~c Hydrauihisncit alce See henkes toloi veryrt sandit 510Srfagce

SA

NAw-vdrd

26I

73

21

31

411

1T 1

NA

NA

2N1

3N1

4N1

Has 2W N

11 A

212 N

312 A

412 N

Siltysandy mediumto fiee Rigl ntPebble onyverycoarsetodu 13 _________

1283 283

fadoe peed sm nd 40 56Gael 407 W~~~lerTbeNdA

Hanford/Al25

d

002

Tewlate 241 TX for

____

____241__

_____

taik

10

(f~

pt

50vaio (f t)

137)

Dryioeri tin

P

,ipesadiyryoaurstofnoneandtot Piisocn

155

510 Hppnfod

SG

013

1253

457Sind

GS 522

55e

10T-______

indvl .rated pebl to 5.1w edy Me.iu to fiedu HiGislihnydly very w-s tolri besm cidraed Unit

~ ~ ~ ~) S8~Elvaio ~ ~ ~18~ryvDepth

IPI Unitcr

(N) (ftbly

NA5

10

137

50

tAverage thicknns

l

i.26T2&-

ane tonraieteaeaesrt

p S NA5

HI

211

1

212

NA

NAht

NAn

__

Tye PC NAi

K Zn NAd

1

K CasdCls NA 1

NAyfr

21141

P 1

ser

N

ANA

NA

NA 21

al

cnse oe

PP-z

medurfir sandrto

to n .r i e Iartet

23 47Water Sei - fnrecteee/release poitesf~.rvre BLUi E =6

ty

pisovn i ieto veryfine sandoity snd5 bapery Rainsi~ sltyyooeryfna Siirvee Pltiy coady oine san tocdtyz Pn

trdot

Ke Zoe-

S

Decitfin) o si ad t ih

sebly ver crs to

10

NAn

ver fine,_ t__vey insad

__

11Cs

Tpe~

er sado tot

25

253s457t WaterTto to1

Te10rt37

Typ

yUnitue

cigty ito y i

25

____2__

____

siropetoeryfneSadtosoil

eolcn

Thckes Ticpis

10)

____

ltettltikeso

H

A.NA

raoslzne

N 6T4

Appendix B Hydraulic Property Distributions

Hydraulic Property Distributions - Revised (4/22/03) (After Freeman's May 14, 2003 White Paper "Revised SAC Statistical Properties Tables of Vadose Hydraulic Properties"; Khaleel's Sept. 2000 White Paper, and

Table 1. Approximation for the distribution function for soil type "B" (backfill) based on KhaleeI Raw B Number Standard Of High Mean Deviation Transtormt sape Low Parameter 0.262 0.072 NO 0,187 0.375 s6 NO 0 064 0.03 0.029 BR D 7 D 0213 0.102 0.DB95 NO 5. -1(1/cm) 6 0,003 0,103 0,032 0&036 LN n 6 1.256 1.629 1.4 0.131 NO 6 0.0000276 K.(cm/s) 0,068 0015 0,027 LR Longitudinal Dispersivity' UIN INA 0,09 0,178 2 70E-02 NA (in) % Gravel

____

and Freeman (1995) soil category SSG

Transformed (normal distribution) Upper Lower Standard Limit Limit Mean Deviation

-56843

-2.27B

-3957

1,166

-10,854

2995

-5.262

5499

-

-

-

(sand and gravel mixed with finer Observed Data Beta Distribution A

B

0.136

-

-

_______

1,94 COBulk Density NA tND = Normal (astransformation reqaired): LN=Lognormal; LR Lo[0ratio; SN= Hyperbolic arcsine UN = Uniform,GD = Constant, BE =Beta 1Takes tramHo, et.al. 1999 [Stochastic Parameter Development for PDRFLOW Simulations of the HanfordAX Tank Farm] 2Takes tramKhaleel, et. al. 2009 (Modeling Data Package tarS-aX FieldInvestigatian Report(FIR) [DRAFT])

-

Upr 0,942 0,879 0 893 0.926 0.9%01

-

-

_____________________________________

Loe 0.149 0.150 0128 0.056

_______

-

-

Table 2. Approximation for the distribution function for soil type 'Has' (Hanford silty fine sand based on Khaleel and Freeman (1995) soil category SS (sand mixed with finer Beta Distribution Truncation Limits Transformed (normal distribution) Raw Hss Number Standard Standard Upper Lower Of Upper Mean Deviation A B Lower Deviation Transformt Limit Limit samples Low High Mean Parameter 0.991 0,019 NO 0,445 0.060 0.587 0.321 s38 1 000 0,053 0.033 NO 0.019 0.181 0,072 a38 5 9070 31.3000 0030 0.999 0 059 NO 38 0.047 0339 0,159 S, -7131 -4,866 1.212 0,031 0,999 -(1/cm) 36 0.001 0.387 0.008 0.076 LN -0.949 0.998 0.461 NO 0.078 n 38 1 262 3.265 1.915 K, (cm/n) 30 3.20E-07 8.88E-04 8,58E-05 2 66E-04 LN -7.027 -14,955 -9363 1.865 0.002 0 8921 Longitudinal Dispersivityl UN NA 0,031 0.0341 0 0279 NA () % Gravel 38 0 2 0,18 0,51 ____________ Bulk Density' 3cm 35, 1.28 213 1 61 017 NO3

Density

_

3

(9/CM )

NO

tND = Normal (no transformation required), [N = Lognormal;LR = Logratio;SIN= Hyperbolic arcsiac, UIN= Uniform, CD Constant, BE =Beta Simulations of the HanfordAX Tank Farm]. 'Taken from Ho, et. al. 1999 [Stochastic Parameter Development far PDRFLOWI 2Taken from Khaleel, et. al. 2000 (Modeling Data Package for S-ax FieldInvestigation Report (FIR) [DRAFT]). 3Taken from Freeman's e-mail to George Last, dated 12/27/01 (finetexiadoc and HSfexl doc). Table 3. Approximation for the distribution function for soil type "Hss 2W (Hanf rd silty fine sand - 200 West Area) based on Khaleel and Freeman (1995) soil category SS Beta Distribution Truncation Limits Transformed (normal distribution) Number Raw Hss 2W Lower Standard Standard Upper Of B Lower Upper Limif Mean Deviation A Deviation Transformt Limit Low High Mean Parameter samples 0.155 0,987 NO 0.076 0.566 0,398 0.321 s11 0.077 0,952 0.027 NO 0.102 0,057 11 0.019 0,914 652710 38.2750 0.046 NO 0.141 0.052 11 0.054 0,211 a, 0.804 0.015 0.949 0.004 [N -4.080 -7.131 -5,397 11 0.001 0.017 0.005 -;(1/cm) 0.985 0.132 2.116 0,528 NO n 11 1.527 3.265 0,150 0,9261 5SlOE-O5 LN -8.971 -12.226 -10,865 1.312 K. (cm/s) 5 4.90E-06 1,27E-04 1 91E-05 Longitudinal Dispersivityl NA UN0031 00279 0,0341 NA (in) 0.00D % Gravel 11 0.000 0,000 0 000 Bulk Density' 310,

Dens ity

1400

1.900

1,669

0167

NO-

-

-

3

tND = Normal(no transformation required); LN =Lognormal; LR = Logratio, SIN=Hyperbolic arosive, UN = Uniform, GO= Constant BE=Beta 'Taken from Ho, atf al., 1999[Stochastic Parameter Development for PDRFLOW Simulations of the HanfordAXTank Farm], 2Taken fromKhaleel et, al, 2000 (Modeling DataPackage for S-aX FieldInvestigation Repot (FIR) (DRAFT) 3Taken from Freeman's e-mail to George Last, dated 12/27/01 (finotexaadoc and HStexl .doc).

B. I

-

-

-

Table 4. Approximation for the distribution tunction tor soil type "Hss U" (Hanfor silty fine sand - 200-UP-i) based on Khaleel and Freeman (1995) soil category SS (sand Hss LI Number Raw Transformed (normal distribution) Beta Distribution Truncation Limits of Standard Upper Lower Standard Parameter Low High Mean Deviation Transformt Limit samples Limit Mean Deviation A B Lower Upper 0.140 0.952 0A437 0,078 NO 0.353 0.566 s6 0.074 0,866 0,033 NO 0.019 0.102 0.066 R6 S,6 0.054 0.211 0.147 0.064 NO 4.4347 25.6347 0,071 0.841 - (1/cm) 6 0.003 0,017 0.007 0.005 LN -4,080 -5.843 -4.994 0.596 0.077 0.937 n 6 1.527 3.265 2.347 0.597 NO 0.O085 0,938 K. (cm/s( 2 4 90E-06 1.276-04 2.49E-05 &.63E-05 LN -8.971 -12.226 -10 599 2.302 0.240 0.7601 Longitudinal Dispersivityl UN NA 0.031 0.0341 0.0279 NA () % Gravel 6 0 0 0 0 B~ulkDensity No1.4 1.72 1.58 0.131 (g/cm( 61 7'ri-cle

tNO = Narmal (ne transformation required); LN=Logrnormal; LR = Lagratio; SN = Hyperolic arcoine UN Uniform, CD = Constant, BE Beta 'Takes from Ho, et. al., 199e [Stochastic Parameter Development for PORFLOW Simulations of the Hanford AXTask Farm]. 2 Taken tram Khaleel, et. al. 2000 (Modeling Data Package for 0-OXFieldInvestigation Report(FIR) [DRAFT]). 3Taken from Freeman's e-mail to George Last, dated 12/27/01 (finetexaodoc and HStexl .doc). Table 5. Approximation for the distribution function for soil type "Hiss Raw Has Z Number of Parameter samples Low High Mean -s5 0.3208 0.4134 0.35058 -n 5,

5 5 5 5 1

(1 /cm) n K, (cm/s( Longitudinal Dispersivityl () %/aGravel

NA 5

Z" (Hanford silty fine sandl - 200-ZP-1 ) based on Khateet and Freeman (1995) soil category SS (sand Transformed (normal distribution) Beta Distribution Truncation Limits Standard Standard Upper Lower Limit Limit Mean Deviation A B Lower Upper Deviation Transformt 0.0401409 NO 0.229 0.941

0.03 0.06 0.047 0.01548031 0.09349845 0.17837508 0.13273273 0.0378506 0.0008 0.0064 0.00279414 0.00211376 1.63766 2.2593 1 839872 0.27356881 6.556-06 6.55E-06 6.556-06 0.006+00

NO NO LN NO LN

-5.05146 -11.936

-11.936

NA

UN

-

-

0.0279 0

0.0341 0

0.031 0

10.5323 -7.1309

-5.88023

0.136 0.150 0.058 0.230 0.000

68.8176

0.70664

-11.936

1

-

-

-

0

0.799 0.886 0.851 0.937 1.000

______

Buk ensity' 1 61

R M34

1.9

1.8

0.12987173

NO-

-

-

-

-

3

Density 3 NDO_______ (g/CM ) tNO = Normal (no transformation required); LN= Lognormal; LR = Logratio,SN = Hyperbolic arosine;UN = Uniform, CO = Constant, 66E Bela 'Taken fromHo, et. al., 1999 [Stochastic Parameter Development for PORFLOW Simulations of the Hanford AX Tank Farm]. 2Taken from Khaleel, et. al, 2000 (Modeling Data Package for S-OXField Investigation Report (FIR)[DRAFT]). 3Taken from Freeman's e-mail to George Last, dated 12/27/01 (fineteal adoc and H~fexi .doc). 3Revised by Nichols (unacceptable to truncate both the lower 50% and the upper 50%) Table 6. Approximation frorthe distribution function for soil type "Hfs'" (Hanford fine snd) baed on Khaleel and Freeman (1995) soil caeoyS(ad.As His Number Raw Transtormed (normal distribution) Beta Distribution Standard Standard Upper Lower Of Parameter samples Low High Mean Deviation TransformLimit Mean Deviation A Limit B -u40 0.266 0.657 0.397 0.076 NO 40

-n S,40 7.(1/cm) n K,)cm/s) Longitudinal Dispersivityl

mNA

Bulk ensity cm330 Density

40 40 40

0.000 0.000 0.002 1.193 6.726-08

0.183 1.33

0.426 0548 0.742 4.914 4.426-02

0.223 216

0.049 0.110 0.025 2.107 2.87E-04

0.076 0.122 0.135 0.859 7.84E-03

NA

0.203 1.60

018

NO NO LN NO LN

-0.299

-6.032

-3.694

1.337

-3.119

-16.516

-8.158

2.975

N

-

NO-

0.6183

-

-

Lower Upper, 0.042 1.000 1.000 0.261 0.183 1.000 0.040 0.994 0.143 0.999 0.002 0.955

-

-

_______________________________ 1NO (g/cm ) tNO = Normal/(no transformation required); LN=Lognormal: LR = Logratio:ON=Hyperbolic arcsine;UN Uniform, CO =Constant, BE Beta Simulations of the Hanford AX Tank Farm] Taken from Ho, et. al., 1999[Stochastic Parameter Development for PORIFLOW 2Taken from Khaleel, et. al 2000 (Modeling Data Package for a-OXFieldInvestigation Report(FIR) [DRAFT]) 3Taken from Freeman's e-mail to George Last, dated 12/27)01 (finetexla doc and H~texll.dloc).

B.2

4.9937

--

3

3

modified b Truncation Limits

-

-

Table 7 Approximation for the distribution function for soil type "HfsBC" (Hanfod fine sand - BC Cribs and Trenches) based on KhaleeI and Freeman (1995) soil category Number Hfs BC Raw Transformed (normal distribution) Beta Distribution Truncation Limits Of Standard Upper Lower Standard Parameter samples Low High Mean Deuiafion Transformt Limit Lim it Mean Deviation A B Lower Upper 0 081 0,945 s18 0,323 0,444 0380 0.040 NO 0,992 0.011 NO 0.065 R18 0.016 0.061 0.033 S,18 0,045 0,184 0.089 0.035 NO 5.8391 59.8393 0.102 0.997 1)(1/cm) 18 0,005 0.201 0.021 0.045 LIN -1.604 -5.279 -3,874 0.889 0.057 0.995 n 18 1.542 4,914 2,507 1,036 NO 0,176 0.990 K, (cm/s) 18 1.40E-04 4.428-02 2.25E-03 1 09E-02 LN -3.119 -8.874 -6,097 1.563 0.038 0.9721 Longitudinal Dispersivity (in) % Gravel BukDensity' 3

'gcm )

Density

0.183 0

0.223 2

0.203 0.38

NA 0.57

UN

18 8

1.52

1.79

1.65

0.10

NO-

NA

-

-

-

-

-

-

-

-

-

3

3

NO )g/CM ) tNO =Normal (ne transformation required); LN= Lagsorrna: LR Logratio, SN = Hyperboic arcsine; UN = Uniform, CO = Constant, BE=Beta 1Takes from Ho, et. al.,,1998 [Stochastic Parameter Development for PORFLOW Simalations of the Hanford AXTank Farm] 2Taken tramKhaieei, et, al, 2000 (Modeling Data Package for S-SXFieldInvestigation Report(FIR) [DRAFT]) 3Taken from Freeman's e-mail to George Last, dated 12127101(finetex adoc and HStexl .doc).

_______

Table 8. Approximation for the distribution function for soil type "Hfs 2W" (Hanford fine sand-200 West Area) based on Khaleel and Fireeman (1995) soil category S (sand). Hfs 2W Number Raw Transformed (normal distribution) Beta Distribution Truncation Limits Upper Lower Standard Of Standard Parameter samples Low High Mean Deviation Transformf Limit Limit Mean Deviation A B Lower Upper 71 s 8 0.325 0.433 0.356 0.035 NO 0.188 0.986 -R8 S, 7- (1/cm) n K, (cm/s) Longitudinal Dispersivity' ()

0.027 0.074 0.004 1.574 6.2l0

0.058 0.167 0.026 3.294 4.62E-04

8

0.183 0

0.223 2

7

1.58

1.82

NA

% Gravel Bulk ensity' (A/c

8 8 8 8

3

)

0.042 0.118 0.010 2.177 3.67E-05

0.014 0.040 0.008 0.546 1.76E-04

NA

0.203 0.38

074

1.70

0.10

NO NO LN NO LN

7.3390 -3.646

-5.613

-4.584

0.704

-7.680

-16.516

-10.212

2.808

UIN-

-

-

-

NO-

-

-

-

55.0938

0.143 0.142 0.072 0.135 0.012

0.869 0.889 0.909 0.980 0.816

-

-

3

Density 3

INO )(g/CM) tNO = Normal (no transformation required); LIN= Lognorma, LB Logratio;SN =Hyperbolic arcsine; UN =Uniform, CO = Constant, BE =Beta 'Taken fromHo, et. ai., 1999 [Stochastic Parameter Development tsr PORFLOWSimulations ot the Hanford AX Tank Farm) 2Taken from Khaleet,et. at. 2000 (Modeling Data Package for S-SXFieldInvestigation Report (FIR)[DRAFT]) 3Taken from Freeman's e-mail to George Last, dated 12/27/01 (finetexla.doc and HSteol doc).

_______

Table 9. Approximation for the distribution function for soil type "Hfs-U" (Hanford fine sand - 200-UP-i) based on Khaleel and Freemin (195) oilcategor S sand). As Hfs U Number Raw Transformed (normal distribution) Beta Distribution Truncation Limits Of Standard Upper Lower Standard Parameter samples Low High Mean Deviation Tranoformf Limit Limit Mean Deviation A B Lower Upper is4 0.325 0.374 0.347 0.021 0.150 0.902 NO IR4 S, (1/cm) n K. (cm/s) Longitudinal m Dispersivity N () % Gravel BukDensity' m34

(

Den sty

0.028 0.074 0.004 1.673 6.72E-08

0.057 0.163 0.026 3.294 4.62E-04

0.042 0.122 0013 2.451 1,71E-05

0.183 0

0.223 0

0.203 0

NA 0

UN

4

1.58

1.82

1.72

0.12.

NO-

A

0.015 0.047 0.010 0.1563 2.15E-04

NO NO LN NO LN

4 4 4 4

-5.613

-4.380

0.888

-7.680

-16.516

-10.975

3.841

-

-

-

-

-

-

-

-

-

-

-

I_________________________ NO 0 _______________________________ /(g/CM) fNO = Normal (no transformation required); LN= Lognormal; LR = Logratio,SN =Hyperbolic arcsine; UN = Unitorm, CO = Constant, BE Beta 1Taken from Ho, et al., 1888 [Stochastic Parameter Development for PORFLOW Simuiations of the Hanford AXTank Farm) 2Taken tromKhaleei. et. ai. 2000 (Modeling Data Package for S-SXFieldInvestigation Report (FIR) [DRAFT]) 3Taken from Freeman's e-mail to George Last, dated 12/27/01 (finetexla doc and HSteo1.doc).

B.3

42.5209

-3.646

3

3

5.9087

0.173

0.837

0.153 0.082 0.120 0.075

0.809 0.796 0.898 0.8051

Table 10 Approximation for the distribution function for soil type "Hfs Z" (Hanfor fine sand -200-ZP-1) based on Khaleel and Freeman (1995) soil catego ryS (sand). As Beta Distribution Truncation Limits Transformed (normal distribution) Raw Hfs Z Number Standard Lower Upper Standard Of Lower Upper B Deviation A Mean Limit Limit Mean Deviation Transformt High Low samples Parameter 0925 0199 NO 0047 0,433 0366 0326 4 0169 0850 0015 NO 0042 0027 0058 n4 0911 6 9964 54 8679 0.218 NO 0113 00B40 0,082 0,167 S,4 0,074 0.802 0.508 -4.788 LN -4.358 -5.521 0.008 0.004 4 0.004 0.013 (1/cm) 0.083 0.779 0238 NO0 1 903 1.574 2.086 4 n 0114 0.6581 -9.449 1.446 LN -7,902 -11.191 7.886-05 1.61E-04 4 1 38B-05 3 70E-04 K, (cm/s) 1 Longitudinal Dispersivityl UN NA 0.203 0.223 0183 NA (in) NO_______ 0.75 095742711 0 2 % Gravel 4 Bulk Density' 3 NO1.68 008544004 1.59 1 76 4 /cm

Den sity

3

NO I (9/cm) tNO Normal (so trassformation required); LN=Lognormal, LR = Lagratio,SN = Hyperbolic arcsine. UN = Uniform,CO= Constant, BE =Beta 'Takes tramHa, et. al ,.1999 [Stochastic Parameter Developmnt far PORFLOW Simulations of the HanfordAX Task Farm] 2Takes from Khaleel. et. al 2000 (Modeling Data Package farS-SX FieldInvestigative Report (FIR)[DRAFT]) 3Taken from Freeman's e-mail to George Last, dated 12(27(01 (tinetesla doc and HStexl .doc). Table 11. Approximation for the distribution function for soil type H1cs"(Hanford coarse sand based on Khaleel and Freeman (1995) soil category S (sand) As modified by Beta Distribution Truncation Limits Transformed (normal distribution) Raw Number Hcs Standard Upper Lower Standard Of Lower Upper A B Deviation Limit Mean Limit Deviation Transforml Mean High Low Parameter samples 1.000 0.022 NO 0077 0.353 0.651 0.197 s82 1 000 0.225 NO 0.041 0.031 0.370 0 000 R82 1.000 0.111 1.2795 13.8715 NO 0.069 0.569 0.084 0000 S,82 0.995 0001 1.052 -2838 LN -0149 -6.119 0.059 0.133 0.861 82 0.002 (1/cm) 1.000 0134 NO 2.020 0.680 5000 1.266 82 n 0.970 0004 1.741 -6125 LN -2.847 -10.771 2 188E-03 1 197B-02 81 210GB-OS5 5 800E-02 K, (cm/s) Longitudinal Dispersivityi UN NA 0.203 0.223 1.83E-01 NA () 4.56 31 90 2.55 82 000 % Grasel Bulk Density' 369 1.51 2.02 1.66 0.10 NO-

Dens ity

3

3

NO __________________ I ( tNO =Normal (no transtormation required); LN= Lognormal, LR = Log ratio SIN= Hyperbolic arcoise, UN uniform, C0 = Constant, BE=Beta of the HanfordAX Task Farm] 'Takes from Ho, et. al., 1999 [Stochastic Parameter Deveiopment for PORFLOW Simalations 2Takee tramKhaleel, et. at. 2000 (Modeling DataPackage for S-SXField Investigation Report(FIR)[DRAFT]) (g/CM

3Taken from Freeman's e-mail to George Last, dated 12/27/01 (tinetecl adoc and HStesl .doc). Table 12 Approximation for the distribution function for soil type "Hcs BIC' (Hanford coarse sand - BC crib and trench area) based on Khalee and Freeman (1995) soil Beta Distribution Truncation Limits Transformed (normal distribution) Raw Number Hcs BIC Standard Upper Lower Standard Of Upper B Lower A Mean Deviation Limit Lim it Transformt Deviation High Mean Low sam ples Parameter 0.968 0.016 NO 0.052 0357 0.453 0.245 s46 0.984 0.007 NO 0.026 0.011 0.045 46 0.000 0.009 0.954 5.1305 64.6175 NO 0.031 0.074 0.000 0.129 46 S, 0.016 0.999 0.800 -4343 -2632 LN -0.149 0.072 0146 05B61 46 0.013 (1/cm) 0111 1.000 NO 0581 4170 2.047 1.337 46 n 0023 0971 -5.235 1 173 -3010 -7,569 I.18E-02 LIN 5.32E-03 5.16E-04 4 93E-02 46 K, (cm~s) Longitudinal Dispersivityi UN NA 0.203 0.223 1.836-01 inNA

Bulk

ensity m)37

1.51

1.92

1.67

0.10

NO-

-

-

3

Density -(NO= Normal (no transforaton reqoired); LN=Lognormal, LR =Log ratio,SIN=Hyperbolic arcsine, UIN=Usiformn, CO=Constant. 86E Beta Simulations of the HanfordAXTank Farm] 'Takes fmomHo, et. al., 1999 [Stochastic Parameter Development for PORFLOhV 2Taken from Khaleel, et. al. 2000 (Modeling Data Package for S-SXFieldInvestigation Report (FIR) [DRAFT]) 3Taken from Freeman's e-mail to George Last dated 12127/01(finetesla doc and HStexl .doc).

BA4

-

-

-

Table 13. Approximation for the distribution function for soil type "Hics 2W" (Hanfrd coarse sand -200 West Area) based on Khaleel and Freeman (1995) soil category S Beta Distribution Truncation Limits Transformed (normal distribution) Raw Number Hcs 2W Standard Lower Upper Standr Of Lower Upper B A Mean Deviation Limit Limit Mean Deviation Transformt High Low sam ples Parameter 0 900 0098 NO 0085 0,318 0427 0208 s7 0936 0048 NO 0016 0026 0050 0000 7 R 0025 0.8543 3.4657 41 3731 NO 0.077 0,039 0117 7 0.000 S, 1(1 /cm) 7 0007 0,131 0,041 0042 -2.034 LN -4.978 -3,183 0.970 0.032 0,882 7 7

n

K. (cm/s)

1,311 1.80E-04

2,096 5,80E-02

1.759 1 09E-03

0301 2 16E-02

NO0 LN

-2,847

-6822

-8623

0.068 0.184

2.002

0,868 0.976

Longitudinal Dispersivityl

3

7

1 83E-01 0.000

5

1490

NA

()

% Gravel BukDensity' 1

0.223 15.000

1 860

NA

0,203 2.143

5.669

1.650

0143

UN

-

-

-

-

______

_______

NO-

-

-

-

-

-

Dens ity (9/cm) tND =

_____

NO______

I________I___________

Normal (no transtormation reqairedl: LN= Lognormal, LR= Logratio,SN= Hyperbolic arcsine:UN uniform, CO = Constant, BE= Beta 1Takes fromHo, et. al 1999[Stochastic Parameter Development for PORFLOW Simulations of the Hanferd AXTask Farm) 2Takes tram Khaleel, et. al. 2000 (Modeling Data Package forS-OXFieldInvestigatien Repott (FIR) [DRAFT) 3Taken from Freeman's e-mail to George Last, dated 12(27(01 (fineteoladoc and HSteol .doc).

Table 14. Approximation to- the distribution function for soil type "Hcs Z" (Hanfrd coarse sand - 200-ZP-1) based on Khaleel and Fireeman (1995) soil category S (sand). Beta Distribution Truncation Limits Transformed (normal distribution) Raw Number Hcs Z Standard Lower Upper Standard Of Upper B Lower A Deviation Mean Limit Limit Deviation Transformt Mean High Low sam ples Parameter 0.886 0157 NO 0.083 0292 0.392 0.208 s5 0.903 0.065 NO 0.014 0.021 0.040 0.000 5 R 0,054 0.824 2.3367 31.3462 NO 0.043 0.069 0.110 0.000 5 S, 0.914 0.162 0.496 -2.710 -2.034 -3.199 LIN 0.037 0.067 0.131 5 0041 (1/cm) 0.880 0.116 NO 0319 2067 1.692 1.311 5 n 0940 0.1 86 2.361 -6.512 LN -2.847 -8623 2 55E-02 1 49E-03 5 80E-02 5 1.80E-04 K, )cm/s) Longitudinal Dispersivityl UN NA 0.203 0.223 1 83E-01 NA (in) ______ 0 0 0 0 5 %/.Gravel T-kDensity' 3 (2cm

Denslty

3

1.49

1.65

1.56

0.08

NO-

-

-

-

-

-

3

__________0___ NO required); LN= Lognormal, LR = Logratio,SIN= Hyperbolic arosine:UN = Uniform,CO= Constant, BE =Beta of the Hanford AXTask Farm) Simulations 1Taken trin Ho, nt. al.. 1999 [Stochastic Parameter Development for PORFLOW 2Taken from Khaleel, et. al, 2000 (Modeling DataPackage for S-OXField Investigation Report(FIR) [DRAFT]) 3Taken from Freeman's e-mail to George Last, dated 12127/01 )finetexla doc and HStexl.doc).

(9,M)( tNO = Normal(no transformation

Table 15 Approximation for the distribution function for soil type "Has" Hanford ravelly sanit based on Khaleel and Freeman (1995) soil category GS. Beta Distribution Truncation Limits Transformed (normal distribution) Raw Number Hgs Standard Lower Upper Standard Of Lower Upper B A Deviation Mean Limit Limit Deviation Transformt Mean High Low samples Parameter 0.995 0164 NO 0.071 0.250 0.436 0180 s17 1.000 0.258 NO 0.055 0.046 0.248 0.01 17 F, 0.134 1.000 6.8814 1.3622 NO 0.122 0.165 0.569 0.030 17 03 1 000 0.330 -4.313 1.033 -5.655 -2.411 0023 LN 0.013 0090 0.004 17 (1/1cm) 0.999 0197 INO 0681 2.111 4148 1.529 17 n 1 0 26261 -7657 -2408 -13.122 LR 2 16E-02 900OE-02 4,73E-04 17 2.006-06 K, (cm/n) Longitudinal Disperoivity' UIN NA 0.088 0.134 4.680-02 NA (m)____ _______ NO _________________ 9.65 40.00 25.78 10 17 % Gravel NO0.16 1 92 2.16 15, 168 Bulk Density tND = Normal (no transformation reqaired); LN Logeormal, LR =Log ratio,SIN= Hyperbolic arcoine, UN =Uniformi, COD Constant, BE Beta 1Taken from Ho, at. al ,.1999 (Stochastic Parameter Deveiopment for PORFLOWSimulations of the HanfordAXTank Farm] 2Taken tromKhaleel, et. al. 2000 (Modeling Data Package for S-OXField Investigation Report(FIR) [DRAFT)) Sameas SG1.

B.5

Table 16. Approximation for the distribution function for soil type "Hgs 2W" (Ha rd aravelfr sand - 200 West Area) based on Khaleet and Freeiman1995 soil categor Hgs-2W Number Raw Transformed (normal distribution) Beta Distribution Truncation Limits of Standard Upper Lower Standard Parameter samples Low High Mean Deviation Transform Limit Limit Mean Deviation A B Lower Upper -s2 0.208 0.091 0.337 0.273 NO 0.240 0.760 -R2 0.010 0.049 0.030 0.028 NO 0.240 0.760 S, 2 0.030 0.237 0.133 0.147 BE 0.5829 3.7866 0.103 0,049 7(1/cm) 2 0.004 0.016 0.008 0.008 LN -4.160 -5.521 -4.841 0.962 0.317 0.826 n 2 2.023 2423 2.223 0.283 NO 0.240 0.7601 K. (cm/s) . 2 5.43E-05 1,02E-03 2.35E-04 6.83E-04 LR -6.888 -9.821 -8.354 2.074 0 1 Longitudinal Dispersivity' () NA 4,68E-02 0.134 0088 NA UN% Gravel 2 17.00 31 00 24.00 9.90 NO ________________ Bulk Density 2 1.73 1.89 1.81 0.11 NO tNO = Normal(so transftormatien required); LN=Lognormal; LR = Log ratie,SN = Hyperbolic arcsise; UN = Usiferm.,CO = Censtant, BE =Beta ITakes tmomHa,et. al., 1999 [Stochastic Parameter Developmnst tar PORFLOiS Simalatiens at the Hanterd AX Task Farm] 2Takes tram Khateel,et. al. 2000 (Modeling DataPackage for S-SXField Investigatian Report(FIR) [DRAFT]).Same as 601. Tabl

17 Apoimation tor the distribution function for soit type "Hip"(Hanford sandy ravel) based on Khaleel and Freeman (1995) soil categor SGI (sandy gravel with Hg Number Raw Transformed (normal distribution) Beta Distribution Truncation Limits of Standard Upper Lower Standard Parameter sam ples, Low Mean High Deviation Transformt Limit Limit Mean Deviation A B Lower Upper s29 0.072 0.307 0.047 NO 0.167 0.022 0.999 r'29 0.000 0.062 0.023 0.014 NO 0.046 0.997 5, 29 0.000 0.387 0.143 0.084 NO 2.3024 13.8393 0.046 0.998 -(1 /cm) 29 0.002 0.919 0.08 0.190 LN -0.084 -6.075 -4.024 1.481 0.083 0.996 n 29 1.347 2.947 1.727 0.360 INO 0.146 1.000 K. (cm/s) 28 1 90E-07 3,70E-02 3,56E-04 8.72E-03 LN -3.297 -16.476 -7,941 3.228 0.010 0.925 Longitudinal Dispersivity' INA UIN 0,178 0.09 NA 0.027 (in) % Gravet 29 22 80 51.42 12.8 NO _______________ 2 Bulk Density 26 1.6 2.3 1.91 0.21 NOtND Normal(so trasftormatian required); LN =Lognormal; LR = Log ratia;SN = Hyperbolic arcsirre;UN =Usitarm, CO = Constant, BE =Beta Takes from Ho, et. al., 1999 [Stochastic Parameter Development tar PORFLOW Simalations of the Hanford AX Task Farm]. Sameas SSG Takes tram Khaleel, et. at. 2000 (Modeling DataPackage tar S-SXField Investigation Report (FIR)(DRAFT). Same as SC-i. 9 95

Table 18. Approximation tor the distribution function for soil type "Hg_2W' (Hanr sandy gr vl -200 West Area) based on Khaleel and Feman (1 ) soil catgory SG1I Hg_2W Number Raw Transformed (normal distribution) Beta Distribution Truncation Limits of Standard Lower Upper Standard Parameter samples High Low Mean Deviation Transforint Limit Limit Mean Deviation A B Lower Upper 12 0.072 0.217 0.154 0.040 NO 0.020 0.940 -R12 0.000 0.062 0.027 0.017 NO 0.054 0.980 s' 12 0. 000 0.387 0.172 0.106 BE 2.0011 9.6331 0 0.087 - (1/cm) 12 0.002 0.276 0.016 0.077 [N -1.288 -6.075 -4.106 1.318 0.068 0.984 n 12 1.347 1.745 2.269 0.324 INO 0109 0.848 K, (cm/s( 12 3.30E-06 3.70E-02 1.48E-03 1.21E-02 LN -3.297 -12.622 2.829 -6.515 0015 & 0.8721 Longitudinal Dispersivity (in) NA 0.027 0178 0.09 INA UN% Gravel . 12 39.000 80.000 54.358 12380 NO ________________ _______ Bulk Density2 9 1.630 2300 1.891 0.225 NOtNC = Normal (no transformation reqaired); LN= Lognormal; LR = Log ratio;SIN=Hyperbolic arcoise; UN = Uniform, CC = Constant, BE=Beta Taken from Ha, et. al., 1999 [Stochastic Parameter Development for PORFLCSISimalatioss at the Hanford AXTask Farm. Sameas SSG Taken tram Khaleel, St. al. 2900 (Modeling DataPackage tar S-SXField Investigation Report(FIR)[DRAFT)).Same as SG-1.

B.6

Table 19 Approximation for the distribution function for soil type "Hg U" (Hanfor sandy grave I- 200-UP-i) based on Khaleel and Freeman (1995) soil category SG11(sandh Beta Distribution Truncation Limits Transformed (normal distribution) Raw Hg U Number Standard Lower Upper Standard Of Lower Upper A B Deviation Limit Mean Limit Deviation Transforml Mean High Low Parameter samples 0.875 049 NO 0039 0194 0150 3 0124 0136 0.805 NO 0029 0.001 0 028 0 030 n3 0 0087 12,0545 46.9891 BE 0.204 0.052 0239 0.144 S,3 0.875 0253 -4,473 0.918 -3417 -5,083 0.015 LN 0.011 0.006 0.033 3 (1/cm) 0876 0.277 NO 1,845 0.312 2.205 3 1.8660 n 0.128 07741 -8151 3940 LN -5.187 -12.622 2 924E-03 5.590E-03 2.884E-04 3 3 300E-06 K. (cml/s) Longitudinal Dispersivity' UN NA 0.09 0 178 0.027 IA (m) ______ _______ 11 99 NO _______________ 43.3 65 57.10 % Gravel 3 2.09 0.26 NO1.8 2.3 Bulk Density3 tNO = Normal(no transformation required): LN= Lognormal, LR = Lagratio, SN = Hyperbolic arcsine, UN =Uviform, CDO Constant, BE =Beta 1Taken from Ho, et al., 1989[Stochastic Parameter Developmnent for PDRFLDOkSimulations otthe Hanford AXTank Farm). Same as SSG 2Taken from Khaleel, et. al 2000 (Modeling Data Package for S-OXFieldInvestigation Report(FIR) [DRAFT]).Same as SD-i. Table 20. Approximation for the distribution function for soil type "Hg Z" (H-anfor sandy rave ]- 200-ZP-1) based on Khaleel and Freeman (1995) soil categor SGI (sandy Beta Distribution Truncation LimitsI Transformed (normal distribution) Raw Number Hg Z Standard Lower Upper Standard of Lower Upper A B Deviation Mean Limit Limit Transformi~ Deviation High Mean Low samples Parameter 0922 0.025 NO 0.043 0.156 0,217 0,072 s9 0964 0.090 NO 0.026 0&020 0062 9 0000 0.970 7,0918 0.089 1.3637 0.120 NO 0.387 0.161 0.000 s'9 0.075 0 968 1,453 -6075 -3983 LN -1.288 0.019 0.088 0.002 0276 9 (1/cm) 0.141 0.950 NO 1.711 0,339 2.269 9 1 347 n 0.8411 0020 2.359 -5.651 -3.297 -10.473 1 37E-02 LN 3.51 E-03 3 70E-02 8 2.83E-05 K. (cm/s) Longitudinal Dispersivity' UN NA 0.09 0.178 0027 NA () ______ _______ NO ________________ 80 53.44 13.08 9 39 % Gravel 013 NO1.92 1.79 6 1.63 Bulk Density tNo = Nor-mal(no transtormation required), LN =Lognormal, LR = Logratio,SIN= Hyperbolic arcsine, UIN=Unitorm, CD = Constant, BE =Beta Taken from Ho, et al_ 1999[Stochastic Parameter Development for PORFLDW Simulations of the Hanford AX Tank Farm). Same as SOD Taken fromKhaleel. et. al. 2000 (Modeling Data Package for S-OXFieldInvestigation Report(FIR)[DRAFT]).Same as SG-1. (sandv ravel with SG2 Table 21. Approximation for the distribution function for soil type "Hirg" (Hanford River Gravel based on Khaleel and Freeman (1995) so ator Beta Distribution Truncation Limits Transformed [normal distribution) Raw Hrg Number Standard Upper Lower Standard of Upper B Lower Deviation A Limit Mean Limit Deviation Transformt Mean Low High samples Parameter 0048 0998 0.102 0.031 NO 0051 0191 140 0.987 0.045 NO 0 007 0 020 0.036 0.007 40 R 0 0.079 6.8937 28.1745 BE 0.066 0.359 0.197 0.082 40 5, 0.056 0.993 -4.907 0.763 -3.047 -6.119 LN 0.007 0.010 0.048 40 0.002 (1 /cm) 0.993 0026 0.197 INO 1.831 2.315 40 1.449 n 0037 09971 -6.532 2.062 -0 942 -10.205 6 26E-02 LN 3 90E-01 1 46E-03 40 3 70E-05 K, (cm/s) Longitudinal Dispersivity' UN INA 0.09 0 178 0.027 NA (in) 883 NO______ 85 6763 50 40 % Gravel NO1.97 016, 2.42 1.56 40, Bulk Density tND = Normal (no transtormation required), LN=Lognormal; LR = Logratio;OIN=Hyperbolic arcoine;UN =Uniform, CD = Constaet, BE =Beta PDRFLOW Simulations of the Hanford AX Tank Farm)].Same as 00G. Taken from Ho,et. aL 1999 [Stochastic ParameteroDevelopmnenttfor 2Taken from Khaleel, et. at. 2000 (Modeling Data Package for S-OXFieldInvestigation Report(FIR)[DRAFT]) Same as SD-i

B.7

Table 22. Approximation for the distribution function for soil type "PPitz"(Plio-Pleistocene-silt) based on Khateet and Freeman (1995) soil category SS (sand mixed with finer PPtz Number Raw Transformed (normal distribution) Beta Distribution Truncation Limits of Standard Upper Lower Standard Parameter samples Low High Mean Deviation Transformt Limit Limit Mean Deviation A B Lower Upper -S9 0.293 0.533 0A420 0.092 NO 0.082 0.891 9 9 9 9

0.010 0.020 0.001 1.522 4.12E-07

0.060 0.113 0.019 2.815 1.36E-01

0.034 0.080 0.006 2.101 5.57E-05

0.016 0.029 0.005 0.464 4 53E-02

9

0.0279 0

0.0341 4

0.031 0.44

NA 1 33

9.

1 55

1.8

1.68

0.08

-R9

S, -(1/cm) n K, (cm/s) Longitudinal Dioperoivityl (in) % Gravel Bulk 3 ensity' (C )

NA

NO NO LN NO LN

-3,988

-6.522

-5.200

0.702

-1.995

-14.702

-9,795

3.805

UN

-

-

-

6.8296

78.7949

-

-

-

-

-

-

0.073 0.020 0.030 0.106 0.099

0.946 0.870 0.958 0.938 0.9801

___

NO-

-

Density'

7

(g/cm)

7NO

_________________________

tNO = Normal (no transformation required); LN=Lognormal; LR =Lea ratio, SN =Hyperbolic arcoine;UN = Uniform, CO= Constant, BE =Beta 1Taken from Ho, et. al., 1989[Stochastic Parameter Development for PORFLOW Simulations ot the Hantord AXTank Farm]. 2Taken tromKhaleel, et. al. 2000 (Modeling Data Package for S-SXFieldInvestigation Report (FIR) [DRAFT)). 3Taken from Freeman's e-mail to George Last, dated 12/27/01 (fineteola doc and HStexl .doc). Table 23. Approximation for the distribution function for soil type "PPlz U"(Plio-Pleistocene-siht - 200-UP-i) based on Khaleel and Freeman (1995) soil category SS (sand PPlz U Number Raw Transformed (normal distribution) Beta Distribution Truncation Limits Of Standard Upper Standard Lower Parameter samples Low High Mean Deviation Transformt Limit Limit Mean Deviation A B Lower Upper 1,5 0,293 0.525 0.103 0.398 NO 0.152 0.890 -eR S, - (1/cm) n K. (cm/s) Longitudinal Diopersivity' ()

% Gravel Bulk Density' 3

(9/cm ) Density

5 5 5 5 5

0.020 0.068 0.001 1.522 4,12E-07

0.050 0.098 0.019 2.743 6874E-04

0.035 0.086 0.005 2.020 7.27E-06

0.0279 0

0.0341 04

0.031 00

NA 0.18

UN

5 5.

1.55

1.8

1.71

0.10,

NO

NA

0.013 0.013 0.007 0. 500 3.OOE-04

NO NO LN NO0 LN

37.9068 405.1820 -3.988

-6522

-5.355

0,923

-7302

-14.702

-11.831

2.818

-

-

__

-

-

-

-

-

-

-

-

0.122 0.097 0.103 0.159 0.154

0.884 0.825 0.931 0.926 0.946

____________

-

3

3

)(g/cm ) INO 0 ___________1____ fND = Normal Inn transformation reqaired); LN= Lognormal; LR = Log ratio;SN = Hyperbolic arxsine; UN =Uniformn, CD = Constant, BE =Beta 1Taken from Ho. et. al., 1989 [Stochastic Parameter Development for PDRFLDW Simeslations of the Hanford AXTank Farm]. 2Taken from Khaleel, et. al.2000 (Modeling Data Package tar S-OXFieldInvestigation Report (FIR) [DRAFT)). 3Taken from Freeman's e-mail to George Last, dated 12/27/01 (fineteoladoc and HStexl .doc). Table 24 Approximation fo- the distribution function for soil type "PPlz Z' (Plio- leistocene-silt - 200-ZP-1 I based on Khaleel and Freeman (1995) soil category SS (sand PIRlzZ Number Raw Transformed (normal distribution) Beta Distribution Truncation Limits Of Standard Upper Lower Standard Parameter samples High Low Mean Deviation Transformt Limit Limit Mean Deviation A Lower B Upper o4 0.373 0.533 0.081 0.448 NO 0177 0.855 -n 4 0.010 0.060 0.033 0.022 NO 0.155 0.893 5, 4 0.020 0.113 0.073 NO 0.044 2.4964 31.9252 0.114 0.821 7- (1/cm) 4 0.005 0.010 0.007 LN 0.002 -4.605 -5.279 0.295 -5.007 0.179 0.913 n 4 1.702 2.815 2.203 0.485 NO 0.906 0.141 K. cm/o) 1 4 6 70E-05 7.11 E-04 1.36E-01 6 79E-02 LN -1.995 -9.611 -7.249 3.532 0.252 0.9321 Longitudinal Dioperoivity (m) NA 00279 0.0341 0.031 NA UN% Gravel 4 0 4 1 _____________ 2 Bulk Density' A 33

1.49

1.66

1.58

0.091

NO-

-

Density' tND = Normal (no transformation required); LN=Lognormal; LR = Log ratio;SN =Hyperbolic arosine:UN Uniform, CD = Constant, BE =Beta Taken tram Ho, et. al., 1998 [Stochastic Parameter Development for PORFLDW Simulations of the Hanford AXTank Farm). Taken trom Khaleel, et. al. 2000 (Modeling Data Package for S-SXFieldInvestigation Report (FIR) [DRAFT) 3Taken from Freeman's e-mail to George Last, dated 12/27/01 (finetenl a doc and HStexl~doc),

B.8

-

-

-

Table 25. Approximation for the distribution function for soil type "PPIc" (Plio-Pleistocene-carbonate) based on Khaleel and Freeman (1995) soil category SS (sand mixed PPlC Number Raw Transformed (normal distribution) Beta Distribution Truncation Limits Of Standard Upper Lower Standard Parameter Low High samples Mean Deviation Transformt Limit Limit Mean Deviation A B Lower Upper S16 0.193 0.631 0.3D6 0.111 NO 0.155 0.998 16 0.019 0.241 0.072 NO 0.057 0.175 0999 S,16 0.097 0.445 0.214 0.096 NO 36651 13.4934 0,113 0.992 - (1/cm) 16 0.003 0.073 0.011 0.017 LIN -2.620 -5.843 -4.525 0.847 0.988 0.060 n 16 1.262 1.727 2.537 0.332 INO0 0.081 0.993 K, (cm/s) 16 2.60E-07 6.80E-02 1,73E-02 5.00E-04 LN -2.688 -15.163 -7.600 3.280 0011 0.9331 Longitudinal Dispersivity' INA UN 0031 0.0279 0.0341 NA () % Gravel 15 0 59 16.73 19.21 NO Bulk Density' 3 lg/cm ) 16l 1.48 2.13 1.71 0.181 NO-

Densty

3

T

3 (g/cm

)

NO

_____________________

_

tNO = Nvrmal (no transformation required), LN= Lognormal;LR = Legratio, SIN= Hyperbolic arcsise; UIN=Usiterm, CO = Constant, BE Beta 1Taken from He, et. at., 1889[Stechastic Parameter Development fer PORFLOV Simulations ef the Hanford AXTank Farm)]. 2Taken frem Khaleel, et. al. 2000 (Modeling Data Package for S-SXFieldInvestigation Report (FIR) [DRAFT]). 3Taken from Freeman's e-mail to George Last, dated 12/27101(finetex adoc, and HStexl.doc). Table 26. Approximation for the distribution function for soil type "PPIc Z" (Plio-Pleistocene-carbonate - 200-ZP-1) based on Khaleet and Freeman (1995) soil category SS PPtc Z Number Raw Transformed (normal distribution) Beta Distribution Truncation Limits Of Standard Lower Standard Upper Parameter Low High samples Deviation Transformt Mean Limit Limit Mean Deviation A B Lower Upper 15 0.193 0.631 0.312 NO 0.112 0.146 0.998 1

eR

15

S,15 71(1/cm) n K, (cm/s) Longitudinal Dispersivityl (in) % Gravel BukDensity' cm141

15 15 15

0.019 0.097 0.003 1.262 000000026

14

0.0279 0.00

0.0341 59.00

0.031 1507

NA 18.79

UIN NO

1.48

1.94

1.68

0.16

NO-

NA

0.241 0.075 0.057 0.220 0.445 0.096 0.073 0.011 0.01 2.537 0.343 1.734 0.068 0.00057392 0.01771766

NO NO LN NO LN

3.8823

13.7626

-2.620

-5,843

-4.518

0.876

-2.688

-15.163

-7.463

3.348

-

-

-

-

-

-

-

-

-

-

-

0.164 0.100 0.065 0.084 0.011

0.998 0.990 0.985 0.990 0.9231

________________

3

Density 3 )g/cm ) INO __________________ tNO = Normal (no transformation required), LN=Lognormal, LR Logratio,SN =Hyperbolic arcsine; UN =Uniform. CO=Constant 88E Beta 1Taken from He, et. al., 1999 [Stochastic Parameter Development for PORFLOW Simulations of the HanfordAX Took Farm]. 2Taken from Khaleel, 0t. 01.2000 (Modeling Data Package for S-SXField Investigation Report(FIR)[DRAFT]). 3Taken

from Freeman's e-mail to George Last, dated 12/27/01 (finetecl a doc and HStexl .doc).

Table 27. Approximation for the distribution function for soil type "Rg (Ringold sandv raeol) based on Khaleel and Freeman (1995) s Rg Raw Transformed (normal distribution) Number Of Standard Upper Lower Standard Parameter samples Low High Mean Deviation Transformt Limit Limit Mean Deviation 18 0.056 0.433 0.178 0.139 NO o1 18 0.000 0.780 0.063 0.180 NO S, 18 0.000 1.952 0.230 0.437 NO - (1/cm) 18 0.003 0.059 0.008 0.014 LN -2.827 -5.952 -4.853 0.893 n 18 1.297 0.231 2.357 1.697 NO K cm/o) 18 6.20E-06 1.30E-01 4.13E-04 3.04E-02 LN 1-2.040 -11.991 -7.791 2.572 Longitudinal Dispersivityl NA UN 0.09 0.027 0,178 NA (in) % Gravel 18 0 82 46.082 30.71 INOI Bulk Density 181 2.17 1 63 1.90 0.1 NOtNO = Normal (no transformation required), LN=Lognormal; LR = Logratio;SN =Hyperbolic arcsine; UN =Uniform, CO =Constant, BE Beta Taken fromHo, af. aW., 1999 [Stochastic Parameter Development for PORFLOW Simulations of the Hanford AX Tank Farm)].Same as SSG. Takes from Khaleel, et. al. 2000 (Modeling Data Package for S-SXFieldInvestigation Report(FIR) [DRAFT]).Same as SO-i.

B.9

lctgr G sandy gravel with Beta Distribution Truncation Limits

A

B

-Lower'- Upper 0.189 0.967

2.1112

14.3331

-

-

-

-

-

-

-

-

-

0.363 0.299 0.109 0.042 0051

1.000 1.000 0.988 0.998 0.987

Table 28 Approximation for the distribution function tor soil type "Ro 2W' (Ring Id sandy gravel -200 West Area) based on Khaleel and Freeman (1995) soil category SG2 Beta Distribution Truncation Limits Transformed (normal distribution) R WRaw Number Standard Lower Upper Standard Of Upper B Lower Deviation A Mean Limit Limit Mean Deviation Transformt High Low samles Parameter 0.852 0051 NO 013 030 043 0.08 s8 0993 0318 0,27 NO013 078 0 00 B 0 0079 1,7377 152226 BE 033 066 1 95 000 S,8 0,956 0083 0.879 -5.547 -4329 -2 827 0.02 LN 001 0.00 0.06 8 (1/cm) 0063 0.978 0 INO 175 030 2.36 1.30 8 n 0.155 0 957 2564 -9155 LN 1 -4.744 -11.761 302E-03 8 70E-03 1 D6E-04 8 7 80E-06 K, (cm/s) Longitudinal Dispri NA UN 0.09 0,178 0,027 NA ______ _______ 28.788 NO 70 22,175 8 0 % GAraviel NO1.838 0.167, 2118 1 81 1.630 B6ulkDensity tiN= Normal (so transformation required), LN=Lognormnal LR = Lagratia, SN =Hyperbolic arcsine; UN =Unitarm. CO = Constant, BE Beta 'Takes tram Ha, et. al., 198 [Stachastic Parameter Develapment tarPOIFOV Simalations ofthe Hanfvrd AXTask Farm). Same as SSG. 2 Taken tram Khaieel, et. al. 2009 (Modeling Data Package tarS-SXFieldInvestigatian Report (FIR) [DRAFT)) Sameas SG-i. Tabl29Apoimation for the distribution function for soil type "R _U' Ringo'l sdygra eI - 200-UP-if based on Khal eel and Freeman 1995) soil caegory SG2 (sandy Beta Distribution Truncation Limits Transformed (normal distribution) R URaw Number Standard Lower Upper Standard of Upper B Lower A Deviation Limit Mean Limit Mean Deviation Transformt High Low samples Parameter 0.821 030 NO 0125 0.318 0433 0.083 s7 0.988 0316 NO 0.282 0.144 0780 0.009 7 R 0 0,079 3.2853 241993 BE 0,381 0.695 1 952 0,060 s'7 0098 0.942 0,949 -5547 -4.320 -2.827 0.019 LN 0.013 0059 7 0.004 (1 /cm) 0070 0.967 NO0 0.319 1.768 1.297 2357 7 n 0.134 0.943 -9455 1,961 -6.348 -11,629 6 87E-04 LN 1 75E-03 7.83E-05 6 8 90E-06 K. (cm/a) Longitudinal Dispersivity' UN NA 0.09 0 178 0.027 . NA () 2578 NO 7000 1649 7 0 % Gravel 0.17, NO1.82 1.63 212 7, Bulk Density tN0 = Narmal (no transtormation required), LN= Lognormal, LR = Logratio,SN = Hyperbalic arcsine:UN =Uniform-, CO = Canstant, BE=Beta Taken tram Ha, et al._ 198 [Stochastic Parameter Development tarPORFLOW Simulations of the Hanford AXTank Far) Sameas SSG. Takes tram KhaleeI, et. al. 2000 (Modeling Data Package far S-SXField Investigative Report(FlI [DRAT) Same as SO-i.

B. 10

Appendix C Resolution of Discrepancies in the System Assessment Capability Vadose Zone Model for the BC Cribs and Trenches

Appcndix C Resolution of Discrepancies in thc System Assessment Capability Vadose Zone Model for the BC Cribs and Trenches W. E. Nichols The System Assessment Capability (SAC) Initial Assessment (Bryce et al. 2002) exhibited large, early releases of technetium-99. In all cases, the releases from the vadose zone to groundwater were nearly instant, following disposal to ground by only a year or two. To date, no groundwater monitoring data show evidence of any technetium-99 plume from the area of these sites consistent with such large releases. Because of the large predicted impact of technetium-99 from the BC cribs and trenches and inconsistency between predictions and groundwater monitoring data, resolution of the vadose zone model at these sites is required.

C.1 Approach The SAC vadose zone modeling uses a one-dimensional approach for computational speed. It is recognized that the multidimensional aspects of the vadose zone are highly important, but multidimensional modeling of the hundreds of waste disposal sites addressed in the SAC in a stochastic framework is computationally untenable. For vadose zone sites with liquid discharges, this is compensated by applying a Ks-dependent wetted area adjustment, wherein the area of the vadose zone area represented in the onedimensional model is scaled so that a unit gradient is attained in the layer with the lowest saturated hydraulic conductivity for the period with the highest liquid discharge rate. However, for the BC cribs and trenches, the Ks-depended wetted area adjustment method does not yield an area larger than the site area, so the SAC model defaults to using the Waste Information Data System (WIDS) area. This is equivalent to declaring there is no lateral movement of liquid associated with the liquid discharges at these sites. I propose that lateral spreading would still occur for the short-duration (less than one year) discharges that occurred at the BC cribs and trenches, and that two-dimensional modeling of each crib and trench for median input values can be used to quantify the extent of lateral spreading. Lateral spreading of fluid will tend to delay arrival of technetium-99 at the aquifer. If enough delay occurs, then the disposal inventory could still be consistent with the groundwater monitoring data that does not indicate a substantial technetium-99 plume in the vicinity of the BC cribs and trenches before calendar year 2000.

C. 1

C.2

Multidimensional Modeling of BC Trenches

The BC trenches and their respective areas and discharge volumes are listed in Table C. 1. The BC trenches are long relative to their width and were, therefore, idealized as a two-dimensional feature symmetric about the length axis of the trench. An idealized two-dimensional model was constructed that assumes the trench is infinite in length, and that lateral spreading is strictly perpendicular to the trench length axis. The SAC one-dimensional model for each BC trench with a substantial inventory of technetium-99 (trenches below 216-13-34 in Table C.1I did not have a large disposal of technetium-99) was expanded into a two-dimensional axial-symmetric model (half the trench represented, with results scalable to represent the whole trench). The vertical resolution (580 0.1 5-meter grid cells) was retained, and the x-axis was resolve into 96, 0.1 5-meter grid cells. This yielded a model grid of 55,680 grid nodes. The liquid and analyte discharges were converted to density-type sources and assigned to the topmost nodes in the grid index range from I to 10 (inner 1.5 meters), representing half the source term (again, consistent with the axial-symmetric treatment). Hanford soils are anisotropic, considered about 10 times more conductive in the horizontal dimension than in the vertical. To consider this feature, each trench was modeled twice, once with isotropic properties and once with 10:1 anisotropy in saturated hydraulic conductivity. Table C.1. BC Trenches (data from Maxfield 1979) WIDS Identification 216-13-20 216-13-21 216-13-22 216-13-23 216-13-24 216-13-25 216-B3-26 216-13-27 216-B-28 216-B-29 216-B3-30 216-13-31 216-B-32 216-B3-33 216-13-34 216-13-52 216-B-53A 216-13-5313 216-13-54 216-B3-58

WIDS

-

IArea (square meters) [Discharge Volume(ies 152.4x3 .0 = 457.2 152.4x3.0 = 457.2 152.4x3.0 =457.2 152.4x3.0 =457.2 152.4x3.0 =457.2 152.4x3.0 = 457.2 152.4x3.0 -457.2 152.4x3.0 =457.2 152.4x3.0 =457.2 152.4x3.0 = 457.2 152.4x3.0 = 457.2 152.4x3.0 = 457.2

4.68x 106 4.67x 10 6 4.74x 106 4.52x 10 6 4.7- 106 3.76- 106 5.88x 106 4.42x 106 5.05x 106 4.84x 10 6 4.78 x 10 6 4.74x 106

152.4x3.0 =457.2 152.4x3.0 =457.2 152.4x3.0 =457.2 176.8x3.0 = 530.4 18.3x3.0 =54.9 45.7x3.0 = 137.2 61.0x3.0 - 182.9 61.0x3.0 =182.9

4.77x 106 4.74x 106 4.87x 10 6 8.53x 106 5.49x 10-5 1.51x10 4 9.99X 10 5 4.13x10>5

Waste Information Data System

C.2

Once the release histories for the multidimensional model runs were available, the one-dimensional model was rerun with several AreaX (area scaling parameter) values. By trial-and-error, an AreaX scaling factor that would cause the one-dimensional model to produce releases similar to the twodimensional model (with explicit treatment of lateral flow) was determined. For all BC trenches, the value AreaX = 3.0 provided the best match for isotropic conductivity and AreaX = 6.5 provided the best match for anisotropic (10: 1 ratio) conductivity. Figures C. I through C.15 provide the modeling results for the BC trenches with substantial technetium-99 inventory (216-B-20 through 216-B-34, inclusive). Each figure depicts the release from the VADER vadose zone release model (i.e., the "input signal"), the release from the various Subsurface Transport Over Multiple Phases (STOMP) one-dimensional models (with variable AreaX factor values), and from the STOMP two-dimensional models (with isotropic and anisotropic conductivity). BC Trench 216-B-20

25

2

Cumulative Mass Released to Vadose Zone VAE

20

-SAC

Cumulative Mass Released to Groundwater

Co

a,

15-

C:

of

-

STOMP One-Dimensional Model AreaX = 1.0

4)

-

- - -

.>~-

CZ8o

E

=

6.5

STOMP Two-Dimensional Cartesian Model Length = 502.2 ft Trench Width = 10Oft 96 horizontal nodes, Ax = 0.5 ft Isotropic Conductivity Anisotropic Conductivity (10: 1)

10 -Trench

(D

AreaX = 3.0

AreaX

>-

cc

Rev. 0

5 -

02000

2200

2600 2400 Calendar Year

2800

3000

Figure C.1. Vadose Zone Cumulative Release to Groundwater Modeled for Trench 216-B-20

C.3

30 BC Trench 216-B-21

~25 'a

2

Cumulative Mass Released to Vadose Zone VAE

20

-SAC

Rev. 0

Cumulative Mass Released to Groundwater

Mn a) 73

15 -TM

OeDmensional Model = 1.0 AreaX = 3.0 AreaX =6.5

-AreaX

a)>1-

STOMP Two-Dimensional Cartesian Model Length = 502.2 ft Trench Width = l0oft 96 horizontal nodes, Ax = 0.5 ft Isotropic Conductivity Anisotropic Conductivity (10:1)

5->

10 -Trench

C: (D

.> in

E

5

0

0ii

i

2000

2200

ii

iiiiTl

2400 2600 Calendar Year

i

1

hl

2800

it

3000

Figure C.2. Vadose Zone Cumulative Release to Groundwater Modeled for Trench 216-B-21 BC Trench 216-B-22

~25c:

Cumulative Mass Released to Vadose Zone VAE

20

2

SAC Rev. 0 Cumulative Mass Released to Groundwater

in

a,

15-

a)

STOMP One-Dimensional Model -AreaX = 1.0 .

a)--Aea

AreaX = 6.5

>1

a)

S 10-

~Trench

-

a)

STOMP Two-Dimensional Cartesian Model Trench Length = 502.2 ft Width = 10 ft 96 horizontal nodes, Ax = 0.5 ft -Isotropic Conductivity Anisotropic Conductivity (10:1)

in

5 0

2000

2200

2600 2400 Calendar Year

2800

3000

Figure C.3. Vadose Zone Cumulative Release to Groundwater Modeled for Trench 216-B-22 CA4

30BC Trench 216-B-23

~25 Cumulative Mass Released to Vadose Zone 2

20 -VADER SAC Rev. 0

0-

Cumulative Mass Released to Groundwater 15

Z3

STOMP One-Dimensional Model -AreaX

- ---

a) C:

10 -Trench

=

1.0

AreaX = 3.0 AreaX =6.5

STOMP Two-Dimensional Cartesian Model Length = 502.2 ft = 10 Oft Trench W~idlh 96 horizontal nodes, Ax = 0.5 ft Isotropic Conductivity -Anisotropic Conductivity (10: 1)

D (D .>

5-3

2000

2200

2400

2600

2800

3000

Calendar Year

Figure CA4 Vadose Zone Cumulative Release to Groundwater Modeled for Trench 216-B-23 BC Trench 216-B-24

~.25-

2

Cumulative Mass Released to Vadose Zone VAE

20

CDDE -SAC

Rev. 0

W,

Cumulative Mass Released to Groundwater S 15-

STOMP One-Dimensional Model = 1.0e -AreaX AreaX = 3.0 AreaX =6.5

a) >1-

STOMP Two-Dimensional Cartesian Model Trench Length = 502.2 I't Trench Width = 1Oft 96 horizontal nodes, Ax = 0.5 ft Isotropic Conductivity Anisotropic Conductivity (10: 1)

5)

S 10-

5,

76C)

5

02000

2200

2400

2600

2800

3000

Calendar Year

Figure C.5. Vadose Zone Cumulative Release to Groundwater Modeled for Trench 216-B-24 C.5

BC Trench 216-B-25

~25 Cumulative Mass Released to Vadose Zone

2

20-

AE o

Rev. 0

_______________________________SAC

Cumulative Mass Released to Groundwater

5)

One-Dimensional Model AreaX =1.0

33 15 -STOMP x~ ---

a)

S 10-

Two-Dimensional Cartesian Model Trench Length = 502.2 ft Trench Width = 10ft 96 horizontal nodes, As = 0.5 ft Isotropic Conductivity Conductivity (10:1) -Anisotropic

-STOMP

(D

.>

E

AreaX = 3.0

AreaX = 6.5

>-

5

2000

2600 2400 Calendar Year

2200

2800

3000

Figure CA6 Vadose Zone Cumulative Release to Groundwater Modeled for Trench 216-B-25 BC Trench 216-B-26

~25-

VADER SAC Rev. 0

-

(D

Cumulative Mass Released to Vadose Zone

2(D

Cumulative Mass Released to Groundwater

~

STOMP One-Dimensional Model

15

-AreaX

>-

a)

STOMP Two-Dimensional Cartesian Model Trench Length = 502.2 ft = 10 f Trench WNidth 96 horizontal nodes, As = 0.5 ft Isotropic Conductivity Anisotropic Conductivity (10: 1)

10 -

a, 76

E

= 1.0

AreaX = 3.0 AreaX =6.5

(D

5

2000

2200

2600 2400 Calendar Year

2800

3000

Figure C.7. Vadose Zone Cumulative Release to Groundwater Modeled for Trench 216-B-26 C.6

BC Trench 216-B-27

O25-

Cumulative Mass Released to Vadose Zone

2D 20ADER

SAC Rev. 0

.2

Cumulative Mass Released to Groundwater 15-

STOMP One-Dimensional Model -AreaX = .0 AreaX =3.0

a)

AreaX =6.5

--

STOMP Two-Dimensional Cartesian Model Trench Length =502.2 ft Trench Width = 10Oft 96 horizontal nodes, Ax = 0.5 ft Isotropic Conductivity -Anisotropic Conductivity (10: 1)

a,

10-

Z)

-

a,

E

5 00

2000

2800

2400 2600 Calendar Year

2200

3000

Figure C.8. Vadose Zone Cumulative Release to Groundwater Modeled for Trench 216-B-27 30 -

~25

-

BC Trench 216-B-28

_

_

_

_

_

_

_

_

_

----

2

20-

Cumulative Mass Released to Vadose Zone

VADER

SAC Rev. 0

CD

Cumulative Mass Released to Groundwater

W a)

15-STOMP

One-Dimensional Model = 1.0 = 3.0 AreaX = 6.5

-AreaX

a,

a)

--

STOMP Two-Dimensional Cartesian Model Length = 502.2 ft Trench Wdth = 10 It 96 horizontal nodes, Ax = 0.5 ft -Isotropic Conductivity Anisotropic Conductivity (10:1)

S 10 -Trench a) C

E

-AreaX --

5 0

2000

2200

2600 2400 Calendar Year

2800

3000

Figure CA9 Vadose Zone Cumulative Release to Groundwater Modeled for Trench 216-B-28 C.7

30-

..

I.. 1.. 1 iip...1

.

...

l

p~

I

l

l

....I p

... I

.,l

BC Trench 216-B-29

~25 Cumulative Mass Released to Vadose Zone

2

oD

20

VADER

SAC Rev. 0

.2-

Cumulative Mass Released to Groundwater

a3 15-

STOMP One-Dimensional Model -AreaX = 1.0 -AreaX =3.0 -- AreaX =6.5

a,

STOMP Two-Dimensional Cartesian Model Length = 502.2 ft Trench Wdth = 10 ft 96 horizontal nodes, Ax = 0.5 ft -Isotropic Conductivity -Anisotropic Conductivity (10:1)

a,

C:

10 -Trench

a,)

:3 5

(02000

2200

2400 2600 Calendar Year

2800

3000

Figure C.10. Vadose Zone Cumulative Release to Groundwater Modeled for Trench 216-11-29 30 BC Trench 216-B-30

O25-

2

Cumulative Mass Released to Vadose Zone VAE

20

SAC Rev, 0 Cumulative Mass Released to Groundwater

cc a,

15

STOMP One-Dimensional Model -AreaX

a,

----

STOMP Two-Dimensional Cartesian Model Trench Length =502.2 ft Trench Width = 10 Oft 96 horizontal nodes, Ax = 0.5 It Isotropic Conductivity -Anisotropic Conductivity (10: 1)

a,

S 10

=1.0

AreaX =3.0 AreaX = 6.5

a,

.>~-

0

2000

2200

2400 2600 Calendar Year

2800

3000

Figure CA11. Vadose Zone Cumulative Release to Groundwater Modeled for Trench 216-B-30 C.8

30-

BC Trench 216-B-31

~25 Cumulative Mass Released to Vadose Zone

20VDR

2

-SAC

Cumulative Mass Released to Groundwater

in (D

15-

Z

Rev. 0

STOMP One-Dimensional Model =1.0

-AreaX -

-

>-

S 10 -Trench

STOMP Two-Dimensional Cartesian Model Length = 502.2 ft Wdth = 1Oft 96 horizontal nodes, As= 0.5 ft Conductivity -Isotropic Conductivity (10:=1) -Anisotropic

~Trench

D a)

AreaX = 3.0 AreaX = 6.5

in

E

2000

2400 2600 Calendar Year

2200

2800

3000

Figure C.12. Vadose Zone Cumulative Release to Groundwater Modeled for Trench 216-B-31 BC Trench 216-B-32

~25C:

Cumulative Mass Released to Vadose Zone

2 20 0

VADER

SAC Rev. 0

0

Cumulative Mass Released to Groundwater

MiL Z

15-STOMP

One-Dimensional Model -AreaX

--

Si

>-

a) 2:

10 -Trench

:D

-

= 1.0

AreaX =3.0 AreaX = 6.5

STOMP Two-Dimensional Cartesian Model Length = 502.2 ft Trench W~idth = 10 ft 96 horizontal nodes, Ax = 0.5 ft -Isotropic Conductivity Anisotropic Conductivity (10:1)

-

SD in

E 0-

2000

2200

2400 2600 Calendar Year

2800

3000

Figure C.13. Vadose Zone Cumulative Release to Groundwater Modeled for Trench 216-B-32 C.9

30-

. .I. ...

.1

..

-

BC Trench 216-B-33

~25 _0 Cumulative Mass Released to Vadose Zone VAE

20

2

SAC Rev. 0

.2-

Cumulative Mass Released to Groundwater

CU

15-

(D

CU

a)

STOMP One-Dimensional Model AreaX = 1.0 AreaX =3.0 -AreaX =6.5

Of (U >1-

STOMP Two-Dimensional Cartesian Model Length =502.2 ft Trench W~dth= l Oft 96 horizontal nodes, Ax = 0.5 ft Isotropic Conductivity Conductivity (10: 1) -Anisotropic

S 10 -Trench t)

=3 5

2200

2000

2600 2400 Calendar Year

2800

3000

Figure C.14. Vadose Zone Cumulative Release to Groundwater Modeled for Trench 216-B-33 BC Trench 216-B-34

~25 Cumulative Mass Released to Vadose Zone

VAE

20

2

SAC Rev. 0

.2

Cumulative Mass Released to Groundwater

CU t,

15-

STOMP One-Dimensional Model = 1.0 -AreaX --

a,

>-

-

AreaX = 3.0

AreaX = 6.5

ca

a)

STOMP Two-Dimensional Cartesian Model Length = 502.2 ft Trench W~dth= 1lOft 96 horizontal nodes, Ax = 0.5 ft Isotropic Conductivity Anisotropic Conductivity (10: 1) -

S 10 -Trench

(D

.>~-

15

:3

5

2000

2200

2600 2400 Calendar Year

2800

3000

Figure C.15. Vadose Zone Cumulative Release to Groundwater Modeled for Trench 216-B-34 C. 10

C.3

Multidimensional Modeling of BC Cribs

The BC cribs and their respective areas and discharge volumes are listed in Table C.2. The BC cribs are essentially square and were idealized as a two-dimensional circular feature symmetric about the diameter. An idealized two-dimensional cylindrical model was constructed that assumes lateral spreading will be strictly radial outward. The SAC one-dimensional model for each BC crib was expanded into a two-dimensional axialsymmetric cylindrical model (a 180-degree arc, or half the crib, represented with results scalable to represent the whole crib). The vertical resolution (580, 0.15-meter-grid cells) was retained, and the x-axis was resolved several ways. Ideally, the model should be resolved to the same degree horizontally (0. 15 meter) as vertical to avoid numerical dispersion, but for the high volume (relative to disposal area) the number of nodes necessary to accomplish this leads to a model too large to solve practically with available computer systems. Instead, several successively finer resolutions were simulated for the first crib (216-B-14) to demonstrate convergence in the release history with finer resolution. It is notable that lower resolution leads to greater lateral flow (due to numerical dispersion in the horizontal dimension), which in turn leads to lower release predictions. This indicates the need to use full resolution in twodimensional models if release is not to be systematically under-predicted in SAC analyses. Liquid and analyte discharges were converted to density-type sources and assigned to the topmost nodes in the grid index range covering the inner 13.7 meters (the radius of a circle with the same area as a typical BC crib), representing half the source term (again, consistent with the axial-symmetric treatment). Note that the area given in Table C.2 does not match the area declared in WIDS and the SAC database; often the WIDS area is larger than the true footprint. Hanford soil is anisotropic, considered about 10 timnes more conductive in the horizontal dimension than in the vertical. To consider this feature, each crib was modeled twice, once with isotropic properties and once with 10: 1 anisotropy in saturated hydraulic conductivity. Once the release histories for the multidimensional model runs were available, the one-dimensional model was rerun with several AreaX (area scaling parameter) values. By trial-and-error, an AreaX scaling factor that would cause the one-dimnensional model to produce releases similar to the Table C.2. BC Cribs (data from Maxfield 1979) WIDS Identification 216-13-14 216-B3-I5 216-13-16

WIDS

I

Area (square feet) 40x40 =1600 40x40 =1600 40x50 =2000

I

Discharge Volume (liters)_

216-13-17

40x40 =1600

8.71 X106 6.32x 106 5.6 x106 3.41 X106

216-B-18 216-13-19

40x4 = 1600 40x40 =1600

8.52x 106 6.4x106

=

Waste Informnation Data System

C.11I

two-dimensional model (with explicit treatment of lateral flow) was determined. For all BC cribs, the value AreaX = 1.5 provided the best match for isotropic conductivity and AreaX =3.0 provided the best match for anisotropic (10: 1 ratio) conductivity. Figures C. 16 through C.24 shows simulated vadose zone release to groundwater results for BC crib 216-13-14 for various horizontal resolutions of the two-dimensional cylindrical model for the early years 1944 to 2000 for both isotropic and anisotropic (10: 1) conductivity. Note that increasing release with increasing resolution, showing the need for a highly resolved two-dimensional model to preclude substantially under predicting release. The highest model resolution simulated was 580 vertical (0. 15 meter) by 192 horizontal (0.43 meter) nodes, for a total model grid of 111,360 nodes. Ideally, the horizontal should be resolved to 0.1 5-meter nodes also, but this would yield a model domain of more than 300,000 nodes, too large to simulate with available equipment in a reasonable time. As it was, the final resolution (111,360 nodes) could only be simulated on the analysis stations (paper.pnl.gov or plastic.pnl.gov) and not on any RANSAC compute node due to the memory demands of such a large domain. Hence, the release for the highest resolution should be seen as close, but not quite as high as the release that would be predicted for the fully resolved (0. 1 5-meter grid) model if it were run. Also displayed in Figure C.16 are the release results for the one-dimensional model for AreaX = 1.0 (SAC Rev. 0 default) and for AreaX = 1.5, which approximates the isotropic release history, and AreaX3.0, which approximates the anisotropic (10: 1) release history. The one-dimensional model is shown to slightly under predict annual releases from the crib in early years (up to about 1980) and slightly over predict annual releases thereafter. BC Crib 216-B-14 Cumulative Mass Released to Vadose Zone VADER -SAC Rev. 0

40

o

Cumulative Mass Released to Groundwater

2

STOMP 1D SAC Rev. 0, AreaX =1.0 -Rev. 0, AreaX = 1.5 Rev. 0, AreaX = 3.0

30

0

o

~0di

- -

- -

a) a)-

_0

20-

Osfroic a)

--

a)

STOMP 2D Cylindrical Domain Radius =270 ft

>, 10

Anisotropic Conductivity (10:1) -6radial nodes, Ar = 45 ft 12 radial nodes, Ar 22.5 ft 24 radial nodes, Ar = 11.25 ft 48 radial nodes, Ar = 5.625 ft 96 radial nodes, Ar = 2.8125 ft radial nodes, Ar = 1.40625 ft

E C.)-

~192

0 1940

Figure C.16.

1950

STOMP 2D Cylindrical Domain Radius =270 ft Source Radius =45 ft Conductivity !. - b radial nodes, Ar =45 f 12 radial nodes, Ar = 22.5 ft 24 radial nodes, Ar = 11.25 ft 48 radial nodes, Ar = 5.625 ft 96 radial nodes, Ar = 2.8125 It 192 radial nodes. Ar = 1.40625 It

1960

1970 1980 Calendar Year

1990

2000

Vadose Zone Cumulative Release to Groundwater Modeled for Crib 216-B-14 (1944 to 2000) C. 12

40

Cumulative Mass Released to Vadose Zone

____

-SAC

Rev. 0

CU Cumulative Mass Released to Groundwater

2

30

STOMP 1D SAC Rev. 0, AreaX 1.0 Rev. 0, AreaX = 1.5 Rev. 0, AreaX = 3.0

-

0D-o 2

STOMP 2D Cylindrical Radius =270 ft Source Radius =45 ft Conductivity -6radial nodesAr = 45 ft 12 radial nodes, Ar = 22.5 ft 24 radial nodes, Ar = 11.25 ft 8rda r=565f oes r=565f 8rda oes 96 radial nodes, Ar = 2.8125 It 192 radial nodes, Ar = 1.40625 ft

m

aDomain

CD a)

osoroic

20

>1-

cc

U

a)

V

STOMP 2D Cylindrical Radius =270 ft Source Radius 45 ft Anisotropic Conductivity (10:1) 6 radial nodes, Ar = 45 ft 12 radial nodes, Ar = 22.5 ft 24 radial nodes, Ar = 11.25 ft 48 radial nodes, Ar = 5.625 ft 96 radial nodes, Ar = 2.8125 ft 192 radial nodes, Ar = 1.40625 ft

> -Domain

10 E C.)

:3~-

2000

2600 2400 Calendar Year

2200

2800

3000

Figure C.17. Vadose Zone Cumulative Release to Groundwater Modeled for Crib 216-B-14

80

T9oc enatonCG 00001

7

E-06

0

13- 50 0

0

10 25

50

75

R-Direction Node Positions, m

Figure C.18.

Tc-99 Concentration (Ci/M 3 ) of Two-Dimensional Axial-Symmetric (192 radial nodes) Isotropic Model of Crib 216-B-14 (center of crib is the left-hand side and the water table is the bottom of the domain)

C. 13

80

Tc99 Concentrabon. Ci S0 000

1E-05

E 70

IE-06 E 09

Z.; .60 0 IL 50 0 0

Z 40 C 0 ;:30 0 0

75

50

25

R-Direction Node Positions, m

Figure C.19.

Tc-99 Concentration (Ci/M 3 ) of Two-Dimensional Axial-Symmetric (192 radial nodes) Anisotropic (10:1 conductivity ratio) Model of Crib 216-B-14 (center of crib is the left-hand side and the water table is the bottom of the domain).

BC Crib 216-B-1i5 Cumulative Mass Released to Vadose Zone

40 o

VADER -SAC

Rev. 0

79

2

(0 o

30

3:

Cumulative Mass Released to Groundwater

=3

STOMP 10D SAC Rev. 0, AreaX =1.0 0, AreaX = .5 -Rev. 0, AreaX = 3.0

-Rev.

STOMP 2D Cylindrical Domain Radius = 270 ft Source Radius = 45 ft

a) a) -0 (D

20-

122grdial nodes, Ar = 45 ft 12 radial nodes, Ar = 22.5 ft 24 radial nodes, Ar = 11.25 ft 48 radial nodes, Ar = 5.625 ft 96 radial nodes, Ar = 2.8125 ft

a, a,

-o C.

.

..

.

.

..

.

.

.

..

=3~-

Q

2000

2200

192 radial nodes, Ar = 1.40625 it

STOMP 20 Cylindrical Domain Radius = 270 ft Source Radius = 45 ft Anisotropic Conductivity (10:1) 6 radial nodes, Ar = 45 ft 12 radial nodes, Ar = 22.5 ft 24 radial nodes, Ar = 11.25 ft -48 radial nodes, Ar = 5.625 ft radial nodes, Ar = 2.8125 ft -96 192 radial nodes Ar = 1.40625 ft

>'

E

.

2400 2600 Calendar Year

2800

3000

Figure C.20. Vadose Zone Cumulative Release to Groundwater Modeled for Crib 216-B-15

C. 14

BC Crib 216-B-1 6 40

Cumulative Mass Released to Vadose Zone

Cs

VADER Rev. 0

30 -SAC

2 (0 CU

0

Cumulative Mass Released to Groundwater

(D(V-

STOMP One-Dimensional Model AreaX = 1.0 AreaX = 1.5 AreaX =3.0

...............................

o20-

STOMP Two-Dimensional Cylindrical Model Domain Radius =270 ft Source Radius 45 ft Isotropic Conductivity

L) a) c

STOMP 2D Cylindrical Domain Radius =270 ft Radius =45 ft -Isotropic Conductivity Anisotropic Conductivity (10: 1)

(D

~

10Source

E~

2000

2200

2600 2400 Calendar Year

2800

3000

Figure C.21. Vadose Zone Cumulative Release to Groundwater Modeled for Crib 216-B-16 BC Crib 216-B-1 7 40

2

Cumulative Mass Released to Vadose Zone

30

CD o

VADER SAC Rev. 0

Cs

Cumulative Mass Released to Groundwater

x

STOMP One-Dimensional Model AreaX =1.0 AreaX = 1.25 --- AreaX = 2.5

(D

-0

20

a)

M

STOMP Two-Dimensional Cylindrical Model Domain Radius 270 ft _----------Source Radius =45 ft ----...... Isotropic Conductivity Conductivity (10: 1) -Anisotropic

>

10

2000

2200

2400 2600 Calendar Year

2800

3000

Figure C.22. Vadose Zone Cumulative Release to Groundwater Modeled for Crib 216-13-17 C. 15

BC Crib 216-B-18 40-

Cumulative Mass Released to Vadose Zone VADER SAC Rev. 0

0 .2-

Cumulative Mass Released to Groundwater

(D

STOMP One-Dimensional Model AreaX = 1.0

Of v 20

-

-AreaX =1.5 ---- AreaX = 3.0

STOMP Two-Dimensional Cylindrical Model Domain Radius =270 ft Radius =45 ft Conductivity Conductivity (10: 1) -Anisotropic

V0 aSource

>-Isotropic

~

10

E

0

.. 2000

2200

2600 2400 Calendar Year

2800

3000

Figure C.23. Vadose Zone Cumulative Release to Groundwater Modeled for Crib 216-B-18 BC Crib 216-B-19 40-

2

:3

30-

0DVAE

Cumulative Mass Released to Vadose Zone

-

o

-

Cumulative Mass Released to Groundwater

en

STOMP One-Dimensional Model AreaX= 1.0 AreaX = 1.5 AreaX=3.0 -----------------------------

ly 20-

_0 (D

STOMP Two-Dimensional Cylindrical Model Domain Radius =270 It Source Radius =45 ft Conductivity Anisotropic Conductivity (10: 1)

>-Isotropic

10

-

2000

SAC Rev. 0

2200

2600 2400 Calendar Year

2800

3000

Figure C.24. Vadose Zone Cumulative Release to Groundwater Modeled for Crib 216-B-19 C. 16

CA4

Computer Simulation Time

An important implication of two-dimensional simulation in the SAC context is the simulation time required to solve for vadose zone transport of analytes. As a stochastic simulator, SAC will invoke a STOMP model of a vadose zone site for a number of cases equal to the number of realizations times the number of analytes. Ideally, locations with liquid discharges (such as the BC cribs and trenches) would be modeled as two-dimensional features. However, if the computer time required to performn the number of two-dimensional cases required is too great, a problem of feasibility arises. The times required to solve the various one- and two-dimensional simulations of the crib 216-B3- 14 provides a basis for consideration. Table C.3 provides the timing results. Note all time are for simulations on a Pentium 4 processor, except the highest resolution grid which had to be run on a SAC analysis node due to the high RAM requirements of this resolution grid. The highest resolution twodimensional model, with 111,360 nodes, was too large to run on any RANSAC compute node as it required more RAM than any of the compute nodes are equipped with. The high memory demand of this size model has important implications for inclusion in SAC of a two-dimensional model of the BC cribs. Moreover, this model still wasn't sufficiently resolved (that would require a model with more than 300,000 nodes).

C.5

Summary

Based on the simulation times in Table C.3 and the simulation results shown earlier, several points can be made with respect to SAC Rev. I implementation: 1. If a two-dimensional capability is desired, the SPLIB solver is substantially faster for grid domains over 20,000 nodes and should be made standard for STOMP in SAC. Table C.3.

Computer Simulation Time for Various One- and Two-Dimensional STOMP Models of 216-B-14 Crib (Pentium 4, 2.2-Gllz processor running under Linux) Solution Time(s) Number Of Banded Marix

Number of Nodes in Direction

1Total

___ _ I

zNodes

Solveri

SPLIB Solver 129

1 6 12

1 1 1

580

580

137

580

3,480

960

955

580

6,960

2,081

2,055

24

1

48 96

1 1

580 580

13,920 27,840

4,910 21,835

4,501 9,522

192

1

580

55,680

580

111,360

20,588 55,748 (a) 1_______

(a) Simulated on Pentium 111, 1.3-GHz processor instead because RAM was insufficient on any RANSAC compute node for this large of grid domain.

C. 17

2. If a two-dimensional model were to be used directly in SAC, the time required to solve the vadose zone segment of SAC would increase starkly. For crib 216-13-14, more than 15 hours were required at a grid resolution that was nearly sufficient. In a production run with 25 realizations and 10 analytes, this would imply 3,750 hours of computer time for just one crib, or 22,500 hours for the six BC cribs. Spread over 132 compute nodes (assuming these were equipped with enough RAM to carry the problemn), it would take 170 hours, or about one week, just to solve for the six BC cribs. Worse, these timne estimates were based on runs on 2.2-GI-z processors; 128 of the 132 compute nodes on RANSAC are 1.O-GHz processors (about three times slower). And this only for the BC cribs; there are many other liquid-discharge sites that make good candidates for two-dimensional simulation in SAC. It is clear that direct two-dimensional treatment of liquid discharge waste sites remains impractical, requiring at least RAM upgrades to the entire SAC cluster and unacceptably long simulation times to solve. 3. However, the results also demonstrate that the one-dimensional model can be made to approximate the direct two-dimensional model by selecting an appropriate value of the vadose zone wetted area based on detailed two-dimensional modeling. It is recommended that for the BC cribs and trenches the one-dimensional model continue to be used in SAC Rev. 1, but with vadose zone wetted area scaling factors derived fromn the simulations performed in this report.

C.6

Projected Impact on Initial Assessment

To demonstrate the change from following these calibration factors, the total technetium-99 release fromn all BC cribs and trenches was simulated both using the SAC Rev. 0 approach (effectively AreaX = 1.0) and with the vadose zone wetted area scaling parameters derived in this study. The results are shown in Figure C.25. Note the difference predicted by year 2000; 449 curies released to the aquifer in the initial assessment model (one-dimnensional model, AreaX =1 .0) compared to only 18.2 curies released in the one-dimensional model with scaling factors drawn from the detailed two-dimensional models. Based on the more detailed modeling, the absence of a detected technetium plume in groundwater monitoring data for this area, the much lower release is considered much more realistic.

C.7

References

Bryce RW, CT Kincaid, PW Eslinger, and LE Morasch (eds.). 2002. An Initial Assessment of Hanford Inmpact Performed with the System Assessment Capability. PNNL-14027, Pacific Northwest National Laboratory, Richland, Washington. Maxfield HL. 1979. Handbook -200 Areas Waste Sites. RHO-CD-673, Volumes I and 11, Rockwell Hanford Company, Richland, Washington.

C. 18

500-

iiii11111..1111..11,11111,

111

-

99

Tc Total Release to Vadose Zone from BC Cribs and Trenches - .SAC

Rev. 0 (AreaX

j5

=

1.0)-

Modeling AreaX Factors---

-Two-Dimensional

400-

n: 30070(D

L)

D

a)

100

a

01940

1950

1960

1970

1980

1990

2000

Calendar Year

Figure C.25.

Total Annual Release from all BC Cribs and Trenches Simulated in SAC Rev. 0 Initial Assessment and with Vadose Zone Wetted Area Scaling Parameters Conditioned to Direct Two-Dimensional Simulations

C. 19

Appendix D Surface Barrier Degradation

Appendix D Surface Barrier Degradation G. W. Gee and A. L. Ward Surface barriers, consisting of vegetated soil and assorted sublayers, will be constructed and placed over as many as 200 waste sites at Hanford. These surface barriers, if effective, will isolate the general public from buried waste and limit surface erosion and minimize water and biotic intrusion into the waste. Over time, it is assumed that numerous forces, including wind, water, fire, drought, and seismic activity will act to degrade the barrier surface. This appendix describes key potential failure mechanisms and outlines several scenarios that could be used to simulate barrier degradation in long term assessments. The most probable failure mechanism is wind erosion resulting in sand dune formation, which can change surface texture and vegetation and result in increased recharge rates. In terms of recharge control, a surface barrier at Hanford may change from a very low recharge rate (<0.1I millimeter per year) to something more representative of a stabilized sand dune at the Hanford Site (e.g., 4 millimeters per year or greater).

D.1

Introduction

In the mid 1980s the U.S. Department of Energy initiated a Barrier Development Program at the Hanford Site (see Attachment 1). The purpose of the program was to develop a long-term barrier, capable of isolating waste for more than 1,000 years. The barrier development program included 12 elements designed to address all aspects of barrier design and construction: " " " " " *

biointrusion water intrusion Wind and water erosion physical stability material quality and quantity monitoring

*

modeling

* prototype design and construction * natural analogs

climate change 9 regulatory issues * technical exchange

*

Field tests were initiated to test selected aspects of the long-term barrier and culminated in the design and construction of a prototype surface barrier (PSB), placed over the B-57 crib in the 200 BP-1 Operable Unit, adjacent to the BY Tank Farm in the 200 East Area at the Hanford Site. Over 130 reports and papers have been published to date, documenting various aspects of the PSB, construction, and performance (see Attachment 1). Figure D.1 shows the general features of PSB designed for long-term (1,000 year) protection. Testing of PSB has successfully demonstrated that above-grade vegetated covers at Hanford act as a sponge, storing incident precipitation during wet (winter) periods and subsequently losing water by evapotranspiration (ET) during dry (summer) periods, thus minimizing water intrusion into underlying D. I

Precipitation

J

Multi-Layer ET Cover

TLs

Recharge Gain

silt loam soil

<0.5 mm/yr

Advantages: -long-term protection -no biointrusion -redundant controls Issues: -cost *sideslopes -lateral flow

(<0.5mm/yr?) *

Figure DA1.

water table

Hanford Prototype Surface Barrier (PSB) Designed for Long-Term (1,000 year) Protection of Hanford Waste Sites

waste. In contrast, the side slopes, built to engineering specifications (DOE 1994), are designed to stabilize the barrier against wind and water erosion. Because they are coarse and mostly barren they allow significant water to infiltrate into subsurface sediments surrounding the waste (Ward and Gee 1997; Gee et al. 2002; Wittreich et al. 2003). The results from the PSB studies indicate that the complete barrier system, soil cover and side slopes, must be understood to evaluate total barrier performance. In the final design of long-term barriers there may be tradeoffs between erosion control and water intrusion protection, as illustrated by the side slope drainage measurements which have shown that coarse side slopes, used for erosion protection, can drain up to 20% or more of the annual precipitation (Wittreich et al. 2003).

D.2

Alternative Designs

In addition to PSB (Figure D. 1), other barrier designs have been proposed for Hanford (DOE 1997). Only PSB has been tested in full-scale prototype. However, some alternative covers have been tested in small lysimeters (Fayer et al. 1999). These include the so-called modified RCRA C cover. The modified RCRA C cover incorporates the low permeability (asphalt layer) layer of PSB but does not use the biointrusion layer; thus, the total thickness is less than PSB and construction costs are correspondingly reduced. Monofill ET covers have also been proposed for use at Hanford. Figure D.2 shows the general features of a monofill ET cover, which consists simply of a soil layer placed above the waste and vegetated with native plants. Side slope issues that exist for all above-grade surface barriers will affect both the modified RCRA C and the monofill ET cover. An alternative cover that has not been considered yet but has great potential for Hanford is what can be called the Shallow Liner FT Cover (Figure D.3).

D.2

E T C over

Precipitation Input ET Loss

Advantages: -simple construction Issues: *sideslopes biointrusion -plant succession -climate change

Figure D.2.

(<3mmlyr?) water table

Simple Evapotranspiration (ET) Cover, with Silt Loam Soil (for optimal water storage) and Native Vegetation (shrub steppe) to Enhance Surface Water Loss

Shallow-Liner ET Cover Shallow iner--

Advantacies: -simple construction -no sideslopes -no biointrusion Issues: *longevity of liner (1000 yr?) water table

Figure D.3.

Shallow Liner Evapotranspiration (ET) Cover. Includes a low permeability (Geomembrane) below a silt loam surface to provide redundant drainage control, minimize biointrusion and eliminate side slopes.

D.3

This design eliminates side slopes and biointrusion and because these are two mechanisms that can aid to the degradation of surface covers, such design features should be seriously considered for placement at Hanford waste sites. No systematic study of all surface barrier degradation mechanisms has been made to date. For example, the impact of side slopes on net water infiltration into the waste has not been addressed in current designs of above grade surface barriers, nor previously factored into discussions of barrier degradation. The interaction of side slope recharge, erosion control, depositional processes and impacts from fire, disease, etc. have not been systematically incorporated into a final design. In the following sections we attempt to describe the most reasonable and expected degradation (or failure) mechanisms for surface barriers at Hanford, including effect of wind erosion, biointrusion protection, and the impact of side slopes on degradation on final barrier performance. We offer some alternative designs for improved side slope performance, and provide several timelines for expected barrier degradation including estimates of overall net infiltration or recharge associated with final barrier performance as a consequence of a specific design.

D.3

Barrier Degradation Assumptions

In recent numerical assessments, (such as the initial assessment performed with the System Assessment Capability (SAC) (Bryce et al. 2002) it was assumed that there were two kinds of barriers: 1) a long-term (1,000 year) barrier used primarily for tank farms and transuranic waste sites and 2) a 500-year barrier used for solid waste landfills and other low-level waste sites at Hanford. There have been no specific degradation mechanisms specified but for the initial assessment performed with SAC, the following assumptions were made about performance and recharge rates.

D.3.1

The 1,000-Year Barrier

This barrier was assumed to perform optimally (0. 1 millimeter per year) for 1,000 years. After 1,000 years, the barrier was assumed to degrade (by a combination of unspecified failure mechanisms) to a pre-operations recharge level specified by the soil type that existed prior to the waste-site construction. The degradation was assumed to take place in 5 equal steps of 200 years over the next 1,000 years. For example, if the pre-operations recharge level was 2 millimeters per year, the following scenario was assumed: * Year 0 to * Year 100 1 to " Year 1201 to " Year 1401 to * Year 1601 to " Year 1801 to

1000 1200 1400 1600 1800 2000 -

recharge recharge recharge recharge recharge recharge

= = = = = =

0.1 0.4 0.8 1.2 1.6 2.0

millimeter per year millimeter per year millimeter per year millimeters per year millimeters per year millimeters per year

DA4

D.3.2

The 500-Year Barrier

This barrier was assumed to perform optimally (0. 1 millimeter per year) for 500 years. After 500 years, the barr ier was assumed to degrade (by a combination of unspecified failure mechanisms) to a pre-operations recharge level specified by the soil type that existed prior to the waste-site construction. The degradation was assumed to take place in 5 equal steps of 100 years over the next 500 years. For example, if the pre-operations recharge level was 2 millimeters per year, the following scenario was assumed: " " " " " "

Year Year Year Year Year Year

0 to 501 to 601 to 701 to 801 to 901 to

500 600 700 800 900 1000

recharge = 0.1 millimeter per year recharge = 0.4 millimeter per year recharge = 0.8 millimeter per year recharge = 1.2 millimeters per year recharge = 1.6 millimeters per year - recharge = 2.0 millimeters per year

These degradation assumptions were made purely to simplify the modeling and do not represent any actual degradation responses. They are considered conservative assumptions, in that degradation processes are generally slow, though some catastrophic events such as floods, drought, and related climate change events can cause rapid alteration of the landscape. In fact, extreme dynamics are responsible for much of the geologic setting for Hanford (Baker et al. 1991; Bjomstad and Teel 1993; Gaylord and Stetler 1994; Peterson et al. 1993). Prediction of the exact timing of degradation is virtually impossible, so the stepwise degradation assumptions are as reasonable as any other alternatives. Other recent assessments (such as the ILAW performance assessment rreference]) have assumed that the barrier disappears at the end of its design life.

D.4

Potential Degradation Mechanisms

This section describes degradation mechanisms that could affect surface barriers placed over Hanford waste sites.

D.4.1 Wind Deposition The most likely mechanism for long-term degradation of a barrier at Hanford is wind induced sanddune formation (sand deposition). Studies by Gaylord et al. (1993); Gaylord and Stetler (1994) demonstrate that most of the surficial soil at Hanford is colian (wind blown) in nature, with about half of the Hanford Site exposed to or covered by stabilized or active dunes. Active and stabilized dunes have their highest densities in areas to the south and east of the 200 Areas, while some stabilized dunes are located in the 200 East Area. All soil in the 200 Areas is covered with a mantle of windblown sand material (Gaylord and Stetler 1994). For long-term considerations, all surface covers are assumed to be affected in some way by wind action. When vegetated, the soil surface is generally stabilized against wind erosion. However, there are local changes to microrelief because of wind action that can affect water storage and other surface properties. Coppice dunes are found extensively at the Hanford Site.

D.5

These miniature dunes consist of fine sands deposited around shrubs, creating small mounds (hummocks) elevated 0.5 meter or more above surroundings. The intermound (or swale) is a depression that is often sparsely vegetated and has different water-storage capacity than that found on the hummock. At one coppice dune site near the Yakima Barricade, west of the 200 Areas at Hanford, Link et a]. (1994) found that water storage was strongly associated with vegetation patterns and that actual water storage was inversely correlated with vegetation, suggesting the greater the plant density the lower the available water in the soil profile, consistent with our ET cover concepts. An irrigation treatment demonstrated that all of the rainfall and irrigation water was consumed (transpired) by plants at this coppice dune site. Soil texture was coarser in the top 0.5 meter of the hummock than in the swale but vegetation density was greatest on the hummock. It is entirely possible that as coarser soils accumulate, that water storage capacities will actually decrease, with corresponding decreases in vegetation density and conversion from deep-rooted vegetation to shallow rooted vegetation. Coppice dunes are complex systems and illustrate the dynamic nature of the soil surface in the Hanford environment. It is most likely that changes similar to coppice dune features will develop on even the most stable cover under the present Hanford climatic regime. Initially, this change may not directly impact barrier drainage rates, but features like coppice dunes are a precursor to larger accumulation of sands over time and the subsequent change from shrub vegetation to sparse grasses as observed on a significant portion of the Hanford Site (Gaylord and Stetler 1994). Based on these observations, it is likely that engineered surface barriers will change from wellcontoured surfaces to surfaces with significant microrelief (hummocks and swales) and finally to more extensive stabilized dunes in the next 1,000 years or more. A possible scenario for wind action on the surface barrier is as follows: 1. Year I (barrier placement) to year 500. Barrier performance as specified (<0.1I millimeter per year) 2. Year 501 to year 1000. Development of stabilized dunes - linearly degrades to 4 millimeters per year of average recharge. This rate is based on recharge estimates of stabilized dunes obtained from chloride mass balance data of Murphy et al. (1996). 3. Year 100 1 and beyond. Surface barrier is assumed to behave like a stabilized sand dune. (Recharge assumed to be 4 millimeters per year). It should be noted that the chloride mass balance method apparently predicts recharge reliably in the very low (<1 millimeter per year) range but there is less certainty when the recharge is above a few mm/yr (Prych 1995; Tyler et al. 1999), so a sand-dune recharge rate of 4 millimeters per year may not be conservative and likely will have to be updated in the future, as more reliable results are obtained.

D.4.2 Water Erosion Studies conducted at PSB have demonstrated that little if any runoff or surface erosion has occurred over the 9 years of monitoring of the surface barrier (Gee et al. 2002; Wittreich et al. 2003). The low grade on slopes for the soil cover plus the well-established vegetation has minimized any water erosion on PSB. There is no evidence that water erosion would cause any significant barrier degradation at the Hanford site. Runoff occurs primarily in winter or early spring when soils are frozen and when snowmelt occurs rapidly due to warmn (e.g., Chinook) winds (Skaggs and Walters 1981; Gee and Hillel 1988). For soil on gentle slopes with well established vegetation, runoff is accompanied by little or no sediment loss. D.6

The lack of evidence for water erosion allows us to assume that there will be no changes in recharge rate due to any plausible water erosion scenario.

D.4.3 Biotic Intrusion There is ample evidence that biotic (plant and animal) intrusion has occurred at waste sites at Hanford in the past (Dabrowski 1973; O'Farrell and Gilbert 1975, Landeen and Mitchell 1982; Marshall 1987). Deep-rooted tumbleweed (Salsoa kali) has a tap root that can penetrate to depths of 5 meters or more in the sandy soil and backfill sediment at Hanford. Dabrowski (1973) describes waste sites near the Columbia River in the 100 Areas where tumbleweeds intruded in to wastes containing cesium-I137 and strontium-90. Uptake of strontium-90 caused the plants to become radioactive. The radioactive tumbleweeds created problems, because as they aged, some were blown off the waste site, thus becoming an undesirable biotic vector. Ants and burrowing insects, small (pocket mice and gophers) and large mammals (badgers) also have been observed to intrude into waste and bring contaminants to the surface where they have been scattered to locations some distance from the waste sites (O'Farrell and Gilbert 1975; Cline et al. 1980; Landeen and Mitchell 1982, Kennedy et al. 1985). A waste site, called the BC cribs, located to the south of the 200 East Area, has documented widespread surface contamination, attributed to biotic intrusion. In the 1950s, a badger bole was found at one of the BC cribs, which contained near-surface contamination (strontium-90 and cesium-137). The badger likely foraged for mice in contaminated soil. Jackrabbits then used the burrow and became contaminated (O'Farrell and Gilbert 1975). Coyotes and raptors subsequently ate the jackrabbits and spread the contamination over a wide area (more than several hundred hectares). Similar situations have been observed at the Idaho National Laboratory, near Arco, Idaho (Arthur and Markum 1983; Arthur et al. 1987). While such intrusion is possible, particularly at waste sites with surface spills or with otherwise nearsurface contamination, a properly designed surface cover will limit biotic intrusion. Features to prevent biotic intrusion were incorporated into the design of the Hanford surface barrier. These features included a sublayer of coarse rock designed to discourage digging (see Cline and Rogers 1982) and an asphalt layer that is impervious to water, small mammals and burrowing insects (Myers and Duranceau 1993; Wing and Gee 1994). An asphalt layer is placed below the rock layer, providing a redundancy that limits not only biotic intrusion (including both plant root and animal intrusion into underlying wastes) but prevents water intrusion as well. For ET cover systems with no rock or asphalt sublayers, the possibility of biointrusion remains. However, in the final barrier design for all waste sites at Hanford, we assume that some kind of biotic intrusion protection will exist and that borrowing animals will be confined to the near surface (top meter of soil) and their presence does not create pathways for water intrusion. This assumption is supported by the work of Landeen (1994) who demonstrated that pocket mice burrows acted much like vent tubes, allowing for advective drying of the near surface soils thus reducing the actual water content in the profile during the summer months and subsequently increasing the actual storage capacity of the soil. Based on past biointrusion studies we conclude that biotic transport can be minimized with a properly designed surface barrier and that water intrusion will not be enhanced. The most probable scenario for biotic intrusion then is to assume that it is minimal and that water intrusion is not affected by biotic vectors, so the recharge impact is zero from biotic intrusion.

D.7

D.4.4 Fire, Plant Succession and Associated Wind Erosion A concern about relying on ET for water removal is the dynamic nature of the vegetation. At Hanford, a key component of any reliable surface barrier will be a vegetated surface. Periodic fires can remove the vegetation in dramatic and often catastrophic fashion. Wildfires have occurred periodically at Hanford. Two of them, one in 1984 and one in 2000, each burned over 64,749 hectares leaving large portions of the landscape temporarily barren (Link et al. 1990; Gee et al. 1992a). The 2000 fire occurred in late June, when understory vegetation (primarily cheatgrass) had senesced (died) and was tinder dry. The fire, started by an auto accident on Highway 24, quickly spread to the Hanford Site, jumping Highways 24 and 240 and burning most of Rattlesnake Mountain and part of Benton City, in addition to spreading onto and around the 200 Areas. The removal of almost all vegetation from the western perimeter of the 200 West Area on to the top of Rattlesnake Mountain left the land surface in that area vulnerable to wind erosion, which did occur. The surface soil in this area has a fine sand texture, which is highly susceptible to wind erosion. It was enough of a problem that tank farm operations were periodically curtailed because of blowing dust. Subsequently, a windbreak, consisting of a double row of 1,500 trees (Australian willow), was placed along the western boarder of the 200 West Area to protect buildings, vehicles, and personnel from sand blasting and dust inhalation. Irrigation of the windbreak was initiated in the summer of 2001 and is continuing because trees do not survive in the Hanford environment without supplemental irrigation (Gee et al. 2002). In addition to the tree placement and irrigation, other measures, including straw mulching were implemented to lessen the impact of bare surface exposures or wind erosion. By the spring of 2003, the surface has stabilized by natural revegetation, so that little erosion, if any, has occurred for the past two years. This is consistent with the observations made by Link et al. (1990), who demonstrated that after the 1984 fire that plants on the Fitzner/Eberhartdt Arid Land Ecology (ALE) Reserve recovered sufficiently to actively remove stored water from the soil profile in a fashion similar to pre-fire conditions. The effectiveness of the plant water uptake was such that after two years there were no marked differences between unburned and burned sites. The data of Link et al. (1990) clearly demonstrate that for silt loam soil, the effect of fire is temporary and recovery is rapid. For most, if not all of the Hanford Site, it would be expected that the no significant impact should occur, particularly when the soil is fine-textured with significantly large storage capacities. Wind erosion occurs from silt loam soil, only if it is very dry and highly disturbed. Vegetation tends to anchor the finer (silt oarns) soil so that is it far less susceptible to wind erosion than coarse soil (e.g., fine sands). Based on these observations, we conclude that fire may have a temporary impact on surface barr iers, but with fine soil (silt loam) dominating the surfaces, that recovery of vegetation is rapid and the impacts from fire can be considered negligible.

D.4.5

Drought and Plant Succession

Another concern with surface barriers is the potential for extended drought followed by elevated precipitation (wet climate) conditions. In such a scenario, the excess (or elevated) precipitation would either be incident on the soil surface and runoff or be infiltrated into the soil. For coarse soils the lack of vegetation would allow drainage while for fine soil drainage would be contained in the soil for subsequent use by plants (ET). Drought in the current shrub-steppe environment often leads to fire, so much of the

D.8

discussion on fire and plant succession hold for this case of drought. There are no data to show performance of a cover under an extreme drought or extended period (multiple years) of dryness. Clearly vegetation would be affected. While much of the shrub-steppe has been altered by fire, the most dramatic thing is the potential conversion of the shrub-steppe vegetation, where deep-rooted shrubs dominate the vegetation type, to cool-season, shallow-rooted grasses (e.g., bromus tectorum or cheatgrass), thus, reducing the water storage capacity of the soil by virtue of the change in both rooting depth and plant phenology (life cycle), such that less water can be lost from the soil by transpiration over time. The famous ecologist, Leopold (1966), described the process of converting the western U.S. native shrubsteppe vegetation to cheatgrass prairie through a succession of fires. Invasion of cheatgrass perpetuates itself. After senescence, cheatgrass stalks and heads acts like dry tinder. When a fire starts (via lightning strike or man) the fuel is the dead cheatgrass, which bums rapidly, destroying the shrubs. Regeneration of the shrubs requires a seed source and the seeds in turn must compete with cheatgrass for a limited water supply in fall and winter. The cheatgrass acts much like winter wheat, germinating in the fall, going dormant in winter, then sprouting in full vigor in early spring. It generally out-competes its rivals for water so that many shrub seedlings do not survive, and the cheatgrass becomes the dominant plant species in a fire-swept steppe country. The process repeats itself until the cheatgrass dominates the entire landscape. It is entirely possible that over time much of the Hanford Site landscape could become cheatgrass dominated. The impact on coarse soil sites would be dramatic since water storage will change and more drainage and recharge will result. Increased recharge has been observed at Hanford where the coarse soil shrub-steppe landscape has been converted from shrub-steppe to grassland (Prych 1995; Fayer and Walter 1995). A fire-affected site near the 300 Area, with a fine sand over coarse (Burbank loamy sand) soil, transitioned from shrub-steppe to grassland (bluegrass and cheatgrass). The estimated recharge rate was 25 millimeters per year, as obtained from neutron-probe monitoring (Fayer and Walter 1995) while at this same site (Prych 1995) used chlorine-36 analysis to estimate a recharge rate of about 5 millimeters per year. This compares to shrub-steppe recharge rate estimates that are generally much less than 1 millimeter per year (Prych 1995; Murphy et al. 1996). In contrast, where soil is fine textured (e.g., silt loams), there appears to be little impact on the recharge with this vegetation change, since the soil water storage is sufficient to contain the water, hold it near the surface long enough that both soil evaporation and plant transpiration act to remove it. Studies at the Field Lysimeter Test Facility near the Hanford Meteorological Station have demonstrated that 1-meter-thick silt loam soil, void of any vegetation, is entirely capable of losing all of the annual precipitation via evaporation. Data collected for over a period of 12 years (Fayer et al. 1999) indicated that there has been no drainage from bare, silt loam soil data, suggesting that fire and subsequent vegetation changes, will have little or no effect on the drainage from a silt-loam surface-barrier. Based on these observations we assume that fire will not adversely impact the barrier performance but may impact the surroundings by increasing the recharge in surrounding areas where there are coarse soils dominated by cheatgrass or similar shallow-rooted plants.

D.4.6

Other Mechanisms

Other mechanisms for barrier degradation include subsidence, human intrusion and climate change. These mechanisms were considered in the Hanford barrier development program.

D.9

D.4.6.1 Subsidence Subsidence or surface collapse is associated with consolidation of waste (e.g., collapse of waste containers, general settlement of surficial materials after backfilling operations or response to seismic events). While subsidence can affect the integrity of a capillary barrier and the impermeable asphalt by differential settlement, the assumption was made that stabilization of the waste with grout injection, dynamic compaction, or other means could minimize effects of consolidation at most waste sites. The PSB has been studied for nearly 10 years and tested for consolidation and surface stability. Civil surveys indicate that the surfaces have remained stable for the first decade after construction (Wittreich et al. 2003) with little indication of settlement even on the 2:1 rock side slopes. Based on these findings, it is assumed that stable surfaces can be achieved and that subsidence will not be a major degradation mechanism for most of the Hanford waste sites. Where there are buried objects such as empty metal tanks, wooden boxes, and building with large void spaces, special consideration will have to be given to address consolidation effects on barrier performance. In principle, technologies such as dynamic compaction and grout injection can be used to minimize subsidence effects. D.4.6.2 Inadvertent Human Intrusion Inadvertent human intrusion is a possible scenario but wamning markers identifying no-dig zones at the wastes sites have been proposed for the Hanford waste sites (Adams and Wing 1986) and if such markers were used it would lessen the chance for inadvertent intrusion. It could be envisioned that after loss of institutional control, that deliberate removal of an entire surface barrier is possible since the surface cover is always exposed and vulnerable. However, the likelihood of such a scenario of cover removal appears remote, particularly if the warning and marker systems are used. D.4.6.3 Climate Change Climate change, on the other hand, is entirely possible and was considered in the barrier development program. One scenario would be for Hanford to experience a wetter, cooler climate, which could increase the chance for water storage to be exceeded. Paleoclimate studies suggest that if the past were a indicator of the future that change to a wetter and cooler environment would produce at most a 30% increase in the precipitation over the long-term (Wing et al. 1995). In the design of PSB, a doubling of precipitation was assumed to be the upper limit of precipitation for 1,000-year performance (Myers and Duranceau 1994). Studies of PSB indicated that applications of 1,000-year-storm events and precipitation elevated to 3 times the annual average value caused less than 0.2 millimeter of drainage in 3 years of testing at rates of 480 millimeters per year or three times the annual average rate (Gee et al. 2002a; Wittreich et al. 2003). Based on these observations, we assume that the human intrusion and climate change scenarios will not significantly impact the recharge rates for surface barriers at Hanford.

D.5

Side Slope Impacts on Degradation

Side slopes can have a huge impact on surface barrier performance. As demonstrated by the Hanford surface barrier tests, sparsely covered gravel and rock side slopes, while effective in eliminating wind and water erosion, add drainage water to the areas surrounding the soil cover. Side slope drainage can be as much as 20% or more of the annual precipitation (Gee et al. 2002a; Wittreich et al. 2003). While D. 10

advective drying reduces the drainage rates, particularly on steep rock side slopes, they still contribute a large portion of the total recharge, particularly when the waste areas are small and the ratio of the side slope area to the total area is large. For sites with dimensions less than 100 meters on a side the side slope area can be 40% or more of the total area when the side slopes have 5:1 (horizontal: vertical) dimensions or less. The contribution of the total recharge then becomes dramatically weighed toward the recharge rate of the side slopes. For many of the proposed waste sites in the 200 Areas at Hanford, which have deep underlying water tables, the added water from the side slopes can percolate into the subsurface and carry contamninants to groundwater. Degradation of stabilized, armored side slopes is not expected under any of thle probable scenarios, except in the case of sand-dune formnation. Under such a scenario, the side slope drainage would be reduced to the drainage rate of the sand dune material and attendant vegetative cover. Improvements over present side slope design might include terracing and additions of fine materials trenched into the side slopes to improve water holding capacity and provide adequate rooting media for native plants. If such schemes were employed it is possible that recharge rates could be reduced to values comparable to the soil cover but such schemes have not yet been demnonstrated.

D.6

Timelines for Barrier Degradation

Timelines for drainage from 500-year and 1,000-year barriers are listed in Table D. I. The tables assume that sand dune form-ation is responsible for barrier degradation and increases the recharge over time. It is assumed that the dune develops sooner on the 500-year barrier but ends at the final recharge rate at the same time as the 1,000-year barrier. This assumption is tied solely to differences in climate effects that cause the sand dune formation (for the 500-year barrier scenario the sand dune forms sooner and expresses its full impact sooner than on the 1,000-year barrier). The final rate for both barriers in 2,000 years is assumed to be 4 millimeters per year, a rate observed by Murphy et al. (1996) on a stabilized sand dune at Hanford. This rate may not be conservative because it was estimated from chloride mass balance techniques, which become insensitive at rates much above a few millimeters per year (Tyler et al. 1999). Also, higher recharge rates have been observed on stabilized soil that are vegetated (Fayer and Walters 1995). Selected barrier performance is illustrated in Table D.2, where the final drainage rates for various covers are listed along with the probabilities of a number of degradation factors.

D.7

Summary and Conclusions

Wind and water erosion, biointrusion, fire, drought, subsidence, humnan intrusion, and climate change were considered as possible barrier degradation mechanisms. In addition, side slope water intrusion was considered in light of its potential effects on overall barrier performance. The most plausible degradation mechanism for the Hanford Site is wind erosion, causing sand dune formation. Timelines of degradation were developed which assumed that the final barrier will be covered with a dune that drains at the rate of 4 millimeters per year. It is possible that higher rates may develop on barriers covered with sand dunes but such rates have yet to be documented.

D.11I

Table D.1.

Drainage Rates for 500-Year and 1,000-Year Surface Barriers (assumes an initial recharge rate of 0.1 mm/yr and a final recharge rate of 4 mm/yr after 2000 years) Time

500-Year Barrier

1,000-Year Barrier

(yrs)

(mmlyr)

(mm/yr)

Present +r500 +600 ±700 +800 --900 +1l000 +1200 +1400 +1600 ±1800 ±2000

0.1 0.1 0.4 0.8 1.2 1.6 2.0 2.4 2.8 3.2 3.6

0.1 0.1 0.1 0.1 0.1 0.1 0.1 1.5 2.5 3.0 3.5

14.0

4.01

Table D.2. Degradation Factor Probabilities for Selected Landfill Covers at the Hanford Site

1Multilayer Factors Wind deposition Water erosion Biointrusion Human intrusion Subsidence Fire Drought Side slope impact Climate change Final Recharge (mm/yr) H = High. L = Low. M = Medium.

D.8

Hafr H L L L L L L H M! 4

Monofill Modified RCRA C H L L M L L L H M 4

ET H M H H M M M H H >4

]

Shallow Line ET H L L L L L L L M <4

References

Adams MR and NR Wing. 1986. Protective Barrierand Warning Marker System Development Plan. RHO-RE-OL-3 5P, Rockwell Hanford Operations, Richland, Washington. Arthur Wi III and OD Markhamn. 1983. "Small Mammal Soil Burrowing as a Radionuclide Transport Vector at a Radioactive Waste Disposal Area in Southeastern Idaho." J Environ. Qua!. 12:112-122. Arthur Wi 111, GD Markham, CR Groves, and BL1 Keller. 1987. "Radionuclide Export by Deer Mice at a Solid Radioactive Waste Disposal Area in Southeastern Idaho." Health Physics 52:45-53. D.12

Baker VR, BN Bjornstad, AJ Busacca, KR Fecht, EP Kiner, UL Moody, JG Rigby, DF Stradling, and AM Tallman. 1991. "Quaternary Geology of the Columbia Plateau." In R. B. Morrison (ed.) QuaternaryNonglacial Geology: Conterminous US.: The Geology of orth America. v. K-2. Geological Society of America, Boulder, Colorado. Bjomnstad BN and SS Teel. 1993. NaturalAnalog Study of Engineered Barriersat the HanfordSite. PNL-8840, Pacific Northwest Laboratory, Richland, Washington. Brunner DR and DJ Keller. 1972. Sanitary Landfill Design and Operation. SW-65ts, U.S. Environmental Protection Agency, Washington, D.C. Cline IF and VA Uresk. 1979. "Revegetation of Disturbed Grounds in the Semi-Arid Climate of Southcentral Washington." Health Physics 36:289-294. Cline JF, KA Gano, and LE Rogers. 1980. "Lose Rock as Biobarriers in Shallow Land Burial." Health Physics 39:497-504.

Dabrowski TE. 1973. Radioactive Tumbleweed in the 100 Areas. UNI-65, United Nuclear Industries, Inc., Richland, Washington. Fayer MJ and TB Walters. 1995. Estimated Recharge Rates at the Hanford Site. PNL-10285, Pacific Northwest National Laboratory, Richland, Washington. Fayer Mi, EM Murphy, JL Downs, FO Khan, CW Lindenmeier, and BN Bjornstad. 1999. Recharge Data Packagefor the Immobilized Low-A ctivity Waste 2001 Performance Assessment. PNNL-13033, Pacific Northwest National Laboratory, Richland, Washington. Gee GW, Mi Fayer, ML Rockhold, and MD Campbell. 1992. "Variations in Recharge at the Hanford Site." Northwest Sci. 66:23 7-250. Gee GW, AL Ward, BG Gilmore, SO Link, GW Dennis, and TK O'Neil. 1996. Hanford PrototypeBarrierStatus Report: FY.1996. PNNL-1 1367, Pacific Northwest National Laboratory, Richland, Washington. Gee GW, AL Ward, and CD Wittreich. 2002a. The Hanford Site 1000-Year Cap Design Test. PNNL 14143, Pacific Northwest National Laboratory, Richland, Washington. Gee GW, IS Carr, JO Goreham, and CE Strickland. 2002b. Water MonitoringReportfor the 200 W Area Shelter Belt, Hanford Site, Richland, Washington. PNNL- 14074, Pacific Northwest National Laboratory, Richland, Washington. Kennedy WE, Jr, LL Cadwell, and DH McKenzie. 1985. "Biotic Transport from a Low-Level Radioactive Waste Site." Health Physics 47:723-728. Landeen DS. 1994. The Influence of Small Mammal BurrowingActivities on Water Storage at the Hanford Site. WHC-EP-0730, Westinghouse Hanford Company, Richland, Washington. D.13

Landeen DS and RM Mitchell. 1982. Intrusion of Radioactive Waste Burial Sites by the Great Basin Pocket Mouse (Perognathus parvus). RHO-SA-2 11, Rockwell Hanford Company, Richland, Washington. Leopold A. 1966. A Sand County Almanac. Oxford University Press, New York, pp. 154-157. Link SO, GW Gee, ME Thiede, and PA Beedlow. 1990. "Response of a Shrub-Steppe Ecosystem to Fire: Soil Water and Vegetational Change." Arid Soil Research and Rehabilitation4:163-1 72. Lutton Ri, GL Regan, and LW Jones. 1979. Design and Construction of Covers for Solid Waste Landfills. USEPA Report 600/2-79-165, U.S. Environmental Protection Agency, Cincinnati, Ohio. Marshall E. 1987. "Hlanford's Radioactive Tumbleweed.- Science 236:1616-1620. Murphy EM, TR Ginn, and IL Phillips. 1996. "Geochemical Estimates of Recharge in the Pasco Basin: Evaluation of the Chloride Mass Balance Technique." Water Resource Research 32:2853-2869. Myers DR and DA Duranceau (eds.). 1994. Prototype Hanford Surface Barrier: Design Basis Document. BHI-00007, Bechtel Hanford, Inc., Richland, Washington. O'Farrell TP and RO Gilbert. 1975. "Transport of Radioactive Materials by Jackrabbit on the Hanford Reservation." Health Physics 29:9-15. Petersen KL, JC Chatters, and WI Waugh. 1993. Long-Term Climate Change Assessment Study Plan for the Hanford Site Permanent Isolation Barrier Development Program. WHC-EP-0569 Rev. 1, Westinghouse Hanford Company, Richland, Washington. Suter 6W 11, Ri Luxmoore, and ED Smith. 1993. "Compacted Soil Barriers at Abandoned Landfill Sites are Likely to Fail in the Long Term." J1Environ. Qual. 22:217-226. Tyler SW, BR Scanlon, GW Gee, and GB Allison. 1999. "Water and Solute Transport in Arid Vadose Zones: Innovations in Measurement and Analysis." In Vadose Zone Hydrology, pp. 334-373, J Hopmnans and MB Parlange (eds.), Oxford Press, New York. Ward AL and GW Gee. 1997. "Performance Evaluation of a Field-Scale Surface Barrier." J Environ. Qual. 26:694-705. Wing NR and 6W Gee. 1994. "Quest for the Perfect Cap." Civil Engr. 64(10):38-41. Wing NR, KL Petersen, C Whitlock, and RL Burk. 1995. Long-Term Climate Change Effects Task for the HanfordSite Permanent Isolation BarrierDevelopment Program:-Final Report. BHI-001 44, Bechtel Hanford, Inc., Richland, Washington. Wittreich CD, JK Linville, GW Gee, and AL Ward. 2003. 200-BP-] Prototype Hanford BarrierAnnual Monitoring Report for Fiscal Year 2002. CP-14873, Rev. 0, Fluor Hanford, Inc., Richland, Washington.

D. 14

Attachment 1: Surface Barrier Publications from the Hanford Site 1.

Phillips, S. J., M. R. Adams, T. W. Gilbert, C. C. Meinhardt, R. M. Mitchell, and W. J. Waugh. 1985. EngineeredBarrier Test Facility Status Report: 1984. RI-O-WM-SR-3P, Rockwell Hanford Operations, Richland, Washington.

2.

Phillips, S. J., T. W. Gilbert, and M. R. Adams. 1985. PreliminaryEngineering Specificationsfor a Test Demonstration Multilayer Protective BarrierCover System. RHO-WM-EV-8 P, Rockwell Hanford Operations, Richland, Washington.

3.

Fayer, M. J., W. Conbere, P. R. Heller, and G. W. Gee. 1985. Model Assessment of Protective BarrierDesigns. PNL-5604, Pacific Northwest Laboratory, Richland, Washington.

4.

Myers, D. R. 1985. DisposalMaterials Study. RH-O-WP-EV- I2P, Rockwell Hanford Operations, Richland, Washington.

5.

Adams, M. R., and M. F. Kaplan. 1986. "Marker Development for Hanford Waste Site Disposal." In Waste Management '86, (Vol. I), pp. 425-43 1, RG Post (ed.). University of Arizona, College of Engineering and Mines, Tucson, Arizona.

6.

Phillips, S. J., and J. N. Hartley. 1986. "Protective Barrier Systems for Final Disposal of Hanford Waste Sites." In Waste Management '86, (Vol. 1), pp. 433-437, RG Post (ed.). University of Arizona, College of Engineering and Mines, Tucson, Arizona.

7.

Kaplan, M. F., and M. R. Adams. 1986. "Using the Past to Protect the Future: Marking Nuclear Waste Disposal Sites." Archeology 39(5):51-54.

8.

Adams, M. R., and N. R. Wing. 1986. Protective Barrierand Warning Marker System Development Plan. RHO-RE-OL-35P, Rockwell Hanford Operations, Richland, Washington.

9.

Fayer, M. J. 1987. Model Assessment qf Protective BarrierDesigns: Part HI. PNL-6297, Pacific Northwest Laboratory, Richland, Washington.

10.

Last, G. V., M. A. Glennon, M. A. Young, and G. W. Gee. 1987. Protective BarrierMaterials Analysis:- Fine Soil Site Characterization. PNL-63 14, Pacific Northwest Laboratory, Richland, Washington.

11.

Gee, G. W. 1987. "Preliminary Analysis of the Performance of the Protective Barrier and Marker System." Appendix M, in FinalEnvironmental Impact Statement, Disposal of Hanford Defense High-Level, Transuranicand Tank Wastes. DOE/EIS-O1 13, U.S. Department of Energy, Richland, Washington.

12.

Kirkham, R. R., G. W. Gee, and J. L. Downs. 1987. Field Lysimeter Test Facilityfor Protective Barriers: Experimental Plan. PNL-635 1, Pacific Northwest Laboratory, Richland, Washington.

D.15

13.

Waugh, W. J., and S. 0. Link. 1988. BarrierErosion Control Test Plan: Gravel Mulch, Vegetation, and Soil Water Interactions. WI-C-EP-0067, Westinghouse Hanford Company, Richland, Washington.

14.

Wing, N. R., M. D. Campbell, J. L. Downs, G. W. Gee, R. R. Kirkham, and S. J. Phillips. 1988. "Protective Barrier Development: The Field Lysimeter Test Facility." In Proceedingsof the InternationalTopical Meeting on Nuclear and Hazardous Waste Management Spectrum '88,

pp. 196-198. American Nuclear Society, Inc., La Grange Park, Illinois, WHC-SA-0203-FP, Westinghouse Hanford Company, Richland, Washington. 15.

Phillips, S. J., M. S. Ruben, and R. R. Kirkham. 1988. "'Engineered Surface Barriers for Waste Disposal Sites: Lysimeter Facility Design and Construction." In DOE Model Conference Proceedings, pp. 1229-1238. CONF-881054, October 3-7, Martin Marietta, Oak Ridge, Tennessee.

16.

Ligotke, M. W. 1988. Soil Erosion Rates from Mixed Soil and Gravel Surfaces in a Wind Tunnel: A PreliminaryReport. PNL-6677, Pacific Northwest Laboratory, Richland, Washington.

17.

Waugh, W. J., and M. G. Foley. 1988. Protective Barrier Climate-ChangeImpacts: Technical Workshop Findings and Recommendations. PNL-66 15, Pacific Northwest Laboratory, Richland, Washington.

18.

Ligotke, M. W. 1989. Surface Stability Test Planfor Protective Barriers. PNL-6722, Pacific Northwest Laboratory, Richland, Washington.

19.

Gee, G. W., R. R. Kirkham, J. L. Downs, and M. D. Campbell. 1989. The Field Lysimeter Test Facility (FL TE) at the Hanford Site: Installation and Initial Tests. PNL-68110, Pacific Northwest Laboratory, Richland, Washington.

20.

Gee, G. W., M. D. Campbell, H. D. Freeman, and J. F. Cline. 1989. Assessment of Cover Systems at the GrandJunction, Colorado, Uranium Mill Tailings Pile: 198 7 FieldMeasurements. PNL6762, Pacific Northwest Laboratory, Richland, Washington.

21.

Petersen, K. L. 1989. The Long-Term Climate Change Assessment Task qf the Hanford Site, Washington Protective BarrierDevelopment Program. WHC-SA-0537-FP, Westinghouse Hanford Company, Richland, Washington.

22.

Cadwell, L. L., L. E. Eberhardt, and M. A. Simmons. 1989. Animal Intrusion Studies for Protective Barriers: Status Report for FY 1988. PNL-6869, Pacific Northwest Laboratory,

Richland, Washington. 23.

Freeman, H. D., G. W. Gee, and J. F. Relyea. 1989. Field Study Planfor Alternate Barriers. PNL-6840, Pacific Northwest Laboratory, Richland, Washington.

24.

Freeman, H. D., and G. W. Gee. 1989. Hanford Protective BarriersProgramAsphalt Barrier Studies - FY 1988. PNL-6874, Pacific Northwest Laboratory, Richland, Washington.

D. 16

25.

Waugh, W. J. 1989. Gravel Admix, Vegetation and Soil Water Interactions in Protective Barriers Experimental Design, Construction and Initial Conditions. PNL-661 6, Pacific Northwest Laboratory, Richland, Washington.

26.

Freeman, H. D., and G. W. Gee. 1989. Hanford Protective BarriersProgram: Status ofAsphalt BarrierStudy - FY 1989. PNL-75 13, Pacific Northwest Laboratory, Richland, Washington.

27.

Link, S. 0., and W. J. Waugh. 1989. EvapotranspirationStudies for Protective Barriers:Experimental Plans. PNL-6899, Pacific Northwest Laboratory, Richland, Washington.

28.

Petersen, K. L. 1990. "The Long-Term Climate Change Assessment Task of the Protective Barrier Development Program for Low-Level Waste Site Remediation at the Hanford Site, Washington." In High Level Radioactive Waste Management. Vol 2, pp. 1235-1239. Proceeding of an International Topical Meeting. American Nuclear Society, La Grange Park, Illinois. WHC-SA0808-FP, Westinghouse Hanford Company, Richland, Washington.

29.

Fayer, M. J. 1990. Test Planfor Hydrologic Modeling of Protective Barriers. PNL-71 52, Pacific Northwest Laboratory, Richland, Washington.

30.

Wing, N. R., and G. W. Gee (eds.). 1990. Hanford Site Protective BarrierDevelopment Program: Fiscal Year 1989 Highlights. WHC-EP-03 18, Westinghouse Hanford Company, Richland, Washington.

31.

Campbell, M. D., G. W. Gee, M. J. Kanyid, and M. L. Rockhold. 1990. Field Lysimeter Test Facility: Second Year (FY 1989) Test Results. PNL-7209, Pacific Northwest Laboratory, Richland, Washington.

32.

Landeen, D. S., L. L. Cadwell, L. E. Eberhardt, R. E. Fitzner, and M. A. Simmons. 1990. Animal Intrusion Field Test Plan. WHC-EP-0253, Westinghouse Hanford Company, Richland, Washington.

33.

Link, S. 0., M. E. Thiede, R. D. Evans, J. L. Downs, and W. J. Waugh. 1990. Evapotranspiration Studies for Protective Barriers: FY 1988 Status Report. PNL-6985, Pacific Northwest Laboratory, Richland, Washington.

34.

Relyea, J. F., M. R. Sackschewsky, and W. J. Waugh. 1989. Small-Tube Lysimeter Facility Status Reportfor Fiscal Year 1989. WHC-EP-0297, Westinghouse Hanford Company, Richland, Washington.

35.

Walters, W. H., K. A. Hoover, and L. L. Cadwell. 1990. Project Test Plan for Runoff and Erosion on Fine-Soil BarrierSurfaces and Rock-Covered Side Slopes. PNL-679 1, Pacific Northwest Laboratory, Richland, Washington.

36.

Hoover, K. A., L. L. Cadwell, and W. H. Walters. 1990. Hanfford Protective BarriersProgram: Water Erosion Studies - FY 1989. PNL-72 14, Pacific Northwest Laboratory, Richland, Washington. D.17

37.

Landeen, D. S. 1990. Animal Intrusion Status Report for Fiscal Year 1989. WHC-EP-0299, Westinghouse Hanford Company, Richland, Washington.

38.

Ligotke, M. W., and D. C. Klopfer. 1990. Soil Erosion Rates from Mixed Soil and Gravel Surfaces in a Wind Tunnel. PNL-7435, Pacific Northwest Laboratory, Richland, Washington.

39.

Waugh, W. J., M. E. Thiede, C. J. Kemp, L. L. Cadwell, and S. 0. Link. 1990. Field Study of Gravel Admix, Vegetation, and Soil Water Interactions: Protective BarrierProgram Status Report -

40.

41.

FY 1989. PNL-7440, Pacific Northwest Laboratory, Richland, Washington.

Hunter, C. R., A. J. Busacca, and W. J. Waugh. 1990. A Feasibility Study of Modeling Pedogenic Carbonates in Soils and Sediments at the US. Department ofEnergy's Hanford Site.. PNL-741 3, Pacific Northwest Laboratory, Richland, Washington. Wing, N. R., and G. W. Gee. 1990. "Protective Barrier Development: Overview." In Proceedings of the Twenty-Eighth Hanford Symposium on Health and the Environment, Environmental Monitoring, Restoration, andAssessment: What Have We Learned?, pp. 147-15 1,

RH Gray (ed.), Pacific Northwest Laboratory, Richland, Washington. WHC-SA-0619 FP, Westinghouse Hanford Company, Richland, Washington. 42.

Wing, N. R., and G. W. Gee. 1990. "Protective Barrier Development: Overview." In Proceedings of the InternationalTopical Meeting on Nuclear and Hazardous Waste Management

Spectrum '90, pp. 335-337. American Nuclear Society, Inc., La Grange Park, Illinois. WHC-EP03 80, Westinghouse Hanford Company, Richland, Washington. 43.

Glantz, C. S., M. N. Schwartz, K. W. Burk, R. B. Kaspar, M. W. Ligotke, and D. J. Perrault. 1990. ClimatologicalSummary of Wind and Temperature Datafor the Hanford Meteorology Monitoring

Network. PNL-747 1, Pacific Northwest Laboratory, Richland, Washington. 44.

45.

Campbell, M. D., and G. W. Gee. 1990. Field Lysimeter Test Facility Protective Barrier Test Results (FY 1990, The Third Year). PNL-7558, Pacific Northwest Laboratory, Richland, Washington. Sackschewsky, M. R., J. C. Chatters, S. 0. Link, and C. A. Brandt. 1991. Protective Barrier Program: Test Plan for PlantCommunity Dynamics. WHC-EP-03 80. Westinghouse Hanford

Company, Richland, Washington. 46.

Nichols, W. E. 1991. Comparative Simulations of a Two-Layer Landfill Barrier Using the Help Version 2.0 and UNSAT-H1 Version 2.0 Computer Codes. PNL-7583, Pacific Northwest Laboratory, Richland, Washington.

47.

Landeen, D. S. 1991. Animal Intrusion Status Report for Fiscal Year 1990. WHC-EP-03 98, Westinghouse Hanford Company, Richland, Washington.

D. 18

48.

Campbell, M. D., G. W. Gee, R. R. Kirkham, S. J. Phillips, and N. R. Wing. 1991. "Water Balance Lysimetry at a Nuclear Waste Site." in Proceedings of the InternationalSymposium on Lysimetry, pp. 125-134, RG Allen (ed.), American Society of Civil Engineers, New York.

49.

Kirkham, R. R., M. L. Rockhold, G. W. Gee, M. J. Fayer, M. D. Campbell, and L. J. Fritschen. 1991. "Lysimeters: Data acquisition and analysis." In Proceedings of the International Symposium on Lysimetry, pp. 362-370, RG Allen (ed.), American Society of Civil Engineers, New York.

50.

Phillips, S. J., J. F. Relyea, C. J. Kemp, N. R. Wing, M. D. Campbell, G. W. Gee, M. J. Graham, R. R. Kirkham, and M. S. Rubin. 1991. "Development of Hanford Site Lysimeter Facilities." In Proceedings of the InternationalSymposium on Lysimetry, pp. 19-27, RG Allen (ed.), American Society of Civil Engineers, New York.

51.

Waugh, W. J., M. E. Thiede, L. L. Cadwell, G. W. Gee, H. D. Freeman, M. R. Sackschewsky, and J. F. Relyea. 1991. "Small Lysimeters for Documenting Arid Site Water Balance." In Proceedings of the InternationalSymposium on Lysimetry, pp. 151-159, RG Allen (ed.), American Society of Civil Engineers, New York.

52.

Cadwell, L. L. (ed.). 199 1. Hanford Site Protective BarrierDevelopment Program: Fiscal Year 1990 Highlights. PNL-783 1, Pacific Northwest Laboratory, Richland, Washington.

53.

Petersen, K. L. 1991. Modern and Pleistocene Climatic Patterns in the West. WHC-EP-0523, Westinghouse Hanford Company, Richland, Washington.

54.

Chatters, J. C., and H. A. Gard. 199 1. ArchaeologicalMounds as Analogs of EngineeredCovers for Waste Disposal Sites Literature Review and ProgressReport. PNL-771 8, Pacific Northwest Laboratory, Richland, Washington.

55.

Sackschewsky, M. R., C. J. Kemp, L. L. Cadwell, M. E. Thiede, and W. J. Waugh. 1991. Status Report for the Small-Tube Lysimeter Facility Fiscal Year 1990. WHC-EP-0381, Westinghouse

Hanford Company, Richland, Washington. 56.

Fayer, M. J., M. L. Rockhold, and D. J. Holford. 1992. Model Assessment of Protective Barriers: PartIII Status of FY 1990 Work. PNL-7975, Pacific Northwest Laboratory, Richland, Washington.

57.

Petersen, K. L. 1992. A Warm and Wet Little Climate Optimum and a Cold and Dry Little Ice Age in the Southern Rocky Mountains, USA. WHC-SA- 13 82-FP. Westinghouse Hanford Company, Richland, Washington.

58.

Link, S. 0., J. L. Downs, M. E. Thiede, D. J. Lettau, T. R. Twaddell, and R. A. Black. 1992. EvapotranspirationStudies for Protective Barriers: FY 1990 Status Report. PNL-8032, Pacific Northwest Laboratory, Richland, Washington.

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59.

Link, S. 0., M. E. Thiede, J. L. Downs, D. J. Lettau, and W. J. Waugh. 1992. "Evapotranspiration Studies for Protective Barriers: FY 1989 Status Report." PNL-803 3, Pacific Northwest Laboratory, Richland, Washington.

60.

Fayer, M. J., M. L. Rockhold, and M. D. Campbell. 1992. "Hydrologic Modeling of Protective Barriers: Comparison of Field Data and Simulation Results." Soil Sci. Soc. Am. J., 56:690-700.

61.

Wing, N. R. 1992. A Peer Review of the Hanford Site PermanentIsolation Surface Barrier Development Program. WHC-MR-0392. Westinghouse Hanford Company, Richland, Washington.

62.

Gee, G. W., M. J. Fayer, M. L. Rockhold, and M. D. Campbell. 1992. "Variations in Recharge at the Hanford Site." Northwest Sci., 66:23 7-250.

63.

Gee, G. W., M. D. Campbell, G. S. Campbell, and J. H. Campbell. 1992. "Rapid Measurement of Low Soil Water Potentials Using a Water Activity Meter." Soil Sci. Soc. Am. J, 56:1068-1070.

64.

Ligotke, M. W. 1993. Soil Erosion Rates Caused by Wind and Saltating Sand Stresses in a Wind Tunnel. PN L-8478, Pacific Northwest Laboratory, Richland, Washington.

65.

Fayer, M. J. 1993. Model Assessment of Protective Barriers: PartIV, Status of FY 1992 Work. PNL-8498, Pacific Northwest Laboratory, Richland, Washington.

66.

Wing, N. R., and G. W. Gee. 1993. "The Development of Permanent Isolation Surface Barriers: Hanford Site, Richland, Washington, U.S.A." in Proceedings of Geoconfine '93, pp. 357-362. June 8-11, 1993, Montpellier, France. WHC-SA-1I799-17P, Westinghouse Hanford Company, Richland, Washington.

67.

Petersen, K. L., J. C. Chatters, and W. J. Waugh. 1993. Long-Term Climate Change Assessment Study Planfor the Hanford Site PermanentIsolation BarrierDevelopment Program. WHC-EP0569 Rev. 1, Westinghouse Hanford Company, Richland, Washington.

68.

Wing, N. R. 1993. The Results of Laboratory Test to Determine the Physical Propertiesof Various BarrierConstruction Materials. WHC-SD-ER-DP-006, Westinghouse Hanford Company, Richland, Washington.

69.

Gee, G. W., L. L. Cadwell, H. D. Freeman, M. W. Ligotke, S. 0. Link, R. A. Romine, and W. H. Walters, Jr. 1993. Testing and Monitoring Planfor the PermanentIsolation Surface Barrier Prototype. PNL-83 91, Pacific Northwest Laboratory, Richland, Washington.

70.

Cadwell, L. L., S. 0. Link, and G. W. Gee. 1993. Hanford Site Permanent Isolation Surface BarrierDevelopment Program: Fiscal Year 1992 and 1993 Highlights. PNL-874 1, Pacific Northwest Laboratory, Richland, Washington.

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71.

Link, S. 0., R. N. Kickert, M. J. Fayer, and G. W. Gee. 1993. A Comparison of Simulation Models for PredictingSoil Water Dynamics in Bare and Vegetated Lysimeters. PNL-8675, Pacific

Northwest Laboratory, Richland, Washington. 72.

Sackschewsky, M. R., C. J. Kemp, and L. L. Cadwell. 1993. Status Reportfor the Small-Tube Lysimeter Facility Fiscal Year 1992. WHC-EP-0597, Westinghouse Hanford Company, Richland,

Washington. 73.

Petersen, K. L., and J. C. Chatters. 1993. Long-Term Climate Change Assessment Task for the Hanford Site PermanentIsolation Barrier Development Program: Status through FY 1992.

WHC-EP-0644, Westinghouse Hanford Company, Richland, Washington. 74.

Chamness, M. 1993. An Investigation of Bergmounds as Analogs to Erosion Control Factors on Protective Barriers. PNL-884 1, Pacific Northwest Laboratory, Richland, Washington.

75.

Bjornstad, B. N., and S. S. Teel. 1993. NaturalAnalog Study of EngineeredProtective Barriers at the Hanford Site. PNL-8840, Pacific Northwest Laboratory, Richland, Washington.

76.

U.S. Department of Energy (DOE). 1993. Treatability Test Planfor the 200-BP-] Prototype Surface Barrier. DOE/RL-93-27, Department of Energy, Richland, Washington.

77.

Gee, G. W., D. Felmy, J. C. Ritter, R. R. Kirkham, S. 0. Link, J. L. Downs, and M. J. Fayer. 1993. Field Lysimeter Test Facility Status Report IV. PNL-89 11, Pacific Northwest Laboratory, Richland, Washington.

78.

Gaylord, D. R., L. D. Stetler, G. D. Smith, and R. W. Mars. 1993. Summary of 1990 Folian CharacterizationStudies, Hanford Site, Washington. PNL- 8862, Pacific Northwest Laboratory, Richland, Washington.

79.

Wing, N. R. 1993. Permanent Isolation Surface Barrier: FunctionalPerformance. WHC-EP0650, Westinghouse Hanford Company, Richland, Washington.

80.

Gilmore, B. G., and W. H. Walters. 1993. Water Erosion Field Tests for Hanford Protective .Barriers: FY 1992 Status Report. PNL-8949, Pacific Northwest Laboratory, Richland, Washington.

81.

Kirkharn,R. R. 1993. Comparison of Surface Energy Fluxes with Satellite-DerivedSurface Energy Flux Estimatesfrom a Shrub-Steppe. PNL-9003, Pacific Northwest Laboratory, Richland, Washington.

82.

U.S. Department of Energy (DOE) 1993. Report on Value EngineeringStudy of Permanent Isolation Surface Barrierand Warning Marker System Development Plan at the Hanford Site. DOE/RL/ 12074-- 8, Department of Energy, Richland, Washington.

83.

Wing, N. R. 1994. PermanentIsolation Surface BarrierDevelopment Plan. WHC-EP-0673, Westinghouse Hanford Company, Richland, Washington. D.21

84.

Waugh, W. J., J. C. Chatters, G. V. Last, B. N. B3jornstad, S. 0. Link, and C. R. Hunter. 1994. BarrierAnalogs:- Long-Term Performance Issues, PreliminaryStudies, and Recommendations.

PNL-9004, Pacific Northwest Laboratory, Richland, Washington. 85.

Link, S. 0., L. L. Cadwell, C. A. Brandt, J. L. Downs, R. E. Rossi, and G. W. Gee. 1994. Biointrusion Test Planfor the Permanent Isolation Surface BarrierPrototype. PNL-941 1, Pacific

Northwest Laboratory, Richland, Washington. 86.

Kirkhamn, R. R., and G. W. Gee. 1994. Experimental Plan and Construction Guidancefor Hanford Protective Barrier Test at H-ill AFB, Utah. PNL-94 12, Pacific Northwest Laboratory, Richland, Washington.

87.

Freeman, H. D., and R. A. Romine. 1994. Hanford Permanent Isolation BarrierProgram: Asphalt Technology Test Plan. PNL-9336, Pacific Northwest Laboratory, Richland, Washington.

88.

Link, S. 0., W. J. Waugh, J. L. Downs, M. E. Thiede, J. C. Chatters, and G. W. Gee. 1994. "Effects of Coppice Dune Topography and Vegetation on Soil Water Dynamics in a Cold-Desert Ecosystem." J A rid Environ. 27:265-278.

89.

Waugh, W. J., M. E. Thiede, D. J. Bates, L. L. Cadwell, G. W. Gee, and C. J. Kemp. 1994. "Plant Cover and Water Balance in Gravel Admixtures at an Arid Waste-Burial Site." J1Environ. Qual. 23:676-685.

90.

Landeen, D. S. 1994. The Influence of Small Mammal Burrowing Activity on Water Storage at the Hanford Site. WHC-EP-0730, Westinghouse Hanford Company, Richland, Washington.

91.

U.S. Department of Energy. 1994. ConstructabilityReportfor the 200-BP-1 Prototype Surface Barrier. DOE/RL-94-76, U.S. Department of Energy, Richland Operations Office, Richland, Washington.

92.

Myers, D. R., and D. A. Duranceau (eds.). 1994. Prototype Hanufford Surface Barrier: Design Basis Document." BHI-00007, Bechtel Hanford, Inc., Richland, Washington.

93.

Wing, N. R., and G. W. Gee. 1994. "~Quest for the Perfect Cap." Civil Engineering 64(l10):3 8-4 1.

94.

Gee, G. W., and N. R. Wing (eds.). 1994. In-Situ Remediation: Scientific Basis for Current and Future Technologies, Parts 1-2. Thirty-Third Hanford Symposium on Health and the Environment. November 7-11, 1994, Pasco, Washington. Battelle Press, Columbus, Ohio.

95.

Wing, N. R., and G. W. Gee. 1994. "The Development of Surface Barriers at the Hanford Site." In G. W. Gee and N. R. Wing (eds.) pp. 427-440. In-Situ Remediation:- Scientific Basis for Current and Future Technologies, Parts 1-2. Thirty-Third Hanford Symposium on Health and the Environment. November 7-11, 1994, Pasco, Washington. Battelle Press. Columbus, Ohio.

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96.

Waugh, W. J., K. L. Petersen, S. 0. Link, B. N. Bjornstad, and G. W. Gee. 1994. "Natural Analogs of the Long-Termn Performance of Engineered Covers." In G. W. Gee and N. R. Wing (eds.) pp. 379-410. In-Situ Reinediation: Scientific Basis for Current and Future Technologies, Parts 1-2. Thirty-Third Hanford Symposium on Health and the Environment. November 7-1 1, 1994, Pasco, Washington. Battelle Press, Columbus, Ohio.

97.

Freeman, H. D., and R. A. Romine. 1994. "Hanford Permanent Isolation Barr ier Program: Asphalt Technology Development." In G. W. Gee and N. R. Wing (eds.) pp. 491-506. In-Situ Remediation:- Scientific Basisfor Current and Future Technologies, Parts 1-2. Thirty-Third Hanford Symposium on Health and the Environment. November 7-11, 1994, Pasco, Washington. Battelle Press, Columbus, Ohio.

98.

Gilmore, B. G., and W. H. Walters. 1994. "Summary of Method Develop a Representative Equation for Soil Loss from the Hanford Permanent Isolation Barrier." In G. W. Gee and N. R. Wing (eds.) pp. 507-522. In-Situ Remediation: Scientific Basis for Current and Future Technologies, Parts 1-2. Thirty-Third Hanford Symposium on Health and the Environment. November 7-11, 1994, Pasco, Washington. Battelle Press, Columbus, Ohio.

99.

Landeen, D. S. 1994. "The Influence of Small-Mammal Burrowing Activity on Water Storage at the Hanford Site." In G. W. Gee and N. R. Wing (eds.) pp. 523-544. In-Situ Remediation: Scientific Basis fbr Current and Future Technologies, Parts 1-2. Thirty-Third Hanford Symposium on Health and the Environment. November 7-1 1, 1994, Pasco, Washington. Battelle Press, Columbus, Ohio.

100.

Ligotke, M. W. 1994. "Control of Eolian Soil Erosion from Waste-Site Surface Barriers." In G. W. Gee and N. R. Wing (eds.) pp. 545-5 60. In-Situ Remediation: Scientific Basis for Current and Future Technologies, Parts 1-2. Thirty-Third Hanford Symposium on Health and the Environment. November 7-11, 1994, Pasco, Washington. Battelle Press, Columbus, Ohio.

10 1. Link, S. 0., W. J. Waugh, and J. L. Downs. 1994. "The Role of Plants in Isolation Barrier Systems." In G. W. Gee and N. R. Wing (eds.) pp. 56 1-592. In-Situ Reniediation: Scientific Basis ,for Current and Future Technologies, Parts 1-2. Thirty-Third Hanford Symposium on Health and the Environment. November 7-11, 1994, Pasco, Washington. Battelle Press, Columbus, Ohio. 102. Myers, D. R., and N. R. Wing. 1994. "Hanford Site Protective Isolation Surface Barrier: Taking Research and Development to Engineered Application." In G. W. Gee and N. R. Wing (eds.) pp. 61 3-624. In-Situ Rem ediation:- Scientific Basis for Current and Future Technologies, Parts I2. Thirty-Third Hanford Symposium on Health and the Environment. November 7-11, 1994, Pasco, Washington. Battelle Press, Columbus, Ohio. 103. Petersen, K. L. 1994. "The Long-Terrn Climate Change Task of the Hanford Permanent Isolation Barrier Development Program." In G. W. Gee and N. R. Wing (eds.) pp. 633-648. In-Situ Remiediation: Scientific Basis for Current and Future Technologies, Parts 1-2. Thirty-Third Hanford Symposium on Health and the Environment. November 7-11, 1994, Pasco, Washington. Battelle Press, Columbus, Ohio. D.23

104. Gee, G. W., H. D. Freeman, W. H. Walters, M. W. Ligotke, M. D. Campbell, A. L. Ward, S. 0. Link, S. K. Smith, B. G. Gilmore, and R. A. Romine. 1994. Hanford Prototype Surface Barrier Status Report:- FY1994. PNL-10275, Pacific Northwest Laboratory, Richland, Washington. 105. Gaylord, D. R., and L. D. Stetler. 1994. "Aeolian-Climate Thresholds and Sand Dunes at the Hanford Site, South-Central Washington, U.S.A."' J Arid Environments 28:95-1 16. 106.

Freeman, H. D., R. A. Romine, and A. H. Zacher. 1994. Hanford PermanentIsolation Barrier Program:-Asphalt Technology Data and St at us Report - FY 1994. PNL-l 0194, Pacific Northwest Laboratory, Richland, Washington.

107.

Wing, N. R., G. W. Gee, and J. W. Bammann. 1995. "Program Management of a Multi-Year Technology Development Effort." PM Network 9(3):47-50.

108.

Sackschewsky, M. R., C. J. Kemp, S. 0. Link, and W. J. Waugh. 1995. "Soil Water Balance Changes in Engineered Soil Surfaces."~ J Environ. Qual. 24:352-359.

109.

Rockhold, M. L., M. J. Fayer, C. T. Kincaid, and G. W. Gee. 1995. Estimation of Natural Ground Water Recharge for the Performance Assessment of a Low-Level Waste Disposal Facility at the

Hanford Site. PNL-10508, Pacific Northwest Laboratory, Richland, Washington. 110.

Link, S. 0., M. E. Thiede, R. D. Evansj. L. Downs, and G. W. Gee. 1995. "Responses of Big Sagebrush and Spiny Hopsage to Increasing Water Stress." In B. A. Roundy, E. D. McArthur, J. S. Haley, and D. K. Mann (eds.). In Proceedings of the Wildland Shrub and Arid Land Restoration Symposium, pp. 196-201. USDA-ES, Intermountain Research Station, Ogden, Utah.

111.

Wing, N. R., F. M. Corpuz, K. L. Petersen, and A. M. Tallman. 1995. Physical Stability of LongTerm Surface Barriers-Assessment of Potentially Disruptive Natural Events. BHI-00 145, Bechtel Hanford, Inc., Richland, Washington.

112. Wing, N. R., K. L. Petersen, C. Whitlock, R. L. Burk. 1995. Long-Term Climate Change Effects Task for the Hanford Site Permanent Isolation BarrierDevelopment Program:- FinalReport.

BHI-00 144, Bechtel Hanford, Inc., Richland, Washington. 113.

Duranceau, D. A. 1995. Site Evaluation Report for Candidate Basalt Quarry Sites. BHI-00005, Bechtel Hanford, Inc., Richland, Washington.

114.

Fayer, M. J., and C. S. Simmons. 1995. "Modified Soil Water Retention Functions for All Matric Suctions." Water Resour. Res. 31:1233-123 8.

115.

Petersen, K. L., S. 0. Link, and G. W. Gee. 1995. Han~ford Site Long-Term Surface Barrier Development Program:-Fiscal Year 1994 Highlights. PNL-1 0605, Pacific Northwest Laboratory, Richland, Washington.

116.

Link, S. 0., N. R. Wing, and G. W. Gee. 1995. "The Development of Permanent Isolation Barriers for Buried Wastes in Cold Deserts: Hanford, Washington." J Arid Land Studies 4:215-224. D.24

117.

Link, S. 0., L. L. Cadwell, K. L. Petersen, M. R. Sackshewsky, and D. S. Landeen. 1995. The Role qf'Plants and A nimals in Isolation Barriersat Hanford, Washington. PNL- 10788. Pacific Northwest National Laboratory, Richland, Washington.

118.

Gee, G. W., A. L. Ward, B. G. Gilnmore, M. W. Ligolke, and S. 0. Link. 1995. Hanford Prototype-BarrierStatus Report: FY 199.5. PNL-1 0872. Pacific Northwest National Laboratory, Richland, Washington.

119.

Gee, G. W., A. L. Ward, B. G. Gilmore, S. 0. Link, G. W. Dennis, and T. K. O'Neil. 1996. HanfordPrototype-BarrierStatus Report: FY.1996. PNNL-l 1367. Pacific Northwest National Laboratory, Richland, Washington.

120.

U.S. Department of Energy (DOE). 1996. Focused Feasibility Study of EngineeredBarriersfor Waste Management Units in the 200 Areas. DOE/RL-93-33. Bechtel Hanford, Inc., Richland, Washington.

121.

Ward, A. L., and G. W. Gee. 1997. "'Performance Evaluation of a Field-Scale Surface Barrier." J Environ. Qual. 26:694-705.

122.

Gee, G. W., N. R. Wing, and A. L. Ward. 1997. "Development and Testing of Permanent Isolation Surface Barriers at the Hanford Site." pp. D3-D22. In BarrierTechnologies for Environmental Management. National Academy Press, Washington, D.C.

123.

Gee, G. W., and A. L. Ward, 1997. "Still in Quest of the Perfect Cap." pp. 145-164. In T. D. Reynolds and R. C. Morris (eds.). Landfill Capping in the Semi-Arid West, -Conference Proceedings. Jackson Lake, Wyoming, May, 1997, Environmental Science and Research Foundation, Idaho Falls, Idaho.

124.

Fayer, M. J., and G. W. Gee. 1997. "Hlydrologic Model Tests for Landfill Covers Using Field Data." pp.53-68. In T. D. Reynolds and R. C. Morris (eds.). Landfill Capping in the Semi-Arid West, -Conference Proceedings. Jackson Lake, Wyoming, May, 1997, Environmental Science and Research Foundation, Idaho Falls, Idaho.

125.

Gee, G. W., A. L. Ward, and M. J. Fayer. 1997. "Surface Barrier Research at the Hanford Site." Land Contaminationand Reclamation. 5(3) :233-237.

126.

Ward, A. L., G. W. Gee, and S.O0. Link. 199 7. HanfordPrototype-BarrierStatus Report: FY 1997. PNNL-1 1789. Pacific Northwest National Laboratory, Richland, Washington.

127.

Gee, G. W., A. L. Ward, and R. R. Kirkham. 1997. "'Long-tenn Performance of Surface Covers Estimated with Short-term Testing." pp. 67-81. CONF-980652. Conference Proceedingsof the Long-Termn Stewardship Workshop. U.S. Department of Energy, Grand Junction, Colorado.

128.

U.S. Department of Energy (DOE). 1999. 200-BP-1 Prototype Barrier Treatahility Test Report. DOE/RL-99-1 1. U.S. Department of Energy, Richland, Washington.

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129. Ward, A. L., and G. W. Gee. 2000. "Hanford Site Surface Barrier Technology." pp. 1415-1423. In B. B. Looney and R. W. Falta (eds.). Vadose Zone Science and Technology Solutions. Battelle Press, Columbus, Ohio. 130.

Gee, G. W., and A. L. Ward. 2000. Comment on paper 19209-HZ Moisture accumnulating under asphalt cover at radioactive waste-burial site. J Haz. and Toxic and Rad. Waste Mgt. 4(1):40-41.

131.

Miller, C. W., and C. D. Wittreich. 2001. Alternative Fine-GrainedSoil Borrow Source Study Work Plan. BHI-0 1478. Bechtel Hanford, Inc., Richland, Washington.

132. Galgoul, M. J., and C. Sump. 2002. Alternative Fine-GrainedSoil Borrow Source Study Final Report. BHI-01551. Rev. 0. Bechtel Hanford, Inc. Richland, Washington. 133. Gee, G.W., A.L. Ward and C.D. Wittreich. 2002. The Hanford Site 1000- Year Cap Design Test. PNNL 14143, Pacific Northwest National Laboratory, Richland, Washington. 134. Wittreich, C. D., J. K. Linville, G. W. Gee, and A. L. Ward. 2003. 200-BP-1 Prototype Hanford BarrierAnnual Monitoring Report.jbr Fiscal Year 2002. CP-14873. Rev. 0. Flourl-Hanford, Richland, Washington.

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PNNL- 14702, Rev. 0

Distribution No. of Copies

No. of Copies

ONSITE

8 Fluor Hanford, Inc.

2 DOE Office of River Protection R. M. Yasek R. W. Lober 9

J. V. Borghese F. M. Coony B. H. Ford T. W. Fogwell R. Jackson V. J. Rohay L. C. Swanson M. E. Todd-Robertson

H6-60 H6-60

DOE Richland Operations Office B. L. Charboneau B. L. Foley J. P. Hanson R. D. Hildebrand J. G. Morse K. M. Thompson S. H. Wisness DOE Public Reading Room (2)

A6-33 A6-3 8 A5-13 A6-38 A6-38 A6-38 A3-04

Stoller R. G. McCain

51 Pacific Northwest National Laboratory R. L. Aaberg C. Arimescu M. P. Bergeron B. N. Bjornstad R. W. Bryce A. L. Bunn K. J. Cantrell Y. J. Chien W. J. Deutsch R. L. Dirkes J. L. Downs D. W. Engle P. W. Eslinger M. J. Fayer E. J. Freeman M. D. Freshley G. W. Gee T. J. Gilmore D. G. Horton C. T. Kincaid G. V. Last (5) C. A. LoPresti W. J. Martin T. B. Miley C. J. Murray

1H9-01 1-9-04 H16-60 HO0-23 HO0-23

9 CH2M HILL Hanford Group, Inc. F. J. Anderson A. J. Knepp M. N. Jarayssi F. M. Mann W. J. McMahon C. W. Miller D. A. Myers C. D. Wittreich M. 1. Wood

E6-35 116-03 1-6-03 E6-3 5 E6-35 H-6-62 E6-35 H6-62 H18-44

2 Fluor Federal Services R. Khaleel R. J. Puigh

B2-62

1-2-53

5 Bechtel Hanford Inc. P. G. Doctor K. R. Fecht K. A. Gano J. K. Linville S. G. Weiss

E6-35 E6-35 E6-35 E6-35 E6-35 E6-35 E6-35 E6-35

E6-17 E6-17

Distr. I

K3-54 K6-04 K9-36 K6-81 E6-35 K6-85 K6-81 K6-81 K6-81 K6-75 K6-85 K5-12 K6-04 K9-33 K9-36 K9-33 K9-33 K6-81 K6-81 K9-33 K6-81 K5-12 K6-81 K6-04 K6-81

PNNL-14702, Rev. 0 No. of Copies

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PNNL-14725, Rev. 0

Geographic and Operational Site Parameters List (GOSPL) for the 2004 Composite Analysis

G. V. Last W. E. Nichols C. T. Kincaid

July 2004

Prepared for the U.S. Department of Energy under Contract DE-AC06-76RL01 830

DISCLAIMER This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor Battelle Memorial Institute, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

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PNNL-14725, Rev. 0

Geographic and Operational Site Parameters List (GOSPL) for the 2004 Composite Analysis

G. V. Last W. E. Nichols C. T. Kincaid

July 2004

Prepared for the U.S. Department of Energy under Contract DE-AC06-76RL01830

Pacific Northwest National Laboratory Richland, Washington 99352

Executive Summary A composite analysis is required by U.S. Department of Energy (DOE) Order 435.1 to ensure public safety through the management of active and planned low-level radioactive waste disposal facilities associated with the Hanford Site. Kincaid et al. (2004) indicated that the System Assessment Capability (SAC) (Kincaid et al. 2000; Bryce et al. 2002; Eslinger 2002a, 2002b) would be used to analyze over a thousand different waste sites. A master spreadsheet termed the Geographic and Operational Site Parameters List (GOSPL) was assembled to facilitate the generation of keyword input files containing general information on each waste site, its operational/disposal history, and its environmental settings (past, current, and future). This report briefly describes each of the key data fields, including the source(s) of data, and provides the resulting inputs to be used for the 2004 Composite Analysis.

Contents Executive Summary..........................................................................................

iii

1.0

Introduction...........................................................................................

2.0

Background............................................................................................

3.0

Geographic and Operational Site Parameter List Definitions .......................................

6

3.1

Site-Specific Parameters ......................................................................... 3.1.1 Site Identifiers.............................................................................. 3.1.2 General Site Design and Operational History Information............................ 3.1.3 Geographic Information................................................................... 3.1.4 Facility Dimensions .......................................................................

6 6 7 8 9

3.2

Model-Specific Instructions ..................................................................... 3.2.1 Selected for Simulation in the 2004 Composite Analysis............................. 3.2.2 Release Model Designation .............................................................. 3.2.3 Vadose Zone Model Hydrostratigraphy .................................................

10 10 10 11

3.3

Remediation/Recharge Assumptions ........................................................... 3.3.1 Pre-Hanford Recharge Class ............................................................. 3.3.2 Operational Recharge Class .............................................................. 3.3.3 Interim Remedial Actions ................................................................ 3.3.4 Remediation ..............................................................................

18 19 19 20 21

4.0

Conclusions and Recommendations ...................................................................

24

5.0

References............................................................................................

25

Appendix

-

Geographic and Operational Site Parameters for Waste Sites To Be Simulated in the 2004 Composite Analysis ..............................................................

A.1I

Figures 2.1

Conceptual Model of the System Assessment Capability............................................

3

2.2

Inform-ation Flow in SAC Rev. I Software Design...................................................

4

3.1

Geographic Areas Used to Define Different Hydrostratigraphic Profiles .........................

14

v

Tables 3.1

Default Site Areas .......................................................................................

10

3.2

Summary of Release Model Assignments to Waste Source Types ................................

11

3.3

Site Type Codes Used in the Hydrostratigraphic Templates ........................................

12

3.4

Geographic Area Designations Used in the Hydrostratigraphic Template Codes ................

15

3.5

Site-Specific Area Designations Used in the Hydrostratigraphic Template Codes...............

15

3.6

Waste Chemistry Groups Used in the Base Template Codes........................................

16

3.7

General Hydrostratigraphic Templates for Each Geographic Area ................................

16

3.8

Site-Specific Templates Established for a Few Key Facilities ......................................

18

3.9

Pre-Hanford Recharge Classes for the 2004 Composite Analysis .................................

19

3.10

Operational Recharge Classes for the 2004 Composite Analysis ...................................

20

3.11

Example of Interim Remedial Actions Defined for the 2004 Composite Analysis...............

21

3.12

Post-Remediation Recharge Classes ..................................................................

23

3.13

Post-Reined iation/Barrier Design Life ................................................................

24

vi

1.0

Introduction

A composite analysis is required by U.S. Department of Energy (DOE) Order 435.1 to ensure public safety through the management of active and planned low-level radioactive waste disposal facilities associated with the Hanford Site. The original composite analysis detailed in Kincaid et al. (1998) must be revised and submitted to DOE Headquarters (DOE-HQ) because of revisions to waste site information in the 100, 200, and 300 Areas; updated performance assessments and environmental impact statements (EIS); changes in inventory estimates for key sites and constituents; and a change in the definition of offisite receptors. Kincaid et al. (2004) describe the technical scope of the 2004 Composite Analysis for the Hanford Site and the approach to perform this analysis. It will be a site-wide analysis, considering final remedial actions for the Columbia River corridor and the Central Plateau, and will support waste-specific and sitespecific assessments throughout the Hanford Site. The 2004 Composite Analysis also will provide supporting information on a regional or site-wide basis for use in important Hanford assessments and decisions such as the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) 5-year review in 2005, tank closure decisions, decisions on final groundwater remedies for the 200 Areas, decisions on final groundwater remedies for the 100 Areas, and the Columbia River corr idor final record of decision. Kincaid et al. (2004) identified 1,046 waste sites from the 2,730 Waste Information Data System (WIDS) sites and several existing and future storage sites for inclusion in the 2004 Composite Analysis. (a) Each of these sites will be modeled as an individual release or storage site whenever inventory and release data permit. Beginning in fiscal year (FY) 2003, the DOE Richland Operations Office (DOE-RL) initiated activities to develop the input data needed to support the 2004 Composite Analysis. This report describes the compilation of site-specific parameters for incorporation into the Geographic and Operational Site Parameters List (GOSPL) to support the 2004 Composite Analysis. This work was conducted as part of the Characterization of Systems Task of the Groundwater Remediation Project (formerly the Groundwater Protection Program) managed by Fluor Hanford, Inc., Richland, Washington.

2.0

Background

Kincaid et al. (2004) indicated that the System Assessment Capability (SAC) (Kincaid et al. 2000; Bryce et al. 2002; Eslinger 2002a, 2002b) would be used for the analysis. The SAC is a set of models and data that have been assembled since the previous 1998 Composite Analysis (Kincaid et al. 1998) was

(a)

Originally 974 of 2,730 Waste Information Data System (WIDS) sites were identified for inclusion in the 2004 Composite Analysis. Further work identified 48 more waste sites bringing the total to 1,022. Subsequent reviews identified an additional 24 sites that have been included, many of which account for offsite transfers of waste and nuclear material. This brings the total to 1,046.

performed to estimate the collective impact of all the waste that will remain at the Hanford Site. Computer codes that have been well tested at the Hanford Site have been used when possible and new software has been written when necessary to simulate the features and processes that affect the release of contaminants into the environment, transport of contaminants through the environment, and the impact those contaminants have on living systems, cultures, and the local economy. The various SAC components have been organized to simulate the transport and fate of contaminants from their presence in Hanford waste sites, through their release into the vadose zone, to their movement in the groundwater, and into the Columbia River. Components of SAC such as the groundwater model, the ecological impact component, and the human health component were originally developed and tested for previous Hanford assessments. The elements of the SAC computational tool include: "Inventory Module - develops an inventory of specific waste disposal and storage locations for the period 1944 to Hanford Site closure based on disposal records, process knowledge, the results of tank and field samples, and planned disposals and remedial actions. The year 2035 is used as the Hanford Site closure date for the 2004 Composite Analysis because it has been identified as the time of site closure for the majority of facilities (e.g., tanks, solid waste burial grounds, chemical separations plants). However, the commercial waste site (US Ecology) is assumed to close in 2056 and the graphite cores of the production reactors are moved to the Central Plateau in 2056. Future runs will use the closure date predicted at the time of the run. This module also identifies the material scheduled for disposal in offsite repositories, including high-level waste, transuranic waste, and spent fuel. " Release Module - simulates the annual release of contaminants to the vadose zone from the variety of waste types in the modeled waste sites. This module also simulates future remediation actions that move waste to the Environmental Restoration Disposal Facility (ERDF) and other permanent disposal locations. * Air Transport Module - simulates the transport of contaminants through the air pathway from release points to points of deposition. " Vadose Zone Transport Module - simulates fluid flow and contaminant transport in the vadose zone, which is the unsaturated sediment between the land surface and the unconfined aquifer. The module also simulates the release of volatile contaminants out of the vadose zone into the air pathway. * Groundwater Transport Module - simulates fluid flow and contaminant transport in the unconfined aquifer that underlies the Hanford Site using the transient inverse calibrated three-dimensional Sitewide groundwater model. " Soil Module - simulates the buildup of contaminants in the plant root-zone soil layer due to air deposition and irrigation. Solutions are available for the cases of no irrigation, irrigation with groundwater, and irrigation with river water. " River Module - simulates river flow and contaminant/sediment transport in the Hanford Reach from Vernita Bridge downstream to the city of Richland. This module simulates background concentra2

lions and background plus the Hanford Site concentrations to enable an assessment of the Hanford Site incremental impact to the Columbia River and its ecosystem. " Riparian Zone Module - uses river and groundwater information to simulate the concentration of contaminants in seep or spring water and in the wet soil near the edge of the Columbia River. * Risk/Impact Modules - performs risk/impact analysis in four topical areas: human health, ecological health, economic impact, and cultural impact with the latter two being new impact metrics for Hanford assessments. The ecological and human health risk modules will be applied in the 2004 Composite Analysis. The remaining two modules of risk/impact will be applied in a supplemental analysis to inform the public and regulators regarding issues related to the composite analysis (for example, the economic and cultural impacts of chemical hazards). Each module was assembled so that it could be tested and evaluated independently of the other modules. The inventory, release, environmental pathways, and risk/impact modules were then linked to test the overall performance of the system. A conceptual illustration of SAC (Figure 2. 1) portrays a linear flow of informnation. In general, inventory feeds release mechanisms, which feed to the atmospheric, vadose zone, groundwater, and Columbia River pathways. At times, release occurs directly to the groundwater through reverse wells and to the Columbia River from the single-pass reactors. During chemical separation plant operation, release also occurred to the atmosphere. The atmosphere, groundwater, Columbia River, riparian zone and soil technical modules provide media-specific concentration estimates used in the risk and impact assessment.

System Assessment Capability Conceptual Model Environmental Pathways

inventory

R.ease

Risk and

Atmospheric U

impact

soil Solid waste .Uquid Waste

HmnHat Eooia Rues

VaclosO Zone

Gases Tanks Facilities

Eooi

hetease

Figure 2.1.

Clua

Cobal

Rve

Conceptual Model of the System Assessment Capability

Background information for the development of the initial SAC is presented in Groundwater/Vadose Zone IntegrationProject: PreliminarySystem Assessment Capability Concepts for Architecture,

3

Platform and Data Management!'a) This document includes a description of alternate architectures for SAC as well as conceptual models for each technical element of the capability. Design of the initial SAC tool is summarized in Kincaid et a]. (2000). Results of an initial assessment performned with the SAC are provided in Bryce et al. (2002). A description of the software is provided in Eslinger et al. (2002a, 2002b). The system of codes includes existing computer programs, new computer programs, electronic data libraries, and data formatting processors (or data translators). The relationships among code modules that make up the SAC Systems Code are illustrated in Figure 2.2. Major modules appearing on the left side of the diagram perform inventory and transport calculations providing estimates of the concentrations of analytes in various media. Modules shown on the right perform calculations related to the impact from the contaminated media. Impacts include potential effects on humans, the ecology of the area, the economy of the region, and the proximity of contamninants to social and cultural resources.

GkC-EP'

&k-EODFlow

Enuromert~chatcPrcesorEnuromerla Sfins efiifonRev.

Diagram for the SAC 1

Computer Codes

Revieor Cnacisu23200

Fiue2.. IfomtonFo ESfwreDsg i AHRv (a) Goundwter/adoseZoneIntegatio Projct: Pelimnary yste Assesmen Capaiityncetso Archeictre, Patodfor n aaMngmn.(tp/ whnfrEo/pgpmdln/aacie 30rep rr n ICprodfrai curlrb (CD)14E Daa

As can be seen in Figure 2.2, the SAC Rev. I Systems Code consists of a number of components that can be executed separately. A number of pieces of information, such as the site identification, coordinates, release model, hydrogeologic column (template), remediation action, infiltration class, and the start time and stop timne of a simulated problem, are needed for the system components. The environmental settings definition (ESD) keyword file was designed to contain this common information. Generally, if information is needed by one or more modules of the suite of codes, it is entered in the ESD keyword file. A number of the ESD keywords are generated fromn general information on the waste site, its operational! disposal history, and its environmental settings (past, current, and future). To facilitate the generation of these ESD keyword input files, a database termed the Geographic and Operational Site Parameters List (GOSPL) was assembled. One of the challenges associated with performing an assessment is appropriately presenting how well the results predict what might actually occur. This is because the attributes of the site that effect transport of contaminants, the impact of contaminants on living systems, and the future conditions used in the assessment, as well as many other factors upon which the predictions depend, are not completely understood. SAC was developed to allow the performance of a probabilistic risk assessment so an indication of the effect of parameter uncertainty on results could be examined. In general, other sources of uncertainty, such as conceptual model uncertainty, will not be handled within the calculations but will be discussed in the interpretation of the results of this analysis. For the 2004 Composite Analysis, SAC has been modified to enable the import of results from detailed assessments of individual waste sites by other Hanford Site programs/projects. Such results come from selected tank waste analyses (e.g., the Integrated Disposal Facility [IDFJ Performance Assessment [Mann 2003]). Information on 1) release to vadose zone or 2) release to water table will be imported into the SAC deterministic analysis. The 2004 Composite Analysis will treat best estimate simulations by other Hanford Site programs as "median" simulations and incorporate them into an overall "'median-input" deterministic simulation. For most waste sites simulated by others, the SAC modules will be adjusted to achieve comnparable results. To performn a stochastic analysis, best-estimate data (geologic profile, hydraulic properties, geochemical properties, recharge sequence, etc.) used by other Hanford Site programs to perfonrn assessments will be interpreted as "median" values for distributions where the data range is defined by the Hanford-wide data set previously compiled for SAC. A simplified model (such as, release and one-dimensional vadose zone or release and two-dimensional vadose zone) will be calibrated to reproduce key aspects of the median simulation provided by the detailed assessment. This simplified but calibrated model will be used to generate the stochastic realizations. Where available, comparison will be made between the range of SAC stochastic responses and the range of deterministic sensitivity cases provided by the other Hanford Site program. Significant differences may exist between the SAC representation of uncertainty and the representation of sensitivity created by other assessments. This is especially true when the site-specific assessment is using sensitivity analyses to explore alternate conceptual models of waste form release (for example, tank residuals modeled with a solubility model, diffusion model, advection-desorption model, linear release-tim-e-model) or barrier performance (for example, alternate surface barriers and engineered containment systems surrounding a glass waste form). 5

3.0

Geographic and Operational Site Parameter List Definitions

Of the more than 2,730 waste sites at Hanford and several storage sites, a subset of 1,046 sites was selected for inclusion in the 2004 Composite Analysis (Kincaid et al. 2004). A number of pieces of information are needed for the assessment, such as the site location, the release model, the hydrostratigraphic column (template), and the remedial action and infiltration assumptions. If this type of informnation is needed by one or more module of the suite of codes used by SAC, for a particular site, then the data are assembled for entry in the ESD keyword file. Of the 1,046 sites to be included in the 2004 Composite Analysis, 24 sites are primarily just place holders used to account for offisite transfers and nuclear material that are not directly simulated in any of the SAC codes. Thus, data have been assembled to enable the simulation of each of the 1,022 remaining sites, individually, using their site-specific parameters, and environmental settings. A master spreadsheet termed the Geographic and Operational Site Parameters List (or GOSPL) was developed for the initial assessments conducted using the SAC to define the site-specific location and facility design parameters as well as the key model assumptions for each assessment. GOSPL has continued to evolve as the site information and assessment basis has changed. It can generally be subdivided into three main sections: Site-Specific Parameters, ModelSpecific Instructions, and Remediation/Infi Itration Assumptions. Brief descriptions of each key data field, including the source(s) of data are provided below. Note that other subordinate data fields that are not directly used by the current SAC modules are not described here. This version of GOSPL (containing the 1,022 sites to be individually simulated for the 2004 Composite Analysis) is provided in the appendix.

3.1

Site-Specific Parameters

Key site-specific geographic parameters used in the SAC include such input as the site identifiers (e.g., Site Code), general site design and operational history information, site geographic inform-ation (e.g., location), and facility dimensions. Much of this information is taken from WIDS. Please refer to the WIDS home page on the Hanford Intranet at http://apweb02.rl.gov/rapidweb/phmc/cp/wids/index.cfm?PageNum=l, and in particular the WIDS Data Field Definitions and Criteria http://apweb02.rl. gov/rapidweb/phmc/cp/wids/docs/5/docs/datacritlI.pdf. 3.1.1

Site Identifiers

There are three fields used to identify each specific site to be represented in the composite analysis: the WIDS Site Identification Number, the Site Code, and the Site Names. 3.1.1.1

WIDS Site Identification Number (Siteld)

-

Site Table

The WIDS Siteld (e.g., 575) provides a numeric identification number to uniquely identify each site record within WIDS. The primary data source for this information is the WIDS database, either directly or indirectly via the Hanford Site Waste Management Units Report (DOE 2003) or the QMAP geospatial mnap portal (http://www7.rl.gov/cfroot/knowledgenet/qmap/index.cfm). Future sites or facilities not contained in the WIDS database were assigned a Siteld equal to or greater than 9,900.

6

3.1.1.2

WIDS Site Code (SiteCode)

-

Site Table

The SiteCode (e.g., 216-Z-9) is a unique alphanumeric identification tag (code) assigned to a site when it is entered into WIDS. The codes have been assigned in accordance with the facility naming conventions in use at the time the site was entered into the database or as modified during database reengineering. The site codes generally consist of a prefix indicating the designed area in which the site is located and its facility type (such as I100-D-, 216-B-, 618-), followed by a sequential number. The primary data source for the SiteCode is the WIDS database. Planned or proposed future waste sites or facilities not contained in the WIDS database were assigned their own unique identifier by SAC project staff. 3.1.1.3

WIDS Site Names (SiteNames)

-

Site Table

The SiteNames field (e.g., 216-Z-9, 216-Z-9 Cavern, 234-5 Recuplex Cavern, 216-Z- 10, 216-Z-9 Crib, 21 6-Z-9 Covered Trench) provides the common or working names by which the site is known, including all aliases for a site. The primary data source for this information is from WIDS and was obtained either directly from the WIDS database, or indirectly via the Hanford Site Waste Management Units Report (DOE 2003) or the QMAP geospatial map portal. The purpose of this field is to provide a cross reference to previously used site codes and names used in reference documents. 3.1.2

General Site Design and Operational History Information

General information on the design and operational history of the site is captured via four fields: site type, waste type, and start and end dates. 3.1.2.1

Site Type (SiteType)

-

Site Table

The SiteType (e.g., Trench) describes the structural design of the site. Generally, the site types are defined by the general function of the site (e.g., ground disposal) and its design (e.g., trench). The primary data source for this information is WIDS, and was obtained either directly from the WIDS database, or indirectly via the Hanford Site Waste Management Units Report (DOE 2003) or the QMIAP geospatial map portal. The purpose of this field is to help describe the manner in which the sites were used to store or dispose of waste. 3.1.2.2

Waste/Material Type (Type) - Waste Table

The waste/material type describes the type of waste at the site in terms of its source, its appearance, its use before becoming a waste, or other general category (e.g., steam condensate, process effluent, bismuth phosphate metal waste). The primary source of this data is WIDS. If the information was missing from WIDS, then it may be that the type of waste was unknown or the informnation has not been entered. The purpose of this information is to allow grouping of sites into similar waste chemistry groups to aid selection and assignment of linear sorption coefficients.

7

3.1.2.3

Operational Start Date (StartDate)

-

Site Table

The start date is the year the site started receiving waste. The primary source of this data is WIDS. If the information was missing from WIDS, then a start date was estimated from other nearby sites receiving similar waste types or servicing the same major process facilities. 3.1.2.4

Operational End Date (EndDate)

-

Site Table

The end date is the year the site stopped receiving waste. The primary source of this data is WIDS. If the inform-ation was missing from WIDS, then an end date was estimated from other nearby sites receiving similar waste types or servicing the same major process facilities. 3.1.3

Geographic Information

The basic geographic information captured for each site includes the site location and the type of feature used to represent the site within the Hanford Geographic Information System (HGIS) and Hanford Site Atlas (BHI 1998). 3.1.3.1

Site Location (Center X Coordinate, Center Y Coordinate)

-

GisSite Table

The X and Y coordinates for the site location are defined in terms of the Washington State Plane Easting and Northing coordinates (respectively), Southern Section, North American Datum 1983, in meters. The coordinate information represents the centroid of the site for sites mapped as a polygon. For sites mapped as a point (e.g., injection/reverse well), it represents the site itself. The primary data source for this information is WIDS, either directly from the WIDS database, or indirectly via the HanfordSite Waste Management Units Report (DOE 2003) or the QMAP geospatial map portal. However, coordinates are not recorded in WIDS for sites that are mapped as a line (e.g., sewers). So, for sites mapped as a line, and for sites where coordinate informnation is not available in WIDS, the centroid coordinates were estimated from HGIS documentation (i.e., the Hanford Site Atlas [BHI 1998]). More detailed coordinate information was provided for large high volume liquid waste sites (e.g., ponds, ditches, cribs, and trenches) that might spatially overlap a number of different groundwater nodes. Rather than representing the centroid of the site, this information provides a number of key X,Y coordinate points that represent the perimeter of the site. Two fields are provided for this input, the number of coordinate points used to define the perimeter of the site, and the actual string of X, Y coordinates. Number of X, Y Coordinate Points. This field provides the number of distinct X, Y coordinate points included in the X, Y coordinate string defined below. X, Y Coordinate String. This field provides a string of paired X, Y coordinates used to define the perimeter of the site. The primary source of this informnation is estimates of selected key points used to represent the gross perimeter of the site as derived from the QMAP geospatial map portal (http://www7.rl.gov/cfroot/knowledgenet/qinap/index.cfm) or from HGIS documentation (i.e., the Hanford Site Atlas [BHI 1998]).

8

3.1.3.2

GIS Feature Type (GISFeatu reType)

GisSite Table

-

The Geographic Information System (GIS) feature type describes the spatial representation of the site features in the HGIS. This includes sites mapped as a polygon, point, or line. 3.1.4

Facility Dimensions

Facility dimensions are captured via five fields generally taken fromn the WIDS database. These data fields include: Site Length, Site Width, Site Depth (or Height), Site Diameter, and Site Area. In general, dimensions are provided in length and width fields or in the diameter field, but not both. 3.1.4.1

Site Length (LengthMtrs)

-

Dimensions Table

The site length is the longest dimension of a rectangular or nearly rectangular site. The primary source of this data is the WIDS database. If the data were not directly available from WIDS, then the site length was estimated from the QMAP geospatial map portal or HGIS documentation (i.e., the Hanford Site Atlas [BHl 1998]). If the value is blank, then it may be that the site length is unknown, or the inform-ation has not been entered (i.e., was not readily available for entry in the WIDS database). 3.1.4.2

Site Width (WidthMtrs) - Dimensions Table

The site width is the shortest dimension of a rectangular or nearly rectangular site. The primary source of this data is the WIDS database. If the data were not directly available from WIDS, then the site width was estimated from the QMAP geospatial map portal or HGIS documentation (i.e., the Hanford Site Atlas [BHI 1998]). If the value is blank, then it may be that the site width is unknown, or the inform-ation has not been entered (i.e., was not readily available for entry in the WIDS database). 3.1.4.3

Site Depth/Height (DepthlleightMtrs)

-

Dimensions Table

The site depth/height is the maximum depth of the site (in meters) below the ground surface or the maximum height of the unit above the ground surface. This includes the overburden depth. The primary source of this data is the WIDS database. If the value is blank, then it may be that the depth/height is unknown, or the information has not been entered (i.e., was not readily available for entry in the WIDS database). 3.1.4.4

Site Diameter (DiameterMtrs)

-

Dimensions Table

The site diameter is the distance (in meters) through the center of a circular or cylindrical (or nearly circular or cylindrical) site. The primary source of this data is the WIDS database. If the field is blank then it may be that the site diameter is unknown, there is no diameter (e.g., the site is rectangular), or the information has not been entered. 3.1.4.5

Site Area (AreaSqMtrs)

-

Dimensions Table

The site area is the surface extent of the site, measured in square meters. The primary source of this data is the WIDS database. If the data were not directly available from WIDS, then the site area was 9

calculated from other site dimensions (i.e., site width and site length, or site diameter). If site dimension information was unavailable, then the area was estimated from the QMAP geospatial map portal or HGIS documentation (i.e., the HanfordSite Atlas [BH1 1998]). If data could not be found with which to estimate the site area, then the site was assigned a default value. Table 3.1 lists the default site area values used for different site types.

Table 3.1.

Default Site Areas

Site Type

Default Area

Unplanned Release, French Drain Storage Tank, Trench Radioactive Process Sewer, Crib Burial Ground

(in)

0.999 9.99 99.9 999

The site area is used to represent the footprint of the release area (e.g., the bottom area of a crib). However, a comparison of facility dimension information in WIDS with that by Maxfield (1979) suggests that the site area as recorded in WIDS is quite a bit bigger than the actual bottom area of the waste sites. It is believed that the site area represents the maximum surface extent of the facility, or perhaps even the fenced boundaries of the radiation zone surrounding the site. Thus, site area, as recorded in WIDS, may over estimate the actual footprint of the release area.

3.2

Model-Specific Instructions

This portion of GOSPL provides key model instructions for various components of the SAC system. This includes information regarding the release models and the vadose zone hydrogeologic templates.

3.2.1

Selected for Simulation in the 2004 Composite Analysis

This field identifies those sites that have been selected for simulation in the 2004 Composite Analysis. This field designates those sites selected for the 2004 Composite Analysis with a "1,"'while those that will not be simulated are designated with a "0" or left blank.

3.2.2

Release Model Designation

The Release Models field is used to identify the type of release model that will be used in the SAC simulations. The designation for each site is based in part on the site type (see Section 3.1.2. 1), the physical state of the waste (as taken from the PhysicalState field in the Waste Table of WIDS), and the material type (see Section 3.1.2.2). Table 3.2 lists the release model designations generally assigned by site type. Note that the release models assigned to each site are subjective in nature, based on best professional judgment, and may account for a combination of physiochemnical processes (i.e., multiple release models).

10

Table 3.2.

Summary of Release Model Assignments to Waste Source Types (after Riley and LoPresti 2004)

Release Model Atmosphere

]Site (waste source) Type JStacks

JExceptions

Liquid

Single-shell tanks, (a) unplanned releases, (b) trenches, cribs, drain/tile fields, radioactive process sewers, French drains, retention basins, ponds, ditches, sumps, injection/reverse wells, storage tanks, diversion boxes, catch tanks, valve pits, settling tanks, receiving vaults, and neutralization tanks

Receiving vault 241 -WR -Vault will be modeled using the cement model.

Soil-Debris

Unplanned releases, (b) sand filters, burial grounds, laboratories, storage, stacks,(') landfills, surplus production sites (i.e., the soil below and surrounding a site), storage tunnels

The GTF Landfill contains grouted waste, so the cement model should be applied. Site I 16-C-2C will be modeled as a liquid release.

Cement

Process unit/plants, control structures, cemented waste in burial grounds

_______________

Salt-cake

Single-shell tanks, (a) double-shell

Reactor Block(')

Decommissioned surplus production reactor cores

Glass~f)

Vitrified ILAW waste from single-shell tanks

River

Process sewer, outfall

tankS(d)

(a) Releases from single-shell tanks will be modeled using a combination of liquid, salt-cake, and/or diffusion (cement) models. Releases include past tank leaks, liquid released during retrieval and contaminant release from dissolution of residual solids following waste retrieval completion. (b) Modeled as initial liquid release, release from surface contaminated soil or a combination of both. (c) Modeled as initial atmospheric release, then as soil-debris following its operational period. (d) Double-shell tanks are assumed not to leak prior to and during retrieval. Release of contaminants fr-om residual solids modeled using salt-cake and/or diffusion (cement) model. (e) B reactor release occurs entirely in the 100 Area. Following a specified period of time (75 years). The remaining inventories for all other reactors are moved to a 200 Area burial ground where release continues using the reactor block model. (f) An empirical model that approximates the results from the ILAW STORM model, allowing SAC (VADER) to generate stochastic results through variation of recharge rate. GTE = Grout Treatment Facility. ILAW = Immobilized low-activity waste. STORM = Subsurface Transport Over Reactive Multiphases. VADER = Vadose Zone Environmental Release.

3.2.3

Vadose Zone Model Hydrostratigraphy

Each site contained in GOSPL was assigned to a general vadose zone hydrostratigraphic profile based on its location within one of 26 geographic areas (representing 17 general geographic areas and 9 sitespecific locations), its site type (surface, near surface, tank, or injection well), and its waste chemistry designation. Each hydrostratigraphic profile (template) identifies the hydraulic and geochemnical parameters necessary for STOMP to simulate the flow and transport through the vadose zone. As many as five variations of a single hydrostrati graphic template were incorporated to more accurately represent the depth of waste releases and the thickness of the vadose zone beneath the point of release. Additional 11I

variations of the hydrostratigraphic templates were necessary to accommodate variations in Kd values associated with different waste chemistry designations. Thus, a series of 63 base templates were ultimately identified using a unique alphanumeric code consisting of a three-digit number that reflects the waste site type, a letter designating the geographic area, and a number designating the waste chemistry group for assigning Kd values. Nine site-specific hydrostratigraphic templates were created by adding additional alphanumeric characters to the geographic area designation. These codes are explained below. A more complete discussion regarding the development of the vadose zone templates is provided by Last et al. (2004).

3.2.3.1

VZ (Vadose Zone) Template Site Type (reflecting the depth of waste injection)

The VZ Template Site Type Code (e.g., 216) generally consists of a three-digit number, with the first digit indicating the operational area in which the facility is located, and the second and third digits signifying the relative depth of waste release based on its facility type (such as 100-, 241-, 616-). This code is primarily derived from the WIDS SiteCode (see Section 3.1.1.2), the WIDS SiteType (see Section 3.1.2.1), the WIDS DepthHeightMtrs (see Section 3.1.4.3), and the WIDS Site Description (SiteDesc), which are used to classify the sites into six main categories reflecting the relative depth of waste release as defined in Table 3.3. This code identifies variants to the geographic area hydrostratigraphic columns to account for the thickness of the soil column beneath different waste release depths. Table 3.3. Site Type Code (a)

[ [

Site Type Codes Used in the Hydrostratigraphic Templates

Relative Depth of Waste Release

Representative WIDS SiteTypes

100,200, 300, 400

Ground Surface (generally less that 3 mn deep).

Surface and/or near surface facilities (e.g., process sewers, reactor buildings, laboratory buildings, storage, stacks, ponds, ditches, valve pits, process unit/plants, unplanned releases except tank leaks).

116, 216, 316, 616

Shallow Subsurface (generally 3-7 mn below ground surface)

Shallow liquid and/or dry waste disposal facilities (e.g., cribs, burial grounds, retention basins, trenches, French drains, storage tunnels, drain/tile fields, pipelines, sewers).

241

Intermnediate Subsurface (generally 9 to 17 mn below ground surface)

High level waste tanks, settling tanks, diversion boxes, catch tanks, tank leak unplanned releases.

166, 266

Deep Subsurface (generally greater than 18 mn below ground surface)

Deep injection sites (e.g., reverse wells)

276

Very Deep Subsurface (generally near or into the

Very deep injection sites (e.g., very deep reverse wells)

River(b)

water table) River Level

River outfalls and associated pipelines

(a) First digit represents the area: I = 100 Area, 2 200 Area, 3 = 3 00 Area, 4 = 400 Area, 6 = 600 Area. Second and third digits indicate the general facility type and relative release depth. (b) River outfall discharged waste directly to the river, thus there is no vadose zone flow and transport component for these sites. WIDS = Waste Information Data System. =

12

Geographic Area

3.2.3.2

Sixteen geographic areas were identified that could each be represented by a single generalized hydrostratigraphic column (Figure 3. 1). Each of the six 100 Areas were designated as separate geographic areas because each area is geographically distinct and have distinct hydrogeologic characteristics. The 200 Areas were divided into six aggregate areas based on differences in hydrogeologic characteristics. The 200 West and 200 East Areas were each divided into two geographic areas. Additional geographic areas were designated for the 200 North Area, Gable Mountain Pond area, and the B-Pond area. A single geographic area was designated to encompass waste sites in the 300 Area. Finally, three additional geographic areas were defined for isolated sites in the 400 and 600 Areas. Table 3.4 presents the letter designations and brief descriptions of each geographic area. Nine site-specific designations were created by adding additional alphanumeric characters to two of the geographic area designations (Table 3.5). Waste Chemistry Group (for assigning Kd ranges)

3.2.3.3

Six waste chemistry types were defined by Kincaid et a]. (1998) for use in the first composite analysis published in 1998. These waste chemistry types describe chemically distinct waste streams that impact the sorption of contaminants. These same waste chemistry designations were adapted for use in the initial assessment conducted using SAC to assign K,3 values to the vadose zone base templates (Bryce et al. 2002). However, based on the results of a recent compilation of contaminant distribution coefficients (Kd) for Hanford sediments (Cantrell et al. 2003a, 2003 b), the six waste stream categories used in these assessments were reduced to four (Table 3 .6 ).(a) Refer to the vadose zone data package (Last et al. 2004) for additional information regarding the assignment of these waste chemistry designations. VZ Base Templates

3.2.3.4

A total of 61 base templates were identified based on various combinations of the site types, geographic areas, and waste chemistry types. This field is calculated by combining the information from the VZ Template Site Type, Geographic Area, and Waste Chemistry data fields, unless the VZ Template Site Type is "River," in which case this field is calculated as "River." However, if the Site Type is blank or the site is not on the list of sites for the composite analysis (i.e., the On Composite Analysis List field is "0"), then this field is left blank. The general Excel formula used to calculate this field is as follows: =

where

A B C D

= = = =

IF(A =1, IF(B =" River", "River", IF(B

="........ B&

C&"-"&D)),""

On CA List Site Type Geographic Area Waste Chemistry Group.

(a) Cantrell KJ, RJ Seine, and GV Last. Waste Stream Descriptions, Impact Zones and Associated K,, Estimates Including Rational for Selections (Revision May 16, 2003).

13

1

200~10

o

Hs

Areaa

r

100E Are

r-tl,

Nortawes

r

400 Ara

10

-AreaAr

3,g

t.?dI SA D

Cit Rihlnd Lnfl

RiHand

Rivers/PondsnAreL T

ZIIBaal0Aov

Wt Table

~Site ArAre34am

0114

TEDF810

10 Ae

30 Are

Table 3.4. Designation A

Geographic Area Description Southern 200 East Area - encompassing the PUREX (A Plant), Hot Semi-Works (C-Plant), associated facilities (including PUREX tunnels), US Ecology, and the A, AN, AP, AW, AX, AY, C Tank Farms

___________AZ,

B

Northwestern 200 East Area - encompassing the B-Plant Area, associated waste disposal

_____________facilities,

C D E F G

Q R S T ERDF PUREX REDOX

and the B, BX, BY Tank Farms

100-B/C Area I00-D/DR Area East of 200 East - B-Pond Area 100-F Area Gable Mountain Pond Area 200 North Area

1_______

H K M N P

Geographic Area Designations Used in the Hydrostratigraphic Template Codes

100-H Area Il00-KE/KW Area 600 Area near Energy Northwest and the 618-Il burial ground 100-N Area 600 Area southwest of the 400 Area near the 618-1 0 burial ground 400 Area 300 Area (and a few isolated facilities in and near the 400 Area) Southern 200 West Area - encompassing the REDOX (S-Plant), U-Plant, Z-Plant associated facilities, ERDF, and the S, SX, SY, U Tank Farms Nor-thern 200 West Area - encompassing T Plant , associated facilities, and the T, TX, TY Tank Farms Environmental Restoration Disposal Facility. = Plutonium-Uranium Extraction (Plant). - Reduction Oxidation (Plant). =

Table 3.5. Designation

Site-Specific Area Designations Used in the Hy drostrati graphic Template Codes

ISite-Specific

Area Description

A BC W

Southern 200 East Area -representing the western portion of the BC cribs area

ABCE

Southern 200 East Area - representing the eastern portion of the BC cribs area

A BT N

Southern 200 East Area - representing the northern portion of the BC trench area

A BT S

Southern 200 East Area - representing the southern portion of the BC trench area

A BT W

Southern 200 East Area - representing the western portion of the BC trench area

AILAWC

Southern 200 East Area - representing the central portion of the ILAW/IDF site

S U N

Southern 200 West Area

-

representing the northern portion of the 216-U-I1 &2 crib area

S US

Southern 200 West Area

-

representing the southern portion of the 216-U-1&2 crib area

S Z9

Southern 200 West Area

-

representing the 21 6-Z-9 trench area

IDF ILAW

=

Integrated Disposal Facility. Immobilized low-activity waste.

15

Table 3.6.

Waste Chemnistry Groups Used in the Base Template Codes Waste Chemistry Designation

Waste Stream Description

I_________

Very Acidic

2

High Salt/Very Basic

3

Chelates/H-igh Salt

4

Low Salt/Near Neutral

Table 3.7 provides a description of the general hydrostratigraphic templates established for each geographic area. Table 3.8 describes the site-specific templates set up for a number of key facilities within two of these general geographic areas.

Table 3.7.

General Hydrostratigraphic Templates for Each Geographic Area

VZ Base Geographic Area DeintinArlnatin raDsinto emplnateo I100C-4 100 B/C C 11 6C-4

IOOD-4 1 16D-4

IOOF-4 116174 1OOH-4 116H-4 1OOK-4 11 6K-4 166K-4 1OON-4 11 6N-4 200G-4 2001-4 200E-4

_____

_____

Deigato

[Waste Destoyd Ch)eiton(d

100

4

116

4

100

4

Surface Facilities

116

4

100 116 100 116 100 116 166 100 116 200 200 200

4 4 4 4 4 4 4 4 4 4 4 4

Description

a

Surface Facilities Surface Facilities

___Near

100 D

Waste Site Types

D ___Near

Surface Facilities

100 F

F

100 H

H

100 K

K

100 N

N

Gable Mtn. Pond 200 North E 200 E

G I E

Surface Facilities Near Surface Facilities Surface Facilities Near Surface Facilities Surface Facilities Near Surface Facilities Reverse Wells Surface Facilities Near Surface Facilities Surface Facilities Surface Facilities Surface Facilities

N 200 E (B-Plant)

B

Surface Facilities

200

Near Surface Facilities

216

Tanks Reverse Wells

241 266

2 4 3 4 2 4

267'c)

2

_________(B-Pond)

200B-2 200B-4 21613-3 21 6B-4 241 B-2 26613-4 26713-2

______

____________

16

Table 3.7. (contd) VZ Base

Geographic Area

Template Designation 200A-2 200A-4 21 6A-2 216A-4 241 A-2 241 A-3 266A-4

200S-2 200S-4 216S-1 2 16S-2 216S-4 241S-2 241S-3 241S-4 266S-4

Area S 200 E (PUREX, BC Cribs)

TWaste Site Types

1b) jDesignation (a) I A

Description

200

Near Surface Facilities

216

Tanks

241 Wells

River

-

300 Area (North Richland 400 600 600

4

2 4

Surface Facilities

200

S

Near Surface Facilities

2161

241

2 4 2 3 4

266

4

Surface Facilities

200

Near Surface Facilities

216

Tanks Reverse Wells

241 266

Surface Facilities Near Surface Facilities Surface Facilities Near Surface Facilities Near Surface Facilities

300 316 400 616 616

2 4 2 3 4 2 2 4 4 4 4 4 4

-

-

Wells

__________Reverse

N 200 W (T-Plant)

T

R

Q M P

2 4 2 4 2 3

266

S

Tanks

200T-2 200T-4 21 6T-2 216T-3 21 6T-4 241 T-2 266T-2 266T-4 300R-4 316R-4 400Q-4 616M-4 616P-4

Chemistry(d

Designation~~ Designationd

Surface Facilities

__________Reverse

S 200 W (REDOX, U-Plant, Z-Plant) S 200 W (REDOX, U-Plant, Z-Plant)

Waste

River

(a) Assigned letter designation for geographic area. (b) Assigned number designation for waste site type: first number designates traditional Hanford Site area (i.e., 100, 200, 300, 400, 600 Areas); last two numbers designate waste site type (00 =surface facilities, 16 near surface facilities, 41 tanks, 66/67 - reverse wells) (c) Two designations are used for reverse wells that have very different depths within a single geographic area. The "~67" designation distinguishes the very deep reverse wells from those at a more intermediate depth (66). (d) Assigned number designation for waste chemistry type (see Table 3.6). PUREX = Plutonium-Uranium Extraction (Plant). REDOX = Reduction Oxidation (Plant). =

=

17

Table 3.8. Tepae

Templa[ Designation 216ABCW-3 216ABCE-3 216A BTN-3 21AT_-

Site-Specific Templates Established for a Few Key Facilities

bSite-Specific

IArea S 200 E, BC Cribs, Western Portion S 200 E, BC Cribs, Eastern Portion S 200 E, BC Trenches, Northern Portion

Area

Waste Site TypesWat

Designation (a) A_BC_W A_BC_E A BTN

Description

[Designation(b)

Chemistry Designation (d)

Near Surface Facilities Near Surface Facilities Near Surface Facilities4

216

3

216

3

216

3

216ABTS-3

S 200 E, BC Trenches, Southern Portion

A_BT_S

Near Surface Facilities

216

3

216ABTW-3

S 200 E, BC Trenches, Western Portion S 200 E, ILAW Site, Central Portion

A_BT_W

Near Surface Facilities Near Surface Facilities

216

3

216

3

S 200 W, 216-U-l1&2 Area, Northern Porti on S 200 W, 216-U-1&2 Area, Northern Portion

SUN

Near Surface Facilities Near Surface Facilities

216

4

216

4

216AILAWC-3 216SUN-4 216SUS-4

AILAWC

SUS

216SZ9-l

S 200 W, 216-U-1&2 S_Z9 Near Surface 216 1 Area, Northern Portion Facilities (a) Assigned letter designation for geographic area. (b) Assigned number designation for waste site type: first number designates traditional Hanford Site area (i.e., 100, 200, 300, 400, 600 Areas); last two numbers designate waste site type (00 = surface facilities, 16 - near surface facilities, 41 =tanks, 66/67 = reverse wells) (c) Two designations are used for reverse wells that have very different depths within a single geographic area. The -67" designation distinguishes the very deep reverse wells from those at a more intermnediate depth (66). (d) Assigned number designation for waste chemistry type (see Table 3.6). ILAW = Immobilized low-activity waste.

3.2.3.5

Site Template

The Site Template uniquely identifies the site for the set of geographic and operational parameters to be used for the vadose zone simulations. For the 2004 Composite Analysis, this field is identical to that of the WIDS Site Code (see Section 3.1.1.2). However, this field has been used to aggregate multiple sites to a single template.

3.3

Remediation/Recharge Assumptions

This portion of GOSPL provides key assumptions regarding the surface soil conditions and deep drainage (recharge) at each waste site. These soil conditions and recharge estimates were derived from a suite of available field data and computer simulation results and assembled into a suite of recharge classes that describe the probability distribution function for recharge at the site. Recharge classes are defined for

18

a number of different time intervals: Pre-Hanford, Operations, Post-Rem ed iation, and Post-Hanford. Each recharge class was identified with a unique code based on either the primary native soil and vegetation type or the type and size of the surface barrier. Refer to the vadose zone data package (Last et al. 2004) for details.

3.3.1

Pre-Hanford Recharge Class

This field defines the recharge class to be applied to the simulations for the timne period prior to the establishment of the Hanford Site in 1943. The source of this informnation is the vadose zone data package (Last et al. 2004), which generally assumed a natural soil cover with undisturbed shrub-steppe plant community and based on the Hanford soil map produced by 1-ajek (1966). Table 3.9 lists the PreHanford Recharge Classes used for the 2004 Composite Analysis.

Table 3.9.

Pre-Hanford Recharge Classes for the 2004 Composite Analysis

I

Estimated

Best Estimate

Recharge Class Code

j(mm/yr)

Description

Standard Deviation (mm/yr)

Minimum (mm/yr)

Maximum (mmlyr)

Eb-s

Ephrata stony loam (Eb) - with shrub-steppe (s) plant community

1.5

0.75

0.75

3.0

El-s

Ephrata sandy loam (El) plant community

1.5

0.75

0.75

3.0

Ba-s

Burbank loamy sand (Ba) - with shrub-steppe (s) plant community

3.0

1.5

1.5

6.0

Rpe-s

Rupert sand (Rp) in 200 East (e) - with shrubsteppe (s) plant community

0.9

0.45

0.45

1.8

Rp-s

Rupert sand (Rp) outside 200 East - with shrubsteppe (s) plant community

4.0

2.0

2.0

8.0

River

Assumes discharge directly to the river, no release or vadose zone modeling is required, so recharge rates are not applicable.

NA

NA

NA

NA

NA

=

3.3.2

-

with shrub-steppe (s)

Not applicable.

Operational Recharge Class

This field defines the recharge classes to be used for simulations for the time period during and after site operations, prior to any site remediation. Once again, the source of this information comes directly from the vadose zone data package (Last et al. 2004). This generally assumes that the site is covered by native soils or backfilled soils with or without vegetation; asphalt, buildings, concrete, or gravel covers. Table 3. 10 lists the Operational Recharge Classes used for the 2004 Composite Analysis.

19

Table 3.10.

Operational Recharge Classes for the 2004 Composite Analysis

Recharge Class Code Eb-dn

Best Estimate (mm/yr)

Description Ephrata stony loam (Eb), disturbed (d) - with no

Estimated Standard Deviation (mm/yr)

Minimum (mm/yr)

Maximum (mm/yr)(a)

17

8.5

8.5

34

17

8.5

8.5

34

(n) vegetation_____

EI-dn

Ephrata sandy loam (El), disturbed (d) (n) vegetation

Ba-dg

Burbank loamy sand (Ba), disturbed (d) - with cheatgrass (g) plant community

26

13.0

13.0

52

Ba-dn

Burbank loamy sand (Ba), disturbed (d) - with no (n) vegetation

53

26.5

26.5

101

Rpe-dn

Rupert sand (Rp) in 200 East, disturbed (d) no (n) vegetation

44

22

22

88

Rp-dn

Rupert sand (Rp) outside 200 East, disturbed (d) with no (n) vegetation Gravel surface (G), disturbed - with no (n) vegetation

44

22

22

88

89

44.5

44.5

G-dn

-

with no

-

with -

ABC

Soil Surface covered by Asphalt, Building, or Concrete

River

Assumes discharge directly to the river, no release or vadose zone modeling is required, so recharge rates are not applicable.

0.1 NA

0.05 NA

0.05 NA

101 0.2 NA

(a) Note: the maximum recharge was truncated at the mean extended winter precipitation value of 10 1 mm/yr. NA - Not applicable.

3.3.3

Interim Remedial Actions (IRA-i and IRA-2)

Interim remedial actions (IRA) have been identified or proposed for some sites. Currently, GOSPL is configured to handle two different interim remedial action events (I RA-lI and IRA-2). For these particular sites, three additional fields have been defined (Year Interim Remedial Action Complete, Interim Remedial Action Type, and Interim Barrier/Soil Cover Type) for each remedial action event defined. The primary source of this inform-ation was from Maxfield (1979) or the WIDS database (via the Hanford Site Waste Management Units Report [DOE 2003]). An example for the BC cribs and trenches is shown in Table 3.11, with the fields in that table as defined below.

3.3.3.1

Year Interim Remedial Action Complete (year IRA-I complete; year IRA-2 complete)

This field defines the year that the interim remedial action was completed.

20

Table 3.11.

WIDS Site Code

Example of Interim Remedial Actions Defined for the 2004 Composite Analysis

IIRA-] IfBarrier/Soil Year

Complete

Type

216-B-14

1981

ABAR

216-B-20

1969

ABAR

[Type

[ [

Rp-ds

G-dn

IRA-2 IBarrier/Soil Complete j Type [Type ]______I____________ ] 1982 J ABAR [ Rpe-ds Year

ABAR =Aggregate barrier. IRA =Interim remedial actions. WIDS = Waste Information Data System. 3.3.3.2

Interim Remedial Action Type (IRA-I type, IRA-2 type)

This field defines the type of interim remedial action that was taken at the site. For the 2004 Composite Analysis, this includes: (I) remove, treat, and dispose (RTD) or (2) surface stabilization (e.g., aggregate barrier [ABAR], isolated barrier [IBARI). 3.3.3.3

Interim Barrier/Soil Type (recharge class) (IRA-i barrier/soil type; IRA-2 barrier/soil type)

This field, when populated, defines the recharge class to be applied to the site during thle period after interim remediation and prior to any other interim remediation or final site remediation. For the 2004 Composite Analysis only three IRA recharge classes have been identified, G-dn (as described in Table 3. 10) and Rp-ds and Rpe-ds (as described in Table 3.12). 3.3.4

Remediation

Some form of remnediation (or no action) was identified for each site. A number of data fields were used to define the recharge classes to be used during the period following remediation and prior to the long-term post-remediation/closure design-life. The primary source of this information comes from the Hanford Disposition Baseline and Kincaid et al. (2004). These sources determined the schedule and type of remediation (e.g., engineered surface barriers) to be applied to each site for the 2004 Composite Analysis. The vadose zone data package (Last et al. 2004) describes the assumptions regarding the recharge rates to be used for barriers during the institutional control period, their design life, and after their design life. A key assumption of the 2004 Composite Analysis is that deep drainage beneath barrier side slopes and the surrounding terrain does not appreciably affect contaminant release from immediately below the barrier, nor transport in the vadose zone to the water table. This assumption is consistent with the previous composite analysis as well as recent and ongoing assessments. 3.3.4.1

Year Remedial Action Complete

This field defines the planned (or actual) year that remediation will be (or was) completed at the site. This assumes that all remnedial action for that particular site is completed within a given year. For those sites slated for no further action, a value of "NA" was used, indicating that the recharge class would not change from its pre-remediation time period.

21

3.3.4.2

Remediation Type

This field identifies the type of remedial action planned (or completed) for the site, including: no action; decontamination and decommissioning (D&D); remove, treat, and dispose (RTD); isolated barriers (IBAR), or aggregate barriers (ABAR). This field identifies a number of different aggregate barriers defined by a unique alphanumeric code, with the same code assigned to all sites to be covered by the same aggregate barrier. 3.3.4.3

Barrier Type

This field identifies the type of barrier planned (or completed) for the site. If the remediation type is anything other than an MBAR or ABAR, then this field is blank. Otherwise this field contains either Resource Conservation and Recovery Act (RCRA) C or Hanford to designate the two types of surface barriers currently planned for Hanford waste sites. 3.3.4.4

Barrier Infiltration Class

This field assigns an infiltration (recharge) class to those sites that are to receive a surface barrier. If the remediation type (Section 3.3.6.2) is anything other than an IBAR or ABAR, then this field is blank. Otherwise this field is calculated from a lookup table of barrier infiltration classes based on the estimated barrier top-to-side slope ratio. It was developed to help address the possible effects of side slopes on barrier recharge rates. However, for the 2004 Composite Analysis it is assumed that deep drainage beneath the barrier side slopes and the surrounding terrain does not appreciably affect contaminant release and transport (Last et al. 2004). Thus far, for the baseline case of the 2004 Composite Analysis, the actual values in this field are of no consequence. These infiltration assignments that account for side slope influence may be used in a sensitivity case. 3.3.4.5

Post Remnediation Recharge Classes

This field provides the recharge class to be used for the post-remediation time period (i.e., following site remnediation and prior to any soil/barrier evolution/degradation). This field is calculated by comnbining the information from the Barrier Type and Barrier Infiltration Class, if the Barrier Type is not blank, or by modifying the inforiation in the Pre-Operations Recharge Class to replace the suffix with "-ds"' (to reflect disturbed shrub-steppe vegetation). If the VZ Template Site Type is "River," then this field is calculated as "River." The general Excel formula used to calculate this field is as follows: =1"", JF(B ="River",""River", REPLA CE(C, SEARCH("-", C,l),2, "-c/s')), D&" -"&A)

=IF(A

where

A B C D

= = = =

Barrier Infiltration Class Vadose Zone Template Type Pre-Operations Infiltration Class Barrier Type.

22

(2)

Table 3.12 lists the post- remed iation recharge classes for the composite analysis. Note that for this composite analysis all sizes of RCRA C and Hanford Barriers have the same estimated recharge rates (i.e., there are no side-slope effects). Refer to the vadose zone data package (Last et a]. 2004) for further discussion.

Table 3.12.

Post- Remediation Recharge Classes

1 Best Estimate

Recharge ClssCoe

esritin(mm/yr)

Estimated Standard Deviation (mm/yr)

Minimum (mm/yr)

Maximum (mm/yr)

RCRA C-lxx

Modified RCRA C - barrier top during design life

0.1

0.05

0.05

0.20

Hanfordlxx

Hanford Barrier

barrier top during design life

0.1

0.05

0.05

0.20

Ba-ds

Burbank loamy sand (Ba), disturbed (d) - with young shrub-steppe (s) plant community

6.0

3.0

3.0

12

Eb-ds

Ephrata stony loam (Eb), disturbed (d) - with young shrub-steppe (s) vegetation

3.0

1.5

1.5

6.0

El-ds

Ephrata sandy loam (El), disturbed (d) young shrub-steppe (s) vegetation

3.0

1.5

1.5

6.0

Rp-ds

Rupert sand (Rp) outside 200 East, disturbed (d) with young shrub-steppe (s) plant community

-

8.0

4.0

4.0

16.0

Rpe-ds

Rupert sand (Rp) in 200 East, disturbed (d) young shrub-steppe (s) plant community

with

1.8

0.9

0.9

3.6

River

Assumes discharge directly to the river, no release or vadose zone model Ing is required, so recharge rates are not applicable.

NA

NA

NA

-

-

with

-

NA

NA - Not applicable.

3.3.4.6

Post-Remediation/Barrier Design Life

This field defines the design life of the post-remediation period (i.e., that period after remediation is complete and prior to any significant degradation of the surface soils (e.g., barrier) or succession of plant communities). Table 3.13 lists the Post- Remediation/Barrier Design Life.

23

Table 3.13.

Post-Remediation/lBarrier Design Life

Post-Remediation Soil Conditions (recharge classes)

[

Design Life (years)

Native soil with young shrub-steppe plant community (Ba-ds, Eb-ds, EI-ds, Rp-ds, Rpe-ds)

30 ___________

RCRA C surface barrier Hanford surface barrier River NA = Not applicable. RCRA = Resource Conservation and Recovery Act. 3.3.4.7

500 1,000 NA

Barrier End Date

This field defines the date at which the post-remediation recharge period ends and the final long-term recharge period begins. This field is calculated by adding the Design Life to the Year Remedial Action Complete. However, if the Release Model Designation is "River," then this field is calculated as "NA," or if the Year Remedial Action Complete field is "NA," then this field is calculated as "201 0." The general Excel formula used to calculate this field is as follows: =

where

3.3.4.8

A B C

= = =

JF(A

="

River",,"NA", IF(B =" NA",20 10, B + C))

(3)

Release Model Designation Year Remedial Action Complete Post-remediation/Barrier Design Life.

Final Long-Term Recharge Class

This field defines the final long-term recharge class to be used for the final simulation period. This field is calculated as being equal to the Pre-Operational Infiltration Class.

4.0

Conclusions and Recommendations

A composite analysis is required by U.S. Department of Energy (DOE) Order 435.1 to ensure public safety through the managemnent of active and planned low-level radioactive waste disposal facilities associated with the Hanford Site. Kincaid et a]. (2004) indicated that the System Assessment Capability (SAC) (Kincaid et al. 2000; Bryce et al. 2002; Eslinger 2002a, 2002b) would be used for the analysis. They also identified 1,046 waste sites from the 2,730 WIDS sites and several existing and future storage sites for inclusion in the 2004 Composite Analysis. Each of these sites will be handled as an individual release or storage site whenever inventory and release data permit.

24

A number of pieces of information, such as the site identification, coordinates, release model, hydrogeologic column (template), remediation action, infiltration class, and the start time and stop time of a simulated problem, are needed for the numerical assessment. The ESD keyword file was designed to contain this common information. Generally, if inform-ation is needed by one or more module of the suite of codes used by SAC, it is entered in the ESD keyword file. A number of the ESD keywords are generated from general informnation on the waste site, its operational/disposal history, and its environmental settings (past, current, and future). To facilitate the generation of these ESD keyword input files, a master spreadsheet termed the Geographic and Operational Site Parameters List (GOSPL) was assembled. It can generally be subdivided into three main sections: Site-Specific Parameters, Model-Specific Instructions, and Remnedilation/Inf iltration Assumptions. This report briefly describes each of the key data fields, including the source(s) of data, and provides the inputs to be used for the 2004 Composite Analysis. This master spreadsheet was originally developed for the initial assessments conducted using the SAC to lock down the site-specific location and facility design parameters as well as the key model assumptions for each assessment. GOSPL has continued to evolve as the site information and/or assessment basis has changed. It is recommended that a complete restructuring of GOSPL be developed to interactively retrieve data directly from the record databases (e.g., WIDS) and to streamline the selection of sites and model assumptions.

5.0

References

BHI. 1998. Hanford Site Atlas. BHI-01 119, Rev. 1, Bechtel Hanford Inc., Richland, Washington. Bryce RW, CT Kincaid, PW Eslinger, and LF Morasch (eds.). 2002. An Initial Assessment of Hanford Impact Performed with the System Assessment Capability. PNNL-14027, Pacific Northwest National

Laboratory, Richland, Washington. Cantrell KJ, Ri Seine, and GV Last. 2003a. Hanford Contaminant Distribution Coefficient Database and Users Guide. PNNL- 13895, Rev. 1, Pacific Northwest National Laboratory, Richland, Washington. Cantrell KJ, RJ Seine, and GY Last. 2003b. Applicability of the Linear Sorption Isotherm Model to Represent Contaminant Transport Processes in Site- Wide Performance Assessments

-

A White Paper.

CP- 17089, Fluor Hanford, Inc., Richland, Washington. Comprehensive Environmental Response, Compensation, and Liability Act. 1980. Public Law 96-150, as amended, 94 Stat. 2767, 42 USC 9601 et seq. DOE. 2003. Haqford Site Waste Management Units Report. DOE/RL-88-30, Rev. 12, U.S. Department of Energy, Richland, Washington (http://apweb02 .ri.gov/rapidweb/phmc/cp/wids/index2.cfi-n .cfm?FileNaine=/docs/5/docs/RI 88-30ORlII.pdf)

25

DOE Order 435.1. 1999. Radioactive Waste Management. U.S. Department of Energy, Washington, D.C. Available on the Internet at http://www.hanford.gov/wastemgt/doe/psg/pdf/doe0435.pdf Eslinger PW, DW Engel, LH Gerhardstein, CA Lo Presti, WE Nichols, and DL Strenge. 2002a. User Instructions for the Systems Assessment Capability, Rev. 0, Computer Codes, Volume ]: Inventory,

Release, and Transport Modules. PNNL- 1393 2, Volume 1, Pacific Northwest National Laboratory, Richland, Washington. Eslinger PW, C Arimescu, DW Engel, BA Kanyid, and TB Miley. 2002b. User Instructionsfor the Systems Assessment Capability, Rev. 0, Computer Codes, Volume 2:- Impacts Modules. PNNL- 13932, Volume 2, Pacific Northwest National Laboratory, Richland, Washington. Hajek BF. 1966. Soil Survey Hanford Project in Benton County, Washington. BNWL-243, Pacific Northwest Laboratory, Richland, Washington. Kincaid CT, MP Bergeron, CR Cole, MD Freshley, NL H-assig, VG Johnson, DI Kaplan, RI Seine, GP Streile, DL Strenge, PD Thome, LW Vail, GA Whyatt, and SK Wurstner. 1998. Composite Analysis ,for Low-Level Waste Disposal in the 200 Area Plateau of the Hanford Site. PNNL-1 1800, Pacific Northwest National Laboratory, Richland, Washington. Kincaid CT, PW Eslinger, WE Nichols, AL Bunn, RW Bryce, TB Miley, MC Richmond, SF Snyder, and RL Aaberg. 2000. Groundwater!Vadose Zone Integration Project, System Assessment Capability (Revision 0), Assessment Description, Requirements, Software Design, and Test Plan. BHI-0 1365, Draft A, Bechtel Hanford, Inc., Richland, Washington. Kincaid CT, RW Bryce, and JW Buck. 2004. Technical Scope and Approach./br the 2004 Composite Analysis of Low-Level Waste Disposal at the Hanford Site. PNNL-143 72, Pacific Northwest National Laboratory, Richland, Washington. Last GV, EJ Freeman, KJ Cantrell, MJ Fayer, GW Gee, WE Nichols, and BN Bjomstad. 2004. Vadose Zone Hydrogeology DataPackage for the 2004 Composite Analysis. PNNL-14702, Rev. 0, Pacific Northwest National Laboratory, Richland, Washington. Mann FM. 2003. Annual Summary of the Immobilized Low-Activity Waste Performance Assessment for 2003, Incorporatingthe IntegratedDisposal FacilityConcept. DOE/ORP-2000-19, Revision 3, U.S. Department of Energy, Richland, Washington. Maxfield HL. 1979. Handbook - 200 Areas Waste Sites. RHO-CD-673, Volumnes 1,11, and 111, Rockwell Hanford Operations, Richland, Washington. Resource Conservation and Recovery Act. 1976. Public Law 94-5 80, as amended, 90 Stat. 2795, 42 USC 6901 et seq. Riley RG and C Lo Presti. 2004. Release Model Data Packagefor the 2004 Composite Analysis. PNNL- 14760, Rev. 0, Pacific Northwest National Laboratory, Richland, Washington.

26

Appcndix

Geographic and Operational Site Parameters for Waste Sites To Be Simulated in the 2004 Composite Analysis

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PNNL-14725, Rev. 0

Distribution No. of

No. of

Copies

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ONSITE

J. V. Borghese F. M. Coony B. H. Ford T. W. Fogwell R. Jackson V. J. Rohay L. C. Swanson M. E. Todd-Robertson

2 DOE Office of River Protection R. M. Yasek R. W. Lober 9

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K3-54 K6-04 K9-36 K6-81 E6-35 K6-85 K6-81 K6-81 K6-75 K6-85 K5-12 K6-04 K9-33 K9-36 K9-33 K9-33 K6-81 K6-81 K9-33 K6-81 K5-12 K6-81 K6-04 K6-81

PNNL-14725, Rev. 0 No. of Copies

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PNNL-14753, Rev. 0

Groundwater Data Package for the 2004 Composite Analysis

P. D. Thorne

August 2004

Prepared for the U.S. Department of Energy under Contract DE-AC06-76RL01 830

DISCLAIMER This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor Battelle Memorial Institute, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof.

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PNNL- 1475' , Rev. 0

Groundwater Data Packagc for thc 2004 Composite Analysis

P. D. Thorne

August 2004

Prepared for the U.S. Department of Energy under Contract DE-AC06-76RL01 83 0

Pacific Northwest National Laboratory Richland, Washington 99352

Summary A composite analysis is required by U.S. Department of Energy (DOE) Order 435.1 to ensure public safety through the management of active and planned low-level radioactive waste disposal facilities associated with the Hanford Site. The original composite analysis performed in 1998 must be revised because of updated waste site information, updated performnance assessments and environmental impact statements, changes in inventory estimates for key sites and constituents, and a change in the definition of offsite receptors. Beginning in fiscal year 2003, the DOE Richland Operations Office initiated activities, including the development of data packages, to support the composite analysis. This report presents data and interpreted information that supports the groundwater module for the composite analysis. The objective of the groundwater module is to predict movement of radioactive and chemical contaminants through the aquifer to the Columbia River or other potential discharge locations. Future contaminant concentrations in groundwater also need to be known for any location where groundwater may be acquired from watersupply wells. For the composite analysis, this includes all areas outside of the "Core Zone" surrounding the 200 Areas. The Core Zone is assumed to remain under institutional control for the foreseeable future and it is assumed that water supply wells in this zone will be prohibited. The groundwater module will provide estimates of contaminant concentrations over the time period of the analysis within the unconfined aquifer underlying the Hanford Site outside of the Core Zone. These concentrations will provide the basis for the estimated impact to human health and supplemental ecosystem risk. The groundwater module will also provide predictions of contaminant mass and volumetric flux to the Columbia River over time for the period of analysis. The groundwater prediction for the composite analysis will be for radionuclide contaminants. Chemical contaminants will be simulated as an additional effort to provide perspective to stakeholders, regulators, and Tribal Nations. This report presents data and information that supports the groundwater module. The conceptual model of groundwater flow and transport at the Hanford Site is described and specific information applied in the numerical implementation module is provided.

Contents Summary......................................................................................................

iii

1.0

Introduction............................................................................................

1.1

1.1 Purpose............................................................................................

1.1

1.2

1.1

Scope..............................................................................................

1.3 Requirements/Assessment Basis................................................................... 2.0 Background..............................................................................................

1.2 2.1

2.1

Implementation Model..............................................................................

2.1

2.2

Uncertainty...........................................................................................

2.2

2.3

Continuing Model Improvements .................................................................

2.2

2.4

Interaction with Other SAC Modules..............................................................

2.2

3.0 Model Input Parameter Requirements...................................................................

3.1

4.0 Data Gathering Methods................................................................................

4.1

5.0 Data and Information for the Groundwater Module....................................................

5.1

5.1

Groundwater Flow System .........................................................................

5.2 Hydrogeologic Units of the Unconfined Aquifer System ....................................... 5.3

Boundary Conditions.............................................................................. 5.3.1 Columbia River Boundary ................................................................. 5.3.2 Yakima River Boundary.................................................................... 5.3.3 Natural Surface Recharge at Upper Boundary ........................................... 5.3.4 Recharge Along Western Model Boundary and Basalt Subcrops ..................... 5.3.5 Artificial Recharge at Upper Boundary ................................................... 5.3.6 Lower Model Boundary.................................................................... 5.3.7 Discharge from Onsite Wells ..............................................................

5.4 Hydraulic Property Parameters....................................................................

V

5.1 5.3 5.7 5.10 5.12 5.13 5.15 5.16 5.17 5.17 5.18

5.5

6.0

Contaminant Transport Parameters................................................................

5.21

5.6 Contaminant Data for Groundwater...............................................................

5.24

References..............................................................................................

6.1

Figurcs Location of the Core Zone...............................................................................

1.2

5.1

Extent of Regional and Local Groundwater Flow Systems Beneath the Hanford Site............

5.2

5.2

Schematic Cross Section of the Pasco Basin ..........................................................

5.3

5.3

Cross-Sections Showing Distributions of Hydrogeologic Units Below the Maximum Water Table Elevation Along A-A' and B-B'..........................................................

5.4

5.4

Distribution of Hydrogeologic Units at the Top of the Model .......................................

5.5

5.5

Distribution of Hydrogeologic Units Present at the Water Table for 1944 Conditions ...........

5.6

5.6

Distribution of Boreholes Used to Determine Hydrogeologic Structure for the Composite Analysis Groundwater Model...........................................................................

5.8

5.7

Groundwater Model Grid and Lateral Boundary Conditions.........................................

5.9

5.8

Hanford Site and Outlying Areas Water Table Map, March/April 2000 ..........................

5.11

5.9

Estimates of Natural Recharge Based on 1979 Vegetation and Land-Use Patterns Without Considering Anthropomorphic Alternation ...........................................................

5.14

.1

5.10 Artificial Discharges to the Unconfined Aquifer from 1943 to 1998 ..............................

5.16

5.1 1 Hydraulic Conductivity Distribution for Units at Top of Model ....................................

5.19

5.12 Cross Section of Model Along A-A' Showing Distribution of Hydrogeologic Units and Hydraulic Conductivity................................................................................

5.20

5.13 Cross Section of Model Along B-B' Showing Distribution of Hydrogeologic Units and Hydraulic Conductivity................................................................................

5.21

vi

Tables 4.1

Summary of Groundwater Data and Information Supporting the Composite Analysis Groundwater Model...................................................................................

4.1

5.1

Fluxes from Four Recharge Sources Resulting from Transient Calibration.......................

5.2

Ranges of Hydraulic Property Values Applied to Each Composite Analysis Model Unit ....... 5.18

5.3

Dispersivity Values Used in the Composite Analysis Groundwater Transport Model ...........

5.22

5.4

Half-Lives and Specific Activities for Radioactive Contaminants ..................................

5.23

5.5

Distribution Coefficients and Effective Retardation Factors ........................................

5.23

vii

5.15

1.0

Introduction

This report presents data and interpreted information that supports the groundwater module of the System Assessment Capability (SAC) as applied to the Hanford Site Composite Analysis. The composite analysis is an assessment of the cumulative impact from all sources of radioactive contamination, including present and future low-level waste disposal facilities, on the radiation dose to future members of the public (Kincaid et al. 2004). At the Hanford Site, a composite analysis is required for continued disposal of radioactive waste at several existing and planned facilities that are critical for site cleanup. The SAC is an integrated assessment tool that includes several linked computer models designed to simulate the movement of contaminants from waste sites through the vadose zone, groundwater, and Columbia River to receptors. It also incorporates modules that calculate the risks to human health and the environment. Background information on the development of the SAC is presented in Preliminary System Assessment Capability Concepts for Architecture, Platform and Data Management and Kincaid et al. (2000). A discussion of an initial assessment performed with the SAC is presented in Bryce et al. (2002).

1.1

Purpose

The objective of the groundwater module is to predict movement of radioactive and chemical contaminants through the aquifer to the Columbia River or other potential discharge locations. Future contaminant concentrations in groundwater also need to be known for any location where groundwater may be acquired from water-supply wells. For the composite analysis, this includes all areas outside of the "Core Zone" surrounding the 200 Areas (Figure 1.1). The Core Zone is assumed to remain under institutional control for the foreseeable future, and it is assumed that water supply wells in this zone will be prohibited (Kincaid et al. 2004). The groundwater module will provide estimates of contaminant concentrations over the time period of the analysis within the unconfined aquifer underlying the Hanford Site outside of the Core Zone. These concentrations will provide the basis for the estimated impact to human health and supplemental ecosystem risk. The groundwater module will also provide predictions of contaminant mass and volumetric flux to the Columbia River over time for the period of analysis. The groundwater prediction for the composite analysis will be for radionuclide contaminants. Chemical contaminants will be simulated as an additional effort to provide perspective to stakeholders, regulators, and Tribal Nations.

1.2

Scope

The scope of the groundwater module is limited to the unconfined aquifer system within sediments overlying the Columbia River Basalts. The unconfined aquifer system includes some aquifer sediment that is locally confined beneath relatively extensive Ringold Formation mud units. However, the permeable Ringold sediment is interconnected on a site-wide scale. Confined aquifers within the

Proposed Line for Core Zone to Include Main B Pond I - -- - -- - -

200 -WestI Area

11----

--

~ BC

Cribs

S Ponds -

~

/Ecology

Proposed Line for Core Zone to Include S Ponds

ECare

Zone of Central Platea u Core Zone Boundary Proposed Segments of Care Zone

o

W 05

6o 0oo

00~f

02'O 11

2 3

3

P111

Figure 1.1. Location of the Core Zone Columbia River Basalt are not included in the scope of composite analysis simulations. However, potential impacts from groundwater contaminants within the basalt-confined aquifers have been considered in other studies (Spane and Webber 1995; Thorne 1998; Newcomer et al. 2002). Although some Hanford Site contaminants have been found within the basalt-confined aquifers, the concentrations are much lower than those found in the overlying sedimentary aquifer. Therefore, the maximum impact is predicted without including the small mass of contaminants in the basalt-confined aquifer system. Groundwater simulations will extend through the year 3035, thereby including the 1,000 years following an assumed Hanford Site closure date of 2035 as required by U.S. Department of Energy (DOE) Order 43 5.1 (Kincaid et al. 2004).

1.3

Requirements/Assessment Basis

The objectives, requirements, assessment basis, and scope of the composite analysis are presented in Kincaid et at. (2004). They also describe the modified data quality objectives process applied to the composite analysis.

1.2

2.0

Background

Data presented in this report supports a conceptual model of groundwater flow. The conceptual model is a working description of the characteristics and processes that describe the dynamics of the physical and chemical hydrogeologic system. The conceptual model must be consistent with available data and understanding. Assumptions are made to define the conceptual model where information is lacking. However, assumptions must also be consistent with available data and understanding of the groundwater flow system.

2.1

Implementation Model

An "implementation model" was developed based on the conceptual model and incorporated simplifications where needed and appropriate. For example, groundwater-river interactions have been implemented in the model using a specified-head boundary where head in the Columbia River does not change over time. The simplification of the boundary condition would be part of the description of the implementation model. However, the actual groundwater-river interactions, which are affected by both annual and daily fluctuations of river stage, are described in the conceptual model. This simplification is appropriate because only long-term transport to the river is being evaluated in the composite analysis and the effect of short-term river-stage fluctuations is expected to be small. Assumptions, parameters, and even processes in an implementation model may conflict with the available information regarding local details. This is part of the spatial and temporal aggregation process associated with choosing the appropriate simplifications needed to model complex systems (Cole et al. 2001 a). The groundwater flow model used to simulate contaminant transport for the composite analysis is based on the three-dimensional model presented in Cole et al. (2001Ib). This Hanford site-wide groundwater model has evolved over the past 30 years. A two-dimensional model was initially developed in the 1970s. In the 1980s, work began on building two- and three-dimensional models using the Coupled Fluid, Energy, and Solute Transport (CFEST) code (Gupta 1997). Historical development and earlier calibrations of the CFEST model are described in Chapter 5 of Evans et al. (1989) and in Wurstner et al. (1995). The CFEST code was also used to implement the groundwater flow and transport model used for the composite analysis. For the composite analysis, the model grid used to simulate transport was refined to reduce errors caused by "numerical dispersion" and permit the use of lower values for hydrodynamic dispersion parameters. The model was calibrated to transient head conditions using an automated inverse modeling technique as described in Cole et al. (2001ib). Calibration of the model matched model-predicted hydraulic heads to historical observations of hydraulic head from 1944 through 1996. The transient calibration process included the discharge of large volumes of wastewater to a variety of waste facilities during this period, which caused changes in hydraulic head over parts of the Hanford Site. This artificial recharge to the aquifer raised the water table and created groundwater mounds near discharge facilities. In 1988, the change in Hanford's mission from weapons production to environmental restoration resulted in a reduction in wastewater discharges and significant declines in hydraulic heads.

2.1

2.2

Uncertainty

Uncertainties in the conceptual model arise from a lack of information concerning features and events, or a lack of understanding of the processes controlling groundwater flow and transport. It is important to understand these uncertainties and their potential impact on model results. Additional uncertainty arises from simplifications in developing the implementation model. Cole et al. (2001 a) provides a detailed discussion of sources of uncertainty in the Hanford site-wide groundwater model. Specific sources of uncertainty pertaining to various components of the groundwater model are discussed in Chapter 5.

2.3

Continuing Model Improvements

Improvements continue to be made in the site-wide groundwater model. These improvements are aimed at quantifying uncertainty within the model and improving model accuracy as recommended by an outside review panel in 1998 (Cole et al. 2001 a). The review panel recommended that the concept of uncertainty be acknowledged and that a new modeling framework be established that is stochastic rather than purely deterministic. The panel also requested an assessment of the relative importance of uncertainties due to alternative model structures and constructs of processes (e.g., different zonation, different boundary conditions, large-scale features, stresses, chemical reactions) and due to variations in parameter values. Based on the panel's recommendations, a strategy was devised for assessing model uncertainty through the development and calibration of alternative conceptual models, where the calibration is based on the transient changes in hydraulic heads since the start of Hanford operations. Cole et al. (2001