NUREG/CR-6948, Vol. 2 

 

Integrated Ground-Water 

Monitoring Strategy for 

NRC-Licensed Facilities and 

Sites: Case Study Applications 

Advanced Environmental 

Solutions, LLC 

U.S. Nuclear Regulatory Commission 

Office of Nuclear Regulatory Research 

Washington, DC 20555-0001 
DISCLAIMER: This report was prepared as an account of work sponsored by an agency of the U.S. Government. 

Neither the U.S. Government nor any agency thereof, nor any employee, makes any warranty, expressed or

implied, or assumes any legal liability or responsibility for any third party’s use, or the results of such use, of any

information, apparatus, product, or process disclosed in this publication, or represents that its use by such third

party would not infringe privately owned rights.

AVAILABILITY OF REFERENCE MATERIALS

IN NRC PUBLICATIONS

NRC Reference Material

As of November 1999, you may electronically access

NUREG-series publications and other NRC records at

NRC’s Public Electronic Reading Room at 

http://www.nrc.gov/reading-rm.html. Publicly released

records include, to name a few, NUREG-series

publications; Federal Register notices; applicant,

licensee, and vendor documents and correspondence;

NRC correspondence and internal memoranda;

bulletins and information notices; inspection and

investigative reports; licensee event reports; and

Commission papers and their attachments.

NRC publications in the NUREG series, NRC

regulations, and Title 10, Energy, in the Code of

Federal Regulations may also be purchased from one

of these two sources.

1. The Superintendent of Documents

 U.S. Government Printing Office

 Mail Stop SSOP

 Washington, DC 20402–0001

 Internet: bookstore.gpo.gov

 Telephone: 202-512-1800

 Fax: 202-512-2250

2. The National Technical Information Service

 Springfield, VA 22161–0002

 www.ntis.gov 

 1–800–553–6847 or, locally, 703–605–6000

A single copy of each NRC draft report for comment is

available free, to the extent of supply, upon written

request as follows:

Address: U.S. Nuclear Regulatory Commission

 Office of Administration 

 Mail, Distribution and Messenger Team

 Washington, DC 20555-0001

E-mail: DISTRIBUTION@nrc.gov 

Facsimile: 301–415–2289 

Some publications in the NUREG series that are 

posted at NRC’s Web site address

http://www.nrc.gov/reading-rm/doc-collections/nuregs 

are updated periodically and may differ from the last

printed version. Although references to material found

on a Web site bear the date the material was accessed,

the material available on the date cited may

subsequently be removed from the site.

Non-NRC Reference Material

Documents available from public and special technical

libraries include all open literature items, such as

books, journal articles, and transactions, Federal

Register notices, Federal and State legislation, and

congressional reports. Such documents as theses,

dissertations, foreign reports and translations, and

non-NRC conference proceedings may be purchased

from their sponsoring organization.

Copies of industry codes and standards used in a

substantive manner in the NRC regulatory process are

maintained at—

The NRC Technical Library 

Two White Flint North

11545 Rockville Pike

Rockville, MD 20852–2738

These standards are available in the library for 

reference use by the public. Codes and standards are

usually copyrighted and may be purchased from the

originating organization or, if they are American

National Standards, from—

American National Standards Institute

11 West 42nd Street

New York, NY 10036–8002

www.ansi.org 

212–642–4900

Legally binding regulatory requirements are stated

only in laws; NRC regulations; licenses, including

technical specifications; or orders, not in 

NUREG-series publications. The views expressed

in contractor-prepared publications in this series are

not necessarily those of the NRC.

The NUREG series comprises (1) technical and

administrative reports and books prepared by the

staff (NUREG–XXXX) or agency contractors

(NUREG/CR–XXXX), (2) proceedings of

conferences (NUREG/CP–XXXX), (3) reports

resulting from international agreements

(NUREG/IA–XXXX), (4) brochures

(NUREG/BR–XXXX), and (5) compilations of legal

decisions and orders of the Commission and Atomic

and Safety Licensing Boards and of Directors’

decisions under Section 2.206 of NRC’s regulations

(NUREG–0750).
 NUREG/CR-6948, Vol. 2 

 

 

Integrated Ground-Water 

Monitoring Strategy for 

NRC-Licensed Facilities and 

Sites: Case Study Applications 

Manuscript Completed: August 2007 

Date Published: November 2007 

Prepared by 

V. Price, T. Temples, R. Hodges, Z. Dai, D. Watkins, J. Imrich 

Advanced Environmental Solutions, LLC 

407 West Main Street 

Lexington, SC 29072 

T.J. Nicholson, NRC Project Manager 

Prepared for 

Division of Fuel, Engineering and Radiological Research 

Office of Nuclear Regulatory Research 

U.S. Nuclear Regulatory Commission 

Washington, DC 20555-0001 

NRC Job Code Y6020 
iii 

ABSTRACT 

This document discusses results of applying the Integrated Ground-Water Monitoring 

Strategy (the Strategy) to actual waste sites using existing field characterization and 

monitoring data. The Strategy is a systematic approach to dealing with complex sites. 

Application of such a systematic approach will reduce uncertainty associated with site 

analysis, and therefore uncertainty associated with management decisions about a site. 

The Strategy can be used to guide the development of a ground-water monitoring 

program or to review an existing one. The sites selected for study fall within a wide 

range of geologic and climatic settings, waste compositions, and site design 

characteristics and represent realistic cases that might be encountered by the NRC. No 

one case study illustrates a comprehensive application of the Strategy using all available 

site data. Rather, within each case study we focus on certain aspects of the Strategy, to 

illustrate concepts that can be applied generically to all sites. The test sites selected 

include: 

• Charleston, South Carolina, Naval Weapons Station, 

• Brookhaven National Laboratory on Long Island, New York, 

• The USGS Amargosa Desert Research Site in Nevada, 

• Rocky Flats in Colorado, 

• C-Area at the Savannah River Site in South Carolina, and 

• The Hanford 300 Area. 

A Data Analysis section provides examples of detailed data analysis of monitoring data. 

Paperwork Reduction Act Statement 

This NUREG does not contain information collection requirements and, therefore, is not 

subject to the requirements of the Paperwork Reduction Act of 1995 (44 U.S.C. 3501 et 

seq.). 

Public Protection Notification 

The NRC may not conduct or sponsor, and a person is not required to respond to, a 

request for information or an information collection requirement unless the requesting 

document displays a currently valid OMB control number. 
iv 
 v

FOREWORD 

This research report was prepared by Advanced Environmental Solutions, LLC (AES), under a commercial 

research contract (NRC-04-03-061) with the U.S. Nuclear Regulatory Commission (NRC). As such, 

this two-volume report presents a logical framework for assessing what, when, where, and how to monitor 

with regard to subsurface ground-water flow and transport, in order to ensure that the environs of a licensed 

nuclear site or facility behave within the expected limits, as prescribed by the performance assessment (PA). 

Volume 1 provides the logic, strategic approach, and examples of how to integrate ground-water monitoring 

with modeling. Specifically, the integrated ground-water monitoring strategy is implemented in an iterative 

manner, beginning with analysis of any existing site and facility characterization and monitoring data 

and the relevant conceptual site model (CSM), hydrogeologic model, and/or risk assessment or PA model. 

The iterative nature of this strategy provides a graded approach for use in developing or evaluating 

a ground-water monitoring program. In so doing, the analyst derives an initial assessment of what, when, 

where, and how to monitor to evaluate system performance. The monitoring is then integrated with 

modeling through the identification, measurement, and analysis of performance indicators (PIs). These PIs 

include hydrogeologic conditions and process attributes; chemical conditions and constituents; and other 

features, events, or processes (FEPs) that may significantly influence contaminant flow and transport. 

As such, PIs may be directly measurable using a monitoring program, or may be derived from compilations 

and interpretations of geophysical or other indirect data. This integrated ground-water monitoring and modeling 

strategy offers the following benefits: 

• Characterization allows the development of a CSM. 

• The CSM allows modeling and/or numerical simulation. 

• Modeling allows prediction of system behavior, while monitoring allows refinement of models. 

• Refinement supports confidence in the performance assessment, as well as the need for 

(and selection of) remediation approaches in the event of a contaminant release. 

Volume 2 presents practical examples of the applications of this strategy, which provide practical means 

of testing, evaluating, and improving both the ground-water monitoring program and its related model. 

Although the strategy and its applications were originally planned for decommissioning sites, they are also 

very useful for assessing ground-water monitoring programs, remediating ground water, and identifying and 

selecting approaches to preclude offsite migration of abnormal radionuclide releases at nuclear facilities. 

This approach is consistent with the NRC’s strategic performance goal of making the agency’s activities 

and decisions more effective, efficient, realistic, and timely by characterizing and monitoring radionuclide 

transport in ground water. Toward that end, this report demonstrates, using examples relevant to nuclear 

facility performance, that ground-water monitoring and modeling can be integrated within a systems approach. 

This information will assist NRC licensing staff and regional inspectors, Agreement State regulators, 

and licensees in their decision-making by promoting a greater understanding of ground-water monitoring 

concepts that relate to PA models. Nonetheless, this report is not a substitute for NRC regulations, 

and compliance is not required. Consequently, the approaches and methods described in this report 

are provided for information only, and publication of this report does not necessarily constitute NRC approval 

or agreement with the information contained herein. Similarly, use of product or trade names in this report 

is intended for identification purposes only, and does not constitute endorsement by either the NRC or AES. 

Christiana Lui, Director 

Division of Risk Analysis 

Office of Nuclear Regulatory Research 
vi 

EXECUTIVE SUMMARY 

This document discusses results of applying the Integrated Ground-Water Monitoring 

Strategy (the Strategy) to actual sites using existing field characterization and monitoring 

data. The sites selected for study fall within a wide range of geologic and climatic 

settings, inventory compositions, and site design characteristics and represent realistic 

cases that might be encountered by the NRC. 

Within each case study we focus on certain aspects of the Strategy, to illustrate concepts 

that can be applied generically to all sites. 

The six test sites selected include: 

Chapter 2. Charleston, SC Naval Weapons Station. This study illustrates the value of 

detailed geological study aided by shallow seismic reflection data to develop a conceptual 

site model (CSM). The resulting model explained monitoring observations and allowed 

simulation of plume movement that matched observed concentrations. Wells could be 

recommended for deletion, and an additional sentinel well for model confirmation was 

recommended. 

Chapter 3. Brookhaven National Laboratory on Long Island, New York. At this site 3-D 

visualization (e.g., Figures 3-11 and 3-12 on page 3-20) allowed better communication of 

plume movement. 

Chapter 4. The USGS Amargosa Desert Research Site in Nevada. A revised CSM 

integrating all available site data, including resistivity soundings, allowed reinterpretation of observed tritium vapor movements. With the revised CSM, a simple 

spreadsheet model was used and provided a good match to observed tritium distribution. 

Chapter 5. Rocky Flats in Colorado. This site provides an opportunity to observe 

episodic pulses of contaminant apparently being released from a vadose zone source in 

response to water table changes. Data from one well are used to address the issue of 

defining long-term trends (the Mann-Kendall test) and when it is appropriate to stop 

sampling a well. The data are also discussed in Chapter 8. 

Chapter 6. C-Area at the Savannah River Site in South Carolina. This site has both 

tritium and chlorinated solvent plumes. An adjacent location that was characterized as a 

potential landfill site provides data that may not be consistent with the CSM used to 

model the C-Area ground water. Because of the site’s isolation, there are no risk 

consequences of the possible CSM error. 

Chapter 7. The Hanford 300 Area. A revision to the CSM is suggested that includes river 

water dynamics as part of the hydrogeologic model. 

In addition a section on Data Analysis appears as Chapter 8 of this document. This 

chapter is not intended to be a review of statistics, but to give some examples of data 

analysis. A FORTRAN program to calculate well to well correlations and Mann-Kendall 

parameters is included.
vii 

CONTENTS 

ABSTRACT.......................................................................................................................iii 

FOREWORD ...................................................................................................................... v

EXECUTIVE SUMMARY ............................................................................................... vi 

CONTENTS...................................................................................................................... vii 

FIGURES........................................................................................................................... xi 

TABLES .......................................................................................................................... xvi 

ACRONYMS AND ABBREVIATIONS....................................................................... xvii 

1 Introduction..............................................................................................................1-1

1.1 Charleston Naval Weapons Station ....................................................................1-4 

1.2 Brookhaven National Laboratory .......................................................................1-4 

1.3 USGS Amargosa Desert Research Site ..............................................................1-5 

1.4 Rocky Flats......................................................................................................... 1-5 

1.5 Savannah River C-Area......................................................................................1-5 

1.6 Hanford Site 300 Area........................................................................................1-6 

1.7 Data Analysis...................................................................................................... 1-6 

2 Charleston Naval Weapons Station .........................................................................2-1 

2.1 Introduction ........................................................................................................2-1 

2.2 Compilation and Analysis of Available Data.....................................................2-2 

2.2.1 Regional Geology..................................................................................... 2-2 

2.2.2 Site Hydrogeology.................................................................................... 2-3 

2.3 Conceptual Site Modeling .................................................................................. 2-6 

2.3.1 First Approach: Analytical Model:...........................................................2-6 

2.3.2 Second Approach: Numerical Model / Simple Geology:.........................2-7 

2.3.3 Third Approach: Numerical Model / Complex Geology..........................2-8 

2.4 Designing a Performance Confirmation Monitoring Network.........................2-10 

2.5 Strategy Application Conclusions ....................................................................2-14 

2.6 Charleston References ......................................................................................2-16 

Appendix 2-A............................................................................................................. 2-17 

3 Brookhaven National Laboratory ............................................................................3-1 

3.1 Introduction ........................................................................................................3-1 

3.2 Compilation of Available Data...........................................................................3-2 

3.2.1 Site Background ....................................................................................... 3-2 

3.2.2 Geologic Information ...............................................................................3-4 

3.2.3 Hydrogeologic Information ......................................................................3-4 

3.2.4 Hydrologic Data .......................................................................................3-5 

3.2.5 Tritium Plume Ground-Water Monitoring Data.....................................3-12 

3.3 Ground-Water Modeling and Visualization .....................................................3-19 

3.3.1 Plume visualization.................................................................................3-19 

3.3.2 Flow and transport modeling..................................................................3-21 

3.3.3 Active Monitoring ..................................................................................3-21 

3.3.4 Performance Indicators...........................................................................3-23 

3.4 Monitoring Strategy Application Conclusions.................................................3-24 
viii 

3.5 Brookhaven References....................................................................................3-24 

4 Amargosa Desert Research Site...............................................................................4-1 

4.1 Introduction ........................................................................................................4-1 

4.2 Compilation of Available Data...........................................................................4-1 

4.2.1 Geologic Setting .......................................................................................4-2 

4.2.2 Regional Geologic Information................................................................4-4 

4.2.3 Site-specific Geologic and Analytical Data..............................................4-4 

4.3 Application of the Strategy............................................................................... 4-13 

4.3.1 Chemical Constituents in Ground Water or Soil Gas.............................4-13 

4.3.2 Chemical Constituents in Other Fluids...................................................4-13 

4.3.3 Chemical Constituents in Plants and Animals........................................4-14 

4.3.4 Geophysical Modeling and Evaluation................................................... 4-15 

4.3.5 Hydrologic Data .....................................................................................4-18 

4.3.6 Vadose Zone Data ..................................................................................4-21 

4.3.7 Meteorological Data ...............................................................................4-25 

4.3.8 Transport Modeling ................................................................................4-26 

4.4 Monitoring Strategy Application Conclusions.................................................4-30 

4.5 Amargosa References.......................................................................................4-31 

Appendix 4-A............................................................................................................. 4-33 

Appendix 4-B............................................................................................................. 4-47 

5 Rocky Flats Facility .................................................................................................5-1 

5.1 Introduction ........................................................................................................5-1 

5.2 Compilation of Available Data...........................................................................5-3 

5.3 Geologic Setting .................................................................................................5-3 

5.3.1 Hydrologic Data .......................................................................................5-4 

5.4 Application of the Strategy................................................................................. 5-6 

5.4.1 Case Study 1: Conceptual Site Model Assessment ..................................5-6 

5.4.2 Case 1: Existing Site Monitoring Data..................................................... 5-7 

5.4.3 Case 1: Application of the Strategy..........................................................5-7 

5.4.4 Case 2: VOC Plume Analysis................................................................5-12 

5.4.5 Case 2: Application of the Strategy........................................................5-12 

5.4.6 Performance Indicators and FEPs........................................................... 5-14 

5.5 Monitoring Strategy Application Conclusions.................................................5-15 

5.6 Rocky Flats References ....................................................................................5-16 

6 Savannah River Site, C Area ................................................................................... 6-1 

6.1 Introduction ........................................................................................................6-1 

6.2 Compilation of Available Data...........................................................................6-3 

6.3 C-Area Background............................................................................................ 6-3 

6.3.1 Geology and Hydrogeology...................................................................... 6-4 

6.3.2 Site Characterization and Monitoring....................................................... 6-5 

6.3.3 Contaminant Distribution .........................................................................6-6 

6.4 Synthesis of a Conceptual Site Model and Flow and Transport Simulations .... 6-8 

6.5 Data Visualization ............................................................................................6-11 

6.6 Alternative Conceptual Models........................................................................6-12 

6.7 Performance Indicators and FEPs..................................................................... 6-14 

6.8 Monitoring Strategy Application Conclusions.................................................6-15 
ix 

6.8.1 Possible Future Actions..........................................................................6-16 

6.9 References ........................................................................................................6-17 

7 Hanford 300 Area .................................................................................................... 7-1 

7.1 Introduction ........................................................................................................7-1 

7.2 Compilation of Available Data...........................................................................7-2 

7.2.1 Geologic Setting .......................................................................................7-2 

7.2.2 Regional Geologic Information................................................................7-2 

7.2.3 Site-specific Geologic Information ..........................................................7-4 

7.2.4 Site-specific Hydrogeologic Information .................................................7-5 

7.2.5 Vadose Zone Data ....................................................................................7-8 

7.2.6 Hydrologic Data .......................................................................................7-9 

7.2.7 Seasonal Variability in Water-Table Conditions....................................7-10 

7.2.8 300 Area Uranium Plume.......................................................................7-12 

7.2.9 Monitoring Considerations.....................................................................7-14 

7.3 Application of Ground Water Monitoring Performance Strategy....................7-15 

7.3.1 Performance Indicators and FEPs........................................................... 7-19 

7.4 Monitoring Strategy Application Conclusions.................................................7-20 

7.5 Hanford References .......................................................................................... 7-21 

8 Analysis of Characterization and Monitoring Data ................................................. 8-1 

8.1 Introduction ........................................................................................................8-1 

8.1.1 Data Types – Characterization versus Monitoring................................... 8-1 

8.1.2 Data Evaluation versus Statistical Analysis .............................................8-2 

8.2 Univariate data....................................................................................................8-3 

8.2.1 Basic Statistical Analysis.......................................................................... 8-4 

8.2.2 Identification of Outlier Points.................................................................8-4 

8.2.3 Quality Control Charts: the T-Test...........................................................8-5 

8.2.4 Applying the Mann-Kendall Test............................................................. 8-7 

8.3 Rainfall Data – Sources of Uncertainty for Infiltration....................................8-11 

8.3.1 Consider All Water Infiltration Sources.................................................8-12 

8.3.2 Ensure Rain Station Data Match Facility-Specific Gauging.................. 8-12 

8.4 Correlations between different wells................................................................8-15 

8.5 Water Level Measurements..............................................................................8-18 

8.6 Unmixing of Multimodal Data .........................................................................8-19 

8.7 Multivariate Analysis Methods: Cluster and Factor Analysis.........................8-23 

8.7.1 Case Study: Multivariate Data Analysis at Mill Tailing Site ................8-23 

8.8 Analysis of Mapped (Spatial) Data .................................................................. 8-28 

8.8.1 Outliers in Mapped Data.........................................................................8-29 

8.8.2 Uncertainty in Mapped Data...................................................................8-29 

8.8.3 Incongruity between Mapped Variables.................................................8-31 

8.9 Quality Assurance.............................................................................................8-34 

8.9.1 Quality Assurance Case Studies.............................................................8-35 

8.10 References .....................................................................................................8-39 

Appendix 8-A............................................................................................................. 8-42 

Appendix 8-B Fortran 90 code for well-well correlations and for the Mann-Kendall 

test..............................................................................................................................8-45 

GLOSSARY ................................................................................................................... G-1 
x 
xi 

FIGURES 

Figure 1-1. Integrated Ground Water Monitoring Strategy framework . ....................... 1-2 

Figure 2-1. Map showing the location of SWMU 12 at the Charleston Naval Weapons 

Station (Danielsen, 2003).........................................................................................2-1 

Figure 2-2. This cross section is an example of the complex geology that can result from 

a changing coastal environment. (Figure from Ferm in Saxena, 1976, Fig. 2) ......2-2 

Figure 2-3. Map of SWMU 12 showing locations of wells and nearby marshes 

(Danielsen, 2003).....................................................................................................2-3 

Figure 2-4. Seismic reflection profiles. The green line is interpreted as the base of the 

major channel or the older channel, the red line indicates the base of younger 

channel that has incised into the older channel........................................................2-4 

Figure 2-5. Elevation of the base of the channel contoured from seismic data and well 

picks. The orange shows the lower elevations, the green shows the higher 

elevations, and the grey lines represent the seismic profile locations. ....................2-5 

Figure 2-6. Graph of data from the slug test, with hydraulic conductivity (ft/d) on the 

vertical axis and the cumulative percentage of samples having that value or less 

plotted on the horizontal axis...................................................................................2-6 

Figure 2-7. Cross Section of the assumed geology for the analytical solution CSM. ....2-7 

Figure 2-8. Cross Section of the “Layer Cake Geology” used for our second approach. 2-

8 

Figure 2-9. The PCE plume from Model II is presented at left, and the computed PCE 

concentrations at monitoring well MW-03 are much lower than the observed values 

(right). ...................................................................................................................... 2-8 

Figure 2-10. The cross-section shows the Major channel and Younger channel, as well as 

the other hydrofacies in the site. ..............................................................................2-9 

Figure 2-11. The simulated PCE plume from Model III is presented at left; computed 

PCE concentrations at monitoring well MW-03 more closely match observed values 

(right). ...................................................................................................................... 2-9 

Figure 2-12. The predicted PCE plume in five years. Circled wells are suggested to be 

removed from the monitoring program to save money, while a new point is 

suggested to be added at the yellow dot to test the CSM and simulation results. .2-11 

Figure 2-13. Change in water table over time. Note how MW-08 is the only well that 

doesn’t match the others. .......................................................................................2-12 

Figure 2-14. Contour Map of water table using data from July 2004 (feet above MSL) .2-

13 

Figure 2-15. Contour map of water table using data from July 2004, without well MW08 (feet above MSL) .............................................................................................. 2-13 

Figure 2-16. Activities and results of the Strategy application at Charleston Naval 

Weapons Station ....................................................................................................2-15 

Figure 3-1. Schematic of tritium/VOC plume pump and treat system (DOE, 2000) .....3-2 

Figure 3-2. Location of the Brookhaven National Laboratory (Scorca et al., 1999)...... 3-3 

Figure 3-3. Hydrostratigraphy of the Brookhaven National Laboratory (BNL, 2004) .3-4 

Figure 3-4. Precipitation and water-table altitude at Brookhaven National Laboratory, 

Suffolk County, N.Y.,1970-97. A. Annual precipitation at Upton. B. Typical water 

levels in wells (Scorca et al., 1999) .........................................................................3-9 
xii 

Figure 3-5. Water-table altitude in 300-mi2 study area surrounding Brookhaven National 

Laboratory, Suffolk County, N.Y., August 1995 (Scorca et al., 1999) .................3-10 

Figure 3-6. Schematic of plume configuration below the HFBR (Looney and Paquette, 

2000). Used by permission of Battelle Press .........................................................3-13 

Figure 3-7. Simplified calculation of plume thickness immediately downgradient of a 

vadose zone source (Looney and Paquette, 2000). Used by permission of Battelle 

Press. ......................................................................................................................3-14 

Figure 3-8. Cross section of tritium plume emanating from the HFBR (Looney and 

Paquette, 2000). Used by permission of Battelle Press. ........................................3-16 

Figure 3-9. December 2005 water table map of BNL with extraction wells (BNL, 2005)

................................................................................................................................3-17 

Figure 3-10. Location of tritium plume emanating from the High Flux Beam Reactor 

(DOE, 2000)........................................................................................................... 3-18 

Figure 3-11. Oblique view looking northeast of tritium plume with concentrations 

emanating from the HFBR.....................................................................................3-20 

Figure 3-12. Oblique view looking northwest of tritium plume with concentrations 

emanating from the HFBR.....................................................................................3-20 

Figure 3-13. Computer simulation of tritium plume emanating from the HFBR after 

twenty years, no pumping......................................................................................3-21 

Figure 3-14. Computer simulation of tritium plume emanating from the HFBR after 

twenty years, pumping monitoring well. ...............................................................3-22 

Figure 4-1. Location of ADRS (Stonestrom et al., 2003)...............................................4-2 

Figure 4-2. Cross section of a typical horst and graben sequence (CG, 1992)............... 4-3 

Figure 4-3. Oblique view of a typical alluvial fan in Death Valley................................4-3 

Figure 4-4. Location of ADRS and soil gas sampling boreholes UZB-2 and UZB-3 

(Stonestrom et al., no date) ...................................................................................... 4-4 

Figure 4-5. Geologic distribution of clay lenses and marsh deposits in ADRS Wells 301, 

302, and 303 (Fischer, 1992) ................................................................................... 4-5 

Figure 4-6. ADRS water table contours (measured in meters MSL) and well locations 

(Walvoord et al., 2005) ............................................................................................4-6 

Figure 4-7. Map of tritium concentrations in ground water below ADRS (Data from 

Prudic, 1997)............................................................................................................ 4-7 

Figure 4-8. Map showing numbered survey locations of Schlumberger soundings 

(modified from Bisdorf, 2002).................................................................................4-8 

Figure 4-9. Cross section of interpreted resistivity and basin fault (Bisdorf, 2002). 

(Triangles along the top axis correspond to sounding locations as mapped in Figure 

4-8. Subvertical solid black line represents basin fault as defined by Bisdorf 2002.)

..................................................................................................................................4-9 

Figure 4-10. Map showing contours of interpreted resistivity at a depth of 97 m 

overlying topographic contours (Bisdorf, 2002).................................................... 4-10 

Figure 4-11. A vertical cross section made by direct current electrical resistivity (DCresistivity) imaging near the ADRS (Stonestrom et al., no date)...........................4-11 

Figure 4-12. Monitoring shaft and instrument borehole showing locations of TCPs and 

respective geologic information (Fischer, 1992). Thermocouple psychrometers 

installed in the monitoring shaft are designated with L (left), M (middle), and R 

(right), followed by a number from 1 to 11 that indicates level in shaft. 
xiii 

Thermocouple psychrometers installed in the instrument borehole are designated 

OD1 through OD13. Depth of each thermocouple psychrometer, in meters below 

land surface, is given in parentheses. (Fischer, 1992). ..........................................4-11 

Figure 4-13. Monitoring shaft geologic and geophysical information (Fisher, 1992)..4-13 

Figure 4-14. Plant sample locations and contours of plant-water tritium concentrations 

(Andraski et al., 2005) ........................................................................................... 4-14 

Figure 4-15. A comparison of plant water tritium with soil water tritium (Stonestrom et 

al., no date)............................................................................................................. 4-15 

Figure 4-16. Simplified geologic cross section of the ADRS looking northwest......... 4-15 

Figure 4-17. Three-dimensional resistivity block model of the ADRS looking northwest 

(Well UZB-2 can be seen in the southwestern portion of the figure) (created with 

data from Bisdorf, 2002)........................................................................................ 4-17 

Figure 4-18. Location of the Southern Structural offset as defined by resistivity data in 

relation to the burial trenches (adapted from Stonestrom et al., no date) ..............4-18 

Figure 4-19. Map of tritium concentrations in ground water below ADRS in relation to 

the Southern Structural Offset (data from Prudic, 1997).......................................4-20 

Figure 4-20. Plan view of tritium soil gas concentrations in the 1.5m below ground 

surface interval (data from Striegl et al., 1997) .....................................................4-22 

Figure 4-21. Soil vapor concentrations of tritium in UZB-2 ........................................ 4-23 

Figure 4-22. Tritium soil gas concentrations from UZB-3 (modified from Stonestrom et 

al., no date)............................................................................................................. 4-24 

Figure 4-23. Carbon dioxide and carbon-14 soil gas concentrations from UZB-2 and 

UZB-3 (Stonestrom et al., no date)........................................................................4-24 

Figure 4-24. Data from southeast corner of ADRS (Prudic, 1996) .............................. 4-25 

Figure 4-25. Conceptual Model for the movement of tritium proposed by Striegl et al., 

1996........................................................................................................................ 4-26 

Figure 4-26. Comparison of actual data to modeled tritium concentrations in UZB-2 in 

pCi/L (UZB-2 tritium data from Striegl et al., 1997) ........................................... 4-28 

Figure 4-27. Alternative conceptual model for the distribution of tritium in vadose zone 

based on Southern Structural offset and UZB-2 tritium concentrations (tritium data 

from Striegl et al., 1997)........................................................................................4-29 

Figure 5-1. Location of the Rocky Flats Facility in Colorado (DOE, 2005)..................5-2 

Figure 5-2 Photograph of the Rocky Flats Facility (looking east) Photo is in “Linking 

Legacies”, DOE publication EM-0319 (DOE 1997) Appendix B, page 190. ......... 5-3 

Figure 5-3. Map of Rocky Flats Facility drainage basins (from: 

http://lanl.gov/source/orgs/nmt/nmtdo/AQarchive/06springsummer/page5.shtml) 5-5 

Figure 5-4. Ground-water monitoring well locations and depiction of VOC and nitrate 

plumes for the Rocky Flats Facility (CDPHE, (No Date)) ......................................5-6 

Figure 5-5. Conceptual cross-section for the Rocky Flats Facility (Modified from K-H, 

2004) ........................................................................................................................ 5-7 

Figure 5-6. Diagram of multiyear variability in ground-water contaminant concentrations 

due to water table changes (K-H, 2004) .................................................................. 5-8 

Figure 5-7. Conceptual cross section showing affects of water table changes on 

contaminant movement (modified from K-H, 2004)............................................... 5-8 

Figure 5-8. Potential changes in ground-water movement due to closure....................5-10 

Figure 5-9. Predicted water level changes after closure (K-H, 2004) ..........................5-11 
xiv 

Figure 5-10. Generalized depiction of the Rocky Flats Facility TCE plume ............... 5-12 

Figure 5-11. Conceptual model of complex flow of contaminants ..............................5-14 

Figure 6-1. Savannah River Site location map. Courtesy of Bill Jones, SRNL. ...........6-1 

Figure 6-2. Photograph of the A Area Burning/Rubble Pit during operation.................6-2 

Figure 6-3. Map of C Area with facilities and wells (WSRC, 1998)..............................6-3 

Figure 6-4. Simplified hydrogeologic cross section near C Area (Kegley et al., 1994). 

Courtesy of W.P. Kegley. ........................................................................................ 6-5 

Figure 6-5. Topographic map of C-Area facility boundary with TCE plume and detected 

TCE concentrations..................................................................................................6-6 

Figure 6-6. C Area tritium CPT data .............................................................................. 6-7 

Figure 6-7. C Area TCE CPT data..................................................................................6-8 

Figure 6-8. C Area hydrologic Conceptual Site Model ..................................................6-9 

Figure 6-9. C Area simulated transport model for Layer 3 from the CBRP................. 6-10 

Figure 6-10. C Area simulated transport model for Layer 7 from the CBRP...............6-10 

Figure 6-11. Cross section of C Area hydrogeologic conceptual model. The Gordon 

confining unit (green clay) is shown as a green band above the Gordon aquifer. 

Fourmile Branch is correctly called Four Mile Creek elsewhere in this document...6-

11 

Figure 6-12. Looking from beneath the Gordon confining unit to the NE towards the 

plume (All dim points are above the Gordon confining unit)................................6-12 

Figure 6-13. Structural contour map of the top of the Gordon confining unit (WSRC, 

1992) ...................................................................................................................... 6-13

Figure 6-14. Maps of ground water flow directions within the Gordon aquifer...........6-14 

Figure 7-1. Hanford Site map including the 300 Area (DOE, 1999)..............................7-2 

Figure 7-2. Hanford Site regional geologic setting (Vermeul et al., 2003) ....................7-3 

Figure 7-3. Structural geologic features of the Hanford Site within the Pasco Basin 

(Vermeul et al., 2003) ..............................................................................................7-4 

Figure 7-4. Major geological units at the Hanford Site (DOE, 1999) ............................7-5 

Figure 7-5. Index map to cross sections shown in Figures 6, 7, and 8 (Peterson, 2005) 7-6 

Figure 7-6. West to east cross section along flow path from 300 Area process trenches to 

the Columbia River (Peterson, 2005).......................................................................7-7 

Figure 7-7. North to south cross section along shoreline wells (Peterson, 2005)...........7-7 

Figure 7-8. West to east cross section through central portion of 300 Area (Peterson, 

2005) ........................................................................................................................ 7-7 

Figure 7-9. Conceptual model of fluid flow beneath single shell tanks at Hanford Site 

showing fingering, funnel flow, and flow associated with clastic dikes or poorly 

sealed borehole annular space (Faybishenko, 2000)................................................7-9 

Figure 7-10. 300 Area water-table elevation, March 1992 (averaged hourly) (Peterson, 

2005) 7-10 

Figure 7-11. 300 Area water-table elevation, May 1992 (averaged hourly) (Peterson, 

2005) .......................................................................................................... 7-10

Figure 7-12. 300 Area water-table elevation, June 1992 (averaged hourly) (Peterson, 

2005) ...................................................................................................................... 7-11

Figure 7-13. 300 Area water-table elevation, September 1992 (averaged hourly) 

(Peterson, 2005) ..................................................................................................... 7-11 
xv 

Figure 7-14. 300 Area water-table elevation, December 1992 (averaged hourly) 

(Peterson, 2005) ..................................................................................................... 7-11 

Figure 7-15. 300 Area ground water monitoring locations (Peterson, 2005) ...............7-14 

Figure 7-16. Hydrogeologic conceptual model of contaminant movement below the 

Hanford 300 Area (DOE, 2002)............................................................................. 7-15 

Figure 7-17. Transient storage mechanisms (Runkel, 1998) ........................................7-16 

Figure 7-18. Alternative conceptual model of Hanford 300 Area showing potential 

infiltration and downstream flushing of formation................................................ 7-17 

Figure 7-19. Extent of river water intrusion as estimated from nitrate concentrations in 

2002(Yabusaki et al, 2004)....................................................................................7-18 

Figure 7-20. 300 Area Ground-Water Uranium Concentrations, August 1997............7-19 

Figure 8-1. Example control chart ..................................................................................8-6 

Figure 8-2. Mann-Kendall Example ...............................................................................8-8 

Figure 8-3. Published figure indicating declining PCE concentrations in ug/L (DOE, 

2006) ........................................................................................................................ 8-9 

Figure 8-4. Linear regression fit to PCE data from MS-EXCEL ................................. 8-10 

Figure 8-5. Parsing time series data into three groups.................................................. 8-11 

Figure 8-6. SRS rain gauging station and well locations. Rain stations are located under 

respective station identifier A, C, F, H, and S. Well locations are denoted by black 

dots. Adapted from Jones, 1990............................................................................8-13 

Figure 8-7. Rain data for Stations F and H, which are only two miles apart, show that 

particularly in summer, rainfall patterns are highly variable, even over short 

distances.................................................................................................................8-13 

Figure 8-8. Rain Gauges C and S are about 7 miles apart and show significant variation 

in observed rainfall. ...............................................................................................8-14 

Figure 8-9. Correlation of rainfall as a function of distance in July and January.........8-15 

Figure 8-10. Rejection of outliers .................................................................................8-16 

Figure 8-11 Periodic and continuous water level measurements compared for SRS well P13D. Courtesy Bill Jones, SRNL. .........................................................................8-18 

Figure 8-12. Unmixing bimodal data............................................................................8-20 

Figure 8-13. Probability plot.........................................................................................8-22 

Figure 8-14. Tri-modal distribution ..............................................................................8-22 

Figure 8-15. Cross section showing concept of merged water bodies. Our study 

examines whether this water is separated into two isolated chambers. ................. 8-24 

Figure 8-16. Dendrogram (partial) of the clusters for the water analyses presented in 

Appendix 8-A. The left-most column is the well name and the right column 

indicates the observation number...........................................................................8-26 

Figure 8-17. Map of chloride plume (blue) superimposed on a vector potentiometric data 

(arrows), and contoured hydraulic conductivity data (red)....................................8-31 

Figure 8-18. Typical alluvial fan ...................................................................................8-32 

Figure 8-19. Diagram of alluvial fans in Wyoming......................................................8-33 

Figure 8-20. Schematic of monitoring well with steps in installation. .........................8-36 

Figure 8-21. pH with time for well ASB8B..................................................................8-37 

Figure 8-22. pH with time for well ABP3 .....................................................................8-38 

Figure 8-23 Field and laboratory measurements compared...........................................8-39 
xvi 

TABLES 

Table 1-1 Classification of Performance Indicators ........................................................1-3 

Table 2-1. Slug test data compared to the number of hammer blows needed to 

penetrate 1 ft, averaged over the length of the screen zone.....................................2-5 

Table 2-2. Estimated flow and transport parameters for Model III. .............................2-10 

Table 2-3. Water elevations (ft above MSL) in wells...................................................2-12 

Table 3-1. Generalized description of geologic and hydrogeologic units underlying 

Brookhaven National Laboratory and vicinity, Suffolk County, N.Y. (Scorca et al., 

1999) ........................................................................................................................ 3-6 

Table 3-2. Hydraulic conductivity of Upper Glacial aquifer at Brookhaven National 

Laboratory, Suffolk County, N.Y., as indicated by aquifer tests (Scorca et al., 

1999) ........................................................................................................................ 3-7 

Table 4-1. Summary of model for estimation of tritium movement in the vadose zone 

between the Southern Structural Offset and UZB-2.............................................. 4-27 

Table 4-2. Tritium model dispersivity values assigned to various materials................4-29 

Table 4-3. Comparison of results from the tritium model to actual concentrations in 

UZB-2 (UZB-2 data from Striegl et al., 1997) ......................................................4-30 

Table 6-1. Hydrologic layer parameters (adapted from Flach et al. (1999) and Geotrans 

(2001))...................................................................................................................... 6-9 

Table 8-1 . Statistical analysis of water head observations from Savannah River Site.8-17 

Table 8-2. The identified distributions of three sources and the estimated parameters 8-21 

Table 8-3. Correlations between monitoring data variables .........................................8-28 

Table 8-4. Hydraulic conductivity data ........................................................................8-34 
xvii 

ACRONYMS AND ABBREVIATIONS 

°C degrees celcius

μg/L micrograms per liter 

ADRS Amargosa Desert Research Site 

AEA Atomic Energy Act 

AES Advanced Environmental Solutions, LLC 

AEC Atomic Energy Commission 

AOCs Areas of Concern 

ASTM American Society for Testing and Materials 

bgs below ground surface 

BNL Brookhaven National Laboratory 

BRP burning and ruble pit 

CERCLA Comprehensive Environmental Response Compensation and Liability Act 

CFC chlorofluorocarbon 

cfs cubic feet per second 

Ci Curie 

cm centimeters 

cm/day centimeters per day 

CO2 carbon dioxide 

COC contaminant of concern 

cpt cone penetrometer test 

CRBG Columbia River Basalt Group 

CSM conceptual site model 

CV coefficient of variation 

DC-resistivity direct current resistivity 

DCE dichloroethylene 

DNAPL dense nonaqueous phase liquid 

DoD Department of Defense 

DOE United States Department of Energy 

DQO data quality objective 

EDB ethylene dibromide 

EM electromagnetic 

EM expectation-maximization 

EPA Environmental Protection Agency 

ft feet 

ft/d feet per day 

ft/ft feet per foot 

FEPs features, events, or processes 

GC green clay 

GIS geographic information system 

gpm gallons per minute 

GPR ground-penetrating radar 

HFBR High Flux Beam Reactor 

INEEL Idaho National Engineering and Environmental Laboratory 

Kd distribution coefficient 

LANL Los Alamos National Laboratory 

LBNL Lawrence Berkeley National Laboratory 

LLNL Lawrence Livermore National Laboratory 

LLW low-level waste 

LNAPL light non-aqueous phase liquid 

m meter 

MCL maximum contaminant level 

m/d meters per day 
xviii 

m/m meters per meter 

mg/g milligrams per gram 

MDL method detection limit 

mi miles 

mi2 square miles 

MLE maximum likelihood estimation 

MNA monitored natural attenuation 

ND no date 

NE northeast 

NRC Nuclear Regulatory Commission 

NURE National Uranium Resource Evaluation 

ORNL Oak Ridge National Laboratory 

OU Operable Unit 

PA Performance Assessment 

PAH polycyclic aromatic hydrocarbon 

pCi/L picocuries per liter 

PCB polychlorinated biphenyl 

PCE tetrachloroethylene 

PCP pentachlorophenol 

PNNL Pacific Northwest National Laboratory 

ppb parts per billion 

PVC polyvinyl chloride 

QΑ quality assurance

RCRA Resource Conservation & Recovery Act 

RSB reactor seepage basin 

SCDHS Suffolk County Department of Health Services 

SNL Sandia National Laboratories 

SP spontaneous potential 

SPSS Statistical Package for the Social Sciences 

SRS Savannah River Site 

SRTC Savannah River Technology Center 

SSE south/southeast 

SVE soil vapor extraction 

SWMU Solid Waste Management Unit 

TCA l,l,l-trichloroethane 

TCE trichloroethylene 

TCLP toxicity characteristics leaching procedure 

TCPs thermocouple psychrometers 

TOC total organic carbon 

U(VI) hexavalent uranium 

UMTRA uranium mill tailings remedial action 

USGS United States Geological Survey 

VOC volatile organic compound 
1-1 

1 Introduction 

This document discusses results of applying the Integrated Ground-Water Monitoring 

Strategy (the Strategy) to actual waste sites using existing field characterization and 

monitoring data. The sites selected for study fall within a wide range of geologic and 

climatic settings, waste compositions, and site design characteristics and represent 

realistic cases that might be encountered by the NRC. 

We gratefully acknowledge the U.S. Navy, the U.S. Geological Survey, and the U.S. 

Department of Energy for data used in this report. 

A Test Plan submitted to NRC in July, 2005, set forth a plan that was applied to produce 

this report. No one case study illustrates a comprehensive application of the Strategy 

using all available site data. Rather, within each case study we focus on certain aspects 

of the Strategy, to illustrate concepts that can be applied generically to all sites. 

The six test sites selected include: 

Chapter 2. Charleston, SC Naval Weapons Station, 

Chapter 3. Brookhaven National Laboratory on Long Island, New York, 

Chapter 4. The USGS Amargosa Desert Research Site in Nevada, 

Chapter 5. Rocky Flats in Colorado, 

Chapter 6. C-Area at the Savannah River Site in South Carolina, and 

Chapter 7. The Hanford 300 Area. 

In addition a section on Data Analysis appears as Chapter 8 of this document. This 

chapter is not intended to be a review of statistics, but to give some examples of data 

analysis. The Strategy is a systematic approach to dealing with complex sites. 

Application of such a systematic approach will reduce uncertainty associated with site 

analysis, and therefore uncertainty associated with management decisions about a site. 

The Strategy can be used to guide the development of a ground-water monitoring 

program or to review an existing one. The high level logic, as expressed in Figure 1-1, is 

simple. 
1-2 

Figure 1-1. Integrated Ground Water Monitoring Strategy framework . 

One begins by gathering, compiling, and analyzing all available data about the site and its 

geological and hydrological context. A Conceptual Site Model (CSM) based on geology 

and hydrogeology is constructed from the data. Engineered features such as trenches and 

back-filled areas may be important in the CSM. Numerical simulations based on this 

model may be made to estimate ground water flow directions and rates of contaminant 

transport. 

For any site, there will be performance criteria to be met. Using the CSM, which 

incorporates hydrogeologic and geochemical information and knowledge of inventory, 

measurable or observable indicators of site performance can be selected. In this Strategy, 

these are called Performance Indicators (PIs). Locations and frequency for measuring 

indicators can also be selected. The indicators may be risk-related potential contaminants, 

or they may be physical measurements like water levels. The objective is to measure 

something that helps to indicate whether the overall site/facility/ground-water system is 

actually functioning as modeled. 

The purpose of monitoring in the context of this guide is confirmation of a performance 

assessment model. Once we have confidence that the site is understood, we can place 

monitoring points as sentinels to give early detection of off-normal behavior, and to 

assure compliance with ground-water protection standards. But it is worth repeating that 

understanding system behavior, not regulatory compliance is the goal of this work. 

Site and system Performance Indicators are measurable or observable features that 

provide insight into reliability of the Conceptual Site Model (CSM). During analysis of 

data from each site, performance indicators are identified and examined. A table of 

potential Performance Indicators (PIs) is shown below. Actual PIs will be site-specific. 
1-3 

Table 1-1 Classification of Performance Indicators 

Class 1 - Chemical 

A. Regulated and Direct Drivers of Risk - U, Cs-134, Pu, Sr-90 these are Primary 

Performance Indicators (PIs) 

B. Surrogates and Indicators that a process is occurring – 

1. gross Alpha for Uranium 

2. Cl or NO3 from same source as risk drivers 

3. degradation products - Am241 for Pu, organic breakdown products for MNA 

C. Process control chemical indicators needed to model transport 

• pH, alkalinity, conductivity, major cations, major anions, redox indicators... 

Class 2 - Physical 

• examples include water content, pressure distributions 

• physical properties of rocks 

• physical properties of subsurface fluids 

Class 3 - Modeled or Derived from Data Analysis 

A. Distribution of uncertainty 

This would be determined by examining the distribution of characterization 

data available to develop a site conceptual model and flow model. Areas of 

sparse or questionable data would have high uncertainty. 

B. Lack of Congruity - Tests of site conceptual and flow / transport models - 

• Do actual plume maps match predicted plumes? 

• Does site geology match regional geology? 

• Does site geology match geology reported from adjacent areas? 

C. Outliers 

Spatial - for example: 

• bulls eyes around data points on contoured maps 

• areas of high characterization uncertainty 

Statistical (no spatial component) - 

• univariate includes control chart anomaly, 

• multivariate would include single-sample cluster 

Short discussions of each site follow and highlight the unique site features, Performance 

Indicators or lessons learned. More detailed discussions are in subsequent chapters and 

include data that were available for the analysis. 
1-4 

1.1 Charleston Naval Weapons Station 

At this site, a leaking solvent storage tank produced a plume of contaminated ground 

water. Initial site investigations were conditioned by proximity to a tidal creek, assumed 

to be the likely surface discharge place for ground water, and by a well with a low water 

level. Monitoring wells placed between the tank and the creek were free of 

contamination. Examination of water levels with time revealed that a well initially 

thought to be down-gradient should have been considered up-gradient. A seismic 

reflection survey and other geologic data were combined to produce a better Conceptual 

Site Model (CSM). This model included sandy channels interpreted from the seismic 

survey. The improved model led to practical suggestions regarding placement of 

monitoring wells for the purpose of Performance Confirmation Monitoring. Specifically, 

these results suggest that several wells can be abandoned, and that one additional well 

should be placed to test whether the plume is advancing. 

This case highlighted the importance of continued validation of the conceptual model 

using site data. In this case three iterations of conceptual and transport modeling were 

necessary to produce a model with sufficient geologic complexity to reproduce observed 

results. This iterative process was key to identifying Performance Indicators for the site 

and for guiding recommended monitoring strategies. 

A lesson learned is that periodic water level measurements might not give a true picture 

of the water table if wells respond differently to rainfall events or surface runoff. 

1.2 Brookhaven National Laboratory 

At Brookhaven National Laboratory (BNL), tritium leaked from a fuel storage pool into 

the ground water. Early attempts to understand the leak with horizontal wells beneath the 

reactor were confounded by the fact that tritium from this slow leak rode the top of the 

water table laterally until leaving the building footprint. Outside the area covered by the 

building, infiltrating precipitation moved the plume downward. 

The shape of the plume has been delineated with wells and direct-push sampling. The 

plume shape is very narrow, prompting us to suspect geologic control, such as a subglacial channel, now buried, and to explore various modeling scenarios. Modeling 

suggests the plume shape may simply be a function of high hydraulic conductivity 

(without the need for a more complex geologic model), and that the plume migration is 

likely influenced by remediation pumping of extraction wells in the vicinity of the plume. 

Because of a high density of sampling points, visualization of the plume is especially 

effective for communication of its extent. The cover illustration is of the BNL tritium 

plume. 

Risk from the tritium is considered very low, and the main issue, rather than health, is 

public perception. Data visualization is a direct and readily understood way to share 

information with the all shareholders. 
1-5 

1.3 USGS Amargosa Desert Research Site 

The U.S. Geological Survey (USGS) Amargosa Desert Research Site (ADRS) is at the 

location of the Nation’s first licensed radioactive waste disposal site near Beatty, Nevada. 

USGS has maintained a research program here since 1975 with the objective of 

understanding dry climate hydrology. USGS has installed wells and collected data on 

migration of tritium and other contaminants including carbon-14 and mercury in the 

vadose zone. USGS has also conducted geophysical (e.g., resistivity) surveys and has 

modeled migration of tritium and mercury. 

USGS reports that modeling results do not match the observed distribution of tritium. 

We evaluated all available site data to produce an alternative CSM which includes a fault 

as a preferential pathway for migration of tritium below the waste site. Rough 

spreadsheet modeling suggests the addition of the fault allows an improved match to the 

observed tritium concentrations. 

The discussion points out the value of using all available data in constructing conceptual 

models, and the critical monitoring needed to test a proposed conceptual model. 

Performance indicators that suggested issues with the conceptual site model included 

strong bending of water-table contours and the distribution of tritium at the water table. 

1.4 Rocky Flats 

Established in 1951, the primary mission of the Rocky Flats facility (RF) was to produce 

weapons components. Decades of these manufacturing operations led to several areas of 

contamination at this site. This report focuses on application of the Strategy at two areas 

of chlorinated organic solvent contamination. 

In the first area of contamination, analysis of characterization data helped us identify a 

correlation in water table levels with observed episodic spikes in contaminant 

concentrations. This finding in turn led to an alternative conceptual model which can aid 

in determining how long some of the monitoring wells should remain in service. 

In the second area of contamination, application of the Strategy revealed that careful 

plume mapping, including recognition of degradation products as key Performance 

Indicators, improves source definition. Some RF data are also used in the Data Analysis 

Chapter. 

1.5 Savannah River C-Area 

At the Savannah River Site (SRS), we find both tritium and chlorinated solvents issuing 

from a few sources near the reactor building. Because the facility is on a ground-water 

divide, contaminants from sources that are close together move in different directions. 

This site is very well characterized through monitoring wells and direct-push sampling. 

Visualization of the ground-water sampling data is useful. Modeling suggests that 

solvents from this facility could have penetrated a regional confining unit and moved to 

the north beneath a local surface-water divide. Some sampling was done in the direction 

of plume movement, but modeling suggests the plume may not have reached the down-
1-6 

gradient area at the time of sampling. This illustrates the importance of flow simulation 

to timing of sampling. 

Additional data discovered during application of the Strategy suggest that the CSM used 

by all modelers, including ourselves, maybe too simplistic and that a confining unit could 

be breached by faulting. It appears that the current data distribution does not permit an

adequate test of this hypothesis. The level of risk does not justify further 

characterization, but it is likely that the CSM is flawed. 

Application of the Strategy helped guide recommendations made with regard to further 

monitoring activities. 

1.6 Hanford Site 300 Area 

DOE’s Hanford Site 300 Area is located immediately adjacent to the Columbia River. 

River discharge is roughly 50,000 cfs adjacent to the Site, and river elevation (stage) is 

controlled by dams. Recent work reported by researchers at the Pacific Northwest 

National Laboratory is used as a backdrop to a discussion of some modeling and 

monitoring issues including the impact of river stage changes on movement of a uranium 

plume. 

One possible addition to the current CSM is the inertia of river water impinging on the 

cutbank adjacent to the 300 Area. Indicators (PIs) of this model modification include the 

distribution of nitrate and uranium plumes adjacent to the river as well as average water 

table elevations. 

1.7 Data Analysis 

Chapter 8 briefly discusses approaches to data analysis techniques, and highlights some 

common pitfalls and issues which can confuse interpretation of monitoring data. Data 

analysis may lead to results that challenge an existing conceptual site model and the 

understanding of how site facilities, geology, and ground water interact and behave. Data 

analysis and data mining are essentially synonymous. This is not a chapter on statistical 

testing. 

Data examples are drawn largely from the DOE Savannah River Site (SRS), the Rocky 

Flats Site, and from a uranium mining and milling site in the northwestern United States. 

Quarterly water levels in wells cannot be simply and reliably related to rainfall data. 

There is some suggestion that data loggers may provide water level data that can be 

related to rainfall. 

Rainfall data from weather stations across the SRS are compared. Results suggest that 

ground-water studies including infiltration estimated from rainfall must use very local 

rainfall data. 

Analysis of 20 years of water level data highlights some QA issues with field 

measurements and with well construction. Data are used to illustrate some statistical 

methods to identify trends or to group data based on general chemistry as well as 

contaminants. Anomalous water levels occur at widely separated wells on the same 
1-7 

sampling date, suggesting opportunities for data QA. A FORTRAN program for well-towell correlation and the Mann-Kendall test is listed. 

Also discussed are simple tests of trends in data that may obscure data structure and 

require examination of the hydrogeologic conceptual model. 

A proposed alternative conceptual model at the northwestern U.S. site is that the water 

table and a lower water bearing zone presented by the site custodian were actually one 

underground water body because of breach of a proposed confining unit by faulting. Data 

analysis indicates that a few contaminated wells stand out, but that most wells yield water 

that can be grouped into two chemically distinct groups or clusters. This supports the site 

custodian’s original conceptual site model that a confining layer has some integrity across 

the site. 
2-1 

2 Charleston Naval Weapons Station 

2.1 Introduction 

The Charleston Naval Weapons Station is located just north of Charleston, South 

Carolina on about 17,000 acres of land. Solid Waste Management Unit 12 (SWMU 12) 

is located in the southeastern portion of the base, near the Cooper River (Figure 2-1). 

This site housed a wood treatment facility that operated from the early 1970s to 1981 

(Danielsen, 2003). 

The site is relatively flat with a total relief ranging from 3.0 to 8.5 feet above mean sea 

level. Four structures were located at the site. The area outside of the fence line consists 

of forest, wetlands, and marshes. 

Past operations at the site included use of the hazardous wood preservative 

pentachlorophenol (PCP). In 1998, a breached 500-gallon underground storage tank was 

found during a RCRA Facility Investigation, and elevated levels of chlorinated organic 

solvents were confirmed in site ground water (Danielsen, 2003). 

Figure 2-1. Map showing the location of SWMU 12 at the Charleston Naval Weapons Station 

(Danielsen, 2003). 
2-2 

In 2001, a seismic survey performed at the site revealed the presence of shallow high 

permeability channels in the subsurface. Conceptual site models which included these 

channels were developed for computer simulations of flow and transport as part of this 

strategy application. Visualization of contaminant transport over time using these 

simulations enabled AES to design a Performance Confirmation Monitoring plan that 

included abandonment of several existing monitoring wells, as well as the placement of 

one additional sentinel well. 

2.2 Compilation and Analysis of Available Data 

2.2.1 Regional Geology 

The geology of the Charleston Naval Weapons Station is made up of sediments deposited 

through near-shore coastal processes. Sands grade into clays and back into sands, 

presenting a complex pattern of layers, as ancient tidal channels meandered through the 

ancient salt marsh, with intervening beach ridges and sand dunes (Weems and Lemon, 

1993). Figure 2-2 is an example of a cross section through a complex coastal 

environment. 

Figure 2-2. This cross section is an example of the complex geology that can result from a changing 

coastal environment. (Figure from Ferm in Saxena, 1976, Fig. 2) 

The surface unit in the area is the Wando Formation. The Wando Formation lithology is 

variable and includes both fluvial and estuarine facies. Typically these include coarsegrained, poorly sorted, cross-bedded sands and clayey, fine- to medium-grained quartz 

sands, sandy to clayey silts, and sandy to silty clays (Gohn et al., 2000). 
2-3 

At a depth of about 40 ft the Ashley Formation is present. This unit is referred to in 

characterization reports as the Cooper Marl. The Ashley Formation consists of a 

relatively homogeneous section of calcareous, phosphatic, microfossiliferous, silty and 

sandy clays deposited in a fluvial and estuarine environment. 

2.2.2 Site Hydrogeology 

The total area of the contaminant release site, referred to as Solid Waste Management 

Unit 12 (SWMU 12), is approximately 3 acres. SWMU 12 is relatively flat with a total 

relief ranging from 3.0 to 8.5 feet above mean sea level. The water table is very shallow, 

ranging from 2 to 3 feet below ground surface. Danielsen (2003) interprets the groundwater flow to be primarily toward the east with a minor northerly component, except in 

wet periods, where it flows toward the northern marsh with a slight easterly component 

(Figure 2-3). 

MW01

MW04

MW10 MW05

MW03

MW02

MW09

MW08

MW11

MW06

MW07

Northern Marsh

Eastern Marsh

Figure 2-3. Map of SWMU 12 showing locations of wells and nearby marshes (Danielsen, 2003). 

In down-gradient parts of the plume, a shallow clay layer does not allow the 

contaminants to encounter water until a depth of about 8 to 10 ft below ground surface. 

The contaminated aquifer consists of fine sand beneath clay. The average horizontal 
2-4 

hydraulic conductivity of the aquifer is approximately 1.2 ft/day (DOD, 2005). The 

potentiometric surface is relatively flat lying, with an average hydraulic gradient of 

0.0015 to 0.0017 ft/ft. Recharge most likely occurs primarily through infiltration in areas 

where the surficial clay is breached or absent (DOD, 2005). 

Seismic evidence suggests that parts of the sand aquifer may be ancient buried channels 

(Figure 2-4 and Figure 2-5). This hypothesis is supported by hydraulic conductivity 

estimates from slug test data (Table 2-1). When the hydraulic conductivity is graphed 

verses the cumulative percentage of samples having that value or less (Figure 2-6), we 

can see two distinct sample populations, these populations correspond to where the slope 

of the line changes. We interpret the higher conductivity values to belong to wells 

screened in the channels. 

Figure 2-4. Seismic reflection profiles. The green line is interpreted as the base of the major channel 

or the older channel, the red line indicates the base of younger channel that has incised into the older 

channel. 
2-5 

Figure 2-5. Elevation of the base of the channel contoured from seismic data and well picks. The 

orange shows the lower elevations, the green shows the higher elevations, and the grey lines represent 

the seismic profile locations. 

Table 2-1. Slug test data compared to the number of hammer blows needed to penetrate 1 ft, 

averaged over the length of the screen zone. 

Well Screen Zone 

Depth (ft) 

Average 

Blow Counts 

Slug test 

results (ft/d) 

12mw01D 29-39 3.43 2.86 

12mw01S 4-14 3.95 3.69 

12mw02D 21-31 2.38 2.98 

12mw02S 4-14 5.14 1.06 

12mw03D 20-30 2.29 3.19 

12mw03S 4-14 6.10 4.19 

12mw04D 22-32 3.19 1.47 

12mw04S 4-14 4.00 7.22 

12mw05D 38.5-48.5 0.69 0.432 

12mw05S 4-14 4.46 3.7 

12mw06D 32-42 1.48 0.36 

12mw06S 4-14 5.46 0.0873 

12mw07D 35-45 1.52 0.19 

12mw07S 4-14 2.29 0.93 

12mw08D 29-39 0.29 0.073 

12mw08S 4-14 5.96 0.17 

12mw09D 26-36 1.48 5.3 

12mw09S 4-14 4.96 3.2 
2-6 

Cumulative % Slug Data

0.01

0.1

1

10

100

0 20 40 60 80 100

percent of samples

K ft/d 

Figure 2-6. Graph of data from the slug test, with hydraulic conductivity (ft/d) on the vertical axis 

and the cumulative percentage of samples having that value or less plotted on the horizontal axis. 

2.3 Conceptual Site Modeling 

Prior to modeling, the data must be collected and formatted to allow for sequential 

modeling using a graded approach. Our approach began with a simple Conceptual Site 

Model that honored existing data. The CSMs were gradually increased in complexity 

until the model output adequately represented the flow regime for the site as judged by 

comparison of predicted contaminant levels with monitoring results. In total, three 

conceptual models were developed. Each of these models is discussed in detail below. 

2.3.1 First Approach: Analytical Model: 

The first approach assumed a one-layer homogeneous aquifer structure with semi-infinite 

boundary conditions (Figure 2-7). An analytical solution of the reactive solute transport 

can be obtained with BIOCHLOR (Aziz et al., 2000). The results completely failed to 

match the plume data. Multiple iterations using different parameters failed to achieve 

results that matched the field conditions at the site. 
2-7 

12MW01D 12MW06D

SANDY_CLAY

SC

CLAY1

SAND1

CLBACY2

SAND2

CLAY3

COOPER

COOPER

1 70

GAMM

1 70

GAMM

5 10 15 20 25 30 35 40 45 505 10 15 20 25 30 35 40 45 50

Log

Depth

Log

Depth

0 0

5 5

10 10

15 15

20 20

25 25

30 30

35 35

40 40

45 45

50 50

SWMU site A-A' Cross-section

PETRA 1/19/2005 10:10:29 AM

Figure 2-7. Cross Section of the assumed geology for the analytical solution CSM. 

2.3.2 Second Approach: Numerical Model / Simple Geology: 

The second approach used only borehole descriptions and geophysical log data to 

develop the CSM. This model incorporated a layer-cake multi-aquifer system (Figure 

2-8). Petra was used to perform the correlations that were exported into GMS for 

modeling. In GMS MODFLOW and RT3D were used to simulate the migration of the 

chlorinated solvents. 

The results from Model II yielded a better fit than the first approach but did not 

adequately define the plume (Figure 2-9). 
2-8 

Sandy Clay

Sand 1

Clay 1

Sand 2

Clay 2

Sand 3

Clay 3

Cooper Marl

MW01D MW04D MW10S MW05D MW11D MW06D

Figure 2-8. Cross Section of the “Layer Cake Geology” used for our second approach. 

MW01

MW05 MW10

MW03

MW07

MW04

MW02

MW11 MW06

MW09

MW08

1996 1998 2000 2002 2004

0

3

6

9

12

15

18

concentration (mg/L)

Time (year)

PCE MW03S

 Computed

 Measured

Figure 2-9. The PCE plume from Model II is presented at left, and the computed PCE 

concentrations at monitoring well MW-03 are much lower than the observed values (right). 

2.3.3 Third Approach: Numerical Model / Complex Geology 

The third approach entailed development of a site model that incorporated both the 

geologic and seismic data in an attempt to more accurately represent the subsurface 

geology. These data were input into Petra and PetraSeis (Figure 2-10). Table 2-2 

contains the input parameters for Model III. Based on the seismic data two ancient 

stream channels were mapped through the middle of the PCE source. The channels 

control the local ground-water flow direction and provide a preferential chemical 

transport pathway. This new interpretation of the conceptual site model was used to run 

simulations again in GMS. 
2-9 

Sandy Clay

Clay 1

Silty Sand

Clay 2

Sand

Clay 3

Cooper Marl

Young

Channel

Major

Channel

MW-01D MW-04D MW-10S MW-03D MW-05D MW-11D MW-06D

Figure 2-10. The cross-section shows the Major channel and Younger channel, as well as the other 

hydrofacies in the site. 

By using a relatively high Horizontal K, and a low Kd for both of the channels (Table 

2-2), model output from the third simulation closely matched observed PCE 

concentrations and accurately predicted the direction and extent of the plume (Figure 

2-11). 

MW01

MW08

MW09

MW11

MW02

MW04 MW10

MW03 MW05

MW07

MW06

Figure 2-11. The simulated PCE plume from Model III is presented at left; computed PCE 

concentrations at monitoring well MW-03 more closely match observed values (right). 

1996 1998 2000 2002 2004

0

3

6

9

12

15

18

Concentration (mg/L 

Time (year)

PCE MW03S 

 Computed

 Measured
2-10 

Table 2-2. Estimated flow and transport parameters for Model III. 

Stratigraphic 

units 

Horizontal K 

(ft/d) 

Vertical K 

(ft/d) 

Long 

dispersivity 

PCE Kd 

(mL/g)

TCE Kd 

(mL/g)

Sandy clay 0.085 0.05 65 1.15 0.96 

Young channel 48 1.2 112 0.43 0.28 

Clay 1 0.06 0.01 83 1.36 0.84 

Major channel 41 1 98 0.48 0.35 

Silty sand 0.2 0.1 75 1.18 0.91 

Clay 2 0.05 0.009 50 1.28 0.82 

Sand 8 2 50 0.99 0.60 

Clay 3 0.005 0.001 50 1.28 0.60 

Cooper marl 0.2 0.05 50 1.15 0.96 

2.4 Designing a Performance Confirmation Monitoring Network 

After validation of the CSM with actual site data, AES used this model to determine an 

appropriate monitoring scheme for the contaminant plume. Specifically, the current 

monitoring program included four wells located outside the predicted 5-year footprint of 

the PCE plume (see circled wells in Figure 2-12). Removal of these 4 wells from future 

monitoring is recommended. The monitoring scheme also lacked any monitoring in the 

vicinity of the predicted plume head. A new monitoring point was recommended to be 

added at the yellow dot in Figure 2-12. 
2-11 

MW01

MW04 MW10

MW03

MW02

MW09

MW08

MW11

MW07

MW05

MW06

Figure 2-12. The predicted PCE plume in five years. Circled wells are suggested to be removed from 

the monitoring program to save money, while a new point is suggested to be added at the yellow dot 

to test the CSM and simulation results. 

2.4.1.1 Alternate Conceptual Site Model 

Further review of water level data (Table 2-3), revealed that MW-08 was an outlier 

because the water levels did not follow the same patterns as the other wells (Figure 2-13). 

Because of the nearly flat water table, the water level differences in MW-08 can seriously 

alter contour maps of the water table (Figure 2-14 and Figure 2-15). 

This well should be investigated to determine the cause of the observed water level 

discrepancies. If the discrepancies are caused by poor well construction or poor data 

quality, then the water levels in this well should be ignored. If, however, the data proves 

reliable, this well could indicate the need to further revise the CSM. In particular, close 

attention should be paid to how the ground-water flow changes with respect to climatic 

conditions. 
2-12 

Table 2-3. Water elevations (ft above MSL) in wells. 

Well Name Apr-98 Jun-98 Aug-99 Jul-04 May-05 

12MW01S 5.34 3.32 3.39 

12MW02S 5.26 3.16 3.29 2 

12MW03S 5.27 3.16 3.3 2.74 2.07 

12MW04S 5.35 3.23 3.4 2.72 2.14 

12MW05S 3.19 2.52 1.79 

12MW06S 2.65 2.47 1.71 

12MW07S 3.14 2.53 1.82 

12MW08S 3.61 3.81 1.25 

12MW09S 3.28 2.67 1.88 

Changes in Water Table Over Time

0

1

2

3

4

5

6

Oct-95 Jul-98 Apr-01 Jan-04 Oct-06

Time

Water Table (Feet above MSL)

MW-01

MW-02

MW-03

MW-04

MW-05

MW-06

MW-07

MW-08

MW-09

Figure 2-13. Change in water table over time. Note how MW-08 is the only well that doesn’t match 

the others. 
2-13 

2325200 2325250 2325300 2325350 2325400 2325450 2325500 2325550 2325600 2325650

404950

405000

405050

405100

405150

405200

405250

405300

405350

405400

405450

12MW02S

12MW03S 12MW05S

12MW06S

12MW08S

12MW09S

Figure 2-14. Contour Map of water table using data from July 2004 (feet above MSL) 

2325200 2325250 2325300 2325350 2325400 2325450 2325500 2325550 2325600 2325650

404950

405000

405050

405100

405150

405200

405250

405300

12MW02S

12MW03S 12MW05S

12MW06S

12MW09S

Figure 2-15. Contour map of water table using data from July 2004, without well MW-08 

(feet above MSL) 
2-14 

2.5 Strategy Application Conclusions 

This study demonstrates the importance of adequate conceptual site modeling as a tool to 

assess monitoring network performance. In this case, the conceptual site model 

simulation helped improve understanding of the extent of contamination and guided 

suggestions which may increase efficiency of the existing monitoring scheme and, 

significantly reduce monitoring costs. Specifically in this case, four monitoring wells 

were removed from the network, and one was added in order to better observe the plume 

frontier. 

Outcome from this case suggests that the bias and uncertainty introduced from inadequate 

conceptual models can exceed those introduced from an inadequate choice of model 

parameter values. In particular, adequate mapping of the subsurface geology through 

incorporation of log and seismic survey data with geophysical software was important in 

developing an accurate conceptual site model. 

Time trend analysis of water levels from monitoring wells results in very good 

correlation, with the exception of MW-08. The discrepancies between MW-08 and the 

other monitoring wells result in significant variations in the modeled water table surface. 

Because MW-08 has been identified as an outlier, these discrepancies should be 

evaluated. 

Figure 2-16 presents a visual illustration of the activities and outcomes resulting from 

application of the Strategy at the Charleston Naval Weapons Station below. 
2-15 

Figure 2-16. Activities and results of the Strategy application at Charleston Naval Weapons Station 
2-16 

2.6 Charleston References 

Aziz, C.E., et al. EPA /600/R-00/008. “BIOCHLOR Version 1.0, User’s Manual.” 2000. 

Department of Defense. Site Information for RDT&E Opportunities, Strategic 

Environmental Research and Development Program. November 2005. 

Ferm, J.C.. Depositional Model in Coal Exploration and Development, Sedimentary 

Environments and Hydrocarbons, R.S. Saxena, ed. AAPG/NOGS Short Course, 

New Orleans Geological Society. pp. 60–78. 1976. 

Gohn, G.S., et al. “Preliminary Stratigraphic Database for the Subsurface Tertiary and 

Uppermost Cretaceous Sediments of Dorchester County, South Carolina.” U.S. 

Geological Survey Open-File Report 00-049-A. 2000. 

Danielsen, M.W. The Use and Implementation of Innovative Technologies for 

Investigating Selected Sites at the Naval Weapons Station, Charleston, South 

Carolina. Master Thesis for University of South Carolina. 2003. 

Weems, R.E., and E.M., Jr. Lemon. Geologic Map of the Cainhoy, Charleston, Fort 

Moultrie, and North Charleston quadrangles, S.C., with text (1:24,000). U.S. 

Geological Survey Map I-1935. 1993. 
2-17 

Appendix 2-A. 

Summary of Selected Volatile Organic Compounds in Ground Water
2-18 

SWMU 12 Naval Weapons Station, Charleston 

 PCE TCE cis-1,2-DCE Vinyl Chloride 1,1,1-TCA 1,1-DCE 1,1-DCA 1,2-DCA 

Location ID Sample Date ug/L ug/L ug/L ug/L ug/L ug/L ug/L ug/L 

12MW02D 8/30/00 < 5 < 5 < 5 < 2 < 5 < 5 < 5 < 5 

12MW02D 11/29/00 < 0.21 < 0.17 < 0.17 < 0.15 < 0.18 0.22 < 0.18 < 0.21 

12MW02D 2/27/01 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 < 0.16 < 0.23 < 0.2 

12MW02D 5/15/01 < 0.38 1.5 < 0.31 < 0.19 < 0.27 < 0.26 < 0.29 < 0.35 

12MW02D 8/29/01 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 0.32 < 0.23 < 0.2 

12MW02D 12/3/01 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 < 0.16 < 0.23 < 0.2 

12MW02D 2/28/02 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 < 0.16 < 0.23 < 0.2 

12MW02D 6/10/02 < 0.1 < 0.13 < 0.28 < 0.18 < 0.17 < 0.13 < 0.64 < 0.15 

12MW02D 9/9/02 2.1 1.2 0.25 < 0.2 0.52 1.2 0.39 < 0.18 

12MW02D 1/8/03 0.2 0.36 < 0.28 < 0.18 < 0.17 0.35 < 0.64 < 0.15 

12MW02D 4/15/03 < 0.17 < 0.12 < 0.22 < 0.1 < 0.16 < 0.17 < 0.11 < 0.14 

12MW02D 7/16/03 < 0.31 < 0.25 < 0.4 < 0.11 < 0.27 < 0.41 < 0.3 < 0.34 

12MW02D 8/16/04 < 0.31 < 0.25 < 0.4 < 0.11 < 0.27 < 0.41 < 0.3 < 0.34 

12MW02S 8/30/00 0 0 0 0 0 200 12 0 

12MW02S 11/29/00 < 0.21 0.24 0.75 < 0.15 < 0.18 110 5.7 < 0.21 

12MW02S 2/27/01 < 1.3 < 1.4 < 2.4 < 1.7 < 2.2 160 8.6 < 2 

12MW02S 5/15/01 < 3.8 6.4 < 3.1 < 1.9 < 2.7 81 5.4 < 3.5 

12MW02S 8/29/01 < 0.21 4.8 < 0.56 < 0.35 < 0.33 23 2.1 < 0.3 

12MW02S 12/3/01 < 0.25 0.47 0.66 < 0.35 < 0.44 69 5.5 < 0.39 

12MW02S 2/28/02 < 0.63 < 0.68 < 1.2 < 0.87 < 1.1 46 2.8 < 0.98 

12MW02S 6/10/02 < 0.52 < 0.64 < 1.4 < 0.88 < 0.84 84 6.7 < 0.76 

12MW02S 9/9/02 < 0.82 < 0.83 < 1 < 0.99 < 1.3 58 5.4 < 0.88 

12MW02S 1/8/03 < 0.52 2.3 1.6 < 0.88 < 0.84 130 15 < 0.76 

12MW02S 4/15/03 < 2.2 < 1.5 2.9 < 1.3 < 2.1 250 27 < 1.8 

12MW02S 7/15/03 < 3.1 < 2.5 < 4 < 1.1 < 2.7 100 14 < 3.4 

12MW02S 9/17/03 < 1.7 2.1 < 2.2 2.8 < 1.6 150 26 < 1.4 

12MW02S 1/14/04 < 2.2 < 1.5 < 2.7 < 1.3 < 2.1 140 29 < 1.8 

12MW02S 4/28/04 < 2.6 11 11 3.4 < 2.4 530 200 < 2.7 

12MW02S 8/16/04 < 0.31 < 0.25 < 0.4 < 0.11 < 0.27 1.9 < 0.3 < 0.34 

12MW03D 8/30/00 0 6 18 0 0 0 0 0 

12MW03D 11/30/00 < 0.41 5.8 24 < 0.31 < 0.36 0.99 < 0.35 < 0.42 

12MW03D 2/27/01 < 0.13 1.4 6.8 < 0.17 < 0.22 0.54 < 0.23 < 0.2 

12MW03D 5/15/01 6 15 15 0.88 9.8 7.5 1.6 < 0.35 

12MW03D 8/29/01 < 0.1 12 19 0.73 < 0.17 2.7 < 0.64 < 0.15 

12MW03D 12/4/01 < 0.1 33 44 1.3 < 0.17 6.3 < 0.64 < 0.15 

12MW03D 3/1/02 < 0.13 3.3 13 0.2 < 0.22 1.2 < 0.23 < 0.2 

12MW03D 6/11/02 < 0.1 19 21 < 0.18 < 0.17 3.2 < 0.64 < 0.15 

12MW03D 9/10/02 0.7 4.6 14 0.3 0.57 2.1 0.45 < 0.18 

12MW03D 1/9/03 < 0.1 2 11 0.73 < 0.17 1.2 < 0.64 < 0.15 

12MW03D 4/15/03 < 0.31 3.2 11 0.65 < 0.27 1.9 1.8 < 0.34 

12MW03D 7/15/03 < 0.17 3.3 13 0.82 < 0.16 1.9 1.5 < 0.14 

12MW03D 8/16/04 < 0.31 4 16 1.8 < 0.27 4.3 4.7 < 0.34 

12MW03S 8/30/00 7300 9,500 7,600 1,600 16,000 4,500 4,000 2,300 

12MW03S 11/30/00 8500 9000 7000 160 31000 11000 5100 < 170 

12MW03S 2/27/01 6500 5200 12000 230 3700 3100 2100 < 200 

12MW03S 5/15/01 11000 7900 8900 < 940 76000 29000 20000 < 1700 
2-19 

12MW03S 8/29/01 12000 16000 12000 < 880 73000 34000 23000 < 760 

12MW03S 12/5/01 16000 12000 14000 < 880 92000 46000 35000 < 760 

12MW03S 3/1/02 7100 5600 13000 600 5300 5400 4500 < 200 

12MW03S 6/11/02 13000 5900 13000 1100 32000 20000 16000 260 

12MW03S 9/10/02 7700 4700 13000 430 5200 6100 5300 < 190 

12MW03S 1/9/03 4600 4300 7300 370 4000 5100 3300 45 

12MW03S 4/21/03 6800 3600 9900 640 15000 12000 8800 150 

12MW03S 7/17/03 2100 1900 3100 140 580 1200 960 < 85 

12MW03S 9/16/03 2600 1400 2800 120 1700 2300 1200 < 50 

12MW03S 1/14/04 1900 3000 3300 150 940 1700 1000 < 17 

12MW03S 4/27/04 6400 5300 5700 380 8100 10000 5100 65 

12MW03S 8/18/04 1200 1400 1700 96 370 1000 590 < 27 

12MW04D 8/28/00 < 5 < 5 < 5 < 2 < 5 < 5 < 5 < 5 

12MW04D 11/28/00 < 0.21 < 0.17 < 0.17 < 0.15 < 0.18 < 0.17 < 0.18 < 0.21 

12MW04D 2/26/01 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 < 0.16 < 0.23 < 0.2 

12MW04D 5/14/01 < 0.38 < 0.34 < 0.31 < 0.19 < 0.27 < 0.26 < 0.29 < 0.35 

12MW04D 8/27/01 < 0.38 < 0.34 < 0.31 < 0.19 < 0.27 < 0.26 < 0.29 < 0.35 

12MW04D 12/3/01 < 0.1 < 0.13 < 0.28 < 0.18 < 0.17 < 0.13 < 0.64 < 0.15 

12MW04D 2/28/02 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 < 0.16 < 0.23 < 0.2 

12MW04D 6/11/02 < 0.1 < 0.13 < 0.28 < 0.18 < 0.17 < 0.13 < 0.64 < 0.15 

12MW04D 9/9/02 < 0.16 < 0.17 < 0.2 < 0.2 < 0.26 < 0.33 < 0.24 < 0.18 

12MW04D 1/7/03 < 0.1 < 0.13 < 0.28 < 0.18 < 0.17 < 0.13 < 0.64 < 0.15 

12MW04D 4/15/03 < 0.31 0.28 < 0.4 < 0.11 < 0.27 < 0.41 < 0.3 < 0.34 

12MW04D 7/14/03 < 0.17 < 0.12 < 0.22 < 0.1 < 0.16 < 0.17 < 0.11 < 0.14 

12MW04D 8/18/04 < 0.2 < 0.2 < 0.15 < 0.15 < 0.19 < 0.18 < 0.2 < 0.22 

12MW04S 8/28/00 < 5 < 5 < 5 < 2 < 5 < 5 < 5 < 5 

12MW04S 11/28/00 < 0.21 < 0.17 < 0.17 < 0.15 < 0.18 < 0.17 < 0.18 < 0.21 

12MW04S 2/26/01 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 < 0.16 < 0.23 < 0.2 

12MW04S 5/14/01 < 0.38 < 0.34 < 0.31 < 0.19 < 0.27 < 0.26 < 0.29 < 0.35 

12MW04S 8/27/01 < 0.38 < 0.34 < 0.31 < 0.19 < 0.27 < 0.26 < 0.29 < 0.35 

12MW04S 12/3/01 < 0.1 < 0.13 < 0.28 < 0.18 < 0.17 < 0.13 < 0.64 < 0.15 

12MW04S 2/28/02 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 < 0.16 < 0.23 < 0.2 

12MW04S 6/11/02 < 0.1 < 0.13 < 0.28 < 0.18 < 0.17 < 0.13 < 0.64 < 0.15 

12MW04S 9/9/02 < 0.16 < 0.17 < 0.2 < 0.2 < 0.26 < 0.33 < 0.24 < 0.18 

12MW04S 1/7/03 < 0.1 < 0.13 < 0.28 < 0.18 < 0.17 < 0.13 < 0.64 < 0.15 

12MW04S 4/15/03 < 0.31 < 0.25 < 0.4 < 0.11 < 0.27 < 0.41 < 0.3 < 0.34 

12MW04S 7/14/03 < 0.17 < 0.12 < 0.22 < 0.1 < 0.16 < 0.17 < 0.11 < 0.14 

12MW04S 9/16/03 < 0.17 < 0.12 < 0.22 < 0.1 < 0.16 < 0.17 < 0.11 < 0.14 

12MW04S 1/12/04 < 0.31 < 0.25 < 0.4 < 0.11 < 0.27 < 0.41 < 0.3 < 0.34 

12MW04S 4/26/04 < 0.31 < 0.25 < 0.4 < 0.11 < 0.27 < 0.41 < 0.3 < 0.34 

12MW04S 8/18/04 < 0.31 < 0.25 < 0.4 < 0.11 < 0.27 < 0.41 < 0.3 < 0.34 

12MW05D 8/30/00 < 5 9.6 6.2 < 2 < 5 < 5 < 5 < 5 

12MW05D 11/30/00 3.1 5.3 2.5 < 0.15 1.4 2.6 < 0.18 < 0.21 

12MW05D 2/28/01 < 0.13 1.8 1.4 < 0.17 < 0.22 0.68 < 0.23 < 0.2 

12MW05D 5/15/01 < 0.38 1.8 2.1 < 0.19 < 0.27 0.83 < 0.29 < 0.35 

12MW05D 8/28/01 < 0.1 0.55 3.5 < 0.18 < 0.17 0.97 < 0.64 < 0.15 

12MW05D 12/4/01 < 0.13 1 0.75 < 0.17 < 0.22 0.3 < 0.23 < 0.2 

12MW05D 3/1/02 < 0.13 0.74 0.76 < 0.17 < 0.22 0.37 < 0.23 < 0.2 

12MW05D 6/11/02 < 0.1 0.89 0.97 < 0.18 < 0.17 0.39 < 0.64 < 0.15 

12MW05D 9/10/02 < 0.16 0.56 0.54 < 0.2 < 0.26 < 0.33 < 0.24 < 0.18 
2-20 

12MW05D 1/8/03 < 0.1 0.64 0.39 < 0.18 < 0.17 0.34 < 0.64 < 0.15 

12MW05D 4/15/03 < 0.31 0.47 < 0.4 < 0.11 < 0.27 < 0.41 < 0.3 < 0.34 

12MW05I 8/30/00 < 5 < 5 < 5 < 2 < 5 < 5 < 5 < 5 

12MW05I 11/30/00 12 20 23 0.43 23 12 3.3 < 0.42 

12MW05I 2/28/01 0.46 0.73 1.1 < 0.17 0.33 0.46 < 0.23 < 0.2 

12MW05I 5/16/01 0.86 0.71 0.31 < 0.19 1.4 0.6 < 0.29 < 0.35 

12MW05I 8/29/01 0.7 0.73 < 0.31 < 0.19 0.48 0.59 < 0.29 < 0.35 

12MW05I 12/4/01 < 0.13 1 < 0.24 < 0.17 < 0.22 0.25 < 0.23 < 0.2 

12MW05I 3/1/02 < 0.13 1.5 < 0.24 < 0.17 < 0.22 0.4 < 0.23 < 0.2 

12MW05I 6/11/02 < 0.1 1 < 0.28 < 0.18 < 0.17 0.35 < 0.64 < 0.15 

12MW05I 9/10/02 0.17 0.63 < 0.2 < 0.2 < 0.26 < 0.33 < 0.24 < 0.18 

12MW05I 1/8/03 < 0.1 0.61 < 0.28 < 0.18 < 0.17 < 0.13 < 0.64 < 0.15 

12MW05I 4/15/03 < 0.31 0.3 < 0.4 < 0.11 < 0.27 < 0.41 < 0.3 < 0.34 

12MW05I 7/14/03 < 0.17 0.37 < 0.22 < 0.1 < 0.16 < 0.17 < 0.11 < 0.14 

12MW05I 8/18/04 < 0.31 < 0.25 < 0.4 < 0.11 < 0.27 < 0.41 < 0.3 < 0.34 

12MW05S 8/30/00 580 27,000 1,500 33 640 10,000 66 13 

12MW05S 11/30/00 400 22000 890 < 31 440 8500 < 35 < 42 

12MW05S 2/28/01 270 12000 580 < 170 360 7100 < 230 < 200 

12MW05S 5/16/01 500 16000 690 < 190 590 8900 < 290 < 350 

12MW05S 8/29/01 3100 23000 1400 < 190 2600 16000 310 < 350 

12MW05S 12/4/01 740 25000 1100 < 350 < 330 13000 < 1300 < 300 

12MW05S 3/1/02 360 18000 800 < 350 < 440 9300 < 460 < 390 

12MW05S 6/11/02 < 210 23000 1600 < 350 790 13000 < 1300 < 300 

12MW05S 9/10/02 600 20000 1600 < 350 < 330 12000 < 1300 < 300 

12MW05S 1/8/03 460 20000 1200 < 350 < 330 11000 < 1300 < 300 

12MW05S 4/22/03 < 61 21000 1200 < 21 < 53 9400 < 60 < 68 

12MW05S 7/17/03 740 20000 1200 < 210 < 330 10000 < 210 < 280 

12MW05S 9/16/03 660 16000 1200 < 350 < 460 8900 < 430 < 400 

12MW05S 1/14/04 620 18000 1200 < 21 230 8600 < 60 < 68 

12MW05S 4/27/04 880 21000 1300 58 210 7800 36 < 34 

12MW05S 8/18/04 910 22000 1400 120 290 9600 68 < 43 

12MW06D 8/29/00 < 5 < 5 < 5 < 2 < 5 < 5 < 5 < 5 

12MW06D 11/29/00 < 0.21 < 0.17 < 0.17 < 0.15 < 0.18 < 0.17 < 0.18 < 0.21 

12MW06D 2/27/01 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 < 0.16 < 0.23 < 0.2 

12MW06D 5/14/01 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 < 0.16 < 0.23 < 0.2 

12MW06D 8/28/01 < 0.1 < 0.13 < 0.28 < 0.18 < 0.17 < 0.13 < 0.64 < 0.15 

12MW06S 8/29/00 < 5 < 5 < 5 < 2 < 5 < 5 < 5 < 5 

12MW06S 11/29/00 < 0.21 < 0.17 < 0.17 < 0.15 0.42 < 0.17 < 0.18 < 0.21 

12MW06S 2/27/01 < 0.13 < 0.14 < 0.24 < 0.17 0.29 < 0.16 < 0.23 < 0.2 

12MW06S 5/14/01 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 < 0.16 < 0.23 < 0.2 

12MW06S 8/28/01 < 0.38 < 0.34 < 0.31 < 0.19 < 0.27 < 0.26 < 0.29 < 0.35 

12MW06S 12/4/01 < 0.13 0.15 < 0.24 < 0.17 < 0.22 < 0.16 < 0.23 < 0.2 

12MW06S 3/1/02 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 < 0.16 < 0.23 < 0.2 

12MW06S 6/11/02 < 0.1 < 0.13 < 0.28 < 0.18 < 0.17 < 0.13 < 0.64 < 0.15 

12MW06S 9/9/02 < 0.16 < 0.17 < 0.2 < 0.2 < 0.26 < 0.33 < 0.24 < 0.18 

12MW06S 1/7/03 < 0.16 < 0.17 < 0.2 < 0.2 < 0.26 < 0.33 < 0.24 < 0.18 

12MW06S 4/15/03 < 0.31 < 0.25 < 0.4 < 0.11 < 0.27 < 0.41 < 0.3 < 0.34 

12MW07D 8/28/00 < 5 < 5 < 5 < 2 < 5 < 5 < 5 < 5 

12MW07D 11/29/00 < 0.21 < 0.17 < 0.17 < 0.15 < 0.18 < 0.17 < 0.18 < 0.21 

12MW07D 2/26/01 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 < 0.16 < 0.23 < 0.2 
2-21 

12MW07D 5/14/01 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 < 0.16 < 0.23 < 0.2 

12MW07D 8/29/01 1 0.44 < 0.31 < 0.19 0.7 0.78 < 0.29 < 0.35 

12MW07S 8/28/00 < 5 < 5 < 5 < 2 < 5 < 5 < 5 < 5 

12MW07S 11/28/00 < 0.21 < 0.17 < 0.17 < 0.15 < 0.18 < 0.17 < 0.18 < 0.21 

12MW07S 2/26/01 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 < 0.16 < 0.23 < 0.2 

12MW07S 5/14/01 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 < 0.16 < 0.23 < 0.2 

12MW07S 8/29/01 0.77 0.38 < 0.31 < 0.19 0.55 0.67 < 0.29 < 0.35 

12MW08D 8/29/00 < 5 < 5 < 5 < 2 < 5 < 5 < 5 < 5 

12MW08D 11/28/00 < 0.21 < 0.17 < 0.17 < 0.15 < 0.18 < 0.17 < 0.18 < 0.21 

12MW08D 2/26/01 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 < 0.16 < 0.23 < 0.2 

12MW08D 5/14/01 < 0.38 < 0.34 < 0.31 < 0.19 < 0.27 < 0.26 < 0.29 < 0.35 

12MW08D 8/27/01 < 0.38 < 0.34 < 0.31 < 0.19 < 0.27 < 0.26 < 0.29 < 0.35 

12MW08S 8/28/00 < 5 < 5 < 5 < 2 < 5 < 5 < 5 < 5 

12MW08S 11/28/00 < 0.21 < 0.17 < 0.17 < 0.15 < 0.18 < 0.17 < 0.18 < 0.21 

12MW08S 2/26/01 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 < 0.16 < 0.23 < 0.2 

12MW08S 5/14/01 < 0.38 < 0.34 < 0.31 < 0.19 < 0.27 < 0.26 < 0.29 < 0.35 

12MW08S 8/27/01 < 0.38 < 0.34 < 0.31 < 0.19 < 0.27 < 0.26 < 0.29 < 0.35 

12MW09D 8/29/00 < 5 < 5 < 5 < 2 < 5 0 0 < 5 

12MW09D 11/29/00 < 0.21 < 0.17 < 0.17 < 0.15 < 0.18 0.18 0.24 < 0.21 

12MW09D 2/27/01 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 0.34 0.34 < 0.2 

12MW09D 5/15/01 < 0.38 < 0.34 < 0.31 < 0.19 < 0.27 0.3 0.31 < 0.35 

12MW09D 8/29/01 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 0.52 0.33 < 0.2 

12MW09D 12/3/01 < 0.1 < 0.13 < 0.28 < 0.18 < 0.17 < 0.13 < 0.64 < 0.15 

12MW09D 2/28/02 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 0.19 < 0.23 < 0.2 

12MW09D 6/10/02 < 0.1 < 0.13 < 0.28 < 0.18 < 0.17 < 0.13 < 0.64 < 0.15 

12MW09D 9/10/02 < 0.16 < 0.17 < 0.2 < 0.2 < 0.26 < 0.33 < 0.24 < 0.18 

12MW09D 1/7/03 < 0.1 < 0.13 < 0.28 < 0.18 < 0.17 < 0.13 < 0.64 < 0.15 

12MW09D 4/15/03 < 0.17 < 0.12 < 0.22 < 0.1 < 0.16 < 0.17 0.14 < 0.14 

12MW09D 7/16/03 < 0.31 < 0.25 < 0.4 < 0.11 < 0.27 < 0.41 < 0.3 < 0.34 

12MW09D 8/16/04 < 0.2 < 0.2 < 0.15 < 0.15 < 0.19 < 0.18 < 0.2 < 0.22 

12MW09S 8/29/00 < 5 < 5 < 5 < 2 < 5 120 120 < 5 

12MW09S 11/29/00 < 0.21 0.94 0.3 0.49 1 98 97 < 0.21 

12MW09S 2/27/01 < 0.13 0.89 0.32 0.24 0.79 86 86 < 0.2 

12MW09S 5/15/01 < 3 < 2.7 < 2.4 < 1.5 < 2.2 60 73 < 2.8 

12MW09S 8/29/01 < 1 1.3 < 1.9 < 1.4 < 1.7 83 76 < 1.6 

12MW09S 12/3/01 < 0.82 < 1 < 2.2 < 1.4 < 1.3 69 73 < 1.2 

12MW09S 2/28/02 < 1 < 1.1 < 1.9 < 1.4 < 1.7 52 51 < 1.6 

12MW09S 6/10/02 < 0.82 < 1 < 2.2 < 1.4 < 1.3 110 100 < 1.2 

12MW09S 9/10/02 < 0.66 1.3 < 0.81 < 0.79 < 1 31 35 < 0.7 

12MW09S 1/7/03 < 0.41 < 0.51 < 1.1 < 0.7 < 0.67 18 20 < 0.6 

12MW09S 4/16/03 < 0.34 0.47 < 0.44 < 0.21 < 0.33 23 22 < 0.28 

12MW09S 7/15/03 < 0.61 0.71 < 0.8 0.39 < 0.53 32 30 < 0.68 

12MW09S 9/17/03 < 0.34 0.61 < 0.44 < 0.21 < 0.33 28 28 < 0.28 

12MW09S 1/13/04 < 0.43 < 0.31 < 0.55 < 0.26 < 0.41 24 23 < 0.35 

12MW09S 4/28/04 < 0.51 < 0.5 < 0.36 < 0.39 < 0.47 26 23 < 0.54 

12MW09S 8/16/04 < 0.61 < 0.49 < 0.8 < 0.21 < 0.53 25 20 < 0.68 

12MW10S 11/30/00 3300 1900 9300 660 19000 2400 7000 < 420 

12MW10S 2/28/01 3100 1100 5500 480 38000 5100 15000 < 390 

12MW10S 5/16/01 3500 1800 6400 1600 17000 5600 5000 < 440 

12MW10S 8/29/01 4200 3500 9200 1800 19000 7000 6600 < 190 
2-22 

12MW10S 12/5/01 4400 2600 12000 2200 16000 12000 6100 < 300 

12MW10S 3/1/02 3400 1600 7300 1400 16000 9300 5400 < 390 

12MW10S 6/11/02 2400 1200 6800 1600 6800 4900 2800 < 140 

12MW10S 9/10/02 3400 1300 7000 1400 11000 4800 4400 < 120 

12MW10S 1/8/03 2400 950 3900 900 17000 5700 7700 79 

12MW10S 4/23/03 1800 710 2300 470 5600 4800 2400 < 170 

12MW10S 7/16/03 3400 1100 3000 610 9300 9700 4200 < 270 

12MW10S 9/16/03 1600 550 2100 480 3600 4400 1800 < 140 

12MW10S 1/14/04 1600 580 1900 460 2700 4300 1600 < 27 

12MW10S 4/27/04 2200 840 2100 460 4200 5400 2400 37 

12MW10S 8/18/04 2100 730 630 3100 3900 2100 27 

12MW11D 8/29/00 < 5 < 5 < 5 < 2 < 5 < 5 < 5 < 5 

12MW11D 11/29/00 < 0.21 < 0.17 < 0.17 < 0.15 < 0.18 < 0.17 < 0.18 < 0.21 

12MW11D 2/27/01 2.3 0.98 0.75 < 0.17 < 0.22 0.41 < 0.23 < 0.2 

12MW11D 5/15/01 < 0.38 < 0.34 < 0.31 < 0.19 < 0.27 < 0.26 < 0.29 < 0.35 

12MW11D 8/28/01 < 0.13 0.47 < 0.24 < 0.17 < 0.22 0.24 < 0.23 < 0.2 

12MW11D 12/4/01 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 < 0.16 < 0.23 < 0.2 

12MW11D 3/1/02 < 0.13 < 0.14 < 0.24 < 0.17 < 0.22 < 0.16 < 0.23 < 0.2 

12MW11D 6/10/02 < 0.1 < 0.13 < 0.28 < 0.18 < 0.17 < 0.13 < 0.64 < 0.15 

12MW11D 9/9/02 < 0.16 < 0.17 < 0.2 < 0.2 < 0.26 < 0.33 < 0.24 < 0.18 

12MW11D 1/8/03 < 0.1 < 0.13 < 0.28 < 0.18 < 0.17 < 0.13 < 0.64 < 0.15 

12MW11D 4/15/03 < 0.17 < 0.12 < 0.22 < 0.1 < 0.16 < 0.17 < 0.11 < 0.14 

12MW11D 7/16/03 < 0.31 < 0.25 < 0.4 < 0.11 < 0.27 < 0.41 < 0.3 < 0.34 

12MW11S 8/29/00 < 5 7.6 < 5 < 2 < 5 130 20 < 5 

12MW11S 11/29/00 < 0.21 3.8 0.37 < 0.15 0.34 65 6.1 < 0.21 

12MW11S 2/27/01 15 16 8.9 < 0.7 < 0.87 70 9.3 < 0.78 

12MW11S 5/15/01 < 1.5 2.6 < 1.2 < 0.75 < 1.1 41 5.5 < 1.4 

12MW11S 8/28/01 < 0.5 38 1.3 < 0.7 1.1 80 7 < 0.78 

12MW11S 1/8/03 < 0.1 1.4 0.58 < 0.18 < 0.17 71 12 0.23 

12MW12D 8/28/01 < 0.13 2.3 < 0.24 < 0.17 < 0.22 0.34 < 0.23 < 0.2 

12MW12S 8/28/01 15 2900 29 0.44 10 420 5.8 0.95 

12MW12S 12/4/01 65 2400 38 < 7 < 8.7 680 < 9.2 < 7.8 

12MW12S 3/1/02 < 31 1800 < 61 < 44 < 55 280 < 58 < 49 

12MW12S 6/10/02 110 2400 < 70 < 44 < 42 880 < 160 < 38 

12MW12S 9/9/02 94 2200 < 51 < 49 < 64 400 < 59 < 44 

12MW12S 1/8/03 < 13 1400 < 35 < 22 < 21 190 < 80 < 19 

12MW12S 4/22/03 < 6.9 430 9.2 < 4.1 < 6.6 140 4.7 < 5.6 

12MW12S 7/16/03 < 7.7 250 < 10 < 2.7 < 6.6 99 < 7.5 < 8.5 

12MW12S 9/15/03 < 7.7 180 < 10 < 2.7 < 6.6 68 < 7.5 < 8.5 

12MW12S 1/13/04 2.6 120 4 < 0.21 1.2 48 2.7 < 0.28 

12MW12S 4/27/04 2.6 84 4.1 < 0.31 0.94 44 3 < 0.43 

12MW12S 8/17/04 2.7 93 4.2 0.24 1.2 58 3.1 0.29 
3-1 

3 Brookhaven National Laboratory 

3.1 Introduction 

The Brookhaven National Laboratory (BNL) site was chosen to test the applicability of 

the Strategy to a glacial till environment in the Northeastern United States. In this case 

study we focus on applying certain concepts in the Strategy to an area of tritium 

contamination at the BNL site. 

As outlined in the Strategy, our application began with a compilation and analysis of 

existing characterization and monitoring data and synthesis of an alternative conceptual 

site model. Information in Section 3.2 is background information including location, 

geology and hydrology of the site. Discussion of the tritium contamination begins in 

Section 3.2.5 and is summarized below. 

Tritium Plume and Remediation 

In early 1997, monitoring data revealed a plume of tritium contaminated ground water 

from the High Flux Beam Reactor (HFBR) at the BNL site. Tritium, radioactive 

hydrogen that forms water, was leaking from the spent fuel pool within the HFBR. 

In May 1997, a system to pump the leading edge of the tritium plume was started as an 

interim action to prevent any further movement of the tritium and to ensure that the 

contamination remains entirely on-site. The contaminated water is being recharged onsite at levels below the Federal and State standards farther from the site boundary. The 

spent fuel has all been shipped off-site and the water was drained from the fuel pool, 

eliminating further leaks. The reactor is currently shut down, and the United States 

Department of Energy (DOE) has decided not to restart the reactor (DOE, 2006). 

Currently, to remediate the tritium in the ground water at the BNL, a series of extraction 

and re-injection wells provide a recirculation system (Figure 3-1). Because the half-life 

of tritium is 12.5 years, this recirculation system allows time for the tritium to decay 

before exiting the BNL boundary. The schematic in Figure 3-1 also mentions a VOC 

plume in the HBFR vicinity. While this plume is not the focus of this Case Study, it is 

worthwhile to note that understanding of the flow and transport behavior of this plume 

may provide useful information about the potential pathway of the tritium plume 

Key Conclusions 

This case study illustrates the following key points: 

Conceptual Site Models and flow and transport simulations are powerful visualization 

techniques for communicating the impact of Performance Indicators. In this Chapter, we 

show examples of models developed using, Excel, MODFLOW, and GMS (Section 3.3). 

Conceptual Site Models and flow and transport simulations can be useful in evaluating 

the effectiveness of various pumping alternatives, and thus, can aid in development of an 

efficient and cost effective monitoring and/or remediation program (Section 3.3.2). 
3-2 

Figure 3-1. Schematic of tritium/VOC plume pump and treat system (DOE, 2000) 

3.2 Compilation of Available Data 

This section provides a summary of the readily available data compiled to prepare this 

evaluation with the majority of the information collected from BNL online reports. 

3.2.1 Site Background 

Brookhaven National Laboratory, located on Long Island in New York, is a multiprogram DOE National Laboratory (Figure 3-2). Established in 1947, BNL has been 

operated by contractors, first to the Atomic Energy Commission (AEC), and now to the 

United States Department of Energy (DOE) - the site owners. Since March 1998, BNL 

has been operated and managed by Brookhaven Science Associates. BNL conducts basic 

and applied research in high energy nuclear and solid state physics, fundamental material 

and structure properties and the interaction of matter, nuclear medicine, biomedical and 

environmental sciences, and selected energy technologies. To conduct this research BNL 

has designed, built, and run installations for scientific research, such as particle 

accelerators and nuclear reactors. Most of its main facilities are in an area of 

approximately 900 acres near the center of the site (DOE, 2006). 

There are a number of areas at BNL where ground-water contamination is known or 

suspected. Over 30 Areas of Concern (AOCs) have been identified. On-site soil is 

contaminated with volatile organic compounds (VOCs), heavy metals, polycyclic 

aromatic hydrocarbons (PAHs), and radioactive materials including cesium-137, 
3-3 

strontium-90 and tritium. On-site and off-site ground water is contaminated with VOCs, 

radionuclides, and the pesticide/fumigant ethylene dibromide (EDB). On-site 

contaminated drinking water wells have been closed or treatment systems have been 

added. VOCs in off-site ground water exceed Federal and State drinking water standards, 

so the DOE has connected neighboring properties to public water as a protective measure 

until the final cleanup is complete. Radionuclides in off-site ground water do not exceed 

Federal or State standards (DOE, 2006). 

Figure 3-2. Location of the Brookhaven National Laboratory (Scorca et al., 1999) 
3-4 

3.2.2 Geologic Information 

Brookhaven National Lab is located on Pleistocene glacial deposits of the Northeastern 

United States. The stratigraphy in the region of the BNL consists of approximately 1,300 

feet of unconsolidated deposits overlying pre-Cambrian bedrock (Figure 3-3). Among 

these unconsolidated deposits, the Ground-Water Monitoring Programs at BNL currently 

focus on ground-water quality within upper Pleistocene glacial deposits, and the upper 

portions of the Matawan Group-Magothy Formation. 

The Pleistocene deposits are about 100 to 200 feet thick and are divided into two primary 

hydrogeologic units: undifferentiated sand and gravel outwash and moraine deposits; and 

finer-grained, more poorly sorted fine to medium white to greenish sand with interstitial 

clay. 

The most obvious Pleistocene glacial features are the large erratics (glacier transported 

boulders) and scattered deposits of glacial till (a mix of fine silt, sand, gravel, and large 

boulders). The flowing ice of the southward advancing ice sheet sculpted the landscape 

by not only eroding and transporting vast quantities of rock and sediment, but also by 

blocking and altering the course of rivers, filling valleys with sediment, and depositing 

large quantities of till in the terminal moraines along its leading edge. These hills are 

apparent throughout Long Island (BNL, 2004). 

3.2.3 Hydrogeologic Information 

Table 3-1 presents a generalized comparison of the geologic and hydrogeologic units 

below BNL. Descriptions of the units in the table are limited to the unconsolidated 

Pleistocene and Cretaceous material overlying the Paleozoic bedrock. Hydrostratigraphic 

relationships are shown in cross-section in Figure 3-3. 

Figure 3-3. Hydrostratigraphy of the Brookhaven National Laboratory (BNL, 2004) 
3-5 

3.2.4 Hydrologic Data 

The saturated part of the upper Pleistocene deposit forms the Upper Glacial Aquifer, 

which contains the water table throughout most of Long Island. This unit consists mostly 

of moderately to well-sorted sand and fine gravel and is highly permeable in most places. 

The Upper Glacial aquifer underlies the entire 300-square mile (mi2

) study area and is the 

source of base flow to streams. 

The average island-wide horizontal hydraulic conductivity value for the Upper Glacial 

aquifer is about 270 ft/d (Smolensky et al., 1989), but aquifer tests conducted at BNL by 

Warren et al. (1968) indicated the value at the site to be one-third lower—about 175 ft/d 

(based on an aquifer thickness of 145 ft), and the specific yield (effective porosity) to be 

0.24. Subsequent tests at BNL have measured similar hydraulic conductivities 

(Holzmacher et al., 1985). Total porosity of the Upper Glacial aquifer is estimated to be 

0.33 (Warren et al., 1968). A summary of aquifer properties obtained from onsite 

pumping tests is presented in Table 3-2 (Scorca et al., 1999). 

Data from aquifer tests and infiltration tests conducted at BNL (Warren et al., 1968) 

indicate that the anisotropy (ratio of vertical to horizontal hydraulic conductivity) of the 

Upper Glacial aquifer is between 1:4 and 1:18. The average value for the Upper Glacial 

aquifer throughout Long Island has been estimated to be 1:10 (Smolensky et al., 1989). 

The hydraulic properties of the basal Upton unit cannot be defined with certainty from 

the current well network, but the high clay and silt content of the Upton unit, especially in 

the northwestern part of the BNL site, indicate that these deposits are probably less 

permeable than the overlying glacial outwash sand and gravel. 

The Gardiners Clay, where present, confines water and affects ground-water flow, but its 

limited extent indicates that the effects are only local. Studies by Warren et al. (1968) 

indicate that the hydraulic conductivity of the Gardiners Clay is about 0.040 ft/d, but the 

hydraulic conductivity of sandy zones within the unit is higher. 
3-6 

Table 3-1. Generalized description of geologic and hydrogeologic units underlying Brookhaven 

National Laboratory and vicinity, Suffolk County, N.Y. (Scorca et al., 1999) 

 

Series Geologic Unit Hydrogeologic 

Unit 

Description and Water-bearing Characteristics 

Upper Pleistocene deposits Upper glacial 

aquifer 

Mainly brown and gray sand and gravel deposits of moderately high 

horizontal hydraulic conductivity (270 ft/d average for Long Island; about 

180 ft/d measured at Brookhaven National Laboratory); may also include 

deposits of clayey till and lacustrine clay of low hydraulic conductivity. A 

major aquifer. 

Upton unit Upper glacial 

aquifer 

Mainly greenish, with shades of yellow-green, greenish-gray, olivebrown, and gray, poorly to well sorted sand, with some silt and clay. 

Upper surface in some borings is marked by a clay or silty layer, 

generally less than 10 ft thick, that produces a noticeable response on a 

gamma-ray log. Horizontal hydraulic conductivity is estimated to be 

similar to or slightly less than that of the shallow part of the upper glacial 

aquifer. 

Gardiners Clay Gardiners Clay Green and gray clay, silt, clayey and silty sand, and some interbedded 

clayey and silty gravel. Unit has low vertical hydraulic conductivity 

(0.001 ft/d) and tends to confine water in underlying aquifer. 

PLIESTOCENE 

Sand below Gardiners 

Clay 

Upper glacial 

aquifer 

Mainly light brown, olive-brown, and grayish-brown, poorly to well 

sorted sand. Hydrologically, unit could also be considered part of 

Magothy aquifer because of confinement by Gardiners Clay. 

Monmouth Group Monmouth 

greensand 

Interbedded marine deposits of green, dark-greenish gray, greenishblack, dark gray, and black clay, silt, and sand, containing much 

glauconite. Unit has low hydraulic conductivity (0.001 ft/d) and tends to 

confine water in underlying aquifer. 

Matawan Group and 

Magothy Formation, 

undifferentiated 

Magothy 

aquifer 

Gray, white, and brownish-gray, poorly to well sorted, fine to coarse sand 

of moderate horizontal hydraulic conductivity (50 ft/d). Contains much 

interstitial clay and silt, and lenses of clay of low hydraulic conductivity. 

Generally contains sand and gravel beds of low to high conductivity in 

basal 100 to 200 ft. A major aquifer. 

grayish-brown clay Dark grayish-brown to yellow-brown, solid to silty clay, in some layers 

laminated with beds of very fine sand up to 1 in. thick. Unit is 

encountered in upper part of Magothy Formation. Has low hydraulic 

conductivity and tends to confine water. 

Unnamed clay member of 

the Raritan Formation 

Raritan 

confining unit 

Gray, black, and multicolored clay and some silt and fine sand. Unit has 

low vertical hydraulic conductivity (0.001 ft/d) and confines water in 

underlying aquifer. 

CRETACEOUS 

Lloyd Sand Member of the 

Raritan Formation 

Lloyd aquifer White and gray fine-to-coarse sand and gravel of moderate horizontal 

hydraulic conductivity (40 ft/d) and some clayey beds of low hydraulic 

conductivity. 

PALEOZOIC 

AND 

PRECAMBRIAN Bedrock Undifferentiated 

crystalline 

bedrock 

Mainly metamorphic rocks of low hydraulic conductivity; considered to 

be the base of the ground-water flow system. 
3-7 

Table 3-2. Hydraulic conductivity of Upper Glacial aquifer at Brookhaven National Laboratory, 

Suffolk County, N.Y., as indicated by aquifer tests (Scorca et al., 1999) 

Source of data Hydraulic conductivity 

(in feet per day) 

Warren et al. (1968) 180 

Holzmacher et al.(1985) 180 

Camp Dresser and McKee (1995) 200 

Grosser (1997) 60-160 

Geraghty & Miller (1997) 150 

The Monmouth Group, which lies along the southern shore of Long Island, forms the 

hydrogeologic unit known as the Monmouth greensand. Monmouth greensand and the 

Gardiners Clay underlie the Upper Glacial aquifer and confine water in the Magothy 

aquifer. The Upper Glacial aquifer directly overlies the Magothy aquifer in areas where 

both of these units are absent. 

Deltaic sediments of the Matawan Group- Magothy Formation make up the Magothy 

aquifer. The hydraulic conductivity of this unit is estimated to average 50ft/d (Smolensky 

et al., 1989) but varies widely as a result of local differences in lithology, thickness, and 

lateral extent. This hydraulic variation can affect local ground-water flow patterns and 

contaminant transport. Warren et al. (1968) conducted an aquifer test in a coarse sand 

zone of the Magothy aquifer and obtained a hydraulic conductivity value of 57ft/d. 

Much of the Magothy aquifer consists of silty sand with clayey layers. The upper 

Magothy sediment at BNL is mostly a silty sand with clayey layers but includes layers of 

well-sorted sand as well as locally extensive clay layers, such as the grayish-brown clay 

unit. Although the grayish-brown clay unit has a sandy texture in some intervals, it is 

fairly solid in general and forms a major local confining unit (Scorca et al., 1999). 

Hydrologic Cycle 

The hydrologic cycle on Long Island was summarized by Scorca (1997) and discussed at 

length by Franke and McClymonds (1972), who evaluated the relations among major 

hydrologic factors, including precipitation, evapotranspiration, direct runoff, groundwater recharge, ground-water movement, and pumpage, to develop an island-wide water 

budget. The hydrologic cycle can be thought of as beginning with precipitation, which 

has averaged 48.29 in/yr at Upton station since 1949. Upon reaching the ground, 
3-8 

precipitation flows as direct runoff into streams, infiltrates into the highly permeable 

unsaturated zone, or evaporates. Part of the water that infiltrates the soil evaporates or is 

transpired by plants; the rest infiltrates downward to the water table (Scorca et al., 1999). 

Ground-Water Recharge and Discharge 

The water table recharge rate varies from year to year as a function of precipitation. It 

also fluctuates seasonally because plants capture and transpire most of the water that 

enters the unsaturated zone during the growing season (May through October) (Figure 

3-4). Thus, in most years, virtually all recharge occurs during the non-growing season 

(November through April) (Warren et al., 1968). The water table rises in response to 

recharge and typically undergoes a net rise in years when precipitation is notably higher 

than in the preceding year. This rise, in turn, results in increased ground-water discharge 

to streams, bays, and the ocean. Under long-term conditions in undeveloped areas of 

Long Island, about 50 percent of precipitation is lost through evapotranspiration and 

direct runoff to streams. The other 50 percent infiltrates the soils and recharges the 

ground-water system (Aronson and Seaburn, 1974; Franke and McClymonds, 1972). 
3-9 

Figure 3-4. Precipitation and water-table altitude at Brookhaven National Laboratory, Suffolk 

County, N.Y.,1970-97. A. Annual precipitation at Upton. B. Typical water levels in wells (Scorca et 

al., 1999) 

Regional Ground-Water Flow 

The Long Island ground-water system consists of two major components—the regional 

(deep) flow system and the shallow flow system associated with streams. Ground water 

enters the regional flow system of Long Island in the area bordering the main groundwater divide, where it moves downward through the Upper Glacial aquifer into the 

underlying aquifers and eventually moves seaward. Water that enters the regional flow 

system south of the main divide flows southward, and water that infiltrates north of the 

divide flows northward. All precipitation that infiltrates upgradient of each stream’s 

shallow-flow system becomes part of the regional flow system, and precipitation that 

infiltrates within the ground-water contributing area of a stream becomes part of that 

stream’s shallow-flow system (Prince et al., 1988). 
3-10 

Ground-Water Divide 

The position of a ground-water divide depends on the water-table configuration. The 

main ground-water divide on Long Island is aligned generally east-west and lies about 

0.5 mi north of BNL’s northern boundary (Figure 3-5). Ground water north of the divide 

flows northward and ultimately discharges to Long Island Sound; ground water south of 

the divide flows southward and discharges to south-shore streams, the Peconic River, 

Great South Bay, Peconic Bay, and the Atlantic Ocean. Ground water near the divide has 

a large downward vertical-flow component and recharges the deep aquifers of the 

ground-water system. 

Figure 3-5. Water-table altitude in 300-mi2 study area surrounding Brookhaven National 

Laboratory, Suffolk County, N.Y., August 1995 (Scorca et al., 1999) 
3-11 

Local Ground-Water Flow Patterns near Brookhaven National Laboratory 

Ground-water flow and contaminant movement through the aquifer system below the 

BNL site are affected by several factors. First, pumping of ground water for supply at the 

site lowers ground-water levels and affects hydraulic gradients in the local ground-water 

system. Second, discharge from BNL’s sewage-treatment plant to the Peconic River can 

affect the position of the start of flow and the discharge of Peconic River. Recharge 

basins and pumping of onsite ground-water-remediation systems also affect ground-water 

levels locally. The stream channel of the Peconic River extends onto the site, but the start 

of flow can be either east or west of the site under extreme hydrologic conditions. The 

amount of flow in Peconic River and base-flow discharge to the stream affect the position 

of the secondary (southeastward trending) ground-water divide. The hydraulic properties 

of several hydrogeologic units, including the Upper Glacial aquifer, Magothy aquifer, 

grayish-brown clay, Gardiners Clay and localized near-surface clay units along the 

Peconic River drainage system also affect ground-water flow (see Table 3-1 for a 

description of these units). 

Water-table elevations at the site in March 1997 declined not only near supply wells, but 

near remediation (extraction) wells along the southern boundary of the site. At the same 

time, treated water from these systems was discharged to recharge basins and produced 

localized ground-water mounds near the basins (Scorca et al., 1999). 

Flow Gradients in Brookhaven National Laboratory Area 

The horizontal hydraulic gradient at BNL is typically 0.001 feet per foot (ft/ft), but in 

recharge areas and pumping areas, it can steepen to 0.0024 ft/ft or greater (Scorca et al., 

1999). The natural ground-water flow velocity in most parts of the site is estimated to be 

about 0.75 ft/d, but flow velocities in recharge areas can be as high as 1.45 ft/d, and those 

in areas near BNL supply wells have been estimated to have velocities as great as 28 ft/d 

(Scorca et al., 1999). 

Water-level measurements at paired water-table wells and deep wells screened in the 

Upper Glacial aquifer along the northern boundary of the site (near the regional groundwater divide) indicate significant deep-flow recharge areas, with downward vertical 

hydraulic gradients of as much as 0.007 ft/ft. Head differences at paired wells in the 

central and southern areas of the site become negligible, indicating that ground-water 

flow within the Upper Glacial aquifer is predominantly horizontal in these areas. Vertical 

gradients between the deep part of the Upper Glacial aquifer and the shallow part of the 

Magothy aquifer were about 0.018 ft/ft throughout the BNL site. 

The BNL site is located within a Suffolk County Department of Health Services -

designated deep-flow recharge area for the Magothy and Lloyd aquifers (Koppleman, 

1978). Comparison of water level measurements from Upper Glacial aquifer and 

Magothy aquifer wells indicate significant downward flow across the BNL site (BNL, 

1998, Paquette, 1998). 

Ground-water flow in the vicinity of the HFBR varies due to BNL pumping and recharge 

operations in the area. In general, ground-water flow is toward the south or southeast. 

Evaluation of ground-water flow and quality data indicate that the downgradient portion 

of the tritium plume (south of Brookhaven Avenue) has shifted to the east since 1997 in 
3-12 

response to changing flows to various recharge basins, and the reduced pumping of BNL 

supply wells (BNL, 2004). 

Ground water in the Upper Glacial aquifer beneath BNL generally exists under 

unconfined conditions (BNL, 2000). The Upper Glacial aquifer supplies both private and 

public water on Long island and is the exclusive source of drinking water and process 

water at BNL. The Laboratory currently operates six potable water supply wells that can 

be pumped at rates of 1,200 gallons per minute (gpm), and five process supply wells that 

can be pumped at rates between 50 and 1,200 gpm. During maximum water usage at 

BNL, up to 6 million gallons per day are pumped from the Upper Glacial aquifer. Most 

of this water returns to the aquifer by way of recharge basins or discharge of effluent to 

the Peconic River. 

A main east-west trending regional ground-water divide lies approximately 0.5 miles 

north of BNL (Figure 3-5). A second ground-water divide, which transects portions of 

the BNL site during periods of high water table position (i.e., during periods of inflow 

from the aquifer to the stream bed), defines the southern boundary of the area 

contributing ground water to the Peconic River watershed (Scorca et al., 1996, Scorca et 

al., 1997). Natural drainage systems influence shallow ground-water flow directions 

across the BNL site: flow runs eastward along the Peconic River, southeastward toward 

the Forge River, and southward toward the Carmans River. Additionally, pumping and 

recharge induces considerable stress on the aquifer system in the central area of the site. 

Due to variable supply well pumping schedules and rates, considerable variations in 

ground-water flow directions and velocities occur. Pumping at the Suffolk County Water 

Authority well field located on the west side of the William Floyd Parkway also 

influences ground-water flow directions in the southwest corner of the site (Paquette, 

1998). 

Aquifer pumping tests conducted at BNL indicate that the horizontal hydraulic 

conductivity of the Upper Glacial aquifer is approximately 1,300 gpd/ft2

 (or 175 ft/d) 

based upon an aquifer thickness of 145 feet and a specific yield (effective porosity) of 

0.24 (Warren et al., 1968; H2M/Roux Associates, 1985; CDM, 1995; Grosser, 1997). 

Total porosity value for the Upper Glacial aquifer is estimated to be 0.33 (Warren et al., 

1968). Data from aquifer pumping tests and infiltration tests conducted at BNL by the 

United States Geological Survey (USGS) indicate that the vertical to horizontal 

anisotropy within the Upper Glacial aquifer is between 1:4 to 1:18 (Warren et al., 1968). 

The average vertical to horizontal anisotropy within the Upper Glacial aquifer on Long 

Island has been estimated to be 1:10 (Smolensky et al., 1989). The hydraulic properties 

of the basal Unidentified Unit cannot be determined with any degree of certainty using 

the current well network. Since the Unidentified Unit contains significant clay and silt, it 

is expected that these deposits are less permeable than the overlying glacial outwash and 

morainal sand and gravel (Paquette, 1998). 

3.2.5 Tritium Plume Ground-Water Monitoring Data 

Ground-water monitoring has been ongoing at BNL since the beginning of operation of 

the facility. The current HFBR monitoring well network consists of 159 wells, sampled 

quarterly (BNL, 2004). In 1996, a tritium leak was discovered from the spent storage 

canal of the High Flux Beam Reactor (HFBR) Facility. Initial concentrations of tritium 
3-13 

in proximal down-gradient monitoring wells were in the range of 600,000 picocuries per 

liter (pCi/L) (maximum contaminant level [MCL] for drinking water is 20,000 pCi/L). 

After determining the tritium source was from the fuel canal associated with the HFBR, 

two 125 meter-long horizontal wells were installed upgradient and downgradient of the 

canal and between 0.6 to 1.6 meters below the water table, respectively (Figure 3-6). 

Both wells were constructed with six separated screen zones running parallel to and 

within five meters of the canal footprint. The stated goal of the wells was to rapidly and 

absolutely confirm that the canal was the source of the tritium contamination by showing 

that the upgradient well was clean and the downgradient well was contaminated. 

Unfortunately, the lateral spread of moisture and tritium in the vadose zone resulted in 

tritium concentrations that were similar in the two wells. Also, the concentrations 

measured in the horizontal wells during their first sampling were <5,000 pCi/L, 

significantly lower than the 140 million pCi/L concentration of the canal water and 

approximately 600,000 pCi/L concentrations detected in nearby downgradient monitoring 

wells. At the time, the project was viewed by some as a failure because it did not provide 

rapid and absolute confirmation. In fact, the project resulted in the successful and highquality installation of two horizontal wells that would have provided useful confirmatory 

information when sampled over a period of several years. Importantly, vadose zone 

processes influenced the data in a manner consistent with theory (Looney and Paquette, 

2000). 

The vadose zone at the BNL is relatively thin (approximately 15 m). The flow path of 

water and tritium in the vadose zone immediately below the HFBR reactor building is 

shown schematically in Figure 3-6. 

Figure 3-6. Schematic of plume configuration below the HFBR (Looney and Paquette, 2000). Used 

by permission of Battelle Press 
3-14 

In this situation, the vadose zone is dry because it is capped by the large building. The 

small leak from the fuel storage canal spreads out laterally and makes its way slowly to 

the water table. The lateral spread in the vadose zone is enhanced as the water tends to 

accumulate in and move through fine grained zones (silt and sand) and around coarse 

grained (gravel) zones (that is, water does not fill the holes in the sponge under these 

conditions). These vadose zone behaviors caused problems in interpreting data from two 

horizontal wells (discussed in the following section) that were installed in the water table 

to confirm the source of contamination 

The overall geometry of the contaminant plume beneath the reactor is a direct result of 

the slow leak rate and the lateral spread in the vadose zone. As the contaminated vadose 

zone moisture slowly enters the relatively fast moving aquifer (~0.3 meters per day 

[m/d]), the plume forms a thin plume at the top of the water table. The thickness of this 

contaminated layer can be estimated from a simple analysis of the relative flow rates and 

areas (Figure 3-7) 

Figure 3-7. Simplified calculation of plume thickness immediately downgradient of a vadose zone 

source (Looney and Paquette, 2000). Used by permission of Battelle Press.
3-15 

Based on leak rate data, measured lateral migration in the vadose zone, and typical 

hydrogeological values for this site, the tritium plume immediately beneath the reactor is 

expected to be very thin (<0.2 m). Even if this layer is smeared by seasonal water level 

fluctuations and other complexities, a simple evaluation of vadose zone delivery versus 

ground-water flow provides a clear understanding of why the initial sampling of the 

horizontal wells yielded low concentrations. Despite the wells being installed within a 

few feet of the water table, each of these wells were collecting water beneath the main 

body of the plume throughout most of the year. Thus, data from these wells were not 

providing an accurate picture of the plume location. Only when the wells were sampled 

during a seasonal drop in the ground water level was the plume location -- beneath HFBR 

primarily within a thin discrete zone at the water table surface – confirmed. Tritium 

concentrations of >650,000 pCi/L were detected in the upgradient well when the ground 

water level was within 0.3 meters of the well’s screened zone. However, during the same 

period, low tritium concentrations continued to be low in the downgradient horizontal 

well (<2,000 pCi/L) because the sample was taken approximately 1 meter below the 

water table. Because water levels have remained greater than 0.6 meters above the 

downgradient well since its installation, the originally expected high levels of tritium 

have not been observed (Looney and Paquette 2000). By 1998, the highest 

concentrations of tritium in ground water downgradient of the HFBR exceeded 5,000,000 

pCi/L. 

When the plume exits the footprint of the HFBR, infiltration places clean water above the 

plume. Vertical migration of the plume accelerates, and the plume is expected to exhibit a 

classic downward trajectory ( 

Figure 3-8). Once again, actual monitoring data proved to be of high quality, and the 

large-scale measured Brookhaven plume behavior matches the expected pattern. This 

highly discrete vertical plume behavior resulted in additional complexity in the data 

interpretation from monitoring wells—highly variable measurements for samples 

collected at different times. Figure 3-6 documents the principal source of this variability 

for an example water table well located immediately down gradient of the source 

(Looney and Paquette, 2000). 
3-16 

Figure 3-8. Cross section of tritium plume emanating from the HFBR (Looney and 

Paquette, 2000). Used by permission of Battelle Press. 

Based on simple geometry for the case of a thin plume (<0.3 m thick), the tritium 

measurement in a water table well is simply the plume concentration adjusted by the ratio 

of the plume thickness to the wetted screen thickness ( 

Figure 3-8). As site operations and seasonal events impact ground-water levels, tritium 

levels in vertical monitoring wells will vary widely. While most pronounced for water 

table wells, the issue of plume/well geometry impacting concentration data is general and 

should be evaluated for all sites (Looney and Paquette, 2000). 

As shown in Figure 3-9, ground-water flow below BNL is to the south-southeast and 

swings to the south-southwest upon exiting the site. However, the shape of the tritium 

plume bulges from the westin 1998 (Figure 3-10). This is not in agreement with the 

regional flow data in the water table and is likely influenced by remediation pumping on 

extraction wells EW-13 and EW-14, (Figure 3-9). After the plume passes EW-13 and -

14, it swings back to the southeast most likely due to a combination of conditions 

including: 

• the presence of other extraction wells in line and down gradient of the plume, 

including EW-15 (Figure 3-9), 

• the direction of regional flow, and 

• a circular topographic low located where the split in the plume occurs represents a 

relative increase in contribution to the water table that may result in localized 

mounding, and may act as a diversion to the movement of water. 

Contaminant capture zones below the HFBR are large because of the high permeability 

of the water table aquifer and are obvious when comparing the water table contour maps 

with the contaminant plume maps. 
3-17 

Figure 3-9. December 2005 water table map of BNL with extraction wells (BNL, 2005) 
3-18 

Figure 3-10. Location of tritium plume emanating from the High Flux Beam Reactor (DOE, 2000) 
3-19 

3.3 Ground-Water Modeling and Visualization 

Through examination of existing site characterization and monitoring data, it became 

clear that nearby process and remediation well pumping significantly influenced 

migration of the tritium plume. Recognizing this fact, we realized that it was necessary 

to include these influencers in our conceptual site model. Based on earlier research on 

vadose zone transport at BNL (largely done by Looney and Falta), we also recognized the 

importance in developing flow and transport models that accurately accounted for this 

transport. In this Section 3.3, we describe the CSM and flow and transport models we 

developed to evaluate contaminant migration. 

3.3.1 Plume visualization 

For the three-dimensional data presentation, ground-water analytical data, along with 

survey information for the temporary monitoring wells, were loaded into a three 

dimensional data presentation software database (Arcview with 3D Analyst). From this 

information, a three-dimensional model of the actual tritium plume was created that 

allows a 360 degree horizontal and vertical perspective of the model. In addition, levels 

can be placed in the model corresponding to various surfaces such as ground images, 

water table surfaces, and geologic layers. By evaluating these complex data in three 

dimensions, a more complete picture of the temporal distribution of contamination can be 

visualized. As demonstrated below, this conceptual model assisted understanding of the 

observed data from the existing monitoring wells and guided our analysis regarding how 

and where future contaminant monitoring or remediation should occur. 

Figure 3-11 and Figure 3-12 present two perspectives of temporary monitoring well data 

extracted from the BNL tritium database. The ability of 3D Analyst to present complex 

analytical data in an easily manipulated format makes the program ideal for presentations 

to anyone especially people who do not have a scientific or engineering background. 

Data used to prepare Figures 11 and 12 were current in April, 2006. 
3-20 

Figure 3-11. Oblique view looking northeast of tritium plume with concentrations emanating from 

the HFBR. 

Figure 3-12. Oblique view looking northwest of tritium plume with concentrations emanating from 

the HFBR. 
3-21 

3.3.2 Flow and transport modeling 

The second part of this exercise was to evaluate the effects of aquifer pumping on plume 

configuration by an active system that continuously pumps water from one or more 

monitor wells near the facility. Ground-water flow and transport simulation was 

performed utilizing a combination of techniques including excel spreadsheets, 

MODFLOW and GMS. Figure 3-13 and Figure 3-14 present the results of the groundwater modeling using GMS for visualization. The model assumed a homogeneous matrix 

with a hydraulic conductivity of 200 ft/day and a porosity of 0.3. Each square on the grid 

is 100 by 100 feet. 

Modeling predicts, after 20 years with no pumping or remediation, the contaminant 

plume should be moving south by southeast, following the slope of the water table. 

Figure 3-13 presents the slope of the observed water table with the modeled tritium 

plume in color and the actual tritium plume uncolored. The actual plume did not follow 

the slope of the water table surface, but was pulled to the west by site extraction wells. 

3.3.3 Active Monitoring 

As has been observed from historical monitoring data, the tritium plume is relatively 

narrow, making it difficult to sample the plume through passive ground-water 

monitoring. For a similar facility and situation, an active extraction well monitoring 

program increases the size of the capture zone and the likelihood of detection. 

After

20 years

Figure 3-13. Computer simulation of tritium plume emanating from the HFBR after twenty years, 

no pumping 
3-22 

Because an active extraction well creates a large capture zone both vertically and 

horizontally, there is a greater opportunity for early detection. In the case of the HFBR, 

the tritium plume was confined to the upper 0.3 m of the water table and as stated above, 

the horizontal wells place below the HFBR failed to detect the tritium plume until the 

water level dropped enough to allow the wells to capture water from the top of the water 

table. By placing an active pumping monitor well just down gradient of the facility, a 

larger cone of influence can be evaluated, resulting in earlier detection. 

The principal contaminants of concern at nuclear facilities are radionuclides, which can 

be detected at low concentrations, minimizing the concern of dilution due to pumping. 

Early detection of mobile contaminants through pumping could mitigate contamination, 

prevent offsite migration, minimize efforts associated with remediation of a larger, multicontaminant plume, as well as serve as a Performance Indicator to validate and revise the 

conceptual model. Figure 3-14 provides the results of the modeling program shown in 

Figure 3-13 utilizing the same parameters, only with the addition of an active pumping 

well adjacent to the HFBR, pumping at a continuous rate of 100 gallons per minute. In 

this scenario, the plume has been pulled to the west by the pumping. A passive 

monitoring well at this location would not have detected this tritium plume; however, the 

active well easily captured the plume. 

After

20 years

Figure 3-14. Computer simulation of tritium plume emanating from the HFBR after twenty years, 

pumping monitoring well. 
3-23 

3.3.4 Performance Indicators 

Ground-water monitoring does not only entail analyzing for constituents of concern, but 

also various Performance Indicators that could trigger monitoring and/or remedial 

actions. These indicators can be used to validate or refine the conceptual site model. 

Performance Indicators and features, events, or processes (FEPs) which influence HFBR 

plume flow and transport include, but are not limited to: 

tritium concentrations in the ground water – Tritium needs to be evaluated to not only 

determine if concentrations have exceeded monitoring limits (e.g., drinking water limits, 

etc..), but also to trigger low-flow pumping of extraction wells for removal and reinjection up gradient. 

ground-water level distributions – The tritium plume emanating from below the HFBR 

is very narrow and the direction of movement of the plume is susceptible to slight 

changes in water table orientation due to varying meteorological conditions or changes in 

infiltration related to surface changes. Thus, in this environment, it is essential to account 

for ground-water level distributions when modeling and monitoring performance. 

nearby remediation well pumping – Brookhaven is a rather small site in geographic 

extent. Any pumping on the site regardless of whether it is for remediation or process 

water can impact how plumes behave and interact. Ongoing remediation of other plumes 

in the vicinity may impact movement and capture rate of the HFBR tritium plume. 

Inception or termination of ground-water extraction for other plumes can significantly 

affect the orientation of the water table surface regionally. An adjacent pumping system 

could result in the migration of the HFBR tritium plume out of the path of current 

monitoring. 

process water extraction- Production wells that are used to extract water for industrial 

processes can alter the direction, speed and concentrations of plumes. Water levels in 

monitoring wells should be carefully evaluated to determine if the cycling of process 

wells have an influence on contaminant plumes. 

tritium as a tracer for other ground-water contamination – Because of its high 

mobility, tritium acts a tracer for the movement of future, less mobile contaminants. 

Because strontium-90 has been identified in the vicinity of the HFBR tritium plume, the 

tritium plume movement data can be applied to future strontium-90 monitoring and 

remediation efforts. Careful examination of older plumes (TCE plume) in the vicinity of 

the tritium plume can give insight to how the tritium plume and any subsequent plume 

might behave in the future. 

tritium as a tracer for early warning – Tritium is very mobile within the vadose zone 

and is usually detected on the leading edge of contaminant plumes making the presence 

in soil vapors an excellent candidate for early warning of potential releases. 

While the VOC plume mentioned in Figure 3-1 is not discussed in this Chapter, it may be 

worthwhile to note that flow and transport behavior of this plume may provide useful 

information about the potential pathway of the tritium plume. 
3-24 

3.4 Monitoring Strategy Application Conclusions 

This case study illustrates how 3-D modeling can be a powerful tool for evaluating the 

shape, progress, and future paths of contaminant plumes. Because examination of 

existing site characterization and monitoring data led us to believe that the flow path of 

the tritium plume emanating from HBFR facility was being influenced by nearby process 

water and remediation well pumping, we realized the importance of incorporating these 

nearby wells into our CSM. In addition, based on earlier work done by Looney and 

Paquette, we realized that it was necessary to develop flow and transport simulations that 

could accurately model the observed tritium transport through the vadose zone. 

The flow and transport simulations, which were developed using Excel, MODFLOW, 

and GMS, are effective tools for evaluating the effectiveness of various pumping 

alternatives, and thus, can aid in development of an efficient and cost effective 

monitoring and/or remediation program. 

An optimally designed and operated monitoring network will increase the likelihood of 

early detection of plume migration. These flow and transport simulations can not only 

help place monitoring wells, but they can also help establish optimal pump rates. In this 

case, for example actively pumping monitoring wells may help create a larger cone of 

influence, resulting in less chance of a narrow plume being missed. By increasing the 

cone of influence, less monitoring wells may be required. By detecting these plumes 

earlier, remediation efforts can be put in place sooner, minimizing the chance for the 

plume to spread offsite or to other aquifers. 

Detailed contour maps of changing water table surfaces may also be helpful to evaluate 

the effects of seasonal changes to the water table as well as the effects of 

extraction/injection activities at remediation start up, during operation, or after 

termination of activities. The narrow nature of these plumes makes understanding 

changes vital. 

3.5 Brookhaven References 

Aronson, D.A., and G.E Seaburn. “Appraisal of the operating efficiency of recharge 

basins on Long Island, N.Y., in 1969.” U.S. Geological Survey Water- Supply 

Paper 2001-D, 22 p. 1974. 

Brookhaven National Labortary (BNL). “1997 Environmental Restoration Division 

Sitewide.” Groundwater Monitoring Report. June 1998. 

BNL. Source Water Assessment for Drinking Water Supply Wells. Brookhaven National 

Laboratory, December 2000. 

BNL. “2003 BNL Groundwater Status Report.” Environmental and Waste Management 

Services Division/Environmental Restoration. June 2004. 

BNL. 2005 Site Environmental Report, Brookhaven National Laboratory, p. 7-5.2005. 
3-25 

CDM Federal Programs Corporation. “Technical Memorandum, Pre-Design Aquifer 

Test, October 10-20, 1995.” Brookhaven National Laboratory. December 1995. 

Department of Energy (DOE). Brookhaven National Laboratory, EPA Region 2, 

Operable Unit III, Record of Decision, Environmental Restoration Division, April 

14, 2000. 

DOE. Brookhaven National Laboratory, EPA Region 2, NPL Listing History, 

www.epa.gov/region02/superfund/npl/0202841c.pdf, August 17, 2006. 

Franke, O.L., and N.E. McClymonds. “Summary of the Hydrologic Situation on Long 

Island, New York, as a Guide to Water-Management Alternatives.” U.S. Geological 

Survey Professional Paper 627-F, 59 p. 1972. 

Grosser, P.W. (Consulting Engineer and Hydrogeologist, P.C.). Operable Unit III Pump 

Test Report.1997. 

Holzmacher, McLendon and Murrel, P.C. (H2M), and Roux Associates, Inc. Waste 

Management Area, Aquifer Evaluation and program Design for Restoration. 

Volumes I and II. 1985. 

Koppelman, L.E. (Ed.). The Long Island Comprehensive Water Treatment Management 

Plan (Long Island 208 Study). Nassau-Suffolk Regional Planning Board. 

Hauppague, New York. Volumes I and II. July 1978. 

Looney, B.B., and D.E. Paquette. Tritium Source Characterization at the High Flux 

Beam Reactor Brookhaven National Laboratory. Compiled in Vadose Zone Science 

and Technology Solutions. Vol. 1, p. 50-59.2000. 

Paquette, D.E. Brookhaven National Laboratory AGS Booster Applications Facility, 

Potential Impacts to Groundwater Quality. September 1998. 

Prince, K.R., O.L Franke, and T.E. Reilly. “Quantitative Assessment of the Shallow 

Ground-Water Flow System Associated with Connetquot Brook, Long Island, New 

York:” U.S. Geological Survey Water- Supply Paper 2309. 28 p. 1988. 

Quadrel, M., and R. Lundgren. Managing an Effective Vadose Zone Project. Compiled 

in Vadose Zone Science and Technology Solutions. Vol. 1, p. 61-124.2000. 

Scorca, M.P. “Urbanization and Recharge in the Vicinity of East Meadow Brook, Nassau 

County, New York, Part 1—Streamflow and Water-Table Altitude, 1939-90.” U.S. 

Geological Survey Water-Resources Investigations Report 96-4187, 39 p. 1997. 

Scorca, M.P., W.R Dorsch, and D.E Paquette. “Water-Table Altitude Near the 

Brookhaven National Laboratory, Suffolk County, New York, in March 1995.” 

U.S. Geological Survey Fact Sheet FS-128-96. December 1996. 
3-26 

Scorca, M.P., W.R Dorsch, and D.E Paquette. “Water-Table Altitude Near the 

Brookhaven National Laboratory, Suffolk County, New York, in August 1995.” 

U.S. Geological Survey Fact Sheet FS-233-96. April 1997. 

Scorca, M.P., W.R. Dorsch, and D.E Paquette. “Stratigraphy and Hydrologic Conditions 

near the Brookhaven National Laboratory and Vicinity, Suffolk County, New York, 

1994-1997.” U.S. Geological Survey Water Resource Investigations Report 99-

4086. 1999. 

Smolensky, D.A., H.T Buxton, and P.K Shernoff. “Hydrogeologic Framework of Long 

Island, New York.” U.S. Geological Survey, Hydrogeologic Investigations Atlas 

709, 3 Sheets. 1989. 

Warren, M.A., W. deLaguna, and N.J Lusczynski. “Hydrogeology of Brookhaven 

National Laboratory and Vicinity, Suffolk County, New York.” U.S. Geological 

Survey Bulletin 1156-C, 127 p. 1968. 

Woodward-Clyde Consultants. Potable Well Stud., Brookhaven National Laboratory, 

Upton, Long Island, New York. 10 p. 1993. 
4-1 

4 Amargosa Desert Research Site 

4.1 Introduction 

The Amargosa Desert Research Site (ADRS), located in Nevada’s Mojave Desert, was 

selected to test the applicability of the Advanced Environmental Solutions, LLC (AES) 

Strategy to an arid environment. This exercise is for demonstration only. This report is 

based on readily available information and does not constitute a comprehensive 

evaluation of all data for the site. Data used in this exercise were provided courtesy of 

the United States Geological Survey (USGS). 

The Amargosa Desert Research Site was previously a commercially-operated low-level 

waste-burial facility on the Mojave Desert, about 40 km east of Death Valley, near 

Beatty, Nevada. Beginning in 1962, low-level waste was disposed in unlined trenches. 

By 1970, hazardous waste was also placed in unlined trenches. Starting in 1988, the 

hazardous material was placed in lined trenches. Low-level disposal was ceased in 1992. 

In 1976, the USGS began studies of water movement at the Beatty Low-Level Waste 

Disposal Facility. In 1997, after unexpectedly high levels of tritium were discovered in 

shallow soil gas samples, the site was included in the USGS’s Toxic Substances 

Hydrology Program and became known as the Amargosa Desert Research Site. 

The primary issue of concern at the ADRS is the migration of radionuclides and VOCs 

from the waste buried in the facility trenches. Tritium, when present in the ground water 

or the vadose zone, is an excellent indicator for the movement of contaminants. 

Evaluation of all available data for the ADRS has resulted in several questions, the most 

significant of which is: Why is tritium present across the vadose zone and in the ground 

water below the ADRS? Research has indicated that overall soil moisture in the vadose 

zone adjacent to the ADRS exhibits an upward movement (Andraski et al., 2005). 

However, the presence of elevated tritium across the vadose zone, to a depth of over 100 

meters below ground surface (bgs), would indicate that there is a mechanism for the 

downward migration of contamination. 

Soil vapor modeling by Striegl et al., 1996 failed to produce a mechanism for the vertical 

component of movement of tritium within the vadose zone below the ADRS. Striegl et 

al., 1996 also proposed that the only mechanism for the vertical migration of tritium was 

in liquid form along complex hydrogeologic layers, but were unable to find specific 

geologic data to support this hypothesis. 

Because of the necessity for a fast pathway for the downward movement of soil gases 

containing tritium and after a comprehensive review of all available data for the site, an 

alternate conceptual model for movement of tritium through the vadose zone and into the 

underlying water table below the ADRS is proposed in the following sections. 

4.2 Compilation of Available Data 

This section provides a summary of the readily available data compiled to prepare this 

evaluation. The majority of the data used in this evaluation has been provided by or is 

available on line from the USGS. 
4-2 

4.2.1 Geologic Setting 

The ADRS is located in the Basin and Range Province of southern Nevada (Figure 4-1). 

This area of the Mojave Desert southwestern United States is considered one of the driest 

in the United States (Andraski et al., 2005). 

The Basin and Range Province of Nevada is characterized by a series of north-southtrending extensional sedimentary basins represented by patchwork mountain ranges or 

“horsts”, commonly 10 miles wide and rarely longer than 80 miles long, bounded by 

faults and adjacent downthrown valleys or “grabens”. The bounding faults have been 

active during the last 20 million years and represent an extensional geologic regime. The 

normal bounding fault planes usually dip approximately 60 degrees and extend deep into 

the crust, creating vertical displacement of as much as 10,000 feet. Figure 4-2 presents a 

generalized cross section of a horst and graben sequence (CG 1992). 

Figure 4-1. Location of ADRS (Stonestrom et al., 2003) 
4-3 

Figure 4-2. Cross section of a typical horst and graben sequence (CG, 1992) 

Weathering and erosion began soon after formation of the horsts. The movement of the 

sediments into the adjacent basins created alluvial fans on top of basin sediments. Figure 

4-3 provides an oblique view of a typical alluvial fan. These fans form when upland 

streams with steep gradients leave rugged terrain and enter a valley. Alluvial fans 

contain sequences of poorly sorted material. In addition, they contain series of active and 

abandoned interlacing channels. 

The interlacing of these channels results in complex patterns of alternating high and low 

permeability, which significantly affects ground-water movement. However, because the 

fans were deposited with a generally radial pattern, the permeability of the sediments 

should also generally follow the same trends. 

Figure 4-3. Oblique view of a typical alluvial fan in Death Valley 
4-4 

4.2.2 Regional Geologic Information 

The Amargosa Desert Research Site is located in a 13 km wide northwest-trending 

graben of the Basin and Range Province of southern Nevada (Figure 4-4). The regional 

geology underlying the ADRS appears to consist of shallow river gravels overlying 

unconsolidated alluvial fan, fluvial, and marsh deposits, and ultimately Paleozoic bedrock 

(Fischer, 1992). Since the ADRS is located adjacent to the northeast flank of the graben, 

the promulgation of the alluvial fan is from the northeast to the southwest across the site. 

The graben is bounded by mountain ranges composed of lower Paleozoic carbonate and 

clastic sediments, metasediments, and volcanics. The valley floor below the ADRS is 

presumably composed of similar material. 

In addition to the alluvial fan deposition at the ADRS, the Amargosa River has 

subsequently overprinted a floodplain of coarse river gravels near ground surface, 

covered by a thin (1 m thick) layer of finer grained sediments. 

Figure 4-4. Location of ADRS and soil gas sampling boreholes UZB-2 and UZB-3 (Stonestrom et al., 

no date) 

4.2.3 Site-specific Geologic and Analytical Data 

Available data sources for this analysis included: 

• Geophysical borehole log data (neutron-moisture, natural gamma, and gammagamma) 

• Monitoring well data from existing wells 

• Schlumberger soundings 

• Soil gas data 

• Thermocouple psychrometer / water potential data 

• Soil moisture data 

• A summary of each of these data sets, and relevant conclusions is below: 
4-5 

Geophysical borehole log data analysis (neutron-moisture, natural gamma, and gammagamma): 

While core logs are not available for these wells, Geophysical borehole logging suggests 

the presence of isolated clay lenses (Figure 4-5) (Fischer, 1992). For example, thin clay 

lenses were detected at 10, 20, and 25 m bgs in Well 303, but were not seen in the other 

wells. Also, a clay lens was observed in the log of Well 302 at a depth of 37 m, but was 

not observed in the other wells. Low moisture content at various intervals may indicate 

coarse, more permeable gravel; however, some of these low moisture intervals also have 

elevated gamma readings. 

Figure 4-5. Geologic distribution of clay lenses and marsh deposits in ADRS Wells 301, 302, and 303 

(Fischer, 1992) 

The most consistent subsurface layer appears to be a 20 m thick clay marsh deposit at a 

depth of 70 to 90 m bgs and is present in all three boreholes (Fischer, 1992). Based on 

the top of the clay horizon, Fisher determines the unit dips to the south-southeast at a rate 

of approximately 0.07 meters per meter (m/m). 
4-6 

Figure 4-6 presents contours of the water table surface which show a south-southwest dip 

in the water table toward the southwestern portion of the facility. Depth to bedrock 

below the ADRS is approximately 170 m and depth to ground water is approximately 100 

meters bgs. This Figure also shows the location of 14 monitoring wells within the ADRS 

burial site and several others in the surrounding vicinity (shown as circles in the Figure); 

however, data for these wells were unavailable. 

Figure 4-6. ADRS water table contours (measured in meters MSL) and well locations 

(Walvoord et al., 2005) 

These tight contours 

represent a sharp drop in 

the water table surface 
4-7 

Monitoring well data analysis 

Tritium is present in the water table over 100 meters below the ADRS, albeit in 

concentrations well below drinking water standards. Figure 4-7 provides a map of tritium 

concentrations in water table monitoring wells (monitoring well data is summarized in 

Appendix 4-A). The elevated tritium concentrations in ground water at location MR-3 in 

relation to the other facility monitoring wells brings into question the source of this 

tritium and the potential need for a revised CSM of contaminant movement in the vadose 

zone. 

Figure 4-7. Map of tritium concentrations in ground water below ADRS (Data from Prudic, 1997) 

Based on the regional geologic setting of the ADRS in a graben, with the nearest horst 

fault boundary to the northeast, the alluvial fan pattern for the geology below the site 

should dip to the west-southwest with some degree of radial dispersion present. Vertical 

variability in the fine to medium grain portion of the layering creates a significant 

anisotropic effect for movement of constituents within the vadose zone that should be 

accounted for in a monitoring program. In addition, the coarse gravel layer present at 

approximately 1.5 m bgs appears to act as a conduit for the lateral transport of 

contaminants. 

527200 527300 527400 527500 527600 527700 527800 527900 528000 528100 528200

4068600

4068700

4068800

4068900

4069000

4069100

4069200

4069300

4069400

527200 527300 527400 527500 527600 527700 527800 527900 528000 528100 528200

4068600

4068700

4068800

4068900

4069000

4069100

4069200

4069300

4069400

TRITIUM CONCENTRATIONS IN GROUND WATER FROM AVAILABLE MONITORING WELLS

ADRS

Tritium in pCi/L

MR-3

UZB-2

W001

MW311

MW600 MW313

Site Well

MW604

MW315

MW316

0.16 1.28

0.64 1.28

2.24

0.16

0.16 12.16 1.92

MW314

2.88

0

1

2

3

4

5

6

7

8

9

10

11

12
4-8 

Schlumberger sounding data analysis 

A resistivity survey of Schlumberger soundings conducted in 2002 (Bisdorf, 2002) over 

the ADRS area indicates the presence of a significant northwest to southeast striking 

basin fault approximately 500 feet northeast of the site. The sounding results suggest that 

the fault line dips steeply to the southwest beneath the subsurface. This fault orientation 

is most likely related to the regional horst and graben faulting (Figure 4-8 depicts 

numbered Schlumberger sounding survey locations with faults; Figure 4-9 shows the 

suggested location and fault orientations). 

Figure 4-8. Map showing numbered survey locations of Schlumberger soundings (modified from 

Bisdorf, 2002) 

The trace of US Highway 95 on Figure 4-8 appears to follow the toe of the alluvial fan as 

it emerges from below the alluvial river gravel. The trace of the basin fault, as defined by 

the results of the Schlumberger Soundings, also roughly parallels the trace of US 

Highway 95. The thin blue lines on the map represent intermittent stream drainages. The 

trace of the cross section presented in Figure 4-9 runs between sounding locations 110 

and 116. An additional fault was later identified during the application of this Strategy 

Location of 

the cross 

section 

depicted in 

Figure 4-9. 

Approximate 

trace of main 

fault shown on 

Figure 4-9. 

Approximate 

trace of 

southern 

structural 

offset. 
4-9 

and is referenced in this report as the “southern structural offset”. This offset was 

identified through the application of three-dimensional visualization of the resistivity data 

and is discussed further in Section 4.3.4 below. 

Figure 4-9 presents a cross section of the Bisdorf resistivity soundings indicating the 

location and orientation of the fault between sounding locations 103 and 107. As shown 

in Figure 4-9, Bisdorf infers the location of the basin fault by the presence of the steep 

resistivity gradient between sounding locations 103 and 107. 

Figure 4-9. Cross section of interpreted resistivity and basin fault (Bisdorf, 2002). (Triangles along 

the top axis correspond to sounding locations as mapped in Figure 4-8. Subvertical solid black line 

represents basin fault as defined by Bisdorf 2002.) 
4-10 

Figure 4-10 is a contour map of the resistivity survey at approximately 97 m bgs and 

shows the displacement of sediments down on the southwest side of the northwesttrending structure. 

Figure 4-10. Map showing contours of interpreted resistivity at a depth of 97 m overlying 

topographic contours (Bisdorf, 2002) 

Surficial soil gas data analysis 

Surficial soil gas data and terrestrial sampling seem to indicate that, at least in the near 

surface, contaminant migration is along gravel layers to the south and west from the 

burial trenches, following topography and away from this fault. 

Direct current electrical resistivity (DC-resistivity) imaging 

A vertical cross section (Figure 4-11) made by Stonestrom using direct current electrical 

resistivity (DC-resistivity) imaging near UZB-2 and UZB-3 (vadose zone soil gas 

sampling wells) shows intermittent gravel layers that thicken to the southwest toward the 

center of the basin, providing preferential pathways for contaminant migration 

(Stonestrom et al., no date). 
4-11 

Figure 4-11. A vertical cross section made by direct current electrical resistivity (DC-resistivity) 

imaging near the ADRS (Stonestrom et al., no date) 

Moisture Data 

The vadose zone below the ADRS is between 85 m and 115 m thick. A monitoring shaft 

was installed in the vadose zone southwest of the waste facility to a depth of 13.7 m bgs. 

Within this shaft were installed a series of thermocouple psychrometers (TCPs) as shown 

in Figure 4-12. These TCPs were installed horizontally out of the shaft into the 

surrounding vadose zone sediments and were used for measuring water potentials. 

Figure 4-12. Monitoring shaft and instrument borehole showing locations of TCPs and respective 

geologic information (Fischer, 1992). Thermocouple psychrometers installed in the monitoring shaft 
4-12 

are designated with L (left), M (middle), and R (right), followed by a number from 1 to 11 that 

indicates level in shaft. Thermocouple psychrometers installed in the instrument borehole are 

designated OD1 through OD13. Depth of each thermocouple psychrometer, in meters below land 

surface, is given in parentheses. (Fischer, 1992). 

Moisture content of soils was estimated using a neutron probe. Figure 4-13 provides a 

relative comparison between the varying lithology at the monitoring shaft location and 

the variable moisture content of the different gravel horizons. 

In the gravel layers at 1.5 and 9 m bgs, moisture contents were less than 3%, below 1.5 m 

bgs, moisture content was in the 4 to 8% range. Temporally invariant water contents 

below 0.75-1 m bgs indicate that the textural discontinuity between the two uppermost 

soil layers (loamy sand over gravelly coarse sand) provides a natural capillary break that 

impedes downward percolation of moisture (Andraski, 1995). 

Hydraulic conductivities 

Hydraulic conductivities were estimated using air permeability tests. Saturated hydraulic 

conductivities of the sediments ranged from 1 to 48 centimeters per day (cm/day), which 

are not unreasonable for poorly sorted sediments with at least 10 percent fines and silt. 

For unsaturated sediments, hydraulic conductivities were estimated at between 3x10-4 to 

9x10-20 cm/day. Porosity ranges from 25 to 43 percent and bulk density ranges from 1.4 

to 1.8 g/cm-3 (Fischer, 1992). 

In the sediments directly below the gravel layer at 1.5 m bgs, a significant increase occurs 

in the chloride content from <5 milligrams per gram (mg/g) to 160 mg/g by 3 m and 

remains above 100 mg/g to 7 m, then falls off steadily until it returns to <5mg/g at 11 m 

bgs. These elevated chloride readings basically are bracketed in the zone between the 

two major gravel layers that occur at 1.5 and 9 m bgs. 
4-13 

Figure 4-13. Monitoring shaft geologic and geophysical information (Fisher, 1992) 

4.3 Application of the Strategy 

Although on a regional basis, movement within the vadose zone below the ADRS is 

upward, contamination is moving downward along preferential pathways and has already 

reached the water table over 109 meters below ground surface. Past modeling efforts 

have failed to provide a conceptual site model that reproduces the observed vadose zone 

and ground water contamination. To evaluate the potential for hydrogeologic fast 

pathways below the ADRS and to prepare a revised conceptual site model, a more 

thorough examination of the available geologic and geophysical data was performed. 

4.3.1 Chemical Constituents in Ground Water or Soil Gas 

Based on available data, tritium is by far the most pervasive and anomalous constituent in 

either ground water or soil gas. Tritium partitions well between water and gas phases and 

is usually the most mobile constituent detected at sites with radiological contamination. 

The path of the tritium plume can be used to infer the potential path of other constituents 

in either ground water or soil gas. 

4.3.2 Chemical Constituents in Other Fluids 

This is an arid environment, but many constituents can migrate without the use of water, 

such as: mercury, iodine, radon, argon, krypton, and other waste components such as 

organic liquids. It is critical to determine the nature of the material contained within the 

burial trenches to know what constituents need potential evaluation. Based on available 
4-14 

information, constituents contained in the waste at the ADRS include, but are not limited 

to various isotopes of radionuclides including tritium and various hazardous compounds 

including carbon-14; three chlorofluorocarbon (CFC) compounds, eight chlorinated 

solvent compounds, and toluene although data for constituents other than tritium were not 

available for this exercise. 

4.3.3 Chemical Constituents in Plants and Animals 

Plants have been used in geochemical exploration for many years. Andraski et al., (2005) 

have demonstrated that sampling of creosote bushes in the vicinity of the waste site 

confirms the presence of tritium in the shallow gravels (1.5 m bgs). Figure 4-14 shows 

the distribution of sampling points for the creosote bush sampling. The contours indicate 

the concentration of tritium in plant water in BqL-1. The tritium plume as defined by the 

creosote bush sampling shows two potential sources of contamination emanating from 

the waste facility, one on the west side and one on the south side. 

Figure 4-15 shows a comparison (in tritium units) of plant water tritium with soil water 

tritium that correlates extremely well. Based on these results, it becomes apparent that 

analysis of plant material in this type of environment can act as a performance indicator 

for tracking movement of contamination within the underlying formation. 

Figure 4-14. Plant sample locations and contours of plant-water tritium concentrations 

(Andraski et al., 2005) 
4-15 

Figure 4-15. A comparison of plant water tritium with soil water tritium (Stonestrom et al., no date) 

4.3.4 Geophysical Modeling and Evaluation 

After assembling and reviewing the available data for the ADRS, it became apparent that 

there was a previously undefined mechanism for the downward migration of tritium 

across the vadose zone to the water table. 

Based on the limited geologic data available for the ADRS, the following simplified 

geologic CSM for the ADRS was proposed (Figure 4-16). 

Alluvial Fan

Bare Mountain

Paleozoics

Basin

Fault

Amargosa

River

Channel Gravels

Amargosa Desert

Research Site

Water Table

ADRS Fault

2000

3000

2500

3500

4000

4500

Elevation in Feet

Above MSL

Figure 4-16. Simplified geologic cross section of the ADRS looking northwest 
4-16 

As there is limited geologic information available for the ADRS, the Strategy application 

process turned to available geophysical data. After evaluating the available geophysical 

information it appears that the most useful geophysical technique applied in relation to 

observed patterns of contaminant transport at the ADRS is direct-current electricalresistivity (DC-resistivity) imaging, a surface-based technique employing automated, 

inverse-Schlumberger-array soundings (Bisdorf, 2002). 

Bisdorf (2002) presents a significant database of Schlumberger resistivity soundings 

across the ADRS. Figure 4-8 and Figure 4-9 show the resistivity data from Bisdorf 2002 

in cross section and plan view, respectively. These two figures are the only two 

representations of the resistivity data provided in Bisdorf 2002; however, the appendix to 

Bisdorf 2002 presented all of the collected data. 

Based on the resistivity data provided in the appendix of Bisdorf (2002), AES prepared 

an electronic database of the sounding information (Appendix 4-A). Sounding locations 

were estimated from Figure 4-8 of Bisdorf (2002). Elevations of sounding points were 

extracted from regional topographic maps. AES loaded all data into a geologic modeling 

package (HydroGeo Analyst 2.0) and a three-dimensional (3-D) block model of the site 

was created by kriging the data. 

Three dimensional kriging of this resistivity data identified a subtle fault not previously 

recognized in the data (heretofore referenced as the “Southern Structural offset”). The 

Southern Structural offset cuts across the southwest corner of the ADRS. The Structure 

runs nearly east-west and dips steeply southwest beneath the ground with approximately 

30 meters of vertical offset. The Southern Structural offset coincides with the location of 

the southern tritium plume emanating from low-level waste trenches of the ADRS. 
4-17 

Figure 4-17. Three-dimensional resistivity block model of the ADRS looking northwest (Well UZB-2 

can be seen in the southwestern portion of the figure) (created with data from Bisdorf, 2002) 

Figure 4-17 presents the three-dimensional block model of the ADRS looking to the 

northwest. Well UZB-2 can be seen in the southwestern portion of the model. The upper 

1.5 meters of undisturbed soil at the ADRS consists of highly resistive material. The 

upper 20 meters are not shown in order to remove high resistivity soils including the 1.5 

meters near the surface. In addition, the block model has all lower resistivity values 

(values below 42 Ohm-m) removed for clarity. By comparing Figure 4-8 and Figure 4-9 

with the 3-D model provided in Figure 4-17, the increase in the level of geologic detail 

becomes apparent. 

The Southern Structural offset is located directly north of UZB-2. It cuts across the 

southwestern corner of the low-level trenches. To the northeast can be seen the major 

regional west-northwest-striking horst and graben structural offset originally defined in 

Bisdorf, 2002, represented by a sharp vertical gradient in the resistivity data. Localized 

lateral variations in gravel content within the alluvial fan are defined by the horizontal 

layering seen in the northern portion of the model. 

Figure 4-18 shows the location of the Southern Structural offset in relation to the ADRS 

and UZB-2 both at ground surface and projected to 100 meters bgs (the intersection with 

the water table). 

UZB-2 

Approx. LLRW 

disposal trench 

location 
4-18 

Figure 4-18. Location of the Southern Structural offset as defined by resistivity data in relation to 

the burial trenches (adapted from Stonestrom et al., no date) 

4.3.5 Hydrologic Data 

Water levels in the monitoring wells indicate that the water table surface is between 85 

and 115 m bgs and dips at approximately 0.06 m/m (Figure 4-6). The contours of the 

water table appear to contain aspects of two flow directions; 1) flow toward the southwest 

(corresponding with the dip of the alluvial fan), and 2) flow toward the southeast 

(corresponding with the regional dip of the paleo river channel). However, the apparent 

curve in the water table to the southeast may not be related to the shallow river channel, 

which does not extend down into the water table, but instead may be due to structural 

features, such as the proposed Southern Structural Offset. 

Figure 4-6 has an arrow showing a northwest kink in the water table contours that closely 

parallels the strike of the Southern Structural offset. If the regional dip of the water table 

527200 527300 527400 527500 527600 527700 527800 527900 528000 528100 528200

4068600

4068700

4068800

4068900

4069000

4069100

4069200

4069300

4069400

Southern Structural

offset at Ground Surface

Southern Structure

at 100 meters bgs

LOCATION OF SOUTHERN STRUCTURAL OFFSET AT THE ADRS

ADRS

UZB-2

Dip

UZB-3
4-19 

parallels the dip of the alluvial fan, then the water table should flow to the west-southwest 

with a sharp drop in water table expected northeast (upgradient) of the offset. 

Figure 4-19 provides a copy of the same map of the tritium concentrations in water table 

monitoring wells presented in Figure 4-7 with the location of the Southern Structural 

offset added. The offset is depicted by two lines, one at ground surface and one 100 

meters bgs at the intersection with the water table to show the tilt of the structure. As 

noted in the Strategy, initial evaluation of available data may ultimately point to a need to 

revise our CSM. In the case of the ADRS, the presence of a bulls-eye on the water table 

contour map in Figure 4-19 infers a potential fast path for tritium, as the water table 

surface is over 100 meters bgs. 

As shown in Figure 4-19, monitoring well MR-3 cuts the Southern Structural offset but 

based on the projection of the dip of the structure, the well is screened slightly up dip of 

the intersection of the Southern Structural offset with the water table. There is slightly 

elevated tritium in the ground water adjacent to MR-3 (4 to 6 times higher) in contrast to 

the other available ground-water monitoring wells associated with the ADRS. These 

elevated concentrations of tritium in the ground water presumably are due to vertical 

contaminant migration and confirm the fast path movement of soil gas downward from 

the ADRS to the water table along the Southern Structural offset. Furthermore, because 

the half-life of tritium is 12.5 years, and the ground water in the vicinity of the ADRS is 

described as thousands of years old (Prudic, 1996), this suggests a continued 

contaminant influx into the area. 
4-20 

Figure 4-19. Map of tritium concentrations in ground water below ADRS in relation to the Southern 

Structural Offset (data from Prudic, 1997) 

Geophysical logs of three monitoring wells (MW-301, 302, and 303), collected within the 

boundaries of the ADRS all indicate the presence of a significant continuous clay layer at 

approximately 70 meters bgs showing no vertical offset (Figure 4-5). However, all of 

these wells are northwest of the Southern Structural offset. The resistivity change across 

the offset indicates a change from a lower resistivity material (clays to silty clay gravels) 

to coarser, higher resistivity gravels. A significant drop in the water table across this 

feature is reflected in the water table values provided in Figure 4-6. Contouring in Figure 

4-6 suggests an offset in stratigraphy across the center of the ADRS may be causing the 

drop in water table surface; however, the lateral continuity of the clays in monitoring 

wells 301 through 303 suggest that if a geologic feature is causing the significant drop in 

head, the feature is not located directly below the ADRS, but is more likely in the vicinity 

of the proposed Southern Structural offset. In addition, as the water table surface occurs 

within the lower clay horizon below the ADRS, there could be a local aspect of perching 

occurring in the water table surface where the lower clay is present. Further evaluation of 

geologic well logs from monitoring wells installed beyond the boundary of the ADRS 

would provide necessary information to evaluate the presence of the Southern Structural 

offset, the lateral continuity of the clays, and the nature of the overall site geologic 

setting. 

527200 527300 527400 527500 527600 527700 527800 527900 528000 528100 528200

4068600

4068700

4068800

4068900

4069000

4069100

4069200

4069300

4069400

527200 527300 527400 527500 527600 527700 527800 527900 528000 528100 528200

4068600

4068700

4068800

4068900

4069000

4069100

4069200

4069300

4069400

Southern Structural

offset at Ground Surface

Southern Structural

offset at 100 meters bgs

TRITIUM CONCENTRATIONS IN GROUND WATER FROM AVAILABLE MONITORING WELLS

ADRS

Tritium in pCi/L

MR-3

UZB-2

W001

MW311

MW600 MW313

Site Well

MW604

MW315

MW316

0.16 1.28

0.64 1.28

2.24

0.16

0.16 12.16 1.92

MW314

2.88

Dip

0

1

2

3

4

5

6

7

8

9

10

11

12
4-21 

Based on regional topography, it appears that the structural offset predates the final 

deposition of the uppermost gravel layers at the ADRS, as it is not reflected at ground 

surface. Evaluation of any additional geologic or geophysical logs below or adjacent to 

the ADRS, collected during the installation of monitoring wells, would assist in the 

evaluation of the distribution of geologic units at depth and any potential offsets in these 

units. 

4.3.6 Vadose Zone Data 

In arid environments, assessment of water flux must be considered as a performance 

indicator. Water flux potentials in the vadose zone indicate persistent upward driving 

forces for water (both liquid and vapor) (Andraski et al., 2005). In addition geothermal 

gradient suggests an upward driving force (Andraski et al., 2005); however, this does not 

explain how tritium has reached the water table over 100 m bgs. In addition, chloride 

mass balance suggests that percolation of precipitation has been limited to the upper 10 m 

bgs during the last 16,000 to 33,000 years. However, the presence of tritium in the 

deeper vadose zone (to the water table at 108.8 meters bgs) and ground water would tend 

to indicate that some other mechanism exists for moving contaminants downward. One 

option is the movement of water downward along fault planes, such as the Southern 

Structural offset. 

Tritium in both the vadose zone and water table at many radioactively-contaminated sites 

has historically proven to be an excellent indicator of contaminant migration pathways 

because of its high mobility. Tritium concentrations in vadose zone sediments are 

highest in the vicinity of the waste unit and are highly concentrated within the gravel 

zone located at 1.5 m bgs. Figure 4-20 presents the results of a soil gas survey taken 

from the 1.5 m bgs interval over the shallow tritium plume in the southwest corner of the 

ADRS. 

Tritium concentrations are in excess of 64,000 pCi/L in the gravel at 1.5 m bgs and 

immediately fall to within the 600 to 1,900 pCi/L range by 6 m bgs, then steadily increase 

to 1,920 to 3,840 pCi/L by 30 m bgs. Below 30 m, the tritium falls back to below 640 

pCi/L (and generally below 16 pCi/L) to at least 100 m bgs. One exception, test hole 

UZB-2 (located on the downthrown side of the Southern Structural offset) maintains 

tritium concentrations down to 94 m bgs in excess of 5,648 pCi/L. Although the highest 

tritium contamination are confined to the upper 1.5 m bgs gravel layer, the presence of 

tritium down to the water table indicates that there is a mechanism for the downward 

migration of contaminants through the vadose zone. More characterization of the entire 

vadose zone is necessary to determine the mechanism for transport and the extent of the 

contaminant plume. The vertical movement of tritium downward appears to be related to 

the presence of the Southern Structural offset. 
4-22 

Figure 4-20. Plan view of tritium soil gas concentrations in the 1.5m below ground surface interval 

(data from Striegl et al., 1997) 

Tritium concentrations shown in Figure 4-21 for UZB-2 are highest in the 1.5 meter bgs 

sampling interval (49,632 pCi/L); however, concentrations of tritium from just below the 

1.5 meter interval (1,174 pCi/L) increase steadily down to the water table, with the 

maximum concentration occurring just above the water table surface at 108.8 meters bgs 

(5,648 pCi/L). This downward increasing trend in tritium appears to consist of two 

separate trends: a lower concentration tritium trend associated with finer 

grained/relatively higher soil moisture materials; and a higher concentration tritium trend 

associated with coarser grained/relatively lower moisture materials (Figure 4-21). 

Concentrations increase steadily downward as UZB-2 approaches the southwestern 

dipping Southern Structural offset. Tritium concentrations in all intervals sampled in 

UZB-2 have increased steadily at a rate of between 50 and 230 pCi/L per year, between 

the time the well was completed in 1993, and the latest available analytical data from 

1996. 
4-23 

Tritium Concentrations in Soil Gas at UZB-2

-120

-100

-80

-60

-40

-20

0

0 2,000 4,000 6,000 8,000 10,000

Tritium (pCi/L)

Depth Below Ground 

Surface (meters)

Conc entration Tritium 

at 1.5 m = 49,632 pCi/L Tritium in gravels and in 

layers of lower moisture

Figure 4-21. Soil vapor concentrations of tritium in UZB-2 

In addition, UZB-3, which at the surface is located on the downthrown side of the 

Southern Structural offset (Figure 4-18), crosses the structure at approximately 25 to 30 

meters below ground surface. The downward movement of contaminants, including 

tritium, and carbon-14, is presented in Figure 4-22 and Figure 4-23, respectively 

(Stonestrom et al., no date). Tritium concentrations in UZB-3 are from 2001. Note that 

tritium concentrations in UZB-3, below the high concentrations in the 1.5 m bgs interval, 

increase steadily downward to the point of intersection with the Southern Structural offset 

(around 30 meters bgs). 

As the well passes the structure, the concentrations drop back off dramatically to near 

detection limits. The presence of carbon-14, in addition to the tritium, indicates that 

other constituents are moving downward along the Southern Structural offset. Based on 

available data for UZB-3, CFCs, VOCs, and toluene are present in UZB-3, but quantities 

and depths are not readily available. Because of lack of readily available data, it is 

impossible to determine the nature and extent of any other contaminants that may have 

leached from the trenches into the vadose zone. 
4-24 

Figure 4-22. Tritium soil gas concentrations from UZB-3 (modified from Stonestrom et al., no date) 

Figure 4-23. Carbon dioxide and carbon-14 soil gas concentrations from UZB-2 and UZB-3 

(Stonestrom et al., no date) 

Tritium in UZB-3

-120

-100

-80

-60

-40

-20

0

0 10000 20000 30000 40000 50000 60000

Tritium (pCi/L)

Depth BGS

 (meters)

Tritium at 1.5 m 

exceeds 100,000 pCi/L 

Approximate location where 

Southern Structural offset 

crosses UZB-3
4-25 

4.3.7 Meteorological Data 

USGS Annual Open File Reports for the ADRS provide a significant database of 

meteorological data. Based on the results of data from the ADRS and other similar 

facilities in arid environments, it becomes apparent that changes in barometric pressure at 

ground surface are also reflected at depth. 

Figure 4-24 presents barometric pressure data for the southeast corner of the ADRS (The 

original source report only stated that the well was from the southeast corner of the 

ADRS, so the actual well used is unknown). This figure also shows a strong correlation 

of changes in surficial barometric pressure with changes at depth, down to 30 meters bgs. 

Below 30 meters, even at 89 meters bgs, minor responses to surficial barometric pressure 

changes are evident (Prudic, 1996). This data indicates that there is significant soil gas 

interaction between the surface and depth. The barometric pumping of the vadose zone 

could produce significant vertical migration of soil contaminants along preferential 

pathways. As it is unclear of the source well, a determination of the source of the data 

needs to be performed and additional barometric pressure data needs to be collected. 

Figure 4-24. Data from southeast corner of ADRS (Prudic, 1996) 
4-26 

4.3.8 Transport Modeling 

As noted in Striegl et al., 1996, the distribution of tritium cannot be explained simply by 

vapor transport, either by diffusive or advective mechanisms. Thus, liquid transport 

appears to have played a role in moving tritium to well UZB-2. Liquid transport may 

have been enhanced by precipitation and runoff into open trenches that resulted in the 

occasional accumulation of ponded water in the trenches and flow along preferential 

pathways in the underlying unsaturated zone (Striegl et al., 1996). As the conceptual 

model proposed by Striegl et al., 1996 failed to produce a mechanism for the vertical 

component of movement of tritium in soil gas within the vadose zone below the ADRS, 

an alternative conceptual model needed to be developed. 

Striegl et al., 1996 then proposed an alternative conceptual model for tritium transport 

stating that liquid tritiated water may have moved laterally at shallow depth from one or 

more of the trenches to some point near UZB-2 and then percolated downward, resulting 

in the tritium activity distribution shown in Figure 4-25. Such lateral flow could occur 

along complex, preferential pathways formed in the presence of large-scale 

hydrogeologic heterogeneities during periods when liquid waste was being released 

directly into open trenches, and/or when the trenches received runoff from large 

precipitation events (Striegl et al., 1996). 

Figure 4-25. Conceptual Model for the movement of tritium proposed by Striegl et al., 1996 
4-27 

Based on this hypothesis, Striegl et al., 1996 proposed that water could collect in an open 

trench due to liquid waste disposal and/or collection of runoff from precipitation events. 

This ponded water could percolate rapidly through the clean sands and gravels down to a 

discontinuous sloping clay lens, where it could mound and move horizontally as saturated 

flow. Once the mounded water reached the edge of the clay lens, it could spill into the 

sand and gravel, and presumably move as unsaturated flow until it reached the next lens. 

Based on the limited geologic and hydrogeologic data available, there are a significant 

number of parameters we can use to refine flow and transport simulations. We can define 

multiple hydrogeologic environments (river gravels, alluvial sediments, Paleozoic 

bedrock, etc.); make informed decisions on ground water and soil vapor flow; provide 

specific structural parameters for preferential vertical vadose zone flow pathways; apply 

variable horizontal flow variography based on geologic sediment type; and include 

various parameters for hydraulic conductivity and porosity. 

Based on the assumption that the Southern Structural offset acts as a preferential pathway 

for the migration of soil gas, a spreadsheet matrix model of the dispersion of tritium 

through the vadose zone was prepared by AES. Table 4-1 presents a summary of the 

results of the model. 

For simplicity, the model assumes that the Southern Structural offset is vertical and the 

calculated values for UZB-2 can be extracted from the matrix at the appropriate depth 

and distance from the fault. The model was prepared on a 1-foot by 1-foot grid. The first 

column of the model contains a formula assuming a dispersion constant for the Southern 

Structural offset. The subsequent columns utilize the value for the Southern Structural 

offset at the given depth and utilize the dispersion constant for the different geologic 

environments. The dispersion model utilizes a first order decay rate with the dispersion 

constant encompassing several parameters including the decay rate of the tritium, the 

permeability of the sediments, and the rate of movement of the soil gas through the 

sediments. 

Table 4-1. Summary of model for estimation of tritium movement in the vadose zone between the 

Southern Structural Offset and UZB-2 

 Distance from Fault (m) 

Depth 

(m) 

Fault 

(pCi/L) 20 40 60 80 100 120 140 160 180 200 

2 911775 675460 500393 370700 274621 203445 150715 111653 82714 61276 45395 

6 48932 34620 24494 17330 12261 8675 6138 4342 3072 2174 1538 

12 46863 35418 26768 20231 15290 11556 8734 6601 4989 3771 2850 

18 44881 31754 22466 15895 11246 7957 5630 3983 2818 1994 1411 

24 42984 32486 24553 18557 14025 10600 8011 6055 4576 3458 2614 

34 39998 28299 20022 14166 10022 7091 5017 3550 2511 1777 1257 

48 36163 27331 20656 15612 11799 8918 6740 5094 3850 2910 2199 

58 33650 23808 16844 11918 8432 5966 4221 2986 2113 1495 1058 

70 30865 21837 15450 10931 7734 5472 3871 2739 1938 1371 970 

80 28721 20320 14377 10172 7197 5092 3602 2549 1803 1276 903 

94 25967 18372 12998 9197 6507 4604 3257 2304 1630 1154 816 

106 23818 16851 11922 8435 5968 4222 2987 2114 1495 1058 749 

109 23309 17616 13314 10063 7605 5748 4344 3283 2481 1875 1417 

Note: Tritium concentrations in pCi/L 
4-28 

Tritium Concentrations for UZB-2 

(Actual vs Modeled)

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

0.0 50.0 100.0

Depth BGS (meters)

Concentration

Actual

Concentrations

Calculated

Concentrations

Figure 4-26. Comparison of actual data to modeled tritium concentrations in UZB-2 in pCi/L (UZB2 tritium data from Striegl et al., 1997) 

Separate dispersion values were assigned to the surficial gravel at 1.5 meters bgs, the 

coarser gravels, and the finer materials (Table 4-2). Table 4-3 summarizes the results of 

the model as compared to actual tritium concentrations in UZB-2. Figure 4-26 provides a 

comparison of the results of the model to the actual tritium concentrations in UZB-2 from 

Striegl et al. (1997), illustrating tightly correlated results between expected and observed 

tritium concentration levels. Figure 4-27 is a hypothetical cross section prepared using 

Surfer to contour the modeling result values summarized in Table 4-1 along with the 

tritium values collected from UZB-2. The gravel horizons presented in Figure 4-27 are 

interpreted from soil moisture data from Prudic (1994) and from relative tritium 

concentrations. Zones with higher moisture are interpreted to be more clay rich, lower 

moisture horizons are interpreted to be coarser gravels. 
4-29 

2,842

3,427

- Gravel layers assumed based on

relatively low moisture content

Projection of Conceptual Contamination Down Southern Structure

Edge of

Trenches

Groundwater

UZB-2 Trace of Southern Structure

Cross Section Looking Southeast

Meters

Depth Below Ground Surface (Meters)

Soil Gas 

Tritium concentrations 

in pCi/L

1,174

49,632

2,064

2,086

4,106

2,530

4,230

5,648

-200 -190 -180 -170 -160 -150 -140 -130 -120 -110 -100 -90 -80

-120

-110

-100

-90

-80

-70

-60

-50

-40

-30

-20

-10

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

50000

2,842

3,427

3,533

Groundwater

Tritium Concentration

at MR-3, near

UZB-2 = 12.16 pCi/L

Water Table Surface Inferred

from Monitoring Wells Projected 

Into Cross Section

Figure 4-27. Alternative conceptual model for the distribution of tritium in vadose zone based on 

Southern Structural offset and UZB-2 tritium concentrations (tritium data from Striegl et al., 1997) 

Table 4-2. Tritium model dispersivity values assigned to various materials 

Material Lambda 

Fault 0.0072

Surface Gravel 0.0150

Coarser Dryer Gravel 0.0173

Finer Moist Gravel 0.0140

Southern 

Structure 
4-30 

Table 4-3. Comparison of results from the tritium model to actual concentrations in UZB-2 (UZB-2 

data from Striegl et al., 1997) 

 UZB-2 Model Model Percent 

Depth (m) Tritium Estimate Depth (m) Comp. 

1.5 49632 49670 2 100% 

5.5 1174 1706 6 69% 

11.9 2842 3324 12 85% 

18.0 2064 1893 18 109% 

24.1 3427 3557 24 96% 

34.1 2086 2149 34 97% 

47.9 4106 4072 48 101% 

57.6 2531 2646 58 96% 

94.2 3533 3613 94 98% 

106.4 4230 4009 106 106% 

108.8 5648 5748 109 98% 

 

Tritium concentrations in pCi/L 

4.4 Monitoring Strategy Application Conclusions 

Based on the results of initial evaluation of data for the Amargosa Desert Research Site, it 

was unclear how tritium was reaching ground water over 109 meters below ground 

surface in an arid environment. 

A Schlumberger resistivity survey was conducted over the site as presented in Bisdorf 

(2002). Bisdorf identified a large scale structural feature northeast of the ADRS. As part 

of this Strategy application, three dimensional modeling of the resistivity data from 

Bisdorf (2002) using the capabilities of a geological modeling program (HydroGeo 

Analyst 2.0) resulted in the confirmation of the large fault identified by Bisdorf as well as 

the identification of a fault labeled the “Southern Structural offset” in the southwest 

corner of the ADRS. The Southern Structural offset appears to coincide with the location 

of the downward movement of tritium within the vadose zone to the water table. 

Modeling of the downward movement of contaminants could now be simulated once 

consideration was given to this additional structural feature as a fast path for the 

migration of contamination. 

Projection of the Southern Structural offset with a steep southwest dip intersected UZB-3 

at approximately 25 to 30 meters bgs. Analytical results of soil gas from this interval 

confirm the location of the feature. In addition, the steady increase in tritium detected 

down monitoring borehole UZB-2 indicates that the Southern Structural offset is 

approaching UZB-2 with depth. The Southern Structural offset intersects the water table 

slightly up dip of UZB-2. Ground water in the vicinity of monitoring well MR-3, 

screened in the water table slightly up dip of the intersection of the Southern Structural 

offset, contains elevated levels of tritium (4 to 6 times higher) in contrast to the other 

available ground-water monitoring wells associated with the ADRS. The presence of the 

elevated tritium in the water table also confirms the fast path movement of contaminants 

downward from the ADRS to the water table along the Southern Structural offset. 
4-31 

The presence of significant barometric pressure interaction between the surface and the 

subsurface within the vadose zone indicates that there is potential for significant soil gas 

movement. The barometric pumping of the vadose zone could produce significant 

vertical migration of soil contaminants along preferential pathways such as the Southern 

Structural offset. 

Only by analyzing the total data package for the site were we able to create a model that 

allows both an upward component of flow and localized downward migration of 

contaminants along a fast pathway. In addition, through examination of all geophysical 

and geologic information available, structures were identified that influence the 

movement of water and soil gas. Based on this more complete picture, an improved 

conceptual site model was developed and from this assessment informed decisions can be 

made for future site monitoring and assessment. 

4.5 Amargosa References 

Andraski, B.J., D.E Prudic, and W.D Nichols. “Waste Burial in Arid Environments--

Application of Information from a Field Laboratory in the Mojave Desert, Southern 

Nevada.” U.S. Geological Survey Fact Sheet FS-179-95, 4 p. 1995. 

Andraski, B.J., et al. Plant-Based Plume-Scale Mapping of Tritium Contamination in 

Desert Soils. Online Publication. August 16, 2005. 

Bisdorf, R.J. “Schlumberger Soundings at the Amargosa Desert Research Site, Nevada.” 

U.S. Geological Survey Open-File Report 02-140. 2002. 

California Geology Magazine. Detachment Faults, California’s Extended Past; 

Mineralization Along Detachment Faults; California Has Its Faults; Faulted WaveCut Terrace Near Point Arena [Mendocino County]. A Photo Essay. 

January/February 1992. 

Fischer, J.M. “Sediment Properties and Water Movement Through Shallow Unsaturated 

Alluvium at an Arid Site for Disposal of Low-Level Radioactive Waste Near 

Beatty, Nye County, Nevada.” U.S. Geological Survey Water-Resources 

Investigations Report 92-4032, 48 p.1992. 

Johnson, M.J., C.J Mayers, and B.J Andraski. “Selected micrometeorological and soilmoisture data at Amargosa Desert Research Site in Nye County near Beatty, 

Nevada, 1998-2000.” U.S. Geological Survey Open-File Report 02-348, available 

on the World Wide Web only. 2002. 

Prudic, D.E. “Estimates of Percolation Rates and Ages of Water in Unsaturated 

Sediments at Two Mojave Desert Sites, California-Nevada.” U.S. Geological 

Survey, Water Resources Investigation Report 91-4160. 1994. 

Prudic, D.E. “Water-vapor movement through unsaturated alluvium in Amargosa Desert 

near Beatty, Nevada--Current understanding and continuing studies, in Stevens, 
4-32 

P.R., and Nicholson, T.J., eds., Joint U.S. Geological Survey, U.S. Nuclear 

Regulatory Commission Workshop on research related to low-level radioactive 

waste disposal, May 4-6, 1993.” National Center, Reston, Virginia, Proceedings. 

U.S. Geological Survey Water-Resources Investigations Report 95-4015, p. 157-

166. 1996. 

Prudic, D.E., D.A Stonestrom, and R.G Striegl. “Tritium, deuterium, and oxygen-18 in 

water collected from unsaturated sediments near a low-level radioactive-waste 

burial site south of Beatty, Nevada.” U.S. Geological Survey Water-Resources 

Investigations Report 97-4062, 23 p.1997. 

Stonestrom, D.A., et al. “Estimates of deep percolation beneath native vegetation, 

irrigated fields, and the Amargosa River channel, Amargosa Desert, Nye County, 

Nevada`” U.S. Geological Survey Open-File Report 03-104, available on the world 

wide web. 2003. 

Stonestrom, D.A., et al. Monitoring Radionuclide Contamination in the Vadose ZoneLessons Learned at the Amargosa Desert Research Site, Nye County, Nevada. No 

Date. 

Striegl, R.G., et al. “Factors affecting tritium and 14carbon distributions in the 

unsaturated zone near the low-level radioactive-waste burial site south of Beatty, 

Nevada.” U.S. Geological Survey Open-File Report 96-110, 16 p. 1996. 

Striegl, R.G., et al. “Tritium in unsaturated zone gases and air at the Amargosa Desert 

Research Site, and in spring and river water, near Beatty, Nevada, May 1997.” U.S. 

Geological Survey Open-File Report 97-778, 13 p. 1997. 

Walvoord, M. A., CO2 dynamics in the Amargosa Desert: Fluxes and isotopic speciation 

in a deep unsaturated zone. Water Resources Research, 41, W02006, 

doi:10.1029/2004WR003599. 2005. 
4-33 

Appendix 4-A 

Appendix 4-A. Schlumberger Resistivity Data for the ADRS from Bisdorf, 2002 

Station Easting Northing Ground Elev. 

(m) 

Calculated 

Resistivity 

Reading 

(Ohm-m) 

Depth (m) Sample Elev. 

(m) 

ADRS 001 527081 4068750 846.5 300.55 0.47 846.03 

ADRS 001 527081 4068750 846.5 373.28 0.69 845.81 

ADRS 001 527081 4068750 846.5 514.87 1.01 845.49 

ADRS 001 527081 4068750 846.5 617.03 1.48 845.02 

ADRS 001 527081 4068750 846.5 467.72 2.17 844.33 

ADRS 001 527081 4068750 846.5 184.39 3.19 843.31 

ADRS 001 527081 4068750 846.5 50.72 4.68 841.82 

ADRS 001 527081 4068750 846.5 36.88 6.88 839.62 

ADRS 001 527081 4068750 846.5 61.97 10.09 836.41 

ADRS 002 527331 4068450 844.2 517.15 0.59 843.61 

ADRS 002 527331 4068450 844.2 730.4 0.87 843.33 

ADRS 002 527331 4068450 844.2 896.3 1.28 842.92 

ADRS 002 527331 4068450 844.2 832.2 1.87 842.33 

ADRS 002 527331 4068450 844.2 524.13 2.75 841.45 

ADRS 002 527331 4068450 844.2 203.44 4.04 840.16 

ADRS 002 527331 4068450 844.2 58.43 5.93 838.27 

ADRS 002 527331 4068450 844.2 36.49 8.7 835.5 

ADRS 002 527331 4068450 844.2 60.98 12.77 831.43 

ADRS 002 527331 4068450 844.2 91.39 18.74 825.46 

ADRS 002 527331 4068450 844.2 93.76 27.5 816.7 

ADRS 002 527331 4068450 844.2 69.75 40.37 803.83 

ADRS 003 528755 4068491 847.5 245.39 0.55 846.95 

ADRS 003 528755 4068491 847.5 179.54 0.81 846.69 

ADRS 003 528755 4068491 847.5 142.8 1.19 846.31 

ADRS 003 528755 4068491 847.5 116.74 1.74 845.76 

ADRS 003 528755 4068491 847.5 101.03 2.55 844.95 

ADRS 003 528755 4068491 847.5 74.23 3.75 843.75 

ADRS 003 528755 4068491 847.5 47.5 5.5 842 

ADRS 003 528755 4068491 847.5 43.35 8.074 839.426 

ADRS 003 528755 4068491 847.5 46.72 11.85 835.65 

ADRS 003 528755 4068491 847.5 40.64 17.39 830.11 

ADRS 003 528755 4068491 847.5 29.85 25.53 821.97 

ADRS 003 528755 4068491 847.5 27.5 37.47 810.03 

ADRS 003 528755 4068491 847.5 39.27 55.01 792.49 

ADRS 003 528755 4068491 847.5 63.25 80.74 766.76 

ADRS 003 528755 4068491 847.5 80.41 118.51 728.99 

ADRS 003 528755 4068491 847.5 75.13 173.94 673.56 

ADRS 003 528755 4068491 847.5 64.74 255.31 592.19 

ADRS 003 528755 4068491 847.5 71.71 374.75 472.75 

ADRS 003 528755 4068491 847.5 108.44 550.06 297.44 

ADRS 003 528755 4068491 847.5 186.24 807.37 40.13 

ADRS 004 529050 4068495 842.5 3076.99 0.4 842.1 

ADRS 004 529050 4068495 842.5 5680.3 0.59 841.91 

ADRS 004 529050 4068495 842.5 6983.81 0.87 841.63 

ADRS 004 529050 4068495 842.5 4788.29 1.27 841.23 

ADRS 004 529050 4068495 842.5 1720.84 1.87 840.63 

ADRS 004 529050 4068495 842.5 591.05 2.74 839.76 

ADRS 004 529050 4068495 842.5 617.39 4.02 838.48 

ADRS 004 529050 4068495 842.5 1152.72 5.9 836.6 
4-34 

ADRS 004 529050 4068495 842.5 1714.99 8.66 833.84 

ADRS 004 529050 4068495 842.5 1797.17 12.72 829.78 

ADRS 005 527831 4068650 845 1121.78 0.55 844.45 

ADRS 005 527831 4068650 845 845.5 0.81 844.19 

ADRS 005 527831 4068650 845 471.77 1.19 843.81 

ADRS 005 527831 4068650 845 201.04 1.74 843.26 

ADRS 005 527831 4068650 845 63.05 2.55 842.45 

ADRS 005 527831 4068650 845 35.46 3.75 841.25 

ADRS 005 527831 4068650 845 50.5 5.5 839.5 

ADRS 005 527831 4068650 845 71.77 8.074 836.926 

ADRS 005 527831 4068650 845 89.96 11.85 833.15 

ADRS 005 527831 4068650 845 99.83 17.39 827.61 

ADRS 005 527831 4068650 845 88.93 25.53 819.47 

ADRS 005 527831 4068650 845 60.82 37.47 807.53 

ADRS 005 527831 4068650 845 37.92 55.01 789.99 

ADRS 005 527831 4068650 845 28.37 80.74 764.26 

ADRS 006 527031 4068650 846.5 1129.27 0.55 845.95 

ADRS 006 527031 4068650 846.5 1934.75 0.81 845.69 

ADRS 006 527031 4068650 846.5 2302.09 1.19 845.31 

ADRS 006 527031 4068650 846.5 1674.72 1.74 844.76 

ADRS 006 527031 4068650 846.5 603.86 2.55 843.95 

ADRS 006 527031 4068650 846.5 99.42 3.75 842.75 

ADRS 006 527031 4068650 846.5 31.98 5.5 841 

ADRS 006 527031 4068650 846.5 66.81 8.074 838.426 

ADRS 006 527031 4068650 846.5 102.26 11.85 834.65 

ADRS 006 527031 4068650 846.5 125.95 17.39 829.11 

ADRS 006 527031 4068650 846.5 121.54 25.53 820.97 

ADRS 006 527031 4068650 846.5 78.09 37.47 809.03 

ADRS 006 527031 4068650 846.5 41.58 55.01 791.49 

ADRS 006 527031 4068650 846.5 31.49 80.74 765.76 

ADRS 007 527231 4068650 847.3 639.98 0.55 846.75 

ADRS 007 527231 4068650 847.3 657.29 0.81 846.49 

ADRS 007 527231 4068650 847.3 607.2 1.19 846.11 

ADRS 007 527231 4068650 847.3 494.27 1.74 845.56 

ADRS 007 527231 4068650 847.3 354.49 2.55 844.75 

ADRS 007 527231 4068650 847.3 183.12 3.75 843.55 

ADRS 007 527231 4068650 847.3 64.93 5.5 841.8 

ADRS 007 527231 4068650 847.3 45.76 8.074 839.226 

ADRS 007 527231 4068650 847.3 63.73 11.85 835.45 

ADRS 007 527231 4068650 847.3 84.52 17.39 829.91 

ADRS 007 527231 4068650 847.3 94.6 25.53 821.77 

ADRS 007 527231 4068650 847.3 82.32 37.47 809.83 

ADRS 007 527231 4068650 847.3 56.02 55.01 792.29 

ADRS 007 527231 4068650 847.3 39.32 80.74 766.56 

ADRS 008 527431 4068650 846.5 710.48 0.55 845.95 

ADRS 008 527431 4068650 846.5 766.9 0.81 845.69 

ADRS 008 527431 4068650 846.5 698 1.19 845.31 

ADRS 008 527431 4068650 846.5 487.68 1.74 844.76 

ADRS 008 527431 4068650 846.5 216.52 2.55 843.95 

ADRS 008 527431 4068650 846.5 62.59 3.75 842.75 

ADRS 008 527431 4068650 846.5 38.92 5.5 841 

ADRS 008 527431 4068650 846.5 56.22 8.074 838.426 

ADRS 008 527431 4068650 846.5 72.55 11.85 834.65 

ADRS 008 527431 4068650 846.5 79.96 17.39 829.11 

ADRS 008 527431 4068650 846.5 79.16 25.53 820.97 

ADRS 008 527431 4068650 846.5 71.52 37.47 809.03 

ADRS 008 527431 4068650 846.5 59.5 55.01 791.49 

ADRS 008 527431 4068650 846.5 43.49 80.74 765.76 

ADRS 009 527631 4068650 846.9 619.56 0.55 846.35 

ADRS 009 527631 4068650 846.9 749.02 0.81 846.09 

ADRS 009 527631 4068650 846.9 737.69 1.19 845.71 
4-35 

ADRS 009 527631 4068650 846.9 473.6 1.74 845.16 

ADRS 009 527631 4068650 846.9 144.64 2.55 844.35 

ADRS 009 527631 4068650 846.9 35.12 3.75 843.15 

ADRS 009 527631 4068650 846.9 45.75 5.5 841.4 

ADRS 009 527631 4068650 846.9 97.83 8.074 838.826 

ADRS 009 527631 4068650 846.9 117.38 11.85 835.05 

ADRS 009 527631 4068650 846.9 96.6 17.39 829.51 

ADRS 009 527631 4068650 846.9 74.32 25.53 821.37 

ADRS 009 527631 4068650 846.9 65.33 37.47 809.43 

ADRS 009 527631 4068650 846.9 67.67 55.01 791.89 

ADRS 009 527631 4068650 846.9 52.66 80.74 766.16 

ADRS 010 527831 4068450 843.4 1015.95 0.55 842.85 

ADRS 010 527831 4068450 843.4 1020.61 0.81 842.59 

ADRS 010 527831 4068450 843.4 601.78 1.19 842.21 

ADRS 010 527831 4068450 843.4 168.41 1.74 841.66 

ADRS 010 527831 4068450 843.4 42.01 2.55 840.85 

ADRS 010 527831 4068450 843.4 42.76 3.75 839.65 

ADRS 010 527831 4068450 843.4 67.91 5.5 837.9 

ADRS 010 527831 4068450 843.4 88.2 8.074 835.326 

ADRS 010 527831 4068450 843.4 96.36 11.85 831.55 

ADRS 010 527831 4068450 843.4 93.18 17.39 826.01 

ADRS 010 527831 4068450 843.4 83.65 25.53 817.87 

ADRS 010 527831 4068450 843.4 67.94 37.47 805.93 

ADRS 010 527831 4068450 843.4 43.19 55.01 788.39 

ADRS 010 527831 4068450 843.4 24.92 80.74 762.66 

ADRS 011 527631 4068450 843.8 678.23 0.55 843.25 

ADRS 011 527631 4068450 843.8 685.34 0.81 842.99 

ADRS 011 527631 4068450 843.8 645.88 1.19 842.61 

ADRS 011 527631 4068450 843.8 487.54 1.74 842.06 

ADRS 011 527631 4068450 843.8 240.74 2.55 841.25 

ADRS 011 527631 4068450 843.8 87.28 3.75 840.05 

ADRS 011 527631 4068450 843.8 55.45 5.5 838.3 

ADRS 011 527631 4068450 843.8 62.9 8.074 835.726 

ADRS 011 527631 4068450 843.8 67.77 11.85 831.95 

ADRS 011 527631 4068450 843.8 69.31 17.39 826.41 

ADRS 011 527631 4068450 843.8 71.21 25.53 818.27 

ADRS 011 527631 4068450 843.8 71.2 37.47 806.33 

ADRS 011 527631 4068450 843.8 61.78 55.01 788.79 

ADRS 011 527631 4068450 843.8 42.01 80.74 763.06 

ADRS 012 527431 4068450 844.2 433.81 0.55 843.65 

ADRS 012 527431 4068450 844.2 471.29 0.81 843.39 

ADRS 012 527431 4068450 844.2 471.28 1.19 843.01 

ADRS 012 527431 4068450 844.2 396.9 1.74 842.46 

ADRS 012 527431 4068450 844.2 246.86 2.55 841.65 

ADRS 012 527431 4068450 844.2 109.89 3.75 840.45 

ADRS 012 527431 4068450 844.2 56.97 5.5 838.7 

ADRS 012 527431 4068450 844.2 56.43 8.074 836.126 

ADRS 012 527431 4068450 844.2 72.58 11.85 832.35 

ADRS 012 527431 4068450 844.2 89 17.39 826.81 

ADRS 012 527431 4068450 844.2 92.64 25.53 818.67 

ADRS 012 527431 4068450 844.2 75.26 37.47 806.73 

ADRS 012 527431 4068450 844.2 52.53 55.01 789.19 

ADRS 012 527431 4068450 844.2 39.6 80.74 763.46 

ADRS 013 527231 4068450 844.2 380.67 0.55 843.65 

ADRS 013 527231 4068450 844.2 412.17 0.81 843.39 

ADRS 013 527231 4068450 844.2 456.31 1.19 843.01 

ADRS 013 527231 4068450 844.2 368.39 1.74 842.46 

ADRS 013 527231 4068450 844.2 191.12 2.55 841.65 

ADRS 013 527231 4068450 844.2 85.67 3.75 840.45 

ADRS 013 527231 4068450 844.2 56.85 5.5 838.7 

ADRS 013 527231 4068450 844.2 55.04 8.074 836.126 
4-36 

ADRS 013 527231 4068450 844.2 68.54 11.85 832.35 

ADRS 013 527231 4068450 844.2 91.85 17.39 826.81 

ADRS 013 527231 4068450 844.2 102.52 25.53 818.67 

ADRS 013 527231 4068450 844.2 84.4 37.47 806.73 

ADRS 013 527231 4068450 844.2 54.99 55.01 789.19 

ADRS 013 527231 4068450 844.2 37.7 80.74 763.46 

ADRS 014 527031 4068450 845.2 765.68 0.55 844.65 

ADRS 014 527031 4068450 845.2 622.75 0.81 844.39 

ADRS 014 527031 4068450 845.2 423.58 1.19 844.01 

ADRS 014 527031 4068450 845.2 239.99 1.74 843.46 

ADRS 014 527031 4068450 845.2 132.88 2.55 842.65 

ADRS 014 527031 4068450 845.2 92.59 3.75 841.45 

ADRS 014 527031 4068450 845.2 78.31 5.5 839.7 

ADRS 014 527031 4068450 845.2 72.58 8.074 837.126 

ADRS 014 527031 4068450 845.2 73.29 11.85 833.35 

ADRS 014 527031 4068450 845.2 79.46 17.39 827.81 

ADRS 014 527031 4068450 845.2 83.41 25.53 819.67 

ADRS 014 527031 4068450 845.2 70.71 37.47 807.73 

ADRS 014 527031 4068450 845.2 46.67 55.01 790.19 

ADRS 014 527031 4068450 845.2 32.32 80.74 764.46 

ADRS 015 526831 4068450 846.1 1730.67 0.55 845.55 

ADRS 015 526831 4068450 846.1 1029.1 0.81 845.29 

ADRS 015 526831 4068450 846.1 507.58 1.19 844.91 

ADRS 015 526831 4068450 846.1 242.92 1.74 844.36 

ADRS 015 526831 4068450 846.1 121.2 2.55 843.55 

ADRS 015 526831 4068450 846.1 91.67 3.75 842.35 

ADRS 015 526831 4068450 846.1 95.09 5.5 840.6 

ADRS 015 526831 4068450 846.1 93.79 8.074 838.026 

ADRS 015 526831 4068450 846.1 87.67 11.85 834.25 

ADRS 015 526831 4068450 846.1 80.71 17.39 828.71 

ADRS 015 526831 4068450 846.1 73.39 25.53 820.57 

ADRS 015 526831 4068450 846.1 69.42 37.47 808.63 

ADRS 015 526831 4068450 846.1 66.7 55.01 791.09 

ADRS 015 526831 4068450 846.1 51.37 80.74 765.36 

ADRS 016 528031 4068650 844.8 823.4 0.44 844.36 

ADRS 016 528031 4068650 844.8 534.27 0.65 844.15 

ADRS 016 528031 4068650 844.8 242.29 0.96 843.84 

ADRS 016 528031 4068650 844.8 95.28 1.41 843.39 

ADRS 016 528031 4068650 844.8 54.03 2.06 842.74 

ADRS 016 528031 4068650 844.8 41.87 3.03 841.77 

ADRS 016 528031 4068650 844.8 35 4.44 840.36 

ADRS 016 528031 4068650 844.8 40.13 6.52 838.28 

ADRS 016 528031 4068650 844.8 55.44 9.57 835.23 

ADRS 016 528031 4068650 844.8 69.59 14.05 830.75 

ADRS 016 528031 4068650 844.8 74.39 20.63 824.17 

ADRS 016 528031 4068650 844.8 64.66 30.28 814.52 

ADRS 016 528031 4068650 844.8 42.45 44.44 800.36 

ADRS 016 528031 4068650 844.8 22.36 65.23 779.57 

ADRS 016 528031 4068650 844.8 15.13 95.74 749.06 

ADRS 016 528031 4068650 844.8 18.98 140.53 704.27 

ADRS 016 528031 4068650 844.8 32.09 206.27 638.53 

ADRS 016 528031 4068650 844.8 53.41 302.77 542.03 

ADRS 017 529120 4068595 840.5 1052.67 0.59 839.91 

ADRS 017 529120 4068595 840.5 576.82 0.87 839.63 

ADRS 017 529120 4068595 840.5 349.45 1.28 839.22 

ADRS 017 529120 4068595 840.5 237.41 1.87 838.63 

ADRS 017 529120 4068595 840.5 202.82 2.75 837.75 

ADRS 017 529120 4068595 840.5 217.88 4.04 836.46 

ADRS 017 529120 4068595 840.5 207.57 5.93 834.57 

ADRS 017 529120 4068595 840.5 158.57 8.7 831.8 

ADRS 017 529120 4068595 840.5 132.73 12.77 827.73 
4-37 

ADRS 017 529120 4068595 840.5 155.58 18.74 821.76 

ADRS 017 529120 4068595 840.5 216.59 27.5 813 

ADRS 017 529120 4068595 840.5 281.55 40.37 800.13 

ADRS 017 529120 4068595 840.5 315.72 59.25 781.25 

ADRS 017 529120 4068595 840.5 303.47 86.97 753.53 

ADRS 017 529120 4068595 840.5 250.52 127.66 712.84 

ADRS 017 529120 4068595 840.5 194.4 187.37 653.13 

ADRS 017 529120 4068595 840.5 175.19 275.03 565.47 

ADRS 017 529120 4068595 840.5 189.49 403.69 436.81 

ADRS 018 528168 4068650 846.5 391.05 0.55 845.95 

ADRS 018 528168 4068650 846.5 369.58 0.81 845.69 

ADRS 018 528168 4068650 846.5 234.21 1.19 845.31 

ADRS 018 528168 4068650 846.5 89.01 1.74 844.76 

ADRS 018 528168 4068650 846.5 31.15 2.55 843.95 

ADRS 018 528168 4068650 846.5 25.72 3.75 842.75 

ADRS 018 528168 4068650 846.5 34.28 5.5 841 

ADRS 018 528168 4068650 846.5 44.53 8.074 838.426 

ADRS 018 528168 4068650 846.5 51.31 11.85 834.65 

ADRS 018 528168 4068650 846.5 53.69 17.39 829.11 

ADRS 018 528168 4068650 846.5 54.07 25.53 820.97 

ADRS 018 528168 4068650 846.5 49.57 37.47 809.03 

ADRS 018 528168 4068650 846.5 34.77 55.01 791.49 

ADRS 018 528168 4068650 846.5 20.09 80.74 765.76 

ADRS 019 527306 4068700 847.3 772.14 0.64 846.66 

ADRS 019 527306 4068700 847.3 828.66 0.94 846.36 

ADRS 019 527306 4068700 847.3 802.56 1.38 845.92 

ADRS 019 527306 4068700 847.3 643.98 2.02 845.28 

ADRS 019 527306 4068700 847.3 371.31 2.96 844.34 

ADRS 019 527306 4068700 847.3 135.86 4.35 842.95 

ADRS 019 527306 4068700 847.3 51.43 6.38 840.92 

ADRS 019 527306 4068700 847.3 46.96 9.37 837.93 

ADRS 019 527306 4068700 847.3 61.19 13.75 833.55 

ADRS 019 527306 4068700 847.3 72.53 20.18 827.12 

ADRS 019 527306 4068700 847.3 73.71 29.63 817.67 

ADRS 019 527306 4068700 847.3 67.44 43.49 803.81 

ADRS 019 527306 4068700 847.3 58.09 63.83 783.47 

ADRS 019 527306 4068700 847.3 44.13 93.69 753.61 

ADRS 019 527306 4068700 847.3 28.83 137.51 709.79 

ADRS 019 527306 4068700 847.3 19.33 201.84 645.46 

ADRS 020 527931 4068550 843.5 809.31 0.55 842.95 

ADRS 020 527931 4068550 843.5 687.48 0.81 842.69 

ADRS 020 527931 4068550 843.5 370.81 1.19 842.31 

ADRS 020 527931 4068550 843.5 116.71 1.74 841.76 

ADRS 020 527931 4068550 843.5 43.3 2.55 840.95 

ADRS 020 527931 4068550 843.5 40.78 3.75 839.75 

ADRS 020 527931 4068550 843.5 50.25 5.5 838 

ADRS 020 527931 4068550 843.5 32.6 8.074 835.426 

ADRS 020 527931 4068550 843.5 74.97 11.85 831.65 

ADRS 020 527931 4068550 843.5 81.39 17.39 826.11 

ADRS 020 527931 4068550 843.5 75.32 25.53 817.97 

ADRS 020 527931 4068550 843.5 58.16 37.47 806.03 

ADRS 020 527931 4068550 843.5 40.89 55.01 788.49 

ADRS 020 527931 4068550 843.5 29.69 80.74 762.76 

ADRS 021 527731 4068550 843.9 964.98 0.55 843.35 

ADRS 021 527731 4068550 843.9 929.65 0.81 843.09 

ADRS 021 527731 4068550 843.9 790.15 1.19 842.71 

ADRS 021 527731 4068550 843.9 633.56 1.74 842.16 

ADRS 021 527731 4068550 843.9 389.16 2.55 841.35 

ADRS 021 527731 4068550 843.9 130.76 3.75 840.15 

ADRS 021 527731 4068550 843.9 44.4 5.5 838.4 

ADRS 021 527731 4068550 843.9 45.61 8.074 835.826 
4-38 

ADRS 021 527731 4068550 843.9 64.46 11.85 832.05 

ADRS 021 527731 4068550 843.9 79.5 17.39 826.51 

ADRS 021 527731 4068550 843.9 80.28 25.53 818.37 

ADRS 021 527731 4068550 843.9 65.64 37.47 806.43 

ADRS 021 527731 4068550 843.9 47.84 55.01 788.89 

ADRS 021 527731 4068550 843.9 37.22 80.74 763.16 

ADRS 022 527531 4068550 844.3 900.89 0.55 843.75 

ADRS 022 527531 4068550 844.3 1040.08 0.81 843.49 

ADRS 022 527531 4068550 844.3 952.64 1.19 843.11 

ADRS 022 527531 4068550 844.3 532.79 1.74 842.56 

ADRS 022 527531 4068550 844.3 168.98 2.55 841.75 

ADRS 022 527531 4068550 844.3 56.98 3.75 840.55 

ADRS 022 527531 4068550 844.3 47.7 5.5 838.8 

ADRS 022 527531 4068550 844.3 57.82 8.074 836.226 

ADRS 022 527531 4068550 844.3 71.49 11.85 832.45 

ADRS 022 527531 4068550 844.3 80.84 17.39 826.91 

ADRS 022 527531 4068550 844.3 77.86 25.53 818.77 

ADRS 022 527531 4068550 844.3 63.95 37.47 806.83 

ADRS 022 527531 4068550 844.3 49.76 55.01 789.29 

ADRS 022 527531 4068550 844.3 41.26 80.74 763.56 

ADRS 023 528131 4068550 842.2 924.25 0.55 841.65 

ADRS 023 528131 4068550 842.2 538.83 0.81 841.39 

ADRS 023 528131 4068550 842.2 250.9 1.19 841.01 

ADRS 023 528131 4068550 842.2 87.32 1.74 840.46 

ADRS 023 528131 4068550 842.2 41.03 2.55 839.65 

ADRS 023 528131 4068550 842.2 41.75 3.75 838.45 

ADRS 023 528131 4068550 842.2 53.25 5.5 836.7 

ADRS 023 528131 4068550 842.2 66.64 8.074 834.126 

ADRS 023 528131 4068550 842.2 74.22 11.85 830.35 

ADRS 023 528131 4068550 842.2 70.08 17.39 824.81 

ADRS 023 528131 4068550 842.2 57.51 25.53 816.67 

ADRS 023 528131 4068550 842.2 44.37 37.47 804.73 

ADRS 023 528131 4068550 842.2 33.42 55.01 787.19 

ADRS 023 528131 4068550 842.2 23.22 80.74 761.46 

ADRS 024 528331 4068550 844.5 273.74 0.55 843.95 

ADRS 024 528331 4068550 844.5 186.41 0.81 843.69 

ADRS 024 528331 4068550 844.5 215.12 1.19 843.31 

ADRS 024 528331 4068550 844.5 271.03 1.74 842.76 

ADRS 024 528331 4068550 844.5 204.5 2.55 841.95 

ADRS 024 528331 4068550 844.5 86.94 3.75 840.75 

ADRS 024 528331 4068550 844.5 44.2 5.5 839 

ADRS 024 528331 4068550 844.5 50.95 8.074 836.426 

ADRS 024 528331 4068550 844.5 62.22 11.85 832.65 

ADRS 024 528331 4068550 844.5 47.28 17.39 827.11 

ADRS 024 528331 4068550 844.5 30.61 25.53 818.97 

ADRS 024 528331 4068550 844.5 25.02 37.47 807.03 

ADRS 024 528331 4068550 844.5 23.21 55.01 789.49 

ADRS 024 528331 4068550 844.5 28.17 80.74 763.76 

ADRS 025 528531 4068550 847.4 567.22 0.61 846.79 

ADRS 025 528531 4068550 847.4 434.46 0.9 846.5 

ADRS 025 528531 4068550 847.4 311.32 1.32 846.08 

ADRS 025 528531 4068550 847.4 229.38 1.93 845.47 

ADRS 025 528531 4068550 847.4 179.76 2.84 844.56 

ADRS 025 528531 4068550 847.4 137.9 4.16 843.24 

ADRS 025 528531 4068550 847.4 108.86 6.11 841.29 

ADRS 025 528531 4068550 847.4 95.33 8.97 838.43 

ADRS 025 528531 4068550 847.4 80.95 13.17 834.23 

ADRS 025 528531 4068550 847.4 59.08 19.33 828.07 

ADRS 025 528531 4068550 847.4 41.44 28.37 819.03 

ADRS 025 528531 4068550 847.4 30.21 41.64 805.76 

ADRS 025 528531 4068550 847.4 25.2 61.12 786.28 
4-39 

ADRS 025 528531 4068550 845 32.65 89.71 755.29 

ADRS 026 527911 4068740 845 238.33 0.55 844.45 

ADRS 026 527911 4068740 845 231.35 0.81 844.19 

ADRS 026 527911 4068740 845 148.14 1.19 843.81 

ADRS 026 527911 4068740 845 66.57 1.74 843.26 

ADRS 026 527911 4068740 845 26.28 2.55 842.45 

ADRS 026 527911 4068740 845 18.17 3.75 841.25 

ADRS 026 527911 4068740 845 29.98 5.5 839.5 

ADRS 026 527911 4068740 845 51.67 8.074 836.926 

ADRS 026 527911 4068740 845 57.53 11.85 833.15 

ADRS 026 527911 4068740 845 40.05 17.39 827.61 

ADRS 026 527911 4068740 845 23.93 25.53 819.47 

ADRS 026 527911 4068740 845 21.67 37.47 807.53 

ADRS 026 527911 4068740 845 28.29 55.01 789.99 

ADRS 026 527911 4068740 845 25.29 80.74 764.26 

ADRS 027 527711 4068740 846.1 206.07 0.55 845.55 

ADRS 027 527711 4068740 846.1 271.3 0.81 845.29 

ADRS 027 527711 4068740 846.1 220.19 1.19 844.91 

ADRS 027 527711 4068740 846.1 95.66 1.74 844.36 

ADRS 027 527711 4068740 846.1 32.55 2.55 843.55 

ADRS 027 527711 4068740 846.1 24.44 3.75 842.35 

ADRS 027 527711 4068740 846.1 35.88 5.5 840.6 

ADRS 027 527711 4068740 846.1 53.59 8.074 838.026 

ADRS 027 527711 4068740 846.1 69.07 11.85 834.25 

ADRS 027 527711 4068740 846.1 67.05 17.39 828.71 

ADRS 027 527711 4068740 846.1 45.3 25.53 820.57 

ADRS 027 527711 4068740 846.1 25.82 37.47 808.63 

ADRS 027 527711 4068740 846.1 20.97 55.01 791.09 

ADRS 027 527711 4068740 846.1 28.25 80.74 765.36 

ADRS 028 527516 4068740 847.3 248.61 0.55 846.75 

ADRS 028 527516 4068740 847.3 516.57 0.81 846.49 

ADRS 028 527516 4068740 847.3 839.63 1.19 846.11 

ADRS 028 527516 4068740 847.3 1002.71 1.74 845.56 

ADRS 028 527516 4068740 847.3 753.23 2.55 844.75 

ADRS 028 527516 4068740 847.3 290.52 3.75 843.55 

ADRS 028 527516 4068740 847.3 60.38 5.5 841.8 

ADRS 028 527516 4068740 847.3 23.6 8.074 839.226 

ADRS 028 527516 4068740 847.3 57.29 11.85 835.45 

ADRS 028 527516 4068740 847.3 73.03 17.39 829.91 

ADRS 028 527516 4068740 847.3 45.78 25.53 821.77 

ADRS 028 527516 4068740 847.3 32.91 37.47 809.83 

ADRS 028 527516 4068740 847.3 32.67 55.01 792.29 

ADRS 028 527516 4068740 847.3 31.92 80.74 766.56 

ADRS 029 527321 4068740 847.3 725.68 0.55 846.75 

ADRS 029 527321 4068740 847.3 799.65 0.81 846.49 

ADRS 029 527321 4068740 847.3 946.52 1.19 846.11 

ADRS 029 527321 4068740 847.3 977.51 1.74 845.56 

ADRS 029 527321 4068740 847.3 668.64 2.55 844.75 

ADRS 029 527321 4068740 847.3 274.54 3.75 843.55 

ADRS 029 527321 4068740 847.3 96.49 5.5 841.8 

ADRS 029 527321 4068740 847.3 66.81 8.074 839.226 

ADRS 029 527321 4068740 847.3 89.67 11.85 835.45 

ADRS 029 527321 4068740 847.3 111.46 17.39 829.91 

ADRS 029 527321 4068740 847.3 94.08 25.53 821.77 

ADRS 029 527321 4068740 847.3 57.02 37.47 809.83 

ADRS 029 527321 4068740 847.3 35.91 55.01 792.29 

ADRS 029 527321 4068740 847.3 32.83 80.74 766.56 

ADRS 030 529866 4070887 950.67 2255.45 2.06 948.61 

ADRS 030 529866 4070887 950.67 847.23 3.03 947.64 

ADRS 030 529866 4070887 950.67 859.46 4.44 946.23 

ADRS 030 529866 4070887 950.67 1278.99 6.52 944.15 
4-40 

ADRS 030 529866 4070887 950.67 1306.32 9.57 941.1 

ADRS 030 529866 4070887 950.67 1130.57 14.05 936.62 

ADRS 030 529866 4070887 950.67 1079.34 20.63 930.04 

ADRS 030 529866 4070887 950.67 975.8 30.28 920.39 

ADRS 030 529866 4070887 950.67 756.34 44.44 906.23 

ADRS 030 529866 4070887 950.67 611.74 65.23 885.44 

ADRS 030 529866 4070887 950.67 515.78 85.74 864.93 

ADRS 030 529866 4070887 950.67 391.62 140.53 810.14 

ADRS 030 529866 4070887 950.67 360.73 206.27 744.4 

ADRS 030 529866 4070887 950.67 468.79 302.77 647.9 

ADRS 031 528111 4068740 846.5 774.33 0.55 845.95 

ADRS 031 528111 4068740 846.5 534.72 0.81 845.69 

ADRS 031 528111 4068740 846.5 273.3 1.19 845.31 

ADRS 031 528111 4068740 846.5 100.15 1.74 844.76 

ADRS 031 528111 4068740 846.5 48.04 2.55 843.95 

ADRS 031 528111 4068740 846.5 43.91 3.75 842.75 

ADRS 031 528111 4068740 846.5 48.52 5.5 841 

ADRS 031 528111 4068740 846.5 56.33 8.074 838.426 

ADRS 031 528111 4068740 846.5 63.49 11.85 834.65 

ADRS 031 528111 4068740 846.5 66.78 17.39 829.11 

ADRS 031 528111 4068740 846.5 65.33 25.53 820.97 

ADRS 031 528111 4068740 846.5 55.1 37.47 809.03 

ADRS 031 528111 4068740 846.5 34.68 55.01 791.49 

ADRS 031 528111 4068740 846.5 16.28 80.74 765.76 

ADRS 032 528416 4068729 844.2 450.43 0.55 843.65 

ADRS 032 528416 4068729 844.2 388.56 0.81 843.39 

ADRS 032 528416 4068729 844.2 256.06 1.19 843.01 

ADRS 032 528416 4068729 844.2 154.59 1.74 842.46 

ADRS 032 528416 4068729 844.2 117.02 2.55 841.65 

ADRS 032 528416 4068729 844.2 109.65 3.75 840.45 

ADRS 032 528416 4068729 844.2 105.69 5.5 838.7 

ADRS 032 528416 4068729 844.2 93.74 8.074 836.126 

ADRS 032 528416 4068729 844.2 73.44 11.85 832.35 

ADRS 032 528416 4068729 844.2 54.16 17.39 826.81 

ADRS 032 528416 4068729 844.2 40.94 25.53 818.67 

ADRS 032 528416 4068729 844.2 32.64 37.47 806.73 

ADRS 032 528416 4068729 844.2 27.97 55.01 789.19 

ADRS 032 528416 4068729 844.2 26.9 80.74 763.46 

ADRS 033 528031 4068450 841.2 719.65 0.55 840.65 

ADRS 033 528031 4068450 841.2 590.04 0.81 840.39 

ADRS 033 528031 4068450 841.2 431.46 1.19 840.01 

ADRS 033 528031 4068450 841.2 186.55 1.74 839.46 

ADRS 033 528031 4068450 841.2 44.59 2.55 838.65 

ADRS 033 528031 4068450 841.2 28.7 3.75 837.45 

ADRS 033 528031 4068450 841.2 47.18 5.5 835.7 

ADRS 033 528031 4068450 841.2 70.98 8.074 833.126 

ADRS 033 528031 4068450 841.2 85.77 11.85 829.35 

ADRS 033 528031 4068450 841.2 82.12 17.39 823.81 

ADRS 033 528031 4068450 841.2 66.15 25.53 815.67 

ADRS 033 528031 4068450 841.2 49.55 37.47 803.73 

ADRS 033 528031 4068450 841.2 37.44 55.01 786.19 

ADRS 033 528031 4068450 841.2 28.41 80.74 760.46 

ADRS 034 528031 4068230 841.2 671.98 0.55 840.65 

ADRS 034 528031 4068230 841.2 555.22 0.81 840.39 

ADRS 034 528031 4068230 841.2 189.23 1.19 840.01 

ADRS 034 528031 4068230 841.2 68.81 1.74 839.46 

ADRS 034 528031 4068230 841.2 24.7 2.55 838.65 

ADRS 034 528031 4068230 841.2 26.28 3.75 837.45 

ADRS 034 528031 4068230 841.2 45.68 5.5 835.7 

ADRS 034 528031 4068230 841.2 73.58 8.074 833.126 

ADRS 034 528031 4068230 841.2 66.18 11.85 829.35 
4-41 

ADRS 034 528031 4068230 841.2 87.68 17.39 823.81 

ADRS 034 528031 4068230 841.2 77.76 25.53 815.67 

ADRS 034 528031 4068230 841.2 41.69 37.47 803.73 

ADRS 034 528031 4068230 841.2 45.8 55.01 786.19 

ADRS 034 528031 4068230 841.2 30.53 80.74 760.46 

ADRS 035 528031 4067987 840.1 641.84 0.55 839.55 

ADRS 035 528031 4067987 840.1 526.42 0.81 839.29 

ADRS 035 528031 4067987 840.1 368.19 1.19 838.91 

ADRS 035 528031 4067987 840.1 190.09 1.74 838.36 

ADRS 035 528031 4067987 840.1 67.65 2.55 837.55 

ADRS 035 528031 4067987 840.1 34.24 3.75 836.35 

ADRS 035 528031 4067987 840.1 35.13 5.5 834.6 

ADRS 035 528031 4067987 840.1 48.56 8.074 832.026 

ADRS 035 528031 4067987 840.1 69.03 11.85 828.25 

ADRS 035 528031 4067987 840.1 85.37 17.39 822.71 

ADRS 035 528031 4067987 840.1 83.28 25.53 814.57 

ADRS 035 528031 4067987 840.1 58.86 37.47 802.63 

ADRS 035 528031 4067987 840.1 36.33 55.01 785.09 

ADRS 035 528031 4067987 840.1 35.06 80.74 759.36 

ADRS 036 527731 4068350 842.4 899.93 0.55 841.85 

ADRS 036 527731 4068350 842.4 856.46 0.81 841.59 

ADRS 036 527731 4068350 842.4 587.29 1.19 841.21 

ADRS 036 527731 4068350 842.4 262.51 1.74 840.66 

ADRS 036 527731 4068350 842.4 94.63 2.55 839.85 

ADRS 036 527731 4068350 842.4 54.25 3.75 838.65 

ADRS 036 527731 4068350 842.4 57.55 5.5 836.9 

ADRS 036 527731 4068350 842.4 69.83 8.07 834.33 

ADRS 036 527731 4068350 842.4 79.41 11.85 830.55 

ADRS 036 527731 4068350 842.4 88.31 17.39 825.01 

ADRS 036 527731 4068350 842.4 92.66 25.53 816.87 

ADRS 036 527731 4068350 842.4 77.82 37.47 804.93 

ADRS 036 527731 4068350 842.4 50.5 55.01 787.39 

ADRS 036 527731 4068350 842.4 34.42 80.74 761.66 

ADRS 037 527731 4068106 841.2 399.66 0.55 840.65 

ADRS 037 527731 4068106 841.2 516.77 0.81 840.39 

ADRS 037 527731 4068106 841.2 538.59 1.19 840.01 

ADRS 037 527731 4068106 841.2 404.4 1.74 839.46 

ADRS 037 527731 4068106 841.2 186.08 2.55 838.65 

ADRS 037 527731 4068106 841.2 56.24 3.75 837.45 

ADRS 037 527731 4068106 841.2 32.02 5.5 835.7 

ADRS 037 527731 4068106 841.2 44.82 8.07 833.13 

ADRS 037 527731 4068106 841.2 62.89 11.85 829.35 

ADRS 037 527731 4068106 841.2 75.72 17.39 823.81 

ADRS 037 527731 4068106 841.2 81.03 25.53 815.67 

ADRS 037 527731 4068106 841.2 80.92 37.47 803.73 

ADRS 037 527731 4068106 841.2 71.86 55.01 786.19 

ADRS 037 527731 4068106 841.2 47.18 80.74 760.46 

ADRS 038 528231 4068230 841.2 581.84 0.55 840.65 

ADRS 038 528231 4068230 841.2 379.32 0.81 840.39 

ADRS 038 528231 4068230 841.2 236.06 1.19 840.01 

ADRS 038 528231 4068230 841.2 118.76 1.74 839.46 

ADRS 038 528231 4068230 841.2 48.78 2.55 838.65 

ADRS 038 528231 4068230 841.2 36.7 3.75 837.45 

ADRS 038 528231 4068230 841.2 44.73 5.5 835.7 

ADRS 038 528231 4068230 841.2 54.37 8.07 833.13 

ADRS 038 528231 4068230 841.2 59.75 11.85 829.35 

ADRS 038 528231 4068230 841.2 59.12 17.39 823.81 

ADRS 038 528231 4068230 841.2 53.6 25.53 815.67 

ADRS 038 528231 4068230 841.2 42.89 37.47 803.73 

ADRS 038 528231 4068230 841.2 30.49 55.01 786.19 

ADRS 038 528231 4068230 841.2 25.17 80.74 760.46 
4-42 

ADRS 101 526499 4068853 849.3 855.23 0.55 848.75 

ADRS 101 526499 4068853 849.3 1003.53 0.81 848.49 

ADRS 101 526499 4068853 849.3 1094.85 1.19 848.11 

ADRS 101 526499 4068853 849.3 801.78 1.74 847.56 

ADRS 101 526499 4068853 849.3 284.04 2.55 846.75 

ADRS 101 526499 4068853 849.3 56.56 3.75 845.55 

ADRS 101 526499 4068853 849.3 31.15 5.5 843.8 

ADRS 101 526499 4068853 849.3 49.42 8.074 841.226 

ADRS 101 526499 4068853 849.3 76.29 11.85 837.45 

ADRS 101 526499 4068853 849.3 97.51 17.39 831.91 

ADRS 101 526499 4068853 849.3 93.61 25.53 823.77 

ADRS 101 526499 4068853 849.3 69.03 37.47 811.83 

ADRS 101 526499 4068853 849.3 48.29 55.01 794.29 

ADRS 101 526499 4068853 849.3 41.64 80.74 768.56 

ADRS 101 526499 4068853 849.3 42.76 118.51 730.79 

ADRS 101 526499 4068853 849.3 43.65 173.94 675.36 

ADRS 101 526499 4068853 849.3 42.7 255.31 593.99 

ADRS 101 526499 4068853 849.3 41.32 374.75 474.55 

ADRS 101 526499 4068853 849.3 45.9 550.06 299.24 

ADRS 101 526499 4068853 849.3 69.77 807.37 41.93 

ADRS 102 527219 4069154 849.3 72.64 0.55 848.75 

ADRS 102 527219 4069154 849.3 113.33 0.81 848.49 

ADRS 102 527219 4069154 849.3 168.22 1.19 848.11 

ADRS 102 527219 4069154 849.3 211.66 1.74 847.56 

ADRS 102 527219 4069154 849.3 203.83 2.55 846.75 

ADRS 102 527219 4069154 849.3 140.04 3.75 845.55 

ADRS 102 527219 4069154 849.3 72.98 5.5 843.8 

ADRS 102 527219 4069154 849.3 42.97 8.074 841.226 

ADRS 102 527219 4069154 849.3 48.23 11.85 837.45 

ADRS 102 527219 4069154 849.3 77.3 17.39 831.91 

ADRS 102 527219 4069154 849.3 93.98 25.53 823.77 

ADRS 102 527219 4069154 849.3 70.64 37.47 811.83 

ADRS 102 527219 4069154 849.3 38.43 55.01 794.29 

ADRS 102 527219 4069154 849.3 28.09 80.74 768.56 

ADRS 102 527219 4069154 849.3 36.33 118.51 730.79 

ADRS 102 527219 4069154 849.3 44.91 173.94 675.36 

ADRS 102 527219 4069154 849.3 46.41 255.31 593.99 

ADRS 102 527219 4069154 849.3 55.04 374.75 474.55 

ADRS 102 527219 4069154 849.3 81.27 550.06 299.24 

ADRS 102 527219 4069154 849.3 120.39 807.37 41.93 

ADRS 103 528050 4069162 847.2 158.34 0.59 846.61 

ADRS 103 528050 4069162 847.2 180.04 0.87 846.33 

ADRS 103 528050 4069162 847.2 186.8 1.28 845.92 

ADRS 103 528050 4069162 847.2 122.75 1.87 845.33 

ADRS 103 528050 4069162 847.2 57.75 2.75 844.45 

ADRS 103 528050 4069162 847.2 43.91 4.04 843.16 

ADRS 103 528050 4069162 847.2 59.73 5.93 841.27 

ADRS 103 528050 4069162 847.2 93.42 8.7 838.5 

ADRS 103 528050 4069162 847.2 137.66 12.77 834.43 

ADRS 103 528050 4069162 847.2 149.61 18.74 828.46 

ADRS 103 528050 4069162 847.2 96.77 27.5 819.7 

ADRS 103 528050 4069162 847.2 39.55 40.37 806.83 

ADRS 103 528050 4069162 847.2 21.47 59.25 787.95 

ADRS 103 528050 4069162 847.2 26.71 86.97 760.23 

ADRS 103 528050 4069162 847.2 27.32 127.66 719.54 

ADRS 103 528050 4069162 847.2 21.91 187.37 659.83 

ADRS 103 528050 4069162 847.2 31.02 275.03 572.17 

ADRS 103 528050 4069162 847.2 80.35 403.69 443.51 

ADRS 104 527676 4069165 847.3 288.29 0.55 846.75 

ADRS 104 527676 4069165 847.3 256.7 0.81 846.49 

ADRS 104 527676 4069165 847.3 172.34 1.19 846.11 
4-43 

ADRS 104 527676 4069165 847.3 110.93 1.74 845.56 

ADRS 104 527676 4069165 847.3 70.69 2.55 844.75 

ADRS 104 527676 4069165 847.3 37.33 3.75 843.55 

ADRS 104 527676 4069165 847.3 28.66 5.5 841.8 

ADRS 104 527676 4069165 847.3 41.45 8.074 839.226 

ADRS 104 527676 4069165 847.3 68.67 11.85 835.45 

ADRS 104 527676 4069165 847.3 98.05 17.39 829.91 

ADRS 104 527676 4069165 847.3 103.56 25.53 821.77 

ADRS 104 527676 4069165 847.3 71.13 37.47 809.83 

ADRS 104 527676 4069165 847.3 33.12 55.01 792.29 

ADRS 104 527676 4069165 847.3 17.94 80.74 766.56 

ADRS 105 528050 4068908 845.7 983.55 0.55 845.15 

ADRS 105 528050 4068908 845.7 1033.81 0.81 844.89 

ADRS 105 528050 4068908 845.7 652.68 1.19 844.51 

ADRS 105 528050 4068908 845.7 187.22 1.74 843.96 

ADRS 105 528050 4068908 845.7 34.36 2.55 843.15 

ADRS 105 528050 4068908 845.7 30.05 3.75 841.95 

ADRS 105 528050 4068908 845.7 69.86 5.5 840.2 

ADRS 105 528050 4068908 845.7 120.02 8.074 837.626 

ADRS 105 528050 4068908 845.7 126.94 11.85 833.85 

ADRS 105 528050 4068908 845.7 83.92 17.39 828.31 

ADRS 105 528050 4068908 845.7 41.83 25.53 820.17 

ADRS 105 528050 4068908 845.7 24.3 37.47 808.23 

ADRS 105 528050 4068908 845.7 20.66 55.01 790.69 

ADRS 105 528050 4068908 845.7 21.43 80.74 764.96 

ADRS 106 528235 4068922 845.7 605.34 0.55 845.15 

ADRS 106 528235 4068922 845.7 381.86 0.81 844.89 

ADRS 106 528235 4068922 845.7 222.86 1.19 844.51 

ADRS 106 528235 4068922 845.7 145.32 1.74 843.96 

ADRS 106 528235 4068922 845.7 117.84 2.55 843.15 

ADRS 106 528235 4068922 845.7 113.23 3.75 841.95 

ADRS 106 528235 4068922 845.7 119.23 5.5 840.2 

ADRS 106 528235 4068922 845.7 122.5 8.074 837.626 

ADRS 106 528235 4068922 845.7 105.14 11.85 833.85 

ADRS 106 528235 4068922 845.7 77.51 17.39 828.31 

ADRS 106 528235 4068922 845.7 59.3 25.53 820.17 

ADRS 106 528235 4068922 845.7 45.07 37.47 808.23 

ADRS 106 528235 4068922 845.7 24.81 55.01 790.69 

ADRS 106 528235 4068922 845.7 17.49 80.74 764.96 

ADRS 107 528520 4069180 845.2 320.06 0.55 844.65 

ADRS 107 528520 4069180 845.2 355.46 0.81 844.39 

ADRS 107 528520 4069180 845.2 354.82 1.19 844.01 

ADRS 107 528520 4069180 845.2 270.42 1.74 843.46 

ADRS 107 528520 4069180 845.2 136.74 2.55 842.65 

ADRS 107 528520 4069180 845.2 52.38 3.75 841.45 

ADRS 107 528520 4069180 845.2 29.17 5.5 839.7 

ADRS 107 528520 4069180 845.2 32.35 8.074 837.126 

ADRS 107 528520 4069180 845.2 39 11.85 833.35 

ADRS 107 528520 4069180 845.2 43.99 17.39 827.81 

ADRS 107 528520 4069180 845.2 51.9 25.53 819.67 

ADRS 107 528520 4069180 845.2 49.77 37.47 807.73 

ADRS 107 528520 4069180 845.2 28.23 55.01 790.19 

ADRS 107 528520 4069180 845.2 14.69 80.74 764.46 

ADRS 107 528520 4069180 845.2 18.21 118.51 726.69 

ADRS 107 528520 4069180 845.2 41.17 173.94 671.26 

ADRS 107 528520 4069180 845.2 86.63 255.31 589.89 

ADRS 107 528520 4069180 845.2 138.13 374.75 470.45 

ADRS 107 528520 4069180 845.2 172.69 550.06 295.14 

ADRS 107 528520 4069180 845.2 200.55 807.37 37.83 

ADRS 108 529293 4070102 877.8 1268.75 1.87 875.93 

ADRS 108 529293 4070102 877.8 346.23 2.75 875.05 
4-44 

ADRS 108 529293 4070102 877.8 158.47 4.04 873.76 

ADRS 108 529293 4070102 877.8 267.72 5.93 871.87 

ADRS 108 529293 4070102 877.8 550.29 8.7 869.1 

ADRS 108 529293 4070102 877.8 848.45 12.77 865.03 

ADRS 108 529293 4070102 877.8 1064.11 18.74 859.06 

ADRS 108 529293 4070102 877.8 1043.64 27.5 850.3 

ADRS 108 529293 4070102 877.8 714.81 40.37 837.43 

ADRS 108 529293 4070102 877.8 337.71 59.25 818.55 

ADRS 108 529293 4070102 877.8 157.32 86.97 790.83 

ADRS 108 529293 4070102 877.8 146.76 127.66 750.14 

ADRS 108 529293 4070102 877.8 143.82 187.37 690.43 

ADRS 108 529293 4070102 877.8 82.77 275.03 602.77 

ADRS 108 529293 4070102 877.8 97.39 403.69 474.11 

ADRS 109 528755 4069464 847.29 119.59 2.06 845.23 

ADRS 109 528755 4069464 847.29 31.18 3.03 844.26 

ADRS 109 528755 4069464 847.29 34.35 4.44 842.85 

ADRS 109 528755 4069464 847.29 71.71 6.52 840.77 

ADRS 109 528755 4069464 847.29 114.42 9.57 837.72 

ADRS 109 528755 4069464 847.29 136.8 14.05 833.24 

ADRS 109 528755 4069464 847.29 126.84 20.63 826.66 

ADRS 109 528755 4069464 847.29 92.17 30.28 817.01 

ADRS 109 528755 4069464 847.29 53.12 44.44 802.85 

ADRS 109 528755 4069464 847.29 23.64 65.23 782.06 

ADRS 109 528755 4069464 847.29 12.82 95.74 751.55 

ADRS 109 528755 4069464 847.29 19.98 140.53 706.76 

ADRS 109 528755 4069464 847.29 55.21 206.27 641.02 

ADRS 109 528755 4069464 847.29 177.33 302.77 544.52 

ADRS 110 526850 4069115 849.3 854.58 0.55 848.75 

ADRS 110 526850 4069115 849.3 752.73 0.81 848.49 

ADRS 110 526850 4069115 849.3 720.28 1.19 848.11 

ADRS 110 526850 4069115 849.3 675.46 1.74 847.56 

ADRS 110 526850 4069115 849.3 420.71 2.55 846.75 

ADRS 110 526850 4069115 849.3 140.34 3.75 845.55 

ADRS 110 526850 4069115 849.3 57.19 5.5 843.8 

ADRS 110 526850 4069115 849.3 63.24 8.074 841.226 

ADRS 110 526850 4069115 849.3 77.96 11.85 837.45 

ADRS 110 526850 4069115 849.3 78.54 17.39 831.91 

ADRS 110 526850 4069115 849.3 72.04 25.53 823.77 

ADRS 110 526850 4069115 849.3 66.94 37.47 811.83 

ADRS 110 526850 4069115 849.3 61.83 55.01 794.29 

ADRS 110 526850 4069115 849.3 49.6 80.74 768.56 

ADRS 111 527219 4068967 847.5 1513.99 0.61 846.89 

ADRS 111 527219 4068967 847.5 425.78 0.9 846.6 

ADRS 111 527219 4068967 847.5 275.63 1.32 846.18 

ADRS 111 527219 4068967 847.5 435.2 1.93 845.57 

ADRS 111 527219 4068967 847.5 438.13 2.84 844.66 

ADRS 111 527219 4068967 847.5 174.03 4.16 843.34 

ADRS 111 527219 4068967 847.5 48.76 6.11 841.39 

ADRS 111 527219 4068967 847.5 39.82 8.97 838.53 

ADRS 111 527219 4068967 847.5 64.48 13.17 834.33 

ADRS 111 527219 4068967 847.5 74.94 19.33 828.17 

ADRS 111 527219 4068967 847.5 51.61 28.37 819.13 

ADRS 111 527219 4068967 847.5 30.6 41.64 805.86 

ADRS 111 527219 4068967 847.5 34.65 61.12 786.38 

ADRS 111 527219 4068967 847.5 47.63 89.71 757.79 

ADRS 112 529660 4068760 847.28 311.93 0.61 846.67 

ADRS 112 529660 4068760 847.28 359.02 0.89 846.39 

ADRS 112 529660 4068760 847.28 291.16 1.3 845.98 

ADRS 112 529660 4068760 847.28 162.74 1.91 845.37 

ADRS 112 529660 4068760 847.28 102.12 2.81 844.47 

ADRS 112 529660 4068760 847.28 117.29 4.13 843.15 
4-45 

ADRS 112 529660 4068760 847.28 172.42 6.06 841.22 

ADRS 112 529660 4068760 847.28 207.88 8.89 838.39 

ADRS 112 529660 4068760 847.28 194.84 13.05 834.23 

ADRS 112 529660 4068760 847.28 148.24 19.15 828.13 

ADRS 112 529660 4068760 847.28 100.74 28.11 819.17 

ADRS 112 529660 4068760 847.28 87.17 41.25 806.03 

ADRS 112 529660 4068760 847.28 126.47 60.55 786.73 

ADRS 112 529660 4068760 847.28 217.17 88.88 758.4 

ADRS 112 529660 4068760 847.28 295.51 130.46 716.82 

ADRS 112 529660 4068760 847.28 286.74 191.49 655.79 

ADRS 112 529660 4068760 847.28 212.06 281.06 566.22 

ADRS 112 529660 4068760 847.28 162.05 412.54 434.74 

ADRS 112 529660 4068760 847.28 181.96 605.53 241.75 

ADRS 113 526840 4068330 845.2 552.1 0.55 844.65 

ADRS 113 526840 4068330 845.2 518.17 0.81 844.39 

ADRS 113 526840 4068330 845.2 514.35 1.19 844.01 

ADRS 113 526840 4068330 845.2 501.75 1.74 843.46 

ADRS 113 526840 4068330 845.2 400 2.55 842.65 

ADRS 113 526840 4068330 845.2 232.36 3.75 841.45 

ADRS 113 526840 4068330 845.2 109.37 5.5 839.7 

ADRS 113 526840 4068330 845.2 64.9 8.074 837.126 

ADRS 113 526840 4068330 845.2 72.27 11.85 833.35 

ADRS 113 526840 4068330 845.2 101.57 17.39 827.81 

ADRS 113 526840 4068330 845.2 107.94 25.53 819.67 

ADRS 113 526840 4068330 845.2 76.67 37.47 807.73 

ADRS 113 526840 4068330 845.2 49.5 55.01 790.19 

ADRS 113 526840 4068330 845.2 44.86 80.74 764.46 

ADRS 113 526840 4068330 845.2 48.43 118.51 726.69 

ADRS 113 526840 4068330 845.2 43.24 173.94 671.26 

ADRS 113 526840 4068330 845.2 34.83 255.31 589.89 

ADRS 113 526840 4068330 845.2 31.56 374.75 470.45 

ADRS 113 526840 4068330 845.2 36.15 550.06 295.14 

ADRS 113 526840 4068330 845.2 57.33 807.37 37.83 

ADRS 114 527649 4069521 849.8 685.06 0.44 849.36 

ADRS 114 527649 4069521 849.8 679.46 0.65 849.15 

ADRS 114 527649 4069521 849.8 645.62 0.96 848.84 

ADRS 114 527649 4069521 849.8 437.54 1.41 848.39 

ADRS 114 527649 4069521 849.8 169.78 2.06 847.74 

ADRS 114 527649 4069521 849.8 58.91 3.03 846.77 

ADRS 114 527649 4069521 849.8 47.9 4.44 845.36 

ADRS 114 527649 4069521 849.8 65.44 6.52 843.28 

ADRS 114 527649 4069521 849.8 87.81 9.57 840.23 

ADRS 114 527649 4069521 849.8 102.76 14.05 835.75 

ADRS 114 527649 4069521 849.8 106.46 20.63 829.17 

ADRS 114 527649 4069521 849.8 100.25 30.28 819.52 

ADRS 114 527649 4069521 849.8 75.85 44.44 805.36 

ADRS 114 527649 4069521 849.8 35 65.23 784.57 

ADRS 114 527649 4069521 849.8 12.07 95.74 754.06 

ADRS 114 527649 4069521 849.8 9.46 140.53 709.27 

ADRS 114 527649 4069521 849.8 16.19 206.27 643.53 

ADRS 114 527649 4069521 849.8 36.31 302.77 547.03 

ADRS 115 528000 4069690 847.6 554.22 0.66 846.94 

ADRS 115 528000 4069690 847.6 552.13 0.97 846.63 

ADRS 115 528000 4069690 847.6 523.24 1.42 846.18 

ADRS 115 528000 4069690 847.6 421.63 2.08 845.52 

ADRS 115 528000 4069690 847.6 241.46 3.06 844.54 

ADRS 115 528000 4069690 847.6 89.91 4.49 843.11 

ADRS 115 528000 4069690 847.6 40.64 6.58 841.02 

ADRS 115 528000 4069690 847.6 43.25 9.66 837.94 

ADRS 115 528000 4069690 847.6 54.54 14.18 833.42 

ADRS 115 528000 4069690 847.6 58.38 20.82 826.78 
4-46 

ADRS 115 528000 4069690 847.6 55.66 30.56 817.04 

ADRS 115 528000 4069690 847.6 51.18 44.85 802.75 

ADRS 115 528000 4069690 847.6 42.23 65.84 781.76 

ADRS 115 528000 4069690 847.6 24.22 96.64 750.96 

ADRS 115 528000 4069690 847.6 10.46 141.84 705.76 

ADRS 115 528000 4069690 847.6 9.98 208.19 639.41 

ADRS 115 528000 4069690 847.6 25.71 305.59 542.01 

ADRS 115 528000 4069690 847.6 91.02 448.54 399.06 

ADRS 116 529143 4069201 847.28 155.37 0.44 846.84 

ADRS 116 529143 4069201 847.28 155.76 0.65 846.63 

ADRS 116 529143 4069201 847.28 112.64 0.96 846.32 

ADRS 116 529143 4069201 847.28 82.27 1.41 845.87 

ADRS 116 529143 4069201 847.28 84.69 2.06 845.22 

ADRS 116 529143 4069201 847.28 98.96 3.03 844.25 

ADRS 116 529143 4069201 847.28 114.52 4.44 842.84 

ADRS 116 529143 4069201 847.28 134.11 6.52 840.76 

ADRS 116 529143 4069201 847.28 143.48 9.57 837.71 

ADRS 116 529143 4069201 847.28 132.12 14.05 833.23 

ADRS 116 529143 4069201 847.28 105.49 20.63 826.65 

ADRS 116 529143 4069201 847.28 67.61 30.28 817 

ADRS 116 529143 4069201 847.28 39.28 44.44 802.84 

ADRS 116 529143 4069201 847.28 28.82 65.23 782.05 

ADRS 116 529143 4069201 847.28 25.53 95.74 751.54 

ADRS 116 529143 4069201 847.28 32.72 140.53 706.75 

ADRS 116 529143 4069201 847.28 62.52 206.27 641.01 

ADRS 116 529143 4069201 847.28 137.52 302.77 544.51 
4-47 

Appendix 4-B 

Appendix 4-B. Available Monitoring Well Information 

UTM 

X UTM Y Elev. (ft) 

Elev. 

(m) 

Screened 

Interval 

(Top 

BGS) 

Screened 

Interval 

Bottom 

BGS) 

Depth 

to 

Water 

BGS 

Water 

Surface 

Altitude 

in 

Meters 

Well 

Bottom 

Altitude 

in 

Meters 

Water 

Surface 

Altitude 

in 

Meters 

(May 

'04) 

Tritium 

in units 

Tritium 

in 

pCi/L 

527375 4068715 2776.892 846.5 111 123 112.2 734.3 723.4 734.3 3.8 12.16 

527550 4069125 2782.141 848.1 759.9 744.3 

527425 4068780 2776.236 846.3 dry 737.9 736.9 

527875 4068790 2771.644 844.9 N/A N/A 

528025 4068980 2775.908 846.2 N/A N/A 

528030 4069050 2778.205 846.9 N/A N/A 

527910 4068950 2775.908 846.2 N/A N/A 

528070 4068950 2772.3 845.1 752.5 746.5 

528040 4068780 2769.347 844.2 751.5 745.4 

528075 4069080 2778.205 846.9 759.9 755 

527820 4068780 2771.972 845 91 98 93 752 745.9 751.6 0.05 0.16 

527680 4068980 2776.564 846.4 760.2 755.3 

527610 4069300 2785.422 849.1 86 92 87.8 761.3 755.2 0.4 1.28 

527695 4068880 2776.564 846.4 90 96 92.4 754 748.5 0.9 2.88 

527750 4068725 2772.628 845.2 92 98 93.3 751.9 745.8 0.6 1.92 

528040 4068870 2775.908 846.2 85 91 89 757.2 753.1 0.7 2.24 

527925 4068780 2770.66 844.6 751.3 745.3 751 

527605 4068950 2774.596 845.8 91 173 85.3 N/A N/A 760.5 0.4 1.28 

527615 4069300 2785.422 849.1 141 144 93.3 N/A N/A 0.05 0.16 

527820 4068730 2774.924 845.9 126 130 99.4 N/A N/A 0.05 0.16 

527285 4068950 2781.485 847.9 104 112 105.2 0.2 0.64 

527336 4068713 2776.892 846.5 N/A N/A 109.7 736.8 
5-1 

5 Rocky Flats Facility 

5.1 Introduction 

The Rocky Flats Facility was selected to test the applicability of the AES Advanced 

Environmental Solutions, LLC (AES) Strategy to a semi-arid environment in the 

Midwestern United States. This exercise is for demonstration only. This report is based 

on readily available information and does not constitute a comprehensive evaluation of 

all data for the site. 

The Rocky Flats Facility, a former nuclear weapons facility, is located west of Denver, 

Colorado in an area of complex terrain (Figure 5-1) (DOE, 2005). A primary mission of 

the Rocky Flats facility was to machine plutonium “buttons” into weapons components. 

Figure 5-2 presents an aerial view of the Rocky Flats Facility looking east in 1983, prior 

to decommissioning. 

In this exercise, the AES Strategy is applied in two separate case studies at Rocky Flats, 

both of which focus on ground water contaminated by chlorinated organic solvents. In 

each instance, application of the Strategy yields improved understanding about the 

natural system at the site. 
5-2 

Figure 5-1. Location of the Rocky Flats Facility in Colorado (DOE, 2005) 
5-3 

Figure 5-2. Photograph of the Rocky Flats Facility (looking east) Photo is in “Linking Legacies”, 

DOE publication EM-0319 (DOE 1997) Appendix B, page 190. 

5.2 Compilation of Available Data 

This section provides a summary of the readily available data compiled for evaluation of 

both VOC case studies. 

5.3 Geologic Setting 

The Rocky Flats Facility sits approximately 6,000 feet above mean sea level on the 

western margin of the Colorado Piedmont section of the Great Plains Physiographic 

Province. The Colorado Piedmont is an old erosional surface along the eastern margin of 

the Rocky Mountains underlain by gently dipping sedimentary rocks (Paleozoic to 

Cenozoic in age) which are abruptly upturned at the Front Range (just west of the Rocky 

Flats Facility) to form hogback ridges parallel to the mountain front. The Piedmont 

surface is broadly rolling and slopes gently to the east with topographic relief of only 

several hundred feet. This relief is due both to resistant bedrock units that locally rise 

above the landscape and to the presence of incised stream valleys (DOE, 1990).
5-4 

5.3.1 Hydrologic Data 

Hydrogeology at the Rocky Flats Facility is characterized by three distinct units, the 

upper alluvial aquifer, lower aquitard, and the Laramie-Fox Hills aquifer. 

The upper alluvial aquifer is largely unconsolidated materials that can be as much as 100 

feet thick in the western portions of the site. The upper aquifer is generally recharged 

from precipitation or surface water bodies. Ground water in the unconsolidated alluvial 

aquifer is generally close to the land surface, with an average depth of 11 feet below 

ground surface. Several springs emerge in areas where the contact of the upper aquifer 

and the lower aquitard is exposed at the surface. While most of these springs occur within 

the Rock Creek drainage, Antelope Springs in the Woman Creek drainage has the largest 

discharge at Rocky Flats (Figure 5-3). Antelope Springs discharges continuously over 

several acres. The upper alluvial aquifer has a permeability of approximately 0.5 meters 

per day. 

The lower aquitard comprises deeper claystone and siltstone of the Laramie and 

Arapahoe Formations. These formations combined are up to 800 feet thick below Rocky 

Flats. Recharge of the lower aquitard occurs from downward flow through the upper 

aquifer, or directly through precipitation in areas where the bedrock is exposed. 

Beneath the aquitard lies the regional Laramie-Fox Hills aquifer. It is composed of the 

lower sandstone unit of the Laramie Formation and the Fox Hills Sandstone, and is 

confined by the overlying aquitard. Ground water levels in the bedrock aquifers are 

generally greater than 100 feet. Several portions of the upper alluvial aquifer east and 

northeast of the Industrial Area are known or suspected of being contaminated with 

radionuclides, volatile organic compounds, and metals. The aquitard is less contaminated 

than the upper alluvial aquifer. No contaminant plumes have been identified in the 

aquitard (ERO Resources, 2003). 

Liquid contaminants spilled on the ground and certain substances that dissolve in water 

can easily move down through the soil and contaminate the shallow ground water. Data 

from on-site monitoring wells at Rocky Flats show areas of ground water contaminated 

with elevated radioactivity, nitrates, and volatile organic compounds at different locations 

(CDPHE, (No Date)). Figure 5-4 shows the location of monitoring wells and the extent 

of nitrate plumes and VOC plumes at or above maximum contaminant levels. 
5-5 

Figure 5-3. Map of Rocky Flats Facility drainage basins (from: 

http://lanl.gov/source/orgs/nmt/nmtdo/AQarchive/06springsummer/page5.shtml) 
5-6 

Figure 5-4. Ground-water monitoring well locations and depiction of VOC and nitrate plumes for 

the Rocky Flats Facility (CDPHE, (No Date))

5.4 Application of the Strategy 

5.4.1 Case Study 1: Conceptual Site Model Assessment 

Figure 5-5 presents a Transport Conceptual Model for the Rocky Flats Facility that was 

located during compilation of existing site data. This conceptual model illustrates a 

pathway from ground to surface water. Specifically, it shows the majority of 

contaminant movement within the upper alluvial aquifer. According to this model, 

surface water VOC concentrations are typically higher during the winter months when 

volatilization is reduced by low temperatures and ice covering the surface water. Risk to 

wildlife or wildlife workers through a surface water pathway has been a driving concern 

in Rocky Flats remediation efforts. 
5-7 

Figure 5-5. Conceptual cross-section for the Rocky Flats Facility (Modified from K-H, 2004) 

5.4.2 Case 1: Existing Site Monitoring Data 

Figure 5-6, below shows carbon tetrachloride concentrations in Well 3991 between 1992 

and 2003. Water levels are shown as depth to ground water in feet. Between 1992 and 

1995, carbon tetrachloride concentration declines in this well by a factor of 10, to below 

0.005 mg/l (<5ppb). However, the fourth quarter 1995 sampling result indicates the 

concentration increases to over 50 ppb. Subsequently, concentrations decline, only to 

peak again in 1999, then steadily decline for 5 years to the end of our data set. 

5.4.3 Case 1: Application of the Strategy 

One possible hypothesis to explain the carbon tetrachloride concentration spikes observed 

in the existing monitoring data would include periodic releases or spills at the site; 

however, inclusion of Well 3991 water level data in a conceptual site model (Figure 5-6 

and Figure 5-7) suggests that the concentration spikes are correlated to high water levels. 

Specifically, concentration spikes were seen immediately following well water levels 

between 6 to 10 feet above normal for the well. 
5-8 

Figure 5-6. Diagram of multiyear variability in ground-water contaminant concentrations due to 

water table changes (K-H, 2004) 

monitor

well 

weathered 

bedrock 

(low K) 

alluvium

(high K)

Figure 5-7. Conceptual cross section showing affects of water table changes on contaminant 

movement (modified from K-H, 2004) 

Figure 5-7 shows the revised conceptual model which explains the observed spikes in 

carbon tetrachloride concentrations. This model illustrates how contamination from 

disposal trenches migrates through the vadose zone and collects at the interface between 

the higher permeability alluvium and the lower permeability weathered bedrock. The 

water table is typically in the weathered bedrock, but during periods of very high 

recharge it can rise into the high permeability alluvium and mobilize contamination 

3991

0.0001

0.001

0.01

0.1

1/1/1991 1/1/1996 1/1/2001

mg/L

24

26

28

30

32

34

36

38

depth to water [ft]

CCl4 WL

Well #
5-9 

pooled at the bedrock interface, and subsequently mobilize into the weathered bedrock 

aquifer. The normal water table is indicated by a solid blue line. In a period of heavy 

rain fall or snow melt, water levels rise into the alluvium (dashed blue line) and mobilize 

vadose zone contamination. This results in a concentration spike followed by a slow 

decline as the displaced solvent dissipates. 

It is most important to note that the declining concentrations at the monitoring well 

provide no information on the possible decline of the source pool. It is also important to 

note that a 3-year steep decline ending with four quarters of low concentrations might be 

used to argue that this well could be removed from a contaminant monitoring program. 

Look again at the first 12 concentrations in Figure 5-5 then look at the first 15 

concentrations. Now look at the last several years - when can we stop sampling this 

well? 

This well provides important information on the performance of the hydrologic system at 

this site: these spikes infer that a relatively higher concentration up gradient source is 

present and that water table information is a strong performance indicator. 

It is important to recognize that this well is placed in a critical point to monitor system 

performance. We now have a model to relate observations at a well to the source and an 

indication that the system performance suggests that a high-concentration zone exists in 

the ground – but this model is not sufficient to model the extent of the plume. 

Management (DOE, state agencies, EPA, and other stakeholders) can decide whether 

long-term risk justifies an attempt to characterize and remove most of the source. 

In addition to the natural variations in the water table, long term recharge changes due to 

facility closure need to be considered. Elimination of features such as drains, leaking 

water lines, and covered areas such as asphalt parking lots can affect the water table 

recharge (Figure 5-8). By eliminating these features the shape of the water table surface 

may be altered dramatically. In a 40-plus-year old facility of this size water system leaks 

on the order of tens of gallons per minute could be expected. This would be a major 

fraction of the local infiltration.
5-10 

Figure 5-8. Potential changes in ground-water movement due to closure 

Figure 5-9 shows predicted water level changes after site closure. Comparison of this 

Figure with VOC plume and source maps presented below shows the possibility of 

gradient changes in the vicinity of the VOC sources. This prediction was made with 

MIKE SHE, a modeling code that can incorporate both subsurface and subsurface flow 

(K-H, 2004). 

Infiltration changes upon site closure require that any flow and transport models that are 

relied upon to justify environmental management decisions should be re-evaluated. Once 

again, it is a management decision to do this re-evaluation, but very simple models can be 

constructed to enlighten discussions surrounding the decision. These models would also 

include changes in surface water runoff. 
5-11 

Figure 5-9. Predicted water level changes after closure (K-H, 2004) Note: Positive numbers denote areas where simulated groundwater depths increase from current (WY2000) conditions.

Negative numbers denote areas wehere simulated groundwater depths decrease from current (WY2000) conditionsA

Figure 4.7. Simulated Change in Average Annual Groundwater Levels from Current Conditions (m).

ll areas within the model, with no color, 

represent areas where simulated groundwater levels change less than 0.5 meters.
5-12 

5.4.4 Case 2: VOC Plume Analysis 

The majority of VOC ground-water contamination at the Rock Flats Facility consists of 

chlorinated solvents including tetrachloroethylene (PCE) and trichloroethylene (TCE), 

with minor amounts of dichloroethylene (DCE). Identification of the original 

contamination can often be difficult as the chlorinated solvents break down readily to a 

less chlorinated state (e.g., PCE to TCE to DCE to Vinyl Chloride). 

Results of ground-water monitoring at the Rocky Flats Facility show a significant TCE 

plume emanating from the eastern portion of the site. The initial conceptual model has 

historically been interpreted to be one plume with complex movement of ground water 

creating a radial dispersion pattern. Figure 5-10 shows the general extent of the TCE 

plume assuming a single plume. This figure is taken directly from a talk and not edited. 

RFETS, May 06 ` 2

Area of TCE contamination

mapped as a single plume TCE

Figure 5-10. Generalized depiction of the Rocky Flats Facility TCE plume 

5.4.5 Case 2: Application of the Strategy 

By understanding the nature of the original spills and by evaluating the presence of 

daughter products from the degradation of chlorinated solvents, a revised conceptual 

model can be prepared. 

Also, by associating sources and plumes with ground-water flow fields, it may be 

possible to differentiate multiple overlapping plumes. Discriminators such as probable 

source locations, variable ground-water flow paths, and potential daughter product 
5-13 

distributions can be used to prepare a refined conceptual model for contaminant 

movement. 

Multiple sources will likely result in multiple plumes with unique fingerprints. Figure 

5-11 presents an alternative conceptual model of contaminant plume source and 

migration based on additional information provide below. Further evaluation of groundwater monitoring data indicates that an east-west ground-water divide is present, 

effectively splitting the southern one-third of the plume from the northern two-thirds of 

the plume. By dividing the plumes based on the ground-water flow information above, it 

appears two plumes may be present, straddling the ground-water divide. In addition, an 

evaluation of the concentrations of all chlorinated solvents is undertaken as part of this 

Strategy application. Near the source the two plumes commingle, making differentiation 

difficult. Under reducing conditions, aquifer microorganisms can reductively 

dechlorinate PCE into less chlorinated daughter products such as TCE, DCE and vinyl 

chloride. By evaluating the relative concentrations of these contaminants, the separate 

plumes may be identified. 

In Figure 5-11, the northern plume contains higher concentrations of PCE than TCE, 

suggesting that the TCE is derived from PCE degradation. In the southern plume TCE is 

present in much higher concentrations than PCE, suggesting that the original spill 

consisted mostly of TCE with minor amounts of PCE, or as an alternative conceptual 

model, that a much higher degree of anaerobic degradation is occurring in the southern 

plume, effectively eliminating the presence of the original PCE spill. However, in Figure 

5-10, the southern plume moves down the hill side towards Woman Creek and likely 

represents more of an aerobic environment, thus minimizing the potential for degradation 

of chlorinated solvents. Based on the information provided in Figure 5-10, TCE is 

pervasive in both overlapping plumes; however, the use of PCE as a discriminator or 

performance indicator has resulted in a refined conceptual model of contaminant 

movement showing two separate plumes with two separate sources (Figure 5-11). If two 

sources were not originally identified in this area, this conceptual model would prompt 

the need to evaluate the potential presence of a previously unidentified spill. 
5-14 

Use probable source locations, groundwater flow paths, and 

daughter product distribution to delineate plumes

RFETS, May 06 ` 4

PCE

TCE

Refine conceptual model

Associate sources and concentration distribution within the 

GW flow field

2 probable sources result in 2 separate plumes

Higher concentration of PCE than TCE in northern plume 

suggest TCE derived from PCE degradation (though TCE 

possibly also released)

High TCE and very low PCE concentrations in the southern 

plume suggest significant TCE released along with PCE

Alternative conceptual model would be much higher 

degradation of PCE in southern plume to produce TCE, 

though southern plume conditions should be more aerobic 

along hill-side (less favorable to PCE degradation) 

Associate Source and Plume within GW flow field

Figure 5-11. Conceptual model of complex flow of contaminants 

5.4.6 Performance Indicators and FEPs 

Performance indicators and features, events, or processes (FEPs) for the Rocky Flats 

Facility include, but are not limited to: 

1) monitor water levels- changes in the water table surface or orientation will affect 

the direction of ground-water flow and the potential for remobilization of 

contaminants from the vadose Zone into the aquifer. 

2) time trends for ground-water contamination – by looking at the relative 

concentration of contaminants over time, especially in comparison to water level 

readings, informed decisions can be made on when monitoring efforts can be 

terminated. 

3) monitor all VOC daughter products for the VOC plumes- because the 

fingerprints of various VOC plumes may define multiple sources, determining the 

relative proportions of VOCs that make up a given plume is critical 
5-15 

5.5 Monitoring Strategy Application Conclusions 

Based on the results of the application of the Strategy, the following conclusions can be 

drawn: 

Case 1: Episodic changes in the water table result in the periodic remobilization of 

contaminants from the vadose zone, most likely at the alluvium/bedrock interface, into 

the ground water. By evaluating all of the available ground-water monitoring data 

through time trend analysis, it becomes apparent that the duration of Post-Closure 

ground-water monitoring may need to be extended or further characterization of the 

contamination within the vadose zone may need to be undertaken due to the cyclic 

recontamination of the water table. 

Case 2: A VOC plume is emanating from the southeast corner of the Rocky Flats 

Facility. By evaluating the analytical results for chlorinated solvent daughter products 

together with likely flow directions, it becomes apparent that a revised Conceptual Site 

Model can be proposed with multiple sources contributing to the ground-water 

contamination. By examining the relative concentrations of all of the chlorinated 

solvents, individual plume fingerprints can be identified for the differentiating multiple 

sources. 

Based on the results of the application of the Strategy, the following recommendations to 

management can be made: 

1. Perform detailed time trend analysis for monitoring wells in relation to changes in 

the water table. In addition to the natural variations in the water table, long term 

recharge changes due to facility closure need to be considered due to the potential 

for remobilization of contaminants and changes in the water table surface. In 

addition, changes in the water table may result in the remobilization of 

contaminants from the vadose zone. 

2. Evaluate the relative concentrations of contaminants to daughter products for 

revising plume delineation and sources. 
5-16 

5.6 Rocky Flats References 

Colorado Department of Public Health and Environment (CDPHE). Rocky Flats Public 

Exposure Studies, Movement of Contaminated Groundwater at the Rocky Flats 

Environmental Technology Site. (Available online at 

www.cdphe.state.co.us/rf/movement.htm) 

Department of Energy (DOE). Interim Measures/Interim Remedial Action and Decision 

Document, 881 Hillside Area Operable Unit No. 1, Rocky Flats Plant. January 

1990. 

DOE/EM-0319. Linking Legacies, Connecting the Cold War Nuclear Weapons 

Production Processes to Their Environmental Consequences. 1997. 

ERO Resources Corporation. Rocky Flats National Wildlife Refuge Resource Inventory. 

April 2003. 

K-H. Fate and Transport Modeling of Volatile Organic Compounds. Kaiser-Hill 

Company L.L.C., Rocky Flats Environmental Technology Site: Golden, Colorado. 

April 2004. 
6-1 

6 Savannah River Site, C Area 

6.1 Introduction 

The Savannah River Site (SRS) has a fifty-plus year history of defense nuclear research, 

fuel fabrication, chemical separations and waste disposal. The site covers about 300 

square miles in South Carolina, along the Savannah River, about 100 miles upstream of 

the Atlantic Ocean (Figure 6-1). SRS includes 5 production reactors (Reactors C, K, L, 

P, R), a research lab, fuel fabrication, two chemical separation plants, and supporting and 

waste management facilities. Further description of this site and its history of operation 

are available in Linking Legacies, DOE publication EM-0319 (DOE 1997). 

DOE has been generous in allowing access to documents and data from the Site’s 

extensive environmental characterization and monitoring work. 

Savannah River Site Savannah River Site

South Carolina South Carolina

Atlantic Ocean

Georgia Georgia SRS

C Area

Figure 6-1. Savannah River Site location map. Courtesy of Bill Jones, SRNL.

This Chapter will use the C-Area of SRS to illustrate some results of contaminant plume 

characterization and monitoring. C-Reactor operated from 1955 through 1986, with 

construction beginning in about 1951. Within the reactor building is the disassembly 

basin, similar to a spent fuel pool in a power reactor. External to the reactor building are 

several waste facilities including reactor seepage basins (CRSB) to receive acids and 

caustics, low level radioactive solutions resulting primarily from maintenance, and a pit 

(CBRP) for burning waste and disposing of rubble that could include scrap wood, 

pasteboard, paint, and solvents. A photograph of the A-Area burning and rubble pit 

(ABRP) is shown in Figure 6-2 as an example. 
6-2 

Figure 6-2. Photograph of the A Area Burning/Rubble Pit during operation 

In this Chapter we will look at a TCE plume from the CBRP and, to a lesser extent, a 

tritium plume from the CRSB. Even though the site is intensely characterized and 

monitored, we will show the value of computer simulation and 3-D visualization to 

evaluate the existing site data and present support for management decisions concerning 

the value of further monitoring or characterization. Further, we will show the importance 

of considering all sources of characterization data before using a computer simulation to 

support conclusions about the long-term disposition of a site. 

Figure 6-3 is a map of C-Area. The reactor building (105-C), including the disassembly 

basin, CBRP, and three small seepage basins are shown. Wells from which monitoring 

data are obtained are also shown (e.g., P-18, CCB-1, and CSB-3A). This figure is from 

WSRC, 1998, an inventory of SRS environmental protection wells; similar documents 

are available online at www.osti.gov with authors Janssen or Rogers. 

The wells LWR-1 through -9 were installed in 1992 as part of site characterization for a 

planned landfill (WSRC, 1992). They are not part of the Environmental Protection 

Department’s waste site monitoring program, and we have found no monitoring data for 

them. 
6-3 

Figure 6-3. Map of C Area with facilities and wells (WSRC, 1998) 

6.2 Compilation of Available Data 

6.3 C-Area Background 

DOE/EM-0319 (DOE, 1997), traces the history of the U.S. nuclear program from the 

early 1940s through 1997. Many details of reactor operations are provided in this 

document. While the discussions are not specific to C-reactor, the background provides 

information on chemicals used, processes, accidents, and environmental restoration 

activities. It is available at www.em.doe.gov/publications. At this time it is not available 

through OSTI. 
6-4 

WSRC-TR-99-00310 (Flach et al., 1999), published in 1999, is a modeling report 

covering the C-Area. Overall this is an excellent report that details data gathering, data 

visualization, and flow and transport modeling. It is available in pdf format online at 

www.osti.gov and contains more detailed information on C-Area and C-reactor history and 

operations than are included here. We have relied on it for data and figures in this 

chapter. We do, however, point to some opportunities for alternative conceptual models 

that might change some the model results. 

6.3.1 Geology and Hydrogeology 

The Savannah River Site is situated on multi-layer, interbedded, discontinuous Coastal 

Plain sediments that regionally dip to the SSE at about 20 ft/mile. The sediments are 

predominantly sands and clays deposited in fluvial to near-shore marine environments. 

The hydrology at C-Area is a classic unconfined, semi-confined, and confined aquifer 

sequence with the semi-confined aquifer becoming unconfined as it nears Four Mile 

Creek. High permeability pathways that affect transport can be present due to channels, 

gravel layers, and fractures. 

Figure 6-4 shows a cross-section developed near C-Area at the MWD well field, an 

extensively characterized area. This area served as a field hydrogeology teaching and 

research site. Results of a number of aquifer performance tests, and other measurements 

of hydrologic properties are available from this site (e.g., Kegley et al., 1994). Site 

stratigraphy has been described by Fallaw et al., 1993. 
6-5 

Cross Section – MWD well field (based on well and outcrop data)

(for conceptual model and numerical model mesh—used with Petra)

(10 km northwest along strike)

C-Area, SRS, 11/30/05 18

Figure 6-4. Simplified hydrogeologic cross section near C Area (Kegley et al., 1994). Courtesy of 

W.P. Kegley. 

6.3.2 Site Characterization and Monitoring 

In the late 1960s through about 1985, SRS planned and installed a site-wide network of 

hydrologic characterization wells, called the P-wells. The deepest well in each cluster 

was cored and logged, and piezometer wells were screened in permeable zones. Water 

level measurements, cores, and logs were produced in various programs dating back to 

pre-construction characterization in the late 1940s and 1950s (Siple, 1967). 

Beginning in about 1981, extensive characterization was done in response to new 

environmental regulations. In about 1983 a core logging program was set up, and policies 

were instituted to core and log wells at most waste disposal sites. Data from the coring 

and logging programs were captured digitally. There were several plume characterization 

and mitigation programs, resulting in a wealth of subsurface data for the SRS. 

C-Area in this report includes about 200 wells and is outlined on the map present in 

Figure 6-5. The left (western) boundary of this map is Four Mile Creek. A number of 

wells northwest of the reactor area were installed to characterize a proposed landfill site. 

The landfill would have been in the area north of the TCE plume. (WSRC, 1992) 

More recently, a large number of direct push or cone penetrometer samples were taken to 

characterize both the TCE and tritium plumes. 
6-6 

6.3.3 Contaminant Distribution 

As noted, two contaminant plumes have been described at C Area. A trichloroethene 

(TCE) plume migrates to the west from the C-Area burning rubble pit to Four Mile 

Creek. The plume is delineated by an extensive monitor network of over 150 wells or 

CPT samples, though no wells reach the confined aquifer beneath the plume extent (to 

avoid downward transport during and after well installation). 

A tritium plume migrates southwest from the C-Area seepage basin to Four Mile Creek 

and Caster Creek. The tritium distribution (originally identified in the monitor wells) was 

delineated by over 200 cone penetrometer (CPT) pushes (1998-2001). Transport 

modeling by DOE’s operating contractor, WSRC, (Flach, et al., 1999) was used to predict 

future plume migration and to suggest additional CPT locations. We have chosen not to 

discuss the tritium plume further for this report draft. Our initial reaction to the published 

modeling is that more characterization is needed to understand why the tritium enters two 

surface streams. 

Modeling was also done to evaluate remediation options for the TCE plume (Geotrans, 

2001). This modeling was very limited in scope. 

The CBRP sits at the head of the TCE plume as shown in Figure 6-5. The tritium plume 

has some associated TCE, and emanates from the cluster of TCE “hits” just SW of the 

reactor building (105-C), which is the irregular shaped dark spot on this Figure. 

Figure 6-5. Topographic map of C-Area facility boundary with TCE plume and detected TCE 

concentrations 

CBRP 

105-C 

Four Mile 

Creek 
6-7 

Figure 6-6 shows locations of wells sampled for tritium and Figure 6-7 shows locations 

of wells and CPTs sampled for TCE. CPT locations and analytical data are from Flach et 

al., 1999. Note that there are a very few sampling locations outside the model 

boundaries. These are single-event sampling sites, and not monitoring wells. At the time 

of sampling, no TCE was detected west of Four Mile Creek. 

Average tritium concentration (well and CPT data)

C-Area, SRS, May 06 48

Figure 6-6. C Area tritium CPT data 
6-8 

Average TCE concentration (well and CPT data)

Figure 6-7. C Area TCE CPT data 

6.4 Synthesis of a Conceptual Site Model and Flow and 

Transport Simulations 

By combining the geologic cross-section in Figure 6-4 with log and core data gathered 

through past characterization efforts in the C-Area wells, we developed a 7-layer site 

hydrologic conceptual model for flow and transport simulation. This conceptualization is 

shown in Figure 6-8. In the paragraphs below, we present simulations performed using 

the conceptual model in Figure 6-8 and discuss potential Performance Indicators and 

monitoring strategies which were identified through analysis of this modeling exercise. 

Simulation layer parameters were adapted from Flach et al. (1999) and Geotrans (2001) 

and are shown in Table 6-1 below. 
6-9 

C Area Model Mesh

Layer 1 – unconfined

Layer 2 – unconfined

Layer 3 – unconfined

Layer 4 – tan clay

Layer 6 – green clay

Layer 5 – semi-confined

Layer 7 – Gordon (confined)

Figure 6-8. C Area hydrologic Conceptual Site Model 

Table 6-1. Hydrologic layer parameters (adapted from Flach et al. (1999) and Geotrans (2001)) 

Layer Name K-horiz (m/d) Kh/Kv Porosity 

1 Sand 10 3 0.25 

2 Clay 0.01 50 0.35 

3 Unconfined aquifer 3 3 0.25 

4 Tan Clay 0.02 50 0.35 

5 Semi-confined aquifer 2 3 0.25 

6 Gordon confining unit (Green clay) 0.002 100 0.35 

7 Gordon aquifer 8 3 0.25 

Both the Conceptual Site Model (Figure 6-8) and the flow and transport modeling 

discussed below (Figure 6-9 - Figure 6-12) were prepared with GMS, a modeling 

package developed with NRC, EPA, DOE, and DoD support that incorporates several 

modeling codes such as ModFlow, MT3D, and RT3D. We have found that GMS has 

limited ability to incorporate well logs, so we developed conceptual geologic and 

hydrogeologic models with Petra, or Rockworks. 

Transport modeling (with RT3D) was performed to simulate the TCE distribution and to 

determine if TCE could affect the confined Gordon aquifer. 
6-10 

•Simulated transport at CBRP

layer 3 (unconfined)

1951-2005 constant 

10 mg/L TCE source 

2005

1961

2050

C-Area, SRS, 11/30/05 25

Figure 6-9. C Area simulated transport model for Layer 3 from the CBRP 

•Simulated transport at CBRP

layer 7 (confined)

1951-2005 constant 

10 mg/L TCE source

2005

1961

2050

“green clay” confining unit

Kh = 0.002 m/d

Kv = 0.00002 m/d

C-Area, SRS, 11/30/05 26

Figure 6-10. C Area simulated transport model for Layer 7 from the CBRP 
6-11 

Hill-Slope section, C Area, SRS

CBRP

TCE plume

CBRP

C-Area, SRS, May 06 33

Gordon Aquifer

Fourmile

Branch

UT Runs

W E

Figure 6-11. Cross section of C Area hydrogeologic conceptual model. The Gordon confining unit 

(green clay) is shown as a green band above the Gordon aquifer. Fourmile Branch is correctly called 

Four Mile Creek elsewhere in this document. 

6.5 Data Visualization 

Three-dimensional visualization provides a powerful tool to present data. For example, 

in our 7-layer conceptual model of C-Area hydrogeology, we have used a program called 

3-D Analyst, part of ArcGIS, to display all the TCE analyses available for layer 7, also 

called The Gordon aquifer. 

As shown in the cross-section of Figure 6-11, contamination in the shallower layers, 

those above the “green clay,” (also referred to as Layer 6 in Figure 6-8 and the Gordon 

confining unit in Figure 6-13) should discharge to the surface at Four Mile Creek, but any 

contamination reaching layer 7 will leave the area of our model heading west. 

Figure 6-12 presents a three-dimensional perspective of C Area, looking to the northeast 

and upward from below Layer 6 – the Gordon confining unit (Green Clay). CPT ground 

water sampling intervals above the layer 6- Gordon confining unit are represented by dim 

points. The three CPTs within the plume were pushed in 1999 and indicate TCE levels 

below detection limits (blue dots indicate non-detect). The plume outline as defined by 

data from the unconfined and semi-confined layers (layers 1-5), is shown as a black 

curtain hanging down from the surface. The four CPT samples taken north of the plume 

were pushed in 2000-2001 and indicate extremely low levels of TCE (white dots indicate 

low detection levels). 
6-12 

The three CPT samples (non-detect, blue) left of Four Mile Creek (shown as a blue 

“curtain” extruded down from the surface) were pushed in 2001. These 10-12 CPTs are 

all that sampled the Gordon aquifer near the TCE plume and none of the CPTs go very 

deep into the Gordon aquifer. The Gordon aquifer was sampled but is not being routinely 

monitored. 

Figure 6-12. Looking from beneath the Gordon confining unit to the NE towards the plume (All dim 

points are above the Gordon confining unit). 

Transport modeling discussed above suggested low levels of dissolved TCE could seep 

through the Layer 6 (Gordon confining unit) into the Gordon aquifer and travel beyond 

Four Mile Creek at some time in the future, perhaps by 2010-2020. 

6.6 Alternative Conceptual Models 

Both the flow and transport models referenced in previous characterization exercises and 

the flow and transport model produced by AES for this exercise show Layer 6 (also 

called the “green clay” or “Gordon confining unit) to be laterally continuous and uniform. 

However, limited information from a group of wells installed in 1992 to characterize a 
6-13 

possible new landfill site near C-Area suggests an alternative conceptual model for the 

green clay unit (Layer 6) may exist. 

These wells (designated as LWR-1 through LWR-9) are not part of the environmental 

monitoring program for SRS. No analytical data for these wells exist in the SRS 

monitoring database – it appears that they have never been sampled. 

The well installation report is available as WSRC-RP-92-1316, hereinafter “LWR 

report.” This report was not referenced in existing modeling reports prepared previous to 

our investigation. 

Figure 6-13 is from the LWR report. Its authors interpret data from these wells to 

indicate faulting of the green clay (Gordon confining unit). This shallow faulting was 

confirmed with a seismic reflection survey. The fault trend is northwesterly, similar to 

that of several tributaries to Four Mile Creek (see topographic map of Figure 6-5). This 

suggests the possibility of structural control of the streams, and hence additional faulting. 

Figure 6-13. Structural contour map of the top of the Gordon confining unit (WSRC, 1992) 
6-14 

The maps of CPT locations suggest that those penetrating Gordon confining unit may not 

have been adequate in number or distribution to test any hypothesis relating to whether or 

not the Gordon confining unit was continuous or breached. 

The maps in Flach et al. (1999) do not include scales or north arrows, so it is difficult to 

compare them to the LWR report, but the outline of Site R is shown on both drawings in 

Figure 6-14 as a reference. Gordon aquifer flow in the LWR report is about 60 degrees 

west of SRS plant north (left side of Figure 6-14). The modeling report Fig 4-32 (right 

side of Figure 6-14,) indicates a flow direction of about 38 degrees west of plant north. 

This modeling work was used to guide placement of sampling points in the Gordon 

aquifer (model Layer 7). If the flow direction is off by as much as 20 degrees, point 

sampling by direct push methods might have missed existing contamination altogether 

(see flow direction on left side of Figure 6-14). 

0

200

400

600

800

1000

0

200

400

600

800

1000

200

0

0

0

0

0

0

0

0

0

0

60 

Degrees

38

Degrees

Plant

Plant North

North

Site R

Flow Direction

Flow Direction

Gordon Aquifer in 1992 LWR Report Gordon Aquifer in 1999 report WSRC-TR-99-00310

Figure 6-14. Maps of ground water flow directions within the Gordon aquifer

6.7 Performance Indicators and FEPs 

The Performance Indicators for this system are primarily tritium and VOC concentrations 

in ground water. There is very limited testing for these PIs in the Gordon aquifer. 

Discrepancy between the flow directions in Figure 6-14 is noted as adding to uncertainty 

in the C-Area flow modeling. Faulting in the nearby LWR area is an indicator that the 

CSM should consider a breached confining unit. 
6-15 

Because C-Reactor was used largely for tritium production, lithium might be a good 

tracer, but has not been reported. 

Integrity of the green clay / Gordon confining unit is a key assumption in flow and 

transport calculations. This assumption is not adequately tested. As noted, the nearby 

Site R report indicates faulting of this feature.

6.8 Monitoring Strategy Application Conclusions 

The initial management decision was to characterize the extent of the TCE and tritium 

from the CBRP and the seepage basins. A subsequent decision was to simulate flow and 

transport of these contaminants to evaluate risk and remediation options. These decisions 

were made in the context of the SRS Federal Facilities Agreement and with the advice 

and consent of the South Carolina Department of Health and Environmental Control 

(DHEC). 

Plume sampling and geohydrologic characterization were accomplished with CPT 

methods. In addition, data were compiled from existing sources comprising monitoring 

wells, water production wells, and so forth. 

How important is the problem? Although the Gordon is a regionally important aquifer, 

it discharges into the Savannah River or the adjacent swamp before leaving DOE 

property. Shallower water-bearing zones discharge into smaller streams that lead to the 

Savannah River. Thus, the only reasonable pathway to an offsite receptor is through the 

Savannah River, which has a discharge normally in excess of 5,000 cfs to dilute any SRS 

contribution. 

Computer modeling with 50-year projections suggest that the TCE and tritium groundwater plumes will both be greatly reduced, although not to drinking water standards. 

Is any further action needed? Probably not. Sampling and modeling suggest that the 

contamination will decline naturally over time and that there are no offsite receptors for 

the ground-water pathway. Active ground-water remediation is possible, but impractical. 

The C-Area is totally within a government-owned site and C-reactor is shut down 

permanently. 

Decommissioning of C-Area facilities might initiate a future review of the no further 

action decision. If there were a legal issue with the accuracy of the modeling, the 

exclusion of the LWR report could be used against the SRS. 

How is C-Area different from a facility applying for an NRC license? SRS was 

constructed in the early 1950s to provide materials for defense. There was no private 

funding – cost was not an issue. There was no issue of license approval. There was no 

public review. There was no opportunity for antinuclear activists to intervene. There 

was no profit motive. 

None of these statements are true for a new NRC-licensed facility. Any oversight in data 

collection, or failure to consider alternative Conceptual Site Models could result in costly 

challenges to a proposed facility. 
6-16 

What other hydrogeologic factors would be considered for a new facility? In the 

above discussion we mention three technical weaknesses that could be used against a new 

facility. These are all related to the LWR well installation report. 

Modeling to predict the TCE plume behavior did not reference the LWR well installation 

report. The flow directions for the only aquifer leaving the model boundaries (Layer 7 

or Gordon aquifer) was at variance as much as 20 degrees with flow shown in the LWR 

report. 

The LWR report suggests discontinuities in the Gordon confining unit above the Gordon 

aquifer. These could provide fast paths for contamination to reach the Gordon aquifer 

with much less attenuation than currently predicted in the model. 

In the context of current SRS operations and future long-term stewardship, these 

comments may not be important. The large buffer around the C-Area and the lack of a 

credible pathway to a ground-water receptor largely negate any issues related to the 

failure to incorporate and discuss all available data. 

In the context of a commercial site with a smaller buffer and credible ground water 

pathways to off-site receptors, the failure to account for all available data and to 

thoroughly investigate the continuity of the confining unit could be used by interveners 

and could lead to public distrust of the licensee’s motives or competence. 

6.8.1 Possible Future Actions 

Based on the results of the application of the Strategy, some recommendations are made 

for future investigations. These are made in the context of the discussion above – that is, 

irrespective of the results, there is very little impact to offsite risk. Additional 

characterization and modeling would be strongly recommended if this were a site under 

stakeholder scrutiny. 

Modeling suggests the confined Gordon aquifer could be monitored with wells placed 

west of Four Mile Creek across from the plume. A new round of CPT sampling in about 

2020 would also be sufficient to confirm or deny the hypotheses the TCE is leaving the 

C-Area facility boundary. 

At least one round of ground-water samples should be collected from the LWR-series 

well clusters for a full suite of potential contaminants of concern for C Area. This data 

would help ensure that no contamination has reached this more northern portion of C 

Area. This additional data will also help to provide plume closure for modeling on the 

north side of the facility. 

Lithium should be evaluated as a tracer for this Area. 

Integrity of the Gordon confining unit is a key assumption in the CSM used for flow and 

transport modeling. Uncertainty in this assumption taints all current modeling results. A 

shallow seismic survey coupled with a few wells or CPT tests could test this source of 

uncertainty. 
6-17 

6.9 References 

DOE/EM-0319. Linking Legacies, Connecting the Cold War Nuclear Weapons 

Production Processes to Their Environmental Consequences. 1997. 

Flach, G.P., et al. WSRC-TR-99-00310. “Hydrogeological Analysis and Groundwater 

Flow for C-Reactor Area with Contaminant Transport for C-Reactor Seepage 

Basins (CRSB) and C-Area Burning/Rubble Pit (CBRP)(U).” 1999. 

Fallaw, W.C. “Stratigraphic Relationships in Eocene Outcrops Along Upper Three Runs 

at the Savannah River Site” Carolina Geological Society Field Trip Guidebook. p 

XII1-XII2. 1992. 

GeoTrans. WSRC-TR-2001-00298. “Groundwater Modeling for the C-Area 

Burning/Rubble Pit (U).” 2001. 

Kegley, W.P.,et al. “Textural Factors Affecting Permeability at the MWD Well Field, 

Savannah River Site, Aiken, South Carolina.” Southeastern Geology. Vol. 34, p 

139-161. 1994. 

Siple, G.E. “Geology and Ground Water of the Savannah River Site and Vicinity.” South 

Carolina U.S. Geological Survey Water Supply Paper 1841. U.S. Government 

Printing Office: Washington, D.C. OpenLit. 1967. 

Westinghouse Savannah River Company (WSRC). WSRC-RP-92-1316. “Summary of 

Drilling Program for Site R, New Sanitary Landfill Project.” Westinghouse 

Savannah River Company: Aiken, South Carolina. November 19, 1992 

WSRC. ESH-EMS-980590. “Environmental Protection Department’s Well Inventory.” 

Westinghouse Savannah River Company: Aiken, South Carolina,. July 1998.