EPA’s Composite Model

for Leachate Migration

with Transformation

Products (EPACMTP)

Parameters/Data

Background Document

April 2003
Office of Solid Waste (5305W)

Washington, DC 20460

EPA530-R-03-003

April 2003

www.epa.gov/osw
EPA’s COMPOSITE MODEL FOR LEACHATE MIGRATION

WITH TRANSFORMATION PRODUCTS (EPACMTP)

PARAMETERS/DATA BACKGROUND DOCUMENT

U.S. Environmental Protection Agency

Office of Solid Waste

Washington, DC 20460

April 2003
This page intentionally left blank.
i

TABLE OF CONTENTS

Page

ACKNOWLEDGMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii

LIST OF SYMBOLS AND ABBREVIATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix

1.0 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-1

2.0 WASTE MANAGEMENT UNIT (SOURCE) PARAMETERS . . . . . . . . . . 2-1

2.1 SOURCE PARAMETERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-4

2.2 DATA SOURCES FOR WMU PARAMETERS . . . . . . . . . . . . . . . 2-4

2.3 LANDFILLS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-10

2.3.1 Landfill Area (Aw

) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-10

2.3.2 Landfill Depth (DLF

) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-11

2.3.3 Landfill Base Depth below Grade (dBG) . . . . . . . . . . . . . . 2-12

2.3.4 Waste Fraction (Fh) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-14

2.3.5 Waste Volume (PWS) . . . . . . . . . . . . . . . . . . . . . . . . . . 2-14

2.3.6 Leaching Duration (tp) . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-15

2.4 SURFACE IMPOUNDMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . 2-16

2.4.1 Surface Impoundment Area (Aw

) . . . . . . . . . . . . . . . . . . 2-17

2.4.2 Surface Impoundment Ponding Depth (Hp

) . . . . . . . . . . . 2-18

2.4.3 Surface Impoundment Total Thickness of Sediment (Ds) 2-19

2.4.4 Surface Impoundment Liner Thickness (Dlin) . . . . . . . . . 2-20

2.4.5 Surface Impoundment Liner Conductivity (Klin) . . . . . . . . 2-21

2.4.6 Surface Impoundment Base Depth Below Grade (dBG) . . 2-22

2.4.7 Surface Impoundment Leak Density (leak

) . . . . . . . . . . . 2-23

2.4.8 Distance to Nearest Surface Water Body (R

) . . . . . . . . 2-24

2.4.9 Surface Impoundment Leaching Duration (tp

) . . . . . . . . . 2-25

2.5 WASTE PILES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-26

2.5.1 Waste Pile Area (Aw

) . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-27

2.5.2 Waste Pile Leaching Duration (tp

) . . . . . . . . . . . . . . . . . . 2-28

2.5.3 Waste Pile Base Depth below Grade (dBG) . . . . . . . . . . . 2-28

2.6 LAND APPLICATION UNITS . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-29

2.6.1 Land Application Unit Area (Aw) . . . . . . . . . . . . . . . . . . . 2-29

2.6.2 Land Application Unit Leaching Duration (tp) . . . . . . . . . 2-30

3.0 WASTE AND CONSTITUENT PARAMETERS . . . . . . . . . . . . . . . . . . . . 3-1

3.1 WASTE AND CONSTITUENT PARAMETERS . . . . . . . . . . . . . . 3-2

3.2 WASTE CHARACTERISTICS . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-3

3.2.1 Waste Density (hw) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-3

3.2.2 Concentration of Constituent in the Waste (Cw

) . . . . . . . . 3-5

3.2.3 Concentration of Constituent in the Leachate (CL

) . . . . . . 3-5

3.3 CONSTITUENT PHYSICAL AND CHEMICAL

CHARACTERISTICS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-7

3.3.1 All Constituents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-7

3.3.1.1 Molecular Diffusion Coefficient (Di

) . . . . . . . . . 3-8

3.3.1.2 Drinking Water Standard (DWS) . . . . . . . . . . . 3-8

3.3.1.3 Molecular Weight (MW) . . . . . . . . . . . . . . . . . 3-9
TABLE OF CONTENTS (continued)

Page

ii

3.3.2 Organic Constituents . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-10

3.3.2.1 Organic Carbon Partition Coefficient (koc

) . . . 3-10

3.3.2.2 Parameters Related to Chemical Hydrolysis . 3-12

3.3.2.2.1 Dissolved Phase Hydrolysis

Decay Rate (1

) . . . . . . . . . . . . . . . . . 3-13

3.3.2.2.2 Sorbed Phase Hydrolysis

Decay Rate (2) . . . . . . . . . . . . . . . . . 3-14

3.3.2.2.3 Acid-Catalyzed Hydrolysis Rate

Constant ( ) . . . . . . . . . . . . . . . . . 3-14

3.3.2.2.4 Neutral Hydrolysis Rate

Constant ( ) . . . . . . . . . . . . . . . . . 3-16

3.3.2.2.5 Base-Catalyzed Hydrolysis Rate

Constant ( ) . . . . . . . . . . . . . . . . . 3-17

3.3.2.2.6 Reference Temperature (Tr) . . . . . . . 3-17

3.3.2.3 Parameters Related to Hydrolysis

Transformation Products . . . . . . . . . . . . . . . . . . . 3-18

3.3.2.3.1 Daughter Species Number () . . . . . . 3-18

3.3.2.3.2 Number of Immediate Parents (M

) . . 3-19

3.3.2.3.3 Species Number(s) of Immediate

Parent(s) (m

(i), i = 1, M) . . . . . . . . . . 3-20

3.3.2.3.4 Fraction of the Parent Species (m) . . 3-21

3.3.3 Metals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-22

3.3.3.1 Empirical Kd Data . . . . . . . . . . . . . . . . . . . . . 3-23

3.3.3.1.1 Kd Data Compiled from a

Literature Survey . . . . . . . . . . . . . . . . 3-23

3.3.3.1.2 pH-based Isotherms . . . . . . . . . . . . . 3-24

3.3.3.2 MINTEQA2-Derived Sorption Isotherm Data . 3-25

3.3.3.2.1 Metal Identification Number (ID) . . . . 3-27

3.3.3.2.2 Soil and Aquifer pH (pH) . . . . . . . . . . 3-29

3.3.3.2.3 Iron-Hydroxide Content (FeOx) . . . . . 3-30

3.3.3.2.4 Leachate Organic Matter (LOM) . . . . 3-31

3.3.3.2.5 Percent Organic Matter (%OM) . . . . . 3-32

3.3.3.2.6 Fraction Organic Carbon (foc) . . . . . . . 3-34

3.3.3.2.7 Ground-water Type (IGWT) . . . . . . . . 3-35

4.0 INFILTRATION AND RECHARGE PARAMETERS . . . . . . . . . . . . . . . . . 4-1

4.1 INFILTRATION AND RECHARGE PARAMETERS . . . . . . . . . . . 4-1

4.2 CLIMATE CENTER INDEX (ICLR) . . . . . . . . . . . . . . . . . . . . . . . 4-2

4.3 INFILTRATION RATES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-6

4.3.1 Landfill Infiltration Rate (I) . . . . . . . . . . . . . . . . . . . . . . . . 4-7

4.3.2 Waste Pile Infiltration Rate (I) . . . . . . . . . . . . . . . . . . . . . . 4-9

4.3.3 Land Application Unit Infiltration Rate (I) . . . . . . . . . . . . 4-11

4.3.4 Surface Impoundment Infiltration Rate (I) . . . . . . . . . . . . 4-13

4.4 RECHARGE RATE (IR

) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-15
TABLE OF CONTENTS (continued)

Page

iii

5.0 HYDROGEOLOGICAL PARAMETERS . . . . . . . . . . . . . . . . . . . . . . . . . . 5-1

5.1 HYDROGEOLOGICAL PARAMETERS . . . . . . . . . . . . . . . . . . . . 5-2

5.2 UNSATURATED ZONE PARAMETERS . . . . . . . . . . . . . . . . . . . 5-2

5.2.1 Unsaturated Zone Thickness (Du

) . . . . . . . . . . . . . . . . . . . 5-2

5.2.2 Soil Type (ISTYPE) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-6

5.2.3 Soil Hydraulic Characteristics . . . . . . . . . . . . . . . . . . . . . . 5-7

5.2.3.1 Soil Hydraulic Conductivity (Ks

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

5.2.3.2 Alpha () . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-11

5.2.3.3 Beta () . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-12

5.2.3.4 Residual Water Content (r

) . . . . . . . . . . . . . . . . 5-13

5.2.3.5 Saturated Water Content (s) . . . . . . . . . . . . . . . 5-15

5.2.3.6 Soil Bulk Density (b

) . . . . . . . . . . . . . . . . . . . . . 5-16

5.2.3.7 Percent Organic Matter (%OM) . . . . . . . . . . . . . 5-17

5.2.4 Unsaturated Zone Dispersivity (Lu) . . . . . . . . . . . . . . . . 5-19

5.2.5 Freundlich Adsorption Isotherm Parameters . . . . . . . . . 5-21

5.2.5.1 Leading Coefficient of Freundlich Isotherm for

Unsaturated Zone (Kd) . . . . . . . . . . . . . . . . . . . . 5-23

5.2.5.2 Exponent of Freundlich Isotherm for

Unsaturated Zone () . . . . . . . . . . . . . . . . . . . . . 5-24

5.2.6 Chemical Degradation Rate Coefficient for

Unsaturated Zone (cu) . . . . . . . . . . . . . . . . . . . . . . . . . . 5-25

5.2.7 Biodegradation Rate Coefficient for Unsaturated

Zone (bu

) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-26

5.2.8 Soil Temperature (T) . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-26

5.2.9 Soil pH (pH) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-28

5.3 SATURATED ZONE PARAMETERS . . . . . . . . . . . . . . . . . . . . . 5-29

5.3.1 Particle Diameter (d) . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-29

5.3.2 Porosity () . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-31

5.3.3 Bulk Density (b

) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-33

5.3.4 Aquifer Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . 5-35

5.3.4.1 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-38

5.3.4.2 Hydrogeologic Environment (IGWR) . . . . . . . . . 5-39

5.3.4.3 Saturated Zone Thickness (B) . . . . . . . . . . . . . . 5-43

5.3.4.4 Hydraulic Conductivity (K) . . . . . . . . . . . . . . . . . 5-45

5.3.4.5 Regional Hydraulic Gradient (r) . . . . . . . . . . . . . 5-47

5.3.5 Seepage Velocity (Vx

) . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-49

5.3.6 Anisotropy Ratio (Ar) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-51

5.3.7 Retardation Coefficient for the Saturated Zone (R

s

) . . . . 5-52

5.3.8 Dispersivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-53

5.3.8.1 Longitudinal Dispersivity (L) . . . . . . . . . . . . . . . 5-54

5.3.8.2 Horizontal Transverse Dispersivity (T

) . . . . . . . 5-56

5.3.8.3 Vertical Dispersivity (v

) . . . . . . . . . . . . . . . . . . 5-58

5.3.9 Aquifer Temperature (T) . . . . . . . . . . . . . . . . . . . . . . . . . 5-59

5.3.10 Ground-water pH (pH) . . . . . . . . . . . . . . . . . . . . . . . . . . 5-61

5.3.11 Fractional Organic Carbon Content ( ) . . . . . . . . . . . . 5-63
TABLE OF CONTENTS (continued)

Page

iv

5.3.12 Leading Coefficient of Freundlich Isotherm for

Saturated Zone ( ) . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-64

5.3.13 Exponent of Freundlich Isotherm for Saturated Zone (

s

) 5-66

5.3.14 Chemical Degradation Rate Coefficient for

Saturated Zone ( ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-67

5.3.15 Biodegradation Rate Coefficient for Saturated Zone ( ) 5-68

6.0 RECEPTOR WELL PARAMETERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-1

6.1 RECEPTOR WELL PARAMETERS . . . . . . . . . . . . . . . . . . . . . . . 6-1

6.2 RADIAL DISTANCE TO RECEPTOR WELL (Rrw) . . . . . . . . . . . . 6-4

6.3 ANGLE OF WELL OFF OF PLUME CENTERLINE (rw

) . . . . . . . 6-5

6.4 DOWN-GRADIENT DISTANCE TO RECEPTOR WELL (xrw) . . . 6-6

6.5 WELL DISTANCE FROM PLUME CENTERLINE (yrw

) . . . . . . . . . 6-8

6.6 DEPTH OF INTAKE POINT BELOW WATERTABLE (z

*

rw

) . . . . 6-10

6.7 AVERAGING PERIOD FOR Ground-water

CONCENTRATION AT RECEPTOR WELL (td) . . . . . . . . . . . . . 6-11

7.0 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-1

APPENDIX A: Determination of Infiltration and Recharge Rates

APPENDIX B: Nonlinear Sorption Isotherms Calculated Using the MINTEQA2

Model

APPENDIX C: Physical and Chemical Properties for Organic Constituents

APPENDIX D: WMU and Hydrogeologic Environment Databases
v

LIST OF FIGURES

Page

Figure 2.1 WMU Types Modeled in EPACMTP . . . . . . . . . . . . . . . . . . . . . . . 2-3

Figure 2.2 Geographic Locations of Landfill WMUs . . . . . . . . . . . . . . . . . . . 2-6

Figure 2.3 Geographic Locations of Surface Impoundment WMUs . . . . . . . 2-7

Figure 2.4 Geographic Locations of Waste Pile WMUs . . . . . . . . . . . . . . . . 2-8

Figure 2.5 Geographic Locations of Land Application Unit WMUs . . . . . . . . 2-9

Figure 2.6 WMU with Base Elevation below Ground Surface . . . . . . . . . . . 2-13

Figure 2.7 Schematic Cross-Section View of SI Unit . . . . . . . . . . . . . . . . . . 2-17

Figure 4.1 Locations of EPACMTP Climate Stations . . . . . . . . . . . . . . . . . . . 4-5

Figure 5.1 Ground-water Temperature Distribution for Shallow Aquifers

in the United States (from Todd, 1980) . . . . . . . . . . . . . . . . . . . 5-27

Figure 5.2 Geographical distribution of sites in the API-HGDB data base

(Reproduced from API, 1989) . . . . . . . . . . . . . . . . . . . . . . . . . . 5-37

Figure 5.3 Ground-water Temperature Distribution for Shallow Aquifers

in the United States (from Todd, 1980) . . . . . . . . . . . . . . . . . . . 5-60

Figure 6.1 Schematic plan view showing procedure for determining the

downstream location of the receptor well: (a) well location

determined using radial distance, Rrw

, and angle off center rw;

and (b) well location generated uniformly within plume limit . . . . . 6-3
vi

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vii

LIST OF TABLES

Page

Table 2.1 Waste Management Unit (Source) Parameters . . . . . . . . . . . . . . 2-4

Table 2.2 Cumulative Frequency Distribution of Landfill Area . . . . . . . . . . 2-11

Table 2.3 Cumulative Frequency Distribution of Landfill Depth . . . . . . . . . 2-12

Table 2.4 Cumulative Frequency Distribution of Surface

Impoundment Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-18

Table 2.5 Cumulative Frequency Distribution of Surface Impoundment

Ponding Depth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-19

Table 2.6 Cumulative Frequency Distribution of Surface Impoundment

Depth Below Grade . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-22

Table 2.7 Cumulative Frequency Distribution of Leak Density for

Composite-Lined SIs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-23

Table 2.8 Cumulative Frequency Distribution of Distance to Nearest

Surface Water Body . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-24

Table 2.9 Cumulative Frequency Distribution of Surface Impoundment

Operating Life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-26

Table 2.10 Cumulative Frequency Distribution of Waste Pile Area . . . . . . . 2-27

Table 2.11 Cumulative Frequency Distribution of Land Application

Unit Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-30

Table 3.1 Waste and Constituent Parameters . . . . . . . . . . . . . . . . . . . . . . . 3-2

Table 3.2 Default Cumulative probability distribution of waste density . . . . . 3-4

Table 3.3 Empirical pH-dependent Adsorption Relations

(Loux et al., 1990) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-25

Table 3.4 Metals that have MINTEQA2-derived Non-linear Isotherms . . . . 3-28

Table 3.5 Probability distribution of soil and aquifer pH . . . . . . . . . . . . . . . 3-29

Table 3.6 Probability distribution of fraction iron hydroxide . . . . . . . . . . . . 3-31

Table 3.7 Probability distribution of leachate organic matter . . . . . . . . . . . 3-32

Table 3.8 Probability distribution of percent organic matter in the

unsaturated zone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-33

Table 3.9 Probability distribution of fraction organic carbon in the

saturated zone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-35

Table 4.1 Climate Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-2

Table 4.2 Climate Centers Used in the HELP Modeling to Develop

Infiltration and Recharge Rates . . . . . . . . . . . . . . . . . . . . . . . . . . 4-3

Table 4.3 Cumulative Frequency Distribution of Landfill Infiltration . . . . . . . 4-8

Table 4.4 Cumulative Frequency Distribution of Waste Pile Infiltration . . . 4-10

Table 4.5 Cumulative Frequency Distribution of Land Application

Unit Infiltration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-12

Table 4.6 Cumulative Frequency Distribution of Surface

Impoundment Infiltration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-14

Table 4.7 Cumulative Frequency Distribution of Regional Recharge Rate . 4-16

Table 5.1 Hydrogeological Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-3

Table 5.2 Cumulative Frequency Distribution of Unsaturated

Zone Thickness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-5

Table 5.3 Default EPACMTP Soil Types . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-6
LIST OF TABLES (continued)

Page

viii

Table 5.4 Statistical parameters for soil properties for three soil types

used in the EPACMTP model (Carsel and Parrish, 1988 and

Carsel et al., 1988). All values are in arithmetic space . . . . . . . . 5-8

Table 5.5 Cumulative Frequency Distribution of Soil Hydraulic Conductivity 5-9

Table 5.6 Descriptive statistics for van Genuchten water retention

model parameters, , , and 	 (Carsel and Parrish, 1988) . . . . 5-10

Table 5.7 Cumulative Frequency Distribution of Alpha . . . . . . . . . . . . . . . 5-11

Table 5.8 Cumulative Frequency Distribution of Beta . . . . . . . . . . . . . . . . 5-13

Table 5.9 Cumulative Frequency Distribution of Residual Water Content . 5-14

Table 5.10 Cumulative Frequency Distribution of Saturated Water Content 5-15

Table 5.11 Cumulative Frequency Distribution of Soil Bulk Density . . . . . . . 5-17

Table 5.12 Cumulative Frequency Distribution of Percent Organic Matter . . 5-18

Table 5.13 Cumulative Frequency Distribution of Dispersivity . . . . . . . . . . . 5-20

Table 5.14 Compilation of field dispersivity values (EPRI, 1985) . . . . . . . . . 5-21

Table 5.15 Empirical distribution of mean particle diameter

(based on Shea, 1974) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-30

Table 5.16 Cumulative Frequency Distribution of Particle Diameter . . . . . . 5-30

Table 5.17 Ratio between effective and total porosity as a function

of particle diameter (after McWorter and Sunada, 1977) . . . . . . 5-33

Table 5.18 Cumulative Frequency Distribution of Bulk Density . . . . . . . . . . 5-34

Table 5.19 HGDB Hydrogeologic Environments (from Newell et al., 1990) . 5-35

Table 5.20 Cumulative Frequency Distribution of Saturated Zone Thickness 5-44

Table 5.21 Cumulative Frequency Distribution of Hydraulic Conductivity . . . 5-45

Table 5.22 Cumulative Frequency Distribution of Regional

hydraulic gradient . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-48

Table 5.23 Cumulative Frequency Distribution of Ground-water

Seepage Velocity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-50

Table 5.24 Probabilistic representation of longitudinal dispersivity . . . . . . . . 5-55

Table 5.25 Cumulative Frequency Distribution of Longitudinal Dispersivity . 5-55

Table 5.26 Cumulative Frequency Distribution of Horizontal

Transverse Dispersivity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-57

Table 5.27 Cumulative Frequency Distribution of Vertical Dispersivity . . . . . 5-59

Table 5.28 Probability distribution of aquifer pH . . . . . . . . . . . . . . . . . . . . . . 5-62

Table 5.29 Probability distribution of fraction organic carbon in the

saturated zone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-64

Table 6.1 Receptor Well Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-1

Table 6.2 Cumulative Probability of Distance to Nearest Receptor Well for

Landfills (from EPA, 1993) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-4
ix

ACKNOWLEDGMENTS

A large number of individuals have been involved with the development of

EPACMTP since its inception in the early 1990's. Dr. Zubair A. Saleem of the U.S.

EPA, Office of Solid Waste (EPA/OSW) has coordinated and guided the development

of EPACMTP throughout much of this period. Ms. Ann Johnson, Mr. David Cozzie, and

Mr. Timothy Taylor provided review for the development of this background document.

This report was prepared by the staffs of HydroGeoLogic, Inc. (HGL), and Resource

Management Concepts, Inc. (RMC), under EPA Contract Number 68-W-01-004.
x

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xi

LIST OF SYMBOLS AND ABBREVIATIONS

Symbol Definition Section

Ar anisotropy ratio = Kx/Kz 5.3.6

Aw area of a WMU (m

2

) 2.3.1, 2.4.1,

2.5.1, 2.6.1

B thickness of the saturated zone (m) 5.3.4.3, 6.6

Cd metal concentration in the dissolved phase at equilibrium

(mg/L)

3.3.3.2

Cs metal concentration in the sorbed phase at equilibrium

(mg/L)

3.3.3.2

CLleachate concentration (mg/L) 3.2.3

CV coefficient of variation (%) 5.2.4

Cw constituent concentration in the waste (mg/kg) 3.2.2

dBG depth below grade of WMU (m) 2.3.3, 2.4.6, 2.5.3

Di molecular diffusion coefficient in free water for species i

(m

2

/yr)

3.3.1.1

DLF

landfill depth (m) 2.3.2

Dlin

liner thickness (m) 2.4.4

Ds

total sediment thickness (m) 2.4.3

Dutotal depth of the unsaturated zone (m) 5.2.1

D

s*

effective molecular diffusion coefficient for species of

interest (m

2

/y)

6.6

DWS drinking water standard (mg/L) 3.3.1.2

Ea Arrhenius activation energy (Kcal/mol) 3.3.2.2.3

Fh volume fraction of the waste in the landfill at time of closure

(m

3

/m

3

)

2.3.4

FeOx iron hydroxide content (wt % Fe) 3.3.3.2.3

focfractional organic carbon content (dimensionless) 3.3.3.2.6

foc

s

fractional organic carbon content of the aquifer material

(dimensionless)

5.3.11

g gravitational acceleration (m/s

2

) 5.3.4.4

[H

+

] hydrogen ion concentration (mol/L) 3.3.2.2.1

HP SI ponding depth (m) 2.4.2

I annual infiltration rate through the source (m/y) 4.3.1, 4.3.2,

4.3.3, 4.3.4

ICLR climate center index 4.2

ID metal identification number (unitless) 3.3.3.2.1

IGWR hydrogeologic environment index (unitless) 3.3.3.2.7,5.3.4.2

IGWT ground-water type - carbonate/non-carbonate (unitless) 3.3.3.2.7

ISTYPE soil type 5.2.2
LIST OF SYMBOLS AND ABBREVIATIONS (continued)

Symbol Definition Section

xii

IWLOC Rrw(Receptor well) origination method 6.5

IR effective recharge rate outside the strip source area (m/y)

or recharge rate outside the source area (m/y)

4.4

J symbol used to denote a for the acid-catalyzed reaction, b

for the base-catalyzed reaction and n for the neutral

reaction

3.3.2.2.3

K hydraulic conductivity (m/yr) 5.3.4.4

k1 nonlinear Freundlich parameter for the unsaturated zone

(mg constituent/kg dry soil))

5.2.9

Ka

T

acid-catalyzed hydrolysis rate constant (1/(mol.yr)) 3.3.2.2.1

Ka

Tr

acid-catalyzed hydrolysis rate constant at reference

temperature (1/(mol.yr))

3.3.2.2.3

Kb

T

base-catalyzed hydrolysis rate constant (1/(mol.yr)) 3.3.2.2.2

Kb

Tr

base-catalyzed hydrolysis rate constant at reference

temperature (1/(mol.yr))

3.3.2.2.5

Kd distribution (solid-aqueous phase) partition coefficient in the

unsaturated zone (cm

3

/g) (Freundlich Coefficient)

3.3.3, 5.2.8

Kd

s

solid-liquid distribution coefficient of the aquifer (cm

3

/g) 5.3.12

KJ

T

hydrolysis rate constant for reaction process J, corrected

for the subsurface temperature T (1/(mol.yr) for the acidand base-catalyzed reactions; 1/yr for the neutral reaction)3.3.2.2.3

KJ

Tr

hydrolysis rate constant for reaction process J, measured

at the reference temperature Tr(1/(mol.yr) for the acid- and

base-catalyzed reactions; 1/yr for the neutral reaction)

3.3.2.2.3

Klin saturated hydraulic conductivity of liner (m/y) 2.4.5

Kn

T

neutral hydrolysis rate constant at (1/yr) 3.3.2.2.1

Kn

Tr

neutral hydrolysis rate constant at reference temperature

(1/yr)

3.3.2.2.3

kd soil-water partition coefficient (L/kg) 3.3.2.1

koc constituent-specific organic carbon partition coefficient

(cm

3

/g)

3.3.2.1

kow octanol-water partition coefficient (cm

3

/g) 3.3.2.1

Ks saturated hydraulic conductivity (cm/hr) 5.2.3

Kx hydraulic conductivity in the x direction (m/y) 5.3.5

Ky hydraulic conductivity in the horizontal transverse (y)

direction (m/y)

5.3.6

daughter species number 3.3.2.3.1

LOM leachate organic acid concentration (mol/L) 3.3.3.2.4

LYCHK constraint on well distance from plume centerline 6.5

LZCHK constraint on depth of intake point below water table 6.6
LIST OF SYMBOLS AND ABBREVIATIONS (continued)

Symbol Definition Section

xiii

daughter species number 3.3.2.3.1

LN log normal distribution 5.2.2

M number of immediate parent species 3.3.2.3.2

m species number of immediate parent 3.3.2.3.3

MWmolecular weight of species (g/mol.) 3.3.1.3

N sample size 5.2.4

NO Normal distribution 5.2.2

[OH

-

] hydroxyl ion concentration (mol/L) 3.3.2.2.2

%OM percent organic matter (dimensionless) 3.3.3.2.5, 5.2.7

PWS waste volume (m

3

) 2.3.5

pH ground-water pH (standard units) 3.3.3.2.2, 5.2.10,

5.2.13

Q1

F

background ground-water flux (m

2

/y) 6.6

Q4

F

recharge flux downgradient of the source (m

2

/y) 6.6

r regional hydraulic gradient (m/m) 5.3.4.5

Rg Universal Gas Constant (1.987E-3 Kcal/deg-mol) 3.3.2.2.3

Riretardation factor for species i (dimensionless) 3.3.2.1

Rrw

radial distance between waste management unit and well

(m)

6.2

R distance between the center of the source and the nearest

downgradient boundary where the boundary location has

no perceptible effects on the heads near the source (m)

2.4.8

R

s

retardation coefficient (dimensionless) 5.3.7

SB log ratio distribution 5.2.2

SD standard deviation 5.2.4

Tr hydrolysis reference temperature (°C) 3.3.2.2.6

T ground-water/subsurface temperature (°C) 3.3.2.2.3, 5.2.12,

5.3.9

td exposure time interval of interest (yr) 6.8

tp

leaching duration (yr) 2.3.6, 2.4.9,

2.5.2, 2.6.2

Vxlongitudinal ground-water (seepage) velocity (in the xdirection) (m/y)

5.3.5

X sample mean 5.2.4

x principal Cartesian coordinate along the regional flow

direction (m)

6.4

xrw distance from the downgradient boundary of the WMU to

the receptor well (m)

6.4
LIST OF SYMBOLS AND ABBREVIATIONS (continued)

Symbol Definition Section

xiv

xt average travel distance in the x direction (m) 5.3.8.1

xw

length of the WMU in the x-direction (parallel to groundwater flow) (m)

6.6

y principal Cartesian coordinate normal to the flow direction,

or distance from the plume centerline (m)

6.5

yD source width along the y-axis (m) 6.5

yrw Cartesian coordinate of the receptor well in the y-direction

(m)

6.5

z principal Cartesian coordinate in the vertical direction (m) 6.6

z*rw z-coordinate of the receptor well positive downward from

the water table(m)

6.6

GREEK SYMBOLS

 van Genuchten soil-specific shape parameter (1/cm) 5.2.2, 5.2.4.1

Llongitudinal dispersivity of the aquifer (m) 5.3.8.1, 6.6

Lulongitudinal dispersivity in the unsaturated zone (m) 5.2.6

Refreference longitudinal dispersivity, as determined from the

probabilistic distribution (m)

5.3.8.1

T horizontal transverse dispersivity (m) 5.3.8.2, 6.5

V vertical transverse dispersivity (m) 5.3.8.2, 6.6

 van Genuchten soil-specific shape parameter

(dimensionless)

5.2.2, 5.2.4.2

	 van Genuchten soil-specific shape parameter

(dimensionless) = 1 -1/

5.2.4

 species-specific nonlinear Freundlich exponent for the

unsaturated zone

5.2.9



s Freundlich exponent for the saturated zone

(dimensionless)

5.3.13

 soil water content (dimensionless) 3.3.2.1

rresidual soil water content (dimensionless) 5.2.4.3

rw angle measured counter-clockwise from the plume

centerline (degrees)

6.3

s saturated soil water content (dimensionless) 5.2.4.4

overall first-order hydrolysis transformation rate(1/y) 3.3.2.2

1 hydrolysis constant for dissolved phase (1/y) 3.3.2.2.2

2 hydrolysis constant for sorbed phase (1/y) 3.3.2.2.1

b

s

biodegradation rate in the saturated zone (1/yr) 5.3.15

c

s

chemical degradation rate in the saturated zone (1/yr) 5.3.14

butransformation coefficient due to biological transformation

(1/y)

5.2.11
LIST OF SYMBOLS AND ABBREVIATIONS (continued)

Symbol Definition Section

xv

cutransformation coefficient due to chemical transformation

(1/y)

5.2.10


 dynamic viscosity of water (N-s/m

2

) 5.3.4.4

m stoichiometric fraction of parent m that degrades into

daughter /speciation factor (dimensionless)

3.3.2.3.4

 density of water (kg/m

3

) 5.3.4.4

b bulk density of the aquifer (g/cm

3

) 3.3.2.1, 5.3.3

bu soil bulk density of the unsaturated zone (g/cm

3

) 5.2.5

 porosity/water content in the unsaturated zone

(dimensionless)

3.3.2.2, 5.3.2

e effective porosity of the saturated zone (dimensionless) 6.6
xvi

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Section 1.0 Introduction

1-1

1.0 INTRODUCTION

This document provides background information on the parameters and data

sources used in EPA’s Composite Model for Leachate Migration with Transformation

Products (EPACMTP). EPACMTP is a subsurface fate and transport model used by

EPA’s Office of Solid Waste in the RCRA program to establish regulatory levels for

concentrations of constituents in wastes managed in land-based units. This

document describes the EPACMTP input parameters, data sources and default

parameter values and distributions that EPA has assembled for its use of EPACMTP

as a ground-water assessment tool. EPA has also developed a complementary

document, the EPACMTP Technical Background Document (U.S. EPA, 2003a),

which presents the mathematical formulation, assumptions and solution methods

underlying the EPACMTP. These two documents together are the primary reference

documents for EPACMTP, and are intended to be used together.

The remainder of this section describes how this background document is

organized. The parameters and data are documented in six main categories, as

follows:

 Section 2 describes the Waste Management Unit (Source)

Parameters;

 Section 3 describes the Waste and Constituent Parameters;

 Section 4 describes the Infiltration and Recharge Parameters;

 Section 5 describes the Subsurface Parameters;

 Section 6 describes the Ground-water Well Location Parameters; and

 Section 7 provides a list of References

Several appendices provide complete listings of data distributions for a

number of the EPACMTP input parameters.

To facilitate the cross-referencing of information between this document and

the EPACMTP Technical Background Document (U.S. EPA, 2003a), each section

begins with a table that lists the parameters described in that section, and provides,

for each parameter, a reference to the equation(s) and/or section number in the

EPACMTP Technical Background Document (U.S. EPA, 2003a) that describes how

each parameter is used in the EPACMTP computer code.
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Section 2.0 Waste Management Unit (Source) Parameters

2-1

2.0 WASTE MANAGEMENT UNIT (SOURCE) PARAMETERS

EPACMTP can simulate the subsurface migration of leachate from four

different types of waste management units (WMUs). Each of the four unit types

reflects waste management practices that are likely to occur at industrial Subtitle D

facilities. The WMU can be a landfill, a waste pile, a surface impoundment, or a land

application unit. The latter is also sometimes called a land treatment unit. Figure

2.1 presents schematic diagrams of the different types of WMUs modeled in

EPACMTP.

Landfill. Landfills (LFs) are facilities for the final disposal of solid waste on

land. EPACMTP is typically used to model closed LFs with an earthen cover. LFs

may be unlined, or they may have some type of engineered liner, but the model

assumes no leachate collection system exists underneath the liner. The LF is filled

with waste during the unit’s operational life. Upon closure of the LF, the waste is left

in place, and a final soil cover is installed. The starting point for the EPACMTP

simulation is the time at which the LF is closed, i.e., the unit is at maximum capacity.

The release of waste constituents into the soil and ground water underneath the LF

is caused by dissolution and leaching of the constituents due to precipitation which

percolates through the LF. The type of liner that is present (if any) controls, to a

large extent, the amount of leachate that is released over time from the unit. LFs

are modeled in EPACMTP as WMUs with a rectangular footprint and a uniform

depth. The EPACMTP model does not explicitly account for any loss processes

occurring during the unit’s active life (for example, due to leaching, volatilization,

runoff or erosion, or biochemical degradation), however these processes will be

taken into account if the input value for leachate concentration is based on a sitespecific chemical analysis of the waste (such as results from a Toxicity

Characteristic Leaching Procedure (TCLP) or Synthetic Precipitation Leaching

Procedure (SPLP) analysis). The leachate concentration used as a model input is

the expected initial leachate concentration when the waste is ‘fresh’. Because the

LF is closed, the concentration of the waste constituents will diminish with time due

to depletion of the landfilled wastes; the model is equipped to simulate this

“depleting source” scenario for LFs, but other source options are available, and are

explained in Section 2.3.

Surface Impoundment. A surface impoundment (SI) is a WMU which is

designed to hold liquid waste or wastes containing free liquid. SIs may be either

ground level or below ground level flow-through units. They may be unlined, or they

may have some type of engineered liner. Release of leachate is driven by the

ponding of water in the impoundment, which creates a hydraulic head gradient

across the barrier underneath the unit. The EPACMTP model considers a SI to be a

temporary WMU with a finite operational life. At the end of the unit’s operational life,

we assume there is no further release of waste constituents to the ground water

(that is, there is a clean closure of the SI). SIs are modeled as pulse-type sources;

leaching occurs at a constant leachate concentration over a fixed period of time

equal to the unit’s operating life. The EPACMTP model assumes a constant
Section 2.0 Waste Management Unit (Source) Parameters

2-2

ponding depth (depth of waste water in SI) during the operational life (see Section

2.2.4).

Waste Pile. Waste piles (WPs) are typically used as temporary storage or

treatment units for solid wastes. Due to their temporary nature, they are typically not

covered. Similar to LFs, WPs may be unlined, or they may have some type of

engineered liner. EPACMTP assumes that WPs have a fixed operational life, after

which the WP is removed. Thus, WPs are modeled as pulse-type sources; leaching

occurs at a constant leachate concentration over a fixed period of time which is

equal to the unit’s operating life (see Section 2.5.2).

Land Application Unit. Land application units (LAUs) (or land treatment units)

are areas of land receiving regular applications of waste that is either tilled directly

into the soil or sprayed onto the soil and then tilled. EPACMTP models the leaching

of wastes after they have been tilled with soil. EPACMTP does not account for the

losses due to volatilization during or after waste application. LAUs are only

evaluated for the no-liner scenario because liners are not typically used at this type

of facility. EPACMTP assumes that an LAU is a temporary WMU with a fixed

operational life, after which the waste is no longer land-applied. Thus, LAUs are

modeled in EPACMTP as a constant pulse-type leachate source, with a leaching

duration equal to the unit’s operational life (see Section 2.6.2).
Section 2.0 Waste Management Unit (Source) Parameters

2-3

Figure 2.1 WMU Types Modeled in EPACMTP.
Section 2.0 Waste Management Unit (Source) Parameters

2-4

2.1 SOURCE PARAMETERS

The input parameters used in EPACMTP to describe the waste management

unit are listed below in Table 2.1

Table 2.1 Waste Management Unit (Source) Parameters

WMU

Type Parameter Symbol Units Section

Equation in

EPACMTP TBD

LF

Area Aw m

2

2.3.1 2.3

Depth DLF m 2.3.2 2.3

Depth Below Grade dBG m 2.3.3 2.2.2.2

Landfill Waste

Fraction (Volume

Fraction)

Fh m

3

/m

3

2.3.4 2.5

Waste Volume PWS m

3

2.3.5

Leaching Duration tp yr 2.3.6 2.7

SI

Area Aw m

2

2.4.1 2.2.2.2

Ponding Depth HP m 2.4.2 2.17

Total Sediment

Thickness

Ds m 2.4.3 2.2.2.2

Liner Thickness Dlin m 2.4.4 2.24b

Liner Conductivity Klin m/yr 2.4.5 2.24b

Depth Below Grade dBG m 2.4.6 2.24b

Leak Density leak holes/m

2

2.4.7 2.24c

Distance to Nearest

Surface Water Body

R m 2.4.8 2.31

Operating

Life/Leaching Duration

tp yr 2.4.9 2.2.2.2

WP

Area Aw m

2

2.5.1 2.27

Operating

Life/Leaching Duration

tp yr 2.5.2 2.27

Depth Below Grade dBG m 2.5.3 2.2.2.2

LAU

Area Aw m

2

2.6.1 2.30

Operating Life/

Leaching Duration

tp yr 2.6.2 2.30

2.2 DATA SOURCES FOR WMU PARAMETERS

Data from two nationwide EPA surveys of non-hazardous (RCRA Subtitle D)

industrial facilities were used to develop databases of EPACMTP input values for

WMU parameters. Data for LFs, WPs, and LAUs were obtained from an EPA

survey of industrial Subtitle D facilities conducted in 1985 (U.S. EPA, 1986, referred
Section 2.0 Waste Management Unit (Source) Parameters

2-5

to as “The 1986 Subtitle D Survey”). The survey provides a statistically

representative subset of observations of site specific areas, volumes and locations

for industrial Subtitle D facilities in the United States. Data for SIs were obtained

from a recent U.S. EPA survey of industrial SIs (U.S. EPA, 2001a, “Surface

Impoundment Study”). What follows is a general description of the data used from

these two studies to compile the databases of WMU input parameters for the

EPACMTP model; the actual distributions of values of these WMU input parameters

are then summarized in Sections 2.3 - 2.6, and are listed in their entirety in Appendix

D.

The WMU locations are shown in Figures 2.2 - 2.5. Information on WMU

locations was used to coordinate other WMU-specific data with climate and

hydrogeological parameter values. Specifically, we first used the HELP (Schroeder,

et. al., 1994) water balance model and climate data from 102 climate stations and

three common soil types to develop infiltration and recharge rates for unlined and

single-lined WMUs (see Section 4.2 and Appendix A). Then, for each WMU site, we

assigned: 1) a climate index corresponding to the nearest, representative climate

station (used to select infiltration and recharge rates) (see Section 4.2); 2) a

hydrogeologic index according to the regional aquifer type used to generate depth

to water and aquifer characteristics (see Sections 5.2 and 5.3); and 3) a soil and

aquifer temperature used to calculate hydrolysis transformation rates for organic

constituents (see Sections 3.6.2 and 4.3). This allows appropriate site-based climate

and hydrogeological parameter values to be generated for each site in the WMU

database “on the fly” while the EPACMTP model is running a Monte Carlo analysis.

Landfills

The 1986 Subtitle D Survey provided LF data consisting of 824 observations

of facility locations, area, number of units in the facility, facility design capacity, total

remaining facility capacity, and the relative weight of each facility. The relative

weight was assigned based on the total number of employees working at the facility

and reflects the quantity of the waste managed in that facility. The values of

physical characteristics for each WMU were obtained by dividing the facility values

by the number of units in the facility.

LF data were screened to eliminate unrealistic observations by placing

constraints on the WMU depth and volume . The WMU depth, calculated by dividing

the unit capacity by its area, was constrained to be greater than or equal to 2 feet

(0.67m), and less than or equal to 33 feet (10m); these limits on unit depth were

adopted from a previous analysis used to support the Toxicity Characteristic (TC)

Rule (U.S. EPA, 1990). In addition, the LF volume was constrained to be greater

than the remaining capacity.

A joint distribution was derived from available unit areas correlated with unit

volumes that met the unit depth and remaining capacity constraints. The distribution

was assumed to be lognormal. Random samples of this distribution were used in

cased where the unit area, the unit volume, or both were missing.
Section 2.0 Waste Management Unit (Source) Parameters

2-6

Figure 2.2 Geographic Locations of Landfill WMUs.

If the WMU depth or remaining capacity constrains were violated, the reported unit

volume was replaced with a sample from the joint distribution, based on the reported

unit area, based on the assumption that the reported unit area was more likely to be

correct.

Figure 2.2 shows the geographic locations of LF WMUs used in developing

the EPACMTP database of LF sites. A compete listing of the site-based LF input

parameter values is provided in Appendix D.

Surface Impoundments

The original EPACMTP database of SI input parameter values (based on the

1986 Subtitle D survey) was updated with more complete data derived from the

results of EPA’s recent 5-year study of nonhazardous (Subtitle D) industrial SIs in

the United States (U.S. EPA, 2001a). The Surface Impoundment Study is the

product of a national survey of facilities that operate non-hazardous industrial waste

SIs. The updated database is comprised of SI characteristics from 503 SI units

located at 143 facilities throughout the United States.

The Surface Impoundment Study provided data on impoundment locations,

area, operating depths (depth of ponding in the impoundment), depth of the SI base
Section 2.0 Waste Management Unit (Source) Parameters

2-7

Figure 2.3 Geographic Locations of Surface Impoundment WMUs.

below the ground surface, sludge volume, operational life of the impoundment,

closure plans, and proximity of the impoundment to a surface water body.

The current version of the EPACMTP database of SI sites was compiled for

analyses included in the U.S. EPA Industrial Waste Management Evaluation Model

(U.S. EPA, 2003b). As a result, the database includes assumptions specific to that

effort. Specifically, the thickness of sludge at the bottom of SI units was assumed to

be 0.2 m for all sites; sites with unknown operating lines and no closure plans were

assumed to operate for 50 years; all units were assumed to be built on top of the

ground surface; and unknown distances to the nearest surface water body or

distances given as >2,000 m were set to 5,000 m.

Figure 2.3 shows the geographic locations of SI WMUs (from the Surface

Impoundment Study) used in developing the EPACMTP database of SI sites. Due

to the scale of this map, the individual units at each facility are not shown. A

compete listing of the site-based SI input parameter values is provided in Appendix

D.
Section 2.0 Waste Management Unit (Source) Parameters

2-8

Figure 2.4 Geographic Locations of Waste Pile WMUs.

Waste Piles

The 1986 Subtitle D survey included 847 WP facilities with data on facility

area, number of units, and the total amount of waste placed in the facility (waste

volume) in 1985. Unit values were derived by dividing the facility values by the

number of units in the facility. No screening constraints were placed on the WP

data. The 114 facility areas and the 30 facility waste volumes reporting zero values

were set to 0.005 acres (20 m2) and 0.005 mega-tons (Mton), respectively. These

default values were adopted from a previous analysis used to support the Toxicity

Characteristic (TC) Rule (U.S. EPA, 1990).

Thirty facilities did not report waste volume. All facilities reported facility

area. Missing volume values were replaced by random realizations from the

probability distribution of volume conditioned on area. The conditional distribution

was assumed to be lognormal and was derived from the non-missing unit

area/volume pairs.

Figure 2.4 shows the geographic locations of WP WMUs used in developing

the EPACMTP database of WP sites. A compete listing of the site-based WP input

parameter values is provided in Appendix D.
Section 2.0 Waste Management Unit (Source) Parameters

2-9

Figure 2.5 Geographic Locations of Land Application Unit WMUs.

Land Application Units

The 1986 Subtitle D survey included 352 LAU facilities, with data on location,

area, number of units in each facility, and the total amount of waste managed (waste

volume) in 1985. Individual unit values were derived by dividing the facility values by

the number of units in the facility. Application rates were derived by dividing the

waste managed in 1985 by the site acreage. Unrealistic values were screened from

these data by constraining the waste application rates to be less than 10,000

tons/acre/year. This assumes a maximum application rate of 200 dry tons/acre/year

with a 2% solids content.

Eight did not report waste volume, and twelve were screened out due to the

application rate constraint. Of the 352 facilities, all reported a facility and none were

screened. Three reported zero areas and nine reported zero waste volumes were

set to 0.005 acres (20 m2

) and 0.005 Mton, respectively.

Missing and screened values were replaced by random realizations from the

joint area/volume probability distribution or the corresponding marginal distributions

depending on whether both or only one of either the waste volume or area values

were missing or screened. The joint distribution was assumed to be lognormal and

was derived from the non-missing unit area/volume pairs that met the unit depth

constraint.

Figure 2.5 shows the geographic locations of LAU WMUs used in developing

the EPACMTP database of LAU sites. A compete listing of the site-based database

of LAU input parameter values is provided in Appendix D.
Section 2.0 Waste Management Unit (Source) Parameters

2-10

2.3 LANDFILLS (LF)

This section discusses the individual WMU-related parameters required to

perform a LF analysis using EPACMTP. Most applications of EPACMTP are for

national or regional regulatory development purposes, in which case, each of the

following LF input parameters is described using a probability distribution. The

default distributions are described in the following sections. However, EPACMTP

can also be used in a location-waste-specific mode; in this case, each of the

following LF input parameters could be assigned a site-specific constant value or a

site-specific distribution of values. These site-specific data need to be gathered by

the user prior to performing the EPACMTP modeling analysis. However, sitespecific implementation of EPACMTP will yield results which may not reflect the sitespecific heterogeneities and anisotropic conditions.

The source-specific input parameters for the LF scenario include parameters

to determine the amount of waste disposed in the LF and the source leaching

duration. Together with the infiltration and recharge rates and the initial waste and

leachate concentrations, these parameters are used to determine how much

contaminant mass enters the subsurface and over what time period. The sourcespecific parameters for the LF scenario are individually described in the following

sections.

2.3.1 Landfill Area (Aw)

Definition

The LF area is defined as the footprint of the LF. EPACMTP assumes the

LF to be rectangular. By default, the length and width of the LF are each calculated

as the square root of the area.

Parameter Value or Distribution of Values

The entire distribution is presented in Appendix D. The cumulative frequency

distribution of LF area is listed in Table 2.2. For a given percentile (%) frequency

and area value pair in this table, the percentile denotes the relative frequency or

likelihood of parameter values in the entire distribution being less than or equal to

the corresponding parameter value in the right-hand column.
Section 2.0 Waste Management Unit (Source) Parameters

2-11

Table 2.2 Cumulative Frequency Distribution of Landfill Area.

% Area (m2

)

0

10

25

50

75

80

85

90

95

100

4.05E+01

4.86E+02

2.43E+03

1.21E+04

5.26E+04

6.56E+04

9.11E+04

1.42E+05

2.23E+05

3.12E+06

Data Sources

The data for LF area listed in Table 2.2 were obtained from EPA’s 1986

Subtitle D Survey (U.S. EPA, 1985).

Use In EPACMTP

The LF area is used to determine the area over which leachate enters the

subsurface. It is also one of several parameters used to calculate the total

contaminant mass present in the LF at closure. The total contaminant mass is a

necessary input when using the LF depleting source option, since the contaminant is

leached to the subsurface until the waste in the LF is depleted (see Section 2.2.1.3.3

of the EPACMTP Technical Background Document; U.S. EPA, 2003a).

2.3.2 Landfill Depth (DLF)

Definition

The LF depth is defined as the average depth of the LF, from top to bottom;

the thickness of the cover soil is assumed to be small compared to the depth. Note

that the LF depth is measured from the top to the base of the unit, irrespective of

where the ground surface is.

Parameter Value or Distribution of Values

The entire distribution is presented in Appendix D. The cumulative frequency

distribution of LF depth is listed in Table 2.3. For a given percentile (%) frequency

and value pair in this table, the percentile denotes the relative frequency or likelihood

of parameter values in the entire distribution being less than or equal to the

corresponding parameter value in the right-hand column.
Section 2.0 Waste Management Unit (Source) Parameters

2-12

Table 2.3 Cumulative Frequency Distribution of Landfill Depth.

% Depth (m)

0

10

25

50

75

80

85

90

95

100

5.10E-01

8.80E-01

1.32E+00

2.57E+00

4.09E+00

4.53E+00

5.20E+00

6.13E+00

7.12E+00

1.01E+01

Data Sources

Data for the nationwide distribution of LF depths was obtained from the 1986

Subtitle D survey (EPA, 1986).

Use In EPACMTP

The LF depth is one of several parameters used to calculate the contaminant

mass within the LF; the contaminant mass is an important input for the LF depleting

source option (see Section 2.2.1.3.3 of the EPACMTP Technical Background

Document; U.S. EPA, 2003a).

2.3.3 Landfill Base Depth below Grade (dBG)

Definition

The depth below grade is defined as the depth of the bottom of the LF below

the surrounding ground surface, as schematically depicted in Figure 2.6.
Section 2.0 Waste Management Unit (Source) Parameters

2-13

Figure 2.6 WMU with Base Elevation below Ground Surface.

Parameter Value or Distribution of Values

Data for this parameter were not included in the EPA’s 1986 Industrial

Subtitle D Survey. Unless site-specific data are available, users should set this

parameter to zero, which is equivalent to assuming the base of the unit lies on the

ground surface.

Data Sources

No nationwide distribution of values is currently available. For LF modeling

analyses, this parameter value is typically set to zero, unless site-specific data are

available.

Use In EPACMTP

If a non-zero value is entered for this input, then the thickness of the vadose

zone beneath the LF is adjusted accordingly. In this case, EPACMTP will also verify

that the entered value, in combination with the depth to the water table, and

magnitude of the unit’s infiltration rate, does not lead to a physically infeasible

condition (e.g.,the LF base is not in contact with a static water table or an infiltrationinduced water table mound) in accordance with the infiltration screening

methodology presented in Section 2.2.5 of the EPACMTP Technical Background

Document (EPA, 2003a).
Section 2.0 Waste Management Unit (Source) Parameters

2-14

2.3.4 Waste Fraction (Fh)

Definition

The waste fraction is defined as the fraction of the LF volume occupied by

the modeled waste at LF closure.

Parameter Value or Distribution of Values

By default, this parameter is defined as a uniform distribution with lower and

upper bounds of 0.036 to 1.0, respectively. However, if warranted by site-specific

conditions or other assumptions, this parameter can also be set to 1.0 (the most

protective case – equivalent to a monofill scenario), another constant value, or

another distribution of values.

Data Sources

The default lower bound of 0.036 (which ensures that the modeled waste unit

will always contain a minimum amount of the waste of concern), was obtained from

an analysis of waste composition in municipal LFs (Schanz and Salhotra, 1992).

The upper bound is the maximum value that is physically possible (the waste in the

LF is composed completely of the waste of concern).

Note that an input value for this parameter is required for the LF scenario

only.

Use In EPACMTP

EPACMTP uses the waste fraction to calculate the contaminant mass within

the LF; the contaminant mass is an important input for the LF depleting source

option (see Section 2.2.1.3.3 of the EPACMTP Technical Background Document;

U.S. EPA, 2003a).

2.3.5 Waste Volume (PWS)

Definition

The waste volume is defined as the volume of the waste of interest (at LF

closure) contributed to the Subtitle D LF.
Section 2.0 Waste Management Unit (Source) Parameters

2-15

Parameter Value or Distribution of Values

The waste volume is an input parameter that depends on the EPACMTP

application. For nationwide risk assessments, EPA has typically assumed a default

uniform distribution, where the waste volume is entered as a fraction of the entire

landfill volume (see Waste Fraction in Section 2.3.4). If the landfill volume and the

waste volume are treated as random parameters, specifying the waste volume in

terms of a waste fraction ensures that the modeled waste volume can never exceed

the modeled landfill volume.

For site-specific applications of EPACMTP, the waste volume that is entered

as an EPACMTP input parameter can be calculated by multiplying the annual waste

volume by the number of years of landfill operation. If the annual waste amount is

given as a mass value (e.g., tons/year), it should be divided by the waste density in

order to yield the value as a volume. The user should ensure that the modeled

waste volume does not exceed the landfill volume.

Data Sources

Data sources depend on the EPACMTP application and are typically

provided by waste generation data. For nationwide LF modeling analyses, this

parameter is typically specified in terms of a waste fraction.

Use In EPACMTP

EPACMTP uses the waste volume to calculate the contaminant mass within

the LF; the contaminant mass is an important parameter for the LF depleting source

option (see Section 2.2.1.3.3 of the EPACMTP Technical Background Document;

U.S. EPA, 2003a).

2.3.6 Leaching Duration (tp

)

Definition

The leaching duration is defined as the period of time that leachate is

released from the WMU.

Parameter Value or Distribution of Values

By default, this parameter is set as a “derived” parameter to be calculated

internally by EPACMTP as a function of the total amount of contaminant that is

initially present in the landfill, and the rate of removal through the leaching process.

Alternatively, the user may set this parameter to a specific constant value or a

distribution of values.
Section 2.0 Waste Management Unit (Source) Parameters

2-16

Data Sources

No nationwide distribution of values is currently available. For LF modeling

analyses, this parameter is typically set to be internally derived by EPACMTP.

Use In EPACMTP

If the leaching duration is set to a user-provided value or distribution,

EPACMTP will model the LF using a pulse source (leaching at a constant

concentration over a finite, pre-defined time period).

More commonly, the LF is modeled as a permanent waste management unit;

in this case, the EPACMTP model assumes that leaching continues until the waste is

depleted. To model this depleting source scenario, this input parameter should be

specified as internally derived by EPACMTP. For a detailed discussion of how the

LF source depletion rate is calculated, see Section 2.2.1.3.3 of the EPACMTP

Technical Background Document (U.S. EPA, 2003a).

2.4 SURFACE IMPOUNDMENT (SI)

This section discusses the individual WMU-related parameters required to

perform a SI analysis using EPACMTP. Most applications of EPACMTP are

conducted on a national or regional basis for regulatory development purposes, in

which case, most of the following SI input parameters would be described using the

default probability. Distributions are discussed in the following sections. However,

EPACMTP can also be used in a location- or waste-specific mode; in this case, each

of the following SI input parameters could be assigned a site-specific constant value

or a site-specific distribution of values. These site-specific data need to be gathered

by the user prior to performing the EPACMTP modeling analysis.

The source-specific inputs for the SI scenario include parameters to

determine the unit dimensions, ponding depth, and leaching duration. Together with

the infiltration and recharge rates and the leachate concentration, these parameters

are used to determine how much contaminant mass enters the subsurface and over

what time period.

The source-specific parameters for the SI scenario are individually described

in the following sections, and Figure 2.7 illustrates a compartmentalized SI as

implemented in the EPACMTP model. Shown in the figure are, in descending order:

the liquid compartment, the sediment compartment (with loose and consolidated

sediments), and the vadose zone (with clogged and unaffected native materials).
Section 2.0 Waste Management Unit (Source) Parameters

2-17

Figure 2.7 Schematic Cross-Section View of SI Unit.

2.4.1 Surface Impoundment Area (Aw)

Definition

The SI area is defined as the footprint of the impoundment. In EPACMTP,

the impoundment is assumed to be rectangular. By default the unit is assumed to

be square, i.e., to have equal length and width which are each calculated as the

square root of the area.

Parameter Value or Distribution of Values

The entire distribution is presented in Appendix D. The cumulative frequency

distribution of SI area is listed in Table 2.4. For a given percentile (%) frequency

and value pair in this table, the percentile denotes the relative frequency or likelihood

of parameter values in the entire distribution being less than or equal to the

corresponding parameter value in the right-hand column.
Section 2.0 Waste Management Unit (Source) Parameters

2-18

Table 2.4 Cumulative Frequency Distribution of Surface Impoundment Area.

% Area (m2

)

0

10

25

50

75

80

85

90

95

100

9.30E+00

1.74E+02

4.01E+02

1.77E+03

6.97E+03

8.90E+03

1.67E+04

2.83E+04

5.16E+04

4.86E+06

Data Sources

The data for SI area listed in Table 2.2 were obtained from EPA’s Surface

Impoundment Study (U.S. EPA, 2001a).

Use In EPACMTP

The SI area represents the total surface area over which infiltration and

leachate enter the subsurface.

2.4.2 Surface Impoundment Ponding Depth (Hp

)

Definition

The ponding depth is the average depth of the wastewater in the liquid

compartment as shown in Figure 2.7; that is, this value does not include any

sediment accumulated at the base of the unit.

Parameter Value or Distribution of Values

The entire distribution is presented in Appendix D. The cumulative frequency

distribution of SI ponding depth is listed in Table 2.5. For a given percentile (%)

frequency and value pair in this table, the percentile denotes the relative frequency

or likelihood of parameter values in the entire distribution being less than or equal to

the corresponding parameter value in the right-hand column.
Section 2.0 Waste Management Unit (Source) Parameters

2-19

Table 2.5 Cumulative Frequency Distribution of Surface Impoundment

Ponding Depth.

% SI Ponding Depth (m)

0

10

25

50

75

80

85

90

95

100

1.00E-02

4.60E-01

9.93E-01

1.81E+00

2.95E+00

3.44E+00

3.66E+00

4.24E+00

5.32E+00

1.82E+01

Data Sources

Data for the nationwide distribution of SI ponding depths was obtained from

the 2001 Surface Impoundment Study (EPA, 2001a).

Use In EPACMTP

The SI ponding depth is added to the unconsolidated sediment thickness

(one-half of the total sediment thickness; see Section 2.4.4); this sum represents the

hydraulic head that drives leakage of water from the SI. EPACMTP uses this

parameter in order to calculate SI infiltration rates (see Section 4.3.4).

2.4.3 Surface Impoundment Total Thickness of Sediment (Ds

)

Definition

The SI total thickness of sediment is the average thickness of accumulated

sediment (sludge) deposits on the bottom of the impoundment. This layer of

accumulated sediment is different from an engineered liner underneath the

impoundment, but its presence will serve to restrict the leakage of water from an

impoundment, especially in unlined units. The EPACMTP model assumes that the

accumulated sediment consists of two equally thick layers, an upper unconsolidated

layer and a lower consolidated layer (‘filter cake’) that has been compacted due to

the weight of the sediment and wastewater above it, and, therefore, has a reduced

porosity and permeability.
Section 2.0 Waste Management Unit (Source) Parameters

2-20

Parameter Value or Distribution of Values

A default value of 0.2m was adopted for the development of EPA’s Industrial

Waste Management Evaluation Model (U.S. EPA, 2003b). This agrees with the

determination EPA made for values in the SI module of EPACMTP. Alternative data

on this parameter are available, and can be extracted from EPA’s Surface

Impoundment Survey. However, these data have not currently been included in

EPACMTP database of SI sites. See Section 2.2 for more information on the SI site

database.

Data Sources

Data on SI sediment thicknesses were acquired from the nationwide 2001

Surface Impoundment Study (EPA, 2001a).

Use In EPACMTP

The EPACMTP model uses the SI sediment thickness to calculate the rate of

infiltration from unlined and single-lined SIs (see Section 4.2). The calculated

infiltration rate is inversely related to the thickness of the sediment layer assuming

constant ponding depth. A lower value for sediment thickness will result in a higher

infiltration rate, and a greater rate of constituent loss from the impoundment. A

detailed description of the EPACMTP SI infiltration module is provided in Section

2.2.2.3 of the EPACMTP Technical Background Document (U.S. EPA, 2003a).

2.4.4 Surface Impoundment Liner Thickness (Dlin

)

Definition

EPACMTP is able to account for infiltration through a single compacted clay

liner beneath the SI. In the event that the SI is single-lined, the thickness of the liner

must be provided. The liner thickness is defined as the average thickness of the

single completed clay liner by which the SI is underlain. Additionally, the base of a

lined SI is defined to be the interface between the liner and the native soils below.

This definition permits EPACMTP to establish the elevation of the top of the liquid

compartment relative to the unit base.

Parameter Value or Distribution of Values

As a default, EPA has assumed the SI clay liner thickness to be a constant

3 ft. or 0.916 m for nationwide or regional analyses. However, liner thickness can be

represented by a distribution with the limitation that the minimum value be greater

than zero. The clay liner is not allowed to be less than 0.1m to ensure numeric

stability of the unsaturated zone flow simulation module.
Section 2.0 Waste Management Unit (Source) Parameters

2-21

Data Sources

The default liner thickness of 3 feet is based on typical design criteria for

compacted clay liners underneath land disposal units (U.S. EPA, 2003b).

Use In EPACMTP

The EPACMTP model uses the SI liner thickness to calculate the rate of

infiltration from the unit (see Section 4.2). The calculated infiltration rate is inversely

related to the thickness of the liner assuming constant ponding depth. A detailed

description of the EPACMTP SI infiltration module is provided in Section 2.2.2.3 of

the EPACMTP Technical Background Document (U.S. EPA, 2003a).

2.4.5 Surface Impoundment Liner Conductivity (Klin

)

Definition

The liner hydraulic conductivity is defined as the average saturated hydraulic

conductivity of the clay liner mentioned in Section 2.4.4.

Parameter Value or Distribution of Values

By default, EPA has assumed the SI liner conductivity for compacted clay

liners to be a constant 1.0 x 10

-7

cm/s or 3.15 x 10

-2 m/yr for nationwide and regional

analyses. However, liner conductivity can be represented by any value or

distribution of values with the limitation that the minimum liner conductivity must be

greater than zero.

Data Sources

The default value of 1 x 10

-7

cm/sec is based on typical design criteria for

compacted clay liners beneath land disposal units and is the maximum

recommended hydraulic conductivity for a compacted clay liner given in the EPA’s

Guide for Industrial Waste Management (U.S. EPA, 2003; EPA530-R-03-001).

Use In EPACMTP

The EPACMTP model uses the SI liner conductivity to calculate the rate of

infiltration from the WMU (see Section 4.2). The calculated infiltration rate is directly

related to the conductivity of the liner, assuming constant ponding depth. A detailed

description of the EPACMTP SI infiltration module is provided in Section 2.2.2.3 of

the EPACMTP Technical Background Document (U.S. EPA, 2003a).
Section 2.0 Waste Management Unit (Source) Parameters

2-22

2.4.6 Surface Impoundment Base Depth Below Grade (dBG)

Definition

This parameter represents the depth of the base of the unit below the

surrounding ground surface, as schematically depicted in Figure 2.6.

Parameter Value or Distribution of Values

The default distribution is presented in Appendix D. The cumulative

frequency distribution of SI depth below grade is summarized in Table 2.6. For a

given percentile (%) frequency and value pair in this table, the percentile denotes the

relative frequency or likelihood of parameter values in the entire distribution being

less than or equal to the corresponding parameter value in the right-hand column.

Table 2.6 Cumulative Frequency Distribution of Surface Impoundment Depth

Below Grade.

% SI Depth Below Grade (m)

0

10

25

50

75

80

85

90

95

100

0.00E+00

0.00E+00

0.00E+00

1.22E+00

3.05E+00

3.58E+00

3.90E+00

4.57E+00

5.18E+00

3.35E+01

Data Sources

Data for this nationwide distribution for SI base depth below grade from the

2001 Surface Impoundment Study (EPA, 2001a).

Use In EPACMTP

The depth of the base of the unit below the ground surface reduces the travel

distance through the unsaturated zone before leachate constituents reach the water

table. If a non-zero value is entered, EPACMTP will verify that the entered value, in

combination with the depth to the water table, and magnitude of the unit’s infiltration

rate, does not lead to a physically infeasible condition (e.g., water table mound

height above the ground surface or above the level of the waste liquid in an

impoundment) in accordance with the infiltration screening methodology presented

in Section 2.2.5 of the EPACMTP Technical Background Document (EPA, 2003a).
Section 2.0 Waste Management Unit (Source) Parameters

2-23

2.4.7 Surface Impoundment Leak Density (leak)

Definition

EPACMTP can also account for infiltration through composite liners. The

infiltration is assumed to result from defects (pinholes) in the geomembrane. The

pinholes are assumed to have a circular shape and be uniform in size. The leak

density is defined as the average number of circular pinholes per hectare.

Parameter Value or Distribution of Values

The cumulative frequency distribution of SI composite liner leak density is

listed in Table 2.7.

Table 2.7 Cumulative Frequency Distribution of Leak Density for CompositeLined SIs.

% Leak density (No. Leaks/ha)

0 0

10 0

20 0

30 0

40 0.7

50 0.915

60 1.36

70 2.65

80 4.02

90 4.77

100 12.5

Data Sources

A nationwide, default distribution of leak densities (expressed as number of

leaks per hectare) have been compiled from 26 leak density values reported in

TetraTech (2001). The leak densities are based on liners installed with formal

Construction Quality Assurance (CQA) programs.

Use In EPACMTP

The EPACMTP model uses composite liner leak density to calculate the rate

of infiltration from composite-lined SIs (see Section 4.2). The calculated infiltration

rate is directly related to the leak density of the liner. A lower value of leak density

will result in a lower infiltration rate. A detailed description of the EPACMTP SI
Section 2.0 Waste Management Unit (Source) Parameters

2-24

infiltration module is provided in Section 2.2.2.3 of the EPACMTP Technical

Background Document (U.S. EPA, 2003a).

2.4.8 Distance to Nearest Surface Water Body (R)

Definition

The distance to the nearest permanent surface water body (that is, a river,

pond or lake); note that this distance can be measured in any direction, not only in

the downgradient direction.

Parameter Value or Distribution of Values

The data from the Surface Impoundment Study indicated a distribution of

values with a range of 30 m to 5,000 m (up to 3.1 miles), and a median value of 360

m. The entire distribution is presented in Appendix D for this parameter. The

cumulative frequency distribution is summarized in Table 2.8. For a given percentile

(%) frequency and value pair in this table, the percentile denotes the relative

frequency or likelihood of parameter values in the entire distribution being less than

or equal to the corresponding parameter value in the right-hand column.

Table 2.8 Cumulative Frequency Distribution of Distance to Nearest Surface

Water Body.

% Distance to Nearest Surface Water Body (m)

0

10

25

50

75

80

85

90

95

100

0.00E+00

9.00E+01

2.40E+02

3.60E+02

8.00E+02

1.17E+03

1.60E+03

5.00E+03

5.00E+03

5.00E+03

Data Sources

Data from the EPA’s Surface Impoundment Study (EPA, 2001a) were used

to assign a distance value to each SI unit in the default EPACMTP database of

WMU sites.
Section 2.0 Waste Management Unit (Source) Parameters

2-25

Use In EPACMTP

In the case of deep unlined impoundments, EPACMTP may calculate very

high SI infiltration rates. EPACMTP checks against the occurrence of excessively

high rates by calculating the estimated height of groundwater mounding underneath

the WMU, and if necessary reduces the infiltration rate to ensure the predicted water

table does not rise above the ground surface. The infiltration screening

methodology is described in detail in Section 2.2.5 of the EPACMTP Technical

Background Document (EPA, 2003a). This screening procedure requires as input

the distance to the nearest point at which the water table elevation is kept at a fixed

value. Operationally, this is taken to be the distance to the nearest surface water

body.

2.4.9 Surface Impoundment Leaching Duration (tp

)

Definition

The time period during which leaching from the SI unit occurs. For SIs, the

addition and removal of waste during the operational life period are assumed t be

more or less balanced, without significant net accumulation of waste. Additionally,

industrial SIs are, at the end of their operational life, typically dredged and backfilled.

Even if simply abandoned, the waste in the impoundment will drain and/or evaporate

relatively quickly. Consequently, in the finite source implementation for SIs, the

duration of the leaching period is assumed to be the same as the operational life of

the SI.

Parameter Value or Distribution of Values

In a typical SI modeling analysis, the SI is modeled as a temporary waste

management unit. In this case, if site-specific data are not available, the user can

make use of the distribution of SI operating life values summarized in Table 2.9 and

presented in their entirety in Appendix D. For a given percentile (%) frequency and

value pair in this table, the percentile denotes the relative frequency or likelihood of

parameter values in the entire distribution being less than or equal to the

corresponding parameter value in the right-hand column.
Section 2.0 Waste Management Unit (Source) Parameters

2-26

Table 2.9 Cumulative Frequency Distribution of Surface Impoundment

Operating Life.

% SI Operating Life (yr)

0

10

25

50

75

80

85

90

95

100

4.00E+00

1.50E+01

5.00E+01

5.00E+01

5.00E+01

5.00E+01

5.00E+01

5.00E+01

5.00E+01

9.50E+01

Data Sources

Data used to define this nationwide distribution of unit-specific operational

lives for SIs were obtained from information in the Surface Impoundment Study on

present age of the unit and the planned closing date (EPA, 2001a). If this

information was missing, we assigned an operational life of 50 years.

Use In EPACMTP

EPACMTP assumes that the duration of the leaching period is equal to the

unit’s operational life; this leaching duration is then used to assign the length of the

pulse-source boundary condition in the EPACMTP fate and transport simulation.

2.5 WASTE PILE (WP)

This section discusses the individual WMU-related parameters required to

perform a WP analysis using EPACMTP. Most applications of EPACMTP are

conducted on a national or regional basis for regulatory development purposes, in

which case, most of the WP input parameters could be defined using a default

probability distribution, described in the following sections. However, EPACMTP can

also be used in a location- or waste-specific mode; in this case, each of the following

WP input parameters could be assigned a site-specific constant value or a sitespecific distribution of values. These site-specific data need to be gathered by the

user prior to performing the EPACMTP modeling analysis.

The WMU-specific input parameters for the WP scenario include the area of

the WP, the source leaching duration, and the depth of the base of the unit below

grade. Together with the leachate concentration, infiltration rate, and recharge rate,

these three parameters are used to determine how much contaminant mass enters
Section 2.0 Waste Management Unit (Source) Parameters

2-27

the subsurface from the base of the WP over what time period. These WP input

parameters are described in the following sections.

2.5.1 Waste Pile Area (Aw)

Definition

The WP area is defined as the footprint of the unit. In EPACMTP, the WP is

modeled as being rectangular. By default, the WMU is assumed to be square, i.e.,

equal length and width. Thus, the length and width of the WP are each calculated

as the square root of the area.

Parameter Value or Distribution of Values

The default nationwide distribution is presented in Appendix D. The

cumulative frequency distribution of WP area is summarized in Table 2.10. For a

given percentile (%) frequency and value pair in this table, the percentile denotes the

relative frequency or likelihood of parameter values in the entire distribution being

less than or equal to the corresponding parameter value in the right-hand column.

Table 2.10 Cumulative Frequency Distribution of Waste Pile Area.

% Area (m2)

0

10

25

50

75

80

85

90

95

100

5.06E+00

2.02E+01

2.02E+01

1.21E+02

1.21E+03

2.02E+03

3.72E+03

4.17E+03

1.21E+04

1.94E+06

Data Sources

The data for WP area listed in Table 2.2 were obtained from EPA’s 1986

Subtitle D Survey (U.S. EPA, 1986).

Use In EPACMTP

The WP area represents the total surface area over which infiltration and

leachate enter the subsurface.
Section 2.0 Waste Management Unit (Source) Parameters

2-28

2.5.2 Waste Pile Leaching Duration (tp)

Definition

The time period during which leaching from the WP unit occurs. WPs are a

temporary management scenario in which the addition and removal of waste during

the operational life period are assumed to be more or less balanced, without

significant net accumulation of waste. Typically at the end of the active life of a WP,

the waste material is either removed for land filling, or the WP is covered and left in

place. If the waste is removed, there is no longer a source of potential

contamination. If a WP is covered and left in place, it then becomes equivalent to a

LF and should be regulated as a LF. Consequently, in the finite source

implementation for WPs, the duration of the leaching period will, for practical

purposes, be the same as the operational life of the WP.

Parameter Value or Distribution of Values

Since operational life is not one of the input parameters included in the EPA’s

1986 Subtitle D Survey (U.S. EPA, 1986), EPA has assumed a value of 20 years as

a default value for WP operational life. Alternatively, a distribution of values could

also be used.

Data Sources

The default value of 20 years is based on professional judgement of typical

industrial waste management practices and consistency with EPA regulatory

assessments of the active life of a unit.

Use In EPACMTP

EPACMTP assumes that the duration of the leaching period is equal to the

unit’s operational life; this leaching duration is then used to determine the total

contaminant flux from the WP to the subsurface.

2.5.3 Waste Pile Base Depth below Grade (dBG)

Definition

This parameter represents the depth of the base of the unit below the ground

surface, as schematically depicted in Figure 2.6.

Parameter Value or Distribution of Values

Unless site-specific data are available, users should set this parameter to the

default value of zero, which is equivalent to assuming the base of the unit lies on the

ground surface.
Section 2.0 Waste Management Unit (Source) Parameters

2-29

Data Sources

No survey data on this parameter are currently available. For WP modeling

analyses, this parameter value is typically set to a default value of zero.

Use In EPACMTP

Greater depth of the unit below the ground surface reduces the travel

distance through the unsaturated zone before leachate constituents reach ground

water. If a non-zero value is entered, EPACMTP will verify that the entered value, in

combination with the depth to the water table, and magnitude of the unit’s infiltration

rate, does not lead to a physically infeasible condition (e.g., the WP base is in

contact with a static water table or an infiltration-induced watertable mound) in

accordance with the infiltration screening methodology presented in Section 2.2.5 of

the EPACMTP Technical Background Document (EPA, 2003a).

2.6 LAND APPLICATION UNIT (LAU)

This section discusses the individual WMU-related parameters required to

perform an LAU analysis using EPACMTP. Many applications of EPACMTP are

conducted on a national or regional basis for regulatory development purposes; in

which case, most LAU input parameters would be defined using the default

probability distributions described in the following sections. However, EPACMTP

can also be used in a location-adjusted or waste-specific mode; in this case, each of

the following LAU input parameters could be assigned a site-specific constant value

or a site-specific distribution of values. These site-specific data need to be gathered

by the user prior to performing the EPACMTP modeling analysis.

The WMU-specific input parameters for the LAU scenario include the area of

the LAU and the leaching duration. Together with the leachate concentration,

infiltration rate, and recharge rate, these two parameters are used to determine how

much contaminant mass enters the subsurface from the base of LAU and over what

time period. These LAU input parameters are described in the following sections.

2.6.1 Land Application Unit Area (Aw)

Definition

The LAU area is defined as the footprint of the unit. In EPACMTP, the LAU

is modeled as being rectangular. By default, the WMU is assumed to be square,

i.e., equal length and width. Thus, the length and width of the LAU are each

calculated as the square root of the area.

Parameter Value or Distribution of Values

The default nationwide distribution is presented in Appendix D. The

cumulative frequency distribution of LAU area is summarized in Table 2.11. For a
Section 2.0 Waste Management Unit (Source) Parameters

2-30

given percentile (%) frequency and value pair in this table, the percentile denotes the

relative frequency or likelihood of parameter values in the entire distribution being

less than or equal to the corresponding parameter value in the right-hand column.

Table 2.11 Cumulative Frequency Distribution of Land Application Unit Area.

% Area (m2)

0

10

25

50

75

80

85

90

95

100

2.02E+01

4.05E+01

4.05E+03

4.05E+04

1.82E+05

2.43E+05

4.05E+05

6.48E+05

9.11E+05

8.09E+07

Data Sources

The data for LAU area summarized in Table 2.11 were obtained from EPA’s

1986 Subtitle D Survey (U.S. EPA, 1986).

Use In EPACMTP

The LAU area represents the total surface area over which infiltration and

leachate enter the subsurface.

2.6.2 Land Application Unit Leaching Duration (tp

)

Definition

The time period during which leaching from the LAU occurs. Since LAUs are

typically modeled as temporary waste management units using the pulse (or nondepleting) source scenario, this input is equivalent to the operational life. For LAUs,

the addition and removal of waste (via leaching, biodegradation, etc.) during the

operational life usually are assumed to be more or less balanced, without significant

net accumulation of waste. Once waste application ceases at the end of the

operational life of the LAU, the leachable waste is expected to be rapidly depleted.

Consequently, if the LAU is modeled as a finite source, the duration of the leaching

period will, in most cases be the same as the operational life of the LAU.
Section 2.0 Waste Management Unit (Source) Parameters

2-31

Parameter Value or Distribution of Values

Since operational life is not one of the input parameters included in the EPA’s

1986 Subtitle D Survey (U.S. EPA, 1986), EPA has assumed a value of 40 years as

a default value for LAU operational life. Alternatively, a distribution of values could

also be used.

Data Sources

The default value of 40 years is based on professional judgement of typical

industrial waste management practices and consistency with existing EPA regulatory

assessments on the active life of these units.

Use In EPACMTP

The leaching duration is used to determine the total contaminant flux from

the LAU to the subsurface.
Section 3.0 Waste and Constituent Parameters

3-1

3.0 WASTE AND CONSTITUENT PARAMETERS

This section discusses the individual waste and constituent parameters

required to perform a modeling analysis using EPACMTP. Each of the input

parameters describing the waste and constituent can be specified as a constant

value or as a statistical or empirical distribution of values. As a practical matter,

however, many of these inputs are commonly set to constant values.

When modeling a WMU using a pulse source term (typically done for the SI,

WP, and LAU scenario), the only waste-specific input parameter required by the

model is the leachate concentration. When modeling a LF, the waste volume, waste

density and the waste concentration are also needed by the model (For a complete

listing of the LF source term variables, see Section 2.2.1 of the EPACMTP Technical

Background Document). These additional waste parameters are used to determine

the amount of constituent in the landfill that is available for leaching. The waste

volume is entered in EPACMTP in terms of a fraction of the entire LF volume, and is

discussed in Section 2 of this document, under the source parameters.

The constituent-specific parameters are used to simulate the chemical fate of

constituents as they are transported through the subsurface; these inputs can be

divided into three categories:

1) General and Constitutive Input Parameters

- e.g., molecular weight, molecular diffusion, and regulatory

standard in drinking water.

2) Organic Constituent Specific Input Parameters

- to describe the tendency of the constituent to degrade to form

harmless and/or toxic degradation products; and

- to quantify the capacity of the constituent to adsorb to the

organic components of the soil matrix.

3) Non-Linear Metal Constituent Geochemical Input Parameters

- to determine the mobility of a metal constituent in the

subsurface.

The EPACMTP model simulates the ground-water fate and transport of

waste constituents by using these constituent-specific parameters in conjunction

with the properties of the subsurface.

The waste and constituent parameters are individually described in the

following sections.
Section 3.0 Waste and Constituent Parameters

3-2

3.1 WASTE AND CONSTITUENT PARAMETERS

The input parameters used in EPACMTP to describe the modeled waste and

constituent are listed in Table 3.1.

Table 3.1 Waste and Constituent Parameters

Parameter

Type Parameter Symbol Units Section

Equation

in

EPACMTP

TBD

W

aste

Waste Density hw g/cm

3

3.2.1 2.3

Waste Concentration

(conc. of constituent in

Waste)

CW mg/kg 3.2.2 2.3

Leachate Concentration

(conc. of constituent in

leachate)

CL mg/L 3.2.3 2.1

All C

onstituents

Molecular Diffusion

Coefficient

Di m

2

/yr 3.3.1.1 3.15

Drinking Water Standard DWS mg/L 3.3.1.2

Molecular Weight MW g/mol 3.3.1.3 4.37

Org

anic C

onstituents

Organic Carbon Partition

Coefficient

koc cm

3

/g 3.3.2.1 2.29

Dissolved Phase

Hydrolysis Decay Rate

1 1/yr 3.3.2.2.1 3.13

Sorbed Phase Hydrolysis

Decay Rate

2 1/yr 3.3.2.2.2 3.13

Acid-Catalyzed

Hydrolysis Rate Constant

1/(mol.yr) 3.3.2.2.3

Neutral Hydrolysis Rate

Constant

1/yr 3.3.2.2.4

Base-Catalyzed

Hydrolysis Rate Constant

1/(mol.yr) 3.3.2.2.5

Hydrolysis Reference

Temperature

Tr °C 3.3.2.2.6

Transform

ation Pro

ducts

Degradation Species

Number

 unitless 3.3.2.3.1 4.31

Number of Immediate

Parents

M unitless 3.3.2.3.2 4.31

Species Number of

Immediate Parent

m unitless 3.3.2.3.3 4.31

Speciation Factor lm unitless 3.3.2.3.4 4.31
Table 3.1 Waste and Constituent Parameters (continued)

Section 3.0 Waste and Constituent Parameters

Parameter

Type Parameter Symbol Units Section

Equation

in

EPACMTP

TBD

3-3

M

etal C

onstituents

Metal Identification

Number

ID unitless 3.3.3.2.1 Section

G.4.1.2

(Appendix G)

Soil and Aquifer pH pH standard

units

3.3.3.2.2 Section

G.4.1.2

(Appendix G)

Iron Hydroxide Content FeOx wt % Fe 3.3.3.2.3 Section

G.4.1.2

(Appendix G)

Leachate Organic Acid

Concentration

LOM mol/L 3.3.3.2.4 Section

G.4.1.2

(Appendix G)

Percent Organic Matter %OM unitless 3.3.3.2.5 Section

G.4.1.2

(Appendix G)

Fraction Organic Carbon foc unitless 3.3.3.2.6 Section

G.4.1.2

(Appendix G)

Ground-water Type

(carbonate/

non-carbonate)

IGWT unitless 3.3.3.2.7 Section

G.4.1.2

(Appendix G)

3.2 WASTE CHARACTERISTICS

3.2.1 Waste Density (hw)

Definition

The waste density is defined as the average wet bulk density of the waste,

i.e., mass of waste per unit volume (kg/L or g/cm3) containing the constituent(s) of

concern and should be measured on the waste as disposed, as opposed to a dry

bulk density. This parameter is only used when modeling landfills.

Parameter Value or Distribution of Values

Information on the density of hazardous waste was developed using the

densities of 4 major categories of waste (solvents, paints, petroleum products,

pesticides) and their contributions to the composition of hazardous wastes in Subtitle

D landfills (Schanz and Salhotra, 1992). The results are expressed as an empirical

distribution of waste densities, given in Table 3.2. The default distribution shows a

relatively narrow range of variation, from 0.7 to 2.1 g/cm3

.
Section 3.0 Waste and Constituent Parameters

3-4

For waste-specific applications of EPACMTP, it is recommended to use

appropriate waste-specific data, rather than the default distribution.

Table 3.2 Default Cumulative probability distribution of waste density

Waste Density (g/cm3

) Cumulative Probability

0.7

0.9

1.12

1.13

1.28

1.30

1.33

1.34

1.36

1.46

1.50

1.62

1.63

1.64

1.65

2.10

0

0.530

0.550

0.551

0.553

0.640

0.728

0.815

0.826

0.904

0.905

0.906

0.994

0.995

0.996

0.998

Data Sources

The default data presented in Table 3.2 were developed by Schanz and

Salhotra (1992).

Use In EPACMTP

When modeling a landfill, the EPACMTP model uses the waste density to

convert between waste volume and mass; the total mass of the waste in the landfill

is then used in conjunction with the waste concentration to derive the contaminant

mass available to be leached to the subsurface.

3.2.2 Concentration of Constituent in the Waste (Cw)

Definition

The waste concentration (mg/kg) represents the total fraction of constituent

in the waste which may eventually leach out. Strictly speaking, Cwis the total

leachable waste concentration. However, from a practical perspective, Cw may be

interpreted to represent the total waste concentration and measured accordingly.

This approach will be protective because the measured total waste concentration

should always be at least as high as the more difficult to quantify "leachable" waste

concentration.
Section 3.0 Waste and Constituent Parameters

3-5

The waste concentration used by EPACMTP reflects the average

concentration of the constituent(s) of concern in the waste in the WMU at the time of

closure. Contaminant losses that may occur during the WMU’s active life are not

explicitly modeled in EPACMTP. If such losses are significant, it may be appropriate

to adjust the waste concentration accordingly (see Section 3.2.4) to represent the

remaining constituent concentration available for leaching. However, ignoring these

other loss pathways will be protective for the ground-water pathway analysis.

Parameter Value or Distribution of Values

The waste concentration is waste- and constituent-specific. There is no

default value or distribution for this parameter.

Data Sources

There is no default value or distribution for this parameter. Waste-specific

data should be obtained from appropriate chemical analytical tests on the waste of

interest.

Use In EPACMTP

EPACMTP uses the waste concentration to calculate the contaminant mass

within the landfill; the contaminant mass is an important input for determining the

landfill leaching duration (see Section 2.2.1.3.3 of the EPACMTP Technical

Background Document; U.S. EPA, 2003a).

3.2.3 Concentration of Constituent in the Leachate (CL

)

Definition

The leachate concentration (mg/L) is the mass of the dissolved constituent

per unit volume of water emanating from the base of the WMU. This parameter

provides the boundary condition for the EPACMTP simulation of constituent fate and

transport through the unsaturated and saturated zone. For a continuous or pulse

source, this concentration is constant until leaching stops. For the landfill depleting

source option, the initial leaching concentration value must be provided by the user

as an EPACMTP input parameter; the model then automatically adjusts the value as

the waste is depleted during the simulation.

Parameter Value or Distribution of Values

The leachate concentration is waste- and constituent-specific. There is no

default value or distribution for this parameter.

EPACMTP can accommodate a measured value or distribution of values, as

determined from an appropriate leaching test procedure such as the Toxicity
Section 3.0 Waste and Constituent Parameters

1

Remember that the DAF is calculated by dividing the input leachate concentration by the resulting receptor well concentration. Since

the ground-water transport for organic constituents is linear, if all other model inputs are held constant and the input leachate

concentration is doubled, the receptor well concentration will be doubled – but the DAF will remain the same. For this reason, if

EPACMTP is being used to back-calculate a threshold waste or leachate concentration, the input leachate concentration for an organic

constituent is arbitrary. The value of 1 x 10

6 mg/L is commonly used for this arbitrary concentration simply because its large value

makes insignificant any errors due to numerical oscillations in the transport solution.

3-6

Characteristic Leaching Procedure (TCLP) or the Synthetic Precipitation Leaching

Procedure.

1

If EPACMTP is used to back-calculate a loading or leaching risk-based or

regulatory limit for organic constituents (that is, the DAF is the only required model

output), then the leachate concentration value that is used as an EPACMTP input is

not material and an arbitrary value, such as 1 x 10

6 mg/L, can be used. However, if

a forward risk analysis is being performed for an organic constituent (when the

magnitude of the receptor well concentration is being determined to calculate risk),

then actual analytical concentration(s) is/are used as input to the EPACMTP model.

On the other hand, if the constituent of interest is a metal or inorganic with a

nonlinear sorption isotherm, then the actual value of the leachate concentration is

material to the analysis, no matter if the goal is to calculate risk based on the

resulting receptor well concentration (a forward risk calculation) or to determine a

threshold waste or leachate concentration based on a defined risk level (a backward

risk calculation). The reason for this is that the nonlinear isotherms which can be

used to model the adsorption of metals mean that there is a nonlinear relationship

between the input leachate concentration and the resulting receptor well

concentration. That is, for metals, we can’t calculate a DAF that is constant across

all leachate concentrations. So, even when the goal of the analysis is to determine

an allowable threshold concentration for a metal constituent (a backward risk

calculation), the leachate concentration is an important model input. Such an

analysis will typically require repeated simulations, each with a different leachate

concentration, until the leachate concentration is identified that results in the

receptor well concentration being equal to a given regulatory or risk-based

benchmark concentration. Additionally, when we perform an EPACMTP analysis for

use in a forward risk calculation for metal constituents, actual analytical

concentrations are typically used as input to the EPACMTP model to determine the

resulting risk.
Section 3.0 Waste and Constituent Parameters

3-7

Data Sources

The waste concentration is waste- and constituent-specific. There is no

default value or distribution for this parameter.

Use In EPACMTP

The EPACMTP fate and transport model requires stipulation of the leachate

concentration as a function of time, CL(t). The leachate concentration CL(t) used in

the model directly represents the concentration of the leachate emanating from the

base of the waste management unit, as a boundary condition for the numerical fate

and transport model. EPACMTP accounts for time variation as either a constant

concentration pulse condition, or as an exponentially decreasing leachate

concentration (depleting source).

In the finite source option, the simplest and generally most conservative case

is to assume that the leachate concentration remains constant until all of the initially

present contaminant mass has leached out of the disposal unit. This case is

referred to as the pulse (or non-depleting) source scenario. The boundary condition

for the fate and transport model then becomes a constant concentration pulse, with

defined duration.

A more realistic modeling analysis in the case of a closed landfill with no

continued waste addition to the unit, can be conducted by assuming that linear

equilibrium partitioning between the solid and liquid phase of the waste leads to an

exponential decrease in the leachate concentration over time as a result of depletion

of the source. When using this depleting source option, the user specifies the initial

leaching concentration, and the model automatically adjusts this rate over time

(except for organics with nonlinear isotherms) as explained in Section 2.2.1.3.3 of

the EPACMTP Technical Background Document (U.S. EPA, 2003a).

3.3 CONSTITUENT PHYSICAL AND CHEMICAL CHARACTERISTICS

3.3.1 All Constituents

The molecular diffusion coefficient and the molecular weight are constituentspecific inputs required by the model for all types of constituents and modeling

analyses. In addition, if a finite source analysis is performed, then a value is

required for the applicable drinking water standard for each constituent.

EPACMTP also accounts for constituent-specific transformation and sorption

processes. These are discussed in Sections 3.3.2 and 3.3.3 for organic and metal

constituents, respectively.
Section 3.0 Waste and Constituent Parameters

3-8

3.3.1.1 Molecular Diffusion Coefficient (Di)

Definition

Diffusion is defined as the movement of constituent molecules in an

environmental medium from areas of high constituent concentrations toward areas

with lower constituent concentrations. This process occurs as a result of

concentration gradients. Diffusion can occur both in the absence or presence of

advective flow. In ground-water flow systems, the process of diffusion is quantified

using the diffusion coefficient of the constituent and the concentration gradient of the

constituent in ground water.

The coefficient of molecular diffusion is often negligible compared to the

dispersivity term in the calculation of the dispersion coefficient and is commonly

ignored. However, diffusion can be significant in cases where ground-water velocity

is very low.

Parameter Value or Distribution of Values

The molecular diffusion coefficient is a constituent-specific input parameter

and should be calculated by the user based on the molecular diffusion coefficient in

free water. Molecular diffusion coefficient values for some common organic

constituents are included in Appendix C. If data are not available for the modeled

constituent, this parameter should be set to zero.

Data Sources

The molecular diffusion coefficient values listed in Appendix C were

generated using the Water 9 model (U.S. EPA, 2001b).

Use In EPACMTP

Hydrodynamic dispersion and molecular diffusion are used to calculate the

dispersion coefficient, one of the variables in the transport equation (see Section 4.4

of the EPACMTP Technical Background Document, U.S. EPA, 2000a).

3.3.1.2 Drinking Water Standard (DWS)

Definition

The drinking water standard (mg/L) is the level assumed to be protective. It

may be a Maximum Contaminant Level (MCL) or a health-based number (HBN)

(See Section 5.0 of the IWEM Technical Background Document, U.S. EPA, 2003c)
Section 3.0 Waste and Constituent Parameters

3-9

. Parameter Value or Distribution of Values

The drinking water standard is a constituent-specific input parameter; the

appropriate value must be determined by the user. The default value for this

parameter is zero. The drinking water standard must be expressed in the same units

used for the leachate concentration, usually mg/L. Although a distribution of values

could be used for this input parameter, it is typically specified as a constant value.

Data Sources

Current values for MCLs can be obtained from the EPA’s Office of Ground

Water and Drinking Water (http://www.epa.gov). See Section 5 of the IWEM

Technical Background Document, U.S. EPA, 2003c for a discussion of sources for

HBN values.

Use In EPACMTP

The drinking water standard is used in finite source scenarios when the

depleting landfill source option is invoked to determine the duration of the

exponentially decaying concentration boundary condition (tp). Leaching is assumed

to continue until the constituent concentration in the leachate has dropped below the

drinking water standard. The leaching duration, tp, is determined by setting Equation

2.12 in the EPACMTP Technical Background Document (U.S. EPA, 2003a) equal to

the DWS and solving for t (time).

3.3.1.3 Molecular Weight (MW)

Definition

The molecular weight (g/mol) is defined as the amount of mass in one mole

of molecules of a constituent as determined by summing the atomic weights of the

elements in that constituent, multiplied by their stochiometric factors.

Parameter Value or Distribution of Values

The molecular weight is a constituent-specific input parameter; the

appropriate value must be provided by the user. There is no default value.

Data Sources

Compilations of chemical data such as molecular weight are available on

many web sites and in most chemistry reference books.

Use In EPACMTP

The use of this parameter is reserved for future versions of EPACMTP to

automatically calculate the parent to degradation product yield or decay coefficients

for chain decay simulations.
Section 3.0 Waste and Constituent Parameters

3-10

3.3.2 Organic Constituents

This section describes the parameters used in EPACMTP for organic

constituents. The parameters to be discussed are the organic carbon partition

coefficient, sorbed and dissolved phase hydrolysis decay rate, acid, neutral, and

base-catalyzed hydrolysis rate constants, and the reference temperature.

For organic constituents, EPACMTP takes into account adsorption behavior

of organic constituents by calculating a retardation factor based on the organic

carbon distribution coefficient (koc

) of each constituent and fractional organic carbon

in the soil (foc) (See Section 3.2.1).

In order to model the subsurface fate and transport of organic constituents,

EPACMTP generates a single first-order degradation rate, which includes both

biodegradation and chemical hydrolysis (in both sorbed and dissolved phases). The

biodegradation rate is typically set to zero (due to the difficulty in accurately

estimating it), but a non-zero value can be specified by the user. The user can

directly specify the hydrolysis rates, or they can be internally calculated by the model

(see Section 3.3.2.2). If calculated, EPACMTP requires that the hydrolysis rate

constants and the reference temperature at which they were measured be specified

. EPACMTP then uses these rate constants along with the ground-water

temperature and pH to derive the sorbed-phase and dissolved-phase hydrolysis

rates. These two hydrolysis rates and the biodegradation rate (if non-zero) are then

combined into the overall first-order degradation rate. If the products of this

degradation are themselves toxic, they can be included in the modeling analysis by

specifying them to be part of a decay chain, with the current organic constituent as

the parent chemical.

If desired, the user can override the default of no biodegradation, by

providing appropriate values of the biodegradation rate coefficient for the

unsaturated and saturated zone (see Section 5 of this document).

3.3.2.1 Organic Carbon Partition Coefficient (koc

)

Definition

The organic carbon partition coefficient (cm3

/g) is the ratio of a constituent's

concentration in a theoretical soil containing only organic carbon to its concentration

in the ground water. Thus, koc describes the affinity of a constituent to attach itself to

organic carbon. This parameter is applicable to organic constituents which tend to

sorb onto the organic matter in soil or in an aquifer. Constituents with high koc

values tend to move more slowly through the soil and ground water. Volatile

organics tend to have low koc values, whereas semi-volatile organics often have high

koc values.
Section 3.0 Waste and Constituent Parameters

3-11

(3.1)

(3.2)

Parameter Value or Distribution of Values

The organic carbon partition coefficient is a constituent-specific input

parameter; values for some common organic constituents are included in Appendix

C. Although commonly specified as a constant value, this parameter can also be

specified as a distribution of values. If constituent-specific data for the organic to be

modeled are not available, this input value can be set to zero – a value that means

the constituent’s ground-water concentration will not be decreased due to

adsorption.

Data Sources

Organic carbon partition coefficient (koc) values can be obtained from many

constituent property handbooks, as well as online databases, (e.g., Kollig, Ellington,

Karickhoff, Kitchens, Long, Weber and Wolfe, 1993 or Handbook of Environmental

Data on Organic Constituents, Verschueren, 1983). Sometimes, these references

provide an octanol-water partition coefficient (kow

), rather than a koc value. These

two coefficients are roughly equivalent parameters. A number of conversion

formulas exist to convert kow values into koc; these can be found in handbooks on

environmental fate data (e.g., Verschueren, 1983; Kollig et. al., 1993). This

conversion factor accounts for the mass difference, expressed as a percentage,

between pure organic carbon and natural organic matter which also includes

elements in addition to carbon (Enfield, Carsel, Cohen, Phan and Walters, 1982).

Different conversion formulas exist for different constituents and environmental

media, and there is no single formula that is valid for all organic constituents;

therefore, the conversion formula should be chosen and used with some caution.

Use In EPACMTP

For organic constituents, the effect of equilibrium sorption is expressed in

EPACMTP through the retardation coefficient, R, which is a function of the chemicalspecific organic carbon partition coefficient, koc

:

where

where

R = retardation coefficient for species i (dimensionless)

b = soil bulk density for the unsaturated zone (g/cm3)

 = soil water content (dimensionless)

kd = soil-water partition coefficient (L/kg)

foc = fractional organic carbon content in the soil or aquifer

(unitless)

koc = organic carbon partition coefficient (cm3/g)
Section 3.0 Waste and Constituent Parameters

3-12

(3.3)

(3.4)

The fractional organic carbon can be estimated from the percentage organic

matter (%OM) in the soil or aquifer, as

where

%OM = percent organic matter in the soil (unitless)

174 = conversion factor

3.3.2.2 Parameters Related to Chemical Hydrolysis

The transport of organic constituents can be influenced in part by chemical

hydrolysis, a process that is represented in the EPACMTP model by means of an

overall first-order chemical decay coefficient. This overall decay coefficient includes

both dissolved phase and sorbed phase decay. Dissolved phase and sorbed phase

decay rates can be specified directly, or they can be derived based on chemicalspecific hydrolysis rate constants and the ground-water temperature and pH. In the

latter case, the hydrolysis rate constants for each constituent can be obtained from

reference documents compiled by EPA’s Environmental Research Laboratory in

Athens, GA (U.S. EPA, 1993 and Kollig et al., 1993).

The hydrolysis process as modeled in EPACMTP is affected by aquifer pH,

aquifer temperature, and constituent sorption:

The overall first-order transformation rate for hydrolysis is calculated as:

where:

= Overall first-order hydrolysis transformation rate (1/yr)

1 = Dissolved phase hydrolysis transformation rate (1/yr);

see Section 3.3.2.2.1

2 = Sorbed phase hydrolysis transformation rate (1/yr); see

Section 3.3.2.2.2

 = Porosity (water content in the unsaturated zone)

(dimensionless)

b = Bulk density (kg/L)

kd = Partition coefficient (L/kg)

The calculation of the sorbed phase and dissolved phase hydrolysis rates

from the hydrolysis rate constants is described in the following sections.
Section 3.0 Waste and Constituent Parameters

3-13

(3.5)

3.3.2.2.1 Dissolved Phase Hydrolysis Decay Rate (1)

Definition

Hydrolysis is defined as the decomposition of organic constituents by

interaction with water. The dissolved phase hydrolysis decay rate (1/yr) is the rate at

which the dissolved portion of the contaminant mass is hydrolyzed.

Parameter Value or Distribution of Values

The dissolved phase hydrolysis decay rate can be directly input by the user

(as either a constant value or distribution of values) or it can be set to be internally

derived by the model. In the latter case, it is calculated as follows:

where

1 = First-order decay rate for dissolved phase (1/yr)

= Hydrolysis rate constants; calculated as described in Sections

3.3.2.2.3, 3.3.2.2.4, and 3.3.2.2.5

[H

+

] = Hydrogen ion concentration (mole/L)

[OH

-

] = Hydroxyl ion concentration (mole/L)

[H

+

] and [OH

-

] are computed from the pH of the soil or aquifer using

[H

+

]=10

-pH

[OH

-

]=10

-(14-pH)

Data Sources

In the absence of site-specific data, this parameter typically is set to be derived

by the model based on the constituent-specific hydrolysis rate constants (see Sections

3.3.2.2.3 through 3.3.2.2.6).

Use In EPACMTP

The dissolved phase hydrolysis rate is used to calculate the overall first-order

transformation rate for hydrolysis as presented in Equation 3.4.
Section 3.0 Waste and Constituent Parameters

3-14

(3.6)

3.3.2.2.2 Sorbed Phase Hydrolysis Decay Rate (2

)

Definition

Hydrolysis is defined as the decomposition of organic constituents by interaction

with water. The sorbed phase hydrolysis decay rate (1/yr) is the rate at which the

sorbed portion of the contaminant mass is hydrolyzed.

Parameter Value or Distribution of Values

The sorbed phase hydrolysis decay rate can be directly input by the user (as

either a constant value or distribution of values) or it can be set to be internally derived

by the model. If it is specified in the input file as derived by EPACMTP, the effective

sorbed phase decay rate is calculated as:

where:

2 = First-order hydrolysis rate for sorbed phase (1/yr)

= Acid-catalyzed hydrolysis rate constant (1/mole/yr); see Section

3.3.2.2.3

= Neutral hydrolysis rate constant (1/yr); see Section 3.3.2.2.4

10 = Acid-catalyzed hydrolysis enhancement factor

[H

+

] = Hydrogen ion concentration (computed from the pH of the soil or

aquifer using [H

+

] = 10

-pH

)

Data Sources

In the absence of site-specific data, this parameter typically is set to be derived

by the model based on the constituent-specific hydrolysis rate constants (see Sections

3.3.2.2.3 through 3.3.2.2.6).

Use In EPACMTP

The sorbed phase hydrolysis rate is used to calculate the overall first-order

transformation rate for hydrolysis as presented in Equation 3.4.

3.3.2.2.3 Acid-Catalyzed Hydrolysis Rate Constant

Definition

The tendency of a constituent to hydrolyze is expressed through several

constituent-specific rate constants. The acid-catalyzed rate constant (1/mol-yr) is one

of the values that is used to quantify how the rate of the hydrolysis reaction is affected
Section 3.0 Waste and Constituent Parameters

3-15

(3.7)

by the pH (specifically at the acidic end of pH) of the subsurface. The superscript Tr

indicates that the value is measured at a specified reference temperature.

Parameter Value or Distribution of Values

The acid-catalyzed rate constant is a constituent-specific input parameter;

values for some common organic constituents are included in Appendix C. Although

commonly specified as a constant value, this parameter can also be specified as a

distribution of values. If constituent-specific data for the organic to be modeled are not

available, this input value can be set to zero – a conservative value that means the

constituent’s ground-water concentration will not be decreased due to chemical

hydrolysis at the acidic end of the scale. However, if the modeled constituent

hydrolyzes to form one or more toxic degradation products, then setting this input to

zero and not modeling the formation of the toxic degradation product could result in an

underestimation of the risk of exposure via the ground-water pathway.

Data Sources

values can be obtained from some constituent property handbooks (e.g.,

Kollig et al, 1993 or Handbook of Environmental Data on Organic Constituents,

Verschueren, 1983).

Use In EPACMTP

The acid-catalyzed hydrolysis rate constant is influenced by ground-water

temperature, while acid- and base catalyzed rate constants are also influenced by pH.

As shown below, the Arrhenius equation is used to convert the input hydrolysis rate

constants, measured at a specified reference temperature (Tr), to the actual

temperature of the subsurface:

= Hydrolysis rate constant for reaction process J, corrected for the

subsurface temperature Tr(1/mol-yr for the acid- and basecatalyzed reactions; 1/yr for the neutral reaction)

= Hydrolysis rate constant for reaction process J, measured at

reference temperature T (1/mol-yr for the acid- and base-catalyzed

reactions; 1/yr for the neutral reaction)

J = a for the acid-catalyzed reaction, b for base-catalyzed reaction, and

n for the neutral reaction

T = Temperature of the subsurface (°C)

Tr = Reference temperature (°C)

Rg = Universal gas constant (1.987E-3 Kcal/deg-mole)

Ea = Arrhenius activation energy (Kcal/mole)
Section 3.0 Waste and Constituent Parameters

3-16

Note that, using the generic activation energy of 20 Kcal/mole recommended by

Wolfe (1985), the factor Ea/Rg has a numerical value of 10,000.

The temperature-corrected rate constants are then used in Equations 3.5 and

3.6 to calculate the sorbed phase and dissolved phase hydrolysis rate constants from

which the overall hydrolysis transformation rate is calculated. The overall first-order

transformation rate is one of the parameters required to solve the advection-dispersion

equation (see Sections 3.3.4 and 4.4.4 of the EPACMTP Technical Background

Document (U.S. EPA, 2003a)).

3.3.2.2.4 Neutral Hydrolysis Rate Constant

Definition

The tendency of a constituent to hydrolyze is expressed through several

constituent-specific rate constants. The neutral rate constant (1/yr) is used to quantify

how the rate of the hydrolysis reaction is unaffected by the pH of the subsurface. The

superscript Tr

indicates that the value is measured at a specified reference temperature.

Parameter Value or Distribution of Values

The neutral rate constant is a constituent-specific input parameter; values for

some common organic constituents are included in Appendix C. Although commonly

specified as a constant value, this parameter can also be specified as a distribution of

values. If constituent-specific data for the organic to be modeled are not available, this

input value can be set to zero – a conservative value that means the constituent’s

ground-water concentration (under pH neutral conditions) will not be decreased due to

chemical hydrolysis. However, if the modeled constituent hydrolyzes to form one or

more toxic degradation products, then setting this input to zero and not modeling the

formation of the toxic degradation product could result in an underestimation of the risk

of exposure via the ground-water pathway.

Data Sources

values can be obtained from some constituent property handbooks (e.g.,

Kollig et al, 1993 or Handbook of Environmental Data on Organic Constituents,

Verschueren, 1983).

Use In EPACMTP

As shown in Equation 3.7, the Arrhenius equation is to used convert the input

hydrolysis rate constants, measured at a specified reference temperature (Tr), to the

actual temperature of the subsurface. The temperature-corrected rate constants are

then used in Equations 3.5 and 3.6 to calculate the sorbed phase and dissolved phase

hydrolysis rate constants from which the overall hydrolysis transformation rate is

calculated. The overall first-order transformation rate is one of the parameters required

to solve the advection- dispersion equation (see Sections 3.3.4 and 4.4.4 of the

EPACMTP Technical Background Document (U.S. EPA, 2003a)).
Section 3.0 Waste and Constituent Parameters

3-17

3.3.2.2.5 Base-Catalyzed Hydrolysis Rate Constant

Definition

The tendency of each constituent to hydrolyze is expressed through several

constituent-specific rate constants. The base-catalyzed rate constant (1/mol-yr) is one

of the values that is used to quantify how the rate of the hydrolysis reaction is affected

by the pH of the subsurface, in this case under more alkaline conditions. The

superscript Trindicates that the value is measured at a specified reference temperature.

Parameter Value or Distribution of Values

The base-catalyzed rate constant is a constituent-specific input parameter;

values for some common organic constituents are included in Appendix C. Although

commonly specified as a constant value, this parameter can also be specified as a

distribution of values. If constituent-specific data for the organic to be modeled are not

available, this input value can be set to zero – a conservative value that means the

constituent’s ground-water concentration will not be decreased due to chemical

hydrolysis at the alkaline end of the scale. However, if the modeled constituent

hydrolyzes to form one or more toxic degradation products, then setting this input to

zero and not modeling the formation of the toxic degradation product could result in an

underestimation of the risk of exposure via the ground-water pathway.

Data Sources

The values can be obtained from some constituent property handbooks

(e.g., Kollig et al, 1993 or Handbook of Environmental Data on Organic Constituents,

Verschueren, 1983).

Use In EPACMTP

As shown in Equation 3.7, the Arrhenius equation is used to convert the input

hydrolysis rate constants, measured at a specified reference temperature (Tr), to the

actual temperature of the subsurface. The temperature-corrected rate constants are

then used in Equations 3.5 and 3.6 to calculate the sorbed phase and dissolved phase

hydrolysis rate constants from which the overall hydrolysis transformation rate is

calculated. The overall first-order transformation rate is one of the parameters required

to solve the advection-dispersion equation (see Sections 3.3.4 and 4.4.4 of the

EPACMTP Technical Background Document (U.S. EPA, 2003a)).

3.3.2.2.6 Reference Temperature (Tr)

Definition

The reference temperature (°C) is the temperature at which the input hydrolysis

rate constants were measured.
Section 3.0 Waste and Constituent Parameters

3-18

Parameter Value or Distribution of Values

The chemical-specific hydrolysis rate constants are measured at a constant

reference temperature; the default value is 25 degrees Celsius.

Data Sources

Hydrolysis rate constants can be obtained from some constituent property

handbooks (e.g., Kollig et al, 1993 or Handbook of Environmental Data on Organic

Constituents, Verschueren, 1983). The data source used for the hydrolysis rate

constants should also state the temperature at which the values were measured.

Use In EPACMTP

As shown in Equation 3.7, the reference temperature is used in the Arrhenius

equation to convert the input hydrolysis rate constants to the actual temperature of the

subsurface. The temperature-corrected rate constants are then used in Equations 3.5

and 3.6 to calculate the sorbed phase and dissolved phase hydrolysis rate constants

from which the overall hydrolysis transformation rate is calculated. The overall firstorder transformation rate is one of the parameters required to solve the advectiondispersion equation (see Sections 3.3.4 and 4.4.4 of the EPACMTP Technical

Background Document (U.S. EPA, 2003a)).

3.3.2.3 Parameters Related to Hydrolysis Transformation Products

In the event that the products of this chemical degradation process are toxic and

their constituent-specific parameters are known, they can be included in the simulation

by specifying them to be part of a transformation (or decay) chain. Note that when a

multi-species simulation such as this is performed, the necessary chemical-specific

parameters must be repeated for each species in the decay chain. In addition, the

following parameters are required for each degradation species in a decay chain

analysis: degradation product species number, number of immediate parents for each

degradation product species, species number(s) of immediate parent(s), and fraction

of the parent species that decays into the given degradation product species.

3.3.2.3.1 Degradation Product Species Number ()

Definition

The degradation product species number is an index number that uniquely

identifies a constituent and its properties in EPACMTP.

Parameter Value or Distribution of Values

Degradation product species numbers begin with the number 2 (the parent

species number is 1). Up to 6 degradation products per parent are permitted in

EPACMTP (numbered 2-7).
Section 3.0 Waste and Constituent Parameters

3-19

Data Sources

The degradation product species number is a construction of convenience for

EPACMTP, and as such, there are no data sources. The value of the parameter is

governed by the number of degradation products in a particular transformation chain.

Use In EPACMTP

The degradation product species number allows EPACMTP to track and

associate degradation products with its properties and relationships to its immediate

parent and daughters.

3.3.2.3.2 Number of Immediate Parents (M

)

Definition

The number of immediate parents (M) is defined as the total number of

individual species which degrade directly into degradation product species . This

parameter is used in EPACMTP together with the species number of the immediate

parent (see next section) to represent the structure of the chain decay reaction. The

value of this parameter is zero for the parent species and one for each degradation

product species. The maximum value of Mis one because the EPACMTP model can

handle simulation of only one constituent that has a non-zero initial leachate

concentration (that is, one original parent species per decay chain). For example, if

constituent A degrades into constituent B, and B degrades to C, then degradation

product B has one immediate parent (A) and degradation product C also has one

immediate parent (B).

Parameter Value or Distribution of Values

The number of immediate parent species is governed by the specific

transformation chain to be simulated using EPACMTP.

Data Sources

The number of immediate parent species is governed by the decay chain

reaction being simulated. Reaction chemistry or constituent property handbooks (e.g.,

Kollig et al, 1993, or Handbook of Environmental Data on Organic Constituents,

Verschueren, 1983) may contain chain decay structures for organic constituents.

Use In EPACMTP

The number of immediate parent species of a degradation product species

allows EPACMTP to track its relationships to its immediate parent.
Section 3.0 Waste and Constituent Parameters

3-20

3.3.2.3.3 Species Number(s) of Immediate Parent(s) (m(i), i = 1, M)

Definition

The species number m

(i) of the immediate parent is the ordinal number (see

Section 3.3.2.3.1) of the toxic degradation product that directly degrades into the

degradation product of concern. For example, consider again the straight decay chain

where constituent A degrades into constituent B which degrades into constituent C

shown in the example below:

Parameter Definition

Value for

Constituent A

Value for

Constituent B

Value for

Constituent C

 species

number

1 2 3

M number

(quantity) of

immediate

parents

0 1 1

m(i) species

number of

immediate

parent

0 1 2

Parameter Value or Distribution of Values

The species number of immediate parent species is governed by the specific

decay chain to be simulated using EPACMTP and by the numbering system chosen by

the user.

Data Sources

The numbering of immediate parent species is governed by the decay chain

reaction being simulated and the user's discretion. Reaction chemistry or constituent

property handbooks (e.g., Kollig et al, 1993, or Handbook of Environmental Data on

Organic Constituents, Verschueren, 1983) may contain chain decay structures for

organic constituents.

Use In EPACMTP

The association of an immediate parent to a degradation product species

number allows EPACMTP to track and associate a degradation product with its

properties and relationships to its immediate parent and degradation products.
Section 3.0 Waste and Constituent Parameters

3-21

3.3.2.3.4 Fraction of the Parent Species (m)

Definition

The coefficient m is called the fraction of the parent species which expresses

how many units of species  are produced in the decay of each unit of parent m. The

value of the speciation factor is thus determined by the reaction stoichiometry, as well

as the units used to express concentration. For instance, consider the following

hydrolysis reaction in which 2 units of degradation product B and 1 unit of degradation

product C are formed from the hydrolysis of 3 units of parent A:

where

A = parent compound A

H2O = water molecule

B = degradation product compound B

C = degradation product compound C

(OH)- = hydroxide ion

H+ = hydrogen ion

In this example, BA

is equal to and CAis equal to

where

MW = the molecular weight of species  (g/mol)

BA = speciation factor between parent A and degradation product B

CA = speciation factor between parent A and degradation product C

Parameter Value or Distribution of Values

The value of this parameter is determined by the species and reaction

stoichiometry and is constant for the entire simulation.

Data Sources

The fraction of parent species is governed by the stoichiometry of the decay

chain reaction being simulated and individual constituent properties. Reaction

chemistry or constituent property handbooks (e.g., Kollig et al, 1993, or Handbook of

Environmental Data on Organic Constituents, Verschueren, 1983) may contain chain

decay structures for organic constituents.
Section 3.0 Waste and Constituent Parameters

3-22

Use In EPACMTP

EPACMTP uses the fraction of parent species to determine how much of a

parent species decays to form an immediate daughter. Similarly, the same factor is

used to determine how much degradation product species is produced from its

immediate parent. These relationships are applied in both the unsaturated and

saturated fate and transports simulations (see Equations 3.14 and 4.31, respectively

in the EPACMTP Technical Background Document, (U.S. EPA, 2003a)).

3.3.3 Metals

In the subsurface, metal constituents may undergo reactions with ligands in the

pore water and with surface sites on the solid aquifer or soil matrix material. Reactions

in which the metal is bound to the solid matrix are referred to as sorption reactions and

metal that is bound to the solid is said to be sorbed. The ratio of the concentration of

metal sorbed to the concentration in the mobile aqueous phase at equilibrium is referred

to as the partition coefficient (Kd). During contaminant transport, sorption to the solid

matrix results in retardation of the contaminant front. Thus, transport models such as

EPACMTP incorporate the contaminant partition coefficient into the overall retardation

factor (the ratio of the average linear particle velocity to the velocity of that portion of the

plume where the contaminant is at 50 percent dilution). The use of Kdin EPACMTP

transport modeling implies the assumption that local equilibrium between the solutes

and the sorbents is attained, meaning that the rate of sorption reactions is fast relative

to advective-dispersive transport of the contaminant.

Users can specify a constant value or distribution of values for the Kd(a linear

isotherm); alternatively, tables of non-linear sorption isotherms (for a suite of 21 metals,

some with varying oxidation states) or equations comprising pH-based (linear)

isotherms are available within EPACMTP. Both the non-linear isotherms and the pHbased isotherms were developed especially for use with the EPACMTP model.

The pH-dependent isotherms were developed for 12 metals using the empirical

relationships as described in Loux, Chafin and Hassan (1990). These isotherms were

originally developed as an alternative to the MINTEQA2-derived isotherms (U.S. EPA,

1996 and 1999) because, at that time, there were limitations in the database of

adsorption reactions that made the MINTEQA2 modeling less accurate for metals that

form anions or neutral species in aqueous solution. However, ensuing improvements

in the MINTEQA2 database of adsorption reactions and modeling methodology have

resulted in a new set of non-linear isotherms which supercede the pH-based isotherms.

However, the option to use these pH-based isotherms is still available in the EPACMTP

model, and so they are described in this document.

The non-linear isotherms were estimated using the geochemical speciation

model, MINTEQA2, and are tabulated into auxiliary input files for use by the EPACMTP

model. These isotherms reflect the tendency of Kd

to decrease as the total metal

concentration in the system increases. The non-linear isotherms available for use in

EPACMTP are specified in terms of the dissolved metal concentration and the

corresponding sorbed concentration at a series of total metal concentrations.
Section 3.0 Waste and Constituent Parameters

3-23

For a particular metal, Kd values in a soil or aquifer are dependent upon the metal

concentration and various geochemical characteristics of the soil or aquifer and the

associated pore water. Geochemical parameters that have the greatest influence on

the magnitude of Kd

include the pH of the system and the nature and concentration of

sorbents associated with the soil or aquifer matrix. In the subsurface beneath a

disposal facility, the concentration of leachate constituents may also influence Kd.

Although the dependence of metal partitioning on the total metal concentration and on

pH and other geochemical characteristics is apparent from partitioning studies reported

in the scientific literature, Kd values for many metals are not available for the range of

metal concentrations or geochemical conditions needed in risk assessment modeling.

For this reason, MINTEQA2 was used to estimate partition coefficients. The use of a

speciation model allows Kd values to be estimated for a range of total metal

concentrations in various model systems designed to depict natural variability in those

geochemical characteristics that most influence metal partitioning.

The development of these non-linear (concentration-dependent) metal partition

coefficients is described in Appendix B.1. The following sections describe the available

options and the input parameters required to perform ground-water fate and transport

modeling of metal constituents using the EPACMTP model.

3.3.3.1 Empirical Kd Data

There are two sources of empirical Kd data that can be used to model metals

transport using linear isotherms: Kd data compiled from a recent comprehensive

literature survey and pH-based isotherms that are based on the empirical laboratorybased data of Loux et al (1990). These two types of empirical Kd data are described

in the following sections.

3.3.3.1.1 Kd Data Compiled from a Literature Survey

In the absence of site-specific data, the distribution coefficient for metals can be

specified as a statistical or empirical distribution of values. A comprehensive literature

review of Kd values was conducted for the EPA’s RCRA Hazardous Waste Listing

Determination for Inorganic Chemical Manufacturing Wastes (U.S. EPA, 2000). For this

project, Kd was defined as an empirical distribution of values when sufficient data were

available (six or more literature Kd values) or as a log uniform distribution of values

when fewer data were found in the scientific literature (five or fewer literature Kd values).

This literature review focused on identifying and compiling experimentally derived Kd

values for soil and aquifer materials from published literature. Collected values were

compiled along with geochemical and measurement parameters most likely to influence

Kd. Details of the literature search and data collection strategy are given in Appendix

I of the Risk Assessment for the Listing Determination for Inorganic Chemical

Manufacturing Wastes: Background Document (U.S. EPA, 2000) along with the

resulting distributions of Kd values.

If site-specific Kd data are unavailable, the EPACMTP user can specify that one

of these default distributions be used for the coefficient of the Freundlich isotherm for

the unsaturated and saturated zones. That is, the appropriate distribution, gleaned
Section 3.0 Waste and Constituent Parameters

3-24

from (U.S. EPA, 2000), should be entered twice in the EPACMTP input file, once in the

unsaturated zone parameter group and again for the aquifer parameter group.

3.3.3.1.2 pH-based Isotherms

pH-dependent isotherms for 15 metal species were determined from empirical

relationships as described in Loux et al., 1990. Many of these metals form anions or

neutral species in aqueous solution (e.g., HAsO3

2-

, H2AsO3

-

, and H3AsO3

0

).

The pH-dependent empirical relationships were determined from linear least

squares analysis of laboratory measurements from aquifer materials and their

corresponding ground water and leachate samples collected from six municipal landfills,

as well as other published data. In these experiments, the concentrations of trace metal

contaminants in the ground-water/aquifer material samples were augmented with

additions (spikes), and the spiked samples were allowed to equilibrate for 48 hours.

After equilibration, the trace metal remaining in solution was measured. The difference

between the total trace metal in the system (the metal originally in the sample plus the

amount added) and the amount remaining in solution at equilibrium was regarded as

adsorbed. The distribution coefficient was determined as the ratio of amount of trace

metal adsorbed to the amount remaining in solution. The resulting relationships give

Kd as a function of pH only; the inherent nonlinear character of metal adsorption as a

function of total metal concentration is not represented.

In EPACMTP Monte Carlo analyses for nationwide assessments, a different pH

value is generated for each Monte Carlo iteration. Upon the selection of a pH, the

correspondingKdis automatically calculated from the appropriate empiricalrelationship.

No empirical relation was available for Sb

III

; so the Sb

V

relationship can be used

for both the +3 and +5 oxidation states. Also, the As

III

species is adsorbed somewhat

less strongly than As

V

, and Se

VI

is adsorbed less strongly than Se

IV

. However, the

contrast in adsorption affinity between different oxidation states for these metals is not

nearly so marked as the contrast in Cr

III and CrVI

. Therefore, the As

III and SeVI

relationships can be used to represent both oxidation states for these metals. The

resulting empirical relationships are presented in Table 3.3.
Section 3.0 Waste and Constituent Parameters

3-25

Table 3.3 Empirical pH-dependent Adsorption Relations (Loux et al., 1990)

Metal Species Kd

(liters kg

-1

)

As

III

10

(0.0322 pH + 1.24)

Ba

II

10

(0.190 pH + 0.638)

Cd

II

10

(0.397 pH - 0.943)

Cr

VI

10

(-0.117 pH + 2.07)

Hg

II

10

(0.122 pH + 1.42)

Ni

II

10

(0.332 pH - 0.471)

Pb

II

10

(0.0768 pH + 1.55)

Sb

V

10

(-0.207 pH + 2.996)

Se

VI

10

(-0.296 pH + 2.71)

Tl 10

(0.110 pH + 1.102)

3.3.3.2 MINTEQA2-Derived Sorption Isotherm Data

In the absence of site-specific data, the distribution coefficient for metals can be

automatically drawn from tabulated data comprising a set of non-linear sorption

isotherms created especially for use with the EPACMTP model. This option for

modeling the fate and transport of selected metals incorporates metal-specific

geochemical interactions that control the mobility of metals in the subsurface. This

modeling procedure was originally developed at theEPA’s NationalExposure Research

Laboratory, Ecosystems Research Division for the Hazardous Waste Identification Rule

(HWIR) and utilizes nationwide distributions of key geochemical parameters that impact

metal mobility in the subsurface.

In this methodology, the MINTEQA2 metal speciation code was used to

generate nonlinear adsorption isotherms for each metal. That is, a set of isotherms was

produced for each metal reflecting the range in geochemical environments expected

at waste sites across the nation.

To compute the adsorption distribution coefficient (Kd

) values for a particular

metal, a value was selected for each of the five master variables and the MINTEQA2

model was executed over a range of total metal concentrations. The result is a

nonlinear adsorption isotherm that can be represented by the variation in Kd with total

metal concentration (or, with equilibrium dissolved concentration). This procedure was

repeated (separately for each metal) for numerous combinations of master variable

settings. The final result from MINTEQA2 was nonlinear Kd versus metal concentration

curves for combinations of master variable settings spanning the range of reasonable

values.

For each metal, the resulting set of isotherms was tabulated into a

supplementary input data file for use by the EPACMTP model. In the fate and transport

modeling for a particular metal, EPACMTP is executed and the probability distributions

for these five variables form the basis for the Monte-Carlo selection of the appropriate
Section 3.0 Waste and Constituent Parameters

3-26

adsorption isotherm. A detailed discussion of the MINTEQA2 simulation procedure for

generating the metals sorption isotherms is provided in Appendix B.1.

MINTEQA2-derived sorption isotherms have been developed for the following

metals: antimony (V), arsenic (III), barium, beryllium, cadmium, chromium (III),

chromium (VI), copper (II), mercury (II), nickel, lead, selenium (VI), thallium (I),

vanadium, and zinc.

As implemented in EPACMTP, it is assumed that the non-linearity of the

isotherms is most important in the unsaturated zone where metals concentrations are

relatively high. Although MINTEQA2 isotherms were also generated for the saturated

zone, upon reaching the water table and mixing of the leachate with ambient ground

water, the metals concentration is considered to be low enough that a linear isotherm

(single Kd value not dependent on metal concentration) can always be used. The

appropriate saturated zone retardation factor is determined based on the maximum

ground-water concentration underneath the source.

Geochemical factors that are known to have direct impact on adsorption in

ground-water systems are: (1) ground-water composition, (2) subsurface pH, (3)

hydrous ferric oxide adsorbent content of the soil/aquifer in the subsurface, (4)

concentration of organic acids in the leachate, and (5) natural soil organic matter

content of the soil/aquifer in the subsurface (particulate and dissolved). For a given

metal at a given total concentration, the propensity for adsorption changes greatly as

these parameters vary. For the MINTEQA2 modeling, two ground-water types were

used (carbonate and non-carbonate) and for each ground-water type, the natural

variability of the remaining three parameters (since only low concentrations of leachate

organic acids are expected in the leachate emanating from industrial waste

management units, only the low range was modeled for leachate organic acid content)

was divided into three ranges: high, medium, and low. The approximate mid-point of

each range was identified, and in the MINTEQA2 modeling, these mid-point values

were used to simulate each range of values for pH, hydrous ferric oxide content, and

natural organic matter. For the non-carbonate ground-water type, one isotherm (as a

function of metal concentration) was developed for each combination of the three

possible values for the four master variables. This process was then repeated for the

carbonate ground-water type. For each ground-water type, separate isotherms were

developed for the unsaturated and saturated zone. For each metal, a set of 648

isotherms was developed.

The following EPACMTP input parameters are required to model metals

transport using the MINTEQA2 non-linear isotherms: metal identification number, soil

and aquifer pH, hydrous ferric oxide adsorbent content, leachate organic matter

concentration, percent organic matter of the soil, fraction organic carbon of the aquifer,

and ground-water composition. Each of these inputs, including the data sources and

the default EPACMTP input distributions (which correspond to the values used in the

MINTEQA2 modeling) for each of the five master variables, are described in the

following sections.
Section 3.0 Waste and Constituent Parameters

3-27

3.3.3.2.1 Metal Identification Number (ID)

Definition

The metal identification number is simply an arbitrary number assigned to each

metal in order to provide a simple means of specifying which metal is being modeled.

Parameter Value or Distribution of Values

The metal contaminants whose partition coefficients have been estimated using

MINTEQA2 include arsenic (As), antimony (Sb), barium (Ba), beryllium (Be), cadmium

(Cd), cobalt (Co), copper (Cu), chromium (Cr), fluoride (F), mercury (Hg), manganese

(Mn), molybdenum (Mo), lead (Pb), nickel (Ni), selenium (Se), silver (Ag), thallium (Tl),

vanadium (V), and zinc (Zn).

Several of these metals occur naturally in more than one oxidation state. The

modeling described here is restricted to the oxidation states that are most likely to occur

in waste systems or most likely to be mobile in ground-water waste systems. For

arsenic, chromium, and selenium, partition coefficients were estimated for two oxidation

states. These were: As(III) and As(V), Cr(III) and Cr(VI), and Se(IV) and Se(VI). For

antimony, molybdenum, thallium, and vanadium, only one oxidation state was modeled

although multiple oxidation states occur. For all four of these metals, the choice of

which state to model was dictated by practical aspects such as availability of sorption

reactions and by subjective assessment of the appropriate oxidation state. The

oxidation states modeled were Sb(V) (there were no sorption reactions available for

Sb(III)), Mo(VI) (molybdate seems the most relevant form from literature reports),

thallium (I) (this form is more frequently cited in the literature as having environmental

implications), and V(V) (vanadate; sorption reactions were not available for other

forms).

The metal identification number for each metal with a set of MINTEQA2-derived

non-linear isotherms is presented in Table 3.4. The appropriate identification number

should be specified in the EPACMTP input file as a constant value.
Section 3.0 Waste and Constituent Parameters

3-28

Table 3.4 Metals that have MINTEQA2-derived Non-linear Isotherms

Metal Species Metal ID

Ba 1

Cd 2

Cr (III) 3

Hg 4

Ni 5

Pb 6

Ag 7

Zn 8

Cu 9

V 10

Be 11

Mo 12

As (III) 13

Cr (VI) 14

Se (VI) 15

Tl 16

Sb (V) 17

Co 18

Mn 19

F 20

As (V) 21

Se (IV) 22

Data Sources

These metal identification numbers were arbitrarily created for convenience

during modeling; the list of available metals was determined by the availability of toxicity

and sorption data and their likely occurrence in industrial waste management scenarios

under consideration for Agency rule-making.

Use In EPACMTP

The metal identification number is used by the EPACMTP model to identify

which supplemental input file contains the appropriate non-linear isotherm data.
Section 3.0 Waste and Constituent Parameters

3-29

3.3.3.2.2 Soil and Aquifer pH (pH)

Definition

A measure of the acidity or alkalinity of the moisture present in the vadose zone

or the ground water. pH is measured on a scale of 0 to 14, with 7 representing a

neutral state. Values less than 7 are acidic, and values greater than 7 are basic. pH

is calculated as the negative logarithm of the concentration of hydrogen ions in a

solution.

For modeling purposes, pH is assumed to be the same in the unsaturated zone

and in the saturated zone.

Parameter Value or Distribution of Values

Lacking a site-specific value or distribution of values, a default distribution of pH

values may be used. The data are represented by an empirical distribution with low and

high values of 3.2 and 9.7, respectively and a median value of 6.8. The distribution is

shown in Figure 3.5.

Table 3.5 Probability distribution of soil and aquifer pH

Cumulative Probability (%) pH Value

0.0

1.0

5.0

10.0

25.0

50.0

75.0

90.0

95.0

100.0

3.21E+00

5.40E+00

6.31E+00

7.11E+00

7.59E+00

7.69E+00

7.80E+00

7.90E+00

8.09E+00

9.69E+00

Data Sources

The distribution of pH values shown in Table 3.5 was obtained through analysis

of nearly 25,000 field measured pH values of uncontaminated ground water obtained

from EPA’s STORET database (U.S. EPA, 1996). Note that the upper and lower

bounds of this distribution were established by reference to reported values in the open

literature.

Use In EPACMTP

The ground-water pH is one of the most important subsurface parameters

controlling the mobility of metals. Most metals are more mobile under acidic (low pH)

conditions, as compared to neutral or alkaline (pH of 7 or higher) conditions. The pH

may also affect the hydrolysis rate of organic constituents; some constituents degrade
Section 3.0 Waste and Constituent Parameters

3-30

more rapidly or more slowly as pH varies. The pH of most aquifer systems is slightly

acidic, the primary exception being aquifers in solution limestone settings. These may

also be referred to as ‘karst’, ‘carbonate’ or ‘dolomite’ aquifers. The ground water in

these systems is usually alkaline.

The EPACMTP model assumes that the ground-water/aquifer system is well

buffered with respect to pH. That is, in the modeling analysis, there is no effect on the

ambient pH from the leachate emanating from the base of the WMU.

3.3.3.2.3 Iron Hydroxide Content (FeOx)

Definition

The nature and amount of solid matter in the subsurface to which metals are

attracted (the adsorbent) are important in determining the extent to which a

constituent’s transport through the ground-water pathway is retarded due to adsorption.

Iron hydroxides (FeOx) represent one of the dominant adsorbents for metal sorption in

environmental systems, and were one of the geochemical master variables used in the

calculation of the non-linear sorption isotherms using the MINTEQA2 model. Although

other sorbents such as clay minerals, carbonate minerals, hydrous aluminum and

manganese oxides, and silica may sorb metals in the subsurface, accounting for ferric

hydroxide and particulate organic matter (see Section 3.3.3.2.5 for a discussion on

particulate organic matter) is sufficient to produce a realistic, yet protective, modeling

analysis for most natural ground-water systems.

Parameter Value or Distribution of Values

In the MINTEQA2 modeling that was used to calculate the isotherms for a

number of metals, the type of ferric oxide that was assumed to be present was in the

form of the mineral goethite (FeOOH), a common form of ferric oxide in soils. A

database of sorption reactions for goethite reported by Mathur (1995) was used with the

diffuse-layer sorption model in MINTEQA2 to represent the interactions of protons and

metals with the goethite surface. Further details of the MINTEQA2 modeling procedure

are given in Appendix B.1.

Lacking a site-specific value or distribution of values for this input parameter, a

default distribution may be used. The limited data on iron hydroxide content that are

available (Loux et al., 1990) were used to define a uniform distribution, with a minimum

of 0.0126 and a maximum of 1.115 percent iron hydroxide by weight. A summary of

this default distribution is presented in Table 3.6.
Section 3.0 Waste and Constituent Parameters

3-31

Table 3.6 Probability distribution of fraction iron hydroxide

Cumulative Probability (%) Iron Hydroxide Content (wt %)

0.0

1.0

5.0

10.0

25.0

50.0

75.0

90.0

95.0

100.0

1.82E-02

2.89E-02

4.37E-02

6.85E-02

9.36E-02

9.84E-02

1.04E-01

1.09E-01

1.14E-01

1.19E-01

Data Sources

The default distribution is based on analyses by Loux et al., (1990) on aquifer

samples collected by the U.S. EPA Office of Solid Waste (OSW) in Florida, New Jersey,

Oregon, Texas, Utah, and Wisconsin.

Use In EPACMTP

The iron hydroxide content of the subsurface is one of the most important

subsurface parameters controlling the mobility of metals. In EPACMTP, accounting for

ferric hydroxide determines the extent to which a constituent’s transport through the

ground-water pathway is retarded due to adsorption.

3.3.3.2.4 Leachate Organic Matter (LOM)

Definition

In addition to the metal contaminants, the leachate exiting a WMU may contain

elevated concentrations of leachate organic matter. This organic matter may consist

of various compounds including organic acids that represent primary disposed waste

or that result from the breakdown of more complex organic substances. Many organic

acids found in leachate have significant metal-complexing capacity that may influence

metal mobility. This input represents the concentration of these anthropogenic organic

acids in the leachate emanating from the base of the WMU.

Parameter Value or Distribution of Values

Lacking a site-specific value or distribution of values for the concentration of

organic acids in the leachate (which can then be used to help generate site-specific kd

values), the influence of leachate organic matter on metal sorption may be represented

by using a default distribution of values for this input parameter. The default distribution

is uniform, with a minimum of 0.001173 mg/L and a maximum of 0.00878 mg/L. A

summary of this default distribution is presented in Table 3.7.
Section 3.0 Waste and Constituent Parameters

3-32

Table 3.7 Probability distribution of leachate organic matter

Cumulative Probability (%) Concentration of Leachate Organic Matter (mg/L)

0.0

1.0

5.0

10.0

25.0

50.0

75.0

90.0

95.0

100.0

1.05E+02

1.40E+02

1.94E+02

2.84E+02

3.76E+02

3.94E+02

4.12E+02

4.30E+02

4.47E+02

4.67E+02

Data Sources

In an effort to incorporate in the ground-water modeling the solubilizing effect

of organic acids, a default distribution of leachate organic matter concentrations was

developed based on data presented byGintautas, Huyck, Daniel, and Macalady (1993).

This study examined leachates from six landfills from across the U. S. and found that

over 30 different acids were present. The range of leachate organic matter

concentration levels given in the default distribution is based on the measured total

organic carbon among the six landfill leachates in this study.

Use In EPACMTP

The concentration of anthropogenic organic acids in leachate is one of the most

important subsurface parameters controlling the mobility of metals. In EPACMTP, this

parameter is used to quantify metal-complexing capacity that may influence metal

mobility.

3.3.3.2.5 Percent Organic Matter (%OM)

Definition

The nature and amount of solid matter in the subsurface to which metals are

attracted (the adsorbent) are important in determining the extent to which a

constituent’s transport through the ground-water pathway is retarded due to adsorption.

Particulate organic matter present in the unsaturated zone (input to EPACMTP as

percent organic matter) represents one of the dominant adsorbents for metal sorption

in environmental systems and was one of the geochemical master variables used in the

calculation of the non-linear sorption isotherms using the MINTEQA2 model. Although

other sorbents such as clay minerals, carbonate minerals, hydrous aluminum and

manganese oxides, and silica may sorb metals in the subsurface, accounting for ferric

hydroxides (See Section 3.3.3.2.3 for a discussion of FeOx) and particulate organic

matter (in the soil and aquifer) is sufficient to produce a realistic, yet protective,

modeling analysis for most natural ground-water systems. In EPACMTP modeling, the
Section 3.0 Waste and Constituent Parameters

3-33

amount of particulate organic matter in the soil (as opposed to the aquifer, represented

by the term foc) is represented by the percent organic matter (%OM).

Parameter Value or Distribution of Values

Lacking a site-specific value or distribution of values for this input parameter

(which can then be used to help generate site-specific kd values), a default distribution

may be used. In the EPACMTP model, there are three default soil types (sandy loam,

silty loam, and silty clay loam); each soil type has a unique distribution of values for

each of the soil parameters, including the percent organic matter. When modeling a

metal using the MINTEQA2-derived isotherms, the default distribution for percent

organic matter in the unsaturated zone is based on the default distribution for percent

organic matter for the silty loam soil type. The silty loam soil type is intermediate in

weight percent organic matter in comparison with the other two and is the most

frequently occurring soil type. The default distribution type is Johnson SB; the minimum

value is 0.0 and the maximum value is 8.51. A summary of this default distribution is

presented in Table 3.8.

Table 3.8 Probability distribution of percent organic matter in the unsaturated

zone

Cumulative Probability (%)

Percent Organic Matter in the

Unsaturated Zone (unitless)

0.0

1.0

5.0

10.0

25.0

50.0

75.0

90.0

95.0

100.0

4.08E-03

3.76E-02

6.07E-02

1.04E-01

1.78E-01

2.04E-01

2.38E-01

2.87E-01

3.82E-01

1.80E+00

Data Sources

The default distribution described above for the percent organic matter in the

unsaturated zone is based on data presented in Carsel and Parrish, 1988.

Use In EPACMTP

The percent organic matter in the unsaturated zone is used in EPACMTP

because the nature and amount of solid matter in the subsurface to which metals are

attracted (the adsorbent) are important in determining the extent to which a

constituent’s transport through the ground-water pathway is retarded due to adsorption.

As the adsorption of a contaminant in the unsaturated zone increases, more of the

contaminant is removed from the system, and is unavailable for transport.
Section 3.0 Waste and Constituent Parameters

3-34

3.3.3.2.6 Fraction Organic Carbon (foc)

Definition

The nature and amount of solid matter in the subsurface to which metals are

attracted (the adsorbent) are important in determining the extent to which a

constituent’s transport through the ground-water pathway is retarded due to adsorption.

Particulate organic matter present in the saturated zone represents one of the dominant

adsorbents for metal sorption in environmental systems and was one of the

geochemical master variables used in the calculation of the non-linear sorption

isotherms using the MINTEQA2 model. Although other sorbents such as clay minerals,

carbonate minerals, hydrous aluminum and manganese oxides, and silica may sorb

metals in the subsurface, accounting for ferric hydroxide (see Section 3.3.3.2.3 for a

discussion of FeOx) and particulate organic matter (in the soil and aquifer) is sufficient

to produce a realistic, yet protective, modeling analysis for most natural ground-water

systems. In EPACMTP modeling, the amount of particulate organic matter in the

aquifer is represented by the fraction organic carbon, or foc(as opposed to the soil,

represented by the term %OM).

Parameter Value or Distribution of Values

Lacking a site-specific value or distribution of values for this input parameter

(which can then be used to help generate site-specific kd values), a default distribution

may be used. In the EPACMTP model, there are three default soil types (sandy loam,

silty loam, and silty clay loam); each soil type has unique distribution of values for each

of the soil parameters, including the percent organic matter. When modeling a metal

using the MINTEQA2-derived isotherms, the default distribution for fraction organic

carbon in the saturated zone is based on the default distribution for percent organic

matter for the sandy loam soil type, however, this value is converted from percent

organic matter to fraction organic carbon using Equation 5.1. The sandy loam soil type

is higher in weight percent organic matter in comparison with the other soil types. The

default distribution type is Johnson SB; the minimum value is 0.0 and the maximum

value is 11.0. A summary of this default distribution is presented in Table 3.9.
Section 3.0 Waste and Constituent Parameters

3-35

Table 3.9 Probability distribution of fraction organic carbon in the saturated

zone

Cumulative Probability (%)

Fraction Organic Carbon in the

Saturated Zone (unitless)

0.0

1.0

5.0

10.0

25.0

50.0

75.0

90.0

95.0

100.0

1.61E-05

1.31E-04

2.30E-04

4.31E-04

8.00E-04

9.27E-04

1.10E-03

1.35E-03

1.88E-03

1.24E-02

Data Sources

The default distribution described above for the fraction organic carbon in the

saturated zone is based on data presented in Carsel, Parrish, Jones, Hansen, and

Lamb, 1988.

Use In EPACMTP

The fraction organic carbon in the saturated zone is one of the most important

subsurface parameters controlling the mobility of metals, since it is used in determining

the extent to which a constituent’s transport through the ground-water pathway is

retarded due to adsorption. .

3.3.3.2.7 Ground-water Type (IGWT)

Definition

Ground-water chemistry exerts an important influence on metal partition

coefficients. The major ions present in ground water may compete with trace metals

for sorption sites. Also, inorganic ligands may complex with some metals, thereby

reducing their tendency to sorb. For the purposes of this modeling, partition coefficients

were estimated separately for two ground-water compositional types, one with

composition representative of a carbonate-terrain system and one representative of a

non-carbonate system. The two ground-water compositional types are correlated with

the hydrogeologic environment index in EPACMTP (see Section 5.3.4.2). In

EPACMTP, this parameter may take on one of thirteen values, but issues of practicality

limit the number of ground-water types for which separate partition coefficients can be

estimated to just two. The broadest division of ground waters that may be made for the

thirteen hydrogeologic environments in EPACMTP is carbonate and non-carbonate

types of ground waters. Thus, these are the two broad types for which coefficients

were estimated.
Section 3.0 Waste and Constituent Parameters

3-36

Parameter Value or Distribution of Values

By default, the ground-water type is directly correlated to the hydrogeologic

environment setting in EPACMTP. In the default databases of WMU sites that have

been compiled into auxiliary input files (called the site data files), each WMU site has

been classified by the predominant hydrogeologic environment at the site. In

EPACMTP, there are thirteen possible hydrogeologic environments. For the “solution

limestone” hydrogeologic environment setting (IGWR = 12), the ground-water type is

set to carbonate. The ground-water type for the other twelve possible hydrogeologic

settings in EPACMTP are represented by the non-carbonate ground-water type.

Data Sources

The ground-water type is simply an arbitrary number assigned to provide a

simple means of specifying which set of isotherms should be used (there is one set for

carbonate ground water and another set for non-carbonate ground water). For both

ground-water types, a representative, charge-balanced ground-water chemistry

specified in terms of major ion concentrations and natural pH was selected from the

literature. The carbonate system was represented by a well sample reported for a

limestone aquifer (Freeze and Cherry, 1979). This ground water had a natural pH of

7.5 and was saturated with respect to calcite. The non-carbonate system was

represented by a sample reported from an unconsolidated sand and gravel aquifer with

a natural pH of 7.4 (White, Hem, and Waring, 1963). An unconsolidated sand and

gravel aquifer was selected to represent the non-carbonate compositional type because

it is the most frequently occurring of the twelve (non-carbonate) hydrogeologic

environments in EPACMTP. More details about the MINTEQA2 modeling methodology

and the compositions of both the carbonate and non-carbonate representative groundwater samples are presented in Appendix B.1.

Use In EPACMTP

The ground-water type is one of the most important subsurface parameters

controlling the mobility of metals, since the major ions present in ground water may

compete with trace metals for sorption sites. This may result in less availability of

sorption sites for contaminants as they enter the ground water.
Section 4.0 Infiltration and Recharge Parameters

4-1

4.0 INFILTRATION AND RECHARGE PARAMETERS

This section discusses the individual parameters related to infiltration and

recharge that are required to perform a modeling analysis using EPACMTP.

Although most applications of EPACMTP are conducted on a national or regional

basis for regulatory development purposes, EPACMTP can also be used in a

location or a waste-specific mode. In either case, each of the input parameters

related to the climatic characteristics of the site(s) being modeled can be specified

as a constant value or as a statistical or empirical distribution of values. As a

practical matter, however, many of these inputs are commonly specified as

distributions of values as part of the regional site-based modeling methodology.

In EPACMTP, the infiltration and recharge-related input parameters include

the climate center location, infiltration and recharge rates, and the soil and aquifer

temperature. The climate center location is specified as an index that represents the

climate center nearest to the waste site being modeled. The climate center index

allows the model to access a default set of infiltration and recharge rates that are

specific to a WMU type, soil type, and geographic location.

The infiltration rate is defined as the rate at which leachate flows from the

bottom of the WMU (including any liner) into the unsaturated zone beneath the

WMU. Recharge is the regional rate of aquifer recharge outside of the WMU.

Infiltration rate is among the most sensitive site-specific parameters in an EPACMTP

evaluation, whereas the model is usually much less sensitive to recharge. For

landfills (LFs), waste piles (WPs), and land application units (LAUs), the infiltration

rate is determined primarily by the local climatic conditions, especially annual

precipitation and WMU liner characteristics. For SIs, the infiltration rate is a function

of the surface impoundment ponding depth, liner characteristics, and the presence

of a ‘sludge’ layer at the bottom of the impoundment. The regional recharge rate is

a function of the annual precipitation rate, and varies with geographical location and

soil type.

These infiltration and recharge-related parameters are individually described

in the following sections.

4.1 INFILTRATION AND RECHARGE PARAMETERS

The input parameters that are used in EPACMTP to describe the climatic

characteristics of the WMU site to be modeled are listed in Table 4.1 on the

following page.
Section 4.0 Infiltration and Recharge Parameters

4-2

Table 4.1 Climate Parameters

Parameter Symbol Units Section

Equation in

EPACMTP TBD

Climate Center Index ICLR – 4.2 --

Landfill Infiltration Rate I m/yr 4.3.1 3.4

Waste Pile Infiltration

Rate

I m/yr 4.3.2 3.4

Land Application Unit

Infiltration Rate

I m/yr 4.3.3 3.4

Surface Impoundment

Infiltration Rate

I m/yr 4.3.4 2.24

Recharge Rate IR m/yr 4.4 4.10

4.2 CLIMATE CENTER INDEX (ICLR)

Definition

The climate center index is simply a sequential number assigned to each of

102 climate centers in the default database included with EPACMTP in order to

provide a simple means of specifying which infiltration and recharge rates should be

used to model the given WMU site.

Parameter Value or Distribution of Values

The climate centers for which default infiltration rates (for LFs, WPs, and

LAUs) and recharge rates (for LFs, WPs, SIs, and LAUs) are available are listed in

Table 4.2. The geographic locations are depicted in Figure 4.1. For each of the

locations listed in Table 4.2, the U.S. EPA used the Hydrologic Evaluation of Landfill

Performance (HELP) model (Schroeder, Dozier, Zappi, McEnroe, Sjostrom, and

Peton, 1994) to compute recharge rates for all units, as well as infiltration rates for

LAUs and for LFs and WPs with no-liner and single-liner designs. Appendix A

provides additional information about how EPA used the HELP model, in conjunction

with data from climate stations across the United States, to develop these

nationwide recharge and infiltration rate distributions, as well as a detailed

discussion of how infiltration rates were developed for different liner designs for each

type of WMU.

In developing this default distribution of infiltratoin rates, we started with an

existing database of no-liner infiltration rates for LFs, WPs and LAUs. Also existing

were recharge rates for 97 climate stations in the lower 48 contiguous United States

(ABB, 1995), that are representative of 25 specific climatic regions (developed with

HELP version 3.03). We then added five climate stations (located in Alaska, Hawaii,

and Puerto Rico) to ensure coverage throughout all of the United States. Rather

than calculating infiltration rates for each of the 102 individual climate stations,
Section 4.0 Infiltration and Recharge Parameters

4-3

infiltration rates were calculated for the 25 climate regions, and then assigned the

same value to each climate station in one group. In order to reduce the number of

required HELP simulations, one station from each climate region was simulated, and

the resulting value assigned to each climate station within the region. To be

protective, EPA chose the climate center with the highest average precipitation in

each climate region (which would tend to maximize constituent transport) to

represent the region. Individual infiltration rates were calculated for each of the five

climate centers not assigned to a climate region (centers from Alaska, Hawaii, and

Puerto Rico).

Table 4.2 Climate Centers Used in the HELP Modeling to Develop Infiltration

and Recharge Rates

Index City State Index City State Index City State

1 Fresno CA 29 Dodge City KS 57 Tampa FL

2 Boise ID 30 Midland TX 58 San Antonio TX

3 Denver CO 31 St. Cloud MN 59 Hartford CT

4 Grand Junction CO 32 E. Lansing MI 60 Syracuse NY

5 Pocatello ID 33 North Omaha NE 61 Worchester MA

6 Glasgow MT 34 Tulsa OK 62 Augusta ME

7 Bismarck ND 35 Brownsville TX 63 Providence RI

8 Pullman WA 36 Dallas TX 64 Portland ME

9 Yakima WA 37 Oklahoma City OK 65 Nashua NH

10 Cheyenne WY 38 Concord NH 66 Ithaca NY

11 Lander WY 39 Pittsburgh PA 67 Boston MA

12 Los Angeles CA 40 Portland OR 68 Schenectady NY

13 Sacramento CA 41 Caribou ME 69 Lynchburg VA

14 San Diego CA 42 Chicago IL 70 New York City NY

15 Santa Maria CA 43 Burlington VT 71 Philadelphia PA

16 Ely NV 44 Bangor ME 72 Seabrook NJ

17 Rapid City SD 45 Rutland VT 73 Indianapolis IN

18 Cedar City UT 46 Seattle WA 74 Cincinnati OH

19 Albuquerque NM 47 Montpelier VT 75 Bridgeport CT

20 Las Vegas NV 48 Sault St. Marie MI 76 Orlando FL

21 Phoenix AZ 49 Put-in-Bay OH 77 Greensboro NC

22 Tucson AZ 50 Madison WI 78 Jacksonville FL

23 El Paso TX 51 Columbus OH 79 Watkinsville GA

24 Medford OR 52 Cleveland OH 80 Norfolk VA

25 Great Falls MT 53 Des Moines IA 81 Shreveport LA

26 Salt Lake City UT 54 E. St. Louis IL 82 Astoria OR

27 Grand Island NE 55 Columbia MO 83 New Haven CT

28 Flagstaff AZ 56 Topeka KS 84 Plainfield MA

85 Knoxville TN 91 Tallahassee FL 97 Miami FL

86 Central Park NY 92 New Orleans LA 98 Annette AK

87 Lexington KY 93 Charleston SC 99 Bethel AK
Section 4.0 Infiltration and Recharge Parameters

Index City State Index City State Index City State

4-4

88 Edison NJ 94 W. Palm Beach FL 100 Fairbanks AK

89 Nashville TN 95 Atlanta GA 101 Honolulu HI

90 Little Rock AK 96 Lake Charles LA 102 San Juan PR

Data Sources

The list of available climate centers was determined by the availability of

meteorological data required for the HELP model and geographic coverage of the

United States.

Use In EPACMTP

EPACMTP includes a database of infiltration rates and regional recharge

rates for 102 climate centers located throughout the United States. The climate

center index is a sequential number assigned to each climate center in the default

database included with EPACMTP in order to provide a simple means of specifying

which infiltration and recharge rates should be used to model the given WMU site

(See Appendix A for a discussion on the determination of infiltration and recharge

rates).

This parameter is used as a part of the regional site-based modeling

methodology, in which a number of parameters related to the characteristics of the

waste site are drawn from a correlated set of data. These default databases of siterelated parameters (one for each WMU type) are commonly referred to as the site

data files. To perform a Monte Carlo analysis using the regional site-based

modeling methodology, the climate center index is provided in the site data files as

the default setting, which will ensure that the appropriate climatic data is used for

each WMU site in the database. However, if a location-adjusted or quasi-sitespecific analysis is being performed, this input can either be omitted from the input

file (if site-specific infiltration and recharge rates are available) or assigned a climate

center index that is most appropriate to make use of the default location- and soilspecific infiltration and recharge rates which are included in the site data file.

Usually this is the nearest climate center. However, this is not always the case.

Especially in coastal and mountain regions, the nearest climate center does not

always represent conditions that most closely approximate conditions at a specific

site.
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GreatFalls

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St.Cloud

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RapidCity

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Pocatello

Schenectady

Ithaca Medford

Chicago

DesMoines

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Cheyenne GrandIsland SaltLakeCity 

C 

olumbus Indianapolis

Denver

Cincinnati

GrandJunction Topeka Columbia

Sacramento

DodgeCity

CedarCity

Lynchburg

Glasgow

No

Fresno

LasVegas

Tulsa

Greensboro

Knoxville

OklahomaCity Flagstaff Albuquerque LittleRock LosAngeles Atlanta

SanDiego Phoenix

Dallas

Charlesto

Tucson Shreveport

Midland El Paso TallahasseeJacksonville

LakeCharles NewOrleans

SanAntonio

Orlando

Tampa

Brownsville

Miam

Ely

Lander

NorthOmaha

Plainef

Put-In-Bay

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EastLansing

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EastSt.Louis

SantaMaria

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Nashville-Davidson

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Annette

Bethel

#Honolulu

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SanJuan

Alaska Hawaii PuertoRico

Figure 4.1 Locations of EPACMTP Climate Stations
Section 4.0 Infiltration and Recharge Parameters

4-6

4.3 INFILTRATION RATES

The EPACMTP model requires input of the net rate of vertical downward

percolation of water and leachate through the unsaturated zone to the water table.

Infiltration refers to the water that percolates through a WMU to the underlying soil,

whereas recharge is water percolating through the soil to the aquifer outside the

footprint of the WMU. The model allows the infiltration rate to be different from the

ambient regional recharge rate. These rates can differ for a variety of reasons,

including the engineering design of the WMU, topography, land use, and vegetation.

Note that both infiltration and recharge are specified as areal rates, with the units of

cubic meters of fluid (water or leachate) per square meter per year (m3/m2/yr). Thus,

the units for infiltration and recharge simplify to meters per year (m/yr).

Infiltration and recharge rates for use in EPACMTP modeling applications

have been estimated for selected soil types at cities around the country through the

use of the HELP water-balance model (Version 3.03) (Schroeder et al., 1994), as

summarized below. Further details about the HELP modeling inputs, assumptions

for each type of WMU, and the resulting databases of infiltration and recharge rates

are given in Appendix A.

Using the Soil Conservation Service’s (SCS) county-by-county soil mapping

database, the soil classifications in the U.S. were grouped according to the U.S.

Department of Agriculture's definitions of coarse, medium, and fine textures. These

three categories are represented in EPACMTP by soils equivalent in properties to

sandy loam (SNL), silt loam (SLT), and silty clay loam (SCL). An analysis of the

SCS database indicates that coarse grained soils, medium grained soils, and fine

grained soils represent 15.4 percent, 56.6 percent, and 28.0 percent, respectively, of

the soils that have been mapped by the SCS.

The National Oceanic and Atmospheric Administration (NOAA) has data on

precipitation and evaporation rates in the United States. This nationwide database

was used to categorize the meteorological conditions in the U. S. into 18 climatic

regions; 102 cities covering all 18 of the climatic regions were selected as climatic

centers for the HELP model (Figure 4.1). For each selected city, climatic data for

five years were accessed and used to develop leaching rates for different types of

waste management scenarios as a function of site location and soil type. The

resulting HELP-model-generated infiltration and recharge rates are incorporated into

EPACMTP.

EPACMTP provides default values for infiltration rate as a function of WMU

type, liner design, and site location. These values were calculated for unlined and

single-lined landfills, waste piles, and land application units for each of the 102

climatic centers with the HELP model, using the procedure described in Appendix A.

For composite-lined landfills and waste piles, these values are chosen from an

empirical distribution of values based on the results of a literature review (TetraTech,

2001). In the case of surface impoundments, EPACMTP directly calculates the

infiltration rate as a function of WMU characteristics, including liner type.
Section 4.0 Infiltration and Recharge Parameters

4-7

Because the infiltration rate from a WMU is difficult to measure directly, a

model such as HELP is used to estimate the WMU infiltration rates for use in

EPACMTP.

The data sources for infiltration rates for each type of WMU and the resulting

infiltration rates are summarized in the following sections.

4.3.1 Landfill Infiltration Rate (I)

Definition

The landfill infiltration rate (m/yr) is defined as the rate at which

water/leachate percolates through the landfill to the underlying soil. The landfill

infiltration rate may be different from the ambient regional recharge rate due to the

engineering design of the landfill (e.g., landfill cover soil that has a lower conductivity

than the regional soils), topography, land use, and vegetation.

For the no-liner case, a two-foot (0.61m) soil cover was assumed to

represent Subtitle D landfills that do not contain a liner and leak detection system,

and therefore would not be required by the regulations to have a cap of less

permeability than the liner system. Two feet was selected as the thickness of the

cover as the minimum requirement of Subtitle D. Three default soil types were

selected: sandy loam, silt loam, and silty clay loam, corresponding to the coarse,

medium, and fine grained soil types as described in Section 4.3. These three soil

types are assumed to support vegetation in the United States and are the three soil

types used in the leachate flux analysis performed in support of the TC Rule

modeling analysis (U.S. EPA, 1990).

For the single-clay liner case, a 3-ft. (0.914m) clay cover with a hydraulic

conductivity of 1×10

-7

cm/sec, a 1-ft. (0.305m) layer of loam overlying the cover (to

support vegetation and drainage), a 10-ft. (3.05m) waste layer, a 1-ft. (0.305m)

percolation layer, and a 3-ft. (0.914m) clay liner with a hydraulic conductivity of 1×10

-

7

cm/sec were specified in the HELP model input file. Additionally, the modeling

assumed that there is no leachate collection system and that the infiltration rate is

constant (that is, no increase in hydraulic conductivity of liner) over the modeling

period.

A composite liner was defined as a 60 mil HDPE layer with either an underlying

geosynthetic clay liner with maximum hydraulic conductivity of 5×10

-9

cm/sec, or a 3-

ft. (0.914m) compacted clay liner with maximum hydraulic conductivity of 1×10

-7

cm/sec. As in the single-clay liner case, this scenario assumes a constant infiltration

rate (i.e., no increase in hydraulic conductivity of liner) over the modeling period.

Parameter Value or Distribution of Values

When the EPACMTP model is run for an unlined or single-lined landfill using

the regional, site-based methodology, the model selects a site at random from those

in the site data file for each Monte Carlo realization. Since the landfill cover and soil
Section 4.0 Infiltration and Recharge Parameters

4-8

type for the landfills in the 1986 Subtitle D Survey were unknown, a random

combination of landfill cover soil type and regional soil type are then generated from

a national joint probability distribution (assuming that the relative frequency of

different soil and cover types is nationally uniform) (U.S.EPA, 1990). The climate

center index associated with the chosen site and the randomly generated soil types

are then used by the model to determine the recharge and infiltration values of the

site from the HELP database also included in the site data file. In the case of

unlined landfills, if the cover type and soil type underneath the unit are the same, the

infiltration rate will be identical to the regional recharge rate for that soil type.

The cumulative frequency distributions of LF infiltration for the three default

liner scenarios are presented in Table 4.3, and are based on the estimates

described in the following sections; the LF infiltration rates for each climate center

are presented in Appendix A.

Table 4.3 Cumulative Frequency Distribution of Landfill Infiltration

%

No Liner

Infiltration Rate

(m/yr)

Clay Liner

Infiltration Rate

(m/yr)

Composite Liner

Infiltration Rate

(m/yr)

0

10

25

50

75

80

85

90

95

100

1.00E-05

1.35E-02

6.58E-02

1.09E-01

2.74E-01

3.12E-01

3.53E-01

4.11E-01

4.56E-01

1.08E+00

1.00E-05

9.44E-03

2.53E-02

4.32E-02

4.45E-02

4.77E-02

4.77E-02

4.86E-02

4.86E-02

5.26E-02

0.00E+00

0.00E+00

0.00E+00

0.00E+00

7.30E-05

7.30E-05

1.12E-04

1.69E-04

2.83E-04

4.01E-04

Data Sources

The HELP model (Schroeder, et al., 1994) was used to estimate the rate at

which leachate emanates from the base of the landfill for the no-liner and single-clay

liner scenarios, using the procedure described in Appendix A.

For the composite liner case, the EPACMTP model randomly selects an

infiltration rate from a default database of values which were compiled from a

literature review of leak detection system flow rates (TetraTech, 2001).

When the EPACMTP model is run for a composite-lined landfill using the

regional, site-based methodology, the model selects an infiltration rate at random

from those in the default distribution for each Monte Carlo realization.

In a location-specific modeling analysis, the site-specific infiltration rate can
Section 4.0 Infiltration and Recharge Parameters

4-9

be directly specified in the input file – either as a constant value or as a statistical or

empirical distribution of values.

Use In EPACMTP

The landfill infiltration rate is used by the model to determine the leaching

duration and leachate concentration when the landfill depleting source option is

used. Infiltration rate is also used by the model to determine the leachate flux to the

subsurface and as an input to the subsurface flow and transport modules.

4.3.2 Waste Pile Infiltration Rate (I)

Definition

The waste pile infiltration rate is defined as the rate at which water/leachate

percolates through the waste pile to the underlying soil. The waste pile infiltration

rate may be different from the ambient regional recharge rate due to the engineering

design of the waste pile (e.g., uncovered waste has a different conductivity than the

regional soils), topography, land use, and vegetation.

For the purposes of estimating leaching rates using the HELP model, waste

piles were considered to be similar to non-covered landfills. Thus, the infiltration

rates for unlined and single-lined waste piles were generated using the same

general procedures as for landfills, but with the following modifications. Because of

the limited requirements for leachate collection systems in most states, after closure,

waste piles will approximate the landfill configuration selected for modeling, i.e.,

waste covered by two feet of soil. Modeling of closed waste piles was, therefore, not

necessary as their leaching characteristics are similar to closed landfills. Active

waste piles, however, differ from landfills in that the waste generally remains

uncovered. So the HELP model was used to model the leachate flux for waste piles

through active, uncovered piles without leachate collection systems.

For the unlined scenario, the waste piles were modeled as a one-layer

landfill, with the uncovered waste material comprising the layer. The waste material

was assumed to be a moderate permeability waste – coal bottom ash with a

permeability of 4.1×10

-4

cm/sec.

For the single-lined scenario, an additional parameter – waste type

permeability – is used. Since waste piles are not typically covered, the permeability

of the waste itself can be a factor in determining the rate of leachate released due to

water percolating through the WMU. For waste piles, the HELP modeling was

conducted using three categories of waste permeability: high permeability (0.041

cm/sec); moderate permeability (0.0041 cm/sec); and low permeability (0.00005

cm/sec). The waste permeability is generally correlated with the grain size of the

waste material, ranging from coarse- to fine-grained materials. Additionally, the

modeling assumed that there is no leachate collection system and that the infiltration

rate is constant (that is, no increase in hydraulic conductivity of liner) over the

modeling period.
Section 4.0 Infiltration and Recharge Parameters

4-10

For the composite-lined scenario, the EPACMTP model randomly selects an

infiltration rate from a default database of values which were compiled from a

literature review of leak detection system flow rates (TetraTech, 2001). For the

purposes of this literature review, a composite liner was defined as a 60 mil HDPE

layer with either an underlying geosynthetic clay liner with maximum hydraulic

conductivity of 5×10

-9

cm/sec, or a 3-ft.(0.914m) compacted clay liner with maximum

hydraulic conductivity of 1×10

-7

cm/sec. As in the single-clay liner case, this

scenario assumes a constant infiltration rate (i.e., no increase in hydraulic

conductivity of liner) over the modeling period.

Parameter Value or Distribution of Values

The cumulative frequency distributions of WP infiltration for the three default

liner scenarios are presented in Table 4.4, based on the estimates described in the

following section; the WP infiltration rates for each climate center are presented in

Appendix A.

Table 4.4 Cumulative Frequency Distribution of Waste Pile Infiltration

%

No Liner Infiltration

Rate (m/yr)

Clay Liner Infiltration

Rate (m/yr)

Composite Liner

Infiltration Rate (m/yr)

0

10

25

50

75

80

85

90

95

100

3.00E-04

6.02E-02

1.28E-01

2.55E-01

3.91E-01

4.49E-01

4.76E-01

5.38E-01

6.14E-01

1.82E+00

1.00E-05

2.64E-02

9.50E-02

1.27E-01

1.33E-01

1.33E-01

1.34E-01

1.35E-01

1.35E-01

1.36E-01

0.00E+00

0.00E+00

0.00E+00

0.00E+00

7.30E-05

7.30E-05

1.16E-04

1.67E-04

2.80E-04

4.01E-04

Data Sources

The HELP model (Schroeder et. al., 1994) was used to estimate the rate at

which leachate emanates from the base of the waste pile for the no-liner and singleclay liner scenarios. This modeling methodology is summarized here and is more

fully described in Appendix A.
Section 4.0 Infiltration and Recharge Parameters

4-11

Use In EPACMTP

When the EPACMTP model is run for an unlined or single-lined waste pile

using the regional, site-based methodology,the model selects a site at random from

those in the site data file for each Monte Carlo realization The climate center index

associated with the chosen site and the randomly generated soil types are then used

by the model to determine the recharge and infiltration values of the site from the

HELP databases also included in the site data file.

When the EPACMTP model is run for a composite-lined waste pile using the

regional, site-based methodology, the model selects an infiltration rate at random

from those in the default distribution for each Monte Carlo realization.

In a location-specific modeling analysis, the site-specific infiltration rate can

be directly specified in the input file – either as a constant value or as a statistical or

empirical distribution of values.

Once the waste pile infiltration rate is generated, it is used by the model to

determine the leachate flux to the subsurface and as an input to the subsurface flow

and transport modules.

4.3.3 Land Application Unit Infiltration Rate (I)

Definition

The land application unit infiltration rate is defined as the rate at which water/

leachate percolates through the land application unit to the underlying soil. Although

the actual infiltration rate at a land application site may be slightly different from the

ambient regional recharge rate due to the additional water in the land applied

sludge, topography, land use, and vegetation, the default Monte Carlo analysis in

EPACMTP assumes that these rates are identical.

Based upon sensitivity analyses using a range of waste application rates,

EPA established that the addition of amounts of water through application of sludgetype wastes does not significantly impact the soil water balance, and therefore has

little to no effect on the calculated net infiltration. Only for sites located in arid

regions of the United States with very little natural precipitation did high application

rates have an appreciable effect. For more representative waste application rates,

the effect disappeared because introducing additional moisture in the simulated

water balance resulted in a commensurate increase in runoff and removal by

evapotranspiration.

Based on these results, the land application unit infiltration rates at the 102

climate centers were taken to be the same as the ambient regional recharge rate for

that climatic center and soil type. In addition, the recharge rate for a given climate

center and soil type is taken to be the same as the corresponding landfill infiltration

rate.
Section 4.0 Infiltration and Recharge Parameters

4-12

Parameter Value or Distribution of Values

When the EPACMTP model is run for a land application unit using the

regional, site-based methodology, he model selects a site at random from those in

the site data file for each Monte Carlo realization The climate center index

associated with the chosen site and the randomly generated soil types are then used

by the model to determine the recharge and infiltration values of the site from the

HELP databases also included in the site data file.

The cumulative frequency distribution of LAU infiltration for the no-liner

scenario is presented in Table 4.5, based on the estimates described in the following

sections; the LAU infiltration rates for each climate center are presented in Appendix

A.

Table 4.5 Cumulative Frequency Distribution of Land Application Unit

Infiltration

% No Liner Infiltration Rate (m/yr)

0

10

25

50

75

80

85

90

95

100

1.00E-05

1.30E-02

7.04E-02

1.10E-01

2.01E-01

2.57E-01

2.89E-01

3.26E-01

3.65E-01

7.45E-01

Data Sources

In a location-specific modeling analysis, the site-specific infiltration rate can

be directly specified in the input file – either as a constant value or as a statistical or

empirical distribution of values.

The HELP model was used to estimate the rate at which leachate emanates

from the base of the land application unit for the no-liner scenario. This modeling

methodology is summarized here and is more fully described in Appendix A.

Use In EPACMTP

Once the land application unit infiltration rate is generated, it is used by the

model to determine the leachate flux to the subsurface and as an input to the

subsurface flow and transport modules.
Section 4.0 Infiltration and Recharge Parameters

4-13

4.3.4 Surface Impoundment Infiltration Rate (I)

Definition

The surface impoundment infiltration rate is defined as the rate at which

water/leachate percolates through the surface impoundment to the underlying soil.

The surface impoundment infiltration rate is generally larger than the ambient

regional recharge rate due to the hydraulic head created by the wastewater in the

impoundment.

For the surface impoundment scenario, the leachate flux rate is computed as

a derived parameter, as part of the unsaturated zone flow module in EPACMTP.

The algorithm is described in the EPACMTP Technical Background Document (US

EPA, 2003a). In a typical Monte Carlo modeling analysis of a surface impoundment,

the infiltration rate is derived by the EPACMTP model. Technically, the SI infiltration

rate is not really an input parameter; rather, the model calculates infiltration rates “on

the fly” during the simulation. In the event that the SI is reported to have its base

below the water table, EPACMTP calculates the infiltration using Darcy’s law based

on the hydraulic gradient across and the hydraulic conductivity of the consolidated

sediment and any liner material at the bottom of the impoundment unit. Based on

unit-specific data from EPA’s Surface Impoundment Study (US EPA 2001a), EPA

assumed a fixed sediment layer thickness of 20 cm at the base of the impoundment.

In addition, the EPACMTP model assumes that the depth of clogging underneath

the impoundment was 0.5 m in all cases, and that saturated hydraulic conductivity of

the clogged layer is 10% of that of the native soil underlying the impoundment.

For unlined SIs, the primary parameters that control the infiltration rate are

the ponding depth in the impoundment, the thickness and permeability of any

accumulated sediment layer at the base of the impoundment, and the presence of a

‘clogged’ (i.e., reduced permeability) layer of native soil under the impoundment

caused by the migration of solids from the impoundment.

For single-lined SIs, infiltration rates are typically calculated inside of

EPACMTP in the same manner as described for unlined units, with the exception

that a compacted clay liner (with a given thickness and hydraulic conductivity) is

added at the bottom of the WMU and the effect of clogged native material is not

included due to the filtering effects of the liner. For more information on the

EPACMTP inputs used to describe the SI liner thickness and conductivity, see

Sections 2.4.4.and 2.4.5.

For the composite-lined SI, the EPACMTP model determines its infiltration

rate using a default distribution of leak densities expressed as number of leaks per

hectare (see Section 2.4.7).

Parameter Value or Distribution of Values

When the EPACMTP model is run for any of the three default liners for the

surface impoundment scenario using the regional, site-based methodology, the
Section 4.0 Infiltration and Recharge Parameters

4-14

model selects a site at random from those in the site data file for each Monte Carlo

realization. Using the characteristics of the chosen site and the methods described

above, the model automatically calculates the infiltration rate. The climate center

index associated with the chosen site and the randomly generated soil types are

then used to determine the recharge rate for the site from the HELP database also

included in the site data file.

The cumulative frequency distributions of SI infiltration for the three default

liner scenarios (produced by running a standard regional site-based modeling

analysis) are presented in Table 4.6; the SI infiltration rates for each climate center

are presented in Appendix A.

Table 4.6 Cumulative Frequency Distribution of Surface Impoundment

Infiltration

%

No Liner Infiltration

Rate (m/yr)

Clay Liner Infiltration

Rate (m/yr)

Composite Liner

Infiltration Rate (m/yr)

0

10

25

50

75

80

85

90

95

100

3.78E-15

2.71E-01

5.21E-01

1.14E+00

2.27E+00

2.58E+00

2.94E+00

3.51E+00

4.51E+00

2.23E+01

3.78E-15

4.22E-02

6.29E-02

1.08E-01

1.63E-01

1.76E-01

1.94E-01

2.17E-01

2.69E-01

7.98E-01

0.00E+00

0.00E+00

0.00E+00

4.88E-05

2.02E-04

2.67E-04

3.55E-04

4.98E-04

7.51E-04

3.69E-03

Data Sources

In a location-specific modeling analysis, the site-specific infiltration rate can

be directly specified in the input file – either as a constant value or as a statistical or

empirical distribution of values.

To create the surface impoundment site data file for use with EPACMTP,

EPA used unit-specific data for SIs from EPA’s Surface Impoundment Study (U.S.

EPA, 2001a). The resulting sediment layer permeability has a relatively narrow

range of variation between 1.26×10

-7 and 1.77×10-7

cm/s. This database of surface

impoundment sites is tabulated in Appendix D.

Default data on leak density were compiled from 26 leak density values

reported in TetraTech (2001). Further details of the methodology and data used to

derive SI infiltration for the composite liner scenario are presented in Section 4.2.2.4

of the IWEM Technical Background Document (U.S. EPA, 2003c).
Section 4.0 Infiltration and Recharge Parameters

4-15

Use In EPACMTP

The surface impoundment infiltration rate is used by the model to determine

the leachate flux to the subsurface and as an input to the subsurface flow and

transport modules.

4.4 RECHARGE RATE (IR)

Definition

The recharge rate is the rate at which water percolates through the soil to the

water table outside the footprint of the WMU. The recharge rate is determined by

regional climatic conditions, such as precipitation, evapotranspiration, surface runoff, and regional soil type. The ambient regional rate may be different from the

infiltration rate through the WMU due to the engineering design of the unit (e.g.,

landfill cover soil of a different type, hydraulic head of the impoundment, or low

waste conductivity), topography, land use, and/or vegetation. The recharge rate is

determined by the regional climatic and soil conditions, such as precipitation,

evapotranspiration, surface run-off, and regional soil type. Note that both infiltration

and recharge are specified as areal rates, with the units of cubic meters of fluid

(water or leachate) per square meter per year (m3

/m2/yr). Thus, the units for

infiltration and recharge simplify to meters per year (m/yr).

Parameter Value or Distribution of Values

EPA created the database of recharge rates for the three primary soil types

across the United States (SNL, SLT, and SCL) and ambient climate conditions at

102 climate stations through the use of the HELP water-balance model as presented

in Appendix A. The ambient regional recharge rate for a given climate center and

soil type (for all four WMU types) was assumed to be the same as the corresponding

unlined LF infiltration rate. The cumulative frequency distribution of recharge

(produced by running a standard regional site-based modeling analysis for a landfill)

are presented in Table 4.7; the recharge rate for each climate center is presented in

Appendix A.
Section 4.0 Infiltration and Recharge Parameters

4-16

Table 4.7 Cumulative Frequency Distribution of Regional Recharge Rate

% Recharge Rate (m/yr)

0

10

25

50

75

80

85

90

95

100

1.00E-05

1.35E-02

6.86E-02

1.22E-01

3.08E-01

3.42E-01

3.90E-01

4.38E-01

4.67E-01

1.15E+00

Data Sources

The HELP model was used to estimate the ambient regional recharge rate,

using the procedure described in Appendix A. Note that the recharge rate for a

given climate center and soil type (for all 4 types of WMUs) is assumed to be the

same as the corresponding unlined landfill infiltration rate (see Section 4.3.1.1).

Use In EPACMTP

When the EPACMTP model is run using the regional, site-based

methodology, the model selects a site at random from those in the site data file for

each Monte Carlo realization. The climate center index associated with the chosen

site and the randomly generated soil type are then used by the model to determine

the recharge value of the site from the HELP database also included in the site data

file.

In a location-specific modeling analysis, the site-specific regional recharge

rate can be directly specified in the input file – either as a constant value or as a

statistical or empirical distribution of values.

Once the recharge rate is generated, it is used by the model as an input to

the subsurface flow and transport modules.
Section 5.0 Hydrogeological Parameters

5-1

5.0 HYDROGEOLOGICAL PARAMETERS

EPACMTP treats the subsurface aquifer system as a composite domain,

consisting of an unsaturated (vadose) zone and an underlying saturated zone (an

unconfined aquifer). The boundary between the two zones is the water table. The

unsaturated zone and saturated zone modules are computationally linked through

continuity of flow and constituent concentration across the water table directly

underneath the waste management unit (WMU). The model accounts for the

following processes affecting constituent fate and transport as the constituent

migrates from the bottom of a WMU through the unsaturated and saturated zones:

advection, hydrodynamic dispersion and molecular diffusion, linear or nonlinear

equilibrium sorption, first-order decay and zero-order production reactions (to

account for transformation breakdown products), and dilution due to recharge in the

saturated zone.

This section discusses the individual hydrogeological parameters

characterizing the soil and aquifer that are required to perform a modeling analysis

using EPACMTP. Although most applications of EPACMTP are conducted on a

national or regional basis for regulatory development purposes, EPACMTP can also

be used in a location-specific mode. In either case, each of the input parameters

describing the soil and aquifer beneath the waste site being modeled can be

specified as a constant value or as a statistical or empirical distribution of values. As

a practical matter, however, many of these inputs are commonly specified using a

distribution of values.

There are a number of data sources available to obtain parameter values for

the unsaturated and saturated zone modeling in EPACMTP. For unsaturated zone

modeling, we used a database of soil hydraulic properties for various soil types,

assembled by Carsel and Parrish (1988), in combination with information from the

Soil Conservation Service (SCS) on the nationwide prevalence of different soil types

across the United States. Another primary data source was the Hydrogeologic

Database for Ground-Water Modeling (HGDB), assembled by Rice University on

behalf of the American Petroleum Institute (API) (Newell, Hopkins, and Bedient,

1990). This database provides probability distributions of a number of key groundwater modeling parameters for various types of subsurface environments.

The HGDB was developed from a survey of the hydrogeologic characteristics

at actual hazardous waste sites in the United States and provides site specific data

on ground water parameters (aquifer thickness, unsaturated zone thickness,

hydraulic gradient and hydraulic conductivity) collected by independent investigators

for approximately 400 hazardous waste sites throughout the U.S. These sitespecific data were then regrouped into 13 hydrogeologic environments, based on the

USGS classification of aquifer regions (Heath, 1984) (12 specific environments and

one category called “other”). The result is a database of aquifer types, with each

aquifer type consisting of an empirical distribution of values for each of the four

aquifer parameters.
Section 5.0 Hydrogeological Parameters

5-2

These hydrogeological parameters are individually described in the following

sections.

5.1 HYDROGEOLOGICAL PARAMETERS

The hydrogeological input parameters include parameters to characterize

both the flow regime and constituent transport in both the unsaturated zone and

aquifer in the vicinity of the modeled WMU. These parameters are listed in Table

5.1.

5.2 UNSATURATED ZONE PARAMETERS

In the unsaturated zone, EPACMTP simulates one-dimensional, vertically

downward flow and transport of constituents between the base of the WMU and the

water table. The unsaturated zone-specific model inputs used by the model to

simulate the fate of constituents as they are transported through the subsurface

include the unsaturated zone thickness, hydraulic conductivity and other hydraulic

properties of the soil, the bulk density of the soil, the dispersivity in the unsaturated

zone, percent organic matter, and parameters describing the sorption and/or

degradation of the modeled constituent. The primary output from the unsaturated

zone module is the predicted contaminant concentration entering the saturated zone

at the water table, either as a function of time (the breakthrough curve) or at

steady-state.

These unsaturated zone parameters are individually described in the

following sections.

5.2.1 Unsaturated Zone Thickness (Du

)

Definition

The unsaturated zone thickness is the vertical distance from the ground

surface to the water table. The water table in this case is meant to represent the

‘natural’ water elevation, as it is or would be without the influence from the WMU.

The presence of a WMU, particularly a surface impoundment, may cause a local rise

in the water table called mounding. The EPACMTP model assumes that the

unsaturated zone thickness value you have entered does not include mounding.

The model will calculate the predicted impact of the WMU and liner design (if any)

on the ground water as part of the modeling evaluation.

Note that in cases where the WMU is excavated, such that the base of the

unit is below ground surface, the unsaturated zone thickness should be the longterm average regional depth to ground water, measured outside the footprint of the

WMU. The input variable Depth Below Grade (see Sections 2.3.3, 2.4.6, and 2.5.3)

is used to correct the unsaturated zone thickness beneath an excavated WMU.
Section 5.0 Hydrogeological Parameters

5-3

Table 5.1 Hydrogeological Parameters

Module Parameter

Symbo

l Units Section

Equation in

EPACMTP

Tech. Bkgd.

Doc

Unsaturate

d

Z

one

Unsaturated Zone

Thickness

Du m 5.2.1 3.9

Soil Type Index ISTYPE unitless 5.2.2

Soil Hydraulic Conductivity Ks cm/hr 5.2.3.1 3.4

Alpha  1/cm 5.2.3.2 3.1

Beta unitless 5.2.3.3 3.1

Residual Water Content r unitless 5.2.3.4 3.1

Saturated Water Content s unitless 5.2.3.5 3.1

Soil Bulk Density ρbug/cm3 5.2.3.6 3.16

Percent Organic Matter %OM unitless 5.2.3.7 3.10

Dispersivity αLum 5.2.4 3.9

Leading Coefficient of

Freundlich Isotherm

Kd cm

3

/g 5.2.5.1 3.11

Exponent of Freundlich

Isotherm

 unitless 5.2.5.2 3.18

Chemical Degradation

Rate

 cu 1/yr 5.2.6 3.13

Biodegradation Rate bu 1/yr 5.2.7 3.12

Soil Temperature T

oC 5.2.8 4.4.3.3

Soil pH pH standard

units

5.2.9 4.4.3.4

S

aturate

d

Z

one

Particle Diameter d cm 5.3.1 4.1

Porosity  unitless 5.3.2 4.2

Bulk Density b g/cm3 5.3.3 4.3

Hydrogeologic

Environment Index

IGWR unitless 5.3.4.2

Saturated Zone Thickness B m 5.3.4.3 2.31

Hydraulic Conductivity K m/yr 5.3.4.4 4.4

Regional Hydraulic

Gradient

r unitless 5.3.4.5 4.6

Seepage Velocity Vx m/yr 5.3.5 4.6

Anisotropy Ratio Ar unitless 5.3.6 4.5

Retardation Coefficient R

s

unitless 5.3.7 4.18

Longitudinal Dispersivity L m 5.3.8.1 4.19
Section 5.0 Hydrogeological Parameters

Module Parameter

Symbo

l Units Section

Equation in

EPACMTP

Tech. Bkgd.

Doc

5-4

S

aturate

d zone

Horizontal Transverse

Dispersivity

T m 5.3.8.2 4.28

Vertical Dispersivity V m 5.3.8.3 4.29

Aquifer Temperature T °C 5.3.9 4.4.3.3

Ground-water pH pH standard

units

5.3.10 Section

4.4.3.4

Fractional Organic Carbon

Content

unitless 5.3.11 4.30

Leading Coefficient of

Freundlich Isotherm

cm

3

/g 5.3.12 4.18

Exponent of Freundlich

Isotherm



s

unitless 5.3.13 4.34

Chemical Degradation

Rate

1/yr 5.3.14 Section

4.4.3.9

Biodegradation Rate 1/yr 5.3.15 Section

4.4.3.9

Parameter Value or Distribution of Values

Lacking a site-specific value or distribution of values to input, a default

distribution of unsaturated zone thickness values may be used as part of the

regional site-based modeling methodology. As described in Section 5.5 of the

EPACMTP Technical Background Document (U.S. EPA, 2003a), the regional sitebased modeling methodology is an attempt to ensure that the combination of

parameter values randomly generated by the Monte Carlo module of EPACMTP

represents a realistic set of site conditions. The cumulative frequency distribution of

unsaturated zone thickness listed in Table 5.2 was generated by performing a

default landfill modeling analysis using the regional site-based modeling

methodology; the entire Hydrogeologic Database for Modeling (HGDB) from which

these values were derived is presented in Appendix D.
Section 5.0 Hydrogeological Parameters

5-5

Table 5.2 Cumulative Frequency Distribution of Unsaturated Zone Thickness

% Unsaturated Zone Thickness (m)

0

10

25

50

75

80

85

90

95

100

3.05E-01

1.68E+00

3.96E+00

6.10E+00

1.52E+01

1.83E+01

2.93E+01

4.27E+01

5.08E+01

6.10E+02

Data Sources

EPA obtained data on the unsaturated zone thickness from the

Hydrogeologic Database for Modeling (HGDB; Newell et al., 1990; U.S. EPA,

1997d). A database of soil hydraulic properties for various soil types, assembled by

Carsel and Parrish (1988) was also used, in combination with information from the

Soil Conservation Service (SCS) on the nationwide prevalence of different soil types

across the United States. The Hydrogeologic Database for Modeling (HGDB) from

which the values shown in Table 5.2 were derived is presented in its entirety in

Appendix D.

In the regional site-based Monte Carlo analysis that is typically used for

nationwide modeling applications, the resulting distribution of values for the

thickness of the unsaturated zone is produced through Monte Carlo sampling of the

HGDB, based on the hydrogeologic environment assigned to the waste site selected

for each model realization. In a location-adjusted or quasi-site-specific modeling

analysis, the site-specific unsaturated zone thickness can be directly specified as a

constant value or an empirical or statistical distribution of values.

Use In EPACMTP

The EPACMTP model uses the unsaturated zone thickness to determine the

travel distance of leachate constituents in the unsaturated zone.

5.2.2 Soil Type (ISTYPE)

Definition

Soil type is a way to group or classify soils with similar properties. EPACMTP

incorporates three soil types, sandy loam, silt loam, and silty clay loam, that

represent the most prevalent soil types across the U.S.
Section 5.0 Hydrogeological Parameters

5-6

The soil type is indicated by a numerical index which is simply a sequential

number assigned to each soil type in the default database included with EPACMTP

in order to provide a simple means of specifying which distributions should be used

to generate the input values for the soil characteristics required to run the model.

Parameter Value or Distribution of Values

The soil types for which default data are available are listed in Table 5.3; the

corresponding soil parameter distributions are summarized in Section 5.2.3. When

performing a regional site-based modeling analysis of a landfill, waste pile, or land

application unit, the soil type is randomly chosen based on the nationwide frequency

of occurrence, based on Soil Conservation Service (SCS) soil mapping data. These

percentages are shown below in Table 5.3. When performing a regional site-based

modeling analysis of a WMU, the soil type for each unit is specified in the default site

data file.

Table 5.3 Default EPACMTP Soil Types

Soil Type

Index Texture Soil Name Abbreviation

Frequency of

Occurrence

1 medium silt loam SLT 56.6%

2 coarse sandy loam SNL 15.4%

3 fine silty clay

loam

SCL 28%

Data Sources

Parameter distributions for soil parameters were compiled by Carsel and

Parrish (1988). Information on the relative frequency of each soil type was obtained

from the U.S. Soil Conservation Service as part of the risk analysis in support of

EPA’s development of the Toxicity Characteristic Final Rule (U.S. EPA, 1990).

Use In EPACMTP

To perform a typical Monte Carlo analysis using the regional site-based

modeling methodology, the soil type index should be left in its default setting, ensuring

that the appropriate climatic data is used for each WMU site in the database. However,

if a location-specific analysis is being performed, then this input can either be omitted

from the input file (if site-specific values for the soil characteristics are available) or set

to the appropriate constant value to make use of the default soil data which are included

in the model.
Section 5.0 Hydrogeological Parameters

5-7

5.2.3 Soil Hydraulic Characteristics

EPACMTP uses the so-called van Genuchten model to describe the soil

hydraulic characteristics. The parameters used to describe the soil hydraulic

characteristics include residual water content, saturated water content, and two van

Genuchten empirical water soil moisture parameters (alpha and beta).

Solution of the unsaturated zone flow requires knowledge of the soil characteristic

curves, i.e., the relationship between water saturation and pressure head and between

hydraulic conductivity and water saturation. The van Genuchten (1980) model is widely

used for predicting soil-water content as a function of pressure head. Descriptive

statistical values for the parameters used in this model have been determined by Carsel

and Parrish (1988) for 12 soil classifications. The statistical distributions for the

parameters presented in Carsel and Parrish (1988) (as well as the bulk density and

percent organic matter from Carsel et al., 1988) for the three default soil types used in

EPACMTP are presented in Table 5.4. The variables analyzed by Carsel and Parrish

include saturated hydraulic conductivity (Ks), residual water content (r), saturated water

content ( s

), and three empirical constants (, , and ). Probability distributions for ,

, and  for all 12 soil types from Carsel and Parrish (1988) are presented in Table 5.6.

5.2.3.1 Soil Hydraulic Conductivity (Ks

)

Definition

The hydraulic conductivity of the soil is a measure of the soil’s ability to transmit

water under fully saturated conditions.

Parameter Value or Distribution of Values

If site-specific data are available, then the soil hydraulic conductivity can be

specified as a constant value or an empirical or statistical distribution of values.
Section 5.0 Hydrogeological Parameters

5-8

Table 5.4 Statistical parameters for soil properties for three soil types used in

the EPACMTP model (Carsel and Parrish, 1988 and Carsel et al., 1988).

All values are in arithmetic space

Variable

Distribution

Type

Limits of Variation

Mean

Standard

Minimum Maximum Deviation

Soil Type - Silty Clay Loam

KS cm/hr

r

 cm-1



% OM

b

s

SB

NO

SB

NO

SB

Constant

Constant

0.

0.00

0.00

1.0

0.0

-

-

3.5

0.115

0.15

1.5

8.35

-

-

0.017

0.089

.009

1.236

0.11

1.67

0.43

2.921

0.0094

.097

0.061

5.91

-

-

Soil Type - Silt Loam

KS cm/hr

r

 cm-1



% OM

b

s

LN

SB

LN

SB

SB

Constant

Constant

0.

0.00

0.00

1.0

0.0

-

-

15.0

0.11

0.15

2.0

8.51

-

-

.343

.068

.019

1.409

0.105

1.65

0.45

.989

0.071

0.012

1.629

5.88

-

-

Soil Type - Sandy Loam

KS cm/hr

r

 cm-1



% OM

b

s

SB

SB

SB

LN

SB

Constant

Constant

0.

0.

0.

1.35

0.0

-

-

30.0

0.11

0.25

3.00

11.0

-

-

2.296

0.065

0.070

1.891

0.074

1.60

0.41

24.65

0.074

0.171

0.155

7.86

-

-

% OM = Percent Organic Matter

NO = Normal distribution

SB = Log ratio distribution, Y = ln [(x-A)/(B-x)], A < x < B

LN = Log normal distribution, Y = ln[x]

where Y = normal distributed parameter

x = actual data

Ks = Saturated Hydraulic Conductivity

r = Residual water content

,= van Genuchten parameters

b = Bulk density

s = Saturated Water Content
Section 5.0 Hydrogeological Parameters

5-9

Lacking site-specific data, a default distribution of soil hydraulic conductivity

values may be used as part of the regional site-based modeling methodology (see

Section 5.5 of the EPACMTP Technical Background Document (U.S. EPA, 2003a)).

The EPACMTP model includes a database of soil characteristics for each of three

default soil types; hydraulic conductivity is one of the soil characteristics included in

these default databases. A statistical summary of the values used for each of the three

default soil types, including hydraulic conductivity, is shown in Table 5.4, above. The

cumulative frequency distribution of soil hydraulic conductivity values listed in Table 5.5

was generated by performing a default nationwide landfill modeling analysis using the

regional site-based modeling methodology. For a given percentile (%) frequency and

value pair in Table 5.5, the percentile denotes the relative frequency or likelihood of

parameter values in the entire distribution being less than or equal to the corresponding

parameter value in the right hand column.

Table 5.5 Cumulative Frequency Distribution of Soil Hydraulic Conductivity

% Soil Hydraulic Conductivity (cm/hr)

0

10

25

50

75

80

85

90

95

100

4.30E-05

6.79E-03

2.33E-02

8.90E-02

3.99E-01

6.09E-01

9.97E-01

1.93E+00

4.41E+00

2.79E+01

Data Sources

The databases of soil characteristics for the three default soil types (which

include soil hydraulic conductivity) were derived from soil hydraulic property data

reported by Carsel and Parrish (1988).

Use In EPACMTP

The hydraulic conductivity of the soil is used as an input to the unsaturated zone

flow module and is used to calculate the moisture content in the soil under a given rate

of leachate infiltration from the WMU.
5-10

Table 5.6 Descriptive statistics for van Genuchten water retention model parameters, , 

(Carsel and Parrish, 1988)

Parameter , cm-1 Parameter Para

Soil Type X SD CV N X SD CV N X SD 

Claya 0.008 0.012 160.3 400 1.09 0.09 7.9 400 0.08 0.07 

Clay Loam 0.019 0.015 77.9 363 1.31 0.09 7.2 364 0.24 0.06 Loam 0.036 0.021 57.1 735 1.56 0.11 7.3 735 0.36 0.05 Loamy Sand 0.124 0.043 35.2 315 2.28 0.27 12.0 315 0.56 0.04 

Silty Clay 0.005 0.005 113.6 126 1.09 0.06 5.0 374 0.08 0.05 

Silty Clay

Loam

0.010 0.006 61.5 641 1.23 0.06 5.0 641 0.19 0.04 

Silt 0.016 0,007 45.0 82 1.37 0.05 3.3 82 0.27 0.02 

Silt Loam 0.020 0.012 64.7 109

3

1.41 0.12 8.5 109

3

0.29 0.06 

Sandy Clay 0.027 0.017 61.7 46 1.23 0.10 7.9 46 0.19 0.06 

Sandy Clay

Loam

0.059 0.038 64.6 214 1.48 0.13 8.7 214 0.32 0.06 

Sandy Loam 0.075 0.037 49.4 118

3

1.89 0.17 9.2 118

3

0.47 0.05 

Sand 0.145 0.029 20.3 246 2.68 0.29 20.3 246 0.63 0.04 

N = Sample size, X = Mean

SD = Standard Deviation

CV = Coefficient of Variation (percent)

a

= Agricultural Soil, Clay 60 percent

 = 1-1/Section 5.0 Hydrogeological Parameters

5-11

5.2.3.2 Alpha ()

Definition

Alpha is a soil-specific shape parameter that is obtained from an empirical

relationship between pressure head and volumetric water content; it is one of the

parameters in the van Genuchten (1980) model used for modeling soil-water content

as a function of pressure head, and is used to calculate the moisture content in the soil

under a given rate of leachate infiltration from the WMU.

Parameter Value or Distribution of Values

If site-specific data are available, then the van Genuchten parameter alpha can

be specified in the input file as a constant value or an empirical or statistical distribution

of values.

Lacking site-specific data, a default distribution of soil hydraulic conductivity

values may be used as part of the regional site-based modeling methodology (see

Section 5.5 of the EPACMTP Technical Background Document (U.S. EPA, 2003a)).

The EPACMTP model includes a database of soil characteristics for each of three

default soil types; van Genuchten parameter alpha is one of the soil characteristics

included in these default databases. A statistical summary of the values used for each

of the three default soil types, including the van Genuchten parameter alpha, is shown

in Table 5.4. The cumulative frequency distribution of soil hydraulic conductivity values

listed in Table 5.7 was generated by performing a default nationwide landfill modeling

analysis using the regional site-based modeling methodology. For a given percentile

(%) frequency and value pair in Table 5.7, the percentile denotes the relative frequency

or likelihood of parameter values in the entire distribution being less than or equal to the

corresponding parameter value in the right hand column.

Table 5.7 Cumulative Frequency Distribution of Alpha

% Alpha (1/cm)

0

10

25

50

75

80

85

90

95

100

1.29E-03

5.96E-03

9.35E-03

1.52E-02

2.71E-02

3.26E-02

4.22E-02

5.90E-02

8.92E-02

2.18E-01
Section 5.0 Hydrogeological Parameters

5-12

Data Sources

The databases of soil characteristics for the three default soil types (which

include the van Genuchten parameter ()) were derived from soil hydraulic property

data reported by Carsel and Parrish (1988).

Use In EPACMTP

The van Genuchten parameter alpha is an input to the unsaturated zone flow

module and is used to calculate the moisture content in the soil under a given rate of

leachate infiltration from the WMU.

5.2.3.3 Beta ()

Definition

Beta is a soil-specific shape parameter that is obtained from an empirical

relationship between pressure head and volumetric water content; it is one of the

parameters in the van Genuchten (1980) model used for modeling soil-water content

as a function of pressure head.

Parameter Value or Distribution of Values

If site-specific data are available, then the van Genuchten parameter beta can

be specified in the input file as a constant value or an empirical or statistical distribution

of values.

Lacking site-specific data, a default distribution of soil hydraulic conductivity

values may be used as part of the regional site-based modeling methodology (see

Section 5.5 of the EPACMTP Technical Background Document (U.S. EPA, 2003a)).

The EPACMTP model includes a database of soil characteristics for each of three

default soil types; van Genuchten parameter beta is one of the soil characteristics

included in these default databases. A statistical summary of the values used for each

of the three default soil types, including the van Genuchten parameter beta, is shown

in Table 5.4. The cumulative frequency distribution of soil hydraulic conductivity values

listed in Table 5.8 was generated by performing a default nationwide landfill modeling

analysis using the regional site-based modeling methodology. For a given percentile

(%) frequency and value pair in Table 5.8, the percentile denotes the relative frequency

or likelihood of parameter values in the entire distribution being less than or equal to the

corresponding parameter value in the right hand column.
Section 5.0 Hydrogeological Parameters

5-13

Table 5.8 Cumulative Frequency Distribution of Beta

% Beta (unitless)

0

10

25

50

75

80

85

90

95

100

1.03E+00

1.20E+00

1.27E+00

1.37E+00

1.53E+00

1.58E+00

1.68E+00

1.82E+00

1.96E+00

2.50E+00

Data Sources

The databases of soil characteristics for the three default soil types (which

include the van Genuchten parameter ()) were derived from soil hydraulic property

data reported by Carsel and Parrish (1988).

Use In EPACMTP

The van Genuchten parameter beta is an input to the unsaturated zone flow

module and is used to calculate the moisture content in the soil under a given rate of

leachate infiltration from the WMU.

5.2.3.4 Residual Water Content (r)

Definition

At atmospheric pressure, the saturated water content represents the maximum

fraction of the total volume of soil that is occupied by the water contained in the soil.

The soil will remain saturated as the pressure head is gradually decreased. Eventually,

as the pressure head decreases to a threshold known as the bubbling pressure, the

water will begin to drain from the soil. The moisture content will continue to decline as

the pressure head is lowered until it reaches some irreducible residual water content.

Should the pressure head be further reduced, the soil would not lose any additional

moisture.

Parameter Value or Distribution of Values

If site-specific data are available, then the residual water content of the soil can

be specified as a constant value or an empirical or statistical distribution of values.

Lacking site-specific data, a default distribution of soil hydraulic conductivity

values may be used as part of the regional site-based modeling methodology (see
Section 5.0 Hydrogeological Parameters

5-14

Section 5.5 of the EPACMTP Technical Background Document (U.S. EPA, 2003a)).

The EPACMTP model includes a database of soil characteristics for each of three

default soil types; residual water content is one of the soil characteristics included in

these default databases. A statistical summary of the values used for each of the three

default soil types, including the residual water content of the soil, is shown in Table 5.4.

The cumulative frequency distribution of soil hydraulic conductivity values listed in Table

5.9 was generated by performing a default nationwide landfill modeling analysis using

the regional site-based modeling methodology. For a given percentile (%) frequency

and value pair in Table 5.9, the percentile denotes the relative frequency or likelihood

of parameter values in the entire distribution being less than or equal to the

corresponding parameter value in the right hand column.

Table 5.9 Cumulative Frequency Distribution of Residual Water Content

% Residual Water Content (unitless)

0

10

25

50

75

80

85

90

95

100

1.06E-02

4.89E-02

6.09E-02

7.46E-02

8.57E-02

8.80E-02

9.07E-02

9.37E-02

9.81E-02

1.15E-01

Data Sources

The databases of soil characteristics for the three default soil types (which

include the residual water content) were derived from soil hydraulic property data

reported by Carsel and Parrish (1988).

Use In EPACMTP

The residual water content is an input to the unsaturated zone flow module and

is used to calculate the moisture content in the soil under a given rate of leachate

infiltration from the WMU.
Section 5.0 Hydrogeological Parameters

5-15

5.2.3.5 Saturated Water Content (s)

Definition

At atmospheric pressure, the saturated water content represents the maximum

fraction of the total volume of soil that is occupied by the water contained in the soil.

Parameter Value or Distribution of Values

If site-specific data are available, then the saturated water content of the soil can

be specified in the input file as a constant value or an empirical or statistical distribution

of values.

Lacking site-specific data, a default distribution of soil hydraulic conductivity

values may be used as part of the regional site-based modeling methodology (see

Section 5.5 of the EPACMTP Technical Background Document (U.S. EPA, 2003a)).

The EPACMTP model includes a database of soil characteristics for each of three

default soil types; saturated water content is one of the soil characteristics included in

these default databases. A statistical summary of the values used for each of the three

default soil types, including the saturated water content of the soil, is shown in Table

5.4. The cumulative frequency distribution of soil hydraulic conductivity values listed in

Table 5.10 was generated by performing a default nationwide landfill modeling analysis

using the regional site-based modeling. For a given percentile (%) frequency and value

pair in Table 5.10, the percentile denotes the relative frequency or likelihood of

parameter values in the entire distribution being less than or equal to the corresponding

parameter value in the right hand column.

Table 5.10 Cumulative Frequency Distribution of Saturated Water Content

% Saturated Water Content (unitless)

0

10

25

50

75

80

85

90

95

100

4.10E-01

4.10E-01

4.30E-01

4.50E-01

4.50E-01

4.50E-01

4.50E-01

4.50E-01

4.50E-01

4.50E-01
Section 5.0 Hydrogeological Parameters

5-16

Data Sources

The databases of soil characteristics for the three default soil types (which

include the saturated water content) were derived from soil hydraulic property data

reported by Carsel and Parrish (1988).

Use In EPACMTP

The saturated water content is an input to the unsaturated zone flow module and

is used to calculate the moisture content in the soil under a given rate of leachate

infiltration from the WMU.

5.2.3.6 Soil Bulk Density (b)

Definition

The dry bulk density of the soil is the ratio of the mass of the solid soil to its total

volume.

Parameter Value or Distribution of Values

If site-specific data are available, then the soil bulk density can be specified in

the input file as a constant value or an empirical or statistical distribution of values.

Lacking site-specific data, a default distribution of soil hydraulic conductivity

values may be used as part of the regional site-based modeling methodology (see

Section 5.5 of the EPACMTP Technical Background Document (U.S. EPA, 2003a)).

The EPACMTP model includes a database of soil characteristics for each of three

default soil types; soil bulk density is one of the soil characteristics included in these

default databases. A statistical summary of the values used for each of the three

default soil types, including the soil bulk density, is shown in Table 5.4. The cumulative

frequency distribution of soil hydraulic conductivity values listed in Table 5.11 was

generated by performing a default nationwide landfill modeling analysis using the

regional site-based modeling methodology. For a given percentile (%) frequency and

value pair in Table 5.11, the percentile denotes the relative frequency or likelihood of

parameter values in the entire distribution being less than or equal to the corresponding

parameter value in the right hand column.
Section 5.0 Hydrogeological Parameters

5-17

Table 5.11 Cumulative Frequency Distribution of Soil Bulk Density

% Soil Bulk Density (g/cm3)

0

10

25

50

75

80

85

90

95

100

1.60E+00

1.60E+00

1.65E+00

1.65E+00

1.67E+00

1.67E+00

1.67E+00

1.67E+00

1.67E+00

1.67E+00

Data Sources

The databases of soil characteristics for the three default soil types (which

include the bulk density) were derived from soil property data reported by Carsel et al

(1988).

Use In EPACMTP

The dry soil bulk density (mass of soil per unit volume) is used to calculate the

retardation coefficient of organic constituents and to convert soil mass to volume.

5.2.3.7 Percent Organic Matter (%OM)

Definition

The percent organic matter is a measure of the organic material that is present

within the soil of the unsaturated zone, measured as a weight percent.

Parameter Value or Distribution of Values

If site-specific data are available, then the percent organic matter in the soil can

be specified in the input file as a constant value or an empirical or statistical distribution

of values.

Lacking site-specific data, a default distribution of soil hydraulic conductivity

values may be used as part of the regional site-based modeling methodology (see

Section 5.5 of the EPACMTP Technical Background Document (U.S. EPA, 2003a)).

The EPACMTP model includes a database of soil characteristics for each of three

default soil types; hydraulic conductivity is one of the soil characteristics included in

these default databases. A statistical summary of the values used for each of the three

default soil types, including the percent organic matter in the soil, is shown in Table 5.4.

The cumulative frequency distribution of soil hydraulic conductivity values listed in Table
Section 5.0 Hydrogeological Parameters

5-18

5.12 was generated by performing a default nationwide landfill modeling analysis using

the regional site-based modeling methodology. For a given percentile (%) frequency

and value pair in Table 5.12, the percentile denotes the relative frequency or likelihood

of parameter values in the entire distribution being less than or equal to the

corresponding parameter value in the right hand column.

Table 5.12 Cumulative Frequency Distribution of Percent Organic Matter

% Percent Organic Matter (unitless)

0

10

25

50

75

80

85

90

95

100

3.58E-03

1.05E-01

7.87E-02

4.05E-02

1.18E-01

1.42E-01

1.72E-01

2.15E-01

2.96E-01

1.69E+00

Data Sources

The databases of soil characteristics for the three default soil types (which

include the percent organic matter) were derived from soil property data reported by

Carsel et al (1988).

Use In EPACMTP

For organic constituents, the percent organic matter in the soil which is specified

in the input file is internally converted by the EPACMTP model to fractional organic

carbon content through the following equation (Enfield et al., 1982):

foc = % OM / 174 (5.1)

where:

foc = fractional organic carbon content,

%OM = percent organic matter, and

174 = conversion factor.

Once the fractional organic carbon content is obtained, it is used to calculate the

unsaturated zone linear distribution coefficient for organic constituents (kd

, see Section

5.2.8) assuming that hydrophobic binding dominates the sorption process
Section 5.0 Hydrogeological Parameters

5-19

(Karickhoff, 1985). The distribution coefficient is then used to calculate the amount by

which contaminant transport is retarded relative to the ambient ground-water flow

velocity within the vadose zone.

This input is not used for modeling the transport of metals.

5.2.4 Unsaturated Zone Longitudinal Dispersivity (Lu)

Definition

Dispersion is the phenomenon by which a dissolved constituent in soil or ground

water is mixed with uncontaminated water and becomes reduced in concentration at the

perimeter of the plume. Not all of a constituent is traveling at the same velocity, due to

differences in pore size and flow path length and friction along pore walls, resulting in

mixing along the flow path which decreases solute concentrations. Note that the

unsaturated zone longitudinal dispersivity is measured along the path of flow, that is,

in the downward direction.

Parameter Value or Distribution of Values

The longitudinal dispersivity of the soil can be input as a constant value or a

distribution of values, if site-specific data are available. If not, the dispersivity can be

derived as a linear function of the total depth of the unsaturated zone according the

following equation which is based on a regression analysis of data presented by EPRI

(1985):

αLu = 0.02 + 0.022 Du(5.2)

where

Lu = longitudinal dispersivity (m)

Du = total depth of the unsaturated zone (m)

The cumulative frequency distribution of soil hydraulic conductivity values listed

in Table 5.13 was generated by performing a default nationwide landfill modeling

analysis using the regional site-based modeling methodology. The unsaturated zone

dispersivity was specified as a derived variable in the input file, and this distribution of

values was created through the Monte Carlo sampling of unsaturated zone thickness

from the linked WMU site and HGDB databases (see Section 5.3.4). For a given

percentile (%) frequency and value pair in Table 5.13, the percentile denotes the

relative frequency or likelihood of parameter values in the entire distribution being less

than or equal to the corresponding parameter value in the right hand column.
Section 5.0 Hydrogeological Parameters

5-20

Table 5.13 Cumulative Frequency Distribution of Dispersivity

% Dispersivity (m)

0

10

25

50

75

80

85

90

95

100

2.67E-02

5.70E-02

1.07E-01

1.54E-01

3.54E-01

4.23E-01

6.65E-01

9.59E-01

1.00E+00

1.00E+00

Data Sources

Lacking site-specific data to input, Equation 5.1 is used to calculate the unsaturated

zone dispersivity. This equation is based on a regression analysis of data presented

by EPRI (1985) (shown in Table 5.14) and has a correlation coefficient of 0.66.

Use In EPACMTP

The longitudinal dispersivity of the unsaturated zone is an input to the

unsaturated zone transport module and is used to calculate the concentration history

(breakthrough curve) of the constituent plume arriving at the water table.
Section 5.0 Hydrogeological Parameters

5-21

Table 5.14 Compilation of field dispersivity values (EPRI, 1985)

Author

Type of

Experiment

Vertical Scale of

Experiment (m)

Longitudinal

Dispersivity

L(m)

Yule and Gardner

(1978)

Laboratory 0.23 0.0022

Hildebrand and Himmelblau

(1977)

Laboratory 0.79 0.0018

Kirda et al. (1973) Laboratory 0.60 0.004

Gaudet et al. (1977) Laboratory 0.94 0.01

Brissaud et al.

(1983)

Field 1.00 0.0011,

0.002

Warrick et al.

(1971)

Field 1.20 0.027

Van de Pol et al.

(1977)

Field 1.50 0.0941

Biggar and Nielsen

(1976)

Field 1.83 0.05

Kies (1981) Field 2.00 0.168

Jury et al. (1982) Field 2.00 0.0945

Andersen et al.

(1968)

Field 20.00 0.70

Oakes (1977) Field 20.00 0.20

5.2.5 Freundlich Adsorption Isotherm Parameters

An adsorption isotherm is an expression of the equilibrium relationship

between the aqueous concentration and the sorbed concentration of a chemical

constituent (organic or metal) at a constant temperature. One of the general models

of the sorption process is the Freundlich isotherm, defined as follows:

S = KC



(5.3a)

where:

S = mass of constituent that is sorbed per dry unit weight of solid

(mg/kg)

K = Leading coefficient of the Freundlich isotherm (mg/kg)/(mg/L)



C = aqueous concentration of the constituent at equilibrium with

the sorbed mass (mg/L)

 = Freundlich isotherm exponent (dimensionless)
Section 5.0 Hydrogeological Parameters

5-22

If the sorptive behavior of a constituent can be described by the Freundlich

isotherm, then when log C is plotted against log S, the resulting relationship will be

linear with a slope of  and an intercept of log K. A special case is when  is equal

to 1.0. In this case, the sorption isotherm is linear and the leading Freundlich

coefficient is known as the linear solid-liquid phase distribution coefficient (Kd). A

linear isotherm is commonly used to describe the subsurface fate and transport of

organic constituents, assuming that hydrophobic binding dominates the sorption

process (Karickhoff, 1985). In this case, the Kd can be calculated as follows:

Kd = kocfoc(5.3b)

where

Kd = leading Freundlich coefficient (distribution coefficient) (cm3/g)

koc = normalized organic carbon distribution coefficient (cm3

/g)

foc = fractional organic carbon content (dimensionless)

Equation (5.3a) may be recast as:

S = (KC

-1

)C = Kd(C)C (5.3c)

where:

S = mass of constituent that is sorbed per dry unit weight of solid

(mg/kg)

K = Leading coefficient of the Freundlich isotherm (mg/kg)/(mg/L)



C = aqueous concentration of the constituent at equilibrium with

the sorbed mass (mg/L)

 = Freundlich isotherm exponent (dimensionless)

Kd = distribution coefficient (cm3/g)

The distribution coefficient, Kd, in Equation 5.3c is non-linear and is a function

of aqueous concentration. In EPACMTP, the non-linear Kdfunction in Equation

(5.3c) may be more general than the Freundlich type (see Section 5.2.5.1) below.

To model the fate and transport of constituents with EPACMTP, the user

must specify two adsorption isotherm parameters: the Freundlich sorption

coefficient (K or Kd

) and the Freundlich exponent (). These two parameters are

described in Sections 5.2.5.1 and 5.2.5.2, below.
Section 5.0 Hydrogeological Parameters

5-23

5.2.5.1 Leading Coefficient of Freundlich Isotherm for Unsaturated Zone

(K or Kd)

Definition

The leading coefficient of the Freundlich isotherm is a constant used to

describe the sorptive behavior of a constituent. When the sorption data are plotted

as log C versus log S, the intercept of the resulting line is equal to log K. In the

special case of a linear isotherm, the leading Freundlich coefficient is known as the

linear solid-liquid phase distribution coefficient (Kd

) (commonly called the distribution

coefficient).

Parameter Value or Distribution of Values

When modeling organic constituents with EPACMTP, the leading Freundlich

coefficient is generally specified as a derived parameter in the input file. If derived,

the leading Freundlich coefficient (Kd) is automatically assumed linear and calculated

by the model according to Equation 5.3b. In this case, foc

is internally calculated

from the percent organic matter specified in the unsaturated zone-specific input

group according to Equation 5.2, and kocis a constituent-specific input value (see

Section 3 of this document). However, if site-specific data are available, a constant

value or distribution of values could be used for the leading Freundlich coefficient.

When modeling metals transport in the unsaturated zone with EPACMTP,

the leading Freundlich coefficient can be specified as a constant value or as a

distribution of values, based either on site-specific data or adsorption data reported

in the scientific literature. Alternatively, tables of non-linear sorption isotherms

developed using the MINTEQA2 geochemical model, or equations comprising pHbased (linear) isotherms can be used. For the latter two cases (non-linear isotherms

or pH-based linear isotherms) this input parameter is not used; the record in the

input file is ignored by the model. Instead, the non-linear Kd

(Equation 5.3c) is either

provided in tabular form as a function of the concentration value or calculated as a

function of pH (see Sections 3.3.3.2 and 3.3.3.1.2, respectively).

Data Sources

Generally, the Kdfor organic constituents is specified as a derived parameter;

however, if this option is not appropriate and site-specific data are not available,

there are studies in the scientific literature that provide compilations of Kd’s that have

been measured in the field (for instance, see Risk Assessment for the Listing

Determinations for Inorganic Chemical Manufacturing Wastes; U.S. EPA, 2000). In

this case, the leading Freundlich coefficient would be specified as either a constant

value or a distribution of values (and the Freundlich exponent would be set to its

default value of 1.0).

The leading Freundlich coefficient for metals is specified using either the

non-linear MINTEQA2 isotherms or pH-based linear isotherms that were developed

specifically for use with the EPACMTP model (see Section 3.3.3). However, if
Section 5.0 Hydrogeological Parameters

5-24

neither of these two options is appropriate and site-specific data are not available,

there are studies in the scientific literature that provide compilations of Kd’s that have

been measured in the field (for instance, see Appendix I of U.S. EPA, 2000). In this

case, the leading Freundlich coefficient would be specified as either a constant value

or a distribution of values.

Use In EPACMTP

The leading Freundlich coefficient (also called the distribution coefficient) is

one of the parameters used to calculate the amount by which contaminant transport

is retarded relative to the ambient ground-water flow velocity within the unsaturated

zone. It is an input to the unsaturated zone transport module. For organic

constituents that are subject to hydrolysis, this input is also used as a parameter to

calculate the overall hydrolysis rate.

5.2.5.2 Exponent of Freundlich Isotherm for Unsaturated Zone ()

Definition

The exponent of the Freundlich isotherm is a constant used to describe the

sorptive behavior of a constituent. When the sorption data are plotted as log C

versus log S, the slope of the resulting line is equal to . In the special case of a

linear isotherm, the exponent of the Freundlich isotherm is equal to 1.0.

Parameter Value or Distribution of Values

For modeling organic constituents, the default value of the Freundlich

exponent is 1.0, meaning a linear adsorption isotherm is used.

Generally, the distribution coefficient for metals is specified using either

tabulated non-linear MINTEQA2 isotherms or pH-based linear isotherms that were

developed specifically for use with the EPACMTP model (see Section 3.3.3). In

these two cases, the Kd data is read in from an auxiliary input file or internally

calculated, and the Freundlich isotherm coefficient and exponent are not used. If

the leading Freundlich coefficient is specified using an empirical distribution of

values (e.g., based on reported Kd values in the scientific literature), then the

Freundlich isotherm exponent should be set equal to 1.0.

If this parameter is omitted from the data file, it is assigned a default value of

1.0, which is equivalent to specifying a linear sorption isotherm.

In EPACMTP Version 2.0, only the case of  = 1 is permitted. Non-linear

isotherms (see Equation 5.3c) are handled using the tabular type of input described

in Section 3.3.3.2.
Section 5.0 Hydrogeological Parameters

5-25

Data Sources

For modeling organic constituents, the Freundlich isotherm exponent is

generally set to its default value of 1.0, and so no specific data source is used to

determine the appropriate value for the Freundlich exponent.

For modeling metal constituents, the Freundlich isotherm exponent is not

used as an input parameter, and so no specific data source is used (see Section

3.3.3.2). If literature or site-specific data are used to specify a non-linear adsorption

isotherm, modeling of the adsorption process is implemented via tabular input

describing the relationship in Equation 5.3c.

Use In EPACMTP

The Freundlich exponent is one of the parameters used to calculate the

amount by which contaminant transport is retarded relative to the ambient groundwater flow velocity within the unsaturated zone; it is an input to the unsaturated zone

transport module.

5.2.6 Chemical Degradation Rate Coefficient for Unsaturated Zone (cu)

Definition

EPACMTP accounts for all transformation processes (both biological and

chemical) using a lumped first-order decay coefficient. This overall decay coefficient

is the sum of the chemical and biological transformation coefficients. The chemical

degradation coefficient for the unsaturated zone is simply the rate of decay that is

caused by chemical (usually hydrolysis) reactions in the unsaturated zone.

Parameter Value or Distribution of Values

By default, the chemical degradation coefficient in the unsaturated zone is

set to be internally derived using the hydrolysis rate constants and the unsaturated

zone properties according to Equation 3.4. However, if site-specific data are

available, this parameter can be specified as a constant value or a distribution of

values. In this case, the hydrolysis rate constants can be omitted from the input file.

Data Sources

If this parameter is not derived by the model, then a site-specific data source

must be used to determine the appropriate input value.

Use In EPACMTP

The chemical degradation coefficient is used by the model to calculate the

amount by which contaminant concentrations within the vadose zone are attenuated

due to chemical hydrolysis; it is an input to the unsaturated zone transport module

and is one of the parameters required to solve the transport equation for dissolved
Section 5.0 Hydrogeological Parameters

5-26

leachate constituents (see Sections 3.3.4 and 4.4.4 of the EPACMTP Technical

Background Document (U.S. EPA, 2003a).

5.2.7 Biodegradation Rate Coefficient for Unsaturated Zone (bu)

Definition

EPACMTP accounts for all transformation processes (both biological and

chemical) using a lumped first-order decay coefficient. This overall decay coefficient

is the sum of the chemical and biological transformation coefficients. The biological

degradation coefficient for the unsaturated zone is simply the rate of decay that is

caused by biological processes in the unsaturated zone.

Parameter Value or Distribution of Values

By default, the biological degradation coefficient in the unsaturated zone is

set equal to zero. However, if site-specific data are available, this parameter can be

specified as a constant value or a distribution of values.

Data Sources

If the input value of this parameter is non-zero, then a site-specific data

source must be used to determine the appropriate input value.

Use In EPACMTP

The biological degradation coefficient is used by the model to calculate the

amount by which contaminant concentrations within the vadose zone are attenuated

due to biological processes; it is an input to the unsaturated zone transport module

and is one of the parameters required to solve the transport equation for dissolved

leachate constituents (see Sections 3.3.4 and 4.4.4 of the EPACMTP Technical

Background Document (U.S. EPA, 2003a).

5.2.8 Soil Temperature (T)

Definition

The soil temperature is the long-term average temperature within the vadose

zone. Note that although the temperature within the vadose zone is not an explicit

model input, this temperature is assumed by EPACMTP to be the same as that of

the aquifer.

Parameter Value or Distribution of Values

As modeled in EPACMTP, soil temperature affects the transformation rate of

constituents that are subject to hydrolysis, through the effect of temperature on

reaction rates (see Section 3.3.2.2). In the development of the site data files for

each WMU type, information on average annual temperatures in shallow ground-
Section 5.0 Hydrogeological Parameters

5-27

Figure 5.1 Ground-water Temperature Distribution for Shallow

Aquifers in the United States (from Todd, 1980)

water systems (Todd, 1980) were used to assign a temperature value to each WMU

in the modeling database, based on the unit’s geographical location. For each WMU

site, the assigned temperature was an average of the upper and lower values for

that temperature region, as shown in Figure 5.1. In other words, all WMU’s located

in the band between 10°and 15°were assigned a temperature value of 12.5 °C.

Data Sources

Information on average annual temperatures in shallow ground-water

systems from Todd (1980) were used to assign a temperature value to each WMU

site in the site data files, based on the unit’s geographical location.

Use In EPACMTP

When the EPACMTP model is run using the regional, site-based

methodology, for each Monte Carlo realization, the model selects a site, at random,

from those in the site data file. Since the original data sets did not include all the

site-related input files required by the EPACMTP model, other data sources, such as

this map of ground-water temperatures, are utilized to create a complete data set.

For each WMU site, the ground-water temperature was assigned using the data

from Todd (1980) and the unit’s geographical location.
Section 5.0 Hydrogeological Parameters

5-28

In a location-adjusted modeling analysis, a site-specific ground-water

temperature can be directly specified in the input file – either as a constant value or

as a statistical or empirical distribution of values.

The aquifer temperature associated with the modeled site and the specified

hydrolysis rate constants are then used by the model to derive the appropriate

temperature-dependent first-order hydrolysis rate for organic constituents. Note that

although the temperature of the ground-water within the vadose zone is not an

explicit model input, the EPACMTP model assumes that the soil temperature is the

same as that of the aquifer.

5.2.9 Soil pH (pH)

pH is defined as the negative of the base-10 logarithm of the hydrogen ion

[H

+

] concentration in solution. pH is a measure of acidity. pH values below 7

indicate acidic conditions; values above 7 indicate alkaline conditions.

Parameter Value or Distribution of Values

A nationwide ground-water pH distribution was derived from EPA’s STORET

database (U.S. EPA, 1996). EPACMTP assumes that the ground water is

sufficiently buffered such that pH is not influenced by the input of contaminants or

changes in temperature. The default distribution is an empirical distribution with a

median value of 6.8 or lower and upper bounds of 3.2 and 9.7, respectively. Note

that the value generated for the ground-water pH is assumed to apply to the

unsaturated zone as well.

Data Sources

The pH data distribution was developed from nearly 25,000 field-measured

pH values in EPA’s STORET water quality database (U.S. EPA, 1996). EPA used

these data to develop a pH distribution for ground water that is used in EPACMTP

for the unsaturated zone as well.

Use In EPACMTP

pH is used in the calculation of hydrolysis rates for organic constituents, in

accordance with Equation 3.6.

pH is also one of the key parameters that controls sorption and mobility of

metal constituents. When the default, MINTEQA2 sorption isotherms are used in

EPACMTP, pH is one of the key master variables that controls the selection of a

particular isotherm for each model realization in the Monte Carlo simulation process.

5.3 SATURATED ZONE PARAMETERS

In the saturated zone, EPACMTP simulates ground-water flow and threedimensional constituent transport from the water table to a downgradient well. The
Section 5.0 Hydrogeological Parameters

5-29

saturated zone-specific inputs used by the model to simulate the fate of constituents

as they are transported through the subsurface include particle diameter, porosity,

bulk density, aquifer thickness, hydraulic conductivity, hydraulic gradient, anisotropy

ratio, dispersivity, ground-water temperature and pH, and parameters describing the

sorption and/or degradation of the modeled constituent. The primary model output

is a prediction of the constituent concentration arriving at a downgradient well.

The primary source of data for the default distributions used in the saturated

zone module is the Hydrogeologic Database for Ground-Water Modeling (HGDB),

assembled by Rice University on behalf of the American Petroleum Institute (API)

(Newell et al., 1990). This database provides probability distributions for the

following three aquifer-specific inputs for various types of subsurface environments:

aquifer thickness, hydraulic conductivity, and hydraulic gradient (data on the

unsaturated zone thickness is also included in this database, but this parameter is

discussed with the other unsaturated zone parameters in Section 5.2).

All of the saturated zone parameters are individually described in the

following sections.

5.3.1 Particle Diameter (d)

Definition

The particle diameter is defined as the mean diameter of the particles

constituting the aquifer materials.

Parameter Value or Distribution of Values

Lacking a site-specific value or distribution of values, this input value can be

specified using a default distribution of values (the default option) or it can be

derived based on the aquifer’s porosity. The default distribution of values was

created from data compiled by Shea (1974) and is presented below in Table 5.15.

For a given percentile (%) frequency and value pair in this table, the percentile

denotes the relative frequency or likelihood of parameter values in the entire

distribution being less than or equal to the corresponding parameter value in the

right hand column.

Table 5.16 lists the cumulative frequency distribution of particle diameter that

is generated in a default landfill modeling analysis using the regional site-based

modeling methodology. For a given percentile (%) frequency and value pair in Table

5.16, the percentile denotes the relative frequency or likelihood of parameter values

in the entire distribution being less than or equal to the corresponding parameter

value in the right hand column.
Section 5.0 Hydrogeological Parameters

5-30

Table 5.15 Empirical distribution of mean particle diameter (based on Shea,

1974)

Cumulative Probability Particle Diameter (cm)

3.9x10

-4

7.8x10

-4

1.6x10

-3

3.1x10

-3

6.3x10

-3

1.25x10

-2

2.5x10

-2

5.0x10

-2

1.0x10

-1

2.0x10

-1

4.0x10

-1

8.0x10

-1

0.000

0.038

0.104

0.171

0.262

0.371

0.560

0.792

0.904

0.944

0.976

1.000

Table 5.16 Cumulative Frequency Distribution of Particle Diameter

% Particle Diameter (cm)

0

10

25

50

75

80

85

90

95

100

4.00E-04

1.50E-03

5.57E-03

1.91E-02

4.09E-02

4.60E-02

5.56E-02

7.62E-02

9.73E-02

2.11E-01

Alternatively, if the particle diameter is treated as a derived parameter, then

its value is calculated using the value of porosity (which may be constant or

randomly generated from a probability distribution) using the following empirical

relationship based on data reported by Davis (1969):
Section 5.0 Hydrogeological Parameters

5-31

d = exp [ 0.261 - φγ 0.0385] (5.4)

where:

d = mean particle diameter (cm)

 = total porosity (dimensionless)

γ = van Genuchten soil-specific shape parameter (dimensionless)

Data Sources

For Monte Carlo analyses, an empirical distribution of values is typically used

for the mean particle diameter. This distribution of values is based on data compiled

by Shea (1974) in which a frequency distribution of particle sizes is presented that is

based on analysis of 11,000 samples.

Alternatively, if the particle diameter is treated as a derived parameter, then

its value is calculated from the porosity using Equation 5.4 based on data reported

by Davis (1969).

Use In EPACMTP

For Monte Carlo analyses, the mean particle diameter is typically used to

calculate porosity and bulk density of the aquifer materials. Bulk density is an input

to the saturated zone flow and transport modules. In the transport module, it is one

of several parameters used to calculate the degree to which contaminant velocities

are retarded relative to the ambient ground-water flow velocity within the aquifer.

5.3.2 Porosity ()

Definition

Porosity is the ratio of the volume of void spaces in rock or sediment to the

total volume of rock or sediment. For contaminant transport modeling, it is more

appropriate to use effective porosity, e, than total porosity. The effective porosity

can be significantly smaller than the total porosity. However, the EPACMTP input

parameter porosity can represent either total or effective porosity, depending upon

how it is specified, as described below.
Section 5.0 Hydrogeological Parameters

5-32

Parameter Value or Distribution of Values

Lacking a site-specific value or distribution of values, this input value can be

calculated based on the aquifer’s particle diameter by rewriting Equation 5.4 to solve

for porosity, as shown below:

φ = 0.261 - 0.0385 ln(d) (5.5)

where:

d = mean particle diameter (cm)

 = total porosity (dimensionless)

Equation 5.5 yields the total porosity of the aquifer, but for contaminant

transport modeling, it is more appropriate to use effective porosity, e, than total

porosity. The effective porosity can be significantly smaller than the total porosity,

although a constant relationship between these two parameters cannot be

established. McWorter and Sunada (1977) present data on total and effective

porosity for a range of aquifer materials. Their data was used to create a default

methodology whereby the EPACMTP model calculates the effective porosity based

on the total porosity and the grain size (see Table 5.17).

For Monte Carlo assessments, the effective porosity of the aquifer is, by

default, specified as a derived parameter in the EPACMTP input file. In this case,

the model assumes that the actual ratio between effective and total porosity varies

uniformly between the upper and lower value for e

/ in each particle-size class for a

given value of the mean aquifer grain size class. For a given value of the mean

aquifer grain size, the total porosity can thus be converted into effective porosity.

Please note that EPACMTP makes the conversion from total of effective

porosity only if porosity is specified as a derived parameter (porosity is calculated

from grain size), the default setting in the input file. In all other cases, no conversion

is performed and the user must specify the actual porosity data to be used by the

model, providing a constant value or distribution of values for either total porosity or

effective porosity directly.
Section 5.0 Hydrogeological Parameters

5-33

Table 5.17 Ratio between effective and total porosity as a function of particle

diameter (after McWorter and Sunada, 1977)

Mean Particle Diameter (cm) e

/ Range

 6.25 10

-3 0.03 - 0.77

6.25 10

-3

- 2.5 10

-2 0.04 - 0.87

2.5 10

-2

- 5.0 10

-2 0.31 - 0.91

5.0 10

-2

- 1.0 10

-1 0.58 - 0.94

> 1.0 10

-1 0.52 - 0.95

Data Sources

If the porosity is treated as a derived parameter (the default setting), then the

total porosity is calculated from the mean particle diameter using Equation 5.5 which

is based on data reported by Davis (1969). The total porosity is then converted to

effective porosity by randomly choosing a ratio between effective and total porosity;

this conversion is accomplished through the use of ranges of values for the ratio

between effective and total porosity as a function of mean particle diameter that are

derived from data presented in McWorter and Sunada (1977).

Use In EPACMTP

For Monte Carlo analyses, the porosity, whether directly input or derived, is

used to calculate the bulk density of the aquifer materials. Bulk density is an input to

the saturated zone flow and transport modules. In the saturated zone flow module,

bulk density is used in the calculation of the ground-water seepage velocity. In the

transport module, bulk density is one of several parameters used to calculate the

degree to which contaminant velocities are retarded relative to the ambient groundwater flow velocity within the aquifer.

5.3.3 Bulk Density (b

)

Definition

Bulk density is defined as the mass of aquifer solid material per unit volume

of the aquifer, in g/cm3 or mg/L. Bulk density takes into account the fraction of the

volume that is taken up by pore space.

Parameter Value or Distribution of Values

Lacking site-specific data for bulk density, this input can be derived from the

porosity of the aquifer. Assuming the particle density to be 2.65 g/cm3, the bulk

density can be calculated using the following equation from Freeze and Cherry

(1979):
Section 5.0 Hydrogeological Parameters

5-34

ρ = 2.85 ( 1- φ ) (5.6)

where

b = bulk density of the soil (g/cm3).

 = total porosity of the aquifer material (dimensionless)

Table 5.18 lists the cumulative frequency distribution of bulk density that is

generated in a default landfill modeling analysis using the regional site-based

modeling methodology. For a given percentile (%) frequency and value pair in Table

5.18, the percentile denotes the relative frequency or likelihood of parameter values

in the entire distribution being less than or equal to the corresponding parameter

value in the right hand column.

Table 5.18 Cumulative Frequency Distribution of Bulk Density

% Soil Bulk Density (g/cm3)

0

10

25

50

75

80

85

90

95

100

1.16E+00

1.30E+00

1.43E+00

1.56E+00

1.63E+00

1.64E+00

1.66E+00

1.70E+00

1.72E+00

1.80E+00

Data Sources

In the absence of a site specific value or distribution of values for bulk

density, this input can be specified as a derived parameter in the EPACMTP input

file. In this case, the input value is calculated from the aquifer porosity by assuming

the particle density to be 2.65 g/cm3 and using the relationship from Freeze and

Cherry (1979) that is presented as Equation 5.6.

Use In EPACMTP

Bulk density is an input to the saturated zone flow and transport modules. In

the saturated zone flow submodule, bulk density is used in the calculation of the

ground-water seepage velocity. In the transport flow submodule, bulk density is one

of several parameters used to calculate the degree to which contaminant velocities

are retarded relative to the ambient ground-water flow velocity within the aquifer.
Section 5.0 Hydrogeological Parameters

5-35

5.3.4 Aquifer Characteristics

In the absence of site-specific data to input, default distributions of correlated

values can be used in EPACMTP for the following aquifer characteristics:

1. Depth to ground water;

2. Saturated zone thickness;

3. Saturated zone hydraulic conductivity; and

4. Saturated zone hydraulic gradient.

These default distributions are derived from the Hydrogeologic Database for

Ground-Water Modeling (HGDB), assembled by Rice University on behalf of the

American Petroleum Institute (API) (Newell et al., 1990). The data in this

hydrogeological database were collected by independent investigators for

approximately 400 hazardous waste sites throughout the United States; the

geographical locations of these sites are shown in Figure 5.2 (p. 5-37). In the

HGDB, the data are grouped into twelve subsurface environments, which are based

on EPA’s DRASTIC classification of hydrogeologic settings (U.S. EPA, 1985). Table

5.19 lists these hydrogeologic environments, and a brief description of each

environment is presented in Section 5.3.4.2. Table 5.19 includes a total of 13

categories; 12 are distinct subsurface environments, while the 13

th

category, which is

labeled “other” or “unknown”, was used for waste sites that could not be classified

into one of the first 12 environments. The subsurface parameter values in this 13

th

category are simply averages of the parameter values in the 12 actual subsurface

environments. The resulting database of aquifer types, with each aquifer type

consisting of an empirical distribution of values for each of the four aquifer

parameters, is presented in its entirety in Appendix D.

Table 5.19 HGDB Hydrogeologic Environments (from Newell et al., 1990)

Region Description

1

2

3

4

5

6

7

8

9

10

11

12

13

Metamorphic and Igneous

Bedded Sedimentary Rock

Till Over Sedimentary Rock

Sand and Gravel

Alluvial Basins Valleys and Fans

River Valleys and Flood Plains with Overbank Deposits

River Valleys and Flood Plains without Overbank

Deposits

Outwash

Till and Till Over Outwash

Unconsolidated and Semi-consolidated Shallow

Aquifers

Coastal Beaches

Solution Limestone

Other (Not classifiable)
Section 5.0 Hydrogeological Parameters

5-36

The key feature of this database is that it provides a set of correlated values

of the four parameters for each of the 400 sites in the database. That is, the value

of each parameter is associated with the three other subsurface parameters

reported for the same site. The regional site-based modeling methodology in

EPACMTP preserves these correlations because having information on some

parameters allows us to develop more accurate estimates for missing parameter

values. As described in Section 5.5 of the EPACMTP Technical Background

Document (U.S. EPA, 2003a), the regional site-based modeling methodology is an

attempt to ensure that the combination of parameter values that are randomly

generated by the Monte Carlo module of EPACMTP represents a realistic set of site

conditions. This methodology is called ‘regional site-based’ because waste site

databases are linked by each site’s geographic location and underlying aquifer type

to regional databases of climatic and subsurface parameters, respectively. In this

way, the regional site-based approach attempts to approximate the ideal situation

where we have a complete set of the site-specific input data required to run the

EPACMTP model for each waste site in a statistically valid subset of the universe of

waste management units in the United States.

In developing the regional site-based modeling methodology in EPACMTP,

the U.S. EPA used the HGDB in conjunction with a geographical classification of

aquifers developed by the United States Geological Survey (Heath, 1984) to assign

each waste site in our nationwide database of Subtitle D WMU’s (see Section 2.2) to

one of the 13 subsurface environments included in the HGDB. For each type of

WMU, we used information on its location (see Figures 2.2 - 2.5), in combination

with USGS state-by-state aquifer maps to determine the type of subsurface

environment at that site. Sites that could not be classified into one of the 12

categories were assigned as “other” (that is, they were assigned to environment

number 13). The regional site-based modeling methodology in EPACMTP is then

used to assign a probability distribution of hydrogeologic parameter values to each

WMU location. This methodology is consistent with the methodology used to assign

HELP-derived infiltration and recharge rates to each waste site in our nationwide

database of Subtitle D WMU’s (see Section 4.2 and Appendix A).
Section 5.0 Hydrogeological Parameters

5-37

Figure 5.2 Geographical distribution of sites in the API-HGDB data base

(Reproduced from API, 1989)
Section 5.0 Hydrogeological Parameters

5-38

5.3.4.1 Methodology

Fundamentally, the approach used for a site-based Monte Carlo analysis

consists of conducting the modeling analysis for the existing sites in our nationwide

database of Subtitle D WMU’s (see Section 2.2) on the assumption that these sites

are an adequate representation of the universe of possible waste sites in the U.S.

Since the original data sets (derived from the 1986 Subtitle D Survey (U.S. EPA,

1986) and the Surface Impoundment Study (U.S. EPA, 2001a) only include the area,

volume, location and relative weight of the facility, other data sources were utilized to

determine the additional input parameters required by the EPACMTP model.

As summarized above, the ground-water parameter values are generated

using the existing WMU parameter databases (which assign each waste site to a

climate region and a hydrogeologic environment) together with the HGDB database

of hydrogeologic parameters and the databases of HELP-derived infiltration and

recharge rates. These databases are all included in an auxiliary input file called the

site data file. The following is a description of how the regional, site-based modeling

methodology is used to generate these hydrogeologic parameter values during the

course of a typical Monte Carlo analysis for nationwide assessment purposes:

For each Monte Carlo realization, EPACMTP selects a WMU site, at

random, from the database of WMU sites. The original databases of

WMU sites from which the data in the site data file were compiled

included the facility location, area and volume. The EPACMTP model

samples the sites in the site data files with replacement, i.e., the

same site may be selected more than once. The probability of

selecting a specific site depends on the relative weight assigned to

that site in the original survey. Note that even if the same site is

sampled more than once during the course of a Monte Carlo analysis

in EPACMTP, the specific values of infiltration rate, hydrogeologic

parameters, and receptor well location will still vary; likewise, the

resulting receptor well concentration value will change, as well.

Given the waste site’s geographic location, the climatic region in

which the site is located was identified and added to the WMU site

database in the EPACMTP site data file. For landfills, waste piles,

and land application units, the climatic region, the generated soil type,

and the liner design (if any) are then used by the model to determine

the infiltration rate of the site. In the no-liner and single-clay liner

scenarios, these infiltration rates are determined using the database

of rates generated with the HELP water balance model. For the

composite liner scenario, these infiltration rates are internally

calculated by the model using the relationships described in Sections

4.3.1 and 4.3.2. For surface impoundments (all liner scenarios), the

infiltration rates are internally calculated by the model using the

relationships described in Sections 4.3.4. For all WMU types, the

climatic region and the generated soil type are used by the model to

determine the ambient regional recharge rate of the site.
Section 5.0 Hydrogeological Parameters

5-39

Given the waste site’s geographic location, the aquifer underlying the

site was classified (using USGS state ground-water resources

inventory maps) and added to the WMU site database in the

EPACMTP site data file. The hydrogeologic parameters for the site

are determined by selecting at random a set of aquifer characteristics

(depth to ground water, aquifer thickness, hydraulic gradient, and

hydraulic conductivity) from those available in the HGDB database for

that hydrogeologic environment. In the case where the selected set

of aquifer characteristics has missing values, a joint probability

distribution (derived for each ground-water region) is used to

generate the missing value as a function of the known values.

The remaining parameters for the waste site (e.g., x, y and z

coordinates of the receptor well) are generated according to their

specifications in the input file. The ground-water flow and transport

modules are then used to compute the resulting receptor well

concentration for the site.

These steps are then repeated for the desired number of iterations to

yield a distribution of receptor well concentrations which represent the

nationwide distribution of drinking water exposure concentrations.

These modeling results can then be directly used in a forward risk

calculation, or they can be post-processed to yield the ground-water

dilution-attenuation factor (DAF) that can be used in a backward risk

calculation to calculate an allowable threshold for the waste or

leachate concentration.

5.3.4.2 Hydrogeologic Environment (IGWR)

Definition

The different hydrogeologic environments are represented in EPACMTP by

means of a numerical index. The hydrogeologic environment index is simply a

sequential number assigned to each hydrogeologic environment in the default

database included with EPACMTP in order to provide a simple means of specifying

which correlated set of aquifer characteristics should be used to model the given

WMU site.

Parameter Value or Distribution of Values

To perform a standard Monte Carlo analysis using the regional site-based

modeling methodology, the hydrogeologic environment index should be left in its

default setting which will ensure that the appropriate climatic data is used for each

WMU site in the database. However, if a location-adjusted or a quasi-site-specific

analysis is being performed, then this input can either be omitted from the input file

(if site-specific infiltration and recharge rates are available) or set to the appropriate
Section 5.0 Hydrogeological Parameters

5-40

constant value to make use of the default set of aquifer characteristics which are

included in the site data file.

The text boxes on the following pages provide a summary of the

characteristics of each hydrogeologic environment.
Section 5.0 Hydrogeological Parameters

5-41

1) Igneous and Metamorphic Rocks

This hydrogeologic environment is underlain by consolidated bedrock of volcanic origin. This hydrogeologic

environment setting is typically associated with steep slopes on the sides of mountains, and a thin soil cover.

Igneous and metamorphic rocks generally have very low porosities and permeabilities This hydrogeologic

environment can occur throughout the United States, but is most prevalent in the western US.

2) Bedded Sedimentary Rock

Sedimentary rock is formed through erosion of bedrock. Deposited layers of eroded material may later be buried

and compacted to form sedimentary rock. Generally, the deposition is not continuous but recurrent, and sheets of

sediment representing separate events come to form distinct layers of sedimentary rock. Typically, these deposits

are very permeable and yield large quantities of ground water. Examples of this hydrogeologic environment setting

are found throughout the United States.

3) Till Over Sedimentary Rock

This hydrogeologic environment is found in glaciated regions in the northern United States which are frequently

underlain by relatively flat-lying consolidated sedimentary bedrock consisting primarily of sandstone, shale,

limestone, and dolomite. The bedrock is overlain by glacial deposits which consist chiefly of till, a dense unsorted

mixture of soil and rock particles deposited directly by ice sheets. Ground water occurs both in the glacial deposits

and in the sedimentary bedrock. Till deposits often have low permeability.

4) Sand and Gravel

Sediments are classified into three categories based upon their relative sizes; gravel, consisting of particles that

individually may be boulders, cobbles or pebbles; sand, which may be very coarse, coarse, medium, fine or very

fine; and mud, which may consist of clay and various size classes of silt. Sand and gravel hydrogeologic

environments are very common throughout the United States and frequently overlie consolidated and semiconsolidated sedimentary rocks. Sand and gravel aquifers have very high permeabilities and yield large quantities

of ground water.

5) Alluvial Basins, Valleys and Fans

Thick alluvial deposits in basins and valleys bordered by mountains typify this hydrogeologic environment. Alluvium

is a general term for clay, silt, sand and gravel that was deposited during comparatively recent geologic time by a

stream or other body of running water. The sediments are deposited in the bed of the stream or on its flood plain or

delta, or in fan shaped deposits at the base of a mountain slope. Alluvial basins, valleys and fans frequently

occupy a region extending from the Puget Sound-Williamette Valley area of Washington and Oregon to west

Texas. This region consists of alternating basins or valleys and mountain ranges. The surrounding mountains,

and the bedrock beneath the basins, consist of granite and metamorphic rocks. Ground water is obtained mostly

from sand and gravel deposits within the alluvium. These deposits are interbedded with finer grained layers of silt

and clay.

6) River Alluvium with Overbank Deposits

This hydrogeologic environment is characterized by low to moderate topography and thin to moderately thick

sediments of flood-deposited alluvium along portions of a river valley. The alluvium is underlain by either

unconsolidated sediments or fractured bedrock of sedimentary or igneous/metamorphic origin. Water is obtained

from sand and gravel layers which are interbedded with finer grained alluvial deposits. The alluvium typically

serves as a significant source of water. The flood plain is covered by varying thicknesses of fine-grained silt and

clay, called overbank deposits. The overbank thickness is usually greater along major streams and thinner along

minor streams but typically averages 5 to 10 feet.

Hydrogeologic Environment Descriptions
Section 5.0 Hydrogeological Parameters

5-42

7) River Alluvium without Overbank Deposits

This hydrogeologic environment is identical to the River Alluvium with Overbank Deposits environment

except that no significant fine-grained flood plain deposits occupy the stream valley. The lack of fine

grained deposits may result in significantly higher recharge in areas with ample precipitation.

8) Outwash

Sand and gravel removed or “washed out” from a glacier by streams is termed outwash. This

hydrogeologic environment is characterized by moderate to low topography and varying thicknesses of

outwash that overlie sequences of fractured bedrock of sedimentary, metamorphic or igneous origin.

These sand and gravel outwash deposits typically serve as the principal aquifers within the area. The

outwash also serves as a source of regional recharge to the underlying bedrock.

9) Till and Till Over Outwash

This hydrogeologic environment is characterized by low topography and outwash materials that are

covered by varying thicknesses of glacial till. The till is principally unsorted sediment which may be

interbedded with localized deposits of sand and gravel. Although ground water occurs in both the

glacial till and in the underlying outwash, the outwash typically serves as the principal aquifer because

the fine grained deposits have been removed by streams. The outwash is in direct hydraulic

connection with the glacial till and the glacial till serves as a source of recharge for the underlying

outwash.

10) Unconsolidated and Semi-consolidated Shallow Surficial Aquifers

This hydrogeologic environment is characterized by moderately low topographic relief and gently

dipping, interbedded unconsolidated and semi-consolidated deposits which consist primarily of sand,

silt and clay. Large quantities of water are obtained from the surficial sand and gravel deposits which

may be separated from the underlying regional aquifer by a low permeability or confining layer. This

confining layer typically “leaks”, providing recharge to the deeper zones.

11) Coastal Beaches

This hydrogeologic environment is characterized by low topographic relief, near sea-level elevation and

unconsolidated deposits of water-washed sands. The term beach is appropriately applied only to a

body of essentially loose sediment. This usually means sand-size particles, but could include gravel.

Quartz particles usually predominate. These materials are well sorted, very permeable and have very

high potential infiltration rates. These areas are commonly ground-water discharge areas although

they can be very susceptible to the intrusion of saltwater.

12) Solution Limestone

Large portions of the central and southeastern United States are underlain by limestones and

dolomites in which the fractures have been enlarged by solution. Although ground water occurs in

both the surficial deposits and in the underlying bedrock, the limestones and dolomites, which typically

contain solution cavities, generally serve as the principal aquifers. This type of hydrogeologic

environment is often described as “karst.”

13) Unknown Environment

If the subsurface hydrogeological environment is unknown, or it is different from any of the twelve main

types used in EPACMTP, select the subsurface environment as Type 13. In this case, EPACMTP will

assign values of the hydrogeological parameters (depth to ground water, saturated zone thickness,

saturated zone hydraulic conductivity, and saturated zone hydraulic gradient) that are simply national

average values.

Hydrogeologic Environment Descriptions (continued)
Section 5.0 Hydrogeological Parameters

5-43

Data Sources

In the absence of site-specific data, default distributions of values can be

used for the following aquifer characteristics: depth to ground water and aquifer

thickness, hydraulic conductivity, and hydraulic gradient. These default distributions

are derived from the Hydrogeologic Database for Ground-Water Modeling (HGDB),

assembled by Rice University on behalf of the American Petroleum Institute (API)

(Newell et al., 1990) and are linked to the WMU sites in the site data file using the

hydrogeologic environment index.

Use In EPACMTP

EPACMTP includes a database of aquifer characteristics for 13

hydrogeologic environments. The hydrogeologic environment index is a sequential

number assigned to each hydrogeologic environment in the default database

included with EPACMTP in order to provide a simple means of specifying which

correlated set of aquifer characteristics should be used to model the given WMU site

using the regional site-based modeling methodology.

5.3.4.3 Saturated Zone Thickness (B)

Definition

The saturated zone thickness is the vertical thickness of the zone in which

the voids in the rock or soil are filled with water at a pressure greater than

atmospheric. In an unconfined aquifer such as that simulated by the EPACMTP

model, the water table is at the top of the saturated zone. Usually the base of the

saturated zone is an impermeable layer, e.g., bedrock.

Parameter Value or Distribution of Values

If site-specific data are available, then the saturated zone thickness can be

specified in the input file as a constant value or an empirical or statistical distribution

of values. In this case, if your site has a highly stratified hydrogeology, it may be

difficult to precisely define the “base of the aquifer,” but the stratification may

effectively limit the vertical plume travel distance, so it may be appropriate to enter

the maximum vertical extent of the plume as an “effective” saturated zone thickness.

Lacking site-specific data, a default distribution of saturated zone thickness

values may be used as part of the regional site-based modeling methodology. As

described in Section 5.5 of the EPACMTP Technical Background Document (U.S.

EPA, 2003a), the regional site-based modeling methodology is an attempt to ensure

that the combination of parameter values that is randomly generated by the Monte

Carlo module of EPACMTP represents a realistic set of site conditions. The

cumulative frequency distribution of saturated zone thickness listed in Table 5.20

was generated by performing a default landfill modeling analysis using the regional

site-based modeling methodology; the entire Hydrogeologic Database for Modeling

(HGDB) from which these values were derived is presented in Appendix D. For a
Section 5.0 Hydrogeological Parameters

5-44

given percentile (%) frequency and value pair in Table 5.20, the percentile denotes

the relative frequency or likelihood of parameter values in the entire distribution

being less than or equal to the corresponding parameter value in the right hand

column.

Table 5.20 Cumulative Frequency Distribution of Saturated Zone Thickness

% Saturated Zone Thickness (m)

0

10

25

50

75

80

85

90

95

100

3.05E-01

4.27E+00

7.62E+00

1.43E+01

3.24E+01

4.83E+01

6.66E+01

9.14E+01

1.52E+02

9.14E+02

Data Sources

In the regional site-based Monte Carlo analysis used for nationwide modeling

applications, the distribution of values for the thickness of the saturated zone is

produced through Monte Carlo sampling of the HGDB, based on the hydrogeologic

environment assigned to the waste site selected (from the default database) for

each model realization. The HGDB (Newell et al., 1990; U.S. EPA, 1997d) is an

empirical database of aquifer characteristics developed from a survey of hazardous

waste sites in the United States that provides data on hydrogeologic parameters

(aquifer thickness, unsaturated zone thickness, hydraulic gradient and hydraulic

conductivity) that are required by the EPACMTP model. The HGDB from which the

values shown in Table 5.20 were derived is presented in its entirety in Appendix D.

In a location-specific modeling analysis, saturated zone thickness must be

derived from a site-specific data source and specified in the input file as a constant

value or an empirical or statistical distribution of values.

Use In EPACMTP

The thickness of the saturated zone is an input to the saturated zone flow

module. It is used in EPACMTP to describe the thickness of the ground-water zone

over which the leachate plume can mix with ground water and impacts the dilution

rates in the saturated zone.
Section 5.0 Hydrogeological Parameters

5-45

5.3.4.4 Hydraulic Conductivity (K)

Definition

Hydraulic conductivity is a measure of the ability to transmit water under a

unit hydraulic gradient.

Parameter Value or Distribution of Values

If site-specific data are available, then the hydraulic conductivity can be

specified in the input file as a constant value or an empirical or statistical distribution

of values.

Lacking site-specific data, a default distribution of hydraulic conductivity

values may be used as part of the regional site-based modeling methodology. As

described in Section 5.5 of the EPACMTP Technical Background Document (U.S.

EPA, 2003a), the regional site-based modeling methodology is an attempt to ensure

that the combination of parameter values that is randomly generated by the Monte

Carlo module of EPACMTP represents a realistic set of site conditions. The

cumulative frequency distribution of hydraulic conductivity listed in Table 5.21 was

generated by performing a default nationwide landfill modeling analysis using the

regional site-based modeling methodology; the entire Hydrogeologic Database for

Modeling (HGDB) from which these values were derived is presented in Appendix D.

For a given percentile (%) frequency and value pair in Table 5.21, the percentile

denotes the relative frequency or likelihood of parameter values in the entire

distribution being less than or equal to the corresponding parameter value in the

right hand column.

Table 5.21 Cumulative Frequency Distribution of Hydraulic Conductivity

% Hydraulic Conductivity (m/yr)

0

10

25

50

75

80

85

90

95

100

3.15E+00

1.73E+02

8.04E+02

1.89E+03

1.10E+04

1.39E+04

2.21E+04

3.15E+04

7.48E+04

4.29E+06

Alternatively, the hydraulic conductivity can be specified as a derived

parameter. In this case it is calculated within EPACMTP from the particle diameter

using the Kozeny-Carman equation (Bear, 1979) shown below:
Section 5.0 Hydrogeological Parameters

5-46

K = ρ g φ

2 d2

μ (1-φ

2

) 1.8 (5.7)

where:

K = hydraulic conductivity (cm/s)

 = density of water (kg/m3)

g = acceleration due to gravity (m/s

2

)

	 = dynamic viscosity of water (N-s/m2)

d = mean particle diameter (m)

 = total porosity of the aquifer material (dimensionless)

In Equation 5.7 shown above, the constant 1.8 includes a unit conversion

factor to yield K in units of cm/s. Both the density and the dynamic viscosity of water

are functions of temperature and are computed using the regression equations

presented in CRC (1981).

Data Sources

In the regional site-based Monte Carlo analysis used for nationwide modeling

applications, the distribution of values for the hydraulic conductivity is produced

through Monte Carlo sampling of the HGDB, based on the hydrogeologic

environment assigned to the waste site selected (from the default database) for

each model realization. The HGDB (Newell et al., 1990; U.S. EPA, 1997d) is an

empirical database of aquifer characteristics developed from a survey of hazardous

waste sites in the United States that provides data on hydrogeologic parameters

(aquifer thickness, unsaturated zone thickness, hydraulic gradient and hydraulic

conductivity) that are required by the EPACMTP model. The HGDB from which the

values shown in Table 5.21 were derived is presented in its entirety in Appendix D.

If specified as a derived parameter, the aquifer hydraulic conductivity is

calculated from the mean particle diameter using the Kozeny-Carman equation

(Bear, 1979).

In a location-specific modeling analysis, hydraulic conductivity must be

derived from a site-specific data source and specified in the input file as a constant

value or an empirical or statistical distribution of values.

Use In EPACMTP

The aquifer hydraulic conductivity is an input to the saturated zone flow

module. The hydraulic conductivity, together with the hydraulic gradient, controls the

ground-water flow rate. Assigning a low hydraulic conductivity value will not

necessarily result in lower predicted ground-water exposures. In a broader sense, it

means that siting a WMU in a low permeability aquifer setting is not always more

protective than a high permeability setting. Low ground-water velocity means that it
Section 5.0 Hydrogeological Parameters

5-47

will take longer for the exposure to occur, and as a result, there is more opportunity

for natural attenuation to degrade contaminants. However, for long-lived waste

constituents, it also means that little dilution of the plume may occur.

5.3.4.5 Regional Hydraulic Gradient (r)

Definition

Hydraulic gradient measures the head difference between two points as a

function of their distance. For an unconfined aquifer such as that modeled with

EPACMTP, the hydraulic gradient is simply the slope of the water table in a

particular direction. It is calculated as the difference in the elevation of the water

table measured at two locations divided by the distance between the two locations.

In EPACMTP, this parameter represents the average horizontal ground-water

gradient in the vicinity of the WMU location. The gradient is meant to represent the

‘natural’ ground-water gradient as it is, or would be, without influence from the WMU.

The presence of a WMU, particularly a surface impoundment, may cause local

mounding of the water table and associated higher local ground-water gradients.

The EPACMTP model assumes that the gradient value specified in the input file

does not include mounding; rather, the model will calculate the predicted impact on

the ground water of the WMU and liner design (if any) as part of the modeling

evaluation.

Parameter Value or Distribution of Values

If site-specific data are available, then the regional hydraulic gradient can be

specified in the input file as a constant value or an empirical or statistical distribution

of values.

Lacking site-specific data, a default distribution of regional hydraulic gradient

values may be used as part of the regional site-based modeling methodology. As

described in Section 5.5 of the EPACMTP Technical Background Document (U.S.

EPA, 2003a), the regional site-based modeling methodology is an attempt to ensure

that the combination of parameter values that is randomly generated by the Monte

Carlo module of EPACMTP represents a realistic set of site conditions. The

cumulative frequency distribution of regional hydraulic gradient listed in Table 5.22

was generated by performing a default nationwide landfill modeling analysis using

the regional site-based modeling methodology; the entire Hydrogeologic Database

for Modeling (HGDB) from which these values were derived is presented in

Appendix D. For a given percentile (%) frequency and value pair in Table 5.22, the

percentile denotes the relative frequency or likelihood of parameter values in the

entire distribution being less than or equal to the corresponding parameter value in

the right hand column.
Section 5.0 Hydrogeological Parameters

5-48

Table 5.22 Cumulative Frequency Distribution of Regional hydraulic gradient

% Regional Hydraulic Gradient (unitless)

0

10

25

50

75

80

85

90

95

100

2.00E-06

9.00E-04

2.00E-03

5.70E-03

1.51E-02

2.00E-02

2.46E-02

3.10E-02

4.90E-02

4.91E-01

Data Sources

In the regional site-based Monte Carlo analysis used for nationwide modeling

applications, the distribution of values for the regional hydraulic gradient is produced

through Monte Carlo sampling of the HGDB, based on the hydrogeologic

environment assigned to the waste site selected (from the default database) for

each model realization. The HGDB (Newell et al., 1990; U.S. EPA, 1997d) is an

empirical database of aquifer characteristics developed from a survey of hazardous

waste sites in the United States that provides data on hydrogeologic parameters

(aquifer thickness, unsaturated zone thickness, hydraulic gradient and hydraulic

conductivity) that are required by the EPACMTP model. The HGDB from which the

values shown in Table 5.22 were derived is presented in its entirety in Appendix D.

In a location-specific modeling analysis, regional hydraulic gradient must be

derived from a site-specific data source and specified in the input file as a constant

value or an empirical or statistical distribution of values.

Use In EPACMTP

The hydraulic gradient and the hydraulic conductivity (see Section 5.3.4.4)

are inputs to the saturated zone flow module, and together they control the groundwater flow rate, in accordance with Darcy’s Law. The effect of varying ground-water

flow rate on contaminant fate and transport is complex. Intuitively, it would seem

that factors that increase the ground-water flow rate would cause a higher groundwater exposure level at the receptor well, but this is not always the case. A higher

ground-water velocity will cause leachate constituents to arrive at the well location

more quickly. For constituents that are subject to degradation in ground water, the

shorter travel time will cause the constituents to arrive at the well at higher

concentrations as compared to a case of low ground-water velocity and long travel

times. On the other hand, a high ground-water flow rate will tend to increase the

degree of dilution of the leachate plume, due to mixing and dispersion. This will in

turn tend to lower the magnitude of the concentrations reaching the well. The
Section 5.0 Hydrogeological Parameters

5-49

modeling scenario evaluated in EPACMTP is based on the maximum constituent

concentrations at the well (either a peak concentration or the maximum timeaveraged concentration), rather than how long it might take for that exposure to

occur. Therefore, a higher ground-water flow rate may result in lower predicted

exposure levels at the well.

5.3.5 Seepage Velocity (Vx)

Definition

Seepage velocity is the average linear velocity of a water particle in a ground

water system. It is equal to the Darcy velocity divided by effective porosity.

Parameter Value or Distribution of Values

The ground-water seepage velocity is related to the aquifer properties

through Darcy’s law. The regional seepage velocity may be input directly, as a

constant value or a distribution of values. If site specific data are not available, it

may be specified in the input file as a derived parameter. In this case, it is computed

as:

Vx = Kxr (5.8)

φe

where

Vx = longitudinal ground water seepage velocity (in the x-direction) (m/yr)

Kx = longitudinal hydraulic conductivity (in the x-direction) (m/yr)

r = regional hydraulic gradient (dimensionless)

e = effective porosity (dimensionless)

Default lower and upper bounds for the seepage velocity are 0.1 and 1.1x10

4

m/yr, respectively. This range of values is based on survey data reported by Newell

et al (1990).

The cumulative frequency distribution for the seepage velocity listed in Table

5.23 was generated by performing a default nationwide landfill modeling analysis

using the regional site-based modeling methodology. For a given percentile (%)

frequency and value pair in this table, the percentile denotes the relative frequency

or likelihood of parameter values in the entire distribution being less than or equal to

the corresponding parameter value in the right hand column.
Section 5.0 Hydrogeological Parameters

5-50

Table 5.23 Cumulative Frequency Distribution of Ground-water Seepage

Velocity

% Seepage Velocity (m/yr)

0

10

25

50

75

80

85

90

95

100

2.17E+00

5.99E+00

5.11E+00

4.08E+01

6.73E+02

4.02E+02

2.53E+00

6.57E+00

2.27E+00

4.13E+01

Data Sources

In the regional site-based Monte Carlo analysis that is typically used for

nationwide modeling applications, the seepage velocity is, by default, internally

derived using the correlated values for hydraulic conductivity and gradient that are

produced through Monte Carlo sampling of the HGDB, based on the hydrogeologic

environment assigned to the waste site selected for each model realization. The

default lower and upper bounds for this input are based on survey data reported by

Newell et al (1990).

If specified as a derived parameter, the regional ground-water seepage

velocity is calculated from the hydraulic conductivity and gradient, and the aquifer

porosity using Equation 5.8 with upper and lower bounds based on survey data

reported by Newell et al (1990).

In a location-adjusted or quasi-site-specific modeling analysis, the sitespecific hydraulic gradient must be derived from a site-specific data source and

specified in the input file as a constant value or an empirical or statistical distribution

of values.

Use In EPACMTP

The seepage velocity that is provided as an EPACMTP input parameter

represents ambient ground water flow conditions, that is, without the WMU present.

The EPACMTP saturated zone flow module calculates the final distribution of

seepage velocities in the model domain, taking into account infiltration from the

WMU. These calculated seepage velocities are then used in the saturated zone

transport module to simulate the fate and transport of leachate constituents.
Section 5.0 Hydrogeological Parameters

5-51

5.3.6 Anisotropy Ratio (Ar)

Definition

The anisotropy ratio is a factor used to specify the relationship between the

horizontal and vertical aquifer hydraulic conductivities. It is defined as the ratio of

the horizontal hydraulic conductivity to the vertical hydraulic conductivity.

Parameter Value or Distribution of Values

Although the aquifer properties are assumed to be uniform, the EPACMTP

model can accommodate the situation where the horizontal and vertical aquifer

hydraulic conductivities are different. The anisotropy ratio is a factor used to specify

the relationship between these two hydraulic conductivity values and is defined

according to the following equation:

Ar = Kx/ Kz(5.9)

where:

Ar = anisotropy ratio = Kx/Kz.

Kx = hydraulic conductivity in the x direction (m/yr)

Kz = hydraulic conductivity in the z direction (m/yr)

The default value of Aris 1, which indicates an isotropic system. Note that in

the EPACMTP model, the horizontal transverse hydraulic conductivity is assumed to

be equal to the horizontal longitudinal conductivity, i.e., Ky = Kx.

Data Sources

Because anisotropy ratios observed in the field may commonly be on the

order of 100:1 or even larger (Freeze and Cherry, 1979), a uniform distribution of Ar

with limits of 1 and 100 may be reasonable for some applications of the model.

However, for nationwide assessment purposes, the default value of Aris 1, which

indicates an isotropic system.

Use In EPACMTP

The anisotropy ratio is used to estimate the vertical conductivity from the

horizontal conductivity. However, by default, the vertical conductivity is set equal to

the horizontal conductivity. The horizontal and vertical conductivities are inputs to

the saturated zone flow module.
Section 5.0 Hydrogeological Parameters

5-52

5.3.7 Retardation Coefficient for the Saturated Zone (R

s

)

Definition

The retardation coefficient is a measure of the degree to which contaminant

velocities are retarded relative to that of the bulk mass of ground water within the

aquifer. A value of 1.0 indicates that the constituent is conservative; in other words,

it is not subject to adsorption and travels at the same speed as the bulk mass of

ground-water. Values greater than 1.0 indicate that the constituent transport is

retarded due to adsorption.

Parameter Value or Distribution of Values

In most modeling applications using EPACMTP, the retardation coefficient is

specified as a derived variable; however, if site-specific data are available, this input

parameter can be set to a constant value or a distribution of values.

For constituents modeled with a linear adsorption isotherm (typically, organics and

metals modeled with a pH-dependent isotherm or a constant kd value), when the

retardation coefficient is specified as a derived variable in the EPACMTP input file, it

is calculated according to the following equation:

R

s = 1 + ρbKd

(5.10)

φ

where

R

s = retardation coefficient for the saturated zone (dimensionless)

b = bulk density of the porous media [g/cm3]

kd = distribution coefficient [cm3

/g]

 = porosity

For constituents modeled with a nonlinear adsorption isotherm (that is, R

s

is

no longer constant but is a function of metal concentration), R

s must be specified in

the input file as a derived variable and the Kd-concentration relation must be

specified by the user in one of two ways: 1) in terms of the two Freundlich

parameters (k1 and ; see Sections 5.3.12 and 5.3.13); or 2) in terms of the

tabulated MINTEQA2-derived isotherms (see Section 3.3.3.2).

For the modeling of metals, the EPACMTP user has three options for

specifying the relationship between dissolved and adsorbed concentrations: 1)

MINTEQA2-derived non-linear isotherms, 2) pH-dependent empirical isotherms, or

3) an empirical distribution of values. In the case of the first option, the non-linear

isotherm is only used in the unsaturated zone; a linear sorption isotherm (e.g., an

effective Kd value) is used for the saturated zone. This effective Kd value is

determined from the maximum contaminant concentration at the water table and
Section 5.0 Hydrogeological Parameters

5-53

values of the five environmental master variables (pH, iron-oxide, leachate organic

matter, natural organic matter in the aquifer, and ground water environment type

(carbonate or non-carbonate)), following the procedure described in Appendix B.

Data Sources

Lacking site-specific data, Equation 5.10 is used to calculate the retardation

coefficient for constituents that are modeled using a linear adsorption isotherm. For

constituents modeled with a non-linear adsorption isotherm, the effective retardation

coefficient is calculated inside EPACMTP, based upon the nonlinear concentrationKd

relationship as given by MINTEQA2-derived isotherms.

Use In EPACMTP

The retardation coefficient is an input to the saturated zone transport module.

5.3.8 Dispersivity

The transport of the contaminant plume in the saturated zone is controlled by

two mechanisms: advection and dispersion. The EPACMTP saturated zone flow

module simulates both of these mechanisms. Dispersion is the phenomenon by

which a constituent plume in flowing ground water is mixed with uncontaminated

water and becomes reduced in concentration at the perimeter of the plume. Not all

of a contaminant plume is traveling at the same velocity due to differences in pore

size and flow path length and friction along pore walls, resulting in mixing along the

flow path which decreases solute concentrations. Note that the saturated zone

dispersivity is measured in three directions: longitudinal (along the flow path, or in

the x-direction), horizontal transverse (perpendicular to the flow path, or in the ydirection), and vertical (in the z-direction).

The model computes the longitudinal, horizontal transverse, and vertical

dispersion coefficients as the product of the seepage velocity and longitudinal (L),

transverse (T) and vertical (V) dispersivities. A literature review indicated the

absence of a generally accepted theory to describe dispersivities, although a strong

dependence on scale has been noted (EPRI, 1985; Gelhar, Welty, and Rehfeldt,

1992). In the absence of user-specified values or distributions, the longitudinal

dispersivity is represented through a probabilistic formulation and the horizontal

transverse and vertical dispersivities are, by default, calculated from the longitudinal

dispersivity, as described below.

For non-degrading contaminants, the dilution caused by dispersive mixing is

a controlling factor in determining the concentration observed at a receptor well.

However, in Monte Carlo analyses involving varying well location, the predicted

maximum well concentration is relatively insensitive to dispersion. The reason for

this is as follows: low dispersivities will lead to a compact, concentrated plume. If

the plume is relatively small, the likelihood that the receptor well will intercept the

plume is reduced, but the concentration in the well, if it does, will be high. High

dispersivities will lead to a more dilute plume which occupies a greater volume,
Section 5.0 Hydrogeological Parameters

5-54

thereby increasing the likelihood that a receptor well will intercept the plume.

Concentrations in the plume, however, are likely to be lower than in the first case. In

the course of a full Monte Carlo analysis, these effects will tend to compensate for

each other.

5.3.8.1 Longitudinal Dispersivity (L

)

Definition

Dispersion is the phenomenon by which a contaminant plume in flowing

ground water is mixed with uncontaminated water and becomes reduced in

concentration at the perimeter of the plume. The longitudinal dispersivity is the

characteristic length that defines spatial extent of dispersion of contaminants,

measured in the longitudinal direction, that is, along the flow path or in the xdirection.

Parameter Value or Distribution of Values

If site-specific data are available, then the longitudinal dispersivity can be

specified in the input file as a constant value or an empirical or statistical distribution

of values.

In the absence of site-specific data, the longitudinal dispersivity is, by default,

represented through a probabilistic formulation as shown in Table 5.24, and the

horizontal transverse and vertical dispersivities are then calculated from the

longitudinal dispersivity. The distribution shown in Table 5.24 is based on data

presented in EPRI (1985). For a given percentile (%) frequency and value pair in

this table, the percentile denotes the relative frequency or likelihood of parameter

values in the entire distribution being less than or equal to the corresponding

parameter value in the right hand column. Within each of the three classes shown in

Table 5.24, the longitudinal dispersivity is assumed to be uniform. Note that the

values of longitudinal dispersivity in this table are based on a receptor well distance

of 152.4 m. For distances other than 152.4 m, the following equations are used:

αL(xt) = αRef(xt = 152.4) (xt/ 152.4)

0.5

(5.11)

where: xt = 0.5 xw + xr(5.12)
Section 5.0 Hydrogeological Parameters

5-55

L = longitudinal dispersivity (m)

xt = average travel distance in the x direction (m)

xw = length of the WMU in the x-direction (parallel to ground water

flow) (m)

xrw = distance from the downgradient boundary of the WMU to the

receptor well (m)

Ref = reference longitudinal dispersivity, as determined from the

probabilistic distribution (m)

Table 5.24 Probabilistic representation of longitudinal dispersivity

% L(m)*

0

10

70

100

0.1

1.0

10.0

100.0

*Assumes xt = 152.4 m (see Equation 5.11)

In other words, the travel distance xtis equal to the distance between the

receptor well and the downgradient facility boundary (xrw), plus one-half of the facility

dimension. The average distance for all of the contaminants to migrate to the edge

of the waste management unit is equal to one half the length of the unit or 1⁄2 xw.

The default minimum value of Lis 0.1 m.

Table 5.25 lists the cumulative frequency distribution of longitudinal

dispersivity that is generated in a default landfill modeling analysis using the regional

site-based modeling methodology. For a given percentile (%) frequency and value

pair in this table, the percentile denotes the relative frequency or likelihood of

parameter values in the entire distribution being less than or equal to the

corresponding parameter value in the right hand column.

Table 5.25 Cumulative Frequency Distribution of Longitudinal Dispersivity

% Longitudinal Dispersivity (m)

0

10

25

50

75

80

85

90

95

100

1.00E-01

1.22E+00

3.62E+00

8.96E+00

2.54E+01

4.32E+01

6.53E+01

9.21E+01

1.35E+02

3.18E+02
Section 5.0 Hydrogeological Parameters

5-56

Data Sources

The relationship in Equation 5.11 was derived based on a professional

review of data presented in EPRI (1985). More recently, Gelhar et al. (1992) have

compiled and documented results from a large number of studies in which

dispersivity values have been reported. These studies represent a wide range of

spatial scales, from a few meters to more than 10,000 meters. The data as

presented by Gelhar et al. (1992) show a clear correlation between scale and

apparent dispersivity. Equation 5.11 used in EPACMTP describes the observed

data reasonably well. The field data suggest a somewhat steeper slope of the

distance-dispersivity relation on a log-log scale than is used in the modeling

analyses. However, a sensitivity analysis performed using EPACMTP

(HydroGeoLogic, 1992) has shown that the model results are virtually identical when

the slope is varied from 0.5 to 1.5. For this reason the original relationship as shown

in Equation 5.11 has been retained.

The data presented by Gelhar et al. (1992) also show that the ratios between

longitudinal, and horizontal and vertical transverse dispersivities used in the

nationwide modeling, are consistent with published data.

Use In EPACMTP

The longitudinal dispersivity is an input to the saturated zone transport

module.

5.3.8.2 Horizontal Transverse Dispersivity (T

)

Definition

Dispersion is the phenomenon by which a contaminant plume in flowing

ground water is mixed with uncontaminated water and becomes reduced in

concentration at the perimeter of the plume. The horizontal transverse dispersivity is

the characteristic length that defines spatial extent of dispersion of contaminants,

measured in the horizontal transverse direction, that is, perpendicular to the flow

path, or in the y-direction.

Parameter Value or Distribution of Values

If site-specific data are available, then the horizontal transverse dispersivity

can be specified in the input file as a constant value or an empirical or statistical

distribution of values.

In the absence of site-specific data, the horizontal transverse dispersivity is,

by default, calculated from the longitudinal dispersivity using the following equation:
Section 5.0 Hydrogeological Parameters

5-57

αT = αL/ 8 (5.13)

where:

L = longitudinal dispersivity (m)

T = horizontal transverse dispersivity (m)

Note that in EPACMTP, the input value for Tis actually the ratio of Lto T.

Although the user can define a different value for the ratio of the longitudinal to the

transverse dispersivity, the ratio of L/T = 8 is used by default.

Table 5.26 lists the cumulative frequency distribution of horizontal transverse

dispersivity that is generated in a default landfill modeling analysis using the regional

site-based modeling methodology. For a given percentile (%) frequency and value

pair in this table, the percentile denotes the relative frequency or likelihood of

parameter values in the entire distribution being less than or equal to the

corresponding parameter value in the right hand column.

Table 5.26 Cumulative Frequency Distribution of Horizontal Transverse

Dispersivity

% Horizontal Transverse Dispersivity (m)

0

10

25

50

75

80

85

90

95

100

1.25E-02

1.53E-01

4.52E-01

1.12E+00

3.17E+00

5.40E+00

8.16E+00

1.15E+01

1.69E+01

3.97E+01

Data Sources

By default, the transverse (T

) dispersivity is calculated by the EPACMTP

model as a fraction of the longitudinal dispersivity. The dispersivity relationship

described above has been derived based on a professional review of data presented

in EPRI (1985). More recently, Gelhar et al. (1992) have compiled and documented

results from a large number of studies in which dispersivity values have been

reported. The data presented by Gelhar et al. (1992) show that this default ratio

between longitudinal and horizontal transverse dispersivities is consistent with

published data.
Section 5.0 Hydrogeological Parameters

5-58

Use In EPACMTP

The horizontal transverse dispersivity is an input to the saturated zone

transport module.

5.3.8.3 Vertical Dispersivity (v)

Definition

Dispersion is the phenomenon by which a contaminant plume in flowing

ground water is mixed with uncontaminated water and becomes reduced in

concentration at the perimeter of the plume. The vertical dispersivity is the

characteristic length that defines spatial extent of dispersion of contaminants,

measured vertically downward or in the z-direction.

Parameter Value or Distribution of Values

If site-specific data are available, then the vertical dispersivity can be

specified in the input file as a constant value or an empirical or statistical distribution

of values.

In the absence of site-specific data, the vertical dispersivity is, by default,

calculated from the longitudinal dispersivity using the following equation:

αV = αL/ 160 (5.14)

where:

L = longitudinal dispersivity (m)

V = vertical dispersivity (m)

Note that in EPACMTP, the input value for V

is actually the ratio of Lto V.

Although the user can define a different value for the ratio of the longitudinal to the

vertical dispersivity, the ratio of L/V = 160 is used by default.

Table 5.27 lists the cumulative frequency distribution of horizontal transverse

dispersivity that is generated in a default landfill modeling analysis using the regional

site-based modeling methodology. For a given percentile (%) frequency and value

pair in this table, the percentile denotes the relative frequency or likelihood of

parameter values in the entire distribution being less than or equal to the

corresponding parameter value in the right hand column.
Section 5.0 Hydrogeological Parameters

5-59

Table 5.27 Cumulative Frequency Distribution of Vertical Dispersivity

% Vertical Dispersivity (m)

0

10

25

50

75

80

85

90

95

100

1.00E-02

1.00E-02

2.26E-02

5.60E-02

1.58E-01

2.70E-01

4.08E-01

5.76E-01

8.45E-01

1.99E+00

Data Sources

By default, the vertical (V

) dispersivity is calculated by the EPACMTP model

as a fraction of the longitudinal dispersivity. The dispersivity relationship described

above has been derived based on a review of available data. More recently, Gelhar

et al. (1992) have compiled and documented results from a large number of studies

in which dispersivity values have been reported. The data presented by Gelhar et al.

(1992) show that this default ratio between longitudinal and vertical dispersivities is

consistent with published data.

Use In EPACMTP

The vertical dispersivity is an input to the saturated zone transport module;

dispersion in the saturated zone generally tends to decrease contaminant

concentrations at the receptor well.

5.3.9 Aquifer Temperature (T)

Definition

The aquifer temperature is the long-term average temperature of the ground

water within the aquifer. Note that although the temperature of the ground water

within the vadose zone is not an explicit model input, this temperature is assumed by

EPACMTP to be the same as that of the aquifer.

Parameter Value or Distribution of Values

As modeled in EPACMTP, aquifer temperature affects the transformation

rate of constituents that are subject to hydrolysis, through the effect of temperature

on reaction rates (see Section 3.3.2.2). In the development of the site data files for

each WMU type, information on average annual temperatures in shallow groundwater systems (Todd, 1980) to assign a temperature value to each WMU in the
Section 5.0 Hydrogeological Parameters

5-60

Figure 5.3 Ground-water Temperature Distribution for Shallow

Aquifers in the United States (from Todd, 1980)

modeling database, based on the unit’s geographical location. For each WMU site,

the assigned temperature was an average of the upper and lower values for that

temperature region, as shown in Figure 5.3. In other words, all WMU’s located in

the band between 10°and 15°were assigned a temperature value of 12.5 °C.

Data Sources

We used information on average annual temperatures in shallow groundwater systems from Todd (1980) to assign a temperature value to each WMU site in

the site data files, based on the unit’s geographical location.

Use In EPACMTP

When the EPACMTP model is run using the regional, site-based

methodology, the model selects a site at random from those in the site data file for

each Monte Carlo realization. For each WMU site, the ground-water temperature

was assigned using the data from Todd, (1980) and the unit’s geographical location.

In a location-adjusted modeling analysis, a site-specific ground-water

temperature can be directly specified in the input file – either as constant value or as

a statistical or empirical distribution of values.
Section 5.0 Hydrogeological Parameters

5-61

The aquifer temperature associated with the modeled site and the specified

hydrolysis rate constants are then used by the model to derive the appropriate

temperature-dependent first-order hydrolysis rate for organic constituents. Note that

although the temperature of the ground water within the vadose zone is not an

explicit model input, the EPACMTP model assumes that the soil temperature is the

same as that of the aquifer.

5.3.10 Ground-water pH (pH)

Definition

A measure of the acidity or alkalinity of the ground water, pH is measured on

a scale of 0 to 14, with 7 representing a neutral state. Values less than 7 are acidic,

and values greater than 7 are basic. pH is calculated as the negative logarithm of

the concentration of hydrogen ions in a solution. For modeling purposes, the

EPACMTP model assumes subsurface pH value is the same in the unsaturated

zone and saturated zone.

Parameter Value or Distribution of Values

If site-specific data are available, then the ground-water pH can be specified

in the input file as a constant value or an empirical or statistical distribution of values.

Lacking site-specific data, a default distribution of pH values may be used.

This pH distribution was obtained through analysis of nearly 25,000 field-measured

pH values of uncontaminated ground water obtained from EPA’s STORET database

(U.S. EPA, 1996). The data are represented by an empirical distribution with low

and high values of 3.2 and 9.7, respectively and a median value of 6.8. Because the

STORET database has unrealistic extreme values (presumably from errors in

instrument calibration or reading, or in data entry), the upper and lower bounds of

the distribution were established by reference to reported values in the open

literature. The resulting pH distribution is shown in Table 5.28. For a given

percentile (%) frequency and value pair in this table, the percentile denotes the

relative frequency or likelihood of parameter values in the entire distribution being

less than or equal to the corresponding parameter value in the right hand column.
Section 5.0 Hydrogeological Parameters

5-62

Table 5.28 Probability distribution of aquifer pH

% Ground-water pH (standard units)

0

10

25

50

75

80

85

90

95

100

4.32E+00

7.49E+00

7.30E+00

8.91E+00

7.84E+00

7.43E+00

4.65E+00

7.42E+00

5.74E+00

4.87E+00

Note that these values generated for the ground-water pH is assumed to

apply to the unsaturated zone as well. The EPACMTP model assumes that the

ground-water/aquifer system is well buffered with respect to pH. That is, in the

modeling analysis, there is no effect on the ambient pH from the leachate emanating

from the base of the WMU. Additionally, the generated pH value is assumed to

apply to both the unsaturated zone and saturated zone.

Data Sources

The distribution of pH values shown in Table 5.28 was obtained through

analysis of nearly 25,000 field measured pH values of uncontaminated ground water

obtained from EPA’s STORET database (U.S. EPA, 1996). Note that the upper and

lower bounds of this distribution were established by reference to reported values in

the open literature.

Use In EPACMTP

The ground-water pH is one of the most important subsurface parameters

controlling the mobility of metals. Most metals are more mobile under acidic (low

pH) conditions, as compared to neutral or alkaline (pH of 7 or higher) conditions.

The pH may also affect the hydrolysis rate of organic constituents; some

constituents degrade more rapidly or more slowly as pH varies. The pH of most

aquifer systems is slightly acidic, the primary exception being aquifers in solution

limestone settings. These may also be referred to as ‘karst’, ‘carbonate’ or ‘dolomite’

aquifers. The ground water in these systems is usually alkaline.
Section 5.0 Hydrogeological Parameters

5-63

5.3.11 Fractional Organic Carbon Content (foc

s

)

Definition

The nature and amount of solid matter in the subsurface to which chemical

constituents are attracted (the adsorbent) are important in determining the extent to

which a constituent’s transport through the ground-water pathway is retarded due to

adsorption. Particulate organic matter present in the saturated zone (input to

EPACMTP as fraction organic carbon) represents one of the dominant adsorbents

for sorption of both organic and metal constituents in environmental systems and

was one of the geochemical master variables used in the calculation of the nonlinear sorption isotherms using the MINTEQA2 model.

Parameter Value or Distribution of Values

If site-specific data are available, then the fractional organic carbon content

of the aquifer can be specified in the input file as a constant value or an empirical or

statistical distribution of values.

Lacking site-specific data, a default distribution of values may be used.

Unfortunately, few if any comprehensive subsurface characterizations of organic

carbon content exist. In general, the reported values are low, typically less than

0.01. For the purposes of modeling organic constituents, a low range of values was

assumed and the distribution shape was based on the distribution of measured

dissolved organic carbon recorded in EPA’s STORET data base. The default

distribution for fractional organic carbon content is a Johnson SB distribution with a

mean and standard deviation in arithmetic space of 4.32×10

-4 and 0.0456,

respectively and upper and lower limits of 0.064 and 0.0, respectively. In the case of

metals, the sorption is controlled by complex geochemical interactions which are

simulated using MINTEQA2 (see Section 3.3.3.2 and Appendix B), and this

distribution of focis not used.

A summary of this default distribution is presented in Table 5.29. For a given

percentile (%) frequency and value pair in this table, the percentile denotes the

relative frequency or likelihood of parameter values in the entire distribution being

less than or equal to the corresponding parameter value in the right hand column.
Section 5.0 Hydrogeological Parameters

5-64

Table 5.29 Probability distribution of fraction organic carbon in the saturated

zone

% Fractional Organic Carbon Content (unitless)

0

10

25

50

75

80

85

90

95

100

6.77E-04

4.11E-03

8.51E-04

1.10E-04

4.71E-04

7.82E-04

3.01E-04

9.99E-04

5.99E-04

7.93E-04

Data Sources

The default distribution for foc was derived based on professional judgement

and the distribution shape was based on the distribution of measured dissolved

organic carbon recorded in EPA’s STORET database.

Use In EPACMTP

The organic carbon content, foc, is used to determine the linear distribution

coefficient, Kd. This approach is valid only for organic contaminants containing

hydrophobic groups since these constituents tend to sorb preferentially on non-polar

natural organic compounds in the soil or aquifer. In the case of metals, the organic

matter content in the subsurface is one of the controlling master variables used to

develop the MINTEQA2-derived isotherms, and EPACMTP uses this organic matter

content to select appropriate isotherms to use during the EPACMTP simulation

process.

5.3.12 Leading Coefficient of Freundlich Isotherm for Saturated Zone (Kd

s

)

Definition

The leading coefficient of the Freundlich isotherm is a constant used to

describe the sorptive behavior of a constituent. When the sorption data are plotted

as log C versus log S, the intercept of the resulting line is equal to log K

s

. In the

special case of a linear isotherm, the leading Freundlich coefficient is known as the

linear solid-liquid phase distribution coefficient (Kd

s

) (commonly called the

distribution coefficient).
Section 5.0 Hydrogeological Parameters

5-65

Parameter Value or Distribution of Values

When modeling organic constituents with EPACMTP, the leading Freundlich

coefficient is generally specified as a derived parameter in the input file. If derived,

the leading Freundlich coefficient (Kd

s

) is automatically assumed linear and

calculated by the model according to Equation 5.3b. In this case, foc

is specified in

the aquifer-specific input group according to Equation 5.2, and koc

is a constituentspecific input value (see Section 3.3.2.1). However, if site-specific data are

available, a constant value or distribution of values could be used for the leading

Freundlich coefficient.

When modeling metals transport in the saturated zone with EPACMTP, the

leading Freundlich coefficient can be specified as a constant value or as a

distribution of values, either based on site-specific data or adsorption data reported

in the scientific literature. Another option is to specify sorption according to

equations comprising pH-based (linear) isotherms. In this case, this input parameter

is not used; that is, this record in the input file is ignored by the model. Instead, the

Kd

s

(Equation 5.3c) is calculated as a function of pH (see Section 3.3.3.1.2).

Alternatively, if tables of non-linear sorption isotherms developed using the

MINTEQA2 geochemical model are used to model transport in the unsaturated

zone, then a single Kd

s

value is chosen from these tabulated data to be used in the

aquifer. As implemented in EPACMTP, the non-linearity of the isotherms is most

important in the unsaturated zone where the concentrations are relatively high.

Upon reaching the water table and mixing the leachate with ambient ground water,

the metal’s concentration is considered to be low enough that a linear isotherm can

always be used. The appropriate saturated zone Kd

s

value is automatically chosen

by the model based on the maximum ground-water concentration under the source.

In this case as well, this input parameter is not used; that is, this record in the input

file is ignored by the model. Instead, the Kd

s

(Equation 5.3c) is chosen from

tabulated data (see Sections 3.3.3.2 and 5.3.13 and Appendix B).

Data Sources

Generally, the Kd

s

for organic constituents is specified as a derived

parameter; however, if this option is not appropriate and site-specific data are not

available, there are studies in the scientific literature that provide compilations of Kd

s

values that have been measured in the field (for instance, see Risk Assessment for

the Listing Determinations for Inorganic Chemical Manufacturing Wastes; U.S. EPA,

2000). In this case, the leading Freundlich coefficient would be specified as either a

constant value or a distribution of values (and the Freundlich exponent would be set

to its default value of 1.0).

The leading Freundlich coefficient for metals is generally superceded by use

of either the MINTEQA2-derived sorption data or the pH-based linear isotherms that

were developed specifically for use with the EPACMTP model (see Section 3.3.3).

However, if neither of these two options is appropriate and site-specific data are not

available, there are studies in the scientific literature that provide compilations of Kd

’s
Section 5.0 Hydrogeological Parameters

5-66

that have been measured in the field (for instance, see Appendix I of U.S. EPA,

2000). In this case, the leading Freundlich coefficient would be specified as either a

constant value or a distribution of values.

Use In EPACMTP

The leading Freundlich coefficient (also called the distribution coefficient) is

one of the parameters used to calculate the amount by which contaminant transport

is retarded relative to the ambient ground-water flow velocity within the aquifer. It is

an input to the saturated zone transport module.

5.3.13 Exponent of Freundlich Isotherm for Saturated Zone (

s

)

Definition

The exponent of the Freundlich isotherm is a constant used to describe the

sorptive behavior of a constituent. When the sorption data are plotted as log C

versus log S, the slope of the resulting line is equal to 

s

. In the special case of a

linear isotherm, the exponent of the Freundlich isotherm is equal to 1.0.

Parameter Value or Distribution of Values

For modeling organic constituents, the default value of the Freundlich

exponent is 1.0, meaning a linear adsorption isotherm is used.

When modeling metals transport in the saturated zone with EPACMTP, the

distribution coefficient for metals is generally specified using either tabulated nonlinear MINTEQA2 isotherms or pH-based linear isotherms that were developed

specifically for use with the EPACMTP model (see Section 3.3.3). In these two

cases, the Kd data is either read in from an auxiliary input file or internally calculated,

and the Freundlich isotherm coefficient and exponent are not used. If the leading

Freundlich coefficient is specified using an empirical distribution of values (e.g.,

based on reported Kd values in the scientific literature), then the Freundlich isotherm

exponent should be set equal to 1.0.

If this parameter is omitted from the data file, it is assigned a default value of

1.0, which is equivalent to specifying a linear sorption isotherm.

In EPACMTP Version 2.0, only the case of  = 1 is permitted. Non-linear

isotherms (see Equation 5.3c) to describe metals transport are used only in the

unsaturated zone and are handled using the tabular type of input described in

Section 3.3.3.2 and Appendix B.
Section 5.0 Hydrogeological Parameters

5-67

Data Sources

For modeling organic constituents, the Freundlich isotherm exponent is

generally set to its default value of 1.0, and so no specific data source is used to

determine the appropriate value for the Freundlich exponent.

For modeling metal constituents, the Freundlich isotherm exponent is not

used as an input parameter, and so no specific data source is used (see Section

3.3.3.2). If literature or site-specific data are used to specify a non-linear adsorption

isotherm, modeling of the adsorption process is implemented via tabular input

describing the relationship in Equation 5.3c.

Use In EPACMTP

The Freundlich exponent is one of the parameters used to calculate the

amount by which contaminant transport is retarded relative to the ambient groundwater flow velocity within the aquifer; it is an input to the saturated zone transport

module.

5.3.14 Chemical Degradation Rate Coefficient for Saturated Zone (λc

s

)

Definition

EPACMTP accounts for all transformation processes (both biological and

chemical) using a lumped first-order decay coefficient. This overall decay coefficient

is the sum of the chemical and biological transformation coefficients. The chemical

degradation coefficient for the saturated zone is simply the rate of decay that is

caused by chemical reactions (usually hydrolysis) in the saturated zone.

Parameter Value or Distribution of Values

By default, the chemical degradation coefficient in the saturated zone is set

to be internally derived using the hydrolysis rate constants and the saturated zone

properties according to Equation 3.4. However, if site-specific data are available,

this parameter can be specified as a constant value or a distribution of values. In

this case, the hydrolysis rate constants can be omitted from the input file.

Data Sources

If this parameter is not derived by the model, then a site-specific data source

must be used to determine the appropriate input value.

Use In EPACMTP

The chemical degradation coefficient is used by the model to calculate the

amount by which ground-water concentrations are attenuated due to chemical

hydrolysis; it is an input to the saturated zone transport module and is one of the
Section 5.0 Hydrogeological Parameters

5-68

parameters required to solve the advection-dispersion equation (see Sections 3.3.4

and 4.4.4 of the EPACMTP Technical Background Document (U.S. EPA, 2003a).

5.3.15 Biodegradation Rate Coefficient for Saturated Zone (λb

s

)

Definition

EPACMTP accounts for all transformation processes (both biological and

chemical) using a lumped first-order decay coefficient. This overall decay coefficient

is the sum of the chemical and biological transformation coefficients. The biological

degradation coefficient for the saturated zone is simply the rate of decay that is

caused by biological processes in the saturated zone.

Parameter Value or Distribution of Values

By default, the biological degradation coefficient in the saturated zone is set

equal to zero. However, if site-specific data are available, this parameter can be

specified as a constant value or a distribution of values.

Data Sources

If the input value of this parameter is non-zero, then a site-specific data

source must be used to determine the appropriate input value.

Use In EPACMTP

The biological degradation coefficient is used by the model to calculate the

amount by which ground-water concentrations are attenuated due to biological

processes; it is an input to the saturated zone transport module and is one of the

parameters required to solve the advection-dispersion equation (see Sections 3.3.4

and 4.4.4 of the EPACMTP Technical Background Document (U.S. EPA, 2003a).
Section 6.0 Receptor Well Parameters

6-1

6.0 RECEPTOR WELL PARAMETERS

A receptor well is a hypothetical drinking water well that is located

downgradient of the waste management unit in consideration. It represents the

location at which the potential exposure to the ground water is measured.

Discussed in this section are the EPACMTP input parameters which govern the

generation and constraining of the receptor well location. These include Monte

Carlo parameters that the user can specify. These parameters can be used to apply

(or not apply) particular constraints on parameter values or generation methodology.

6.1 RECEPTOR WELL PARAMETERS

The parameters listed below in Table 6.1 are used to define the

characteristics of the downgradient receptor well.

Table 6.1 Receptor Well Parameters

Parameter Symbol Units Section Equation in EPACMTP TBD

Radial Distance to

Receptor Well

Rrw m 6.2 4.21, 4.22, 4.25 and 4.26

Angle of Well Off of Plume

Centerline

rw degrees 6.3 4.26a

Downgradient Distance to

Receptor Well

xrw m 6.4 4.21, 4.25a and 4.26b

Well Distance From

Plume Centerline

yrw m 6.5 4.22, 4.25b and 4.26c

Rrw Origination Method IWLOC - 6.5 Section 4.4.3.6

Constraint on Well

Distance From Plume

Centerline

LYCHK - 6.5 4.28 as constraint on yrw

Depth of Intake Point

Below Watertable

m 6.6 4.29

Constraint on Depth of

Intake Point Below

Watertable

LZCHK - 6.6 4.29 as constraint on z

*

rw

Averaging Period for

Ground-water

Concentration at Receptor

Well

td yr 6.7 4.108 and 4.109

EPACMTP ultimately represents the receptor well location in a Cartesian

coordinate system whose X axis is oriented along the plume centerline for

convenience. However, the user can specify the areal receptor well location in either

cylindrical (Rrw,rw) or Cartesian (xrw,yrw) coordinates and the model will transform the

inputs accordingly. It’s important to note that the specification of the receptor well
Section 6.0 Receptor Well Parameters

6-2

depth, , is not dependent upon the chosen coordinate system. Figure 6.1

illustrates how the receptor well location is determined using cylindrical coordinates

(Figure 6.1a) and Cartesian coordinates (Figure 6.1b).

EPACMTP provides two optional constraints to force receptor well locations

into the interior of the dissolved constituent plume; one constraint applies to the areal

location of the receptor well (LYCHK), and the other constrains the depth of the

receptor well (LZCHK). By default, the receptor well can be located anywhere

downgradient of the WMU (radial distance of up to about one mile, with the angle offcenter varying uniformly between 0 and 90 degrees) and anywhere within the

saturated thickness of the aquifer.

An additional option (IWLOC) provides a receptor well locating methodology

which addresses the tendency of WMUs with very large areas (e.g., LAUs) to bias

upward the Monte Carlo receptor well concentrations. This option is further described

in Section 6.5.

The final parameter discussed in this section is the averaging period for

ground water concentration at the receptor well. The averaging period is useful for

risk calculations which require an estimate of the exposure concentration over a

period of time, say 30 years.
Section 6.0 Receptor Well Parameters

6-3

Figure 6.1 Schematic plan view showing procedure

for determining the downstream location of the

receptor well: (a) well location determined using radial

distance, Rrw, and angle off center rw; and (b) well

location generated uniformly within plume limit
Section 6.0 Receptor Well Parameters

6-4

6.2 RADIAL DISTANCE TO RECEPTOR WELL (Rrw)

Definition

The radial distance to the receptor well (m) is measured from the

downgradient edge of the WMU to the nearest downgradient receptor well, as

depicted in Figure 6.1a.

Parameter Value or Distribution of Values

As shown in Figures 6.1a and 6.1b, the default reference point or origin for

determining the receptor well location is midpoint of the downgradient edge of the

WMU. EPACMTP provides an alternative receptor well location methodology for

determining the reference point and it is controlled by the Monte Carlo control

parameter IWLOC. Setting the Monte Carlo control parameter IWLOC equal to zero

instructs EPACMTP to use the default reference point for determining the receptor

well location. If IWLOC is set equal to one, the alternate location method is used.

The alternate method has been included as a means to reduce the bias introduced by

WMUs with large areas. When Rrw

is always measured from the default reference

point, receptor well locations are more likely to lay inside the areal extent of the

dissolved constituent plume as the size of the WMU increases, biasing exposure

concentrations upward. To reduce the potential bias, the reference point in the

alternate scenario may be at any point somewhere between the corner and the center

of the downgradient edge of the WMU. Section 4.4.3.6 in the EPACMTP Technical

Background Document (U.S. EPA, 2003a) describes the alternate method in detail.

Rrw may be specified by any appropriate distribution of values or by a constant value

to accommodate site-specific data or analysis-specific assumptions. Lacking sitespecific data, Rrw

is typically determined using the empirical distribution shown in

Table 6.2.

Data Sources

In a Monte Carlo simulation, the primary output from the model is the

exposure concentration at a receptor well located downgradient from the waste site.

Available studies and surveys suggest that on average, multiple downgradient wells

are present within the one-mile distance that is typically considered in regulatory

applications. To ensure a degree of protection in the modeling analysis, the model

computes the concentration at the nearest downgradient well. Information on the

downgradient distance to the nearest receptor well can be obtained from the U.S.

EPA OSW landfill survey (U.S. EPA, 1993). These data are presented as an

empirical distribution in Table 6.2. At most waste sites included in this survey, the

direction of ambient ground-water flow was not known exactly; therefore, it cannot be

ascertained whether the nearest receptor well is located directly along the plume

centerline. To reflect uncertainties and variations in the location of the receptor well

in relation to the direction of ambient ground-water flow, the modeled well is typically

allowed to be positioned at some varying distance from the plume centerline.
Section 6.0 Receptor Well Parameters

6-5

Table 6.2 Cumulative Probability of Distance to Nearest Receptor Well for

Landfills (from EPA, 1993)

Cumulative Probability Radial Distance (m)

0.0

0.03

0.04

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0.60

0.65

0.70

0.75

0.80

0.85

0.90

0.95

0.98

1.00

0.6

13.7

19.8

45.7

103.6

152.4

182.9

243.8

304.8

304.8

365.7

396.2

426.7

457.2

609.6

762.0

804.6

868.6

914.4

1158.2

1219.1

1371.5

1523.9

1609.3

Use In EPACMTP

The first, and default, option of determining the well location involves

determining the Cartesian coordinates of the receptor well as a function of the radial

distance (Rw

) from the center of the downgradient edge of the WMU and the angle off

of thje plume centerline (rw

), as depicted in Figure 6.1a. If Rrwis specified, rw must

also be specified. EPACMTP will derive xrw and yrwfrom the cylindrical coordinates

(see Section 6.4).

6.3 ANGLE OF WELL OFF OF PLUME CENTERLINE (rw)

Definition

The first, and default, option of determining the well location involves

determining the Cartesian coordinates of the receptor well as a function of the radial

distance (Rrw

) from the center of the downgradient edge of the WMU and the angle
Section 6.0 Receptor Well Parameters

6-6

off of the plume centerline (rw), as depicted in Figure 6.1a. This angle, in

conjunction with Rrw, defines the receptor well location in the cylindrical coordinates.

Parameter Value or Distribution of Values

rw may be specified by any appropriate distribution of values or by a constant

value to accommodate site-specific data or analysis-specific assumptions. For

example, setting rw

to zero would constrain the receptor well location to the plume

centerline. Lacking site-specific data, to include all potential wells located

downstream of the waste units, the angle rwis typically taken to be uniformly

distributed between 0°and 90°.

Data Sources

In a Monte Carlo simulation, the primary output from the model is the

exposure concentration at receptor well located downgradient from the waste site. If

site-specific data are unavailable, a default distribution of values may be used. Since

multiple downgradient wells are often present within the default one-mile distance, to

be protective, the modeled receptor well is taken to be the nearest downgradient well

based on an EPA OSW survey of municipal landfills (U.S. EPA, 1993). However, at

most waste sites included in this survey, the direction of ambient ground-water flow

was not known exactly; therefore, it cannot be ascertained whether the nearest

receptor well is located directly along the plume centerline. To reflect uncertainties

and variations in the location of the receptor well in relation to the direction of ambient

ground-water flow, the modeled well is typically allowed to be positioned at a variable

y-distance from the plume centerline.

Thus, to include all hypothetical receptor wells located downstream of the

waste units, the angle rw

is, by default, assumed to be uniformly distributed between

0°and 90°.

Use In EPACMTP

The first, and default, option of determining the well location involves

determining the Cartesian coordinates of the receptor well as a function of the radial

distance (Rrw) from the center of the downgradient edge of the WMU and the angle

off of the plume centerline (rw), as depicted in Figure 6.1a. If rwis specified, Rrw

must also be specified. EPACMTP will derive xrw and yrwfrom the cylindrical

coordinates (see Section 6.4).

6.4 DOWNGRADIENT DISTANCE TO RECEPTOR WELL (xrw)

Definition

The downgradient distance to the receptor well (m) is the distance to the well,

as measured from the center of downgradient edge of the WMU along the long-term

average ground-water flow path (plume centerline), as depicted in Figure 6.1b.
Section 6.0 Receptor Well Parameters

6-7

(6.1)

Parameter Value or Distribution of Values

The first, and default, option of determining the well location involves

determining the Cartesian coordinates of the receptor well as a function of the radial

distance, Rrw, from the center of the downgradient edge of the waste unit, and the

angle off-center, rw

, as depicted in Figure 6.1a. xrwis derived using the following

equation:

where

xrw = X Cartesian coordinate of the receptor well (m)

Rrw = radial distance between waste unit and well (m),

rw = angle measured counter-clockwise from the plume centerline

(degrees)

The second method incorporated in EPACMTP to determine the receptor well

location is to generate a well position directly from the Cartesian coordinates, xrw and

yrw. In this case, the Cartesian parameters are specified in the EPACMTP input file,

and the cylindrical parameters are ignored (typically these inputs are omitted from the

input file). If site-specific data on well location(s) are available, then these data can

be used to specify a constant value or an empirical or statistical distribution of values

for xrw and yrw.

Alternatively, xrw and yrw can also be used to specify the well location such that

the well is located uniformly between the plume centerline and the areal plume

boundary, for any given x-distance (Figure 6.1b). This option is described further in

Section 6.5 (Well Distance From Plume Centerline (yw

)) .

To reflect uncertainties and variations in the location of the receptor well in

relation to the direction of ambient ground-water flow, the modeled well is allowed to

be positioned at some varying distance from the plume centerline.

Data Sources

Lacking site-specific data, information on the downgradient distance to the

nearest receptor well can be obtained from the U.S. EPA OSW landfill survey (U.S.

EPA, 1993). These data are presented as an empirical distribution in Table 6.2.

Use In EPACMTP

The downgradient distance to the receptor well (xrw) is used to represent the

location at which the potential exposure concentration to the ground water is

measured.
Section 6.0 Receptor Well Parameters

6-8

(6.2)

(6.3)

6.5 WELL DISTANCE FROM PLUME CENTERLINE (yrw)

Definition

The well distance from the plume centerline (m) is the distance from the

plume centerline to the well, measured perpendicular to the plume centerline, as

depicted in Figure 6.1b.

Parameter Value or Distribution of Values

The first, and default, option of determining the well location involves

determining the Cartesian coordinates of the receptor well as a function of the radial

distance, Rrw, from the center of the downgradient edge of the waste unit, and the

angle off-center, rw, as depicted in Figure 6.1a. The parameter yrwis derived using

the following equation:

where

yrw = Y Cartesian coordinate of the receptor well (m)

Rrw = radial distance between waste unit and well (m),

rw = angle measured counter-clockwise from the plume centerline

(degrees)

The second method incorporated in EPACMTP to determine the receptor well

location is to generate a well position directly from the Cartesian coordinates, xrw and

yrw. In this case, the Cartesian parameters are specified in the EPACMTP input file,

and the cylindrical parameters are ignored (typically these inputs are omitted from the

input file). If site-specific data on well location(s) are available, then these data can

be used to specify a constant value or an empirical or statistical distribution of values

for xrw and yrw.

Alternatively, xrw and yrw can also be used to estimate the well location such

that the well is located uniformly between the plume centerline and the areal plume

boundary, for any given x-distance (Figure 6.1b). With this option, xrw

is generated

from the empirical distribution in Table 6.2. Next, the yrw of the well is generated from

a uniform distribution with a minimum value of zero, and a maximum value given by

the following equation:
Section 6.0 Receptor Well Parameters

6-9

where

yD = width of the waste unit in the y-direction (m)

xrw = length of the waste unit in the x-direction (m)

T = horizontal transverse dispersivity (m)

xw = length of the WMU in the x-direction (parallel to ground-water

flow) (m)

This approximation for the lateral extent of the contaminant plume is based on

the assumption that plume spreading in the horizontal-transverse direction is caused

by dispersive mixing, which results in a Gaussian profile of the plume cross-section.

Use of Equation 6-3 implies that 99.7% of the contaminant mass will be present

inside the transverse plume limit.

To select this option, the Monte Carlo control parameter LYCHK should be set

to TRUE, the xrw should be specified as an empirical parameter with values as given

in Table 6.2, and the yrw should be specified as a uniform distribution with limits of

zero and one.

Data Sources

No default data sources are available for yrw. Information on the downstream

distance to the nearest receptor well can be obtained from the U.S. EPA OSW landfill

survey (U.S. EPA, 1993). These data are presented as an empirical distribution in

Table 6.2. At most waste sites included in this survey, the direction of ambient

ground-water flow was not known exactly; therefore, it cannot be ascertained whether

the nearest receptor well is located directly along the plume centerline. To reflect

uncertainties and variations in the location of the receptor well in relation to the

direction of ambient ground-water flow, the modeled well is typically allowed to be

positioned at some varying distance from the plume centerline if site-specific data are

not available.

Use In EPACMTP

Along with the term xrw(downgradient distance to the receptor well), the yrw

parameter is used to define the location of a receptor well. The yrw parameter

represents the perpendicular distance from the plume centerline at which the

potential exposure to the ground water is measured. Setting yrw

to zero constrains

the receptor well location to the plume centerline.
Section 6.0 Receptor Well Parameters

6-10

(6.4)

6.6 DEPTH OF INTAKE POINT BELOW WATERTABLE (z

*

rw)

Definition

The depth of the intake point below the water table (m) is the depth at which

the model calculates the resulting ground-water concentration. Unlike most wells in

the real world that have a screened interval of several feet or more, the simulated

receptor well in EPACMTP has an intake that is a single point in space, as if the well

consisted of a solid casing that was open at the bottom. In this case, the intake point

would be the same as the depth of the well (or z

*

rw

). Note that this depth is measured

downwards from the watertable, not from the ground surface.

Parameter Value or Distribution of Values

Three options are available for specifying the vertical position of the well

intake point below the water table: uniform distribution, constrained distribution, or

constant value.

The first, and default, option is to model the vertical position of the well intake

point as being uniformly distributed between the water table (z=0) and the saturated

aquifer thickness. This option is selected by specifying the z-position as a uniform

distribution with lower and upper limits of 0.0 and 1.0. EPACMTP will multiply this

uniformly generated value by the saturated zone thickness to yield the actual receptor

well depth below the water table for each Monte Carlo iteration. When the generated

value for the vertical position of the receptor well intake point exceeds the saturated

thickness of the aquifer (a physically impossible condition), a new well position is

generated to ensure that the well depth is always less than the saturated thickness.

Conversely, the well depth cannot be less than the minimum depth to the saturated

zone.

Alternatively, the vertical position of the observation well can be optionally

constrained to lie within the approximate vertical penetration depth of the contaminant

plume emanating from the waste unit. This is achieved through the Monte Carlo

input variable LZCHK. If LZCHK is set to FALSE, the constraint is not enforced. If

LZCHK is set to TRUE, the z

*

rw

is constrained to lie within the approximate vertical

extent of the contaminant plume as defined by:
Section 6.0 Receptor Well Parameters

6-11

where

z*rw max = Maximum allowable z*-coordinate of the receptor well; that is,

the approximate vertical penetration depth of the dissolved

constituent plume (m)

Q

F

1

-Q

F

4= Components of the ground-water flow field (m2

/yr), see U.S.

EPA (2003a), Section 4, Figure 4.7

B = Saturated zone thickness (m)

xw = Length of source in downstream direction (m)

xrw = Horizontal distance between source and receptor well (m)

L = Longitudinal dispersivity (m)

v = Vertical dispersivity (m)

e = Effective porosity of the aquifer (dimensionless)

D

s* = Effective molecular diffusion coefficient (m2

/y)

As a third option, the well position may be fixed at a constant absolute depth

or as a constant relative depth (as a constant fractional depth of the saturated

thickness).

Data Sources

In the absence of site-specific data for this input, is typically defined as a

uniformly distributed fraction of the saturated thickness.

Use In EPACMTP

The depth of the intake point below the water table is the depth at which the

model calculates the resulting ground-water concentration. It is from this point that a

ground-water concentration of a potential contaminant plume would be established.

6.7 AVERAGING PERIOD FOR GROUND-WATER CONCENTRATION AT

RECEPTOR WELL (td)

Definition

The averaging period for the ground-water concentration at the receptor well

(yr) is the time period over which the average concentration is calculated. For

instance, if this input is specified as 30 years, then the EPACMTP model would

search for the highest 30-year average concentration over the specified modeling

period and report this concentration in the output file. This ground-water averaging

time should correspond to the exposure duration used in the health-risk calculations

for carcinogenic constituents. Up to ten averaging times may be specified.
Section 6.0 Receptor Well Parameters

6-12

Parameter Value or Distribution of Values

Usual values of this parameter are 70 years (lifetime exposure), 30 years

(high-end residence time), 9 years (average residence time), or 7 years (child

exposure) (U.S. EPA, 2000). Although this value is often entered as a constant

value, it can also be specified as a statistical or empirical distribution of values.

By default, the exposure period for averaging the receptor well concentration

is not provided; in other words, the model only calculates the peak receptor well

concentration. The peak receptor well concentration is sometimes used for

calculating the resulting health risk for non-carcinogenic constituents or for

comparisons to the maximum contaminant levels (MCLs) (The National Drinking

Water Standards at 40 CFR 141).

Data Sources

The choice of the averaging period should be consistent with the types of

risks to be calculated using the exposure results generated by EPACMTP. The

EPA’s Exposure Factors Handbook (U.S. EPA 1997a-c) contains constituent-specific

data on exposure durations for various exposure scenarios.

Use In EPACMTP

EPACMTP always generates a steady state receptor well concentration and a

peak concentration. Steady state concentrations correspond to an infinite source

analysis; peak concentrations represent the maximum concentration at the well under

the finite source scenario. Average concentrations for defined exposure periods are

optional results for finite source simulations. If average concentrations are required,

up to 10 averaging periods can be specified. If the period of averaging is longer than

the period of time for which concentrations are observed at the receptor well, the

result will be the average of the available observations.
Section 7.0 References

7-1

7.0 REFERENCES

API, 1989. Hydrogeologic Database for Groundwater Modeling. API Publication No.

4476, American Petroleum Institute.

Bear, J., 1979. Hydraulics of Groundwater. McGraw Hill, New York.

Bonaparte, R., J. P. Giroud, and B.A. Cross, 1989. Rates of leakage through landfill

liners. Geosynthetics 1989 Conference, San Diego, California.

Carsel, R.F., and R.S. Parrish, 1988. Developing joint probability distributions of soil

water retention characteristics. Water Resour. Res. Vol 24, No. 5:755-769.

Carsel, R.F., R.S. Parrish, R.L. Jones, J.L. Hansen, and R.L. Lamb, 1988.

Characterizing the Uncertainty of Pesticide Leaching in Agricultural Soils.

Journal of Contaminant Hydrology Vol 2: 111-124.

CRC, 1981. Handbook of Chemistry and Physics. 62nd edition. Chemical Rubber

Company, Cleveland, OH 44128.

Davis, S.N., 1969. Porosity and permeability of natural materials. In: Flow Through

Porous Media, R.J.M. de Wiest, Editor, Academic Press, NY. 10007

Enfield, C.G., et al., 1982. Approximating pollutant transport to groundwater.

Ground Water, 10(6):711-722.

EPRI, 1985. A review of field scale physical solute transport processes in saturated

and unsaturated porous media. Electric Power Res. Inst., Palo Alto, CA.

Freeze, R.A., and J. Cherry, 1979. Groundwater. Prentice-Hall, Englewood Cliffs,

NJ. 08837

Gelhar, L.W., C. Welty, K.R. Rehfeldt, 1992. A critical review of data on field-scale

dispersion in aquifers. Water Resour. Res., 28(7), 1955-1974.

Gintautas, P.A., K.A. Huyck, S.R. Daniel, and D.L. Macalady, 1993. Metal-Organic

Interactions in Subtitle D Landfill Leachates and Associated Groundwaters, in

Metals in Groundwaters, H.E. Allen, E.M. Perdue, and D.S. Brown, eds.

Lewis Publishers, Ann Arbor, MI. 60604

Heath, R.C., 1984. State Summaries of Groundwater Resources. United States

Geological Survey Water-Supply Paper 2275.

HydroGeoLogic, Inc., 1992. A Revised Procedure for Determining Dispersivity

Values for Use in EPA Fate and Transport Models. HydroGeoLogic, Inc.,

Herndon, VA. 20170
Section 7.0 References

7-2

Karickhoff, S.W., 1985. Sorption protocol for evaluation of OSW chemicals. U.S.

EPA, Athens Environmental Research laboratory, Athens, GA. 30605

Kollig, H.P., 1993, Environmental Fate Constants for Organic Chemicals Under

Consideration for EPA’s Hazardous Waste Identification Projects, Report No.

EPA/600/R-93/132).

Loux, N.T., C.R. Chafin, and S.M Hassan, 1990. Statistics of Aquifer Material

Properties and Empirical pH-dependent Partitioning Relationships for As(III),

As(V), BA(II), Cd(II), Cr(VI), Cu(II), Hg(II), Ni(II), Pb(II), Sb(V), Se(IV), Tl(I),

and Zn(II). U.S. Environmental Protection Agency, Athens, GA. 30605

Mathur, S. S., 1995. Development of a Database for Ion Sorption on Goethite Using

Surface Complexation Modeling. Master’s Thesis, Department of Civil and

Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA.

15230

McWorter, D.B., and D.K. Sunada, 1977. Groundwater Hydrology and Hydraulics,

Water Resources Publications, Fort Collins, CO.

Newell, C. J., L. P. Hopkins, and P. B. Bedient, 1990. A hydrogeologic data base for

groundwater modeling. Ground Water 28(5):703-714.

Schanz, Rob, and Salhotra, Atul, 1992. Subtitle D Landfill Characteristics. Center

for Modeling and Risk Assessment, Woodward-Clyde Consultants, Oakland,

California.

Schroeder, P.R., T.S., Dozier, P.A. Zappi, B.M. McEnroe, J. W. Sjostrom, and R.L.

Peton, 1994. The hydrologic evaluation of landfill performance model

(HELP): Engineering Documentation for Version 3. EPA/600/R-94/1686.

United States Environmental Protection Agency, Cincinnati, OH.

Shea, J.H., 1974. Deficiencies of elastic particles of certain sizes. Journal of

Sedimentary Petrology, 44: 985-1003.

TetraTech, Inc., 2001. Characterization of infiltration rate data to support

groundwater modeling efforts (Draft). Prepared for the U.S. Environmental

Protection Agency, Office of Solid Waste, Contract No. 68-W6-0061, May,

2001.

Todd, D.K., 1980. Groundwater Hydrology (2nd edition), John Wiley & Sons, 535

pages.

U.S. EPA, 1985. DRASTIC: A Standardized System for Evaluating Ground Water

Pollution Potential Using Hydrogeologic Settings. EPA/600-2-85/018,

Washington, DC. 20460
Section 7.0 References

7-3

U.S. EPA, 1986. Industrial Subtitle D Facility Study (Telephone Survey), U.S.

Environmental Protection Agency, October 20, 1986.

U.S. EPA, 1990. Background Document for EPA's Composite Model for Landfills

(EPACML). U.S. EPA, Office of Solid Waste, Washington, D.C., 20460.

U.S. EPA, 1993. Parameter values for the EPA’s composite module for landfills

(EPACML) used in developing nationwide regulations: Toxicity Characteristic

Rule, Office of Solid Waste, Washington, D.C., 20460.

U.S. EPA. 1996. EPA's Composite Model for Leachate Migration with

Transformation Products, Background Document for EPACMTP: Metals

Transport in the Subsurface, Volume 1: Methodology. Office of Solid Waste.

U.S. Environmental Protection Agency, Washington, D.C. 20460.

U.S. EPA, 1997a. Exposure Factors Handbook, Volume I, General Factors.

EPA/600/P-95/002Fa. Office of Research and Development, Washington,

DC. 20460

U.S. EPA, 1997b. Exposure Factors Handbook, Volume II, Food Ingestion Factors.

EPA/600/P-95/002Fb. Office of Research and Development, Washington,

DC. 20460

U.S. EPA, 1997c. Exposure Factors Handbook, Volume III, Activity Factors.

EPA/600/P-95/002Fc. Office of Research and Development, Washington,

DC. 20460

U. S. EPA. 1997d. Analysis of EPA’s Industrial Subtitle D Databases used in

Groundwater Pathway Analysis of the Hazardous Waste Identification Rule

(HWIR). Office of Solid Waste, Washington, DC. 20460

U.S. EPA. 1999. EPA's Composite Model for Leachate Migration with

Transformation Products, Background Document for EPACMTP: Metals

Transport in the Subsurface, Volume 2: Sorption Isotherms. Office of Solid

Waste. U.S. Environmental Protection Agency, Washington, D.C. 20460.

U.S. EPA, 2000. Risk Assessment for the Listing Determination for Inorganic

Chemical Manufacturing Wastes: Background Document. U.S.

Environmental Protection Agency, Office of Solid Waste, Washington, DC

20460.

U.S. EPA, 2001a. Industrial Surface Impoundments in the United States. U.S. EPA

Office of Solid Waste, Washington, DC 20460. USEPA 530-R-01-005.

U.S. EPA, 2001b. Water 9 Model. Office of Air Quality Planning and Standards,

Research Triangle Park, NC. 27711

http://www.epa.gov/ttn/chief/software/water/index.html.
Section 7.0 References

7-4

U.S. EPA, 2003a. EPACMTP Technical Background Document. Office of Solid

Waste, Washington, DC. 20460

U.S. EPA, 2003b. IWEM User’s Guide. Office of Solid Waste, Washington, DC.

20460 USEPA 530-R-02-013.

U.S. EPA, 2003c. IWEM Technical Background Document. Office of Solid Waste,

Washington, DC. 20460 USEPA 530-R-02-012.

van Genuchten, M.Th., 1980. A closed-form equation for predicting the hydraulic

conductivity of unsaturated soils, Soil Sci. Soc. J., v. 44, pp. 892-898.

Verschueren, K., 1983. Handbook of Environmental Data on Organic Chemicals.

Van Nostrand Reinhold Co., New York. 10017

White, D.E., J.D. Hem, and G.A. Waring, 1963. Chemical Composition of

Subsurface Waters, Data of Geochemistry. U.S. Geological Survey

Professional Paper 440-F, U.S. Government Printing Office, Washington,

DC.

Wolfe, N.L., 1985. Screening of hydrolytic reactivity of OSW chemicals. US EPA

Athens Environmental Research Laboratory, Athens, GA. 30605
APPENDIX A

DETERMINATION OF INFILTRATION AND RECHARGE RATES
This page intentionally left blank.
A-i

TABLE OF CONTENTS

Page

A.1 INFILTRATION AND RECHARGE RATES . . . . . . . . . . . . . . . . . . . . . . . A-1

A.1.1 USING THE HELP MODEL TO DEVELOP RECHARGE AND

INFILTRATION RATES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-2

A.1.2 INFILTRATION RATES FOR UNLINED UNITS . . . . . . . . . . . . . A-11

A.1.3 SINGLE-LINED WASTE UNITS . . . . . . . . . . . . . . . . . . . . . . . . . A-14

A.1.4 INFILTRATION RATES FOR COMPOSITE-LINED UNITS . . . . A-16

A.1.5 DETERMINATION OF RECHARGE RATES . . . . . . . . . . . . . . . A-33

A.2 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-34
A-ii

LIST OF FIGURES

Page

Figure A.1 Locations of HELP Climate Stations . . . . . . . . . . . . . . . . . . . . . . . . A-7
A-iii

LIST OF TABLES

Page

Table A.1 Methodology Used to Compute Infiltration for LFs . . . . . . . . . . . . A-3

Table A.2 Methodology Used to Compute Infiltration for SIs . . . . . . . . . . . . A-4

Table A.3 Methodology Used to Compute Infiltration for WPs . . . . . . . . . . . A-5

Table A.4 Methodology Used to Compute Infiltration for LAUs . . . . . . . . . . . A-6

Table A.5 Grouping of Climate Stations by Average Annual Precipitation

and Pan Evaporation (ABB, 1995) . . . . . . . . . . . . . . . . . . . . . . . . A-9

Table A.6 Hydraulic Parameters for the Modeled Soils . . . . . . . . . . . . . . . A-11

Table A.7 Moisture Retention Parameters for the Modeled WP Materials . A-13

Table A.8 Cumulative Frequency Distribution of Infiltration Rate for

Composite-Lined LFs and WPs . . . . . . . . . . . . . . . . . . . . . . . . . A-17

Table A.9 Cumulative Frequency Distribution of Leak Density for

Composite-Lined SIs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-19

Table A.10 Cumulative Frequency Distribution of Infiltration Rate for

Composite-Lined SIs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-19

Table A.11 HELP-derived Landfill Infiltration Rates . . . . . . . . . . . . . . . . . . . A-19

Table A.12 HELP-derived Waste Pile Infiltration Rates . . . . . . . . . . . . . . . . A-23

Table A.13 HELP-derived Land Application Unit Infiltration Rates . . . . . . . . A-27

Table A.14 HELP-derived Regional Recharge Rates . . . . . . . . . . . . . . . . . . A-30
This page intentionally left blank.
A-1

APPENDIX A

DETERMINATION OF INFILTRATION AND RECHARGE RATES

A.1 INFILTRATION AND RECHARGE RATES

EPACMTP requires the input of the rate of downward percolation of water

and leachate through the unsaturated zone to the water table. The model

distinguishes between two types of percolation as infiltration and recharge:

 Infiltration (WMU leakage rate) is defined as water percolating

through the WMU – including a liner if present – to the underlying soil.

 Recharge is water percolating through the soil to the aquifer outside

the WMU.

Infiltration is one of the key parameters affecting the leaching of waste

constituents into the subsurface. For a given leachate concentration, the mass of

constituents leached is directly proportional to the infiltration rate. In EPACMTP,

using a different default liner scenario changes the modeled infiltration rate; more

protective liner designs reduce leaching by decreasing the rate of infiltration.

In contrast, recharge introduces pristine water into the aquifer. Increasing

recharge therefore tends to result in a greater degree of plume dilution and lower

constituent concentrations. High recharge rates may also affect the extent of

ground-water mounding and ground-water velocity. The recharge rate is

independent of the type and design of the WMU; rather it is a function of the climatic

and hydrogeological conditions at the WMU location, such as precipitation,

evapotranspiration, surface run-off, and regional soil type.

In developing the EPACMTP model and the accompanying databases, the

U.S. EPA used several methodologies to estimate infiltration and recharge. We

used the HELP model (Schroeder et al, 1994) to compute recharge rates for all

units, as well as infiltration rates for LAUs, and for LFs and WPs with no-liner and

single-liner designs. For LFs and WPs, composite liner infiltration rates were

compiled from leak-detection-system flow rates reported for actual composite-lined

waste units (TetraTech, 2001).

For unlined and single-lined SIs, infiltration through the bottom of the

impoundment is calculated internally by EPACMTP, as described in Section 4.3.4 of

this document. For composite-lined SIs, we used the Bonaparte (1989) equation to

calculate the infiltration rate assuming circular (pin-hole) leaks with a uniform leak

size of 6 mm2

, and using the distribution of leak densities (number of leaks per

hectare) assembled from the survey of composite-lined units (TetraTech, 2001).

Tables A.1 through A.4 summarize the liner assumptions and infiltration rate

calculations for LFs, WPs, SIs, and LAUs. The remainder of this appendix provides

background on how we used the HELP model in conjunction with data from climate

stations across the United States to develop nationwide recharge and infiltration rate
Appendix A Determination of Infiltration and Recharge Rates

A-2

distributions and provides a detailed discussion of how we developed infiltration

rates for different default liner designs for each type of WMU.

A.1.1 USING THE HELP MODEL TO DEVELOP RECHARGE AND

INFILTRATION RATES

The HELP model is a quasi-two-dimensional hydrologic model for computing

water balances of LFs, cover systems, and other solid waste management facilities.

The primary purpose of the model is to assist in the comparison of design

alternatives. The HELP model uses weather, soil and design data to compute a

water balance for LF systems accounting for the effects of surface storage,

snowmelt, runoff, infiltration, evapotranspiration, vegetative growth, soil moisture

storage, lateral subsurface drainage, leachate recirculation, unsaturated vertical

drainage, and leakage through soil, geomembrane or composite liners. The HELP

model can simulate LF systems consisting of various combinations of vegetation,

cover soils, waste cells, lateral drain layers, low permeability barrier soils, and

synthetic geomembrane liners.

HELP Versions 3.03 and 3.07 (which include WMU- and liner-specific

distributions of infiltration rates) were used to construct the EPACMTP site data files.

We started with an existing database of no-liner infiltration rates for LFs, WPs and

LAUs. Also existing were recharge rates for 97 climate stations in the lower 48

contiguous United States (ABB, 1995), that are representative of 25 specific climatic

regions (developed with HELP version 3.03). We then added five climate stations

(located in Alaska, Hawaii, and Puerto Rico) to ensure coverage throughout all of the

United States. Figure A.1 shows the locations of the 102 climate stations.

The current version of HELP (version 3.07) was used for the modeling of the

additional climate stations for the no-liner scenario. We compared the results of

Version 3.07 against Version 3.03 and found that the differences in calculated

infiltration rates were insignificant. We also used this comparison to verify a number

of counter-intuitive infiltration rates that were generated with HELP Version 3.03.

We had observed that for some climate stations located in areas of the country with

low precipitation rates, the net infiltration for unlined LFs did not always correlate

with the relative permeability of the LF cover. We found some cases in which a less

permeable cover resulted in a higher modeled infiltration rate as compared to a more

permeable cover. Examples can be seen in the detailed listing of infiltration data

that are presented in Tables A.11 to A.14. For instance, Table A.11 shows that for a

number of climate stations, including Albuquerque, Denver, and Las Vegas, the

modeled infiltration rate for LFs with a silty clay loam (SCL) cover is higher than the

values corresponding to silt loam (SLT) and sandy loam (SNL) soil covers. We

determined that in all these cases, the HELP modeling results for unlined LFs were

correct and could be explained in terms of other water balance components,

including surface run-off and evapotranspiration.
Appendix A Determination of Infiltration and Recharge Rates

A-3

Table A.1 Methodology Used to Compute Infiltration for LFs

No Liner Single Liner Composite Liner

Method HELP model

simulations to compute

an empirical distribution

of infiltration rates for a

2 ft. thick cover of three

native soil cover types

using nationwide

coverage of climate

stations. Soil-type

specific infiltration rates

for a specific site are

assigned by using the

infiltration rates for

respective soil types at

the nearest climate

station.

HELP model

simulations to compute

an empirical

distribution of infiltration

rates through a single

clay liner using

nationwide coverage of

climate stations.

Infiltration rates for a

specific site were

obtained by using the

infiltration rate for the

nearest climate station.

Compiled from

literature sources

(TetraTech, 2001) for

composite liners

Final Cover Monte Carlo selection

from distribution of soil

cover types. 2 ft thick

native soil (1 of 3 soil

types: silty clay loam,

silt loam, and sandy

loam) with a range of

mean hydraulic

conductivities (4.2×10

-5

cm/s to 7.2×10

-4

cm/s).

3 ft thick clay cover with

a hydraulic conductivity

of 1×10

-7

cm/sec and a

10 ft thick waste layer.

On top of the cover, a 1

ft layer of loam to

support vegetation and

drainage and a 1 ft

percolation layer.

No cover modeled; the

composite liner is the

limiting factor in

determining infiltration

Liner

Design

No liner 3 ft thick clay liner with

a hydraulic conductivity

of 1×10

-7

cm/sec. No

leachate collection

system. Assumes

constant infiltration rate

(assumes no increase

in hydraulic conductivity

of liner) over modeling

period.

60 mil HDPE layer with

either an underlying

geosynthetic clay liner

with maximum

hydraulic conductivity of

5×10

-9

cm/sec, or a 3-

foot compacted clay

liner with maximum

hydraulic conductivity of

1×10

-7

cm/sec.

Assumes same

infiltration rate (i.e., no

increase in hydraulic

conductivity of liner)

over modeling period.

EPACMTP

Infiltration

Rate

Monte Carlo selection

from HELP generated

location- specific

values.

Monte Carlo selection

from HELP generated

location-specific

values.

Monte Carlo selection

from distribution of leak

detection system flow

rates.
Appendix A Determination of Infiltration and Recharge Rates

A-4

Table A.2 Methodology Used to Compute Infiltration for SIs

No Liner Single Liner Composite Liner

Method EPACMTP SI module

for infiltration through

consolidated sludge

and native soil layers

with a unit-specific

ponding depth from

EPA’s SI Study (EPA,

2001).

EPACMTP module for

infiltration through a

layer of consolidated

sludge and a single

clay liner with unitspecific ponding depth

from EPA’s SI study.

Bonaparte equation

(1989) for pin-hole

leaks using distribution

of leak densities for

units installed with

formal CQA programs

Ponding

Depth

Unit-specific based on

EPA’s SI study.

Unit-specific based on

EPA’s SI study.

Unit-specific based on

EPA’s SI study.

Liner

Design

None. However,

barrier to infiltration is

provided by

layer of consolidated

sludge at the bottom of

the impoundment, and

a layer of clogged

native soil below the

consolidated sludge.

The sludge thickness is

assumed to be

constant over the

modeling period. The

hydraulic conductivity of

the consolidated sludge

is between 1.3×10

-7

and

1.8×10

-7

cm/sec. The

hydraulic conductivity of

the clogged native

material is assumed to

be 0.1 of the unaffected

native material in the

vadose zone.

3 ft thick clay liner with

a hydraulic conductivity

of 1×10

-7

cm/sec. No

leachate collection

system. Assumes no

increase in hydraulic

conductivity of liner

over modeling period.

Additional barrier is

provided by a layer of

consolidated sludge at

the bottom of the

impoundment, see noliner column.

60 mil HDPE layer with

either an underlying

geosynthetic clay liner

with maximum

hydraulic conductivity of

5×10

-9

cm/sec, or a 3-

foot compacted clay

liner with maximum

hydraulic conductivity of

1×10

-7

cm/sec.

Assumptions: 1)

constant infiltration rate

(i.e., no increase in

hydraulic conductivity of

liner) over modeling

period;

2) geomembrane liner

is limiting factor that

determines infiltration

rate.

EPACMTP

Infiltration

Rate

Calculated by

EPACMTP based on

Monte Carlo selection

of unit-specific ponding

depth.

Calculated based on

Monte Carlo selection

of unit-specific ponding

depth

Calculated based on

Monte Carlo selection

of unit-specific ponding

depth and distribution

of leak densities
Appendix A Determination of Infiltration and Recharge Rates

A-5

Table A.3 Methodology Used to Compute Infiltration for WPs

No Liner Single Liner Composite Liner

Method HELP model

simulations to compute

distribution of infiltration

rates for a 10 ft. thick

layer of waste, using

three waste

permeabilities (copper

slag, coal bottom ash,

coal fly ash) and

nationwide coverage of

climate stations.

Waste-type-specific

infiltration rates for a

specific site are

obtained by using the

infiltration rates for

respective waste types

at the nearest climate

station.

HELP model

simulations to compute

distribution of infiltration

rates through 10 ft.

waste layer using three

waste permeabilities

and nationwide

coverage of climate

stations. Infiltration

rates for a specific site

were obtained by using

the infiltration rate for

the nearest climate

station.

Compiled from

literature sources

(TetraTech, 2001) for

composite liners

Cover None None None

Liner

Design

No liner. 3 ft thick clay liner with

a hydraulic conductivity

of 1×10

-7

cm/sec, no

leachate collection

system, and a 10 ft

thick waste layer.

Assumes no increase

in hydraulic conductivity

of liner over unit’s

operational life.

60 mil HDPE layer with

either an underlying

geosynthetic clay liner

with maximum

hydraulic conductivity of

5×10

-9

cm/sec, or a 3-

foot compacted clay

liner with maximum

hydraulic conductivity of

1×10

-7

cm/sec.

1) same infiltration

rate (i.e., no increase in

hydraulic conductivity of

liner) over unit’s

operational life;

2) geomembrane is

limiting factor in

determining infiltration

rate.

EPACMTP

Infiltration

Rate

Monte Carlo selection

from HELP generated

location-specific

values.

Monte Carlo selection

from HELP generated

location- specific

values.

Monte Carlo selection

from distribution of leak

detection system flow

rates
Appendix A Determination of Infiltration and Recharge Rates

A-6

Table A.4 Methodology Used to Compute Infiltration for LAUs

No Liner Single Liner Composite Liner

Method HELP model

simulations to compute

an empirical

distribution of

infiltration rates for a

0.5 ft thick sludge

layer, underlain by a 3

ft layer of three types

of native soil using

nationwide coverage of

climate stations. Soiltype specific infiltration

rates for a specific site

are assigned by using

the infiltration rates for

respective soil types at

the nearest climate

station.

N/A N/A

Liner

Design

No liner N/A N/A

EPACMTP

Infiltration

Rate

Monte Carlo selection

from HELP generated

location specific

values.

N/A N/A
A

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Seattle

GreatFalls

Bismarck

Pullman

Yakima Astoria

St.Cloud

Portland

Burlington

RapidCity

Rutland

Boise

Madison

Syracuse

Pocatello

Schenectady

Ithaca Medford

Chicago

DesMoines

Cleveland 

Cheyenne GrandIsland SaltLakeCity 

C 

olumbus Indianapolis

Denver

Cincinnati

GrandJunction Topeka Columbia

Sacramento

DodgeCity

CedarCity

Lynchburg

Glasgow

No

Fresno

LasVegas

Tulsa

Greensboro

Knoxville

OklahomaCity Flagstaff Albuquerque LittleRock LosAngeles Atlanta

SanDiego Phoenix

Dallas

Charlesto

Tucson Shreveport

Midland El Paso TallahasseeJacksonville

LakeCharles NewOrleans

SanAntonio

Orlando

Tampa

Brownsville

Miam

Ely

Lander

NorthOmaha

Plainef

Put-In-Bay

Watkinsville

SaultSte.Marie

EastLansing

Pittsburgh

EastSt.Louis

SantaMaria

West

Nashville-Davidson

#

#

#

Fairbanks

Annette

Bethel

#Honolulu

#

SanJuan

Alaska Hawaii PuertoRico

Figure A.1 Locations of HELP Climate Stations
Appendix A Determination of Infiltration and Recharge Rates

A-8

The first 97 climate stations were grouped into 25 climate regions based on

ranges of average annual precipitation and pan evaporation, as shown in Table A.5.

For each modeled climate station, HELP provides a database of five years of

climatic data. We used this climatic data, along with data on the regional soil type

and WMU design characteristics, to calculate a water balance for each applicable

default liner design as a function of the amount of precipitation that reaches the top

surface of the unit, minus the amount of runoff and evapotranspiration. The HELP

model then computed the net amount of water that infiltrates through the surface,

waste, and liner layers, based on the initial moisture content and the hydraulic

conductivity of each layer.

In addition to climate factors and liner designs, the infiltration rates calculated

by HELP are affected by LF cover design, permeability of the waste material in WP,

and LAU soil type. For every climate station and WMU type (LF, WP and LAU), we

calculated three HELP infiltration rates. For a selected WMU type and liner design,

the regional site-based modeling process selects randomly from among the HELPderived infiltration and recharge data, to capture both the nationwide variation in

climate conditions, as well as variations in LF soil cover type, WP waste

permeability, and LAU soil type.

The factors related to soil type that affect the HELP-generated infiltration and

recharge rates are the permeability of the soil used in the LF cover, and – in the

case of recharge or for LAUs – the permeability of the soil type in the vicinity of the

WMU. We used the same set of soil types (sandy loam, silty loam, and silty clay

loam) and soil properties in the infiltration and recharge rate calculations as we did in

the unsaturated zone fate and transport simulations (see Table 5.4 in Section 5.2.4).

In the case of uncovered WPs we found that the infiltration rates predicted by

the HELP model are sensitive to the permeability of the waste material itself. Based

on these results, we simulated WP infiltration rates for three different WP materials:

relatively high permeability, moderate permeability, and relatively low permeability.

When these rates are used in the EPACMTP modeling, each waste type has an

equal likelihood of occurrence.
Appendix A Determination of Infiltration and Recharge Rates

A-9

Table A.5 Grouping of Climate Stations by Average Annual Precipitation

and Pan Evaporation (ABB, 1995)

   

	      
 

   

	      
 

     
 

 

    
  
 

 

     
 

 

    
  
 

 

Boise ID < 16 < 30 Columbia MO 32 - 40 30 - 40

Fresno CA Put-in-Bay OH

Madison WI

Bismarck ND < 16 30 - 40 Columbus OH

Denver CO Cleveland OH

Grand

Junction

CO Des Moines IA

Pocatello ID E. St. Louis IL

Glasgow MT

Pullman WA Topeka KS 32 - 40 40 - 50

Yakima WA

Cheyenne WY Tampa FL 32 - 40 50 - 60

Lander WY San Antonio TX

Rapid City SD < 16 40 - 50 Portland ME 40 - 48 < 30

Los Angeles CA Hartford CT

Sacramento CA Syracuse NY

San Diego CA Worchester MA

Santa Maria CA Augusta ME

Ely NV Providence RI

Cedar City UT Nashua NH

Ithaca NY

Albuquerque NM < 16 50 - 60 Boston MA

Schenectady NY

Las Vegas NV < 16 > 60

Phoenix AZ NY City NY 40 - 48 30 - 40

Tucson AZ Lynchburg VA

El Paso TX Philadelphia PA

Seabrook NJ

Medford OR 16 - 24 30 - 40 Indianapolis IN

Great Falls MT Cincinnati OH

Salt Lake City UT Bridgeport CT

Grand Island NE 16 - 24 40 - 50 Jacksonville FL 40 - 48 40 - 50

Orlando FL
Table A.5 Grouping of Climate Stations by Average Annual Precipitation

and Pan Evaporation (ABB, 1995) (continued)

Appendix A Determination of Infiltration and Recharge Rates

   

	      
 

   

	      
 

     
 

 

    
  
 

 

     
 

 

    
  
 

 

A-10

Flagstaff AZ 16 - 24 50 - 60 Greensboro NC

Watkinsville GA

Dodge City KS 16 - 24 > 60 Norfolk VA

Midland TX Shreveport LA

St. Cloud MN 24 - 32 < 30 Astoria OR > 48 < 30

New Haven CT

E. Lansing MI 24 - 32 30 - 40 Plainfield MA

North Omaha NE 24 - 32 40 - 50 Nashville TN > 48 30 - 40

Knoxville TN

Dallas TX 24 - 32 50 - 60 Central Park NY

Tulsa OK Lexington KY

Brownsville TX Edison NJ

Oklahoma City OK 24 - 32 >60 Atlanta GA > 48 40 - 50

Little Rock AK

Bangor ME 32 - 40 < 30 Tallahassee FL

Concord NH New Orleans LA

Pittsburgh PA Charleston SC

Portland OR W. Palm

Beach

FL

Caribou ME

Chicago IL Lake Charles LA > 48 50 - 60

Burlington VT Miami FL

Rutland VT

Seattle WA

Montpelier VT

Sault St. Marie MI
Appendix A Determination of Infiltration and Recharge Rates

A-11

A.1.2 INFILTRATION RATES FOR UNLINED UNITS

Landfill

We used the HELP model to simulate infiltration through closed LFs for each

of the 102 climate station locations shown in Figure A.1. A 2-foot cover was

included as the minimum Subtitle D requirement. Three different soil cover types

were modeled: sandy loam, silty loam, and silty clay loam soils. Table A.6 presents

the hydraulic parameters for these three soil types.

Table A.6 Hydraulic Parameters for the Modeled Soils

Soil Type

HELP

Soil

Number

Total

Porosity

(vol/vol)

Field

Capacity

(vol/vol)

Wilting

Point

(vol/vol)

Saturated

Hydraulic

Conductivity

(cm/sec)

Sandy Loam 6 0.453 0.190 0.085 0.000720

Silt Loam 9 0.501 0.284 0.135 0.000190

Silty Clay

Loam

12 0.471 0.342 0.210 0.000042

Other LF design criteria included:

 A cover crop of “fair” grass — this is the quality of grass cover

suggested by the HELP model for LFs where limitations to root zone

penetration and poor irrigation techniques may limit grass quality.

 The evaporation zone thickness selected for each location was

generally the depth suggested by the model for that location for a fair

grass crop; however, the evaporation zone thickness was not allowed

to exceed the soil thickness (24 inches).

 The leaf area index (LAI) selected for each location was that of fair

grass (2.0) unless the model indicated a lower maximum for that

location.

 The LF configuration was based on a one-acre facility with a 2% top

slope and a drainage length of 200 feet (one side of a square acre).

Runoff was assumed to be possible from 100% of the cover.

Table A.11 presents the LF infiltration rate data for the 102 climate stations.

For all four WMU types, the unlined LF infiltration rate for each soil type at each of

the 102 climate centers was used as the ambient regional recharge rate for that

climatic center and soil type.
Appendix A Determination of Infiltration and Recharge Rates

A-12

Surface Impoundment

We calculated SI infiltration rates using the built-in SI module in EPACMTP

(see Section 4.3.4 of this document and Section 2.2.2.3 of the EPACMTP Technical

Background Document (U.S. EPA, 2003a)). This means that for EPACMTP, the SI

infiltration rate is not really an input parameter, rather the model calculates infiltration

rates “on the fly” during the simulation, as a function of impoundment ponding depth

and other SI characteristics. For unlined SIs, the primary parameters that control

the infiltration rate are the ponding depth in the impoundment, the thickness and

permeability of any accumulated sediment layer at the base of the impoundment,

and the presence of a ‘clogged’ (i.e., reduced permeability) layer of native soil

underneath the impoundment caused by the migration of solids from the

impoundment. In addition, EPACMTP checks that the calculated infiltration rate

does not result in an unrealistic degree of ground-water mounding (see Section

2.2.5 of the EPACMTP Technical Background Document (U.S. EPA, 2003a)).

To create the SI site data file for use with EPACMTP, we used unit-specific

data on SI ponding depths from EPA’s Surface Impoundment Study (U.S. EPA,

2001). We assumed a fixed sediment layer thickness of 20 cm at the base of the

impoundment. The resulting sediment layer permeability has a relatively narrow

range of variation between 1.26×10

-7 and 1.77×10-7

cm/s. We assumed that the

depth of clogging underneath the impoundment was 0.5 m in all cases, and that

saturated hydraulic conductivity of the clogged layer is 10% of that of the native soil

underlying the impoundment.

In the event that the SI is reported to have its base below the water table, we

calculated the infiltration using Darcy’s law based on the hydraulic gradient across

the bottom of the impoundment unit, and the hydraulic conductivity of the

consolidated sediment at the bottom of the impoundment unit.

Waste Pile

For the purpose of estimating leaching rates, we considered WPs to be

similar to non-covered LFs with a total waste thickness of 10 feet. The infiltration

rates for unlined WPs were, therefore, generated with the HELP model using the

same general procedures as for LFs, but with the following modifications:

 No cover

We modeled the leachate flux through active, uncovered piles. We

modeled the WP surface as having no vegetation. The evaporative

zone depth was taken as the suggested HELP model value for the

“bare” condition at each climate center. The Leaf Area Index (LAI)

was set to zero to eliminate transpiration.

 Variable waste permeability

For uncovered WPs, we found that the infiltration rates predicted by

HELP model are sensitive to the permeability of the waste material

itself. Based on these results, we simulated WP infiltration rates for
Appendix A Determination of Infiltration and Recharge Rates

A-13

three different WP materials: relatively high permeability, moderate

permeability, and relatively low permeability (rather than three

different soil types as was done for the LF scenario). The HELP

model input parameters for the three waste types are presented in

Table A.7.

Table A.7 Moisture Retention Parameters for the Modeled WP Materials

Waste Type

HELP

Soil

Number

Total

Porosity

(vol/vol)

Field

Capacity

(vol/vol)

Wilting

Point

(vol/vol)

Saturated

Hydraulic

Conductivity

(cm/sec)

Low Permeability 30 0.541 0.187 0.047 0.00005

Moderate

Permeability

31 0.578 0.076 0.025 0.00410

High

Permeability

33 0.375 0.055 0.020 0.04100

We calculated WP infiltration rates for the 102 climate stations shown in

Figure A.1 and the three waste material permeabilities shown in Table A.7. Table

A.12 presents the resulting WP infiltration rate values for all climate stations and

waste types.

Land Application Unit

LAUs were modeled with HELP using two soil layers. The top layer was

taken as six inches in thickness and represented the layer into which the waste was

applied. The bottom layer was of the same material type as the top layer and was

set at a thickness of 36 inches. Both of these layers were modeled as vertical

percolation layers. The same three soil types for LFs were also used for LAUs (see

Table A.6).

We assumed the waste applied to the LAU to be a sludge-type material with

a high water content. We also assumed a waste application rate of 7.25 inches per

year (in/yr) with the waste having a solids content of 20% and a unit weight of 75

lb/ft

3

. Assuming that 100% of the water in the waste was available as free water, an

excess water amount of 5.8 in/yr, in addition to precipitation, would be available for

percolation. HELP model analyses showed that the additional water available for

percolation generally would have little effect on the simulated water balance and net

infiltration, except for sites located in arid regions of the United States with very little

natural precipitation. For more representative waste application rates, the effect

disappeared because introducing additional moisture in the simulated water balance

results in a commensurate increase in runoff and removal by evapotranspiration.

For this reason, the LAU infiltration rate for a given soil type is assumed to be the

same as the corresponding LF infiltration rate.
Appendix A Determination of Infiltration and Recharge Rates

A-14

We calculated LAU infiltration rates for the 102 climate stations shown in

Figure A.1 and the three soil types shown in Table A.6. Table A.13 presents the

resulting LAU infiltration rate values for all climate stations and soil types.

A.1.3 SINGLE-LINED WASTE UNITS

EPACMTP includes infiltration rates for single clay-lined LFs, WPs, and SIs.

In the case of LAUs, only unlined units are considered.

Landfill

We calculated infiltration rates for single-lined LFs using version 3.07 of the

HELP model. We modeled the LF as a four-layer system, consisting, from top to

bottom of:

 1-foot percolation cover layer;

 3-foot compacted clay cover with hydraulic conductivity of 1×10

-7

cm/s ;

 10-foot thick waste layer; and

 3-foot thick compacted clay liner with a hydraulic conductivity of 1×10

-7

cm/sec.

We simulated the cover layer as a loam drainage layer supporting a “fair”

cover crop with an evaporative zone depth equal to that associated with a fair cover

crop at the climate center. The remaining conditions were identical to those

described in Section A.1.2 for unlined LFs. Note that three different soil types were

not modeled, since the clay liner is the limiting factor affecting the infiltration rate, not

soil type. To avoid changing the standard format of the infiltration rates in the site

data file, the clay-lined LF infiltration rates are repeated in each of the three columns

that correspond to soil type in the case of unlined LFs. So in the course of a Monte

Carlo analysis using the regional site-based modeling methodology for a single-clay

lined LF, the soil type is correlated only to recharge rate.

In developing this default distribution of infiltration rates, we used the

grouping of climate stations into 25 regions of similar climatic conditions depicted in

Table A.5 in order to reduce the number of required HELP simulations. Rather than

calculating infiltration rates for each of the 102 individual climate stations, we

calculated infiltration rates for the 25 climate regions, and then assigned the same

value to each climate station in one group. To ensure a protective result, we chose

the climate center with the highest average precipitation in each climate region as

representative of that region. We calculated individual infiltration rates for each of

the five climate centers in Alaska, Hawaii, and Puerto Rico that were not assigned to

a climate region.

During the process of assembling the HELP infiltration values for the

EPACMTP model, we realized that the grouping of climate centers into regions for

clay-lined units resulted in a number of apparent anomalies in which the suggested

infiltration rate for a lined unit would be higher than the unlined infiltration rate at the

same climate station. This resulted from the fact that we used the infiltration rate for
Appendix A Determination of Infiltration and Recharge Rates

A-15

the climate center with the highest annual precipitation in each region for clay-lined

units, but then compared it with a location-specific infiltration value for unlined units.

The occurrence of these anomalies was restricted to climate stations in arid parts of

the United States, and was noticeable only when the absolute magnitude of

infiltration was low. In order to remove these counter-intuitive results, we recalculated location-specific HELP infiltration rates for clay-lined units at 17 climate

stations (Glasgow, MT; Yakima, WA; Lander, WY; Cheyenne, WY; Pullman, WA;

Pocatello, ID; Grand Junction, CO; Denver, CO; Great Falls, MT; Salt Lake City, UT;

Cedar City, UT; El Paso, TX; Ely, NV; Las Vegas, NV; Rapid City, SD; Phoenix, AZ;

and Tucson, AZ). We then incorporated the location-specific infiltration rates for

these 17 climate stations into the database of infiltration rates in the site data file, to

replace the original regional values. The result is that some of the infiltration rates

for the single-clay lined LF scenario are regional values and some are locationspecific values. Table A.11 shows the infiltration rate values for clay-lined LFs.

Waste Pile

We calculated infiltration rates for single-lined WPs using the HELP model.

We modeled the WP as a two-layer system, consisting, from top to bottom, of:

 10-foot thick, uncovered, waste layer; and

 3-foot thick compacted clay liner with a hydraulic conductivity of 1×10

-7

cm/sec.

Other parameters were set to the same values as in the unlined WP case,

including the three default waste material types (see Section A.1.2). We also

modeled a bare surface for the evaporative zone depth.

In developing the single-clay lined-WP infiltration rates, we used the same

grouping of climate stations in 25 climate regions as previously discussed for LFs.

We calculated individual infiltration rates for each of the five climate centers in

Alaska, Hawaii, and Puerto Rico that were not assigned to a climate region.

Analogous to the situation encountered for LFs, we found a number of

apparent anomalies between WP infiltration rates for unlined as compared to claylined WPs, resulting from the use of regional infiltration values for clay-lined units.

The occurrence of these anomalies for WPs was also restricted to climate centers in

arid parts of the United States, for which the absolute magnitude of infiltration was

low. In order to remove these counter-intuitive results, we re-calculated locationspecific HELP infiltration rates for clay-lined WP units at 17 climate stations

(Glasgow, MT; Yakima, WA; Lander, WY; Cheyenne, WY; Pullman, WA; Pocatello,

ID; Grand Junction, CO; Denver, CO; Great Falls, MT; Salt Lake City, UT; Cedar

City, UT; El Paso, TX; Ely, NV; Las Vegas, NV; Rapid City, SD; Phoenix, AZ; and

Tucson, AZ). We then incorporated the location-specific infiltration rates for these

17 climate stations into the database of infiltration rates in the site data file, to

replace the original regional values, and made them part of a distribution package

for EPACMTP version 2. The result is that some of the infiltration rates for the
Appendix A Determination of Infiltration and Recharge Rates

A-16

single-clay lined WP scenario are regional values and some are location-specific

values.

During the process of verifying the HELP-generated infiltration rates for claylined units, we also replaced incorrect values for clay-lined WPs assigned to the

Lake Charles, LA and Miami, FL climate stations. These two climate stations have

high precipitation (Table A.5), but were assigned low infiltration rates. So for these

two climate stations, we re-ran the HELP model for the clay-lined WP scenario for

each of the three waste permeability values.

Table A.12 shows these finalized infiltration rate values for clay-lined WPs.

Surface Impoundment

For single-lined SIs, infiltration rates were calculated inside of EPACMTP in

the same manner as described in the Section A.1.2 for unlined units, with the

exception that we added a 3-foot compacted clay liner with a hydraulic conductivity

of 1×10

-7

cm/s at the bottom of the WMU, and we did not include the effect of

clogged native material due to the filtering effects of the liner.

A.1.4 INFILTRATION RATES FOR COMPOSITE-LINED UNITS

We conducted an information collection effort that involved searching the

available literature for data that quantify liner integrity and leachate infiltration

through composite liners (TetraTech, 2001). We then assembled these data and

applied them to develop the following methodologies for modeling infiltration from

composite-lined units:

Landfill and Waste Pile

We treated composite-lined LFs and WPs as being the same for the purpose

of determining infiltration rates. For these WMU’s, we developed an infiltration rate

distribution from actual leak detection system (LDS) flow rates reported for clay

composite-lined LF cells, and incorporated them into an EPACMTP input file.

We based the distribution of composite-lined LF and WP infiltration rates on

available monthly average LDS flow rates from 27 LF cells reported by TetraTech

(2001). The data and additional detail for the 27 LF cells are provided in Appendix

D, Table D.5 of the IWEM Technical Background Document (U.S. EPA, 2003c). The

data included monthly average LDS flow rates for 22 operating LF cells and 5 closed

LF cells. The 27 LF cells are located in eastern United States: 23 in the

northeastern region, 1 in the mid-Atlantic region, and 3 in the southeastern region.

Each of the LF cells is underlain by a geomembrane/geosynthetic clay liner which

consists of a geomembrane of thickness between 1 and 1.5 mm (with the majority,

22 of 27, being 1.5 mm thick), overlying a geosynthetic clay layer of reported

thickness of 6 mm. The geomembrane is a flexible membrane layer made from

HDPE. The geosynthetic clay liner is a composite barrier consisting of two
Appendix A Determination of Infiltration and Recharge Rates

A-17

(A.1)

geotextile outer layers with a uniform core of bentonite clay to form a hydraulic

barrier. The liner system is underlain by a LDS.

We decided in this case to use a subset of the reported flow rates compiled

by TetraTech (2001) in developing the composite liner infiltration rates for

EPACMTP. We did not include LDS flow rates for geomembrane/compacted clay

composite-lined LF cells in our distribution. For compacted clay liners (including

composite geomembrane/ compacted clay liners), there is the potential for water to

be released during the consolidation of the clay liner and yield an unknown

contribution of water to LDS flow, such that it is very difficult to determine how much

of the LDS flow is due to liner leakage, versus how much is due to clay

consolidation. We also decided in this case to not use LDS flow rates from three

geomembrane/geosynthetic clay lined-cells. For one cell, flow rate data were

available for the cell’s operating period and the cell’s post-closure period. The

average flow rate for the cell was 26 liters/hectare/day when the cell was operating

and 59 liters/hectare/day when the cell was closed. We believe these flow rates,

which were among the highest reported, are difficult to interpret because the flow

rate from the closed cell was over twice the flow rate from the open cell, a pattern

inconsistent with the other open cell/closed cell data pairs we reviewed. For the two

other cells, additional verification of the data may be needed in order to fully

understand the reported flow rates.

The resulting cumulative probability distribution of infiltration rates for

composite-lined LFs and WPs for use in this application is based on the 27

remaining data points is presented in Table A.8. Note that over 50% of the values

are zero; that is, they have no measurable infiltration.

Table A.8 Cumulative Frequency Distribution of Infiltration Rate for

Composite-Lined LFs and WPs

Percentile 0 10 25 50 75 90 100

Infiltration Rate (m/yr) 0.0 0.0 0.0 0.0 7.30×10

-5

1.78×10

-4

4.01×10

-4

Surface Impoundment

For the surface impoundment scenario, the EPACMTP model derives a value

for leakage through circular defects (pin holes) in a composite liner using the

following equation developed by Bonaparte et al. (1989):

where:

Q = steady-state rate of leakage through a single hole in the liner (m3

/s)

a = area of hole in the geomembrane (m2)

h = head of liquid on top of geomembrane (m)
Appendix A Determination of Infiltration and Recharge Rates

A-18

Ks = hydraulic conductivity of the low-permeability soil underlying the

geomembrane (m/s)

This equation is applicable to cases where there is good contact between the

geomembrane and the underlying compacted clay liner. In the course of a Monte

Carlo analysis using the regional site-based modeling methodology, the EPACMTP

model derives the infiltration rate for each SI unit in the nationwide database

included in the site data file using the above equation. This methodology uses the

unit-specific ponding depth data (corresponding to h in the above equation) from the

recent Surface Impoundment Study (U.S. EPA, 2001) in combination with a

distribution of leak densities (expressed as number of leaks per hectare) compiled

from 26 leak density values reported in TetraTech (2001). The leak densities are

based on liners installed with formal Construction Quality Assurance (CQA)

programs.

The 26 sites with leak density data are mostly located outside the United

States: 3 in Canada, 7 in France, 14 in United Kingdom, and 2 with unknown

locations. The WMUs at these sites (8 LFs, 4 SIs, and 14 unknown) are underlain

by a layer of geomembrane of thickness varying from 1.14 to 3 mm. The majority of

the geomembranes are made from HDPE (23 of 26) with the remaining 3 made from

prefabricated bituminous geomembrane or polypropylene. One of the sites has a

layer of compacted clay liner beneath the geomembrane, however, for the majority

of the sites (25 of 26) material types below the geomembrane layer are not reported.

The leak density data above were used for SIs. The leak density distribution is

shown in Table A.9. Table D.6, Appendix D of the IWEM Technical Background

Document (U.S. EPA, 2003c) provides additional detail.

To use the Bonaparte equation, the EPACMTP model assumes a uniform

leak size of 6 millimeters squared (mm2

). This leak size is the middle of a range of

hole sizes reported by Rollin et al. (1999), who found that 25 percent of holes were

less than 2 mm2, 50 percent of holes were 2 to 10 mm2, and 25 percent of holes

were greater than 10 mm2. Additionally, the model assumes that the geomembrane

is underlain by a compacted clay liner whose hydraulic conductivity is 1×10

-7

cm/s.

In order to ascertain the plausibility of the leak density data, we conducted an

infiltration rate calculation to estimate the range of infiltration resulting from the leaks

in geomembrane. Because of the absence of documented infiltration data for SIs,

for comparison purposes we used the infiltration data for LFs, described previously

under the LF and WP sections, as a surrogate infiltration data set. Because the

comparison was made on the basis of LF data, we set the head of liquid above the

geomembrane to 0.3 m (1 foot) which is a typical maximum design head for LFs.

Calculation results are shown in Table D.6, Appendix D of the IWEM Technical

Background Document (U.S. EPA, 2003c). These results indicate that the

calculated leakage rates, based on the assumptions of above-geomembrane head,

hole dimension, hydraulic conductivity of the barrier underneath the geomembrane,

and good contact between the geomembrane and the barrier, agree favorably with

the observed LF flow rates reported in Table D.5, Appendix D of the IWEM

Technical Background Document (U.S. EPA, 2003c). This result provided
Appendix A Determination of Infiltration and Recharge Rates

A-19

confidence that the leak density data could be used as a reasonable basis for

calculating infiltration rates using actual SI ponding depths. The empirical

distribution of composite-lined infiltration rates for SIs is part of the EPACMTP input

file, if example input files for the composite-lined scenario are to be included in a

distribution package.

In order to use these data in EPACMTP, the user is required to specify the

unit’s ponding depth. EPACMTP will then determine the unit’s infiltration distribution

using the Bonaparte equation and the leak density distribution in Table A.9. The

resulting frequency distribution of calculated infiltration rates for composite-lined SIs

that are generated using the standard regional site-based modeling methodology is

presented in Table A.10.

Table A.9 Cumulative Frequency Distribution of Leak Density for CompositeLined SIs

Percentile 0 10 20 30 40 50 60 70 80 90 100

Leak density

(No. Leaks/ha)

0 0 0 0 0.7 0.915 1.36 2.65 4.02 4.77 12.5

Table A.10 Cumulative Frequency Distribution of Infiltration Rate for

Composite-Lined SIs

Percentile 0 10 25 50 75 90 100

Infiltration Rate

(m/yr)

0.0 0.0 0.0 1.34×10

-5

1.34×10

-4

3.08×10

-4

4.01×10

-3

Table A.11 HELP-Derived Landfill Infiltration Rates

Climate

Center

Index

Climate Center

No Liner Infiltration Rate

(m/yr)

Single Clay Liner Infiltration

Rate (m/yr)

City State

Silt

Loam

Sandy

Loam

Silty

Clay

Silt

Loam

Sandy

Loam

Silty

Clay

1 Fresno CA 0.0307 0.0368 0.0381 0.0046 0.0046 0.0046

2 Boise ID 0.0008 0.0094 0.0038 0.0046 0.0046 0.0046

3 Denver CO 0.0008 0.0008 0.0036 0.0000 0.0000 0.0000

4

Grand

Junction CO 0.0000 0.0000 0.0003 0.0000 0.0000 0.0000

5 Pocatello ID 0.0000 0.0000 0.0000 0.0006 0.0006 0.0006

6 Glasgow MT 0.0099 0.0074 0.0099 0.0001 0.0001 0.0001

7 Bismarck ND 0.0239 0.0300 0.0196 0.0188 0.0188 0.0188

8 Pullman WA 0.0069 0.0132 0.0084 0.0002 0.0002 0.0002

9 Yakima WA 0.0000 0.0023 0.0003 0.0001 0.0001 0.0001
Appendix A Determination of Infiltration and Recharge Rates

Climate

Center

Index

Climate Center

No Liner Infiltration Rate

(m/yr)

Single Clay Liner Infiltration

Rate (m/yr)

City State

Silt

Loam

Sandy

Loam

Silty

Clay

Silt

Loam

Sandy

Loam

Silty

Clay

A-20

10 Cheyenne WY 0.0005 0.0013 0.0086 0.0000 0.0000 0.0000

11 Lander WY 0.0033 0.0053 0.0094 0.0001 0.0001 0.0001

12  	 CA 0.0787 0.0950 0.0699 0.0013 0.0013 0.0013

13 Sacramento CA 0.1024 0.0876 0.0945 0.0013 0.0013 0.0013

14 San Diego CA 0.0221 0.0340 0.0241 0.0013 0.0013 0.0013

15 Santa Maria CA 0.0947 0.1151 0.0841 0.0013 0.0013 0.0013

16 Ely NV 0.0000 0.0000 0.0003 0.0000 0.0000 0.0000

17 Rapid City SD 0.0005 0.0071 0.0033 0.0001 0.0001 0.0001

18 Cedar City UT 0.0000 0.0008 0.0000 0.0001 0.0001 0.0001

19 	
    
   NM 0.0000 0.0000 0.0003 0.0000 0.0000 0.0000

20 Las Vegas NV 0.0000 0.0000 0.0018 0.0001 0.0001 0.0001

21 Phoenix AZ 0.0000 0.0003 0.0003 0.0000 0.0000 0.0000

22 Tucson AZ 0.0000 0.0003 0.0005 0.0000 0.0000 0.0000

23 El Paso TX 0.0076 0.0130 0.0081 0.0001 0.0001 0.0001

24 Medford OR 0.2073 0.2309 0.2096 0.0432 0.0432 0.0432

25 Great Falls MT 0.0036 0.0069 0.0074 0.0001 0.0001 0.0001

26

Salt Lake

City UT 0.0130 0.0269 0.0185 0.0005 0.0005 0.0005

27

Grand

Island NE 0.0442 0.0627 0.0323 0.0196 0.0196 0.0196

28 Flagstaff AZ 0.0239 0.0630 0.0226 0.0241 0.0241 0.0241

29 Dodge City KS 0.0135 0.0345 0.0226 0.0094 0.0094 0.0094

30 Midland TX 0.0180 0.0254 0.0135 0.0094 0.0094 0.0094

31 St. Cloud MN 0.0602 0.0831 0.0554 0.0342 0.0342 0.0342

32 E. Lansing MI 0.1090 0.1452 0.1102 0.0374 0.0374 0.0374

33  
      NE 0.0671 0.0795 0.0536 0.0291 0.0291 0.0291

34 Tulsa OK 0.0686 0.1006 0.0465 0.0241 0.0241 0.0241

35 Brownsville TX 0.0549 0.1049 0.0384 0.0241 0.0241 0.0241

36 Dallas TX 0.0599 0.1067 0.0531 0.0241 0.0241 0.0241

37

Oklahoma

City OK 0.0612 0.0942 0.0389 0.0246 0.0246 0.0246

38 Concord NH 0.1585 0.2057 0.1372 0.0432 0.0432 0.0432

39 Pittsburgh PA 0.0894 0.1313 0.0792 0.0432 0.0432 0.0432

40 Portland OR 0.4171 0.4387 0.3927 0.0432 0.0432 0.0432

41 Caribou ME 0.1082 0.1491 0.0886 0.0432 0.0432 0.0432
Appendix A Determination of Infiltration and Recharge Rates

Climate

Center

Index

Climate Center

No Liner Infiltration Rate

(m/yr)

Single Clay Liner Infiltration

Rate (m/yr)

City State

Silt

Loam

Sandy

Loam

Silty

Clay

Silt

Loam

Sandy

Loam

Silty

Clay

A-21

42 Chicago IL 0.0798 0.1138 0.0620 0.0432 0.0432 0.0432

43 Burlington VT 0.1359 0.1781 0.1166 0.0432 0.0432 0.0432

44 Bangor ME 0.1471 0.2045 0.1227 0.0432 0.0432 0.0432

45 Rutland VT 0.1212 0.1598 0.1008 0.0432 0.0432 0.0432

46 Seattle WA 0.4384 0.4582 0.4077 0.0432 0.0432 0.0432

47 Montpelier VT 0.1062 0.1483 0.0879 0.0432 0.0432 0.0432

48

Sault St.

Marie MI 0.1651 0.2101 0.1435 0.0432 0.0432 0.0432

49 Put-in-Bay OH 0.0508 0.1003 0.0495 0.0409 0.0409 0.0409

50 Madison WI 0.0912 0.1400 0.0686 0.0409 0.0409 0.0409

51 Columbus OH 0.0765 0.1158 0.0663 0.0409 0.0409 0.0409

52 Cleveland OH 0.0780 0.1212 0.0823 0.0409 0.0409 0.0409

53 Des Moines IA 0.1143 0.1641 0.1156 0.0409 0.0409 0.0409

54 E. St. Louis IL 0.1435 0.1676 0.0704 0.0409 0.0409 0.0409

55 Columbia MO 0.1529 0.1989 0.1224 0.0409 0.0409 0.0409

56 Topeka KS 0.1049 0.1483 0.0762 0.0350 0.0350 0.0350

57 Tampa FL 0.0658 0.1031 0.0475 0.0253 0.0253 0.0253

58

San

Antonio TX 0.1095 0.1646 0.0820 0.0253 0.0253 0.0253

59 Hartford CT 0.1709 0.2228 0.1405 0.0445 0.0445 0.0445

60 Syracuse NY 0.2545 0.3251 0.2118 0.0445 0.0445 0.0445

61 Worchester MA 0.2022 0.2591 0.1697 0.0445 0.0445 0.0445

62 Augusta ME 0.2116 0.2700 0.1674 0.0445 0.0445 0.0445

63 Providence RI 0.2131 0.2863 0.1753 0.0445 0.0445 0.0445

64 Portland ME 0.2294 0.2840 0.1872 0.0445 0.0445 0.0445

65 Nashua NH 0.2268 0.2812 0.1943 0.0445 0.0445 0.0445

66 Ithaca NY 0.1684 0.2136 0.1392 0.0445 0.0445 0.0445

67 Boston MA 0.2332 0.2383 0.1542 0.0445 0.0445 0.0445

68        NY 0.1473 0.1928 0.1224 0.0445 0.0445 0.0445

69 Lynchburg VA 0.3081 0.3612 0.2570 0.0444 0.0444 0.0444

70

New York

City NY 0.2436 0.2944 0.1969 0.0444 0.0444 0.0444

71 Philadelphia PA 0.2007 0.2609 0.1641 0.0444 0.0444 0.0444

72 Seabrook NJ 0.1814 0.2428 0.1427 0.0444 0.0444 0.0444

73 Indianapolis IN 0.1300 0.1862 0.1064 0.0444 0.0444 0.0444
Appendix A Determination of Infiltration and Recharge Rates

Climate

Center

Index

Climate Center

No Liner Infiltration Rate

(m/yr)

Single Clay Liner Infiltration

Rate (m/yr)

City State

Silt

Loam

Sandy

Loam

Silty

Clay

Silt

Loam

Sandy

Loam

Silty

Clay

A-22

74 Cincinnati OH 0.1554 0.2210 0.1539 0.0444 0.0444 0.0444

75 Bridgeport CT 0.1953 0.2464 0.1615 0.0444 0.0444 0.0444

76 Orlando FL 0.1016 0.1697 0.0805 0.0362 0.0362 0.0362

77 Greensboro NC 0.3256 0.3896 0.2705 0.0362 0.0362 0.0362

78 Jacksonville FL 0.1511 0.2106 0.1102 0.0362 0.0362 0.0362

79 Watkinsville GA 0.2891 0.3556 0.2332 0.0362 0.0362 0.0362

80 Norfolk VA 0.2643 0.3857 0.1798 0.0362 0.0362 0.0362

81 Shreveport LA 0.2296 0.2939 0.1842 0.0362 0.0362 0.0362

82 Astoria OR 1.0762 1.1494 0.9647 0.0526 0.0526 0.0526

83 New Haven CT 0.3520 0.4628 0.2855 0.0526 0.0526 0.0526

84 Plainfield MA 0.1900 0.2540 0.1521 0.0526 0.0526 0.0526

85 Knoxville TN 0.4107 0.4460 0.3543 0.0486 0.0486 0.0486

86  
 	   
 NY 0.3363 0.4171 0.2738 0.0486 0.0486 0.0486

87 Lexington KY 0.3294 0.3970 0.2700 0.0486 0.0486 0.0486

88 Edison NJ 0.3122 0.3914 0.2492 0.0486 0.0486 0.0486

89 Nashville TN 0.4674 0.5395 0.3769 0.0486 0.0486 0.0486

90 Little Rock AK 0.3531 0.4336 0.2824 0.0477 0.0477 0.0477

91 Tallahassee FL 0.5913 0.7308 0.4564 0.0477 0.0477 0.0477

92    
	  LA 0.5893 0.7445 0.4503 0.0477 0.0477 0.0477

93 Charleston SC 0.2609 0.3287 0.2123 0.0477 0.0477 0.0477

94

W. Palm

Beach FL 0.2611 0.3490 0.1783 0.0477 0.0477 0.0477

95 Atlanta GA 0.3416 0.3993 0.2822 0.0477 0.0477 0.0477

96

Lake

Charles LA 0.3647 0.4641 0.2817 0.0492 0.0492 0.0492

97 Miami FL 0.1450 0.2201 0.1019 0.0492 0.0492 0.0492

98 Annette AK 1.6833 1.8354 1.4610 0.0338 0.0338 0.0338

99 Bethel AK 0.0564 0.0721 0.0554 0.0295 0.0295 0.0295

100 Fairbanks AK 0.0104 0.0234 0.0117 0.0094 0.0094 0.0094

101 Honolulu HI 0.0523 0.0945 0.0366 0.0048 0.0048 0.0048

102 San Juan PR 0.1267 0.1923 0.0945 0.0193 0.0193 0.0193
Appendix A Determination of Infiltration and Recharge Rates

A-23

Table A.12 HELP-derived Waste Pile Infiltration Rates

Climate

Center

Index

Climate Center

No Liner Infiltration Rate

(m/yr)

Single Clay Liner Infiltration

Rate (m/yr)

City State

Low Med High Low Med High

Silt

Loam

Sandy

Loam

Silty

Clay

Silt

Loam

Sandy

Loam

Silty Clay

Loam

1 Fresno CA 0.0206 0.0422 0.0963 0.0136 0.0434 0.0606

2 Boise ID 0.0053 0.0003 0.0318 0.0136 0.0434 0.0606

3 Denver CO 0.0130 0.0366 0.0958 0.0020 0.0013 0.0037

4

Grand

Junction CO 0.0053 0.0003 0.0178 0.0046 0.0017 0.0020

5 Pocatello ID 0.0069 0.0020 0.0579 0.0059 0.0015 0.0319

6 Glasgow MT 0.0056 0.0043 0.0554 0.0005 0.0002 0.0234

7 Bismarck ND 0.0056 0.0003 0.0356 0.0124 0.0689 0.0950

8 Pullman WA 0.0112 0.0259 0.1001 0.0093 0.0143 0.0344

9 Yakima WA 0.0053 0.0003 0.0104 0.0049 0.0047 0.0284

10 Cheyenne WY 0.0053 0.0003 0.0140 0.0014 0.0003 0.0071

11 Lander WY 0.0058 0.0008 0.0544 0.0042 0.0012 0.0200

12 Los Angeles CA 0.0792 0.1331 0.1885 0.0000 0.0556 0.0718

13 Sacramento CA 0.0699 0.1509 0.1991 0.0000 0.0556 0.0718

14 San Diego CA 0.0361 0.0658 0.0658 0.0000 0.0556 0.0718

15 Santa Maria CA 0.0856 0.1234 0.1732 0.0000 0.0556 0.0718

16 Ely NV 0.0056 0.0135 0.0752 0.0059 0.0011 0.0036

17 Rapid City SD 0.0053 0.0003 0.0102 0.0010 0.0011 0.0192

18 Cedar City UT 0.0056 0.0003 0.0259 0.0048 0.0008 0.0053

19 Albuquerque NM 0.0056 0.0003 0.0097 0.0016 0.0151 0.0074

20 Las Vegas NV 0.0206 0.0231 0.0556 0.0052 0.0018 0.0080

21 Phoenix AZ 0.0053 0.0003 0.0351 0.0047 0.0020 0.0008

22 Tucson AZ 0.0064 0.0003 0.0279 0.0064 0.0075 0.0017

23 El Paso TX 0.0053 0.0003 0.0330 0.0058 0.0026 0.0067

24 Medford OR 0.2261 0.2497 0.2990 0.1262 0.1328 0.1313

25 Great Falls MT 0.0132 0.0259 0.0899 0.0019 0.0047 0.0334

26

Salt Lake

City UT 0.0091 0.0193 0.0747 0.0091 0.0105 0.0368

27 Grand Island NE 0.0284 0.0963 0.2050 0.0422 0.1347 0.1342

28 Flagstaff AZ 0.0170 0.0404 0.1016 0.0105 0.1228 0.1234

29 Dodge City KS 0.0295 0.1011 0.1902 0.0033 0.1063 0.1193

30 Midland TX 0.0381 0.0757 0.1283 0.0033 0.1063 0.1193
Appendix A Determination of Infiltration and Recharge Rates

Climate

Center

Index

Climate Center

No Liner Infiltration Rate

(m/yr)

Single Clay Liner Infiltration

Rate (m/yr)

City State

Low Med High Low Med High

Silt

Loam

Sandy

Loam

Silty

Clay

Silt

Loam

Sandy

Loam

Silty Clay

Loam

A-24

31 St. Cloud MN 0.0513 0.1516 0.2418 0.0264 0.1262 0.1255

32 E. Lansing MI 0.0602 0.1361 0.2197 0.0481 0.1153 0.1114

33

North

Omaha NE 0.0439 0.1618 0.2771 0.0202 0.1264 0.1265

34 Tulsa OK 0.0907 0.2471 0.3452 0.0050 0.1329 0.1318

35 Brownsville TX 0.0457 0.2268 0.3256 0.0050 0.1329 0.1318

36 Dallas TX 0.1067 0.2578 0.3543 0.0050 0.1329 0.1318

37

Oklahoma

City OK 0.0851 0.2423 0.3386 0.0075 0.1310 0.1298

38 Concord NH 0.1410 0.2570 0.3147 0.1125 0.1273 0.1266

39 Pittsburg PA 0.1100 0.2131 0.2944 0.1125 0.1273 0.1266

40 Portland OR 0.1003 0.1880 0.2705 0.1125 0.1273 0.1266

41 Caribou ME 0.1016 0.1758 0.2372 0.1125 0.1273 0.1266

42 Chicago IL 0.1158 0.2126 0.2725 0.1125 0.1273 0.1266

43 Burlington VT 0.4663 0.5331 0.5631 0.1125 0.1273 0.1266

44 Bangor ME 0.0820 0.1717 0.2852 0.1125 0.1273 0.1266

45 Rutland VT 0.4486 0.5060 0.5370 0.1125 0.1273 0.1266

46 Seattle WA 0.0485 0.1676 0.2685 0.1125 0.1273 0.1266

47 Montpelier VT 0.1252 0.2098 0.3160 0.1125 0.1273 0.1266

48

Sault St.

Marie MI 0.1283 0.2116 0.2858 0.1125 0.1273 0.1266

49 Put-in-Bay OH 0.0617 0.2022 0.3048 0.0688 0.1325 0.1321

50 Madison WI 0.0790 0.1717 0.2606 0.0688 0.1325 0.1321

51 Columbus OH 0.0559 0.1481 0.2527 0.0688 0.1325 0.1321

52 Cleveland OH 0.0889 0.1821 0.2680 0.0688 0.1325 0.1321

53 Des Moines IA 0.1232 0.2634 0.3907 0.0688 0.1325 0.1321

54 E. St. Louis IL 0.0897 0.2512 0.3546 0.0688 0.1325 0.1321

55 Columbia MO 0.1547 0.3101 0.4277 0.0688 0.1325 0.1321

56 Topeka KS 0.0841 0.2469 0.3620 0.0174 0.1305 0.1302

57 Tampa FL 0.1168 0.2954 0.4026 0.0200 0.1339 0.1333

58 San Antonio TX 0.1059 0.2715 0.3724 0.0200 0.1339 0.1333

59 Hartford CT 0.1496 0.2611 0.3444 0.1193 0.1286 0.1279

60 Syracuse NY 0.2487 0.4100 0.4844 0.1193 0.1286 0.1279

61 Worchester MA 0.1473 0.2751 0.3622 0.1193 0.1286 0.1279
Appendix A Determination of Infiltration and Recharge Rates

Climate

Center

Index

Climate Center

No Liner Infiltration Rate

(m/yr)

Single Clay Liner Infiltration

Rate (m/yr)

City State

Low Med High Low Med High

Silt

Loam

Sandy

Loam

Silty

Clay

Silt

Loam

Sandy

Loam

Silty Clay

Loam

A-25

62 Augusta ME 0.1692 0.3216 0.4209 0.1193 0.1286 0.1279

63 Providence RI 0.1821 0.3482 0.4610 0.1193 0.1286 0.1279

64 Portland ME 0.1765 0.3335 0.4148 0.1193 0.1286 0.1279

65 Nashua NH 0.1773 0.3312 0.4267 0.1193 0.1286 0.1279

66 Ithaca NY 0.1806 0.3132 0.3861 0.1193 0.1286 0.1279

67 Boston MA 0.2090 0.3254 0.3922 0.1193 0.1286 0.1279

68        NY 0.1770 0.2786 0.3622 0.1193 0.1286 0.1279

69 Lynchburg VA 0.2830 0.4590 0.5654 0.1062 0.1336 0.1332

70

New York

City NY 0.1234 0.2690 0.3818 0.1062 0.1336 0.1332

71 Philadelphia PA 0.1577 0.3406 0.4709 0.1062 0.1336 0.1332

72 Seabrook NJ 0.1783 0.3096 0.4133 0.1062 0.1336 0.1332

73 Indianapolis IN 0.2121 0.3988 0.5184 0.1062 0.1336 0.1332

74 Cincinnati OH 0.1773 0.3526 0.4757 0.1062 0.1336 0.1332

75 Bridgeport CT 0.2113 0.3691 0.4717 0.1062 0.1336 0.1332

76 Orlando FL 0.3061 0.4839 0.5941 0.0804 0.1273 0.1266

77 Greensboro NC 0.2426 0.4666 0.5903 0.0804 0.1273 0.1266

78 Jacksonville FL 0.2591 0.4455 0.5710 0.0804 0.1273 0.1266

79 Watkinsville GA 0.2992 0.4544 0.5535 0.0804 0.1273 0.1266

80 Norfolk VA 0.1694 0.3835 0.4737 0.0804 0.1273 0.1266

81 Shreveport LA 0.1996 0.4087 0.5263 0.0804 0.1273 0.1266

82 Astoria OR 0.9865 1.2136 1.2637 0.1316 0.1355 0.1350

83 New Haven CT 0.3561 0.5423 0.5098 0.1316 0.1355 0.1350

84 Plainfield MA 0.1910 0.3033 0.3950 0.1316 0.1355 0.1350

85 Knoxville TN 0.2804 0.4521 0.5733 0.1255 0.1352 0.1349

86 Central Park NY 0.3045 0.4897 0.6066 0.1255 0.1352 0.1349

87 Lexington KY 0.4039 0.5415 0.6421 0.1255 0.1352 0.1349

88 Edison NJ 0.3000 0.5286 0.6525 0.1255 0.1352 0.1349

89 Nashville TN 0.4173 0.6144 0.7435 0.1255 0.1352 0.1349

90 Little Rock AK 0.3332 0.5288 0.6414 0.1184 0.1351 0.1347

91 Tallahassee FL 0.5024 0.8486 0.9792 0.1184 0.1351 0.1347

92 New Orleans LA 0.3018 0.5380 0.6683 0.1184 0.1351 0.1347

93 Charleston SC 0.2794 0.4829 0.5832 0.1184 0.1351 0.1347
Appendix A Determination of Infiltration and Recharge Rates

Climate

Center

Index

Climate Center

No Liner Infiltration Rate

(m/yr)

Single Clay Liner Infiltration

Rate (m/yr)

City State

Low Med High Low Med High

Silt

Loam

Sandy

Loam

Silty

Clay

Silt

Loam

Sandy

Loam

Silty Clay

Loam

A-26

94

W. Palm

Beach FL 0.5126 0.8219 0.9581 0.1184 0.1351 0.1347

95 Atlanta GA 0.2553 0.5641 0.6904 0.1184 0.1351 0.1347

96

Lake

Charles LA 0.1615 0.4227 0.5331 0.0489 0.0558 0.0927

97 Miami FL 0.3891 0.6066 0.7201 0.0489 0.0558 0.0927

98 Annette AK 1.5373 1.8146 1.8789 0.1352 0.1357 0.1354

99 Bethel AK 0.0502 0.0725 0.1225 0.0352 0.0364 0.0660

100 Fairbanks AK 0.0077 0.0167 0.0777 0.0098 0.0118 0.0407

101 Honolulu HI 0.0501 0.1083 0.1983 0.0323 0.0494 0.0871

102 San Juan PR 0.1498 0.2883 0.4442 0.0637 0.0793 0.1114
Appendix A Determination of Infiltration and Recharge Rates

A-27

Table A.13 HELP-derived Land Application Unit Infiltration Rates

Climate

Center Index

Climate Center No Liner Infiltration Rate (m/yr)

City State Silt Loam Sandy Loam Silty Clay Loam

1 Fresno CA 0.0307 0.0368 0.0381

2 Boise ID 0.0008 0.0094 0.0038

3 Denver CO 0.0008 0.0008 0.0036

4 Grand Junction CO 0.0000 0.0000 0.0003

5 Pocatello ID 0.0000 0.0000 0.0000

6 Glasgow MT 0.0099 0.0074 0.0099

7 Bismarck ND 0.0239 0.0300 0.0196

8 Pullman WA 0.0069 0.0132 0.0084

9 Yakima WA 0.0000 0.0023 0.0003

10 Cheyenne WY 0.0005 0.0013 0.0086

11 Lander WY 0.0033 0.0053 0.0094

12 Los Angeles CA 0.0787 0.0950 0.0699

13 Sacramento CA 0.1024 0.0876 0.0945

14 San Diego CA 0.0221 0.0340 0.0241

15 Santa Maria CA 0.0947 0.1151 0.0841

16 Ely NV 0.0000 0.0000 0.0003

17 Rapid City SD 0.0005 0.0071 0.0033

18 Cedar City UT 0.0000 0.0008 0.0000

19 Albuquerque NM 0.0000 0.0000 0.0003

20 Las Vegas NV 0.0000 0.0000 0.0018

21 Phoenix AZ 0.0000 0.0003 0.0003

22 Tucson AZ 0.0000 0.0003 0.0005

23 El Paso TX 0.0076 0.0130 0.0081

24 Medford OR 0.2073 0.2309 0.2096

25 Great Falls MT 0.0036 0.0069 0.0074

26 Salt Lake City UT 0.0130 0.0269 0.0185

27 Grand Island NE 0.0442 0.0627 0.0323

28 Flagstaff AZ 0.0239 0.0630 0.0226

29 Dodge City KS 0.0135 0.0345 0.0226

30 Midland TX 0.0180 0.0254 0.0135

31 St. Cloud MN 0.0602 0.0831 0.0554

32 E. Lansing MI 0.1090 0.1452 0.1102

33 North Omaha NE 0.0671 0.0795 0.0536

34 Tulsa OK 0.0686 0.1006 0.0465

35 Brownsville TX 0.0549 0.1049 0.0384
Appendix A Determination of Infiltration and Recharge Rates

Climate

Center Index

Climate Center No Liner Infiltration Rate (m/yr)

City State Silt Loam Sandy Loam Silty Clay Loam

A-28

36 Dallas TX 0.0599 0.1067 0.0531

37 Oklahoma City OK 0.0612 0.0942 0.0389

38 Concord NH 0.1585 0.2057 0.1372

39 Pittsburg PA 0.0894 0.1313 0.0792

40 Portland OR 0.4171 0.4387 0.3927

41 Caribou ME 0.1082 0.1491 0.0886

42 Chicago IL 0.0798 0.1138 0.0620

43 Burlington VT 0.1359 0.1781 0.1166

44 Bangor ME 0.1471 0.2045 0.1227

45 Rutland VT 0.1212 0.1598 0.1008

46 Seattle WA 0.4384 0.4582 0.4077

47 Montpelier VT 0.1062 0.1483 0.0879

48 Sault St. Marie MI 0.1651 0.2101 0.1435

49 Put-in-Bay OH 0.0508 0.1003 0.0495

50 Madison WI 0.0912 0.1400 0.0686

51 Columbus OH 0.0765 0.1158 0.0663

52 Cleveland OH 0.0780 0.1212 0.0823

53 Des Moines IA 0.1143 0.1641 0.1156

54 E. St. Louis IL 0.1435 0.1676 0.0704

55 Columbia MO 0.1529 0.1989 0.1224

56 Topeka KS 0.1049 0.1483 0.0762

57 Tampa FL 0.0658 0.1031 0.0475

58 San Antonio TX 0.1095 0.1646 0.0820

59 Hartford CT 0.1709 0.2228 0.1405

60 Syracuse NY 0.2545 0.3251 0.2118

61 Worchester MA 0.2022 0.2591 0.1697

62 Augusta ME 0.2116 0.2700 0.1674

63 Providence RI 0.2131 0.2863 0.1753

64 Portland ME 0.2294 0.2840 0.1872

65 Nashua NH 0.2268 0.2812 0.1943

66 Ithaca NY 0.1684 0.2136 0.1392

67 Boston MA 0.2332 0.2383 0.1542

68 Schenectady NY 0.1473 0.1928 0.1224

69 Lynchburg VA 0.3081 0.3612 0.2570

70 New York City NY 0.2436 0.2944 0.1969

71 Philadelphia PA 0.2007 0.2609 0.1641

72 Seabrook NJ 0.1814 0.2428 0.1427
Appendix A Determination of Infiltration and Recharge Rates

Climate

Center Index

Climate Center No Liner Infiltration Rate (m/yr)

City State Silt Loam Sandy Loam Silty Clay Loam

A-29

73 Indianapolis IN 0.1300 0.1862 0.1064

74 Cincinnati OH 0.1554 0.2210 0.1539

75 Bridgeport CT 0.1953 0.2464 0.1615

76 Orlando FL 0.1016 0.1697 0.0805

77 Greensboro NC 0.3256 0.3896 0.2705

78 Jacksonville FL 0.1511 0.2106 0.1102

79 Watkinsville GA 0.2891 0.3556 0.2332

80 Norfolk VA 0.3122 0.0000 0.2685

81 Shreveport LA 0.2296 0.2939 0.1842

82 Astoria OR 1.0762 1.1494 0.9647

83 New Haven CT 0.3520 0.4628 0.2855

84 Plainfield MA 0.1900 0.2540 0.1521

85 Knoxville TN 0.4107 0.4460 0.3543

86 Central Park NY 0.3363 0.4171 0.2738

87 Lexington KY 0.3294 0.3970 0.2700

88 Edison NJ 0.3122 0.3914 0.2492

89 Nashville TN 0.4674 0.5395 0.3769

90 Little Rock AK 0.3531 0.4336 0.2824

91 Tallahassee FL 0.5913 0.7308 0.4564

92 New Orleans LA 0.5893 0.7445 0.4503

93 Charleston SC 0.2609 0.3287 0.2123

94 W. Palm Beach FL 0.2611 0.3490 0.1783

95 Atlanta GA 0.3416 0.3993 0.2822

96 Lake Charles LA 0.3647 0.4641 0.2817

97 Miami FL 0.1450 0.2201 0.1019

98 Annette AK 1.8049 1.9771 1.5159

99 Bethel AK 0.1849 0.1981 0.1781

100 Fairbanks AK 0.1463 0.1483 0.1445

101 Honolulu HI 0.0541 0.0983 0.0363

102 San Juan PR 0.1491 0.2164 0.1049
Appendix A Determination of Infiltration and Recharge Rates

A-30

Table A.14 HELP-derived Regional Recharge Rates

Climate

Center Index

Climate Center

Ambient Regional Recharge Rate (m/yr)

Soil Type

City State Silt Loam Sandy Loam Silty Clay Loam

1 Fresno CA 0.0307 0.0368 0.0381

2 Boise ID 0.0008 0.0094 0.0038

3 Denver CO 0.0008 0.0008 0.0036

4 Grand Junction CO 0.0000 0.0000 0.0003

5 Pocatello ID 0.0000 0.0000 0.0000

6 Glasgow MT 0.0099 0.0074 0.0099

7 Bismarck ND 0.0239 0.0300 0.0196

8 Pullman WA 0.0069 0.0132 0.0084

9 Yakima WA 0.0000 0.0023 0.0003

10 Cheyenne WY 0.0005 0.0013 0.0086

11 Lander WY 0.0033 0.0053 0.0094

12 Los Angeles CA 0.0787 0.0950 0.0699

13 Sacramento CA 0.1024 0.0876 0.0945

14 San Diego CA 0.0221 0.0340 0.0241

15 Santa Maria CA 0.0947 0.1151 0.0841

16 Ely NV 0.0000 0.0000 0.0003

17 Rapid City SD 0.0005 0.0071 0.0033

18 Cedar City UT 0.0000 0.0008 0.0000

19 Albuquerque NM 0.0000 0.0000 0.0003

20 Las Vegas NV 0.0000 0.0000 0.0018

21 Phoenix AZ 0.0000 0.0003 0.0003

22 Tucson AZ 0.0000 0.0003 0.0005

23 El Paso TX 0.0076 0.0130 0.0081

24 Medford OR 0.2073 0.2309 0.2096

25 Great Falls MT 0.0036 0.0069 0.0074

26 Salt Lake City UT 0.0130 0.0269 0.0185

27 Grand Island NE 0.0442 0.0627 0.0323

28 Flagstaff AZ 0.0239 0.0630 0.0226

29 Dodge City KS 0.0135 0.0345 0.0226

30 Midland TX 0.0180 0.0254 0.0135

31 St. Cloud MN 0.0602 0.0831 0.0554

32 E. Lansing MI 0.1090 0.1452 0.1102

33 North Omaha NE 0.0671 0.0795 0.0536

34 Tulsa OK 0.0686 0.1006 0.0465

35 Brownsville TX 0.0549 0.1049 0.0384
Appendix A Determination of Infiltration and Recharge Rates

Climate

Center Index

Climate Center

Ambient Regional Recharge Rate (m/yr)

Soil Type

City State Silt Loam Sandy Loam Silty Clay Loam

A-31

36 Dallas TX 0.0599 0.1067 0.0531

37 Oklahoma City OK 0.0612 0.0942 0.0389

38 Concord NH 0.1585 0.2057 0.1372

39 Pittsburg PA 0.0894 0.1313 0.0792

40 Portland OR 0.4171 0.4387 0.3927

41 Caribou ME 0.1082 0.1491 0.0886

42 Chicago IL 0.0798 0.1138 0.0620

43 Burlington VT 0.1359 0.1781 0.1166

44 Bangor ME 0.1471 0.2045 0.1227

45 Rutland VT 0.1212 0.1598 0.1008

46 Seattle WA 0.4384 0.4582 0.4077

47 Montpelier VT 0.1062 0.1483 0.0879

48 Sault St. Marie MI 0.1651 0.2101 0.1435

49 Put-in-Bay OH 0.0508 0.1003 0.0495

50 Madison WI 0.0912 0.1400 0.0686

51 Columbus OH 0.0765 0.1158 0.0663

52 Cleveland OH 0.0780 0.1212 0.0823

53 Des Moines IA 0.1143 0.1641 0.1156

54 E. St. Louis IL 0.1435 0.1676 0.0704

55 Columbia MO 0.1529 0.1989 0.1224

56 Topeka KS 0.1049 0.1483 0.0762

57 Tampa FL 0.0658 0.1031 0.0475

58 San Antonio TX 0.1095 0.1646 0.0820

59 Hartford CT 0.1709 0.2228 0.1405

60 Syracuse NY 0.2545 0.3251 0.2118

61 Worchester MA 0.2022 0.2591 0.1697

62 Augusta ME 0.2116 0.2700 0.1674

63 Providence RI 0.2131 0.2863 0.1753

64 Portland ME 0.2294 0.2840 0.1872

65 Nashua NH 0.2268 0.2812 0.1943

66 Ithaca NY 0.1684 0.2136 0.1392

67 Boston MA 0.2332 0.2383 0.1542

68 Schenectady NY 0.1473 0.1928 0.1224

69 Lynchburg VA 0.3081 0.3612 0.2570

70 New York City NY 0.2436 0.2944 0.1969

71 Philadelphia PA 0.2007 0.2609 0.1641
Appendix A Determination of Infiltration and Recharge Rates

Climate

Center Index

Climate Center

Ambient Regional Recharge Rate (m/yr)

Soil Type

City State Silt Loam Sandy Loam Silty Clay Loam

A-32

72 Seabrook NJ 0.1814 0.2428 0.1427

73 Indianapolis IN 0.1300 0.1862 0.1064

74 Cincinnati OH 0.1554 0.2210 0.1539

75 Bridgeport CT 0.1953 0.2464 0.1615

76 Orlando FL 0.1016 0.1697 0.0805

77 Greensboro NC 0.3256 0.3896 0.2705

78 Jacksonville FL 0.1511 0.2106 0.1102

79 Watkinsville GA 0.2891 0.3556 0.2332

80 Norfolk VA 0.3122 0.0000 0.2685

81 Shreveport LA 0.2296 0.2939 0.1842

82 Astoria OR 1.0762 1.1494 0.9647

83 New Haven CT 0.3520 0.4628 0.2855

84 Plainfield MA 0.1900 0.2540 0.1521

85 Knoxville TN 0.4107 0.4460 0.3543

86 Central Park NY 0.3363 0.4171 0.2738

87 Lexington KY 0.3294 0.3970 0.2700

88 Edison NJ 0.3122 0.3914 0.2492

89 Nashville TN 0.4674 0.5395 0.3769

90 Little Rock AK 0.3531 0.4336 0.2824

91 Tallahassee FL 0.5913 0.7308 0.4564

92 New Orleans LA 0.5893 0.7445 0.4503

93 Charleston SC 0.2609 0.3287 0.2123

94 W. Palm Beach FL 0.2611 0.3490 0.1783

95 Atlanta GA 0.3416 0.3993 0.2822

96 Lake Charles LA 0.3647 0.4641 0.2817

97 Miami FL 0.1450 0.2201 0.1019

98 Annette AK 1.6833 1.8354 1.4610

99 Bethel AK 0.0564 0.0721 0.0554

100 Fairbanks AK 0.0104 0.0234 0.0117

101 Honolulu HI 0.0523 0.0945 0.0366

102 San Juan PR 0.1267 0.1923 0.0945

A.1.5 DETERMINATION OF RECHARGE RATES

We estimated recharge rates for the three primary soil types across the

United States (SNL, SLT, and SCL) and ambient climate conditions at 102 climate
Appendix A Determination of Infiltration and Recharge Rates

A-33

stations through the use of the HELP water-balance model as summarized in

Sections A.1.1 and A.1.2. We assumed the ambient regional recharge rate for a

given climate center and soil type (for all four WMU types) is the same as the

corresponding unlined LF infiltration rate. Table A.14 presents the resulting regional

recharge rates for all climate stations and soil types.
Appendix A Determination of Infiltration and Recharge Rates

A-34

A.2 REFERENCES

ABB Environmental Services, 1995. Estimation of Leachate Rates from Industrial

Waste Management Facilities. August, 1995.

Bonaparte, R., J. P. Giroud, and B.A. Cross, 1989. Rates of leakage through landfill

liners. Geosynthetics 1989 Conference, San Diego, California.

Rollin, A.L., M. Marcotte, T. Jacquelin, and L. Chaput, 1999. Leak location in

exposed geomembrane liners using an electrical leak detection technique.

Geosynthetics ‘99: Specifying Geosynthetics and Developing Design Details,

Vol. 2, pp 615-626.

Schroeder, P.R., T.S., Dozier, P.A. Zappi, B.M. McEnroe, J. W. Sjostrom, and R.L.

Peton, 1994. The hydrologic evaluation of landfill performance model

(HELP): Engineering Documentation for Version 3. EPA/600/R-94/1686.

United States Environmental Protection Agency, Cincinnati, OH.

TetraTech, Inc., 2001. Characterization of infiltration rate data to support groundwater modeling efforts (Draft). Prepared for the U.S. Environmental

Protection Agency, Office of Solid Waste, Contract No. 68-W6-0061, May,

2001.

U.S. EPA, 2001. Industrial Surface Impoundments in the United States. U.S. EPA

Office of Solid Waste, Washington, DC 20460. USEPA 530-R-01-005.

U.S. EPA, 2003a. EPACMTP Technical Background Document. Office of Solid

Waste, Washington, DC.

U.S. EPA, 2003c. IWEM Technical Background Document. Office of Solid Waste,

Washington, DC.
APPENDIX B

NON-LINEAR SORPTION ISOTHERMS CALCULATED

USING THE MINTEQA2 MODEL
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B-i

TABLE OF CONTENTS

Page

LIST OF FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B-ii

LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B-iii

1.0 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B-1

2.0 MODEL INPUT DATA AND PROCEDURE . . . . . . . . . . . . . . . . . . . . . . . B-3

2.1 METALS OF INTEREST . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B-3

2.2 GROUND-WATER COMPOSITION . . . . . . . . . . . . . . . . . . . . . . B-4

2.3 MODEL ADSORBENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B-6

2.3.1 Goethite Sorbent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B-7

2.3.2 Particulate Organic Matter Sorbent . . . . . . . . . . . . . . . . B-10

2.4 LEACHATE ORGANIC MATTER . . . . . . . . . . . . . . . . . . . . . . . . B-13

2.5 MINTEQA2 MODELING PROCEDURE . . . . . . . . . . . . . . . . . . . B-15

2.5.1 Pre-equilibration With Sorbents . . . . . . . . . . . . . . . . . . . B-15

2.5.2 Titrating Systems To New pH Values . . . . . . . . . . . . . . . B-15

2.5.3 Addition Of Leachate Acids And Contaminant Metal . . . B-16

3.0 RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B-17

3.1 EXAMPLE ISOTHERMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B-17

4.0 ASSUMPTIONS AND LIMITATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . B-21

4.1 GROUND-WATER CHARACTERIZATION ISSUES . . . . . . . . . B-21

4.2 SORBENT CHARACTERIZATION ISSUES . . . . . . . . . . . . . . . . B-21

4.3 LEACHATE CHARACTERIZATION ISSUES . . . . . . . . . . . . . . . B-22

4.4 OTHER ISSUES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B-23

5.0 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B-25
B-ii

LIST OF FIGURES

Page

Figure B.1 MINTEQA2 Computes the Equilibrium Distribution of Metal . . . . . B-2

Figure B.2 Cr(VI) Isotherms Illustrating Influence of pH . . . . . . . . . . . . . . . B-18

Figure B.3 Pb Isotherms Illustrating Influence of FeOx

Sorbent Concentration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B-19

Figure B.4 Pb Isotherms Illustrating Influence of POM/DOM Concentration. B-19

Figure B.5 Cu Isotherms Illustrating Influence of LOM Concentration . . . . . B-20

Figure B.6 Relevant pH-Eh Window And Stable Iron Phases

(after Hem, 1977) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B-24
B-iii

LIST OF TABLES

Page

Table B.1 Settings For The Hydrogeologic Environment Parameter

In EPACMTP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B-5

Table B.2 Composition Of Representative Ground Waters . . . . . . . . . . . . . B-6

Table B.3 Concentration Levels For Goethite Sorbent . . . . . . . . . . . . . . . . . B-7

Table B.4 Model Parameters For The Goethite Sorbent . . . . . . . . . . . . . . . B-8

Table B.5 Goethite Sorption Reactions Used In MINTEQA2 . . . . . . . . . . . . B-9

Table B.6 POM And DOM Concentration Levels . . . . . . . . . . . . . . . . . . . . B-12

Table B.7 Site Concentrations For POM And DOM Components

In MINTEQA2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B-12

Table B.8 POM And DOM Reactions Included In MINTEQA2 Modeling . . . B-13

Table B.9 Model Concentrations Of Representative Leachate Acids . . . . . B-14
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B-1

APPENDIX B

NON-LINEAR SORPTION ISOTHERMS CALCULATED

USING THE MINTEQA2 MODEL

1.0 INTRODUCTION

This appendix describes the development of concentration-dependent metal

partition coefficients for use in EPACMTP. In the subsurface, metal contaminants

undergo reactions with ligands in the pore water and with surface sites on the solid

aquifer or soil matrix material. Reactions in which the metal is bound to the solid matrix

are referred to as sorption reactions and metal that is bound to the solid is said to be

sorbed. The ratio of the concentration of metal sorbed to the concentration in the

mobile aqueous phase at equilibrium is referred to as the partition coefficient (Kd

).

During contaminant transport, sorption to the solid matrix results in retardation of the

contaminant front. Thus, transport models such as EPACMTP incorporate the

contaminant partition coefficient into the overall retardation factor (the ratio of the

average linear particle velocity to the velocity of that portion of the plume where the

contaminant is at 50 percent dilution). Using Kd

in EPACMTP transport modeling

implies the assumption that local equilibrium between the solutes and the sorbents is

attained. This implies that the rate of sorption reactions is fast relative to advectivedispersive transport of the contaminant.

EPACMTP incorporates the option of using tables of non-linear sorption

isotherms. These isotherms reflect the tendency of Kdto decrease as the total metal

concentration in the system increases. The non-linear isotherms available for use in

EPACMTP are specified in terms of the dissolved metal concentration and the

corresponding sorbed concentration at a series of total metal concentrations. The

isotherms were estimated using the geochemical speciation model, MINTEQA2. For

a particular metal, Kd values in a soil or aquifer are dependent upon the metal

concentration and various geochemical characteristics of the soil or aquifer and the

associated pore water. Geochemical parameters that have the greatest influence on

the magnitude of Kdinclude the pH of the system and the nature and concentration of

sorbents associated with the soil or aquifer matrix. In the subsurface beneath a

disposal facility, the concentration of leachate constituents may also influence Kd.

Although the dependence of metal partitioning on the total metal concentration and on

pH and other geochemical characteristics is apparent from partitioning studies reported

in the scientific literature, Kd values for many metals are not available for the range of

metal concentrations or geochemical conditions needed in risk assessment modeling.

For this reason, we chose to use an equilibrium speciation model, MINTEQA2, to

estimate partition coefficients. Using a speciation model allows Kd values to be

estimated for a range of total metal concentrations in various model systems designed

to depict natural variability in those geochemical characteristics that most influence

metal partitioning.
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

1 The version of MINTEQA2 used in this modeling was modified from version 4.02.

B-2

Total

Component

Concentrations

Dissolved Adsorbed Precipitated

Figure B.1 MINTEQA2 Computes the Equilibrium

Distribution of Metal.

MINTEQA2

We produced the non-linear sorption isotherms for metals by using MINTEQA2

1

,

a geochemical speciation model maintained and distributed by the U.S. EPA. From

input data consisting of total concentrations of chemical constituents, MINTEQA2

calculates the fraction of a contaminant metal that is dissolved, adsorbed, and

precipitated at equilibrium (see Figure B.1). The total concentrations of major and

minor ions, trace metals and other chemicals are specified in terms of key species

known as components. MINTEQA2 automatically includes an extensive database of

solution species and solid phase species representing reaction products of two or more

of the components. The model does not automatically include sorption reactions, but

these can be included in the calculations if supplied by the user. When sorption

reactions are included, the dimensionless partition coefficient can be calculated from

the ratio of the sorbed metal concentration to the dissolved metal concentration at

equilibrium. The dimensionless partition coefficient is converted to Kd with units of liters

per kilogram (L/kg) by normalizing by the mass of soil (in kilograms) with which one liter

of pore water is equilibrated (the phase ratio). An isotherm is generated when the

equilibrium metal distribution between sorbed and dissolved fractions is estimated for

a series of total metal concentrations.

Progress in accounting for sorption in equilibrium calculations over the past

decade has resulted in the development of coherent databases of sorption reactions for

particular sorbents. These databases include acid-base sorption reactions and

reactions for major ions in aquatic systems (Ca, Mg, SO4

, etc.). Including such

reactions along with those representing sorption of trace metals makes it possible to

estimate sorption in systems of varying pH and composition. Examples of coherent

databases of sorption reactions include that for the hydrous ferric oxide surface

presented by Dzombak and Morel (1990) and a similar database for goethite presented

by Mathur

(1995).
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-3

2.0 MODEL INPUT DATA AND PROCEDURE

Expected natural variability in Kdfor a particular metal was included in the

MINTEQA2 modeling by including variability in important input parameters upon which

Kd depends. The input parameters for which variability was incorporated include

ground-water composition, pH, concentration of sorbents, concentration of leachate

organic matter (LOM), and concentration of metal.

The ground-water chemistry exerts an important influence on metal partition

coefficients. The major ions present in ground water may compete with trace metals

for sorption sites. Also, inorganic ligands may complex with some metals reducing their

tendency to sorb. For the purposes of this model, we assumed that the influence of

ground-water composition on metal sorption can be adequately represented by dividing

the universe of ground-water compositional types into two categories: carbonate and

non-carbonate. Further, we assumed that the influence of pH can be represented by

depicting each of these two ground water types at a number of equilibrium pH values

within its natural range of variability. Furthermore, the depiction of each ground-water

chemistry at multiple pH values can be accomplished by titrating the natural groundwater chemistry with a mineral acid or base.

The influence of variability in sorption capacity of soil and aquifer materials was

included in the Kd estimates by equilibrating the ground-water systems with various

concentrations of commonly occurring natural sorbents. Two common sorbents in soil

and ground-water systems are ferric oxyhydroxide and particulate organic matter

(POM). Although other sorbents such as clay minerals, carbonate minerals, hydrous

aluminum and manganese oxides, and silica may sorb metals in the subsurface,

representation of ferric oxyhydroxide and particulate organic matter in the model is

sufficient to provide a reasonable assessment of the sorption capacity of most natural

ground-water systems.

Leachate organic matter present as various well-characterized acids may

influence the propensity for metal sorption. The influence of leachate organic matter

on metal sorption is characterized by including representative acids present at

concentration levels that span the expected range.

2.1 METALS OF INTEREST

The metal contaminants whose partition coefficients have been estimated using

MINTEQA2 include arsenic (As), antimony (Sb), barium (Ba), beryllium (Be), cadmium

(Cd), cobalt (Co), copper (Cu), chromium (Cr), fluoride (F), mercury (Hg), manganese

(Mn), molybdenum (Mo), lead (Pb), nickel (Ni), selenium (Se), silver (Ag), thallium (Tl),

vanadium (V), and zinc (Zn).

Several of these metals occur naturally in more than one oxidation state. The

modeling described here is restricted to the oxidation states that are most likely to occur

in waste systems or most likely to be mobile in ground-water waste systems. For

arsenic, chromium, and selenium, partition coefficients were estimated for two oxidation
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-4

states. These were: As(III) and As(V), Cr(III) and Cr(VI), and Se(IV) and Se(VI). For

antimony, molybdenum, thallium, and vanadium, only one oxidation state was modeled

although multiple oxidation states occur. For all four of these metals, the choice of

which state to model was dictated by practical aspects such as availability of sorption

reactions and by subjective assessment of the appropriate oxidation state. The

oxidation states modeled were Sb(V) (there were no sorption reactions available for

Sb(III)), Mo(VI) (molybdate seems the most relevant form from literature reports),

thallium (I) (this form is more frequently cited in the literature as having environmental

implications), and V(V) (vanadate; sorption reactions were not available for other

forms).

2.2 GROUND-WATER COMPOSITION

The extent of metal sorption in a ground-water system is dependent upon the

chemical characteristics of the pore water solution and the interactions between all

solutes and the sorbing sites present on the exposed surfaces of the soil and aquifer

matrix material. In EPACMTP, partition coefficients were estimated separately for two

ground-water compositional types, one with composition representative of a carbonateterrain system and one representative of a non-carbonate system. The two groundwater compositional types are correlated with the hydrogeologic environment parameter

in EPACMTP. In EPACMTP, this parameter may take on one of thirteen values, each

indicative of a particular ground-water type (see Table B.1). Issues of practicality limit

to just two the number of ground-water types for which separate partition coefficients

can be estimated. The broadest division that may be made of the thirteen ground-water

types in EPACMTP is carbonate and non-carbonate. Thus, these are the two broad

types for which coefficients were estimated. The carbonate type corresponds to the

“solution limestone” hydrogeologic environment setting in EPACMTP (hydrogeologic

environment parameter = 12). The other twelve possible hydrogeologic settings in

EPACMTP are represented by the non-carbonate ground-water type.
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-5

Table B.1 Settings For The Hydrogeologic Environment Parameter In

EPACMTP

Hydrogeologic

Environment Parameter Environment (Ground-Water Type) Represented

1 Metamorphic and Igneous

2 Bedded Sedimentary Rock

3 Till Over Sedimentary Rock

4 Sand and Gravel

5 Alluvial Basins Valleys and Fans

6 River Valleys and Floodplains with Overbank Deposits

7 River Valleys and Floodplains without Overbank Deposit

8 Outwash

9 Till and Till Over Outwash

10 Unconsolidated and Semi-consolidated Shallow Aquifers

11 Coastal Beaches

12 Solution Limestone

13 Others (unclassified hydrogeologic environments)

For both ground-water types, we selected from the literature a representative,

charge-balanced ground-water chemistry specified in terms of major ion concentrations

and natural pH. The carbonate system was represented by a well sample reported for

a limestone aquifer (Freeze and Cherry, 1979). This ground water had a natural pH of

7.5 and was saturated with respect to calcite. The non-carbonate system was

represented by a sample reported from an unconsolidated sand and gravel aquifer with

a natural pH of 7.4 (White et al., 1963). An unconsolidated sand and gravel aquifer

was selected to represent the non-carbonate compositional type because it is the most

frequently occurring of the twelve (non-carbonate) hydrogeologic environments in

EPACMTP. The composition of both the carbonate and non-carbonate representative

ground-water samples is shown in Table B.2. These compositions were used in

MINTEQA2 to estimate partition coefficients for carbonate and non-carbonate groundwater types. When EPACMTP is used in site-specific or monte carlo mode, the choice

of the hydrogeologic environment by the user (or the monte carlo routine) dictates the

set of partition coefficients (carbonate or non-carbonate) that should be accessed.
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-6

Table B.2 Composition Of Representative Ground Waters

Constituent Chemical

Concentrations (mg/L)

Carbonate Ground

water

Non-carbonate Ground

water

Ca 55 49

Mg 28 13

SO4 20 27

HCO3 265 384

Na 3.1 105

Cl 10 34

K 1.5 3.0

NO3--- 7.8

F --- 0.3

SiO2

--- 21

pH 7.5 7.4

Temp 18 C 14 C

Other Equilibrium with calcite ---

2.3 MODEL ADSORBENTS

Two types of adsorbents were represented in the MINTEQA2 equilibrium

modeling: ferric oxide and particulate organic matter. Ferric oxides (and hydroxides)

and particulate organic matter are among the most important sorbents in natural

systems. The former may be present as amorphous substances or crystalline minerals

such as hematite, goethite, or ferrihydrite dispersed in soil as discrete particles or as

coatings on particles of other materials. In recent years, databases of equilibrium

sorption reactions for hydrous ferric oxide and goethite have been compiled from

studies described in the literature (Dzombak and Morel, 1990; Mathur, 1995). Both of

the databases cited were designed for use with the MIT Two-Layer sorption model, also

called the diffuse-layer model (DLM; Dzombak and Morel, 1990).

Owing to the complexity and variability of natural organic substances, the

science of modeling surface reactions on particulate organic matter is less advanced

than for sorption onto hydrous metal oxides. The modeling described here assumes

that reactions on POM are analogous to those on dissolved organic matter (DOM); a

DOM model was adapted for the POM calculation. This model, the Gaussian

distribution model (Dobbs et. al., 1989), assumes that organic matter is a complex

mixture of substances exhibiting highly variable binding affinities for metals. Reactions

are represented like conventional pure substance reactions except that the usual single

equilibrium constant is replaced by a distribution of constants (log K values). The

distribution of log K is assumed to be Gaussian in shape. This model is also supplied

with a database of reactions, including acid-base and major ion reactions, each with its

mean log K for depicting the Gaussian distribution.
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-7

When included in equilibrium models, these databases of sorption reactions

provide a means of including competition for sorption sites among major ground-water

ions such as Ca, Mg, and SO4 and contaminant metal constituents. More importantly,

by including in equilibrium calculations the acid-base reactions for these surfaces, the

dependence of trace metal sorption on pH can be reflected in the model.

2.3.1 Goethite Sorbent

Mineralogically, we assumed the ferric oxide sorbent to be goethite (-FeOOH).

Goethite is a common form of ferric oxide in soils. The database of sorption reactions

for goethite reported by Mathur (1995) was used with the diffuse-layer sorption model

in MINTEQA2 to represent the interactions of protons, major ions, and contaminant

metals with the ferric oxide surface (hereafter referred to as FeOx for brevity).

The concentration of sorption sites used in the MINTEQA2 model runs was

based on a measurement of ferric iron extractable from soil samples using

hydroxylamine hydrochloride as reported in EPRI(1986). This method of Fe extraction

is intended to provide a measure of the exposed ferric oxide present as mineral

coatings and discrete particles and available for surface reactions with solutes in the

associated pore water. The variability in ferric oxide sorbent concentration represented

by the variability in extractable Fe from these samples was included in the modeling by

selecting low, medium and high extractable Fe concentrations corresponding to the 17

th

,

50

th and 83rd percentiles of the sample measurements. The extractable Fe weight

percentages used in the modeling are shown in Table B.3.

Table B.3 Concentration Levels For Goethite Sorbent

Concentration Level

Weight Percent

Fe (extractable)

FeOOH Sorbent

Concentration (g/L)

Unsaturated zone

Low 0.0182 1.325

Medium 0.0729 5.309

High 0.1190 8.667

Saturated zone

Low 0.0182 1.032

Medium 0.0729 4.136

High 0.1190 6.751

Although the same distribution of extractable Fe sorbent was used in modeling

the saturated and unsaturated zones, the actual concentration of sorbing sites

corresponding to the low, medium, and high FeOx settings in MINTEQA2 was different

in the two zones because the assumed ratio of soil mass to solution volume (the phase

ratio) was different. For both zones, the phase ratio was calculated as the mean soil

bulk density divided by the mean water content (product of mean porosity and mean

water saturation). In EPACMTP, the mean soil bulk density and mean porosity are
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-8

1.6 kg/L and 45 percent, respectively. The mean water saturation in the unsaturated

zone is 77.7 percent. The water saturation in the saturated zone is, of course, 100

percent. Thus, the phase ratio for the unsaturated zone is 4.57 kg/L and for the

saturated zone is 3.56 kg/L. We used these values and the molar mass ratio of

goethite to Fe to convert the weight percent extractable Fe to the mass of goethite

appropriate for one liter of pore water solution (see Table B.3).

The specific surface area and site density used in the diffuse-layer adsorption

model were as prescribed by Mathur(1995) for goethite. These values along with the

molar concentration of FeOx sorbing sites are shown in Table B.4. The complete

database of goethite sorption reactions used in MINTEQA2, including acid-base surface

reactions and reactions for major ions, is shown in Table B.5. The reactions shown in

Table B.5 have been reformulated for use in MINTEQA2. The reformulation step is

necessary in order to present the reaction to MINTEQA2 in a manner consistent with

its database conventions and its predetermined set of reactants (components). The

MINTEQA2 conventions include the requirement that all reactions be written as

formation reactions. In some cases, the reformulation may have involved adding

ancillary reactions to those presented by Mathur. The addition of ancillary reactions is

necessary if the original reaction is not written in terms of MINTEQA2 components. All

ancillary reactions used to reformulate the Mathur goethite reactions were obtained

directly from the MINTEQA2 (v4.02) thermodynamic database.

Table B.4 Model Parameters For The Goethite Sorbent

Parameter Model Value

Specific surface area (m

2

/g) 60

Site density (moles of sites per mole

Fe)

0.018

Unsaturated zone: Site concentration (mol/L)

Low 2.680x10

-4

Medium 1.074x10

-3

High 1.753x10

-3

Saturated zone: Site concentration (mol/L)

Low 2.087x10

-4

Medium 8.365x10

-4

High 1.365x10

-3
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-9

Table B.5 Goethite Sorption Reactions Used In MINTEQA2

Goethite Sorption Reaction

Intrinsic

Equilibrium

Constant

FeOH2

+ FeOH

o + H+

log Ka1 = 6.93

FeOH

o FeO- + H+

log Ka2 = -9.65

FeOH

o + Ca2+ FeOCa+ + H+

log K1 = -6.48

FeOH

o + Ca2+ FeOHCa2+

log K2 = 3.98

FeOH

o + Ca2+ + H+ FeOCa+ + H2O log K3 = 12.26

FeOH

o + Mg2+ FeOMg+ + H+

log K1 = -3.02

FeOH

o + Mg2+ FeOHMg2+

log K2 = 5.24

FeOH

o + Ba2+ FeOBa+ + H+

log K1 = -5.62

FeOH

o + Ba2+ FeOHBa2+

log K2 = 3.43

FeOH

o + Cu2+ FeOCu+ + H+

log K1 = 1.39

FeOH

o + Cu2+ FeOHCu2+

log K2 = 8.92

FeOH

o + Cd2+ FeOCd+ + H+

log K1 = -1.96

FeOH

o + Cd2+ FeOHCd2+

log K2 = 6.28

FeOH

o + Zn2+ FeOZn+ + H+

log K1 = -0.96

FeOH

o + Zn2+ FeOHZn2+

log K2 = 7.50

FeOH

o + Pb2+ FeOPb+ + H+

log K1 = 0.44

FeOH

o + Pb2+ FeOHPb2+

log K2 = 8.25

FeOH

o + Ni2+ FeONi+ + H+

log K1 = -1.96

FeOH

o + Ni2+ FeOHNi2+

log K2 = 6.38

FeOH

o + Co2+ FeOCo+ + H+

log K1 = -0.79

FeOH

o + Co2+ FeOHCo2+

log K2 = 7.28

FeOH

o + Hg(OH)2

o FeOHgOH

o + H2O log K0 = 2.86

FeOH

o + Hg(OH)2

o + H

+ FeOHg+ + 2 H2O log K1 = 10.03

FeOH

o + Hg(OH)2

o + 2H

+ FeOHHg2+

+ 2 H2O

log K2 = 18.58

FeOH

o + Hg(OH)2

o + H

+ + Cl- FeOHgClo

+ 2 H2O

log K4 = 13.51

FeOH

o + Ag+ FeOAg + H+

log K1 = -4.11

FeOH

o + Ag+ FeOHAg+

log K2 = 4.74

FeOH

o + Mn2+ FeOMn+ + H+

log K1 = -2.66

FeOH

o + Mn2+ FeOHMn2+

log K2 = 5.99

FeOH

o + Be2+ FeOBe+ + H+

log K1 = 2.69

FeOH

o + Be2+ FeOHBe2+

log K2 = 10.61

FeOH

o + Tl+ FeOTlo + H+

log K1 = -5.37

FeOH

o + Tl+ FeOHTl+

log K2 = 3.66

FeOH

o + Cr(OH)2

+ FeOCrOH

+ + H2O log K1 = 8.07
Table B.5 Goethite Sorption Reactions Used In MINTEQA2 (continued)

Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

Goethite Sorption Reaction

Intrinsic

Equilibrium

Constant

B-10

FeOH

o + Cr(OH)2+ + H+ FeOHCrOH+2 + H2O log K2 = 16.07

FeOH

o + H3AsO3o FeH2AsO3o + H2O log K1 = 4.33

FeOH

o + H3AsO4o FeH2AsO4o + H2O log K1 = 6.87

FeOH

o + H3AsO4o FeHAsO4- + H+ + H2O log K2 = -0.89

FeOH

o + H3AsO4o FeOHAsO43- + 3H+

log K4 = -11.09

FeOH

o + VO2+ + H2O FeH2VO4o + H+

log K1 = 2.35

FeOH

o + VO2+ + H2O FeHVO4- + 2H+

log K2 = -5.91

FeOH

o + VO2+ + 2H2O FeOHVO43- + 4H+

log K4 = -17.53

FeOH

o + Sb(OH)6- + H+ FeOH2Sb(OH)6o

log K1 = 11.94

FeOH

o + Sb(OH)6

- FeOHSb(OH)6-

log K2 = 5.76

FeOH

o + SO42- + 2H+ FeHSO4o + H2O log K1 = 12.89

FeOH

o + SO42- + H+ FeSO4- + H2O log K2 = 6.74

FeOH

o + SO42- FeOSO43- + H+

log K4 = -6.26

FeOH

o + HSeO3- + H+ FeHSeO3o + H2O log K1 = 3.25

FeOH

o + HSeO3- FeSeO3- + H2O log K2 = 2.09

FeOH

o + HSeO3- FeOSeO33- + 2H+

log K4 = -14.25

FeOH

o + SeO42- + 2H+ FeHSeO4o + H2O log K1 = 11.65

FeOH

o + SeO42- + H+ FeSeO4- + H2O log K2 = 6.54

FeOH

o + CrO42- + 2H+ FeHCrO4o + H2O log K1 = 17.11

FeOH

o + CrO42- + H+ FeCrO4- + H2O log K2 = 11.17

FeOH

o + CrO42- FeOHCrO42-

log K3 = 4.05

FeOH

o + MoO42- + 2H+ FeHMoO4o + H2O log K1 = 14.65

FeOH

o + MoO42- + H+ FeMoO4- + H2O log K2 = 8.18

FeOH

o + F- + H+ FeOH2Fo

log K1 = 9.20

FeOH

o + F- FeOHF-

log K2 = 1.59

2.3.2 Particulate Organic Matter Sorbent

We obtained the concentration of the second adsorbent, particulate organic

matter, from organic matter distributions already present in EPACMTP. EPACMTP

includes frequency distributions for organic matter for three soil types in the unsaturated

zone: silty clay loam, sandy loam, and silty loam. The silty loam soil type is

intermediate in weight percent organic matter in comparison with the other two and is

the most frequently occurring soil type. Therefore, low, medium, and high POM content

levels for the MINTEQA2 modeling in the unsaturated zone were established as the 7.5,

50, and 92.5 percentiles of the silty loam organic matter distribution. In the saturated

zone, the EPACMTP distribution of organic matter is identical to that for the sandy loam
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-11

soil type of the unsaturated zone. Low, medium, and high POM content levels in

MINTEQA2 modeling of the saturated zone were established as the 7.5, 50, and 92.5

percentile levels, respectively, of this distribution.

As was the case for the goethite sorbent, the concentration of POM included in

the MINTEQA2 modeling was determined from the low, medium, and high content

levels (expressed in weight percent POM) and the mass of soil appropriate for one liter

of pore water solution (see section 2.3.1). Thus, phase ratios of 4.57 kg/L in the

unsaturated zone and 3.56 kg/L in the saturated zone were used to compute the POM

concentration for MINTEQA2 model runs.

We obtained a dissolved organic carbon (DOC) distribution for the saturated

zone from the U.S. EPA STORET database. This distribution is based on 1343

ground-water samples and is approximated by a log normal distribution with a median

loge DOC of 1.974 (corresponding to 7.2 mg C per liter) and loge standard deviation of

1.092. Assuming DOM is approximately 50 percent organic carbon, the DOC values

are multiplied by two to approximate DOM concentrations. The MINTEQA2 modeling

employed low, medium and high concentrations for DOM corresponding to the 7.5,

50.0, and 92.5 percentiles, respectively, of this approximated DOM distribution. An

important point to note is that POM and DOM were not treated as independent variables

in the MINTEQA2 modeling: the high DOM value was associated with the high POM

value, the medium DOM with the medium POM, etc.

Because no directly measured data were available for describing the variation

in DOM concentration in the unsaturated zone, we assumed that high, medium, and low

DOM concentrations reflected a constant ratio of POM content (in weight percent) to

DOM concentration. The constant ratio was arbitrarily chosen as the ratio of the

median DOM (mg/L) from the saturated zone distribution to the median value of POM

(weight percent) from the saturated zone distribution. This ratio, 194.6, was applied to

the low, medium, and high weight percent POM values of the unsaturated zone to

obtain DOM concentrations at the low, medium, and high levels. The weight percent

POM and concentration (mg/L) of both POM and DOM is shown in Table B.6 for all

three concentration levels in both zones.

For both POM and DOM, we assumed a site density of 1.2 x 10

-6 moles of sites per mg

organic matter. The site concentrations for organic matter in both zones are listed in

Table B.7.
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-12

Table B.6 POM And DOM Concentration Levels

POM wt%

POM

Concentration

(mg/L)

DOM Concentration

(mg/L)

Unsaturated zone

Low 0.034 1553.8 6.6

Medium 0.105 4798.5 20.4

High 0.325 14852.5 63.20

Saturated zone

Low 0.020 712.0 3.00

Medium 0.074 2634.4 14.40

High 0.275 9790.0 69.38

Table B.7 Site Concentrations For POM And DOM Components In MINTEQA2

POM Site

Concentration

(mol/L)

DOM Site

Concentration

(mol/L)

Unsaturated zone

Low 1.865 x10

-3

7.896 x10

-6

Medium 5.758 x10

-3

2.439 x10

-5

High 1.782 x10

-2

7.548 x10

-5

Saturated zone

Low 8.544 x10

-4

3.600 x10

-6

Medium 3.161 x10

-3

1.728 x10

-5

High 1.175 x10

-2

8.326 x10

-5

We used a specialized sub-model within MINTEQA2 for calculations involving

the POM and DOM. This sub-model, called the Gaussian distribution model, assumes

that natural organic matter is a mixture of various functional groups having a mean log

K for binding protons and metals, and a standard deviation in log K (Dobbs et al.,

1989). This is in contrast to all other reactants in MINTEQA2 which are implicitly

treated as pure substances with a single equilibrium constant for a particular metal. A

database of DOM reactions proposed by Susetyo et al. (1991) for the metals Ba, Cd,

Cr(III), Cu, Pb, Ni, and Zn and for protons and various other MINTEQA2 components

is included with version 4.02 of the model. Adsorption of metals onto POM was

included in the model calculations by assuming that the reactions were identical to

those for metal complexation with DOM. Table B.8 shows Gaussian organic matter

reactions used in MINTEQA2 for this work. Although the Gaussian model was
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-13

proposed for metal-DOM reactions, we used it here to account for metal-POM reactions

as well. The only difference between the method of calculation for metal-DOM and

metal-POM species in MINTEQA2 was that POM species were excluded from

contributing to the ionic strength.

For the metals Ag, Co, Hg, and Tl, it was necessary to estimate the mean log

K for DOM and POM binding for use in MINTEQA2. The mean log K values for Ag, Co,

and Tl were derived from a linear free-energy relationship based upon to known mean

log K values for several metals, their first hydrolysis constants, and their log K values

for complexation with acetate. For Hg, the mean log K was estimated from a linear

regression based on binding constants for humic and fulvic acid as given by Tipping

(1994).

Table B.8 POM And DOM Reactions Included In MINTEQA2 Modeling

Organic Matter (OM) Reaction

Mean

log K

Standard

Deviation

Species

Charge

OM + H

+ OM-H 3.87 1.7 -1.8

OM + Ca

2+ OM-Ca 2.9 1.7 -0.8

OM + Mg

2+ OM-Mg 1.9 1.7 -0.8

OM + Ba

2+ OM-Ba 3.1 1.7 -0.8

OM + Be

2+ OM-Be 3.5 1.7 -0.8

OM + Cd

2+ OM-Cd 3.3 1.7 -0.8

OM + Cr(OH)2

+ + 2H+ OM-Cr + 2H2O 15.22 1.7 0.2

OM + Cu

2+ OM-Cu 4.9 1.7 -0.8

OM + Ni

2+ OM-Ni 3.3 1.7 -0.8

OM + Pb

2+ OM-Pb 5.2 1.7 -0.8

OM + Zn

2+ OM-Zn 3.5 1.7 -0.8

OM + Hg(OH)2

o + 2H+ OM-Hg + 2H2O 15.2 1.7 -0.8

OM + Co

2+ OM-Co 3.3 1.7 -0.8

OM + Ag

+ OM-Ag 2.0 1.7 -1.8

OM + Tl

+ OM-Tl 1.0 1.7 -1.8

OM + Mn

2+ OM-Mn 3.0 1.7 -0.8

2.4 LEACHATE ORGANIC MATTER

In addition to the metal contaminants, the leachate exiting a landfill may contain

elevated concentrations of leachate organic matter. This organic matter may consist

of various compounds including organic acids that represent primary disposed waste

or that result from the breakdown of more complex organic substances. Many organic

acids found in landfill leachate have significant metal-complexing capacity that may

influence metal mobility. In an effort to incorporate in the Kd modeling the solubilizing

effect of organic acids, we included three representative monoprotic acids as
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-14

components. Data presented by Gintautas et al. (1993) were used to select and

quantify the three representative organic acids. Gintautas examined leachates from six

landfills from across the U.S. Their analyses indicated the presence of over 30 different

acids–most were carboxylic. The three acids chosen to represent the complex mixture

of leachate acids in the MINTEQA2 modeling were acetic acid, propionic acid, and

butyric acid. These were selected based on structure-activity relationships, comparison

of equilibrium constants, and relative concentrations in the leachates analyzed by

Gintautas.

In the MINTEQA2 modeling, low, medium, and high concentration levels for the

representative acids were established based on the lowest, the average, and the

highest measured TOC among the six landfill leachates. The same set of three acids

was used in both the unsaturated and saturated zones. In the latter, their

concentrations were one-seventh of their unsaturated zone concentrations. This

reduction in the leachate acid concentration was applied to account in a rudimentary

way for the effects of dispersion and diffusion in the mixing zone. The factor of oneseventh resulted from flow model tests to estimate an “average” dilution factor in the

mixing zone. Table B.9 gives the low, medium, and high concentrations used in the

MINTEQA2 modeling for each of the three acids in each zone.

The MINTEQA2 thermodynamic database includes complexation reactions

between each of the three representative acids and many of the contaminant metals of

interest. Acid-base and major ion reactions are also included. Some metals, especially

those that behave as anions in aqueous solution (e.g., arsenite, arsenate, chromate,

etc.) do not complex with these acids.

Table B.9 Model Concentrations Of Representative Leachate Acids

Concentration Level

Acetic acid

(mg/L)

Propionic acid

(mg/L)

Butyric acid

(mg/L)

Unsaturated zone

Low 24.80 14.61 15.68

Medium 111.00 64.30 67.94

High 274.60 158.60 169.00

Saturated zone

Low 3.54 2.09 2.24

Medium 15.86 9.19 9.71

High 39.23 22.66 24.14
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-15

2.5 MINTEQA2 MODELING PROCEDURE

The MINTEQA2 modeling was conducted separately for each of the twenty-two

contaminant metals. For each metal, the modeling was performed separately for each

zone (unsaturated and saturated) for each of the two ground waters. Thus, results

were produced in four main categories: the carbonate ground-water unsaturated zone,

the carbonate ground-water saturated zone; the non-carbonate ground-water

unsaturated zone, and the non-carbonate ground-water saturated zone. Within each

of these four categories, we followed a similar modeling procedure. The modeling

procedure consisted of three steps, each involving execution of the MINTEQA2 model.

First, the sorbents were pre-equilibrated with the ground water at the natural groundwater pH. Second, the pre-equilibrated ground-water sorbent systems were titrated to

different pH’s of interest. Finally, leachate organic acids and the contaminant metal

were added to the pre-equilibrated, pH-adjusted systems. In this last step, the metal

salt was added to each system at a series of forty-four total concentrations as in a

titration and the model computed the equilibrium distribution at each titration point to

produce an isotherm.

2.5.1 Pre-equilibration With Sorbents

The goethite and POM sorbents were pre-equilibrated with the ground water at

all nine combinations of their concentration levels. Because the sorbents adsorb some

of the non-contaminant ions present as ground-water constituents (calcium,

magnesium, sulfate, fluoride), we assume the representative compositions used for

both the carbonate and non-carbonate ground waters reflect dissolved concentrations

at equilibrium with an unknown sorbed concentration. The purpose of the preequilibration step is to estimate this unknown sorbed concentration so that it may be

included in subsequent model runs. The method of discovering the sorbed totals for

each of the ground-water constituents that undergoes sorption was trial and error.

Specifically, MINTEQA2 was executed repeatedly with adjusted total concentrations of

these sorbing constituents until the equilibrium dissolved concentration for each was

equal to the measured dissolved concentrations reported for the ground water. This

trial and error pre-equilibration method was performed separately for each of nine

possible combinations of the FeOx and POM sorbent concentrations (e.g., low FeOx,

low POM; low FeOx, medium POM;from Table B.4).

The pre-equilibration step was conducted at the natural pH of each ground

water, and calcite was imposed as an equilibrium mineral for the carbonate groundwater type. Small additions of inert ions (Na

+ or NO3

-

) were added to maintain charge

balance.

2.5.2 Titrating Systems To New pH Values

The nine pre-equilibrated systems were titrated to target pH’s that span the pH

range commonly observed for that ground-water type. Rather than imposing target

pH’s as equilibrium constraints in the model, we used acids and bases to titrate to the

pH targets. The titrants for pH adjustment were NaOH to raise the pH and HNO3to

lower the pH. For the carbonate ground water, the pH was assumed to range from 7.0
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-16

to 8.0. Since the natural pH of the carbonate ground water was 7.5, the acid and base

were used to lower and raise the pH to 7.0 and 8.0, respectively, resulting in three pH

values for this ground water. Since this was done for each of the nine pre-equilibrated

systems, the outcome of this titration step was twenty-seven variants of the carbonate

ground-water system exhibiting various concentration levels of the sorbent and various

pH values. Equilibrium with calcite was maintained in all of these carbonate systems.

For the non-carbonate ground water, the pH of interest was assumed to span

the range 4.5 to 8.2. Each of the nine pre-equilibrated non-carbonate systems was

titrated to nine target pH’s within this range: 4.5, 5.1, 5.6, 6.0, 6.3, 6.6, 6.9, 7.4, and 8.2.

Since the natural pH of the non-carbonate ground water was 7.4, the base was used

only to titrate to pH 8.2. The lower pH’s were attained by titrating with the acid. The

outcome of the titration step for the non-carbonate ground water was eighty-one

variants of the non-carbonate ground-water system exhibiting various concentration

levels of the sorbent and various pH values.

2.5.3 Addition Of Leachate Acids And Contaminant Metal

Each of the pre-equilibrated, pH-adjusted systems were equilibrated with the

three concentration levels of leachate organic acids (see Table B.9). As before, the

equilibrium pH was not imposed as a constraint in MINTEQA2, so the addition of the

leachate acid impacted the calculated equilibrium pH. Because there were three

concentration levels for the leachate organic acids, this step resulted in 81 leachateground-water systems for each zone (unsaturated and saturated) for the carbonate

ground water and 243 leachate-ground-water systems for each zone for the noncarbonate ground water .

The contaminant metal was added in the same step as the leachate organic acids. The

metal was added as a metal salt at a series of forty-four total concentrations spanning

the range 0.001 mg/L to 10,000 mg/L of metal. The choice of chemical species by

which the metal was introduced was predicated on the desire to maintain charge

balance and to avoid species that would exert a great influence on the equilibrium pH.

In some cases, we introduced a fictitious substance to accomplish these goals. The

equilibrium distribution was calculated at each of the forty-four total metal

concentrations to produce an isotherm of sorbed metal versus metal concentration.
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-17

3.0 RESULTS

As shown in Figure B.1, MINTEQA2 computes the equilibrium distribution of

metal among three categories: dissolved, sorbed, and precipitated. The concentration

in the first two of these categories along with the corresponding total metal

concentration define the non-linear isotherm. All three concentrations (dissolved,

sorbed, and precipitated) are made available for use in EPACMTP, but the precipitated

concentration is not used. The ratio of the equilibrium sorbed and dissolved

concentrations recorded in the isotherm is the dimensionless Kd

. For the sorbed

fraction, the concentration recorded in the isotherm is the amount of metal sorbed from

one liter of solution. Of course, this amount is also sorbed onto the mass of soil with

which one liter was equilibrated. This mass is the phase ratio: 4.57 kg/L for the

unsaturated zone and 3.56 kg/L for the saturated zone. The Kd

in units of L/kg is thus

computed by normalizing the dimensionless Kd by the appropriate phase ratio.

For each metal, the modeling resulted in 243 isotherms for the non-carbonate

ground water for the unsaturated zone, and 81 isotherms for the carbonate ground

water for the unsaturated zone. We produced a like number of isotherms for each

ground water for the saturated zone. Each isotherm corresponds to particular

concentration levels of FeOx and POM sorbents, pH, and leachate organic matter

concentration. In monte carlo or site-specific mode, EPACMTP selects the appropriate

isotherm based on the conditions being modeled. Isotherms were produced for Ag,

As(III), As(V), Ba, Be, Cd, Co, Cr(III), Cr(VI), Cu, F, Hg, Mn(II), Mo(V), Ni, Pb, Sb(V),

Se(IV), Se(VI), Tl(I), V(V), and Zn.

3.1 EXAMPLE ISOTHERMS

Example isotherms for Cr(VI) are shown in Figure B.2. This figure shows Kd

versus total Cr(VI) concentration for the non-carbonate ground water saturated zone

at various pH values. The isotherms plotted are for the medium concentration level of

FeOx and POM sorbents and the low concentration level of leachate organic matter.

Because chromate behaves as an anion in ground water, its adsorption is enhanced at

low pH relative to high pH. This behavior is reversed for metals that behave as cations.

Figure B.3 shows the impact of FeOx concentration level on the Kd values of

lead. As expected, sorption is enhanced at the higher FeOx concentrations resulting

in larger Kd values. The example shown is for the unsaturated zone of the carbonate

ground water with the low concentration levels of POM and leachate organic acids. The

pH corresponds to the lowest setting for the carbonate systems: 7.0.

The impact of varying the POM concentration level differs among the various

metals. The effect of POM concentration level also depends on the pH. The variable

impact of POM is due to two factors: the absence of organic matter reactions for anionic

metals and the concurrent influence of DOM for those metals for which organic matter

reactions are included. In the MINTEQA2 modeling procedure we used, increasing the

POM sorbent concentration is always accompanied by a proportional increase in the

DOM concentration. The overall impact on the amount of metal sorbed depends on the
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-18

0

50

100

150

-4 -2 0 2 4

log Total Cr (VI) Conc (mg/L)

lo

g

K

d (L/K

g)

pH 4.5

pH 6.3

pH 8.2

Figure B.2 Cr(VI) Isotherms Illustrating Influence of pH.

relative competition among all constituents in the systems for these two substances.

The “winner” of this relative competition (POM or DOM) shifts with pH because both

substances undergo acid-base reactions. Figure B.4 shows the impact of varying the

POM/DOM concentration level on lead sorption for the non-carbonate ground water

unsaturated zone with medium FeOx concentration level and low leachate organic

matter concentration level at pH 6.3.

The influence of the leachate organic matter concentration level is illustrated in

Figure B.5 for copper sorption. The LOM level is represented in the model by particular

concentrations of three representative leachate organic acids. The acids exert two

modes of influence on metal sorption: (1) they lower the pH, reducing sorption of

cations and enhancing sorption of anions; (2) for those metals that complex these

acids, metal sorption is reduced through competition. The latter effect is generally

restricted to metals that behave as cations. The results shown in Figure B.5 correspond

to high concentration levels of FeOx and POM sorbents in the unsaturated zone for the

carbonate ground water. The pH is 7.0.
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-19

0

10

20

30

40

-4 -2 0 2 4

log Total Pb Conc (mg/L)

lo

g

K

d (L/K

g)

Low FeOx

Med FeOx

High FeOx

Figure B.3 Pb Isotherms Illustrating Influence of FeOx Sorbent Concentration.

0

10

20

30

40

50

-4 -2 0 2 4

log Total Pb Conc (mg/L)

lo

g

K

d (L/K

g)

Low POM

Med POM

High POM

Figure B.4 Pb Isotherms Illustrating Influence of POM/DOM Concentration.
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-20

0

50

100

150

-4 -2 0 2 4

log Total Cu Conc (mg/L)

lo

g

K

d (L/K

g)

Low LOM

Med LOM

High LOM

Figure B.5 Cu Isotherms Illustrating Influence of LOM Concentration.
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-21

4.0 ASSUMPTIONS AND LIMITATIONS

There are many assumptions inherent in the use of a speciation model to

estimate partition coefficients. Some of these must be acknowledged to result in

limitations on the utility of the model results. Undoubtedly, the results are better for

some metals than for others. Various modeling assumptions and limitations we used

are presented below. These are organized as those resulting from the manner in which

the ground-water composition, the sorbents, and the leachate were characterized, and

certain broader, more general issues. The discussion is limited to pointing out each

assumption or limitation. Although the direction of possible error in the estimated Kd

values is apparent from some of these limitations, it would seem to be impossible to

quantify the uncertainty in the estimated Kd values.

4.1 GROUND-WATER CHARACTERIZATION ISSUES

• The categorization of all ground waters into two types, carbonate and noncarbonate, is quite broad. The non-carbonate category is especially broad, and

sorption behavior among different ground-water compositions that might fall into

this category could be quite variable. We did not account for this variability in

the current approach.

• Although the pre-equilibration step is helpful in more realistically establishing

appropriate major ion concentrations, it is somewhat artificial in the sense that

sorbents are not correlated with ground water. Both the FeOx and POM

sorbents were represented as general concentration distributions; the

concentration levels used do not correlate specifically to the ground-water

compositions used.

• Both ground waters were artificially adjusted to different pH’s of interest by

titrating with an acid or base. The degree to which this procedure can result in

model ground-water compositions that adequately represent true variability in

factors that impact Kdis unknown.

4.2 SORBENT CHARACTERIZATION ISSUES

• Only two sorbents are represented in the model systems. Other sorbents are

important in some circumstances including clays, hydrous aluminum and

manganese oxides, calcite, and silica. Failure to include all potential sorbents

could result in underestimation of sorption.

• The ferric oxide was accounted in the modeling as goethite. Other ferric oxides

may be important in ground water, including hydrous ferric oxide (HFO). HFO

has a higher specific surface area and greater reactivity for some metals than

does goethite. The degree of sorption may be underestimated for some metals

in systems where HFO is the dominant form of ferric oxide. Also, equilibrium

constants for adsorption onto goethite were unavailable for some metals;

estimates were used.
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-22

• The data used to quantify the FeOx and POM sorbents (and the DOM) is

sparse. The degree to which the true variability in concentration levels of these

sorbents has been captured in the modeling is unknown.

• There is no provision in the modeling to account for occlusion of sorbents. Both

ferric oxide and organic matter may form coatings over other surfaces. Failure

to account for occlusion could result in overestimating the available sorption

sites.

• The ferric oxide (goethite) sorbent is included in all model runs. This implies

that it is ubiquitous. However, there are natural ground-water conditions that

preclude the formation of ferric oxide precipitates. As illustrated in Figure B.6,

goethite is not the stable iron solid phase at conditions of low pH and low Eh.

The approximate pH-Eh window of applicability for the model results is outlined

by dashes in this figure. The selection of specific pH targets limits the pH range

(4.5 to 8.2). But no explicit Eh was defined in the model (wavy lines at top and

bottom of window in Figure B.6). The “implied” Eh minimum could be

considered as the level where ferric oxide ceases to be the stable iron phase.

Within the pH range of interest, this implies that the lower left corner of the

window shown in Figure B.6 is inconsistent with the use of goethite as a sorbing

phase. Including the goethite sorbent where it cannot exist could obviously lead

to overestimating sorption. The omission of the stable iron phases siderite and

pyrite as model sorbents serves to compensate for this flaw, although the extent

of this compensation is unknown. The main point of the diagram is not to point

out the stability fields of specific iron minerals but to show the applicability

window for our modeling (framed by pH and Eh) with reference to the general

picture of iron sulfide, carbonate, and hydroxide (or oxide) minerals.

• The Gaussian model for estimating metal interactions with organic matter was

developed for dissolved organic matter. It has not been tested for estimating

the degree of metal sorption onto POM. Also, mean log K values for some

metals have not been measured; estimates were used.

4.3 LEACHATE CHARACTERIZATION ISSUES

• The concentration levels for leachate organic matter were based on a limited

sampling from six municipal landfills. Municipal landfills may have leachate

organic content that is significantly different from that of hazardous waste units.

Hazardous waste leachates may show more variability in total organic carbon

concentration and in the nature of the organic species present.

• Other leachate constituents may be present at elevated concentrations, but

these are not accounted for. Some of these (e.g., Ca, Mg, SO4

, Cl, etc.) may

reduce the amount of metal sorption by competing for adsorption sites

(especially Ca) or by complexing metals so that a greater fraction is retained in

solution (especially SO4 and Cl). Failure to include these effects could result in

overestimating sorption of some metals.
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-23

• Leachate from highly alkaline wastes was not included in the modeling. Highly

alkaline leachates may result in elevation of the ground-water pH above the

upper bound for which isotherms have been computed. Sorption tends to

increase with pH for many metals up to about pH 8 to 9. Above this level,

formation of metal hydroxy solution species may inhibit sorption for some

metals.

• The metal was introduced as a metal salt. The metal species was chosen to

avoid impact on the pH, but some pH effect is unavoidable. Arbitrary changes

in pH due to the choice of metal species may have induced undesired changes

in Kd, especially at high total metal concentrations.

• Methylated forms of metal were not accounted for in this modeling. Mercury

and arsenic are known to undergo methylation in the environment.

4.4 OTHER ISSUES

• The system redox potential was not explicitly defined in the modeling. All

species that might undergo oxidation-reduction reactions were constrained to

remain in the form in which they were entered in the model. This restriction

applied to major ions such as sulfate and to all trace metals. The impact on Kd

is unknown, but is expected to be metal-specific.

• All contaminant metals were introduced separately and individually in the

modeling. The possible simultaneous presence of multiple metals is

unaccounted for. The impact on Kdis not expected to be great except at high

metal concentrations were competition for sorption sites may result in less

sorption for some metals than suggested by this modeling.
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-24

ferric hydroxide

siderite

pyrite ferrous

hydroxide

-600

-400

-200

0

200

400

600

800

1000

2 4 6 8 10 12

pH

E

h (m

v)

Figure B.6 Relevant pH-Eh Window And Stable Iron Phases (after

Hem, 1977).
Appendix B Non-linear Sorption Isotherms Calculated Using the MINTEQA2 Model

B-25

5.0 REFERENCES

Dobbs, J.C., W. Susetyo, L.A. Carreira, and L.V. Azarraga, 1989. Competitive binding

of protons and metal ions in humic substances by lanthanide ion probe

spectroscopy. Analytical Chemistry, 61:1519-1524.

Dzombak, D.A. and F.M.M. Morel, 1990. Surface Complexation Modeling: Hydrous

Ferric Oxide. John Wiley & Sons, New York, 393p.

EPRI, 1986. Physiochemical Measurements of Soils at Solid Waste Disposal Sites.

Electric Power Research Institute, prepared by Battelle, Pacific Northwest

Laboratories, Richland, WA, EPRI EA-4417.

Freeze, R.A. and J.A. Cherry, 1979. Groundwater. Prentice-Hall, Inc., New Jersey,

604p.

Gintautas, P.A., K.A. Huyck, S.R. Daniel, and D.L. Macalady, 1993. Metal-Organic

Interactions in Subtitle D Landfill Leachates and Associated Groundwaters, in

Metals in Groundwaters, H.E. Allen, E.M. Perdue, and D.S. Brown, eds. Lewis

Publishers, Ann Arbor, MI.

Hem, J.D., 1977. Reactions of metal ions at surfaces of metal oxides. Geochimica et

Cosmochimica Acta, 41:527-538.

Mathur, S. S., 1995. Development of a Database for Ion Sorption on Goethite Using

Surface Complexation Modeling. Master’s Thesis, Department of Civil and

Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA.

Susetyo, W., L.A. Carreira, L.V. Azarraga, and D.M. Grimm, 1991. Fluorescence

techniques for metal-humic interactions. Fresenius Jour. Analytical Chemistry,

339:624-635.

Tipping, E., 1994. WHAM– A chemical equilibrium model and computer code for

waters, sediments, and soils incorporating a discrete site/electrostatic model of

ion binding by humic substances. Computers and Geosciences, 20:973-1023.

White, D.E., J.D. Hem, and G.A. Waring, 1963. Data of Geochemistry. U.S.

Geological Survey Professional Paper 440-F, U.S. Government Printing Office,

Washington, DC.
APPENDIX C

PHYSICAL AND CHEMICAL PROPERTIES FOR ORGANIC

CONSTITUENTS
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Appendix C Physical and Chemical Properties for Organic Constituents

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Note: Data sources for chemical property values are indicated in the column

headings; exceptions are noted in parentheses for individual chemical values.

Data sources:

a. http://chemfinder.cambridgesoft.com (CambridgeSoft Corporation, 2001)

b. U.S. EPA, 1997b. Superfund Chemical Data Matrix (SCDM). SCDMWIN 1.0

(SCDM Windows User's Version), Version 1. Office of Solid Waste and

Emergency Response, Washington DC: GPO.

http://www.epa.gov/superfund/resources/scdm/index.htm. Accessed July

2001
Appendix C Physical and Chemical Properties for Organic Constituents

C-10

c. Kollig, H. P. (ed.), 1993. Environmental fate consultants for organic

chemicals under consideration for EPA's hazardous waste identification

projects. Environmental Research Laboratory, Office of R&D, U.S. EPA,

Athens, GA.

d. Calculated based on Water 9. U.S. EPA, 2001. Office of Air Quality Planning

and Standards, Research Triangle Park, NC.

http://www.epa.gov/ttn/chief/software/water/index.html. Accessed July 2001

e. Syracuse Research Corporation (SRC), 1999. CHEMFATE Chemical

Search, Environmental Science Center, Syracuse, NY.

http://esc.syrres.com/efdb/Chemfate.htm. Accessed July 2001.

f. Calculated based on U.S. EPA, 2000. Exposure and Human Health

Reassessment of 2,3,7,8-Tetrachlorodibenzo-p-Dioxin (TCDD) and Related

Compounds, Part 1, Vol. 3. Office of Research and Development,

Washington, DC: GPO.

g. USNLM (U.S. National Library of Medicine), 2001. Hazardous Substances

Data Bank (HSDB). http://toxnet.nlm.nih.gov/cgi-bin/sis/htmlgen/HSDB.

Accessed July 2001.

h. MI DEQ. Environmental response Division Operational Memorandum #18

(Opmemo 18): Part 201 Generic Cleanup Criteria Tables, Revision 1, State

of Michigan, Department of Environmental Quality.

http://www.deq.state.mi.us/erd/opmemo18/index.html.

i. Calculated based on U.S. EPA, 1987. Process Coefficients and Models for

Simulating Toxic Organics and Heavy Metals in Surface Waters. Office of

Research and Development. Washington, DC: US Government Printing

Office (GPO).

j. U.S. EPA, 1999. Region III Soil-to-Groundwater SSLs. Region III,

Philadelphia, PA. http://www.epa.gov/reg3hwmd/risk/ssl.pdf

k. U.S. EPA, 2000. Physical-chemical

Data.http://www.epa.gov/Rgeion9/waste/sfund/prg/index.htm

l. Calculated from octanol-water partition coefficient using regression equation

log[Koc] = 1.029 x log[Kow] - 0.18; presented in Table 10.2 of G. deMarsily,

1986. Quantitative Hydrogeology. Academic Press

m. Lyman, W.J., W.F. Reehl, and D.H. Rosenblatt, 1990. Handbook of

Chemical Property Estimation Methods: Environmental Behavior of Organic

Compounds. Washington, DC: American Chemical Society.
APPENDIX D

WMU AND HYDROGEOLOGIC ENVIRONMENT DATABASES
This page intentionally left blank.
D-i

LIST OF TABLES

Page

Table D.1 Nationwide Database of Landfill Sites . . . . . . . . . . . . . . . . . . . . . D-1

Table D.2 Nationwide Database of Surface Impoundment Sites . . . . . . . . D-18

Table D.3 Nationwide Database of Waste Pile Sites . . . . . . . . . . . . . . . . . D-40

Table D.4 Nationwide Database of Land Application Unit Sites . . . . . . . . . D-59

Table D.5 Hydrogeologic Database for HG Environment 1 . . . . . . . . . . . . D-66

Table D.6 Hydrogeologic Statistics for HG Environment 1 . . . . . . . . . . . . . D-67

Table D.7 Hydrogeologic Database for HG Environment 2 . . . . . . . . . . . . D-67

Table D.8 Hydrogeologic Statistics for HG Environment 2 . . . . . . . . . . . . . D-69

Table D.9 Hydrogeologic Database for HG Environment 3 . . . . . . . . . . . . D-69

Table D.10 Hydrogeologic Statistics for HG Environment 3 . . . . . . . . . . . . . D-70

Table D.11 Hydrogeologic Database for HG Environment 4 . . . . . . . . . . . . D-70

Table D.12 Hydrogeologic Statistics for HG Environment 4 . . . . . . . . . . . . . D-72

Table D.13 Hydrogeologic Database for HG Environment 5 . . . . . . . . . . . . D-72

Table D.14 Hydrogeologic Statistics for HG Environment 5 . . . . . . . . . . . . . D-74

Table D.15 Hydrogeologic Database for HG Environment 6 . . . . . . . . . . . . D-75

Table D.16 Hydrogeologic Statistics for HG Environment 6 . . . . . . . . . . . . . D-76

Table D.17 Hydrogeologic Database for HG Environment 7 . . . . . . . . . . . . D-76

Table D.18 Hydrogeologic Statistics for HG Environment 7 . . . . . . . . . . . . . D-78

Table D.19 Hydrogeologic Database for HG Environment 8 . . . . . . . . . . . . D-78

Table D.20 Hydrogeologic Statistics for HG Environment 8 . . . . . . . . . . . . . D-80

Table D.21 Hydrogeologic Database for HG Environment 9 . . . . . . . . . . . . D-80

Table D.22 Hydrogeologic Statistics for HG Environment 9 . . . . . . . . . . . . . D-81

Table D.23 Hydrogeologic Database for HG Environment 10 . . . . . . . . . . . . D-82

Table D.24 Hydrogeologic Statistics for HG Environment 10 . . . . . . . . . . . . D-83

Table D.25 Hydrogeologic Database for HG Environment 11 . . . . . . . . . . . . D-83

Table D.26 Hydrogeologic Statistics for HG Environment 11 . . . . . . . . . . . . D-84

Table D.27 Hydrogeologic Database for HG Environment 12 . . . . . . . . . . . . D-85

Table D.28 Hydrogeologic Statistics for HG Environment 12 . . . . . . . . . . . . D-86

Table D.29 Hydrogeologic Database for HG Environment 13 . . . . . . . . . . . . D-86
This page intentionally left blank.
Appendix D WMU and Hydrogeologic Environment Databases

D-1

Table D.1 Nationwide Database of Landfill Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate

Center

Site

Weighting

1 3.04E+04 -999 12.5 1 69 1.00

2 2.97E+04 3.12 22.5 5 92 1.00

3 1.35E+04 0.67 22.5 4 58 1.00

4 4.05E+04 1.47 17.5 4 93 1.00

5 2.02E+04 3.85 12.5 2 51 1.00

6 4.45E+05 7.68 12.5 12 85 1.00

7 3.84E+04 0.86 12.5 4 74 1.00

8 1.11E+05 2.08 12.5 2 39 1.00

9 3.24E+04 4.30 12.5 5 51 1.00

10 1.21E+04 0.74 22.5 4 58 1.00

11 6.15E+05 1.02 7.5 2 32 1.00

12 1.63E+04 -999 17.5 13 90 1.00

13 2.02E+04 -999 12.5 12 42 19.63

14 3.04E+04 -999 12.5 1 69 19.63

15 1.21E+04 -999 22.5 4 81 2.69

16 8.09E+04 -999 17.5 2 36 2.69

17 2.02E+03 -999 17.5 1 95 2.69

18 6.07E+04 3.17 12.5 2 39 2.69

19 6.07E+04 0.76 17.5 13 34 2.69

20 1.21E+04 0.68 12.5 12 54 2.69

21 9.31E+03 -999 17.5 1 95 2.69

22 8.09E+03 1.22 17.5 12 89 2.69

23 2.02E+05 1.31 17.5 12 95 2.69

24 3.24E+04 7.67 17.5 4 89 2.69

25 4.05E+04 -999 17.5 5 13 2.69

26 4.86E+03 1.36 12.5 2 39 2.69

27 2.02E+02 -999 7.5 4 43 2.69

28 4.05E+03 4.09 7.5 2 66 2.69

29 2.02E+03 4.42 12.5 4 36 2.69

30 5.06E+03 -999 17.5 2 36 2.69

31 2.02E+04 -999 22.5 12 78 2.69

32 4.86E+04 1.19 17.5 12 85 2.69

33 1.21E+04 6.82 17.5 4 95 2.69

34 6.07E+04 1.78 17.5 5 89 1.00

35 1.09E+05 1.52 12.5 2 74 1.00

36 1.21E+05 -999 12.5 9 42 1.00

37 2.43E+04 1.01 22.5 4 91 1.00

38 1.42E+05 0.69 12.5 4 71 1.00

39 4.05E+03 1.23 12.5 4 39 1.00

40 6.88E+04 1.83 12.5 12 54 1.00

41 3.04E+04 -999 12.5 5 51 1.00

42 3.35E+05 -999 12.5 4 52 1.00

43 2.71E+03 3.05 7.5 4 45 1.00

44 6.07E+04 3.00 7.5 13 49 1.00

45 2.02E+06 2.83 12.5 12 88 1.00

46 1.42E+04 1.17 22.5 4 96 1.00

47 1.42E+04 -999 12.5 2 39 1.00
Appendix D WMU and Hydrogeologic Environment Databases

Table D.1 Nationwide Database of Landfill Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate

Center

Site

Weighting

D-2

48 8.09E+03 7.90 17.5 13 34 1.00

49 8.09E+04 0.55 7.5 4 60 1.00

50 4.05E+04 2.86 17.5 12 85 1.00

51 5.26E+04 2.05 7.5 2 32 1.00

52 2.02E+04 0.98 12.5 8 32 1.00

53 1.01E+05 2.45 12.5 4 52 1.00

54 3.97E+04 2.38 12.5 2 39 1.00

55 1.11E+05 7.47 17.5 12 95 1.00

56 1.34E+04 0.84 12.5 9 73 1.00

57 4.86E+04 -999 12.5 1 71 1.00

58 1.27E+05 1.01 12.5 12 50 1.00

59 9.47E+04 1.75 12.5 1 71 1.00

60 6.07E+04 0.87 12.5 4 71 1.00

61 3.32E+05 5.24 17.5 5 13 1.00

62 2.23E+04 2.02 12.5 5 56 1.00

63 6.96E+04 -999 17.5 12 95 1.00

64 6.07E+04 -999 17.5 1 77 1.00

65 6.88E+04 3.32 12.5 8 75 1.00

66 4.05E+03 2.05 17.5 4 93 1.00

67 5.26E+05 3.64 12.5 4 49 1.00

68 2.87E+04 1.93 17.5 2 36 1.00

69 4.05E+04 7.65 12.5 2 39 1.00

70 7.28E+04 -999 7.5 8 48 1.00

71 1.72E+05 -999 12.5 4 72 1.00

72 1.01E+04 5.37 17.5 12 95 1.00

73 3.14E+04 4.83 12.5 5 3 1.00

74 1.07E+05 5.56 12.5 4 51 1.00

75 5.06E+04 1.77 12.5 2 39 1.00

76 6.92E+04 5.09 17.5 4 23 1.00

77 1.42E+05 -999 12.5 12 71 1.00

78 1.94E+04 1.28 12.5 12 69 1.00

79 7.16E+04 3.93 12.5 9 32 1.00

80 9.31E+04 -999 17.5 12 85 1.00

81 3.24E+05 1.84 12.5 12 42 1.00

82 3.72E+05 -999 12.5 2 69 1.00

83 1.21E+03 3.15 17.5 5 34 1.00

84 4.17E+03 2.78 17.5 2 95 1.00

85 2.51E+05 -999 12.5 12 73 1.00

86 1.35E+05 6.55 12.5 9 42 1.00

87 1.66E+03 7.98 12.5 9 73 1.00

88 1.35E+05 4.09 22.5 4 81 1.00

89 8.09E+04 1.53 12.5 5 40 1.00

90 2.55E+05 7.79 12.5 2 71 1.00

91 4.57E+04 -999 12.5 1 71 1.00

92 3.24E+03 -999 12.5 2 39 1.00

93 2.10E+05 1.26 7.5 13 68 1.00

94 5.67E+04 2.51 12.5 2 52 1.00
Appendix D WMU and Hydrogeologic Environment Databases

Table D.1 Nationwide Database of Landfill Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate

Center

Site

Weighting

D-3

95 5.67E+02 1.29 22.5 12 91 1.00

96 5.54E+05 0.53 12.5 5 26 1.00

97 2.43E+04 4.09 12.5 4 39 1.00

98 9.79E+05 0.54 12.5 12 49 1.00

99 5.26E+04 1.13 17.5 2 95 1.00

100 2.19E+05 3.12 12.5 2 71 1.00

101 2.83E+04 2.34 12.5 2 39 1.00

102 8.09E+03 -999 17.5 1 95 1.00

103 2.27E+05 -999 12.5 12 42 1.00

104 4.05E+03 2.95 12.5 2 53 1.00

105 8.50E+04 2.18 22.5 12 93 1.00

106 7.08E+04 -999 12.5 9 42 1.00

107 2.02E+04 6.71 12.5 12 42 1.00

108 2.43E+04 0.82 7.5 4 66 1.25

109 8.09E+03 -999 17.5 12 95 1.25

110 3.28E+03 1.52 12.5 12 69 1.25

111 1.34E+05 1.99 7.5 13 4 1.25

112 1.62E+04 3.07 12.5 2 88 1.25

113 3.64E+04 1.19 17.5 1 77 1.25

114 4.05E+05 -999 12.5 9 73 1.25

115 2.02E+05 1.31 12.5 12 55 1.25

116 8.09E+02 -999 7.5 13 68 16.22

117 3.24E+04 -999 22.5 12 57 1.00

118 4.86E+04 1.58 22.5 4 92 1.00

119 8.50E+02 -999 12.5 12 50 1.00

120 4.86E+04 -999 22.5 12 91 1.00

121 5.14E+05 -999 7.5 13 5 1.00

122 3.12E+06 -999 22.5 4 92 1.00

123 8.09E+04 -999 12.5 12 71 1.00

124 1.30E+04 1.98 17.5 12 95 1.00

125 2.02E+04 -999 22.5 12 57 1.00

126 4.17E+03 -999 22.5 12 93 1.00

127 2.02E+03 -999 17.5 4 29 1.00

128 1.41E+06 -999 22.5 5 92 1.00

129 1.17E+04 0.65 22.5 13 96 1.00

130 6.07E+04 -999 17.5 4 81 1.00

131 2.23E+05 -999 12.5 2 39 22.01

132 4.05E+04 3.96 22.5 4 92 2.55

133 4.05E+02 -999 17.5 2 36 2.55

134 8.09E+04 -999 17.5 2 89 2.55

135 2.27E+04 5.41 12.5 5 33 2.55

136 2.02E+02 1.36 22.5 13 92 2.55

137 2.14E+05 4.82 7.5 8 31 2.55

138 1.54E+05 -999 22.5 12 78 2.55

139 2.71E+04 0.99 7.5 2 31 1.00

140 8.09E+05 8.18 12.5 2 39 1.00

141 1.00E+06 2.35 22.5 4 58 1.00
Appendix D WMU and Hydrogeologic Environment Databases

Table D.1 Nationwide Database of Landfill Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate

Center

Site

Weighting

D-4

142 7.08E+05 4.24 12.5 5 26 1.00

143 7.16E+05 2.14 17.5 13 90 1.00

144 2.02E+04 -999 12.5 2 52 1.00

145 2.54E+05 2.09 17.5 4 80 1.00

146 1.01E+05 -999 12.5 6 89 1.00

147 2.02E+04 -999 22.5 12 58 1.00

148 5.26E+04 1.01 12.5 2 28 1.00

149 5.26E+02 2.03 22.5 4 96 1.00

150 1.86E+05 1.72 12.5 4 27 1.00

151 6.07E+04 -999 12.5 1 72 1.00

152 2.23E+04 1.36 12.5 5 4 1.00

153 1.72E+06 -999 12.5 2 39 1.00

154 1.21E+05 0.65 22.5 2 91 1.00

155 2.63E+05 -999 12.5 13 73 1.00

156 1.86E+05 -999 12.5 12 73 1.00

157 5.67E+04 -999 12.5 12 42 1.00

158 7.69E+05 3.75 12.5 8 55 1.00

159 1.21E+05 4.36 12.5 2 39 1.00

160 1.62E+06 -999 12.5 5 51 1.00

161 8.09E+03 2.62 12.5 1 63 1.00

162 3.44E+04 6.26 12.5 4 72 1.00

163 6.27E+05 6.55 12.5 2 39 1.00

164 2.23E+04 1.26 17.5 2 93 1.00

165 2.43E+04 1.21 17.5 13 77 1.00

166 4.45E+04 -999 12.5 5 29 1.00

167 1.50E+04 1.58 17.5 12 95 1.00

168 1.97E+06 -999 22.5 4 96 1.00

169 1.21E+06 6.00 12.5 12 49 1.00

170 1.24E+06 2.81 7.5 2 32 1.00

171 2.02E+06 3.96 22.5 4 81 1.00

172 5.10E+05 -999 12.5 2 51 1.00

173 4.86E+04 0.55 12.5 4 40 1.00

174 3.24E+04 -999 22.5 4 92 1.00

175 5.54E+05 -999 12.5 13 56 1.00

176 8.09E+05 7.26 22.5 5 22 1.00

177 8.09E+03 -999 17.5 12 89 1.00

178 2.51E+04 0.96 7.5 1 31 1.00

179 1.62E+06 6.14 7.5 13 49 1.00

180 1.62E+05 -999 7.5 2 11 1.00

181 6.75E+04 1.95 12.5 12 20 1.00

182 2.59E+05 0.76 17.5 4 92 1.00

183 2.67E+05 4.20 17.5 13 34 1.00

184 1.62E+05 7.06 22.5 4 58 1.00

185 2.23E+05 6.32 12.5 2 51 1.00

186 4.65E+03 0.66 7.5 2 7 1.00

187 1.01E+06 -999 12.5 13 73 1.00

188 8.05E+05 1.64 12.5 5 74 1.00
Appendix D WMU and Hydrogeologic Environment Databases

Table D.1 Nationwide Database of Landfill Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate

Center

Site

Weighting

D-5

189 1.86E+06 4.55 12.5 5 51 1.00

190 1.18E+06 6.66 22.5 4 36 1.00

191 2.02E+03 1.32 17.5 2 36 1.00

192 9.92E+04 5.01 12.5 2 85 1.00

193 7.16E+05 2.14 17.5 5 90 1.00

194 1.23E+05 4.29 7.5 4 10 1.00

195 1.46E+04 -999 12.5 9 42 1.00

196 1.66E+05 -999 17.5 4 95 1.00

197 1.62E+04 -999 17.5 4 93 1.00

198 7.08E+05 4.24 12.5 5 26 1.00

199 9.29E+04 -999 17.5 2 89 1.00

200 5.26E+05 3.55 22.5 4 36 1.00

201 1.48E+06 -999 17.5 4 81 1.00

202 6.48E+03 0.51 12.5 12 71 1.00

203 2.02E+04 6.55 12.5 12 87 1.00

204 4.87E+05 -999 12.5 4 51 1.00

205 5.46E+04 5.11 7.5 5 10 1.00

206 1.66E+05 5.99 12.5 8 55 1.00

207 1.21E+05 5.28 17.5 13 34 1.00

208 4.05E+03 1.32 12.5 12 69 1.38

209 1.69E+06 4.98 17.5 4 93 1.38

210 1.25E+05 3.32 12.5 12 54 1.38

211 5.67E+04 1.32 12.5 13 73 1.38

212 2.02E+03 -999 22.5 5 12 1.38

213 4.53E+05 8.04 7.5 4 7 1.38

214 4.05E+03 -999 22.5 4 81 1.38

215 4.05E+04 4.91 12.5 12 19 1.38

216 2.02E+04 -999 7.5 13 10 1.38

217 1.82E+05 3.64 12.5 2 39 1.38

218 1.21E+05 -999 22.5 4 92 1.00

219 8.50E+02 -999 17.5 13 77 7.56

220 9.31E+02 -999 17.5 1 79 7.56

221 2.83E+04 -999 22.5 4 58 1.05

222 7.29E+02 2.36 17.5 4 89 1.00

223 1.42E+04 3.27 17.5 4 80 1.00

224 8.09E+04 4.11 12.5 5 74 1.00

225 8.09E+04 1.23 12.5 12 69 1.00

226 1.66E+04 5.39 12.5 1 77 1.00

227 8.90E+04 1.39 17.5 13 29 1.00

228 2.02E+04 -999 22.5 4 58 1.00

229 8.90E+03 1.23 22.5 4 96 1.00

230 3.24E+04 1.33 12.5 6 73 1.00

231 5.67E+04 2.63 17.5 2 30 1.00

232 4.05E+04 -999 22.5 12 57 1.00

233 6.48E+04 2.76 12.5 4 88 1.00

234 5.67E+02 0.88 17.5 4 89 1.81

235 1.11E+04 -999 12.5 12 85 1.81
Appendix D WMU and Hydrogeologic Environment Databases

Table D.1 Nationwide Database of Landfill Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate

Center

Site

Weighting

D-6

236 7.90E+04 -999 12.5 12 55 1.81

237 4.45E+02 1.12 12.5 13 16 1.81

238 4.05E+03 2.45 12.5 5 39 1.81

239 1.62E+04 -999 17.5 12 95 1.81

240 1.01E+04 -999 12.5 12 54 1.81

241 4.86E+04 -999 12.5 1 88 1.81

242 4.86E+04 -999 12.5 4 71 1.81

243 1.05E+05 -999 17.5 13 34 1.81

244 1.38E+03 3.57 22.5 12 93 1.81

245 1.11E+04 2.20 12.5 4 72 1.81

246 1.94E+04 -999 12.5 12 89 1.00

247 7.69E+04 3.70 17.5 12 89 1.00

248 2.94E+04 -999 17.5 5 13 1.00

249 3.64E+03 3.64 17.5 1 85 1.00

250 4.05E+02 6.55 12.5 1 72 1.00

251 2.02E+04 -999 22.5 4 92 1.00

252 3.80E+04 0.52 22.5 4 35 1.00

253 2.12E+03 -999 17.5 5 89 1.00

254 6.75E+04 1.10 17.5 4 79 1.00

255 4.43E+03 1.03 17.5 12 85 1.00

256 2.63E+04 -999 12.5 4 74 1.00

257 2.02E+04 -999 12.5 13 26 1.00

258 4.25E+04 2.44 17.5 4 93 1.00

259 2.02E+04 -999 22.5 12 57 1.00

260 2.83E+04 3.51 12.5 12 69 1.00

261 6.88E+04 1.20 12.5 4 72 1.00

262 2.02E+04 1.27 22.5 4 81 1.00

263 3.89E+04 3.47 17.5 12 89 1.00

264 2.43E+04 2.97 17.5 12 85 1.00

265 2.63E+05 1.35 17.5 4 89 1.00

266 8.09E+04 1.31 22.5 4 96 1.00

267 1.38E+04 1.14 22.5 4 81 1.00

268 5.22E+03 1.08 12.5 12 49 1.00

269 6.39E+05 -999 12.5 2 87 1.00

270 2.02E+04 0.65 12.5 5 34 1.00

271 1.01E+04 -999 7.5 4 60 1.00

272 7.04E+04 -999 12.5 9 42 1.00

273 3.64E+04 0.68 22.5 12 78 1.00

274 8.09E+03 -999 22.5 12 93 1.00

275 3.24E+04 -999 17.5 13 90 1.00

276 9.29E+04 -999 17.5 4 29 1.00

277 4.04E+04 1.06 12.5 5 40 1.00

278 6.21E+04 1.02 12.5 13 26 1.00

279 5.79E+03 0.80 22.5 4 92 1.00

280 2.02E+04 3.54 22.5 4 81 1.00

281 6.52E+03 1.27 12.5 2 51 1.00

282 8.13E+04 -999 22.5 4 96 1.00
Appendix D WMU and Hydrogeologic Environment Databases

Table D.1 Nationwide Database of Landfill Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate

Center

Site

Weighting

D-7

283 5.26E+04 -999 17.5 5 13 1.00

284 2.12E+06 -999 22.5 5 92 1.00

285 6.07E+04 0.65 17.5 13 81 1.00

286 9.31E+04 2.67 22.5 4 92 1.00

287 2.67E+04 -999 22.5 4 35 1.00

288 4.00E+04 0.69 12.5 4 51 1.00

289 4.05E+04 -999 17.5 5 13 1.00

290 2.23E+04 -999 22.5 12 78 1.00

291 2.02E+04 4.09 7.5 13 5 1.00

292 6.88E+04 8.02 22.5 4 96 1.00

293 3.72E+04 1.33 17.5 4 89 1.00

294 4.35E+04 4.22 17.5 12 89 1.00

295 6.07E+04 2.73 12.5 2 69 1.00

296 8.62E+04 -999 12.5 5 87 1.00

297 6.07E+04 -999 17.5 13 81 1.38

298 2.79E+03 1.98 22.5 6 92 1.38

299 4.05E+03 1.82 17.5 1 77 1.38

300 1.21E+03 -999 12.5 4 72 29.81

301 8.09E+03 -999 22.5 4 92 29.81

302 1.21E+04 -999 12.5 8 42 29.81

303 8.09E+04 4.09 12.5 4 52 29.81

304 1.86E+03 -999 12.5 9 56 29.81

305 8.09E+01 3.03 17.5 1 77 29.81

306 2.02E+03 1.23 22.5 4 91 29.81

307 2.02E+04 -999 22.5 5 21 29.81

308 3.72E+03 0.89 7.5 8 45 29.81

309 8.09E+03 -999 22.5 4 92 29.81

310 2.43E+02 2.05 17.5 12 85 29.81

311 9.31E+02 7.12 12.5 8 46 29.81

312 1.01E+04 -999 12.5 12 73 29.81

313 1.01E+04 -999 22.5 12 57 29.81

314 2.02E+04 1.02 12.5 12 39 29.81

315 8.09E+03 0.61 12.5 5 3 29.81

316 8.09E+01 -999 22.5 12 58 29.81

317 1.62E+05 -999 17.5 13 77 9.25

318 4.05E+04 2.45 22.5 4 92 9.25

319 2.02E+02 -999 17.5 13 1 9.25

320 1.01E+03 -999 17.5 1 95 9.25

321 1.21E+04 -999 22.5 12 57 9.25

322 1.62E+03 -999 12.5 4 19 9.25

323 2.63E+04 4.56 17.5 4 79 9.25

324 6.07E+04 5.46 12.5 13 86 9.25

325 4.05E+03 0.82 12.5 12 42 9.25

326 2.02E+03 -999 17.5 4 89 9.25

327 8.09E+03 -999 17.5 5 34 9.25

328 2.47E+04 -999 12.5 1 84 9.25

329 4.05E+04 -999 12.5 4 74 9.25
Appendix D WMU and Hydrogeologic Environment Databases

Table D.1 Nationwide Database of Landfill Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate

Center

Site

Weighting

D-8

330 6.07E+03 -999 17.5 12 89 9.25

331 8.90E+04 4.09 17.5 5 21 9.25

332 4.45E+02 1.38 12.5 13 29 9.25

333 2.43E+04 3.07 17.5 4 80 9.25

334 6.07E+03 5.73 12.5 4 39 9.25

335 4.05E+03 0.74 17.5 13 34 9.25

336 2.83E+02 2.60 7.5 13 66 9.25

337 2.43E+04 5.11 12.5 2 51 9.25

338 4.05E+01 0.91 22.5 12 76 9.25

339 2.83E+04 4.09 12.5 12 73 9.25

340 4.05E+04 1.32 17.5 13 36 9.25

341 6.07E+04 -999 17.5 1 95 9.25

342 4.05E+03 2.05 17.5 2 36 9.25

343 4.05E+03 1.23 7.5 4 5 9.25

344 9.31E+02 3.69 12.5 2 88 9.25

345 2.02E+02 -999 12.5 9 73 9.25

346 3.90E+04 3.98 7.5 2 31 9.25

347 8.09E+03 -999 17.5 12 85 9.25

348 1.14E+04 0.79 17.5 12 95 9.25

349 6.07E+04 -999 7.5 12 48 9.25

350 2.23E+04 0.77 12.5 4 88 9.25

351 3.04E+03 2.73 17.5 1 79 9.25

352 8.09E+03 -999 17.5 1 79 9.25

353 1.21E+03 -999 22.5 12 57 9.25

354 8.09E+03 -999 17.5 4 95 9.25

355 8.09E+03 -999 17.5 1 95 9.25

356 1.01E+04 0.92 12.5 8 56 9.25

357 4.05E+03 -999 22.5 4 81 9.25

358 4.86E+04 1.26 12.5 2 52 9.25

359 4.05E+01 -999 17.5 5 90 9.25

360 2.43E+04 -999 12.5 8 55 1.00

361 8.09E+03 -999 17.5 4 80 1.00

362 6.07E+03 1.09 22.5 4 12 1.00

363 4.05E+04 -999 22.5 13 12 1.00

364 1.43E+04 1.45 17.5 5 13 1.00

365 1.16E+04 -999 12.5 2 39 1.00

366 8.82E+03 2.38 12.5 5 51 1.00

367 4.05E+04 3.17 12.5 4 51 1.00

368 8.09E+03 6.60 12.5 2 52 1.00

369 4.46E+04 3.97 17.5 1 79 1.00

370 4.05E+03 5.11 22.5 4 96 1.00

371 1.42E+04 -999 22.5 4 12 1.00

372 1.09E+04 4.55 7.5 13 66 1.00

373 3.72E+04 4.46 12.5 5 40 1.00

374 2.55E+04 2.79 7.5 4 60 1.00

375 4.45E+05 5.58 17.5 2 36 1.00

376 2.43E+05 6.82 7.5 4 68 1.00
Appendix D WMU and Hydrogeologic Environment Databases

Table D.1 Nationwide Database of Landfill Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate

Center

Site

Weighting

D-9

377 6.07E+03 6.87 7.5 13 66 1.00

378 6.07E+03 4.09 12.5 4 72 1.00

379 8.09E+03 0.61 17.5 12 89 1.00

380 8.09E+03 3.27 22.5 2 58 1.00

381 5.77E+04 2.77 17.5 1 77 1.00

382 3.24E+05 7.16 7.5 12 50 1.00

383 3.75E+04 -999 12.5 1 61 1.00

384 4.25E+02 -999 7.5 13 66 1.00

385 4.86E+05 -999 7.5 8 48 1.00

386 5.67E+04 1.05 17.5 10 79 1.00

387 1.26E+05 -999 22.5 4 12 1.00

388 8.09E+03 0.59 12.5 1 61 1.00

389 2.83E+04 3.11 7.5 2 50 1.00

390 2.63E+05 3.78 12.5 12 42 1.00

391 1.62E+05 4.50 17.5 4 79 1.00

392 1.38E+03 3.01 12.5 2 71 1.00

393 1.62E+05 2.56 17.5 5 21 1.00

394 1.05E+05 -999 12.5 12 49 1.00

395 1.02E+04 3.83 12.5 4 39 1.00

396 4.45E+03 3.95 12.5 12 71 1.00

397 1.82E+04 7.07 12.5 2 66 1.00

398 3.24E+04 0.77 12.5 13 72 1.00

399 3.84E+05 6.46 12.5 4 51 1.00

400 4.86E+04 5.11 12.5 12 39 1.00

401 2.23E+05 5.28 22.5 4 14 1.00

402 2.23E+04 1.12 12.5 12 54 1.00

403 5.67E+04 -999 12.5 2 55 1.00

404 1.01E+05 5.24 17.5 2 36 1.00

405 4.05E+03 -999 22.5 12 58 1.00

406 1.01E+04 -999 17.5 5 13 1.00

407 3.91E+04 2.93 17.5 4 89 1.00

408 1.01E+04 -999 17.5 5 34 1.00

409 9.31E+04 1.78 17.5 12 85 1.00

410 1.67E+04 2.18 12.5 4 39 1.00

411 1.62E+04 -999 12.5 12 49 1.00

412 8.09E+04 -999 17.5 4 79 1.00

413 1.21E+04 -999 12.5 2 39 1.00

414 1.16E+04 -999 12.5 5 39 1.00

415 2.79E+04 2.20 17.5 13 90 1.00

416 2.31E+04 -999 12.5 2 39 1.00

417 1.63E+04 3.81 22.5 13 36 1.00

418 8.09E+03 -999 12.5 2 39 1.33

419 1.27E+04 -999 12.5 12 77 1.33

420 4.45E+04 -999 17.5 4 30 1.33

421 2.59E+03 8.31 12.5 4 52 1.33

422 4.86E+03 3.20 12.5 5 26 1.33

423 8.09E+03 0.82 17.5 2 89 1.33
Appendix D WMU and Hydrogeologic Environment Databases

Table D.1 Nationwide Database of Landfill Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate

Center

Site

Weighting

D-10

424 2.02E+03 -999 17.5 13 36 1.33

425 5.26E+02 1.87 12.5 2 52 1.33

426 3.48E+04 -999 7.5 13 39 1.33

427 5.26E+04 -999 7.5 5 10 1.33

428 2.17E+05 0.53 12.5 5 87 1.33

429 4.05E+04 -999 17.5 12 95 1.33

430 1.21E+05 2.18 17.5 13 34 1.33

431 7.35E+04 6.76 12.5 4 74 1.33

432 2.23E+04 4.46 17.5 12 95 1.33

433 8.09E+03 -999 22.5 2 36 1.33

434 4.05E+03 -999 22.5 4 92 1.33

435 4.05E+04 -999 12.5 2 54 1.33

436 1.21E+05 -999 12.5 5 56 1.33

437 1.05E+05 5.35 12.5 2 53 1.33

438 3.72E+03 1.13 12.5 2 51 1.33

439 3.44E+04 -999 17.5 4 81 1.33

440 2.43E+04 -999 17.5 2 30 1.33

441 8.09E+03 -999 12.5 12 85 1.33

442 6.07E+04 -999 17.5 5 54 1.33

443 2.02E+04 2.05 12.5 13 72 1.33

444 4.05E+03 -999 17.5 1 95 1.33

445 5.26E+03 -999 17.5 5 12 1.33

446 2.43E+05 3.48 12.5 9 73 1.33

447 2.83E+02 -999 22.5 12 57 1.33

448 7.53E+04 0.79 17.5 13 37 1.33

449 1.21E+04 -999 22.5 12 58 1.33

450 6.07E+03 -999 12.5 1 72 1.33

451 1.21E+04 -999 7.5 12 53 1.33

452 4.86E+03 0.81 12.5 2 39 1.33

453 8.09E+03 -999 12.5 12 49 1.33

454 1.98E+05 -999 12.5 12 71 1.33

455 4.86E+04 5.11 12.5 2 88 1.33

456 4.05E+04 -999 12.5 2 50 1.33

457 8.09E+03 -999 12.5 4 74 1.33

458 3.36E+03 -999 7.5 2 53 1.33

459 2.02E+06 -999 7.5 2 53 1.33

460 6.07E+03 -999 22.5 2 58 1.33

461 9.07E+04 5.11 12.5 13 73 1.33

462 3.24E+03 -999 22.5 4 12 1.33

463 2.02E+04 -999 12.5 12 42 1.33

464 4.05E+04 -999 7.5 8 65 1.33

465 1.01E+05 1.28 17.5 4 79 1.33

466 3.34E+04 7.93 17.5 12 85 1.33

467 3.24E+05 2.64 17.5 2 36 1.33

468 7.45E+03 -999 17.5 12 95 1.33

469 1.05E+05 0.97 12.5 12 88 1.33

470 3.24E+04 -999 17.5 13 37 1.33
Appendix D WMU and Hydrogeologic Environment Databases

Table D.1 Nationwide Database of Landfill Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate

Center

Site

Weighting

D-11

471 2.70E+04 2.28 17.5 13 34 1.33

472 3.24E+05 1.53 17.5 4 30 1.33

473 4.86E+04 -999 12.5 13 68 1.33

474 3.04E+04 4.58 12.5 13 56 1.33

475 2.43E+04 -999 17.5 13 37 1.33

476 1.86E+04 -999 12.5 2 51 1.33

477 1.56E+05 2.92 12.5 13 56 1.33

478 4.86E+05 0.53 7.5 2 17 1.33

479 4.05E+04 1.31 12.5 2 51 1.33

480 2.32E+04 3.56 17.5 13 13 1.00

481 1.66E+05 -999 7.5 13 3 1.00

482 2.02E+04 -999 12.5 12 69 1.00

483 1.21E+05 0.55 17.5 2 30 1.00

484 5.46E+04 3.54 12.5 4 74 7.48

485 1.49E+05 4.45 7.5 13 50 7.48

486 1.92E+04 1.49 22.5 4 92 7.48

487 1.82E+04 1.27 12.5 8 46 7.48

488 6.07E+03 6.78 12.5 4 74 7.48

489 1.30E+05 -999 17.5 5 90 7.48

490 3.44E+04 -999 12.5 7 29 7.48

491 3.64E+04 1.59 12.5 5 24 7.48

492 5.18E+04 2.56 22.5 4 96 1.00

493 5.26E+04 1.06 17.5 4 79 1.00

494 1.34E+05 6.20 7.5 1 44 1.00

495 5.87E+04 0.56 17.5 4 93 1.00

496 3.52E+05 2.63 7.5 1 31 1.00

497 2.19E+05 -999 22.5 4 92 1.00

498 7.08E+04 -999 22.5 4 96 1.00

499 7.32E+04 -999 7.5 4 31 1.00

500 4.05E+05 0.63 22.5 13 81 1.00

501 3.84E+04 1.94 7.5 2 50 1.00

502 1.75E+04 2.52 22.5 12 92 1.00

503 1.79E+05 2.83 12.5 12 69 1.00

504 8.09E+04 -999 17.5 4 92 1.00

505 1.84E+05 3.15 17.5 12 89 1.00

506 4.05E+04 2.89 17.5 1 95 1.00

507 2.52E+06 1.77 17.5 13 34 1.00

508 1.21E+05 -999 17.5 4 93 1.00

509 1.58E+05 2.35 7.5 2 31 1.00

510 1.36E+04 1.42 17.5 2 87 1.00

511 6.88E+03 3.95 22.5 12 78 1.00

512 1.05E+05 7.87 22.5 12 78 1.00

513 7.01E+04 2.00 22.5 12 91 1.00

514 2.02E+05 -999 17.5 12 85 1.00

515 1.92E+06 0.79 17.5 4 93 1.00

516 2.43E+04 -999 22.5 4 92 1.00

517 1.62E+05 -999 17.5 4 92 1.00
Appendix D WMU and Hydrogeologic Environment Databases

Table D.1 Nationwide Database of Landfill Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate

Center

Site

Weighting

D-12

518 1.21E+05 2.18 7.5 4 50 1.00

519 1.82E+05 0.84 7.5 13 43 1.00

520 1.24E+04 1.94 17.5 4 90 1.00

521 1.62E+05 -999 17.5 2 80 1.00

522 3.72E+05 1.32 22.5 12 78 1.00

523 1.78E+05 4.65 12.5 2 28 1.00

524 8.09E+04 -999 12.5 2 66 1.00

525 9.31E+04 4.66 7.5 8 41 1.00

526 1.09E+05 7.58 7.5 8 62 1.00

527 6.56E+04 3.27 7.5 2 50 1.00

528 5.38E+04 7.38 7.5 2 50 1.00

529 1.49E+05 7.80 17.5 4 95 1.00

530 1.46E+05 1.32 17.5 4 95 1.00

531 1.21E+05 2.38 17.5 12 95 1.00

532 1.62E+05 3.07 7.5 4 45 1.00

533 5.80E+04 2.47 22.5 4 92 1.00

534 1.52E+04 -999 22.5 4 92 1.00

535 2.29E+04 -999 12.5 5 24 1.00

536 2.02E+03 -999 12.5 4 52 1.00

537 9.15E+04 3.62 22.5 4 96 1.00

538 8.09E+04 -999 17.5 4 93 1.00

539 2.53E+04 6.55 12.5 13 40 1.00

540 8.09E+03 2.86 12.5 2 40 1.00

541 2.43E+04 0.83 12.5 12 39 1.00

542 2.38E+04 5.22 12.5 2 82 1.00

543 2.70E+04 -999 17.5 1 85 1.00

544 1.62E+04 2.86 7.5 2 31 1.00

545 4.86E+04 4.33 7.5 1 47 1.00

546 1.23E+05 2.68 17.5 4 89 1.00

547 2.02E+05 -999 12.5 4 51 1.00

548 4.05E+04 3.60 12.5 8 46 1.00

549 1.62E+05 6.14 22.5 12 91 1.00

550 1.25E+05 2.65 17.5 2 81 1.00

551 1.21E+05 2.21 17.5 4 93 1.00

552 2.02E+04 1.15 7.5 4 25 1.00

553 6.48E+04 4.06 7.5 2 50 1.00

554 4.33E+04 3.29 22.5 4 81 1.00

555 1.42E+05 3.04 17.5 4 80 1.00

556 6.07E+04 6.55 7.5 1 62 1.00

557 3.72E+05 -999 17.5 4 81 1.00

558 1.19E+06 2.61 7.5 2 50 1.00

559 6.07E+05 6.34 17.5 4 92 1.00

560 1.21E+05 3.14 12.5 4 52 1.00

561 3.64E+04 2.43 12.5 12 54 1.00

562 1.62E+05 1.23 12.5 8 32 1.00

563 2.02E+04 -999 7.5 1 31 1.00

564 6.48E+04 1.79 17.5 5 89 1.00
Appendix D WMU and Hydrogeologic Environment Databases

Table D.1 Nationwide Database of Landfill Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate

Center

Site

Weighting

D-13

565 9.96E+04 1.93 17.5 5 81 1.00

566 5.06E+04 0.93 7.5 4 25 1.00

567 1.42E+05 1.17 17.5 4 81 1.00

568 8.09E+04 -999 7.5 2 48 1.00

569 2.02E+05 2.95 12.5 1 9 1.00

570 2.83E+05 5.84 7.5 1 44 1.00

571 2.02E+04 1.23 12.5 4 82 1.00

572 6.07E+05 1.85 17.5 5 81 1.00

573 1.98E+05 1.82 22.5 12 78 1.00

574 7.28E+05 2.73 17.5 1 85 1.00

575 6.68E+04 2.16 22.5 12 78 1.00

576 4.05E+05 0.52 12.5 4 74 1.00

577 1.35E+04 1.43 17.5 2 87 1.00

578 2.02E+05 0.82 7.5 2 50 1.00

579 5.67E+04 4.24 12.5 1 63 1.00

580 1.62E+05 2.86 12.5 13 24 1.00

581 2.83E+04 -999 17.5 1 95 1.00

582 1.23E+06 -999 17.5 2 80 1.00

583 1.62E+05 2.66 22.5 4 91 1.00

584 1.08E+04 -999 12.5 2 71 1.00

585 2.63E+04 2.97 7.5 4 50 1.00

586 1.92E+04 1.49 22.5 4 92 1.00

587 2.02E+05 1.38 12.5 8 32 1.00

588 3.97E+05 5.62 12.5 4 66 1.00

589 3.37E+04 -999 17.5 5 90 1.00

590 3.24E+04 5.16 17.5 4 93 1.00

591 1.34E+05 2.29 7.5 1 31 1.00

592 1.21E+05 2.86 12.5 13 40 1.00

593 1.66E+05 -999 22.5 12 78 1.00

594 5.67E+05 4.09 17.5 4 95 1.33

595 2.37E+04 1.58 17.5 5 90 1.33

596 6.07E+04 4.09 17.5 4 95 1.33

597 8.90E+04 2.10 17.5 5 90 1.33

598 4.86E+04 2.73 7.5 2 50 1.33

599 4.86E+04 4.48 12.5 1 69 1.33

600 3.31E+04 1.71 17.5 12 92 1.33

601 1.05E+06 0.90 7.5 13 48 1.33

602 1.42E+04 4.68 12.5 12 84 1.33

603 3.24E+05 4.09 7.5 8 32 1.33

604 9.31E+02 1.32 17.5 2 89 4.42

605 8.09E+03 -999 17.5 12 95 4.42

606 1.01E+04 0.65 12.5 2 4 4.42

607 1.38E+04 1.06 17.5 13 34 4.42

608 8.09E+03 -999 17.5 12 89 4.42

609 1.63E+05 -999 22.5 5 21 4.42

610 4.86E+02 0.71 12.5 5 40 4.42

611 7.08E+04 5.28 12.5 9 73 4.42
Appendix D WMU and Hydrogeologic Environment Databases

Table D.1 Nationwide Database of Landfill Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate

Center

Site

Weighting

D-14

612 1.66E+03 2.59 22.5 12 58 4.42

613 4.05E+03 -999 7.5 4 60 4.42

614 4.05E+04 8.18 12.5 8 9 1.00

615 2.02E+03 7.39 12.5 4 40 1.00

616 1.78E+05 2.79 17.5 4 29 1.00

617 1.13E+04 2.57 12.5 1 9 1.00

618 4.05E+03 -999 17.5 12 89 1.00

619 7.49E+04 -999 17.5 2 89 1.00

620 9.66E+04 -999 22.5 4 58 1.00

621 5.67E+03 7.95 12.5 12 73 1.00

622 4.05E+04 -999 12.5 2 54 1.00

623 4.05E+04 -999 22.5 2 21 1.00

624 1.21E+05 -999 7.5 4 43 1.00

625 2.02E+04 0.82 12.5 1 8 1.00

626 1.01E+05 -999 12.5 5 26 1.00

627 4.45E+04 4.69 12.5 8 46 1.00

628 1.54E+04 4.55 12.5 8 42 1.00

629 5.36E+04 0.93 22.5 2 22 1.00

630 7.69E+04 1.63 17.5 12 89 1.00

631 4.05E+04 -999 17.5 1 95 1.00

632 1.36E+04 -999 17.5 2 87 1.00

633 1.62E+04 3.58 12.5 12 49 1.00

634 1.13E+04 2.59 12.5 8 9 1.00

635 1.62E+04 -999 17.5 4 93 1.00

636 8.09E+03 2.32 12.5 12 72 1.00

637 8.09E+03 -999 12.5 5 51 1.00

638 1.75E+04 -999 12.5 5 26 1.00

639 8.26E+04 -999 12.5 8 8 1.00

640 1.62E+04 5.11 7.5 4 25 1.00

641 8.50E+04 1.21 7.5 4 60 1.00

642 2.00E+04 -999 12.5 4 20 1.00

643 3.04E+05 0.91 22.5 4 58 1.00

644 2.02E+04 -999 17.5 1 95 1.00

645 1.21E+04 -999 12.5 12 54 1.00

646 1.30E+05 2.56 12.5 6 89 1.00

647 5.40E+04 6.14 22.5 12 91 1.00

648 9.61E+04 -999 22.5 4 58 1.00

649 7.89E+05 3.36 17.5 4 90 1.00

650 2.02E+05 3.27 12.5 2 52 1.36

651 1.06E+04 -999 12.5 12 71 1.36

652 2.43E+04 0.55 12.5 5 40 1.36

653 2.02E+03 -999 7.5 4 83 30.19

654 2.02E+03 -999 22.5 2 22 30.19

655 1.21E+05 -999 22.5 12 91 30.19

656 1.21E+02 0.68 17.5 4 36 30.19

657 1.82E+04 1.36 17.5 13 13 11.28

658 7.90E+04 3.88 22.5 12 91 11.28
Appendix D WMU and Hydrogeologic Environment Databases

Table D.1 Nationwide Database of Landfill Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate

Center

Site

Weighting

D-15

659 1.42E+04 3.10 17.5 1 77 1.00

660 4.05E+04 2.05 12.5 7 29 1.00

661 1.00E+04 8.25 12.5 6 73 1.00

662 7.49E+02 0.92 17.5 4 23 1.00

663 5.26E+04 7.40 17.5 13 13 1.00

664 2.27E+05 7.31 12.5 6 73 1.00

665 2.63E+04 -999 12.5 1 5 1.00

666 5.46E+04 3.15 12.5 6 74 1.00

667 8.09E+03 -999 12.5 5 9 1.00

668 1.48E+04 1.67 17.5 4 89 1.00

669 4.98E+03 -999 17.5 5 90 1.00

670 6.48E+04 0.80 17.5 1 77 1.00

671 4.86E+03 -999 12.5 12 87 1.00

672 3.89E+05 1.49 22.5 4 96 1.00

673 3.64E+05 -999 7.5 2 32 1.37

674 2.43E+04 2.73 12.5 8 83 1.37

675 2.32E+04 -999 22.5 4 92 1.37

676 1.42E+05 -999 17.5 2 36 1.37

677 4.05E+04 4.09 22.5 12 93 1.37

678 6.07E+04 -999 12.5 2 39 24.00

679 9.11E+04 -999 12.5 13 24 24.00

680 2.79E+03 -999 17.5 12 85 1.89

681 9.31E+02 -999 17.5 5 13 1.89

682 2.95E+03 3.34 12.5 2 51 1.89

683 1.62E+05 0.87 17.5 12 85 1.89

684 4.65E+04 1.58 12.5 4 66 1.89

685 8.09E+03 -999 7.5 2 60 1.89

686 1.67E+04 3.47 12.5 12 87 1.00

687 1.42E+05 -999 22.5 12 76 1.00

688 3.52E+03 1.96 12.5 4 66 1.00

689 4.69E+03 1.59 12.5 5 3 1.00

690 2.19E+04 -999 17.5 4 20 1.00

691 1.01E+05 1.32 17.5 5 13 1.27

692 4.05E+03 -999 12.5 2 69 1.27

693 2.83E+04 0.88 22.5 4 96 1.00

694 1.66E+04 -999 12.5 12 69 1.00

695 4.05E+03 -999 22.5 12 92 1.00

696 9.41E+03 0.88 12.5 5 19 1.00

697 4.05E+03 1.06 22.5 4 81 1.00

698 2.27E+04 0.99 17.5 13 37 1.00

699 2.43E+03 2.94 22.5 4 58 1.00

700 1.38E+03 -999 22.5 4 35 1.00

701 2.02E+03 -999 17.5 4 81 1.00

702 8.34E+02 3.97 17.5 4 29 1.00

703 1.62E+04 0.99 22.5 4 96 1.00

704 2.02E+04 -999 12.5 5 27 1.00

705 8.36E+03 -999 7.5 4 7 1.00
Appendix D WMU and Hydrogeologic Environment Databases

Table D.1 Nationwide Database of Landfill Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate

Center

Site

Weighting

D-16

706 2.43E+04 -999 17.5 5 34 1.00

707 4.05E+03 3.27 7.5 2 31 1.00

708 1.63E+04 3.38 22.5 4 92 1.00

709 7.28E+04 2.05 12.5 12 54 1.00

710 2.43E+04 1.32 12.5 8 46 1.00

711 4.18E+04 5.74 12.5 12 54 1.00

712 3.64E+04 2.05 22.5 4 92 1.00

713 4.05E+04 0.98 12.5 4 74 1.00

714 3.04E+04 -999 12.5 8 46 1.00

715 3.04E+05 -999 22.5 4 96 1.00

716 1.62E+04 0.85 17.5 4 23 1.00

717 3.84E+04 -999 17.5 4 80 1.00

718 2.02E+03 1.33 17.5 4 29 1.00

719 2.36E+04 1.18 17.5 13 29 1.00

720 6.21E+02 -999 12.5 2 19 1.00

721 1.01E+05 5.73 12.5 12 73 1.00

722 1.62E+04 -999 17.5 4 95 1.00

723 8.09E+04 -999 17.5 4 20 1.00

724 1.42E+04 1.04 12.5 5 26 1.00

725 4.05E+04 -999 17.5 4 93 1.17

726 4.05E+03 2.05 12.5 2 39 1.17

727 4.65E+04 -999 12.5 5 40 1.17

728 3.24E+02 -999 12.5 2 52 1.17

729 8.09E+03 -999 17.5 4 95 1.17

730 1.52E+05 3.27 7.5 13 68 10.23

731 5.67E+04 2.63 17.5 2 30 10.23

732 2.48E+03 -999 7.5 1 47 10.23

733 1.11E+04 -999 12.5 2 50 1.00

734 2.43E+04 1.91 12.5 2 71 1.00

735 1.66E+05 7.98 12.5 8 32 1.00

736 1.02E+06 0.65 12.5 5 51 1.00

737 1.36E+05 -999 12.5 5 34 1.00

738 1.21E+04 1.09 17.5 1 95 1.00

739 8.09E+04 -999 12.5 12 42 1.00

740 3.10E+04 0.94 12.5 2 52 1.00

741 1.62E+04 -999 7.5 8 32 1.00

742 1.62E+04 -999 17.5 2 90 1.36

743 2.02E+05 1.74 17.5 5 13 1.36

744 1.01E+05 -999 17.5 5 23 1.36

745 1.82E+04 2.83 12.5 5 74 1.36

746 6.07E+02 -999 22.5 2 36 1.36

747 1.82E+04 3.00 17.5 4 93 1.36

748 1.78E+04 0.83 12.5 2 39 1.36

749 4.05E+04 2.36 7.5 4 60 1.36

750 7.90E+04 -999 7.5 12 42 1.36

751 3.34E+04 4.46 12.5 9 74 1.36

752 3.04E+04 2.02 22.5 4 96 1.36
Appendix D WMU and Hydrogeologic Environment Databases

Table D.1 Nationwide Database of Landfill Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate

Center

Site

Weighting

D-17

753 4.05E+03 -999 12.5 2 54 1.36

754 3.72E+03 -999 12.5 12 49 1.36

755 2.43E+04 2.14 12.5 2 74 1.36

756 2.31E+05 -999 7.5 2 32 1.00

757 1.86E+04 0.79 17.5 12 89 1.00

758 1.62E+04 1.32 12.5 12 69 1.00

759 1.82E+04 -999 12.5 13 40 1.00

760 8.09E+04 0.53 22.5 4 96 1.00

761 5.26E+04 -999 22.5 4 96 1.00

762 4.25E+04 -999 22.5 4 96 1.00

763 7.69E+03 1.08 12.5 5 51 1.00

764 1.62E+04 2.86 12.5 2 39 1.00

765 5.67E+04 4.38 22.5 12 91 1.00

766 2.63E+05 0.76 22.5 4 96 1.00

767 8.09E+03 1.02 17.5 1 77 1.00

768 3.64E+04 -999 17.5 4 93 1.00

769 5.95E+04 2.27 17.5 2 93 1.00

770 2.32E+04 1.28 17.5 4 80 1.00

771 1.58E+05 -999 12.5 4 72 1.00

772 2.83E+04 -999 17.5 4 80 1.00

773 8.50E+04 2.92 22.5 2 36 1.00

774 1.21E+05 -999 17.5 4 89 6.82

775 2.43E+05 -999 17.5 4 93 6.82

776 1.82E+04 1.24 17.5 1 85 1.00

777 1.62E+04 2.05 12.5 12 69 1.00

778 1.27E+04 3.34 17.5 1 79 1.00

779 6.07E+03 -999 17.5 1 85 1.00

780 4.29E+04 1.48 17.5 12 85 1.00

781 1.52E+05 1.82 17.5 1 85 1.00

782 1.01E+04 3.14 17.5 1 95 1.00

783 7.97E+03 -999 17.5 4 93 1.00

784 8.09E+03 -999 17.5 4 79 1.00

785 8.09E+03 -999 17.5 1 79 1.00

786 2.43E+05 -999 17.5 12 95 1.00

787 8.09E+03 0.82 7.5 1 31 3.09

788 1.34E+03 1.98 7.5 4 84 3.09

789 6.48E+04 1.84 7.5 8 44 1.00

790 1.21E+04 -999 7.5 8 62 1.36
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

1 6.31E+02 2.13 0.00 0.2 12.5 110 50 1 6 

2 9.39E+03 1.22 0.00 0.2 17.5 5000 50 1 5 

3 9.75E+03 2.44 0.00 0.2 17.5 5000 50 1 5 

4 2.20E+04 2.44 0.00 0.2 17.5 5000 50 1 5 

5 2.93E+04 3.54 5.98 0.2 17.5 5000 50 1 5 

6 8.83E+02 0.61 1.22 0.2 12.5 120 50 2 10 

7 5.81E+03 0.61 1.22 0.2 12.5 110 50 2 10 

8 1.68E+03 6.25 7.32 0.2 12.5 900 7 3 2 

D-18

9 2.59E+05 0.76 1.52 0.2 17.5 1450 22 1 1 

10 3.60E+05 10.97 9.30 0.2 17.5 100 42 3 1 

11 6.56E+04 6.10 8.53 0.2 17.5 625 50 3 1 

12 4.05E+05 5.33 14.48 0.2 17.5 75 50 3 1 

13 1.25E+05 8.53 2.29 0.2 17.5 960 50 3 1 

14 3.24E+05 5.33 12.04 0.2 17.5 125 50 3 1 

15 6.60E+04 8.84 9.60 0.2 17.5 775 50 3 1 

16 2.59E+05 6.10 7.32 0.2 17.5 350 50 3 1 

17 2.93E+03 -999 0.00 0.2 17.5 150 50 3 10 

18 2.69E+03 3.66 4.57 0.2 17.5 1600 50 3 10 

19 1.67E+04 3.66 4.57 0.2 17.5 1600 50 3 10 

20 2.69E+03 3.66 4.57 0.2 17.5 1600 50 3 10 

21 5.40E+02 -999 0.00 0.2 12.5 5000 41 2 8 

22 4.05E+03 3.66 4.57 0.2 17.5 5000 23 3 1 

23 1.17E+04 3.20 3.81 0.2 17.5 5000 50 3 1 

24 4.05E+03 3.66 6.10 0.2 17.5 5000 23 3 1 

25 3.72E+04 1.68 8.23 0.2 17.5 5000 50 3 1 

26 2.42E+03 1.25 3.94 0.2 22.5 20 24 3 10 

27 3.07E+03 1.83 2.19 0.2 22.5 55 22 3 10 
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

28 7.66E+02 2.29 2.29 0.2 22.5 5000 47 1 10 

29 1.52E+02 0.76 1.37 0.2 22.5 5000 17 1 10 

30 5.81E+02 1.83 0.00 0.2 17.5 190 50 1 6 

31 2.32E+03 1.52 2.44 0.2 12.5 115 50 1 2 

32 7.90E+03 0.61 1.52 0.2 12.5 40 27 3 2 

33 1.62E+04 3.51 1.95 0.2 22.5 5000 50 3 10 

34 1.62E+04 3.51 1.95 0.2 22.5 5000 50 3 10 

35 1.21E+04 4.27 1.37 0.2 17.5 410 50 3 6 

D-19

36 4.80E+05 4.80 1.30 0.2 17.5 90 50 3 6 

37 1.21E+05 6.10 1.68 0.2 17.5 50 50 3 6 

38 1.49E+05 4.57 0.00 0.2 17.5 65 50 3 6 

39 7.69E+03 4.27 0.46 0.2 17.5 65 50 3 6 

40 1.02E+05 4.57 2.59 0.2 17.5 65 50 3 6 

41 2.00E+03 1.07 0.61 0.2 7.5 120 50 1 7 

42 2.58E+03 2.44 1.07 0.2 7.5 130 50 1 7 

43 2.58E+03 2.44 1.07 0.2 7.5 145 50 1 7 

44 2.53E+03 2.74 1.07 0.2 7.5 145 50 1 7 

45 1.21E+05 3.12 0.00 0.2 17.5 85 50 1 7 

46 2.75E+05 -999 0.00 0.2 17.5 300 50 1 7 

47 1.11E+06 0.34 0.00 0.2 17.5 85 50 1 7 

48 3.54E+02 -999 0.00 0.2 12.5 20 50 1 2 

49 4.87E+02 0.68 0.00 0.2 12.5 20 50 1 2 

50 6.07E+03 4.18 3.87 0.2 12.5 695 50 3 9 

51 1.42E+04 1.52 0.00 0.2 12.5 330 50 3 9 
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

52 6.07E+03 4.18 3.87 0.2 12.5 710 50 3 9 

53 1.42E+04 3.66 1.83 0.2 12.5 620 50 3 9 

54 1.35E+03 3.66 1.83 0.2 12.5 575 50 3 9 

55 1.35E+03 3.66 1.83 0.2 12.5 590 50 3 9 

56 2.02E+04 4.13 3.61 0.2 12.5 530 50 3 9 

57 6.06E+03 1.52 0.40 0.2 7.5 20 50 2 6 

58 6.04E+03 1.63 0.38 0.2 7.5 60 50 2 6 

59 4.05E+05 2.43 0.00 0.2 12.5 25 50 3 7 

D-20

60 1.01E+06 2.58 0.00 0.2 12.5 25 50 3 7 

61 1.62E+03 2.28 0.00 0.2 12.5 5000 57 3 7 

62 2.02E+02 2.74 0.00 0.2 12.5 5000 50 3 7 

63 6.97E+02 2.28 5.72 0.2 12.5 20 50 1 2 

64 1.04E+03 0.03 0.52 0.2 22.5 1520 50 2 4 

65 1.49E+03 1.22 1.83 0.2 12.5 20 31 3 12 

66 1.39E+02 0.30 1.98 0.2 12.5 20 50 3 12 

67 1.23E+03 1.47 0.00 0.2 12.5 90 5 3 12 

68 2.79E+01 0.61 0.00 0.2 12.5 140 50 3 12 

69 5.06E+04 1.49 3.63 0.2 17.5 1200 50 1 10 

70 1.62E+03 0.46 2.74 0.2 17.5 1100 55 1 10 

71 1.62E+03 1.74 0.61 0.2 17.5 750 55 1 10 

72 4.86E+03 0.46 6.10 0.2 17.5 930 65 1 10 

73 4.86E+03 -999 4.45 0.2 17.5 1600 65 1 10 

74 1.82E+04 1.07 3.51 0.2 17.5 1700 65 1 10 
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

75 4.05E+03 1.98 2.59 0.2 17.5 5000 50 1 10 

76 1.86E+03 -999 0.00 0.2 17.5 5000 5 1 10 

77 6.99E+03 1.31 2.23 0.2 17.5 700 50 1 10 

78 9.68E+03 1.07 8.08 0.2 17.5 1100 50 1 10 

79 5.26E+04 3.89 2.44 0.2 17.5 5000 36 1 10 

80 4.45E+04 4.43 1.83 0.2 17.5 1900 35 1 10 

81 9.31E+03 1.37 2.44 0.2 17.5 700 65 1 10 

82 5.30E+03 2.18 0.91 0.2 7.5 5000 16 3 4 

D-21

83 5.23E+03 4.57 2.74 0.2 7.5 5000 50 3 4 

84 4.46E+03 3.05 1.22 0.2 7.5 5000 50 3 4 

85 3.57E+03 0.61 1.52 0.2 7.5 5000 50 3 4 

86 8.88E+03 4.27 2.74 0.2 7.5 5000 50 3 4 

87 8.76E+03 3.05 3.05 0.2 7.5 5000 50 3 4 

88 4.06E+03 2.13 1.52 0.2 7.5 5000 50 3 4 

89 1.74E+05 4.55 3.51 0.2 22.5 200 50 3 6 

90 1.29E+05 2.26 1.07 0.2 22.5 50 50 3 6 

91 1.86E+04 3.35 4.27 0.2 17.5 255 32 3 7 

92 1.53E+03 1.37 2.90 0.2 17.5 180 27 3 7 

93 2.63E+05 0.30 1.07 0.2 17.5 1220 50 3 10 

94 1.94E+04 3.05 3.66 0.2 17.5 5000 50 3 10 

95 1.62E+04 4.05 5.18 0.2 17.5 5000 50 3 10 

96 3.48E+04 3.05 3.66 0.2 17.5 5000 50 3 10 

97 1.21E+03 3.12 3.66 0.2 17.5 5000 50 3 10 
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

98 1.21E+03 5.49 3.05 0.2 17.5 0 50 1 10 

99 8.58E+05 1.52 1.52 0.2 17.5 1550 50 3 10 

100 6.11E+04 4.57 5.94 0.2 17.5 1020 50 3 10 

101 2.67E+04 3.05 0.30 0.2 17.5 1380 50 3 10 

102 6.07E+04 5.11 4.88 0.2 17.5 1900 50 3 10 

103 1.01E+04 4.49 5.18 0.2 17.5 5000 50 3 10 

104 6.14E+04 1.83 3.05 0.2 17.5 1620 50 3 10 

105 1.54E+05 4.57 1.83 0.2 17.5 1100 50 3 10 

D-22

106 6.19E+04 5.44 6.48 0.2 17.5 1960 50 3 10 

107 8.09E+04 -999 1.07 0.2 17.5 240 50 1 10 

108 2.30E+02 3.35 3.05 0.2 12.5 180 27 1 6 

109 2.09E+03 1.53 0.00 0.2 12.5 800 50 2 2 

110 2.02E+05 2.29 2.90 0.2 17.5 140 50 1 10 

111 8.09E+03 2.44 3.05 0.2 17.5 975 50 1 10 

112 8.09E+03 2.74 2.13 0.2 17.5 895 50 1 10 

113 4.86E+04 2.74 3.66 0.2 17.5 910 50 1 10 

114 8.09E+03 2.44 3.35 0.2 17.5 950 50 1 10 

115 2.31E+04 3.05 3.96 0.2 17.5 845 50 1 10 

116 2.02E+05 5.18 5.49 0.2 17.5 25 50 1 10 

117 6.48E+03 4.85 0.00 0.2 17.5 360 50 1 10 

118 1.70E+05 4.57 6.71 0.2 17.5 500 50 1 10 

119 1.01E+03 2.44 2.74 0.2 17.5 270 50 1 10 

120 2.43E+04 4.57 4.88 0.2 17.5 820 50 1 10 
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

121 1.39E+03 3.05 3.12 0.2 12.5 180 50 3 6 

122 1.39E+03 4.57 5.49 0.2 12.5 230 50 3 6 

123 5.57E+03 4.57 5.49 0.2 12.5 265 50 3 6 

124 5.57E+02 3.81 4.66 0.2 12.5 230 50 3 6 

125 4.06E+03 3.68 4.66 0.2 12.5 270 50 3 6 

126 2.83E+04 -999 1.52 0.2 12.5 180 50 1 4 

127 1.01E+04 0.30 6.10 0.2 12.5 605 50 1 4 

128 1.42E+04 0.30 3.20 0.2 12.5 590 50 1 4 

D-23

129 8.09E+03 3.35 1.98 0.2 12.5 320 50 1 4 

130 2.02E+04 0.91 3.96 0.2 12.5 180 50 1 4 

131 2.83E+03 1.73 3.35 0.2 12.5 330 50 1 4 

132 7.43E+01 1.52 2.44 0.2 12.5 1800 13 3 2 

133 2.86E+05 1.22 0.00 0.2 22.5 150 50 2 10 

134 1.30E+05 1.67 0.00 0.2 22.5 280 52 1 10 

135 7.49E+04 1.98 0.30 0.2 7.5 30 60 2 8 

136 5.26E+03 1.60 2.44 0.2 7.5 290 60 2 8 

137 4.73E+04 0.76 1.83 0.2 7.5 30 60 2 8 

138 7.49E+04 2.74 0.00 0.2 7.5 30 60 2 8 

139 3.68E+04 1.37 1.83 0.2 7.5 30 60 2 8 

140 5.02E+02 1.07 0.00 0.2 17.5 455 30 1 5 

141 1.19E+04 1.45 1.22 0.2 17.5 160 50 1 2 

142 1.39E+03 1.22 2.74 0.2 17.5 340 50 3 2 

143 4.61E+03 0.15 1.83 0.2 17.5 950 50 3 2 
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

144 8.71E+02 1.52 2.44 0.2 17.5 560 50 3 2 

145 5.96E+04 4.57 5.49 0.2 17.5 470 50 3 2 

146 1.33E+03 1.52 5.49 0.2 17.5 480 50 3 2 

147 3.43E+03 1.52 3.51 0.2 17.5 600 50 3 2 

148 1.45E+05 2.29 2.29 0.2 17.5 100 50 3 2 

149 6.01E+03 1.52 3.66 0.2 17.5 700 50 1 2 

150 5.30E+02 1.22 1.22 0.2 7.5 110 20 2 9 

151 1.30E+02 1.22 1.22 0.2 7.5 20 27 2 9 

D-24

152 7.80E+02 1.22 1.22 0.2 7.5 110 20 2 9 

153 7.80E+02 1.22 1.22 0.2 7.5 110 20 2 9 

154 9.14E+02 -999 0.30 0.2 12.5 20 15 2 8 

155 2.93E+03 1.52 2.44 0.2 17.5 1300 50 3 2 

156 2.69E+03 1.52 2.44 0.2 17.5 1330 50 3 2 

157 1.99E+03 -999 1.52 0.2 17.5 1480 17 3 2 

158 2.28E+03 -999 1.52 0.2 17.5 1455 17 3 2 

159 1.36E+03 1.68 1.68 0.2 17.5 1450 50 3 12 

160 8.38E+03 4.57 6.10 0.2 17.5 1180 50 3 12 

161 3.48E+03 2.29 4.42 0.2 17.5 5000 50 3 12 

162 8.09E+05 3.05 0.00 0.2 22.5 1500 50 3 6 

163 2.38E+01 4.57 4.88 0.2 22.5 1575 4 1 7 

164 1.38E+03 4.57 3.05 0.2 22.5 1270 50 3 10 

165 1.39E+03 0.61 3.66 0.2 22.5 1340 50 3 10 

166 2.06E+02 0.76 1.37 0.2 17.5 95 50 3 10 
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

167 5.26E+02 0.64 0.00 0.2 17.5 20 65 1 2 

168 2.02E+03 2.44 3.05 0.2 17.5 20 65 3 2 

169 2.63E+04 -999 4.42 0.2 22.5 215 50 3 10 

170 6.07E+03 0.58 1.22 0.2 22.5 1645 50 3 10 

171 7.08E+05 1.22 2.44 0.2 22.5 35 50 3 10 

172 2.83E+05 0.91 1.83 0.2 22.5 35 50 3 10 

173 4.25E+05 1.37 2.29 0.2 22.5 35 50 3 10 

174 3.64E+04 2.44 3.05 0.2 22.5 20 50 3 10 

D-25

175 1.50E+04 1.98 0.30 0.2 22.5 1440 50 3 10 

176 1.13E+04 -999 0.00 0.2 17.5 20 47 1 1 

177 1.13E+04 -999 0.00 0.2 17.5 30 47 1 1 

178 5.55E+03 -999 2.13 0.2 17.5 1800 50 1 2 

179 3.33E+03 -999 1.98 0.2 17.5 2000 50 1 2 

180 5.14E+05 2.74 3.96 0.2 17.5 5000 50 3 6 

181 5.06E+03 1.37 2.13 0.2 17.5 5000 50 3 6 

182 7.28E+03 0.84 2.06 0.2 17.5 1500 50 3 6 

183 4.05E+05 1.14 4.50 0.2 17.5 5000 50 3 6 

184 6.07E+04 1.70 4.11 0.2 17.5 5000 22 3 6 

185 1.21E+04 4.11 5.18 0.2 17.5 5000 50 3 6 

186 1.21E+04 5.26 6.02 0.2 17.5 5000 50 3 6 

187 2.14E+05 3.21 3.96 0.2 17.5 475 47 3 6 

188 1.21E+04 5.49 6.10 0.2 12.5 60 50 1 4 

189 2.43E+05 4.57 5.18 0.2 12.5 40 50 1 4 
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

190 4.05E+04 3.51 0.00 0.2 12.5 90 50 2 5 

191 6.27E+04 5.05 9.51 0.2 22.5 150 50 2 4 

192 3.04E+04 -999 4.72 0.2 22.5 330 16 2 4 

193 2.67E+04 -999 5.64 0.2 22.5 315 16 2 4 

194 9.29E+03 1.37 3.96 0.2 22.5 1700 24 3 10 

195 1.45E+03 2.26 2.44 0.2 22.5 1600 50 3 10 

196 5.38E+03 2.77 3.66 0.2 22.5 1260 50 3 10 

197 5.38E+03 2.77 3.96 0.2 22.5 1140 50 3 10 

D-26

198 8.99E+02 1.83 3.66 0.2 22.5 1080 50 3 10 

199 8.99E+02 1.83 3.66 0.2 22.5 1080 50 3 10 

200 1.19E+03 3.66 5.03 0.2 17.5 395 50 1 10 

201 6.07E+03 1.37 2.29 0.2 17.5 130 50 1 10 

202 2.20E+03 3.96 4.72 0.2 17.5 395 50 1 10 

203 1.19E+03 3.66 5.03 0.2 17.5 395 50 1 10 

204 8.36E+03 1.52 3.35 0.2 17.5 500 50 1 10 

205 4.49E+04 1.22 1.07 0.2 17.5 550 50 1 10 

206 1.41E+03 3.49 3.89 0.2 17.5 480 50 1 10 

207 3.18E+03 3.57 3.96 0.2 17.5 480 50 1 10 

208 1.76E+03 1.68 1.72 0.2 17.5 660 50 1 10 

209 1.19E+03 3.66 5.03 0.2 17.5 395 50 1 10 

210 4.41E+03 2.16 0.61 0.2 12.5 850 65 3 2 

211 1.30E+04 1.71 1.92 0.2 12.5 695 8 3 2 

212 8.82E+03 0.30 0.30 0.2 22.5 150 50 2 11 
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

213 8.76E+03 0.30 0.30 0.2 22.5 90 50 2 11 

214 2.02E+05 3.66 2.13 0.2 17.5 335 50 2 10 

215 1.21E+03 1.83 3.66 0.2 17.5 600 30 2 10 

216 2.02E+03 -999 0.00 0.2 17.5 65 50 1 10 

217 4.69E+05 2.97 2.67 0.2 17.5 115 50 1 10 

218 2.02E+05 3.66 2.13 0.2 17.5 435 50 2 10 

219 1.55E+03 1.10 2.74 0.2 12.5 270 50 2 7 

220 2.68E+03 2.13 1.83 0.2 12.5 270 50 2 7 

D-27

221 2.21E+03 3.05 3.66 0.2 27.5 1800 50 3 6 

222 3.19E+03 2.13 0.00 0.2 27.5 656 50 3 6 

223 1.90E+03 3.05 3.66 0.2 27.5 1800 50 3 6 

224 1.90E+03 3.05 3.66 0.2 27.5 1800 50 3 6 

225 3.24E+04 1.37 0.15 0.2 7.5 850 50 3 9 

226 3.24E+04 1.98 0.61 0.2 7.5 755 50 2 9 

227 3.16E+04 5.33 2.13 0.2 7.5 320 50 2 9 

228 2.79E+03 3.96 5.79 0.2 17.5 320 50 3 12 

229 2.87E+04 1.37 2.74 0.2 17.5 1580 50 1 12 

230 5.04E+03 3.66 0.00 0.2 17.5 1500 50 1 12 

231 5.04E+03 3.66 0.00 0.2 17.5 1560 50 1 12 

232 2.18E+04 1.68 3.05 0.2 17.5 1750 50 1 12 

233 9.29E+02 1.83 0.91 0.2 22.5 505 18 3 10 

234 2.37E+04 1.83 1.22 0.2 22.5 505 50 3 10 

235 2.42E+03 1.68 2.35 0.2 17.5 350 50 1 2 
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

236 2.98E+04 0.88 3.26 0.2 17.5 400 50 1 2 

237 2.83E+03 1.89 2.26 0.2 17.5 350 50 1 2 

238 3.12E+04 2.07 2.83 0.2 17.5 350 50 1 2 

239 6.07E+03 0.81 0.00 0.2 17.5 580 57 1 2 

240 4.86E+03 1.01 0.00 0.2 17.5 580 55 1 2 

241 6.48E+03 1.11 0.00 0.2 17.5 580 55 1 2 

242 1.07E+04 2.06 2.06 0.2 17.5 350 50 1 2 

243 2.36E+03 1.86 2.53 0.2 17.5 350 50 1 2 

D-28

244 1.62E+04 3.81 4.57 0.2 12.5 200 50 1 1 

245 3.12E+01 1.22 0.00 0.2 12.5 30 12 2 4 

246 5.20E+01 0.24 0.28 0.2 22.5 5000 7 2 4 

247 1.42E+03 3.45 5.18 0.2 12.5 30 50 3 9 

248 1.21E+04 1.22 1.98 0.2 7.5 75 50 2 4 

249 1.21E+04 0.30 0.91 0.2 7.5 25 50 2 4 

250 1.80E+05 -999 0.00 0.2 22.5 95 50 1 10 

251 6.61E+03 5.64 0.00 0.2 22.5 720 50 2 10 

252 7.93E+04 3.05 3.81 0.2 22.5 565 50 1 10 

253 4.82E+05 1.22 2.29 0.2 22.5 670 50 2 10 

254 1.92E+04 3.05 4.27 0.2 22.5 40 50 2 10 

255 1.92E+04 3.05 4.27 0.2 22.5 40 50 2 10 

256 5.67E+03 0.15 1.68 0.2 22.5 5000 37 3 10 

257 5.67E+03 0.38 1.91 0.2 22.5 5000 37 3 10 

258 1.37E+04 -999 0.00 0.2 22.5 60 50 3 10 
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

259 1.86E+05 0.63 0.00 0.2 22.5 250 95 3 10 

260 2.16E+05 -999 0.00 0.2 22.5 85 50 3 10 

261 1.57E+05 -999 0.00 0.2 22.5 385 50 3 10 

262 1.12E+05 -999 0.00 0.2 22.5 700 50 3 10 

263 1.09E+05 2.11 0.00 0.2 22.5 710 75 3 10 

264 1.70E+05 -999 0.00 0.2 22.5 240 50 3 10 

265 4.74E+02 2.13 4.57 0.2 17.5 180 50 3 10 

266 2.01E+03 1.83 3.05 0.2 22.5 5000 50 3 10 

D-29

267 2.01E+03 1.83 3.05 0.2 22.5 5000 50 3 10 

268 4.01E+02 -999 0.00 0.2 17.5 360 50 3 2 

269 9.17E+01 -999 0.00 0.2 17.5 360 50 3 2 

270 2.60E+01 -999 0.00 0.2 17.5 360 50 3 2 

271 4.01E+02 -999 0.00 0.2 17.5 360 50 3 2 

272 4.01E+02 -999 0.00 0.2 17.5 360 50 3 2 

273 3.52E+04 2.05 2.90 0.2 12.5 400 50 3 5 

274 4.05E+03 2.12 3.58 0.2 12.5 350 50 3 5 

275 1.62E+04 4.39 6.16 0.2 17.5 5000 50 2 5 

276 1.78E+04 0.91 1.83 0.2 17.5 5000 27 2 5 

277 3.67E+03 3.05 1.52 0.2 7.5 140 37 1 6 

278 4.30E+03 4.21 7.92 0.2 12.5 1260 47 1 12 

279 6.31E+03 2.50 5.79 0.2 12.5 1260 50 1 12 

280 2.02E+04 -999 0.00 0.2 12.5 1260 50 1 12 

281 9.30E+00 1.83 3.05 0.2 12.5 130 14 2 8 
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

282 5.89E+04 3.35 4.57 0.2 12.5 310 50 3 6 

283 5.65E+04 3.35 4.57 0.2 12.5 110 47 3 6 

284 1.69E+04 4.27 0.00 0.2 7.5 1480 50 1 9 

285 4.58E+04 1.83 3.66 0.2 7.5 1620 50 1 9 

286 1.17E+04 1.98 3.66 0.2 7.5 190 50 1 9 

287 2.02E+03 -999 1.07 0.2 7.5 190 50 1 9 

288 6.07E+03 -999 1.07 0.2 7.5 180 65 1 9 

289 1.68E+05 6.25 5.33 0.2 7.5 1360 50 1 9 

D-30

290 2.84E+03 1.37 1.83 0.2 7.5 20 50 1 9 

291 7.53E+02 0.93 0.00 0.2 7.5 20 50 1 9 

292 1.33E+05 4.27 3.35 0.2 7.5 1040 50 1 9 

293 6.97E+03 2.39 0.00 0.2 17.5 1220 50 3 6 

294 4.46E+03 3.84 5.18 0.2 17.5 1510 50 3 6 

295 1.34E+04 3.20 0.00 0.2 12.5 220 50 2 7 

296 3.67E+02 1.42 0.61 0.2 12.5 50 50 2 4 

297 2.47E+04 3.83 3.81 0.2 7.5 240 50 2 9 

298 8.63E+04 5.48 3.35 0.2 7.5 130 50 2 9 

299 1.01E+03 3.25 2.97 0.2 7.5 40 50 2 9 

300 7.28E+04 0.50 1.46 0.2 7.5 5000 30 3 9 

301 5.26E+04 1.29 2.74 0.2 7.5 5000 50 3 9 

302 5.34E+03 0.91 4.27 0.2 7.5 455 50 3 9 

303 8.90E+03 5.49 3.35 0.2 17.5 710 18 1 10 

304 5.50E+03 3.44 0.00 0.2 17.5 950 50 1 10 
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

305 3.69E+03 4.65 4.53 0.2 17.5 1100 50 1 10 

306 2.79E+05 1.22 0.00 0.2 17.5 905 22 3 10 

307 2.47E+05 3.05 2.13 0.2 17.5 1100 50 1 10 

308 4.86E+06 2.44 0.00 0.2 17.5 125 50 3 10 

309 3.64E+04 1.52 0.61 0.2 17.5 720 50 1 10 

310 9.71E+03 2.74 0.00 0.2 17.5 1500 50 1 10 

311 1.21E+04 1.01 0.79 0.2 17.5 950 50 1 10 

312 2.47E+05 4.57 0.46 0.2 17.5 1540 50 3 10 

D-31

313 1.76E+03 1.83 0.00 0.2 7.5 460 50 1 4 

314 3.59E+03 1.22 0.00 0.2 7.5 480 50 1 4 

315 3.26E+03 1.68 0.76 0.2 7.5 500 50 1 4 

316 3.52E+03 -999 0.91 0.2 7.5 60 22 3 7 

317 5.07E+02 2.44 2.44 0.2 7.5 75 50 3 7 

318 1.00E+03 -999 2.44 0.2 7.5 20 22 3 7 

319 1.28E+03 -999 2.04 0.2 7.5 20 22 3 7 

320 1.17E+05 2.74 3.66 0.2 7.5 5000 50 3 7 

321 1.32E+03 2.08 1.99 0.2 7.5 75 50 3 7 

322 1.11E+03 1.27 0.61 0.2 17.5 90 24 3 2 

323 9.96E+02 5.49 6.10 0.2 17.5 190 47 2 5 

324 1.23E+03 0.91 1.22 0.2 17.5 5000 50 1 2 

325 8.36E+01 -999 6.10 0.2 17.5 5000 50 1 2 

326 9.29E+01 -999 6.10 0.2 17.5 5000 50 1 2 

327 1.24E+03 0.91 1.22 0.2 17.5 5000 50 1 2 
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

328 7.43E+02 -999 1.07 0.2 22.5 150 50 3 6 

329 1.23E+03 3.35 3.96 0.2 22.5 340 50 3 10 

330 1.24E+03 -999 1.98 0.2 22.5 120 50 3 6 

331 2.92E+03 4.27 2.44 0.2 22.5 90 7 3 10 

332 2.92E+03 4.27 2.44 0.2 22.5 90 7 3 10 

333 5.34E+02 0.19 1.22 0.2 22.5 1330 50 3 6 

334 2.42E+03 1.22 2.90 0.2 22.5 130 17 3 10 

335 1.67E+03 0.30 1.22 0.2 22.5 190 17 3 10 

D-32

336 2.92E+03 4.27 2.44 0.2 22.5 20 7 3 10 

337 2.79E+04 13.72 33.53 0.2 12.5 1315 50 3 6 

338 3.72E+04 7.47 4.57 0.2 12.5 40 50 3 6 

339 3.72E+04 8.69 5.79 0.2 12.5 230 50 3 6 

340 2.79E+04 6.10 3.66 0.2 12.5 330 50 3 6 

341 6.97E+04 0.38 6.40 0.2 12.5 65 50 3 6 

342 2.14E+04 3.05 4.57 0.2 22.5 370 75 3 10 

343 2.33E+03 2.97 3.05 0.2 12.5 1080 50 2 10 

344 1.77E+03 3.58 3.66 0.2 12.5 1000 50 2 10 

345 3.04E+03 1.83 2.74 0.2 17.5 700 50 2 10 

346 1.03E+03 -999 7.62 0.2 12.5 260 50 3 9 

347 7.24E+02 -999 4.57 0.2 12.5 240 50 3 9 

348 3.90E+02 0.07 0.00 0.2 22.5 260 50 2 10 

349 8.90E+03 1.07 8.08 0.2 12.5 440 17 1 2 

350 3.90E+03 2.13 3.84 0.2 17.5 85 50 2 2 
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

351 4.07E+04 3.66 1.71 0.2 17.5 840 50 1 10 

352 2.18E+04 3.81 2.01 0.2 17.5 1120 22 1 10 

353 1.16E+03 -999 0.00 0.2 17.5 590 13 3 1 

354 2.92E+03 -999 0.00 0.2 7.5 330 27 1 9 

355 2.02E+04 2.44 1.52 0.2 22.5 1115 50 2 4 

356 4.86E+04 11.46 7.47 0.2 22.5 1115 50 2 4 

357 4.86E+04 11.46 7.47 0.2 22.5 1100 50 2 4 

358 4.86E+04 11.46 7.47 0.2 22.5 970 50 2 4 

D-33

359 4.86E+04 11.46 7.47 0.2 22.5 1360 50 2 4 

360 2.83E+04 3.66 4.88 0.2 22.5 220 50 2 4 

361 3.84E+04 2.44 1.52 0.2 22.5 960 50 2 4 

362 4.86E+04 11.46 7.47 0.2 22.5 1400 50 2 4 

363 8.09E+03 9.07 0.00 0.2 22.5 240 50 2 4 

364 4.05E+03 18.15 0.00 0.2 22.5 410 50 2 4 

365 2.23E+04 3.30 0.00 0.2 22.5 505 50 2 4 

366 1.62E+04 1.83 2.44 0.2 22.5 1295 50 2 4 

367 2.83E+04 3.05 3.35 0.2 22.5 635 50 2 4 

368 7.73E+05 3.66 0.00 0.2 22.5 295 50 2 4 

369 7.47E+03 4.02 5.37 0.2 22.5 395 50 2 4 

370 2.02E+04 3.66 4.88 0.2 22.5 255 50 2 4 

371 4.86E+04 11.46 7.47 0.2 22.5 1650 50 2 4 

372 3.48E+05 3.35 0.30 0.2 22.5 115 50 2 4 

373 4.86E+04 11.46 7.47 0.2 22.5 1380 50 2 4 
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

374 2.43E+04 3.05 4.27 0.2 22.5 495 50 2 4 

375 4.05E+04 4.86 7.47 0.2 22.5 815 50 2 4 

376 4.86E+04 11.46 7.47 0.2 22.5 985 50 2 4 

377 4.86E+04 11.46 7.47 0.2 22.5 1155 50 2 4 

378 4.86E+04 5.18 0.61 0.2 22.5 1380 50 2 4 

379 4.86E+04 11.46 7.47 0.2 22.5 1500 50 2 4 

380 4.86E+04 11.46 7.47 0.2 22.5 1540 50 2 4 

381 2.14E+05 2.90 3.35 0.2 22.5 40 50 2 4 

D-34

382 1.62E+03 -999 0.00 0.2 17.5 40 50 1 5 

383 1.62E+03 -999 0.00 0.2 17.5 110 50 1 5 

384 1.62E+05 -999 0.00 0.2 17.5 5000 50 1 5 

385 1.21E+04 -999 0.00 0.2 17.5 340 50 1 5 

386 5.26E+03 -999 0.00 0.2 17.5 200 50 1 5 

387 5.26E+03 -999 0.00 0.2 17.5 200 50 2 5 

388 5.26E+04 -999 0.00 0.2 17.5 410 50 1 5 

389 1.83E+04 0.38 1.60 0.2 12.5 1075 50 1 6 

390 2.15E+04 0.87 1.55 0.2 12.5 1100 50 1 6 

391 1.70E+03 1.78 1.25 0.2 12.5 1125 50 1 6 

392 8.09E+03 1.68 4.18 0.2 17.5 485 50 3 10 

393 9.71E+02 2.44 0.00 0.2 17.5 120 50 3 10 

394 1.58E+05 1.98 2.13 0.2 17.5 215 50 3 10 

395 7.69E+04 2.44 3.54 0.2 17.5 20 50 3 10 

396 6.84E+05 1.22 2.56 0.2 17.5 405 50 1 10 
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

397 1.58E+05 4.88 2.07 0.2 17.5 1350 50 3 10 

398 8.09E+03 1.68 4.48 0.2 17.5 350 50 3 10 

399 2.67E+05 3.66 2.99 0.2 17.5 245 50 3 10 

400 1.21E+04 1.68 4.39 0.2 17.5 40 50 3 10 

401 5.11E+03 2.13 3.05 0.2 7.5 70 50 3 4 

402 5.11E+03 1.83 3.05 0.2 7.5 80 50 3 4 

403 5.11E+03 0.61 3.05 0.2 7.5 80 50 3 4 

404 1.84E+04 6.72 0.00 0.2 17.5 370 50 3 2 

D-35

405 2.07E+04 1.22 2.13 0.2 17.5 445 50 3 2 

406 4.37E+05 1.28 0.09 0.2 17.5 60 50 3 2 

407 5.26E+04 0.77 0.00 0.2 17.5 460 50 3 2 

408 7.53E+03 1.52 1.83 0.2 17.5 445 50 3 2 

409 2.95E+05 0.58 1.40 0.2 17.5 30 50 3 2 

410 1.16E+03 1.83 2.44 0.2 12.5 360 5 3 7 

411 7.29E+03 2.29 6.55 0.2 12.5 140 37 3 7 

412 1.86E+03 -999 2.59 0.2 12.5 130 20 3 7 

413 9.80E+00 1.14 2.29 0.2 17.5 60 50 3 1 

414 4.65E+03 1.76 3.96 0.2 12.5 185 50 3 9 

415 1.86E+04 2.13 3.66 0.2 12.5 220 50 3 9 

416 1.86E+04 2.29 3.81 0.2 12.5 220 50 3 9 

417 7.28E+04 16.11 0.00 0.2 22.5 40 50 2 4 

418 2.38E+04 4.27 2.90 0.2 7.5 1180 50 2 8 

419 2.38E+04 4.27 2.90 0.2 7.5 1170 50 2 8 
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

420 1.77E+03 2.13 3.05 0.2 12.5 20 29 2 7 

421 1.63E+03 1.68 2.59 0.2 12.5 20 29 2 7 

422 1.95E+03 1.22 2.74 0.2 12.5 40 29 2 7 

423 3.72E+03 1.95 3.32 0.2 12.5 40 29 2 7 

424 2.91E+04 -999 3.05 0.2 17.5 5000 32 3 5 

425 2.91E+04 3.05 3.05 0.2 17.5 5000 32 3 5 

426 1.30E+03 -999 0.00 0.2 7.5 300 15 1 5 

427 1.77E+04 0.94 2.44 0.2 17.5 5000 50 1 6 

D-36

428 5.57E+02 2.04 0.00 0.2 17.5 5000 50 1 6 

429 1.94E+02 1.91 1.78 0.2 12.5 40 50 1 2 

430 1.30E+03 -999 0.00 0.2 12.5 170 50 1 2 

431 6.69E+02 0.46 0.00 0.2 17.5 810 50 3 12 

432 2.91E+04 3.66 2.74 0.2 17.5 1115 50 3 12 

433 3.86E+03 1.83 7.32 0.2 17.5 575 50 3 12 

434 4.65E+05 2.74 2.44 0.2 17.5 105 50 3 12 

435 2.31E+05 4.57 4.57 0.2 17.5 270 50 3 12 

436 1.01E+05 4.57 3.96 0.2 17.5 795 50 3 12 

437 6.96E+03 5.18 3.81 0.2 17.5 565 50 3 12 

438 6.96E+03 5.18 3.81 0.2 17.5 525 50 3 12 

439 7.81E+03 2.44 0.00 0.2 7.5 900 50 2 4 

440 5.95E+03 1.27 0.00 0.2 7.5 550 50 2 6 

441 1.63E+03 2.07 0.00 0.2 7.5 300 50 2 6 

442 2.69E+03 1.89 0.00 0.2 7.5 300 50 2 6 
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

443 1.74E+02 0.46 1.52 0.2 17.5 420 14 3 2 

444 6.09E+02 0.15 1.07 0.2 17.5 420 14 3 2 

445 1.21E+03 1.83 2.44 0.2 27.5 550 50 2 6 

446 1.39E+04 4.26 3.67 0.2 12.5 210 50 2 10 

447 1.78E+03 2.74 3.05 0.2 12.5 610 50 2 10 

448 2.01E+03 1.83 1.53 0.2 12.5 670 50 2 10 

449 3.58E+03 0.30 3.90 0.2 12.5 440 50 2 10 

450 3.09E+03 1.30 0.00 0.2 12.5 500 50 2 10 

D-37

451 1.24E+03 1.45 0.00 0.2 12.5 40 50 2 10 

452 1.24E+03 0.02 0.00 0.2 12.5 30 50 2 10 

453 1.39E+04 3.89 3.38 0.2 12.5 320 50 2 10 

454 1.74E+03 2.74 3.05 0.2 12.5 600 50 2 10 

455 6.88E+03 2.44 2.51 0.2 12.5 280 50 2 10 

456 2.85E+02 1.30 4.18 0.2 12.5 280 50 2 10 

457 2.86E+02 1.81 4.18 0.2 12.5 280 50 2 10 

458 2.36E+05 0.91 0.00 0.2 22.5 300 50 2 4 

459 7.70E+03 -999 0.00 0.2 22.5 700 50 2 4 

460 2.88E+04 -999 0.00 0.2 22.5 0 50 2 4 

461 1.35E+05 0.91 0.00 0.2 22.5 0 50 2 4 

462 5.71E+04 0.91 0.00 0.2 22.5 40 50 2 4 

463 5.32E+05 0.91 0.00 0.2 22.5 20 50 2 4 

464 6.19E+04 0.91 0.00 0.2 22.5 20 50 2 4 

465 2.16E+05 0.91 0.00 0.2 22.5 200 50 2 4 
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

466 1.01E+05 1.29 0.00 0.2 22.5 5000 50 2 4 

467 8.10E+04 -999 0.00 0.2 22.5 0 50 2 4 

468 6.13E+02 3.10 4.63 0.2 17.5 190 50 3 1 

469 2.02E+02 -999 0.00 0.2 12.5 395 27 1 5 

470 2.31E+05 -999 0.00 0.2 12.5 65 38 2 7 

471 5.30E+03 0.61 0.15 0.2 22.5 600 50 2 10 

472 4.27E+03 0.61 1.83 0.2 22.5 800 50 2 10 

473 5.64E+03 1.83 1.83 0.2 22.5 840 50 2 10 

D-38

474 4.16E+03 0.61 1.86 0.2 22.5 740 50 2 10 

475 2.79E+03 4.54 0.27 0.2 22.5 640 50 2 10 

476 6.04E+02 1.22 0.46 0.2 22.5 640 50 2 10 

477 9.75E+03 0.30 0.46 0.2 22.5 440 50 2 10 

478 1.86E+03 1.77 0.30 0.2 22.5 500 50 2 10 

479 1.02E+03 0.73 0.27 0.2 22.5 530 50 2 10 

480 8.36E+02 0.01 0.00 0.2 22.5 5000 17 1 10 

481 7.04E+03 0.76 2.29 0.2 7.5 220 50 2 2 

482 4.06E+04 2.44 3.96 0.2 7.5 240 50 2 2 

483 7.28E+02 0.30 0.61 0.2 7.5 800 50 2 2 

484 1.09E+03 0.15 1.52 0.2 7.5 740 50 2 2 

485 2.31E+03 0.61 4.27 0.2 7.5 600 50 2 2 

486 6.42E+02 1.43 0.91 0.2 7.5 216 50 2 2 

487 3.93E+04 0.61 1.22 0.2 7.5 1220 50 2 2 

488 1.46E+03 3.05 5.18 0.2 7.5 900 50 2 2 
Table D.2 Nationwide Database of Surface Impoundment Sites

Site

Number

Area

(m2)

Operating

Depth

(m)

Base Depth

Below Grade

(m)

Total

Thickness of

Sediment

(m)

Soil/GW

Temp.

( C)

Distance to

Nearest SW

Body

(m)

Operating

Life/Leaching

Duration

(yr)

Soil

Type

HG

Environment

N

C

C

489 2.22E+04 0.23 0.99 0.2 7.5 810 50 2 2 

490 2.33E+04 1.83 2.13 0.2 7.5 1390 50 1 2 

491 1.44E+03 1.22 1.83 0.2 7.5 624 50 2 2 

492 1.86E+03 0.30 0.61 0.2 7.5 230 50 2 2 

493 4.33E+03 0.91 2.59 0.2 7.5 500 50 2 2 

494 7.28E+02 0.91 2.74 0.2 7.5 710 50 2 2 

495 3.99E+04 3.96 4.27 0.2 7.5 1080 50 2 2 

496 4.69E+04 1.98 2.90 0.2 7.5 960 50 2 2 

D-39

497 2.02E+02 2.13 1.83 0.2 22.5 5000 27 2 4 

498 1.52E+03 0.00 0.00 0.2 17.5 5000 12 2 4 

499 1.19E+03 3.20 4.27 0.2 17.5 5000 50 3 1 

500 7.41E+03 -999 0.00 0.2 12.5 240 50 3 6 

501 1.81E+03 -999 0.00 0.2 12.5 190 50 3 6 

502 5.16E+04 -999 0.06 0.2 12.5 150 50 3 6 

503 7.00E+01 0.06 0.76 0.2 22.5 480 6 3 10 
Appendix D WMU and Hydrogeologic Environment Databases

D-40

Table D.3 Nationwide Database of Waste Pile Sites

Site

Numbe

r

Area Depth

Soil/GW

Temperature HG

Environment

Nearest

Climate

Center

Site

(m2) (m) ( C) Weighting

1 1.01E+02 1.71E-01 12.5 2 39 10

2 3.78E+02 1.60E+00 12.5 12 69 10

3 1.21E+02 7.46E+00 17.5 4 90 1

4 1.21E+02 2.10E-01 12.5 12 54 1

5 4.45E+02 2.52E+01 12.5 12 53 1

6 8.09E+01 2.23E-01 17.5 1 79 1

7 5.20E+03 4.79E-02 12.5 2 52 1

8 8.09E+01 7.27E+00 12.5 5 74 1

9 1.35E+03 3.47E-01 22.5 4 58 1

10 3.24E+02 1.40E+01 12.5 12 85 1

11 1.21E+03 9.32E-02 17.5 12 89 1

12 6.07E+02 3.73E-02 12.5 12 42 1

13 6.20E+05 9.65E-07 12.5 12 69 1

14 1.21E+02 2.62E+00 7.5 2 32 1

15 2.43E+02 6.90E-01 17.5 13 90 1

16 6.75E+00 1.34E+02 22.5 4 92 1

17 6.07E+02 5.13E-02 12.5 2 53 1

18 4.05E+01 1.68E+00 17.5 4 95 1

19 2.10E+03 1.38E-01 12.5 12 32 20

20 3.64E+02 1.49E-01 12.5 8 82 20

21 8.09E+01 6.71E-01 12.5 12 42 20

22 4.05E+03 4.47E-02 12.5 4 66 20

23 4.05E+01 2.24E-01 17.5 5 1 20

24 4.86E+03 5.03E-01 17.5 12 93 3

25 4.05E+01 2.22E-02 22.5 4 91 3

26 1.21E+02 8.95E+00 12.5 4 56 3

27 2.02E+01 3.69E+01 12.5 2 71 3

28 2.02E+04 1.12E-03 17.5 4 79 3

29 2.02E+01 1.34E+01 22.5 4 81 3

30 5.58E+03 -9.99E+02 7.5 2 32 3

31 1.21E+02 2.24E+01 12.5 9 51 3

32 1.62E+02 2.01E+01 17.5 5 12 3

33 5.58E+03 1.05E-02 12.5 12 71 3

34 2.02E+01 -9.99E+02 12.5 5 26 3

35 3.24E+04 1.23E+00 12.5 4 74 3

36 2.02E+01 2.24E+01 12.5 12 51 3

37 2.02E+01 4.65E+00 22.5 4 79 3

38 1.21E+02 2.24E+00 12.5 2 66 3

39 2.43E+02 5.22E+00 12.5 2 53 3

40 2.02E+03 8.95E-02 12.5 2 71 3

41 2.02E+01 2.15E+00 12.5 2 66 3

42 2.43E+04 8.76E-02 22.5 4 92 3

43 8.09E+01 1.23E+00 12.5 2 88 3

44 1.01E+03 3.56E-01 17.5 4 80 3
Appendix D WMU and Hydrogeologic Environment Databases

Table D.3 Nationwide Database of Waste Pile Sites

Site

Numbe

r

Area Depth

Soil/GW

Temperature HG

Environment

Nearest

Climate

Center

Site

(m2) (m) ( C) Weighting

D-41

45 4.05E+01 4.47E+00 12.5 12 42 3

46 1.08E+02 1.01E+01 17.5 1 95 3

47 4.05E+01 1.01E+00 12.5 4 66 3

48 1.62E+02 2.10E+00 7.5 2 32 3

49 1.21E+03 1.12E+00 12.5 9 42 3

50 4.05E+01 3.13E+01 12.5 8 42 3

51 8.09E+01 1.85E-02 12.5 4 74 3

52 1.01E+03 1.79E+01 12.5 2 59 3

53 2.02E+01 3.95E-02 7.5 5 3 3

54 2.02E+01 1.10E+01 12.5 2 71 3

55 2.02E+02 1.12E-01 12.5 2 88 3

56 1.86E+04 9.75E-03 7.5 4 60 3

57 8.09E+01 4.92E-01 12.5 9 51 3

58 8.09E+01 3.95E-02 12.5 5 29 3

59 2.63E+04 -9.99E+02 12.5 4 52 3

60 2.02E+01 3.95E-02 17.5 4 80 3

61 4.05E+01 3.80E-01 12.5 2 71 3

62 1.62E+02 7.92E-01 7.5 2 48 3

63 2.02E+02 1.86E-01 12.5 12 85 3

64 2.02E+01 1.34E+02 17.5 12 89 3

65 4.05E+02 3.35E-02 22.5 4 58 3

66 2.83E+02 9.59E-01 7.5 12 32 3

67 6.88E+02 2.63E+00 12.5 4 39 3

68 9.31E+02 3.65E-01 17.5 2 58 3

69 2.02E+01 1.32E+02 12.5 12 85 3

70 2.02E+01 4.04E-01 12.5 2 74 3

71 4.05E+01 5.37E+00 12.5 12 50 3

72 2.79E+03 -9.99E+02 12.5 4 51 3

73 4.05E+01 6.98E+01 12.5 4 51 3

74 2.43E+03 7.46E-02 12.5 2 52 3

75 2.02E+01 8.95E+00 17.5 13 34 3

76 1.00E+05 1.36E-01 12.5 5 26 1

77 2.02E+01 1.97E+01 12.5 12 42 1

78 8.99E+03 1.79E+01 12.5 9 42 1

79 2.43E+02 2.24E+01 22.5 4 81 1

80 4.05E+03 3.36E-01 22.5 4 91 1

81 4.05E+02 1.23E+00 12.5 4 71 1

82 1.08E+02 3.75E+01 12.5 6 74 1

83 2.70E+01 4.59E+01 12.5 2 66 1

84 2.02E+01 1.23E+02 17.5 4 95 1

85 2.02E+02 8.95E+00 12.5 12 42 1

86 8.63E+02 5.77E+00 17.5 12 85 1

87 1.16E+04 7.40E+00 12.5 12 49 1

88 4.05E+03 2.24E-01 12.5 5 69 1
Appendix D WMU and Hydrogeologic Environment Databases

Table D.3 Nationwide Database of Waste Pile Sites

Site

Numbe

r

Area Depth

Soil/GW

Temperature HG

Environment

Nearest

Climate

Center

Site

(m2) (m) ( C) Weighting

D-42

89 7.45E+04 3.65E-01 12.5 4 52 1

90 9.31E+02 1.46E-01 12.5 4 66 1

91 9.44E+01 5.59E+00 17.5 12 95 1

92 4.05E+04 1.79E-02 17.5 1 95 1

93 4.28E+03 1.16E+00 12.5 12 88 1

94 2.02E+01 8.95E+00 12.5 12 52 1

95 5.61E+03 2.53E+00 22.5 4 81 1

96 1.62E+02 3.50E+01 12.5 4 72 1

97 1.21E+04 5.97E+00 12.5 12 49 1

98 5.58E+03 1.22E-01 12.5 2 66 1

99 2.02E+02 2.91E+00 12.5 2 66 1

100 2.02E+03 1.40E-01 7.5 13 66 1

101 2.02E+01 5.38E-01 17.5 2 36 1

102 6.07E+05 1.19E+00 12.5 2 69 1

103 1.11E+03 4.88E-02 12.5 2 52 1

104 1.34E+03 1.48E-01 22.5 4 96 1

105 8.09E+01 5.60E-01 12.5 8 32 1

106 2.10E+03 7.74E-01 12.5 2 74 1

107 4.05E+01 7.05E+00 12.5 12 42 1

108 4.05E+01 2.24E+02 12.5 2 69 1

109 1.21E+02 9.69E+01 17.5 12 95 1

110 4.05E+01 1.73E-02 12.5 1 71 1

111 8.09E+01 1.17E+01 7.5 2 50 1

112 1.62E+02 8.18E+00 12.5 2 39 1

113 1.01E+02 1.61E+01 12.5 1 75 1

114 4.05E+03 1.12E-02 17.5 4 93 1

115 2.33E+02 4.86E+00 12.5 4 74 1

116 9.44E+03 2.08E+00 17.5 12 95 1

117 4.05E+03 8.05E-02 12.5 12 71 1

118 2.02E+01 1.34E+02 7.5 8 32 1

119 2.02E+02 5.37E+01 12.5 2 66 1

120 5.67E+04 8.63E-04 12.5 4 52 1

121 2.43E+02 3.54E+01 12.5 9 51 1

122 4.05E+01 3.27E+02 12.5 4 72 1

123 1.42E+02 -9.99E+02 12.5 12 42 1

124 5.67E+04 1.64E-02 12.5 5 3 1

125 1.62E+02 1.29E+00 12.5 12 42 1

126 1.89E+02 4.15E+01 12.5 4 51 1

127 2.02E+01 1.68E+02 7.5 12 48 1

128 2.16E+04 2.80E+00 7.5 2 32 1

129 6.48E+02 1.96E+00 12.5 12 71 1

130 2.02E+01 1.66E+01 12.5 2 74 1

131 2.02E+03 5.22E+00 17.5 12 89 1

132 1.21E+04 8.95E-01 12.5 13 82 1
Appendix D WMU and Hydrogeologic Environment Databases

Table D.3 Nationwide Database of Waste Pile Sites

Site

Numbe

r

Area Depth

Soil/GW

Temperature HG

Environment

Nearest

Climate

Center

Site

(m2) (m) ( C) Weighting

D-43

133 8.09E+01 -9.99E+02 12.5 12 42 1

134 1.56E+02 2.67E+01 12.5 12 42 1

135 2.10E+03 1.08E-01 7.5 4 47 1

136 4.05E+04 5.59E-02 12.5 9 42 1

137 4.05E+01 5.59E+00 12.5 6 73 1

138 6.27E+03 7.16E-04 22.5 4 81 1

139 1.21E+04 -9.99E+02 12.5 2 66 1

140 4.05E+01 1.68E-01 12.5 13 71 1

141 2.43E+02 3.36E+02 12.5 2 52 1

142 6.48E+02 -9.99E+02 12.5 2 66 1

143 1.01E+04 4.75E-01 12.5 2 52 1

144 2.02E+01 6.44E+01 7.5 4 84 1

145 4.05E+03 8.05E-02 12.5 12 71 1

146 1.86E+03 8.75E-01 12.5 2 39 1

147 3.97E+03 5.24E-02 12.5 2 52 1

148 1.21E+02 -9.99E+02 12.5 4 27 1

149 4.45E+02 6.10E+00 12.5 2 52 1

150 1.52E+03 7.27E-01 12.5 9 42 1

151 7.45E+03 1.80E+00 12.5 4 72 1

152 8.09E+03 5.59E-01 12.5 2 39 1

153 3.91E+02 1.93E+00 7.5 13 45 1

154 4.05E+01 -9.99E+02 12.5 1 75 1

155 1.42E+03 4.79E+00 12.5 2 71 1

156 8.09E+01 1.39E-01 12.5 9 42 1

157 1.25E+03 1.67E+00 7.5 2 32 1

158 6.07E+01 9.32E+00 17.5 12 89 1

159 9.20E+02 1.18E+02 12.5 9 42 1

160 3.64E+02 4.97E-01 12.5 12 51 1

161 9.31E+02 2.43E-01 12.5 12 51 1

162 9.31E+02 1.95E+00 12.5 2 39 1

163 8.09E+01 3.99E+00 12.5 12 69 1

164 6.88E+02 3.29E-01 7.5 12 45 1

165 8.09E+02 9.02E-01 7.5 13 4 1

166 1.51E+04 5.71E-01 7.5 4 60 1

167 5.22E+03 3.69E-02 7.5 8 32 1

168 4.05E+03 4.03E+00 12.5 2 74 1

169 4.05E+03 2.07E-01 17.5 4 95 1

170 4.05E+03 1.12E-02 22.5 12 57 1

171 2.02E+02 2.24E-01 17.5 13 90 1

172 2.70E+03 2.51E-01 7.5 12 48 1

173 5.58E+03 7.29E-02 12.5 5 40 1

174 4.45E+02 5.08E-01 17.5 5 12 1

175 9.75E+03 1.58E+00 17.5 2 37 1

176 1.01E+03 1.23E-05 12.5 8 9 1

177 3.24E+02 8.11E-02 17.5 5 34 1
Appendix D WMU and Hydrogeologic Environment Databases

Table D.3 Nationwide Database of Waste Pile Sites

Site

Numbe

r

Area Depth

Soil/GW

Temperature HG

Environment

Nearest

Climate

Center

Site

(m2) (m) ( C) Weighting

D-44

178 6.07E+03 2.98E-02 12.5 12 50 1

179 4.05E+01 1.33E-01 22.5 12 76 1

180 4.05E+01 5.60E-01 22.5 4 92 1

181 2.02E+03 6.71E-02 7.5 13 5 1

182 2.02E+03 1.57E-01 22.5 5 92 1

183 1.47E+06 4.88E-01 22.5 12 57 1

184 1.82E+03 4.65E-02 17.5 13 29 1

185 9.31E+02 1.23E-01 17.5 13 29 1

186 1.01E+05 8.95E-02 22.5 4 92 1

187 2.02E+04 2.06E+00 12.5 1 71 1

188 1.42E+06 1.92E+00 22.5 12 57 1

189 6.07E+02 1.12E+01 22.5 4 92 1

190 1.15E+06 4.29E-01 22.5 4 92 1

191 2.02E+01 1.45E+00 12.5 13 71 1

192 3.04E+05 5.22E-01 22.5 12 57 1

193 4.05E+03 2.24E-03 17.5 4 30 1

194 2.83E+02 1.59E-02 17.5 2 77 1

195 2.02E+01 5.28E+00 12.5 12 51 1

196 4.45E+02 4.06E-02 17.5 4 90 1

197 8.09E+04 2.24E-02 12.5 4 48 1

198 2.02E+03 4.47E-01 17.5 2 36 1

199 2.02E+02 4.47E-01 17.5 12 79 1

200 2.02E+01 4.93E-03 17.5 4 90 22

201 2.79E+03 6.43E-04 12.5 8 55 22

202 8.09E+01 8.38E-02 17.5 1 95 3

203 1.01E+01 9.86E-03 22.5 4 81 3

204 9.96E+03 4.55E-01 12.5 5 33 3

205 4.05E+01 6.73E-01 17.5 12 90 3

206 8.09E+01 2.71E-02 17.5 4 69 3

207 2.09E+04 1.64E+00 12.5 2 39 3

208 2.02E+01 4.14E+00 17.5 4 90 3

209 2.02E+01 1.13E-01 12.5 13 19 3

210 9.31E+02 7.50E-04 17.5 4 90 3

211 8.50E+02 5.87E-05 12.5 5 56 1

212 3.64E+02 3.35E+00 12.5 1 67 1

213 1.05E+03 2.31E-03 12.5 4 71 1

214 3.04E+03 3.06E-01 17.5 4 69 1

215 9.31E+02 2.34E-02 17.5 12 89 1

216 8.09E+01 1.73E-02 22.5 12 78 1

217 2.02E+01 1.23E-01 17.5 5 12 1

218 1.94E+03 1.03E+00 12.5 12 73 1

219 1.01E+01 -9.99E+02 22.5 12 78 1

220 1.39E+04 2.87E-05 17.5 5 13 1

221 1.01E+01 2.71E-01 7.5 5 3 1
Appendix D WMU and Hydrogeologic Environment Databases

Table D.3 Nationwide Database of Waste Pile Sites

Site

Numbe

r

Area Depth

Soil/GW

Temperature HG

Environment

Nearest

Climate

Center

Site

(m2) (m) ( C) Weighting

D-45

222 3.04E+04 1.41E+01 12.5 5 69 1

223 4.05E+02 1.84E-01 12.5 9 42 1

224 2.02E+02 6.71E+00 12.5 12 42 1

225 2.02E+01 2.47E-01 17.5 5 12 1

226 2.48E+05 -9.99E+02 22.5 4 96 1

227 1.01E+04 -9.99E+02 17.5 1 69 1

228 8.09E+01 1.40E+01 12.5 12 42 1

229 1.50E+04 5.76E-01 12.5 2 39 1

230 4.05E+01 1.12E+01 17.5 5 21 1

231 2.02E+03 2.01E-01 7.5 5 10 1

232 1.50E+03 2.66E-01 7.5 1 64 1

233 2.02E+04 2.17E+00 12.5 4 56 1

234 4.05E+03 4.19E+00 12.5 12 19 1

235 4.05E+01 8.29E-01 17.5 13 13 1

236 2.02E+01 1.13E-01 17.5 13 77 8

237 2.02E+03 2.24E-02 17.5 4 95 1

238 8.09E+03 1.12E-03 22.5 4 58 1

239 1.62E+02 4.05E+01 12.5 5 74 1

240 4.05E+01 2.35E+01 12.5 4 72 1

241 1.86E+03 3.04E-02 12.5 4 73 1

242 1.35E+01 1.11E-01 12.5 12 51 1

243 1.13E+03 4.99E+00 12.5 12 50 1

244 2.02E+01 2.96E-01 12.5 2 88 1

245 1.01E+06 1.34E+00 22.5 12 57 1

246 8.09E+01 1.58E+00 12.5 1 65 1

247 4.05E+01 6.76E-01 22.5 4 92 1

248 5.40E+03 4.19E-02 12.5 5 40 2

249 3.72E+03 1.22E-02 12.5 2 54 2

250 1.13E+03 7.93E-04 17.5 1 79 2

251 6.75E+02 6.04E-02 12.5 4 51 2

252 6.88E+02 8.55E-01 12.5 2 51 2

253 9.29E+03 2.26E-02 12.5 12 54 2

254 6.07E+01 1.49E-01 12.5 5 56 2

255 4.05E+03 1.79E+00 12.5 2 33 2

256 1.62E+04 1.68E+01 17.5 4 74 2

257 4.05E+01 2.71E-02 12.5 8 46 2

258 9.31E+02 2.92E+00 17.5 5 12 2

259 1.62E+04 5.59E-02 17.5 4 79 2

260 1.21E+02 3.58E-01 22.5 4 81 2

261 1.21E+02 2.24E+00 22.5 12 57 2

262 2.02E+01 1.78E-01 17.5 13 90 1

263 2.02E+03 4.47E-02 12.5 12 55 1

264 4.45E+02 5.08E+00 22.5 5 92 1

265 4.86E+03 4.66E-02 12.5 13 20 1
Appendix D WMU and Hydrogeologic Environment Databases

Table D.3 Nationwide Database of Waste Pile Sites

Site

Numbe

r

Area Depth

Soil/GW

Temperature HG

Environment

Nearest

Climate

Center

Site

(m2) (m) ( C) Weighting

D-46

266 3.62E+04 1.90E+00 17.5 1 89 1

267 1.00E+04 2.84E-02 17.5 5 74 1

268 1.52E+03 5.67E-01 12.5 4 74 1

269 1.94E+06 6.52E-01 22.5 4 20 1

270 1.30E+06 1.82E+01 22.5 12 57 1

271 2.91E+05 1.55E+00 22.5 12 57 1

272 4.65E+04 5.44E-02 22.5 4 92 1

273 4.05E+03 4.47E-02 7.5 8 32 1

274 2.63E+02 1.55E-01 12.5 2 66 1

275 2.99E+04 1.36E+00 17.5 12 89 1

276 1.21E+04 8.96E-04 17.5 12 87 1

277 1.21E+02 4.59E+00 22.5 4 81 1

278 7.64E+04 3.26E-01 22.5 4 20 1

279 4.05E+03 2.24E-02 12.5 13 72 1

280 4.25E+05 2.66E+00 17.5 2 80 1

281 4.46E+04 1.52E-02 12.5 1 71 1

282 9.31E+02 1.22E-01 22.5 4 92 1

283 8.09E+03 9.86E-05 22.5 4 35 1

284 4.99E+05 3.45E+00 22.5 12 78 1

285 1.89E+05 9.59E-01 7.5 13 5 1

286 1.42E+02 8.10E-03 17.5 4 74 1

287 2.06E+03 2.19E-01 12.5 13 86 1

288 5.03E+04 1.08E-01 17.5 5 13 1

289 2.02E+03 1.01E-01 22.5 4 96 1

290 4.05E+01 3.08E+00 12.5 4 74 1

291 4.45E+04 9.97E-01 17.5 1 95 1

292 1.30E+03 1.75E-01 22.5 12 93 1

293 4.05E+01 3.92E+00 22.5 4 35 30

294 2.02E+01 -9.99E+02 12.5 9 42 30

295 4.05E+01 -9.99E+02 22.5 4 81 30

296 4.05E+02 4.44E-03 12.5 2 71 30

297 2.02E+01 4.47E+00 17.5 5 12 30

298 2.02E+01 5.03E-01 7.5 4 75 30

299 4.05E+03 5.60E-03 12.5 12 54 30

300 2.02E+03 6.71E-02 22.5 4 92 30

301 6.75E+00 1.18E-01 22.5 13 92 30

302 2.02E+01 8.88E-02 22.5 12 57 30

303 2.43E+02 6.99E-03 7.5 2 48 30

304 1.21E+03 1.89E-03 17.5 12 95 30

305 6.88E+02 -9.99E+02 22.5 4 92 30

306 4.17E+03 8.69E+00 7.5 8 32 30

307 2.02E+01 4.49E-01 17.5 13 37 30

308 1.62E+02 1.05E-01 7.5 2 32 30

309 2.02E+01 1.78E-01 17.5 4 90 30
Appendix D WMU and Hydrogeologic Environment Databases

Table D.3 Nationwide Database of Waste Pile Sites

Site

Numbe

r

Area Depth

Soil/GW

Temperature HG

Environment

Nearest

Climate

Center

Site

(m2) (m) ( C) Weighting

D-47

310 8.09E+01 5.59E+00 12.5 13 74 30

311 5.67E+02 1.60E-01 17.5 2 36 30

312 4.05E+01 3.36E+00 12.5 12 42 30

313 2.02E+01 8.93E-01 7.5 2 43 30

314 3.72E+03 2.43E+00 12.5 12 85 30

315 4.05E+03 8.88E-04 7.5 2 31 30

316 1.21E+02 8.39E-01 12.5 8 46 30

317 8.09E+01 1.01E+02 22.5 4 14 30

318 1.21E+04 7.46E-01 17.5 2 58 30

319 4.45E+02 6.10E-01 17.5 1 69 30

320 7.01E+02 8.60E-02 17.5 4 90 30

321 2.02E+03 1.68E-03 12.5 1 71 30

322 4.05E+02 8.88E-03 17.5 12 79 30

323 2.02E+01 1.97E-02 17.5 5 12 30

324 2.02E+01 1.79E+01 12.5 5 69 30

325 1.01E+04 2.24E-03 22.5 12 57 30

326 4.05E+01 3.92E-01 12.5 5 19 30

327 2.02E+01 3.58E+00 17.5 4 90 30

328 2.02E+01 2.24E+00 7.5 12 48 30

329 2.02E+01 6.90E-02 12.5 9 42 30

330 8.09E+01 1.68E-01 12.5 8 46 30

331 4.05E+01 3.92E+00 7.5 13 49 30

332 2.02E+01 9.37E-02 12.5 4 74 30

333 2.02E+01 3.16E-01 12.5 2 53 30

334 2.02E+03 5.57E-03 22.5 4 92 9

335 8.09E+01 1.01E-01 17.5 12 95 9

336 2.02E+01 8.93E-01 17.5 4 77 9

337 2.02E+02 2.80E-01 22.5 12 91 9

338 4.05E+01 2.33E+01 12.5 12 42 9

339 4.65E+02 8.75E-01 17.5 2 36 9

340 4.05E+02 6.71E-02 17.5 5 13 9

341 2.02E+01 -9.99E+02 12.5 2 71 9

342 1.01E+03 3.31E-02 17.5 12 89 9

343 4.05E+01 2.79E-01 12.5 4 66 9

344 4.05E+02 4.19E-02 7.5 1 44 9

345 4.05E+03 1.12E-02 17.5 4 90 9

346 3.72E+03 1.52E-02 12.5 2 31 9

347 2.02E+03 5.37E-02 12.5 1 71 9

348 4.45E+02 6.59E-02 17.5 12 95 9

349 2.02E+02 4.44E-03 17.5 4 36 9

350 2.02E+03 7.74E-01 22.5 4 92 9

351 2.02E+01 2.91E+00 7.5 5 3 9

352 4.05E+03 8.39E+00 17.5 4 79 9

353 2.14E+05 9.96E-01 17.5 8 74 9

354 6.88E+02 6.58E+00 12.5 12 32 9
Appendix D WMU and Hydrogeologic Environment Databases

Table D.3 Nationwide Database of Waste Pile Sites

Site

Numbe

r

Area Depth

Soil/GW

Temperature HG

Environment

Nearest

Climate

Center

Site

(m2) (m) ( C) Weighting

D-48

355 2.02E+01 4.47E+00 7.5 12 48 9

356 2.02E+01 8.88E-02 17.5 1 79 9

357 4.05E+03 2.24E-02 22.5 12 91 9

358 3.52E+04 2.35E-01 12.5 4 84 9

359 9.31E+02 1.82E-02 22.5 12 93 9

360 4.05E+01 1.23E+01 22.5 12 97 9

361 6.07E+03 -9.99E+02 12.5 12 72 9

362 3.44E+03 4.95E-01 12.5 13 32 9

363 4.45E+02 7.63E-01 22.5 12 91 9

364 6.75E+02 2.49E-02 22.5 12 97 9

365 8.09E+01 1.12E+01 12.5 12 87 9

366 6.07E+03 7.46E-03 17.5 5 14 9

367 2.43E+02 2.79E-02 22.5 11 57 9

368 2.43E+02 1.49E-01 22.5 4 96 9

369 1.21E+03 2.24E-01 12.5 8 54 9

370 8.09E+03 4.14E-02 17.5 13 20 9

371 6.07E+03 2.98E-01 12.5 4 66 9

372 2.79E+03 8.11E-03 7.5 4 31 9

373 1.35E+01 2.80E+01 12.5 5 26 9

374 9.31E+02 8.75E+00 12.5 12 42 9

375 2.02E+01 4.44E-02 12.5 1 8 9

376 3.56E+03 6.36E-02 17.5 4 92 9

377 1.62E+04 4.19E-03 17.5 1 77 9

378 8.09E+03 6.16E-06 17.5 5 12 9

379 1.21E+02 1.49E+00 12.5 2 59 9

380 1.21E+04 2.24E+00 7.5 4 25 9

381 9.31E+02 4.87E-02 12.5 4 13 9

382 2.02E+01 2.80E+00 17.5 2 36 9

383 3.64E+02 1.99E-01 7.5 2 32 9

384 5.67E+02 2.00E-01 22.5 4 35 9

385 8.09E+03 3.36E-01 17.5 1 69 9

386 4.05E+01 2.68E+01 17.5 4 90 9

387 1.01E+01 4.44E-02 17.5 5 13 9

388 1.01E+01 1.17E+01 22.5 4 92 9

389 4.45E+02 5.08E+00 7.5 1 65 9

390 8.09E+01 6.71E-01 22.5 4 81 9

391 2.02E+01 1.33E-01 12.5 2 71 9

392 1.42E+02 1.60E+01 22.5 12 78 9

393 8.09E+01 1.12E-01 7.5 4 6 9

394 8.09E+03 5.59E-01 12.5 8 82 9

395 6.07E+03 1.12E+01 12.5 4 51 9

396 8.09E+01 -9.99E+02 7.5 2 45 9

397 2.02E+03 1.40E-02 17.5 1 79 9

398 4.05E+01 3.35E-01 12.5 5 26 9
Appendix D WMU and Hydrogeologic Environment Databases

Table D.3 Nationwide Database of Waste Pile Sites

Site

Numbe

r

Area Depth

Soil/GW

Temperature HG

Environment

Nearest

Climate

Center

Site

(m2) (m) ( C) Weighting

D-49

399 1.21E+03 3.70E-03 12.5 9 42 9

400 4.65E+03 1.94E-02 12.5 4 19 9

401 1.01E+03 2.24E-02 22.5 12 76 9

402 6.07E+02 1.86E+00 12.5 4 65 9

403 6.07E+02 9.32E-01 7.5 4 10 9

404 1.21E+02 1.40E-01 17.5 5 53 9

405 1.21E+03 1.49E-02 17.5 2 74 9

406 4.05E+01 2.24E-01 17.5 5 1 9

407 2.83E+02 -9.99E+02 12.5 4 72 9

408 1.38E+03 1.97E+00 17.5 12 95 9

409 2.83E+03 3.20E+00 22.5 2 58 1

410 6.88E+02 1.32E-01 17.5 5 12 9

411 8.09E+01 1.68E-01 12.5 4 51 9

412 4.05E+01 5.37E+00 22.5 5 14 9

413 8.09E+03 3.49E-03 17.5 4 69 1

414 4.05E+01 3.35E-01 12.5 8 46 1

415 4.05E+01 3.22E+00 17.5 13 34 1

416 8.50E+02 9.86E-02 12.5 6 51 1

417 4.05E+01 1.79E+01 17.5 5 12 1

418 2.47E+03 1.28E-01 12.5 12 74 1

419 1.42E+02 1.46E+02 12.5 2 71 1

420 8.90E+03 2.24E-05 17.5 8 74 1

421 2.02E+02 2.46E+00 12.5 8 63 1

422 4.05E+01 2.24E+00 12.5 4 72 1

423 1.62E+02 5.59E+01 12.5 9 42 1

424 5.40E+01 1.40E+01 22.5 4 58 1

425 2.27E+04 5.99E-01 7.5 8 32 1

426 8.09E+01 1.39E-01 22.5 4 81 1

427 4.05E+01 3.58E+00 7.5 12 45 1

428 2.63E+02 9.06E-01 17.5 5 34 1

429 4.05E+01 1.23E+01 17.5 5 1 1

430 1.21E+04 1.87E-03 12.5 4 65 1

431 2.02E+02 1.79E+00 12.5 2 74 1

432 1.21E+03 5.44E+00 12.5 12 49 1

433 4.86E+02 3.54E+00 17.5 1 77 1

434 3.64E+02 4.97E-01 12.5 1 61 1

435 4.05E+01 1.04E+02 12.5 4 51 1

436 1.01E+04 1.21E+00 17.5 2 74 1

437 2.23E+04 7.32E-01 12.5 4 39 1

438 8.09E+01 7.94E-01 12.5 9 51 1

439 2.02E+02 1.68E+01 12.5 12 49 1

440 1.62E+04 4.19E-01 22.5 12 78 1

441 4.65E+02 1.70E+00 17.5 5 12 1

442 2.02E+03 2.68E-01 12.5 12 71 1
Appendix D WMU and Hydrogeologic Environment Databases

Table D.3 Nationwide Database of Waste Pile Sites

Site

Numbe

r

Area Depth

Soil/GW

Temperature HG

Environment

Nearest

Climate

Center

Site

(m2) (m) ( C) Weighting

D-50

443 1.38E+03 2.21E-01 12.5 2 69 1

444 1.27E+03 1.67E+00 17.5 1 69 1

445 8.09E+01 2.80E-01 22.5 12 78 1

446 4.05E+01 2.80E+01 17.5 5 13 1

447 6.07E+01 4.00E+01 17.5 5 13 1

448 4.05E+04 1.12E-02 22.5 5 12 1

449 1.13E+03 7.19E-02 12.5 2 74 1

450 1.21E+04 1.64E+00 22.5 12 97 1

451 1.50E+03 1.81E+00 12.5 12 42 1

452 3.34E+04 4.26E-02 17.5 4 79 1

453 8.09E+01 1.01E+00 12.5 4 45 1

454 2.23E+02 3.76E-01 12.5 12 85 1

455 8.09E+01 2.80E+00 22.5 12 97 1

456 6.75E+01 -9.99E+02 7.5 2 66 1

457 2.02E+01 2.24E+01 12.5 2 39 1

458 4.05E+01 1.70E+01 7.5 2 48 1

459 8.50E+02 7.99E-01 22.5 4 91 1

460 2.06E+03 8.77E+00 12.5 12 49 1

461 4.05E+01 8.50E+00 12.5 4 51 1

462 2.02E+01 1.79E+00 12.5 5 74 1

463 4.05E+01 1.37E+01 17.5 1 69 1

464 3.64E+02 3.84E-03 12.5 12 87 1

465 1.21E+03 5.59E+00 22.5 12 78 1

466 4.45E+02 1.42E+00 12.5 2 39 1

467 3.64E+02 1.37E-04 12.5 2 45 1

468 2.02E+02 2.01E+00 17.5 5 34 1

469 5.26E+03 5.68E-01 12.5 12 69 1

470 2.02E+05 1.12E-01 12.5 1 71 1

471 2.02E+01 3.28E+00 7.5 2 32 1

472 2.43E+02 2.79E-01 7.5 8 32 1

473 1.11E+04 1.61E-04 17.5 13 34 1

474 2.02E+01 8.95E+00 12.5 2 56 1

475 7.69E+04 2.05E-01 12.5 12 49 1

476 8.09E+03 7.27E-01 12.5 5 56 1

477 3.24E+04 2.32E+00 12.5 5 33 1

478 2.02E+01 -9.99E+02 12.5 4 66 1

479 7.28E+04 8.08E-01 12.5 12 74 1

480 4.05E+03 1.80E-01 17.5 12 89 1

481 4.45E+02 1.14E+01 17.5 5 12 1

482 2.02E+04 7.40E-05 17.5 1 89 1

483 2.02E+01 2.24E-01 22.5 4 81 1

484 1.38E+03 6.58E+00 12.5 4 66 1

485 1.21E+02 -9.99E+02 22.5 4 35 1

486 2.02E+01 8.95E+00 17.5 2 58 1
Appendix D WMU and Hydrogeologic Environment Databases

Table D.3 Nationwide Database of Waste Pile Sites

Site

Numbe

r

Area Depth

Soil/GW

Temperature HG

Environment

Nearest

Climate

Center

Site

(m2) (m) ( C) Weighting

D-51

487 1.86E+03 2.43E-01 17.5 4 90 1

488 1.01E+01 1.79E+00 12.5 4 71 1

489 4.05E+04 4.47E-01 12.5 2 66 1

490 4.05E+03 2.24E-01 12.5 4 39 1

491 2.02E+03 8.38E-04 22.5 13 36 1

492 1.21E+02 1.86E+03 22.5 5 12 1

493 1.35E+05 1.45E+00 17.5 4 90 1

494 4.05E+01 2.33E+01 17.5 5 12 1

495 1.13E+03 6.23E+00 17.5 5 12 1

496 4.05E+01 6.99E+00 17.5 2 36 1

497 1.62E+04 5.59E-01 12.5 4 39 1

498 2.02E+03 2.91E+00 12.5 4 72 1

499 4.05E+01 5.18E+00 17.5 1 95 1

500 2.51E+05 1.49E-01 12.5 13 56 1

501 4.45E+02 2.44E+01 17.5 5 34 1

502 1.42E+04 5.11E-01 12.5 2 86 1

503 1.21E+04 2.98E-01 12.5 2 66 1

504 4.05E+03 4.44E-04 17.5 4 90 1

505 2.83E+02 8.53E-01 12.5 2 66 1

506 1.94E+04 1.40E-01 12.5 5 29 1

507 4.05E+03 2.80E+00 7.5 4 31 29

508 1.62E+02 8.42E+00 17.5 1 95 29

509 2.02E+01 1.78E-01 12.5 2 86 29

510 4.05E+01 3.22E+01 7.5 2 48 7

511 2.02E+01 3.95E-02 12.5 4 66 7

512 2.02E+01 8.95E+01 17.5 5 12 7

513 4.05E+03 1.96E+00 12.5 13 40 1

514 3.24E+02 2.80E-02 12.5 4 52 7

515 7.28E+02 9.32E-01 17.5 1 98 1

516 1.38E+03 5.26E-01 7.5 1 64 1

517 4.05E+03 3.69E-01 17.5 4 93 1

518 6.07E+03 1.88E+01 12.5 2 2 1

519 6.88E+02 3.29E-01 7.5 4 31 1

520 1.62E+04 3.02E-01 22.5 4 81 1

521 6.27E+03 3.61E+00 12.5 12 69 1

522 2.91E+03 3.26E+00 12.5 8 42 1

523 1.25E+05 3.19E-02 22.5 12 91 1

524 1.01E+04 1.23E-01 17.5 12 93 1

525 6.58E+03 9.11E-02 7.5 4 31 1

526 4.65E+03 2.98E-02 17.5 4 90 1

527 3.08E+03 2.21E+01 22.5 4 92 1

528 1.62E+04 -9.99E+02 7.5 1 62 1

529 2.43E+04 7.46E-01 7.5 2 32 1

530 2.83E+02 1.28E-01 12.5 2 56 1

531 4.45E+02 1.53E+00 17.5 5 53 1
Appendix D WMU and Hydrogeologic Environment Databases

Table D.3 Nationwide Database of Waste Pile Sites

Site

Numbe

r

Area Depth

Soil/GW

Temperature HG

Environment

Nearest

Climate

Center

Site

(m2) (m) ( C) Weighting

D-52

532 9.11E+03 2.14E-01 22.5 4 92 1

533 8.73E+04 1.80E-03 12.5 2 45 1

534 2.19E+03 1.92E-03 7.5 2 48 1

535 2.27E+03 1.20E+00 17.5 4 69 1

536 4.52E+04 1.84E-07 7.5 1 64 1

537 1.42E+02 1.33E+01 12.5 2 45 1

538 6.21E+02 9.73E-01 7.5 2 48 1

539 5.06E+02 5.49E+01 12.5 2 66 1

540 4.11E+02 4.77E+00 7.5 1 62 1

541 1.01E+05 3.36E-02 17.5 4 69 1

542 4.86E+02 1.67E+02 7.5 2 48 1

543 4.05E+01 3.36E+01 12.5 4 66 1

544 2.37E+04 6.69E-01 7.5 1 44 1

545 6.75E+04 1.79E-01 22.5 4 92 1

546 9.31E+02 1.34E+00 12.5 8 46 1

547 6.07E+04 3.73E-01 22.5 12 91 1

548 4.05E+03 5.03E-02 17.5 5 90 1

549 4.05E+04 7.94E-02 12.5 5 40 1

550 1.86E+03 2.58E+00 12.5 8 82 1

551 7.28E+02 9.32E-01 17.5 1 98 1

552 1.62E+04 1.75E-01 17.5 4 90 1

553 5.58E+03 1.35E+00 12.5 5 40 1

554 1.89E+02 2.40E+01 7.5 13 48 1

555 2.02E+03 4.70E-01 22.5 4 96 1

556 8.09E+01 5.55E-02 12.5 5 33 30

557 2.02E+01 1.12E+00 17.5 5 12 30

558 2.02E+02 6.21E-02 17.5 1 79 30

559 2.02E+01 2.47E-03 12.5 4 72 30

560 2.02E+01 3.95E-02 7.5 8 49 4

561 2.83E+02 1.60E-01 7.5 2 32 4

562 4.05E+01 9.86E-03 22.5 4 81 4

563 2.06E+03 2.19E+00 22.5 4 92 4

564 4.45E+02 2.03E+00 17.5 12 95 4

565 9.31E+02 3.65E-01 17.5 12 95 4

566 2.02E+01 4.93E-02 7.5 8 32 4

567 4.05E+01 8.38E-02 7.5 5 3 4

568 2.02E+01 1.13E-01 12.5 2 66 4

569 2.35E+04 3.57E-02 17.5 5 12 4

570 2.02E+01 6.71E+00 12.5 12 42 4

571 2.39E+04 5.00E-01 17.5 13 56 4

572 1.21E+03 2.24E+01 17.5 12 89 4

573 1.29E+06 1.94E-08 22.5 2 21 4

574 1.52E+03 2.98E+00 12.5 2 40 4

575 2.02E+01 3.60E-01 12.5 5 40 4
Appendix D WMU and Hydrogeologic Environment Databases

Table D.3 Nationwide Database of Waste Pile Sites

Site

Numbe

r

Area Depth

Soil/GW

Temperature HG

Environment

Nearest

Climate

Center

Site

(m2) (m) ( C) Weighting

D-53

576 4.17E+03 3.91E-01 22.5 13 30 4

577 8.09E+01 2.12E+00 7.5 2 45 4

578 2.02E+01 2.96E-02 12.5 2 86 4

579 4.25E+02 3.85E-01 17.5 13 90 4

580 1.01E+01 2.24E+00 12.5 8 42 4

581 2.02E+01 5.37E+01 17.5 5 12 4

582 9.31E+02 1.17E+01 12.5 4 74 1

583 8.09E+02 2.52E-01 17.5 1 69 1

584 1.01E+03 3.13E+00 12.5 1 31 1

585 2.23E+02 2.03E+00 12.5 12 45 1

586 7.28E+02 3.11E-02 17.5 12 95 1

587 1.38E+03 3.29E-01 12.5 5 40 1

588 2.31E+03 2.75E+00 17.5 12 93 1

589 2.02E+06 1.57E+00 22.5 5 22 1

590 1.38E+03 1.32E-01 7.5 1 65 1

591 7.61E+03 6.82E-01 12.5 5 69 1

592 2.02E+03 5.03E-02 12.5 13 40 1

593 7.28E+02 6.21E-01 12.5 4 45 1

594 1.74E+03 1.95E-01 17.5 5 90 1

595 3.44E+03 1.32E-01 12.5 8 9 1

596 8.09E+04 2.01E-02 12.5 5 26 1

597 2.57E+04 5.53E+00 22.5 2 22 1

598 8.90E+02 2.85E+00 17.5 2 74 1

599 8.94E+03 3.54E-01 12.5 1 31 1

600 8.38E+03 1.08E-02 17.5 4 93 1

601 3.43E+04 4.30E+00 17.5 4 22 1

602 2.43E+02 5.51E-02 7.5 2 45 1

603 4.86E+03 2.80E-01 12.5 12 72 1

604 1.01E+03 1.97E-01 12.5 2 71 1

605 2.31E+03 3.92E+00 12.5 8 9 1

606 4.05E+03 1.23E-05 12.5 5 40 1

607 5.26E+02 3.66E-01 17.5 4 90 1

608 2.02E+03 4.47E-01 12.5 13 20 1

609 3.56E+05 1.53E-01 17.5 13 90 1

610 4.05E+03 5.59E-02 17.5 4 23 1

611 5.06E+00 3.35E-01 12.5 12 42 1

612 8.50E+02 5.93E+00 12.5 8 46 1

613 4.45E+02 9.41E-03 12.5 12 48 1

614 2.02E+01 1.33E-01 12.5 2 66 1

615 9.31E+02 2.92E-02 17.5 5 53 30

616 2.02E+01 2.22E-01 12.5 2 88 30

617 2.02E+03 2.24E-01 7.5 4 83 30

618 4.65E+02 3.60E-01 17.5 13 53 30

619 2.02E+01 2.71E-02 12.5 8 53 30
Appendix D WMU and Hydrogeologic Environment Databases

Table D.3 Nationwide Database of Waste Pile Sites

Site

Numbe

r

Area Depth

Soil/GW

Temperature HG

Environment

Nearest

Climate

Center

Site

(m2) (m) ( C) Weighting

D-54

620 2.02E+01 4.14E-01 12.5 12 72 30

621 6.75E+00 1.48E-01 22.5 4 96 30

622 2.43E+02 7.40E-03 17.5 5 53 11

623 3.04E+03 1.12E+00 12.5 12 49 11

624 4.05E+01 3.45E-02 7.5 12 48 11

625 2.02E+01 4.47E+01 22.5 4 96 11

626 6.88E+02 2.20E-01 17.5 4 30 11

627 2.02E+01 2.24E+00 12.5 5 40 11

628 1.01E+05 8.95E-04 7.5 5 10 11

629 5.26E+03 3.10E-01 22.5 5 92 11

630 6.07E+03 1.86E-03 17.5 2 90 11

631 2.02E+01 1.97E-02 7.5 12 48 11

632 9.31E+02 1.95E+00 12.5 13 74 1

633 4.86E+04 9.32E-02 22.5 11 94 1

634 5.67E+02 8.81E-05 12.5 2 88 1

635 2.02E+01 2.15E+01 17.5 4 77 1

636 3.72E+03 6.08E-03 17.5 12 95 1

637 4.05E+01 3.36E+01 7.5 12 48 1

638 4.45E+02 4.98E+00 17.5 4 90 1

639 1.21E+04 2.44E-01 7.5 12 48 1

640 1.86E+03 7.29E+00 12.5 12 42 1

641 1.62E+03 2.77E-03 17.5 1 79 1

642 3.64E+02 6.82E-02 12.5 9 51 1

643 2.59E+04 3.32E-01 22.5 13 92 1

644 3.24E+03 2.21E+00 12.5 12 48 1

645 8.09E+03 1.68E-03 22.5 12 76 1

646 1.21E+02 1.68E+00 12.5 12 69 24

647 4.05E+03 5.59E-02 12.5 2 86 2

648 2.02E+01 1.12E+00 12.5 8 46 2

649 5.67E+02 1.48E-01 12.5 2 53 2

650 2.43E+02 2.34E-02 7.5 5 3 2

651 4.05E+02 6.66E-03 22.5 4 96 2

652 8.09E+01 3.32E-01 17.5 5 13 1

653 2.02E+01 2.47E-02 12.5 1 71 1

654 2.02E+01 5.59E+00 12.5 4 88 1

655 1.13E+03 3.99E-01 17.5 13 20 1

656 4.45E+02 -9.99E+02 17.5 5 12 1

657 1.82E+03 5.74E-01 12.5 1 69 1

658 1.01E+01 4.44E-02 22.5 4 96 1

659 3.36E+03 3.37E-02 12.5 1 83 1

660 2.02E+01 4.44E-02 7.5 13 68 24

661 1.38E+03 2.96E-01 12.5 2 74 24

662 3.24E+03 3.48E-03 12.5 2 85 24

663 2.02E+03 3.58E-01 12.5 2 83 1
Appendix D WMU and Hydrogeologic Environment Databases

Table D.3 Nationwide Database of Waste Pile Sites

Site

Numbe

r

Area Depth

Soil/GW

Temperature HG

Environment

Nearest

Climate

Center

Site

(m2) (m) ( C) Weighting

D-55

664 6.48E+02 1.47E-01 12.5 9 42 1

665 4.09E+03 1.66E-01 17.5 5 12 1

666 4.05E+04 4.47E-01 12.5 4 66 1

667 2.23E+02 1.52E-01 17.5 1 95 1

668 2.43E+02 1.19E-02 12.5 5 26 1

669 2.43E+02 3.73E+00 17.5 4 80 1

670 6.07E+03 2.42E-02 12.5 12 74 1

671 4.05E+01 2.68E+01 12.5 4 72 1

672 2.02E+02 8.88E-03 17.5 5 100 1

673 1.82E+02 7.46E+00 22.5 4 96 1

674 2.02E+03 1.13E-03 22.5 12 92 1

675 5.67E+02 3.20E+00 17.5 5 37 1

676 4.05E+03 1.80E-01 12.5 5 4 1

677 4.05E+01 3.23E+00 12.5 2 66 1

678 1.21E+02 6.71E-01 22.5 12 76 1

679 7.43E+03 1.68E-02 7.5 4 25 1

680 2.02E+01 8.38E-02 17.5 5 12 1

681 1.62E+02 1.68E-01 7.5 4 68 1

682 7.28E+02 1.55E-01 12.5 12 54 1

683 1.38E+03 3.26E-03 22.5 4 81 1

684 2.53E+02 3.91E-01 12.5 8 82 1

685 1.62E+04 3.50E-02 12.5 2 45 1

686 2.09E+04 3.03E-02 12.5 12 54 1

687 4.05E+01 5.18E-02 17.5 12 95 1

688 2.83E+02 2.51E+00 17.5 13 13 1

689 3.04E+03 7.40E-04 17.5 4 23 1

690 1.54E+04 4.12E-02 7.5 2 7 1

691 4.05E+02 1.12E+00 12.5 4 72 1

692 4.05E+03 7.22E-01 22.5 4 81 1

693 5.40E+02 1.12E+00 12.5 2 66 1

694 1.01E+04 1.58E-04 17.5 13 90 1

695 9.31E+02 9.73E-01 12.5 5 26 1

696 9.31E+02 2.07E-01 12.5 5 26 1

697 1.42E+02 9.59E-01 12.5 2 66 1

698 1.42E+02 1.60E-01 17.5 4 95 1

699 4.45E+02 1.02E+00 17.5 13 81 1

700 3.72E+03 1.02E-01 7.5 4 31 1

701 1.38E+03 1.69E-02 17.5 4 95 1

702 8.09E+04 3.36E-03 17.5 4 92 1

703 1.38E+03 4.13E-03 12.5 2 45 1

704 6.07E+02 4.44E-03 12.5 5 4 1

705 8.09E+01 6.71E-01 12.5 5 74 1

706 4.05E+01 1.23E-03 17.5 13 37 1

707 4.05E+01 2.07E-01 12.5 5 26 1

708 4.05E+03 7.84E-03 22.5 4 96 1
Appendix D WMU and Hydrogeologic Environment Databases

Table D.3 Nationwide Database of Waste Pile Sites

Site

Numbe

r

Area Depth

Soil/GW

Temperature HG

Environment

Nearest

Climate

Center

Site

(m2) (m) ( C) Weighting

D-56

709 2.02E+04 4.47E-01 12.5 2 66 1

710 4.05E+01 1.12E+00 12.5 2 87 1

711 9.31E+02 9.73E-01 17.5 13 56 1

712 2.02E+03 8.88E-04 12.5 12 74 1

713 5.67E+02 6.39E+00 22.5 4 96 1

714 4.45E+02 2.03E-01 12.5 5 26 1

715 2.02E+01 2.46E+00 12.5 2 69 1

716 2.02E+03 4.47E-02 17.5 13 90 1

717 4.05E+01 2.24E-01 17.5 1 95 1

718 4.05E+01 1.23E-02 17.5 4 30 1

719 2.02E+03 8.95E-02 17.5 5 53 1

720 6.75E+00 1.12E+00 17.5 5 12 1

721 4.05E+03 4.47E-01 7.5 13 45 1

722 2.02E+01 8.88E-02 7.5 2 48 30

723 1.01E+01 1.97E-02 17.5 5 12 10

724 4.05E+01 8.39E+01 12.5 2 69 10

725 2.43E+02 -9.99E+02 12.5 4 63 10

726 2.02E+01 9.86E-03 17.5 5 12 10

727 2.02E+01 3.49E+01 12.5 4 56 10

728 2.02E+01 5.59E+00 7.5 13 45 10

729 2.02E+01 7.45E-01 17.5 5 12 10

730 2.83E+02 6.38E-02 12.5 12 54 1

731 2.02E+02 4.32E+01 17.5 1 89 1

732 8.09E+01 3.50E+00 12.5 12 51 1

733 9.31E+02 8.75E-01 12.5 4 51 1

734 5.06E+01 2.22E-02 12.5 4 45 1

735 8.50E+02 1.44E-01 12.5 4 72 1

736 4.05E+01 5.59E+01 22.5 5 92 31

737 2.02E+01 1.23E-01 22.5 4 92 31

738 2.02E+01 1.33E-01 17.5 2 36 31

739 2.02E+01 1.68E-01 17.5 4 34 31

740 2.02E+01 3.95E-02 17.5 5 21 31

741 1.21E+03 3.73E-02 7.5 1 64 7

742 2.02E+01 -9.99E+02 12.5 2 32 7

743 4.05E+01 1.68E+00 12.5 4 51 7

744 4.65E+02 5.93E-01 12.5 8 46 7

745 2.02E+01 9.86E-03 17.5 5 12 7

746 2.43E+02 1.16E-01 12.5 12 49 7

747 1.66E+03 6.82E-01 17.5 4 80 7

748 1.21E+03 1.49E+00 7.5 4 31 7

749 8.09E+01 5.60E-01 17.5 1 95 7

750 4.45E+02 2.75E+00 12.5 12 49 7

751 4.45E+02 1.64E-02 12.5 5 40 7

752 2.02E+01 8.88E-02 22.5 4 81 7
Appendix D WMU and Hydrogeologic Environment Databases

Table D.3 Nationwide Database of Waste Pile Sites

Site

Numbe

r

Area Depth

Soil/GW

Temperature HG

Environment

Nearest

Climate

Center

Site

(m2) (m) ( C) Weighting

D-57

753 2.02E+01 2.24E+00 17.5 5 14 7

754 2.02E+03 1.16E+00 22.5 12 93 7

755 4.05E+01 4.02E-01 12.5 12 42 7

756 6.48E+02 4.89E+00 17.5 5 12 1

757 1.10E+02 8.68E-01 12.5 4 74 1

758 1.21E+03 2.49E-01 17.5 1 95 1

759 1.62E+02 6.04E+01 12.5 2 52 1

760 1.62E+02 1.51E+01 12.5 12 49 1

761 4.05E+01 1.40E+02 12.5 12 49 1

762 4.05E+01 1.40E+02 12.5 12 49 1

763 4.05E+03 2.10E-01 12.5 6 73 1

764 8.09E+01 6.71E-01 12.5 9 51 1

765 1.21E+02 4.25E+01 7.5 2 45 1

766 2.83E+02 1.28E+01 7.5 1 64 1

767 1.94E+04 7.50E+00 12.5 2 52 1

768 2.02E+03 1.72E+01 7.5 2 32 1

769 8.09E+02 1.34E+01 12.5 8 63 1

770 2.43E+02 1.98E+00 7.5 2 32 1

771 1.01E+02 4.47E+00 7.5 12 48 1

772 8.09E+01 7.05E-01 12.5 2 59 1

773 2.02E+01 2.22E-01 12.5 1 53 1

774 1.82E+02 1.53E+01 12.5 8 42 1

775 4.05E+01 5.67E-02 12.5 4 51 1

776 2.08E+03 6.52E-01 22.5 4 81 1

777 2.02E+01 8.88E-02 17.5 4 90 1

778 8.09E+01 2.24E+00 22.5 4 92 1

779 4.05E+01 2.91E-01 12.5 12 49 1

780 6.75E+01 4.47E+01 12.5 5 40 1

781 4.05E+01 4.24E+00 17.5 4 34 1

782 2.02E+02 2.58E-01 12.5 5 74 1

783 5.06E+00 8.38E-02 12.5 4 72 1

784 4.05E+01 2.80E+00 17.5 1 77 1

785 8.09E+01 5.55E-02 17.5 4 95 1

786 9.31E+02 3.16E-01 12.5 12 52 1

787 4.05E+01 5.60E-01 12.5 1 71 1

788 2.22E+04 4.49E-02 12.5 9 63 1

789 8.09E+01 2.52E-01 17.5 2 36 1

790 8.09E+01 1.99E+00 7.5 13 68 1

791 9.31E+02 4.38E-01 17.5 5 13 1

792 4.05E+01 2.46E+01 7.5 13 32 1

793 9.11E+04 3.69E-01 7.5 2 32 1

794 2.02E+01 3.95E-02 12.5 12 42 22

795 2.02E+01 6.90E-01 12.5 12 42 2

796 6.88E+02 5.53E-02 12.5 2 71 2
Appendix D WMU and Hydrogeologic Environment Databases

Table D.3 Nationwide Database of Waste Pile Sites

Site

Numbe

r

Area Depth

Soil/GW

Temperature HG

Environment

Nearest

Climate

Center

Site

(m2) (m) ( C) Weighting

D-58

797 2.02E+01 2.68E+01 17.5 4 95 2

798 2.02E+01 3.36E+01 12.5 4 39 2

799 1.21E+02 7.46E-01 12.5 4 66 2

800 8.09E+01 7.64E-02 12.5 2 52 2

801 4.05E+01 7.89E-02 17.5 5 12 2

802 3.24E+02 3.50E+00 12.5 5 74 1

803 5.95E+03 2.71E-01 22.5 4 81 1

804 1.01E+01 1.04E-01 7.5 12 45 1

805 1.40E+06 8.41E-06 7.5 8 62 31

806 2.02E+01 4.44E-02 12.5 1 71 31

807 4.05E+01 1.01E-01 12.5 4 61 7

808 2.02E+03 4.44E-04 17.5 1 95 7

809 2.83E+02 3.20E+00 17.5 1 79 7

810 2.02E+01 5.57E-01 17.5 12 89 7

811 2.83E+02 8.00E-02 12.5 1 63 1

812 8.09E+01 4.70E+01 17.5 1 95 1

813 8.09E+01 6.29E-01 17.5 1 89 1

814 1.01E+04 1.18E-01 12.5 12 72 1

815 2.83E+02 2.21E-01 17.5 12 85 1

816 2.33E+03 1.94E-02 17.5 1 77 1

817 8.09E+01 5.55E-03 12.5 2 42 1

818 6.52E+03 2.92E-01 12.5 1 69 1

819 1.49E+04 8.53E-04 12.5 1 69 1

820 8.09E+01 3.08E-02 17.5 1 69 1

821 4.05E+01 1.23E-02 17.5 5 12 29

822 4.05E+03 -9.99E+02 7.5 1 31 3

823 2.02E+01 2.91E+00 7.5 12 48 3

824 2.02E+01 2.22E-01 22.5 12 58 3

825 4.05E+03 1.54E-01 12.5 2 85 1

826 2.02E+03 1.12E+00 7.5 8 62 1

827 2.29E+02 2.63E-01 12.5 2 66 1
Appendix D WMU and Hydrogeologic Environment Databases

D-59

Table D.4 Nationwide Database of Land Application Unit Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate Center

Site

Weighting

1 4.05E+05 9.65E-01 12.5 1 2 1

2 2.43E+04 5.75E-05 12.5 2 2 30

3 4.45E+06 7.11E-01 12.5 2 2 1

4 1.01E+04 2.82E-02 12.5 5 2 1

5 4.05E+03 3.76E-02 7.5 2 3 1

6 6.07E+04 1.71E+00 7.5 5 3 24

7 4.86E+05 1.68E+00 12.5 1 5 1

8 2.02E+04 9.31E-02 7.5 1 7 10

9 4.05E+03 1.86E+00 7.5 1 7 1

10 2.10E+05 9.68E-03 7.5 1 7 11

11 1.01E+03 1.87E-03 7.5 4 7 1

12 2.02E+03 9.49E-02 12.5 1 8 30

13 6.48E+05 4.07E-01 12.5 1 8 11

14 1.94E+06 7.85E-01 12.5 8 9 1

15 1.05E+06 7.09E-01 12.5 8 9 1

16 9.31E+03 1.63E-02 17.5 5 13 1

17 4.05E+03 4.46E-03 17.5 5 13 1

18 8.09E+06 3.02E-04 17.5 5 13 30

19 5.58E+03 5.29E-03 17.5 5 13 30

20 4.05E+01 5.65E-01 17.5 5 13 30

21 6.07E+03 3.10E-01 17.5 5 13 11

22 6.07E+04 6.82E-01 17.5 5 13 11

23 4.05E+05 3.58E-01 17.5 5 13 11

24 1.01E+05 2.98E-01 17.5 5 13 1

25 4.05E+05 1.12E+00 17.5 5 13 1

26 1.21E+06 1.43E-01 17.5 5 13 1

27 1.26E+06 2.47E-01 17.5 5 13 1

28 3.24E+05 8.38E-02 17.5 5 13 1

29 4.05E+03 4.46E-03 17.5 5 15 30

30 5.10E+05 3.91E-01 12.5 4 20 1

31 1.21E+05 6.06E-01 17.5 5 20 1

32 4.05E+03 5.59E-02 22.5 5 21 11

33 9.31E+04 5.62E-01 17.5 4 23 1

34 6.48E+03 4.40E-02 17.5 4 23 1

35 1.21E+04 1.86E-02 17.5 5 23 1

36 1.09E+05 2.84E-01 17.5 5 23 1

37 4.05E+01 -9.99E+02 7.5 1 25 20

38 8.09E+07 1.12E-05 7.5 4 25 16

39 4.32E+04 -9.99E+02 7.5 4 25 1

40 1.27E+05 9.68E-03 12.5 2 29 1

41 2.83E+04 1.99E-03 12.5 7 29 1

42 1.90E+05 6.98E-01 17.5 2 30 1

43 4.61E+05 1.30E-04 17.5 4 30 1

44 9.71E+05 2.43E-02 17.5 4 30 1

45 6.68E+06 4.51E-01 17.5 4 30 1
Appendix D WMU and Hydrogeologic Environment Databases

Table D.4 Nationwide Database of Land Application Unit Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate Center

Site

Weighting

D-60

46 5.71E+04 1.12E-02 7.5 2 31 1

47 8.50E+04 1.59E+00 7.5 2 31 30

48 1.62E+05 2.80E-03 7.5 2 31 30

49 2.43E+04 2.47E-05 7.5 2 31 30

50 1.17E+05 1.48E-03 7.5 4 31 30

51 4.05E+05 1.11E-03 12.5 8 31 1

52 3.74E+05 2.03E+00 12.5 8 31 1

53 4.45E+04 4.07E-03 7.5 2 32 9

54 2.43E+05 5.58E-01 7.5 2 32 1

55 2.43E+05 3.10E-01 7.5 8 32 11

56 3.24E+05 9.60E-01 7.5 8 32 1

57 1.72E+05 8.41E-05 7.5 8 32 1

58 1.90E+04 3.17E-03 12.5 2 33 1

59 6.48E+05 2.80E-03 12.5 5 33 1

60 8.46E+05 3.34E-03 17.5 2 34 1

61 2.36E+05 3.99E-03 17.5 2 34 1

62 3.24E+04 5.03E-03 22.5 4 35 1

63 2.79E+04 4.09E-02 22.5 4 35 1

64 1.42E+03 2.08E-02 22.5 4 35 1

65 8.50E+02 2.66E-01 22.5 4 35 1

66 2.10E+03 2.37E-06 17.5 5 37 3

67 6.48E+05 1.44E-01 12.5 2 39 2

68 1.13E+04 8.81E-08 7.5 1 40 1

69 1.21E+05 6.20E-02 7.5 12 41 11

70 4.05E+03 2.22E-04 12.5 2 42 1

71 3.44E+05 6.51E-04 12.5 12 42 1

72 4.05E+03 2.91E-03 12.5 12 42 1

73 8.09E+03 2.33E-03 12.5 12 42 1

74 1.78E+04 4.23E-03 12.5 12 42 1

75 2.02E+01 5.42E-02 12.5 12 42 30

76 4.45E+02 -9.99E+02 12.5 12 42 1

77 2.02E+05 1.33E-05 12.5 12 42 1

78 2.23E+06 3.72E-04 12.5 12 42 2

79 1.21E+04 7.46E-01 12.5 6 42 1

80 3.04E+05 4.53E-04 12.5 8 42 29

81 5.91E+04 -9.99E+02 12.5 8 42 1

82 1.70E+05 1.66E-02 12.5 8 42 30

83 9.31E+05 3.11E-03 12.5 8 42 1

84 5.74E+04 1.15E+00 12.5 9 42 1

85 2.02E+05 4.49E-05 12.5 9 42 1

86 2.43E+05 3.25E-05 12.5 9 42 24

87 4.17E+04 7.50E-02 12.5 9 42 2

88 1.01E+05 6.26E-04 7.5 2 45 11

89 1.34E+05 1.24E+00 7.5 2 45 1

90 9.31E+02 1.63E-01 12.5 8 46 1
Appendix D WMU and Hydrogeologic Environment Databases

Table D.4 Nationwide Database of Land Application Unit Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate Center

Site

Weighting

D-61

91 4.65E+05 6.31E-01 12.5 8 46 11

92 4.45E+04 4.33E-03 12.5 8 46 1

93 2.43E+04 5.97E-02 12.5 8 46 1

94 2.02E+04 6.71E-01 12.5 1 100 22

95 1.21E+04 7.44E-01 7.5 2 48 30

96 3.84E+05 1.47E-01 7.5 2 48 11

97 6.31E+05 6.92E-02 7.5 2 48 11

98 3.35E+05 5.62E-03 7.5 2 48 1

99 1.74E+06 6.49E-01 7.5 2 48 1

100 3.24E+06 1.17E-02 7.5 4 48 1

101 3.71E+04 2.54E-04 7.5 12 48 1

102 4.86E+04 7.76E-03 7.5 12 48 11

103 2.71E+05 -9.99E+02 12.5 12 48 1

104 8.09E+03 2.17E-03 12.5 12 49 1

105 9.11E+05 4.08E-04 12.5 12 49 30

106 9.71E+04 1.05E-03 12.5 12 49 1

107 5.67E+05 3.09E-01 7.5 2 50 30

108 3.76E+05 1.85E-01 7.5 2 50 11

109 5.91E+04 1.24E-03 12.5 2 50 1

110 2.68E+05 4.92E-03 12.5 12 50 1

111 8.09E+05 2.24E-03 12.5 12 50 1

112 9.11E+05 5.17E-03 12.5 2 51 30

113 1.82E+05 4.55E-02 12.5 4 51 11

114 2.02E+06 6.90E-01 12.5 4 51 1

115 7.57E+05 5.44E-03 12.5 12 51 1

116 3.69E+05 3.20E-04 12.5 9 51 1

117 2.79E+03 3.57E-05 12.5 2 52 3

118 2.02E+01 1.88E+00 12.5 2 52 30

119 2.02E+04 1.07E-02 12.5 4 52 3

120 2.02E+04 2.03E-01 12.5 4 52 1

121 8.78E+05 3.90E-03 12.5 12 52 11

122 2.23E+04 1.01E-03 7.5 12 53 11

123 7.59E+04 7.89E-05 17.5 5 53 1

124 1.01E+06 2.68E-05 17.5 5 53 30

125 2.02E+06 2.13E-03 17.5 5 53 11

126 2.63E+04 5.31E-05 12.5 12 54 1

127 3.72E+03 9.25E-03 12.5 12 54 1

128 8.09E+04 1.40E-04 12.5 12 54 30

129 1.01E+05 4.47E-02 12.5 12 54 1

130 4.05E+04 7.52E-02 12.5 12 54 1

131 2.43E+06 1.45E-04 12.5 4 55 1

132 1.01E+05 6.02E-04 12.5 4 55 1

133 2.02E+04 2.33E-03 12.5 2 56 2

134 8.09E+05 3.50E-04 12.5 5 56 1

135 1.09E+05 1.76E-03 22.5 12 57 1
Appendix D WMU and Hydrogeologic Environment Databases

Table D.4 Nationwide Database of Land Application Unit Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate Center

Site

Weighting

D-62

136 4.05E+01 5.57E-01 17.5 2 58 1

137 3.64E+06 1.02E+00 17.5 2 58 1

138 1.62E+04 2.02E-03 22.5 2 58 9

139 1.21E+04 -9.99E+02 22.5 4 58 1

140 8.09E+03 6.71E-02 12.5 1 63 1

141 1.01E+06 2.68E-03 12.5 5 64 1

142 1.62E+05 5.03E-04 12.5 5 64 1

143 2.43E+04 2.05E-07 12.5 5 64 1

144 3.24E+03 2.80E-03 12.5 4 66 11

145 1.28E+06 2.45E-03 12.5 4 66 1

146 9.31E+02 9.72E-02 7.5 4 68 1

147 4.05E+04 9.31E-03 7.5 4 68 30

148 4.05E+04 2.24E-03 12.5 1 69 1

149 4.05E+04 4.02E-04 12.5 1 69 1

150 1.21E+04 2.33E-03 12.5 1 69 1

151 3.22E+04 4.70E-01 12.5 12 69 1

152 4.05E+04 9.31E-04 12.5 12 69 16

153 1.01E+04 8.93E-02 12.5 12 69 11

154 8.09E+05 1.90E-03 12.5 12 69 1

155 2.10E+03 9.68E-02 12.5 12 69 24

156 2.02E+05 6.83E-01 12.5 5 69 1

157 9.15E+05 8.24E-04 17.5 1 69 1

158 2.83E+04 6.71E-03 17.5 1 69 1

159 1.30E+05 7.30E-02 17.5 1 69 1

160 8.09E+04 3.48E-04 17.5 1 69 2

161 4.05E+04 2.79E-01 17.5 1 69 1

162 1.54E+05 1.71E-01 17.5 1 69 1

163 1.01E+05 2.66E-05 17.5 4 69 1

164 1.21E+05 6.86E-01 12.5 1 71 1

165 1.01E+05 7.52E-03 12.5 1 71 1

166 2.19E+05 6.89E-03 12.5 1 71 1

167 2.02E+04 3.35E-03 12.5 2 71 1

168 1.21E+03 7.40E-04 12.5 2 71 30

169 1.32E+05 4.29E-01 12.5 2 71 11

170 1.19E+05 2.47E-09 12.5 12 71 1

171 2.43E+05 7.44E-05 12.5 1 72 30

172 1.54E+05 2.33E-01 12.5 1 72 1

173 5.67E+02 3.17E-03 12.5 4 72 1

174 4.05E+03 4.50E-04 12.5 4 72 1

175 9.31E+02 -9.99E+02 12.5 4 72 1

176 2.91E+05 6.46E-01 12.5 4 72 1

177 8.09E+01 -9.99E+02 12.5 4 72 2

178 1.62E+05 3.08E-08 17.5 4 72 1

179 2.79E+03 2.70E-01 12.5 4 73 1

180 7.28E+05 2.17E-01 12.5 6 73 1
Appendix D WMU and Hydrogeologic Environment Databases

Table D.4 Nationwide Database of Land Application Unit Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate Center

Site

Weighting

D-63

181 8.09E+03 4.89E-03 12.5 6 73 1

182 9.31E+02 1.98E-01 12.5 9 73 1

183 2.02E+04 2.47E-05 12.5 2 74 30

184 1.42E+05 3.52E-08 12.5 12 74 30

185 4.05E+05 9.31E-02 12.5 12 74 11

186 4.05E+04 6.15E-03 17.5 2 74 1

187 4.09E+04 6.09E-03 17.5 2 74 1

188 8.09E+03 4.93E-05 17.5 2 74 10

189 2.83E+05 2.24E-03 17.5 4 74 1

190 1.21E+05 1.15E-05 17.5 12 74 16

191 8.63E+05 1.25E-03 17.5 12 74 2

192 3.28E+04 1.16E-01 17.5 5 74 1

193 1.21E+04 1.56E-04 22.5 12 76 1

194 4.61E+05 2.19E+00 22.5 12 76 1

195 1.52E+05 -9.99E+02 22.5 12 76 1

196 4.90E+05 1.04E-01 22.5 12 76 1

197 4.05E+05 2.21E-03 22.5 12 76 1

198 2.02E+01 3.45E-02 17.5 1 77 30

199 6.03E+04 4.20E-02 17.5 1 77 11

200 6.07E+04 1.86E-03 17.5 1 77 11

201 3.34E+05 5.63E-03 17.5 1 77 1

202 1.62E+04 2.33E-01 17.5 1 77 1

203 1.34E+05 1.76E+00 17.5 1 77 1

204 4.05E+06 1.40E-03 17.5 1 77 1

205 1.62E+05 1.16E+00 17.5 2 77 1

206 1.94E+05 2.04E-01 17.5 2 77 1

207 6.07E+04 7.75E-02 17.5 4 77 1

208 2.70E+05 9.25E-06 17.5 4 77 16

209 8.09E+05 3.65E-03 17.5 4 77 1

210 2.51E+03 -9.99E+02 22.5 12 78 3

211 1.51E+06 -9.99E+02 22.5 12 78 1

212 1.21E+03 1.57E-02 22.5 12 78 2

213 3.52E+05 -9.99E+02 22.5 10 78 1

214 8.09E+03 -9.99E+02 17.5 1 79 1

215 6.07E+03 3.38E-02 17.5 1 79 9

216 6.75E+05 9.68E-04 17.5 1 79 30

217 5.26E+04 1.18E+00 17.5 1 79 1

218 6.07E+04 6.04E-01 17.5 1 79 1

219 1.62E+04 2.26E-03 17.5 1 79 1

220 4.05E+03 6.71E-03 17.5 1 79 31

221 9.31E+03 6.07E-03 17.5 1 79 7

222 7.42E+03 6.84E-01 17.5 1 79 1

223 6.48E+03 5.82E-02 17.5 1 79 1

224 8.09E+04 6.98E-02 17.5 1 79 1

225 2.02E+05 3.35E-04 17.5 4 79 1
Appendix D WMU and Hydrogeologic Environment Databases

Table D.4 Nationwide Database of Land Application Unit Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate Center

Site

Weighting

D-64

226 1.65E+06 3.56E-03 17.5 4 79 1

227 2.02E+05 1.12E-03 17.5 4 79 1

228 4.61E+05 1.28E-02 17.5 2 80 1

229 2.18E+04 -9.99E+02 17.5 4 80 1

230 4.73E+03 2.71E-02 17.5 4 80 1

231 4.05E+04 1.84E-02 17.5 4 80 1

232 3.24E+02 1.54E-05 22.5 4 81 1

233 5.67E+02 1.76E-04 22.5 4 81 1

234 1.74E+03 1.52E-01 22.5 4 81 1

235 2.43E+04 1.12E-02 22.5 4 81 1

236 5.26E+04 5.01E-01 22.5 4 81 1

237 3.24E+05 1.23E-02 22.5 4 81 1

238 1.34E+05 5.64E-02 22.5 4 81 2

239 1.34E+04 3.74E-07 22.5 4 81 1

240 4.05E+03 9.76E-03 22.5 4 81 1

241 1.62E+04 7.05E-01 22.5 4 81 1

242 1.82E+06 4.59E-03 22.5 4 81 1

243 4.05E+04 3.87E-01 22.5 4 81 2

244 7.28E+05 1.62E-02 22.5 4 81 1

245 2.43E+04 1.54E-02 22.5 4 81 1

246 1.62E+04 1.86E-01 22.5 4 81 1

247 2.43E+04 1.12E-02 22.5 4 81 1

248 9.71E+04 3.89E-03 22.5 4 81 1

249 2.83E+04 7.31E-03 12.5 1 83 1

250 1.62E+04 1.40E-01 7.5 1 84 30

251 1.62E+05 1.12E-03 17.5 12 85 1

252 4.05E+04 1.11E-04 12.5 2 88 30

253 5.67E+03 1.66E-01 12.5 2 88 11

254 2.43E+05 1.21E-01 12.5 2 88 1

255 5.67E+04 4.56E-03 17.5 12 89 1

256 6.88E+05 6.58E-04 17.5 12 89 1

257 4.05E+04 2.09E-02 17.5 12 89 1

258 2.43E+05 7.44E-05 17.5 12 89 2

259 4.05E+02 1.88E-01 17.5 12 89 2

260 2.02E+04 5.10E-03 17.5 12 89 1

261 4.05E+01 2.22E-02 17.5 4 90 30

262 5.26E+04 8.54E-05 17.5 5 90 1

263 2.02E+06 8.95E-04 17.5 5 90 7

264 2.02E+05 5.21E-03 17.5 5 90 30

265 2.02E+04 2.17E-02 17.5 5 90 1

266 6.48E+04 9.07E-01 22.5 12 91 1

267 1.21E+06 6.20E-01 22.5 12 91 1

268 1.54E+05 9.74E-01 22.5 12 91 1

269 3.24E+05 1.01E+00 22.5 12 91 1

270 1.21E+05 1.49E-04 22.5 10 91 1
Appendix D WMU and Hydrogeologic Environment Databases

Table D.4 Nationwide Database of Land Application Unit Sites

Site

Number

Area

(m2)

Depth

(m)

Soil/GW

Temperature

( C)

HG

Environment

Nearest

Climate Center

Site

Weighting

D-65

271 2.63E+03 1.72E-02 17.5 4 92 1

272 7.45E+03 5.11E-01 22.5 4 92 1

273 8.09E+03 3.38E-01 22.5 4 92 2

274 2.79E+04 3.87E-02 22.5 4 92 1

275 4.05E+04 2.51E-03 22.5 4 92 1

276 6.07E+05 5.97E-03 22.5 4 92 7

277 5.58E+05 7.97E-04 22.5 4 92 1

278 5.26E+05 2.68E-02 22.5 5 92 1

279 2.83E+04 1.60E-03 17.5 1 93 1

280 2.02E+06 4.47E-03 17.5 1 93 1

281 3.04E+06 1.49E-05 17.5 1 93 1

282 1.05E+04 5.31E-03 17.5 4 93 1

283 5.34E+05 -9.99E+02 17.5 4 93 1

284 4.05E+05 -9.99E+02 17.5 4 93 1

285 4.65E+05 3.84E-02 17.5 4 93 1

286 1.21E+05 3.10E-02 17.5 4 93 1

287 2.02E+04 1.13E-01 17.5 4 93 1

288 8.22E+05 2.40E-04 17.5 4 93 1

289 5.67E+04 1.13E-01 17.5 12 93 1

290 1.62E+05 2.02E-04 17.5 12 93 1

291 3.24E+03 1.54E-06 22.5 12 93 7

292 2.02E+04 3.00E-02 22.5 10 94 1

293 2.02E+04 2.42E-02 17.5 1 95 1

294 9.31E+04 9.47E-01 17.5 1 95 1

295 2.16E+02 9.40E-01 17.5 1 95 1

296 1.21E+05 7.13E-01 17.5 1 95 7

297 1.62E+04 2.01E-02 17.5 1 95 7

298 2.02E+06 1.79E-03 17.5 4 95 1

299 3.64E+05 4.14E-02 17.5 12 95 1

300 4.05E+05 7.46E-05 17.5 12 95 1

301 1.42E+05 1.46E-03 17.5 12 95 1

302 8.09E+03 1.68E-02 22.5 4 96 3

303 2.51E+04 3.30E-02 22.5 4 96 1

304 8.09E+03 9.40E-02 22.5 4 96 1

305 4.05E+03 9.04E-01 22.5 4 96 9

306 1.62E+04 1.85E-05 22.5 4 96 30

307 4.86E+04 -9.99E+02 22.5 4 96 11

308 2.69E+05 8.71E-04 22.5 4 96 1

309 2.89E+05 1.30E-02 22.5 4 96 1

310 1.01E+03 3.58E-02 22.5 4 96 1

311 2.23E+05 1.65E-03 22.5 4 96 1
Appendix D WMU and Hydrogeologic Environment Databases

D-66

Table D.5 Hydrogeologic Database for HG Environment 1

Subsurface Environment Description

Metamorphic and Igneous

Hydraulic

Conductivity

(m/yr)

Unsaturated Zone

Thickness

(m)

Saturated Zone

Thickness

(m)

Regional Hydraulic

Gradient

(m/m)

-999 2.59E+01 -999 1.66E-02

3.15E+00 1.68E+01 1.52E+02 -999

-999 1.52E+01 1.52E+01 -999

-999 6.10E+02 -999 1.00E-04

-999 5.79E+00 9.14E+00 5.00E-02

9.46E+02 4.57E+00 -999 1.40E-02

1.58E+03 3.05E+00 -999 1.40E-02

6.31E+01 4.88E+00 1.22E+01 7.00E-02

3.47E+03 6.10E+00 1.52E+02 3.00E-02

2.84E+01 2.04E+00 9.14E+00 1.00E-02

1.26E+02 6.10E+00 7.32E+00 3.00E-02

1.58E+01 3.81E+00 3.29E+01 9.00E-02

3.15E+02 2.13E+01 3.05E+00 -999

-999 6.10E+00 6.10E+00 7.00E-06

1.10E+04 3.05E+00 1.83E+01 2.00E-02

9.46E+01 1.83E+00 4.27E+00 4.00E-02

-999 1.22E+00 9.14E+00 1.00E-02

7.57E+03 1.52E+00 3.05E+00 7.00E-06

6.31E+00 9.14E-01 6.10E+00 3.80E-02

6.31E+00 1.83E+00 7.62E+00 1.00E-01

3.15E+01 6.10E+00 -999 6.00E-02

3.15E+01 3.05E-01 6.10E+00 5.00E-03

-999 9.14E+00 1.52E+02 8.00E-03

Note: -999 indicates a missing sample value.
Appendix D WMU and Hydrogeologic Environment Databases

D-67

Table D.6 Hydrogeologic Statistics for HG Environment 1

Subsurface Environment Statistics

Metamorphic and Igneous

Mean Values

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

-8.52129 2.81441 3.76962 -3.97399

Covariance Matrix

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

Hydraulic

Conductivity

ln(cm/s) 6.82319

Unsaturated Zone

Thickness ln(ft) 1.07478 0.8005

Saturated Zone

Thickness ln(ft) 1.80348 0.55257 1.1956

Regional Hydraulic

Gradient ln(ft/ft) -0.39418 0.4367 0.17788 0.81424

Table D.7 Hydrogeologic Database for HG Environment 2

Subsurface Environment Description

Bedded Sedimentary Rock

Hydraulic

Conductivity

Unsaturated Zone

Thickness

Saturated Zone

Thickness

Regional Hydraulic

Gradient

(m/yr) (m) (m) (m/m)

6.31E+01 6.10E+00 2.29E+01 8.00E-02

2.84E+01 6.10E+00 7.93E+01 -999

1.89E+03 7.65E+01 -999 8.00E-03

5.99E+03 3.05E+01 1.83E+02 1.00E-03

3.15E+02 6.55E+01 4.57E+01 5.70E-03

3.15E+01 1.52E+01 2.13E+01 1.00E-01

1.58E+03 1.74E+02 3.05E+01 -999

3.15E+02 5.97E+00 3.60E+00 -999

2.21E+01 1.22E+01 1.07E+01 2.80E-02

2.84E+02 1.68E+01 3.05E+00 3.20E-03

9.46E+00 6.10E+00 1.52E+02 3.10E-02

2.21E+02 9.14E+00 -999 8.00E-03

3.15E+00 3.96E+00 4.57E+00 1.00E-02

3.15E+00 4.57E+00 9.14E+01 1.00E-03

2.21E+03 1.52E+01 3.05E+01 3.30E-02
Appendix D WMU and Hydrogeologic Environment Databases

Table D.7 Hydrogeologic Database for HG Environment 2

Subsurface Environment Description

Bedded Sedimentary Rock

Hydraulic

Conductivity

Unsaturated Zone

Thickness

Saturated Zone

Thickness

Regional Hydraulic

Gradient

(m/yr) (m) (m) (m/m)

D-68

1.10E+04 1.83E+01 9.14E+01 -999

1.26E+02 1.34E+01 7.62E+00 4.00E-03

1.33E+03 6.10E+00 2.13E+01 5.00E-03

3.15E+04 1.83E+00 3.05E+00 -999

-999 4.27E+00 8.90E+01 -999

1.89E+03 5.36E+01 6.10E+00 4.30E-02

9.78E+03 1.83E+01 3.05E+01 1.20E-02

6.31E+00 1.22E+01 2.44E+01 1.50E-02

3.15E+00 1.22E+01 1.22E+01 2.50E-02

1.26E+01 3.70E+00 3.00E+01 1.00E-02

2.21E+07 9.14E+00 1.52E+00 1.00E+00

3.47E+04 1.22E+01 4.57E+00 8.00E-03

3.15E+04 1.52E+01 6.10E+00 5.00E-02

3.15E+00 3.66E+00 9.14E+00 4.00E-02

3.15E+02 9.14E+00 2.13E+01 5.00E-03

3.15E+02 8.53E+00 1.90E+01 2.50E-02

-999 4.88E+00 -999 -999

-999 3.05E+00 -999 2.40E-02

6.31E+01 4.57E+00 1.98E+01 4.00E-02

1.89E+02 6.10E+00 6.10E+01 2.30E-02

2.21E+07 4.57E+00 1.83E+00 1.00E+00

-999 1.83E+02 1.22E+01 4.00E-04

2.21E+01 2.74E+00 3.05E+00 -999

1.89E+02 1.52E+01 6.10E+01 1.20E-02

1.10E+04 1.52E+01 2.29E+01 5.00E-04

-999 3.66E+00 1.83E+01 -999

6.31E+01 8.23E+00 5.18E+02 7.00E-03

1.26E+02 4.57E+00 1.07E+02 3.00E-02

-999 1.52E+00 9.14E+01 -999

Note: -999 indicates a missing sample value.
Appendix D WMU and Hydrogeologic Environment Databases

D-69

Table D.8 Hydrogeologic Statistics for HG Environment 2

Subsurface Environment Statistics

Bedded Sedimentary Rock

Mean Values

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

-7.68877 3.4698 4.2618 -4.42479

Covariance Matrix

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

Hydraulic

Conductivity

ln(cm/s) 12.3279

Unsaturated Zone

Thickness ln(ft) 1.32509 0.54208

Saturated Zone

Thickness ln(ft) 0.47331 -0.01357 1.61831

Regional Hydraulic

Gradient ln(ft/ft) -1.46902 -0.1757 -0.39626 1.75145

Table D.9 Hydrogeologic Database for HG Environment 3

Subsurface Environment Description

Bedded Sedimentary Rock

Hydraulic

Conductivity

(m/yr)

Unsaturated Zone

Thickness

(m)

Saturated Zone

Thickness

(m)

Regional Hydraulic

Gradient

(m/m)

2.55E+04 3.66E+00 3.66E+00 9.00E-04

9.46E+02 9.14E+00 5.33E+00 5.00E-03

1.26E+03 1.77E+00 6.10E+00 4.00E-09

2.84E+01 6.10E+00 -999 3.40E-02

3.78E+03 1.68E+01 1.52E+00 4.00E-02

2.68E+03 6.71E+00 2.44E+00 9.00E-03

3.15E+01 9.45E+00 -999 5.00E-02

-999 7.62E+00 -999 1.00E-02

6.31E+01 2.30E+00 4.12E+00 7.00E-03

6.62E+03 3.05E+01 2.13E+01 2.00E-02

1.26E+02 3.06E+00 1.52E+01 1.00E-02

3.15E+01 -999 -999 1.00E-02

8.83E+03 5.33E+00 4.57E+01 5.00E-04

1.58E+02 9.14E-01 4.57E+00 3.00E-03

6.31E+00 1.37E+00 3.66E+00 2.70E-02

9.46E+00 2.56E+00 2.74E+00 4.20E-02

Note: -999 indicates a missing sample value.
Appendix D WMU and Hydrogeologic Environment Databases

D-70

Table D.10 Hydrogeologic Statistics for HG Environment 3

Subsurface Environment Statistics

Bedded Sedimentary Rock

Mean Values

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

-7.81342 2.72776 2.93298 -4.6888

Covariance Matrix

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

Hydraulic

Conductivity

ln(cm/s) 21.2765

Unsaturated Zone

Thickness ln(ft) 2.78074 1.07038

Saturated Zone

Thickness ln(ft) 0.6463 0.17468 0.96341

Regional Hydraulic

Gradient ln(ft/ft) -1.30916 0.29718 -0.64536 1.9708

Table D.11 Hydrogeologic Database for HG Environment 4

Subsurface Environment Description

Sand and Gravel

Hydraulic

Conductivity

(m/yr)

Unsaturated Zone

Thickness

(m)

Saturated Zone

Thickness

(m)

Regional Hydraulic

Gradient

(m/m)

5.08E+04 4.57E+00 9.14E+00 5.00E-03

1.39E+04 -999 3.35E+01 2.80E-02

-999 6.10E+00 -999 -999

-999 1.22E+01 4.57E+00 1.00E-02

1.58E+03 2.13E+00 1.22E+01 1.00E-03

3.15E+00 1.98E+01 2.44E+00 7.00E-03

1.26E+01 4.57E+00 1.07E+01 7.00E-02

-999 9.14E-01 6.10E+00 4.30E-02

2.52E+03 1.52E+00 3.05E+00 2.00E-02

3.15E+03 2.44E+00 -999 2.00E-06

9.46E+00 1.83E+00 6.04E+00 5.50E-02

9.46E+01 6.10E-01 3.96E+00 6.00E-03

-999 6.98E+00 5.33E+01 -999

1.16E+05 1.52E+01 7.62E+01 4.00E-03

1.26E+04 7.62E+00 6.40E+00 4.90E-02
Appendix D WMU and Hydrogeologic Environment Databases

Table D.11 Hydrogeologic Database for HG Environment 4

Subsurface Environment Description

Sand and Gravel

Hydraulic

Conductivity

(m/yr)

Unsaturated Zone

Thickness

(m)

Saturated Zone

Thickness

(m)

Regional Hydraulic

Gradient

(m/m)

D-71

4.10E+03 2.13E+00 3.20E+01 3.00E-03

-999 1.07E+01 8.53E+00 6.00E-04

-999 6.10E-01 7.62E+00 1.00E-03

3.15E+03 3.05E-01 9.14E+00 3.00E-03

2.21E+02 1.52E+00 7.62E+00 4.00E-03

-999 4.57E+00 2.74E+01 1.50E-02

3.15E+00 3.05E+00 3.05E+00 2.00E-02

6.31E+02 2.44E+00 7.62E+00 5.00E-03

-999 5.08E+01 1.45E+02 9.20E-02

-999 1.52E+01 6.10E+00 1.00E-07

3.15E+01 3.35E+01 -999 2.30E-02

3.15E+02 9.14E+00 3.05E+00 2.00E-03

4.42E+03 1.52E+00 1.98E+01 2.00E-03

6.31E+02 2.21E+00 3.32E-01 1.00E-03

-999 1.22E+00 -999 -999

-999 9.14E+00 3.05E+00 5.00E-03

7.88E+03 2.29E+01 3.05E+00 2.00E-02

5.36E+03 3.05E+00 6.10E+00 1.00E-03

Note: -999 indicates a missing sample value.
Appendix D WMU and Hydrogeologic Environment Databases

D-72

Table D.12 Hydrogeologic Statistics for HG Environment 4

Subsurface Environment Statistics

Sand and Gravel

Mean Values

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

-6.82634 2.65875 3.3063 -4.9212

Covariance Matrix

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

Hydraulic

Conductivity

ln(cm/s) 9.60704

Unsaturated Zone

Thickness ln(ft) 0.51036 1.5223

Saturated Zone

Thickness ln(ft) 1.46619 -0.01024 1.28413

Regional Hydraulic

Gradient ln(ft/ft) -1.4956 0.0939 -0.02391 1.83998

Table D.13 Hydrogeologic Database for HG Environment 5

Subsurface Environment Description

Alluvial Basins Valleys & Fans

Hydraulic

Conductivity

Unsaturated Zone

Thickness

Saturated Zone

Thickness

Regional Hydraulic

Gradient

(m/yr) (m) (m) (m/m)

5.68E+03 3.05E+00 2.13E+01 2.00E-03

-999 9.14E-01 3.96E+00 -999

9.46E+02 -999 1.52E+01 9.30E-02

-999 3.05E+00 6.10E+00 1.00E-02

1.58E+05 6.10E+00 3.05E+00 1.00E-04

6.31E+04 5.18E+00 1.52E+00 5.00E-03

-999 6.10E+00 3.05E+00 5.00E-03

1.56E+01 3.81E+01 1.52E+00 2.50E-02

1.26E+05 4.57E+00 4.57E+00 1.00E-03

-999 4.57E+00 2.29E+01 3.00E-02

7.57E+03 3.05E+01 -999 -999

-999 1.01E+02 1.52E+01 5.00E-02

1.58E+03 3.35E+01 9.14E+02 1.00E-03

3.15E+04 3.05E+01 2.44E+01 1.00E-03

-999 9.75E+00 1.52E+01 -999

6.31E+00 3.38E+00 7.62E+00 3.00E-03

-999 3.29E+01 4.57E+00 -999
Appendix D WMU and Hydrogeologic Environment Databases

Table D.13 Hydrogeologic Database for HG Environment 5

Subsurface Environment Description

Alluvial Basins Valleys & Fans

Hydraulic

Conductivity

Unsaturated Zone

Thickness

Saturated Zone

Thickness

Regional Hydraulic

Gradient

(m/yr) (m) (m) (m/m)

D-73

2.37E+04 4.27E+01 6.10E+00 3.00E-03

-999 1.07E+01 1.07E+00 -999

1.58E+03 1.98E+01 2.44E+01 5.00E-03

1.26E+03 2.44E+00 -999 -999

3.15E+03 1.22E+01 3.81E+00 -999

1.26E+02 1.52E+01 4.57E+00 2.00E-03

9.46E+02 3.05E+00 3.05E+00 2.00E-03

-999 4.57E+00 -999 -999

-999 2.44E+00 -999 -999

1.39E+03 3.41E+01 9.14E+01 3.00E-03

-999 1.22E+01 8.53E+01 -999

-999 3.66E+00 -999 -999

-999 2.74E+01 -999 6.00E-03

-999 1.59E+01 1.62E+01 4.00E-04

9.46E+01 7.01E+00 9.14E+00 3.00E-04

2.84E+03 4.27E+01 3.05E+01 2.00E-03

1.58E+02 1.30E+01 1.30E+02 1.00E-03

-999 1.83E+01 3.66E+00 1.00E-02

1.26E+03 7.32E+00 1.83E+01 1.00E-04

6.31E+01 8.23E+01 -999 -999

1.58E+04 3.66E+01 -999 1.00E-03

3.47E+03 7.62E+00 1.52E+01 2.00E-02

-999 1.22E+01 1.52E+01 1.00E-03

1.26E+02 1.83E+00 1.10E+01 2.00E-03

2.21E+03 1.52E+01 9.14E+00 -999

3.15E+00 3.66E+00 2.44E+00 5.00E-03

-999 1.22E+01 4.88E+01 1.00E-02

-999 3.66E+01 -999 6.80E-02

6.37E+04 6.10E+01 -999 -999

3.15E+00 6.10E+01 1.52E+01 1.50E-02

-999 7.01E+00 1.83E+01 -999

6.31E+02 1.46E+01 2.44E+01 3.00E-03

3.19E+06 9.14E+00 3.05E-01 2.00E-06

3.15E+03 1.07E+01 3.05E+00 6.00E-03

3.15E+00 4.72E+00 1.83E+01 7.00E-02

9.46E+02 1.37E+01 6.10E+00 8.00E-03

3.15E+03 7.62E+00 7.62E+00 -999

3.15E+02 4.88E+00 9.14E+00 1.70E-02

1.10E+04 2.44E+00 6.10E+00 -999

-999 2.44E+00 5.18E+00 4.00E-02

-999 3.96E+00 1.83E+01 -999

1.26E+01 2.13E+00 6.10E-01 -999
Appendix D WMU and Hydrogeologic Environment Databases

Table D.13 Hydrogeologic Database for HG Environment 5

Subsurface Environment Description

Alluvial Basins Valleys & Fans

Hydraulic

Conductivity

Unsaturated Zone

Thickness

Saturated Zone

Thickness

Regional Hydraulic

Gradient

(m/yr) (m) (m) (m/m)

D-74

2.21E+03 9.14E+00 1.52E+00 2.50E-02

-999 3.05E+00 6.10E+00 1.30E-02

2.21E+04 6.10E+00 9.14E+01 1.00E-03

Note: -999 indicates a missing sample value.

Table D.14 Hydrogeologic Statistics for HG Environment 5

Subsurface Environment Statistics

Alluvial Basins Valleys & Fans

Mean Values

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

-5.61434 3.43835 3.53678 -5.61773

Covariance Matrix

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

Hydraulic

Conductivity

ln(cm/s) 9.98295

Unsaturated Zone

Thickness ln(ft) 0.28014 0.8396

Saturated Zone

Thickness ln(ft) 0.08839 0.54136 2.05569

Regional Hydraulic

Gradient ln(ft/ft) 2.96927 0.0448 -0.71488 4.17328
Appendix D WMU and Hydrogeologic Environment Databases

D-75

Table D.15 Hydrogeologic Database for HG Environment 6

Subsurface Environment Description

River Valleys and Flood Plains with overbank deposits

Hydraulic

Conductivity

Unsaturated Zone

Thickness

Saturated Zone

Thickness

Regional Hydraulic

Gradient

(m/yr) (m) (m) (m/m)

-999 1.52E+01 1.83E+01 5.00E-03

-999 1.83E+00 9.14E+00 2.00E-03

3.15E+02 4.88E+00 1.52E+01 1.00E-03

6.31E+02 8.53E+00 9.14E+00 1.00E-02

1.07E+05 3.51E+00 7.32E+00 5.00E-03

1.89E+03 2.44E+01 3.66E+01 1.00E-03

3.15E+00 2.74E+00 3.66E+00 3.00E-03

-999 2.13E+01 7.62E+00 1.00E-03

4.10E+03 2.74E+01 3.05E+00 1.00E-03

1.67E+04 2.44E+00 6.40E+00 4.00E-03

1.10E+04 5.49E+00 1.31E+01 2.00E-03

3.15E+02 1.52E+00 3.05E+00 2.00E-03

-999 1.22E+00 1.83E+00 8.00E-03

1.10E+04 5.79E+00 -999 5.00E-04

-999 3.96E+00 4.27E+00 1.70E-02

-999 1.22E+01 1.68E+01 2.00E-03

1.58E+03 4.57E+00 7.62E+00 4.00E-02

3.31E+04 3.05E+01 2.29E+01 1.00E-02

-999 4.57E+00 7.62E+00 1.00E-01

2.52E+02 1.15E+01 -999 5.00E-03

1.42E+04 4.57E+00 1.83E+01 7.00E-04

3.15E+03 1.52E+00 1.52E+00 4.00E-07

5.68E+03 3.05E+00 6.10E+00 1.00E-03

1.89E+03 3.66E+00 6.10E+00 2.00E-03

3.15E+02 3.66E+00 6.10E-01 1.00E-06

3.15E+01 1.52E+00 -999 2.00E-08

3.15E+03 1.19E+00 3.66E+00 -999

1.55E+04 5.18E+00 7.93E+00 6.00E-03

5.52E+03 3.66E+00 5.49E+00 1.00E-02

3.15E+03 3.05E+00 1.68E+01 1.30E-02

1.58E+02 1.52E+00 3.05E+00 1.20E-02

2.21E+01 1.22E+00 1.37E+01 4.00E-03

-999 1.83E+00 9.14E+00 1.10E-02

9.46E+00 9.14E-01 6.10E+00 8.00E-03

-999 1.07E+01 1.52E+01 8.00E-05

-999 1.22E+01 1.22E+01 1.00E-06

Note: -999 indicates a missing sample value.
Appendix D WMU and Hydrogeologic Environment Databases

D-76

Table D.16 Hydrogeologic Statistics for HG Environment 6

Subsurface Environment Statistics

River Valleys and Flood Plains with overbank deposits

Mean Values

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

-6.7624 2.65846 3.15814 -5.6184

Covariance Matrix

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

Hydraulic

Conductivity

ln(cm/s) 13.8058

Unsaturated Zone

Thickness ln(ft) 1.67704 0.8987

Saturated Zone

Thickness ln(ft) 2.14642 0.34951 0.86919

Regional Hydraulic

Gradient ln(ft/ft) -0.09303 -0.23716 0.00252 1.23921

Table D.17 Hydrogeologic Database for HG Environment 7

Subsurface Environment Description

River Valleys and Flood Plains without overbank deposits

Hydraulic

Conductivity

Unsaturated Zone

Thickness

Saturated Zone

Thickness

Regional Hydraulic

Gradient

(m/yr) (m) (m) (m/m)

9.46E+02 2.44E+00 8.23E+00 2.00E-03

1.26E+03 2.13E+00 3.05E+02 3.00E-03

-999 3.54E+01 -999 -999

6.94E+03 -999 2.29E+01 3.00E-03

2.33E+04 1.52E+01 3.66E+01 4.00E-03

4.42E+03 1.83E+00 3.81E+01 7.00E-04

5.61E+04 3.05E+00 1.01E+01 2.00E-03

5.52E+04 3.05E+00 6.10E+01 -999

9.46E+03 5.79E+01 9.14E+00 1.00E-06

-999 9.14E+00 9.14E+00 2.00E-04

-999 1.22E+01 9.14E+00 2.00E-03

9.46E+02 3.05E+00 3.05E+00 8.00E-03

9.78E+03 3.05E+00 3.05E+00 1.30E-02

-999 5.18E+00 1.22E+01 2.00E-03

4.42E+03 3.66E+00 1.52E+01 5.00E-03

4.42E+03 2.44E+01 2.13E+01 1.00E-02
Appendix D WMU and Hydrogeologic Environment Databases

Table D.17 Hydrogeologic Database for HG Environment 7

Subsurface Environment Description

River Valleys and Flood Plains without overbank deposits

Hydraulic

Conductivity

Unsaturated Zone

Thickness

Saturated Zone

Thickness

Regional Hydraulic

Gradient

(m/yr) (m) (m) (m/m)

D-77

1.58E+03 1.52E+00 2.44E+01 1.00E-02

8.20E+04 1.49E+01 8.53E+00 3.00E-03

9.46E+02 1.22E+01 1.83E+01 2.00E-06

1.10E+04 3.05E+00 4.57E+00 -999

-999 4.57E+00 1.37E+01 1.00E-02

6.94E+03 2.13E+00 7.99E+00 4.00E-03

6.31E+03 7.01E+00 5.18E+00 4.90E-02

2.37E+04 4.88E+00 1.83E+01 3.30E-02

1.77E+04 5.79E+00 4.27E+01 2.00E-03

1.89E+03 4.57E+00 1.07E+01 4.00E-06

1.45E+04 1.52E+00 1.83E+01 1.20E-02

1.20E+05 2.20E+01 -999 1.00E-02

2.52E+03 1.52E+00 6.10E+00 1.10E-02

1.26E+01 5.79E+00 4.27E+00 2.10E-02

3.15E+02 6.10E-01 4.57E+00 6.00E-03

3.15E+01 4.57E-01 -999 1.00E-03

-999 4.57E+01 3.05E+00 -999

Note: -999 indicates a missing sample value.
Appendix D WMU and Hydrogeologic Environment Databases

D-78

Table D.18 Hydrogeologic Statistics for HG Environment 7

Subsurface Environment Statistics

River Valleys and Flood Plains without overbank deposits

Mean Values

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

-5.22204 2.81441 3.78819 -5.30668

Covariance Matrix

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

Hydraulic

Conductivity

ln(cm/s) 13.0649

Unsaturated Zone

Thickness ln(ft) -1.10808 1.13841

Saturated Zone

Thickness ln(ft) 0.50353 0.0496 1.11517

Regional Hydraulic

Gradient ln(ft/ft) -0.73884 0.26902 -0.46202 1.11713

Table D.19 Hydrogeologic Database for HG Environment 8

Subsurface Environment Description

Outwash

Hydraulic

Conductivity

Unsaturated Zone

Thickness

Saturated Zone

Thickness

Regional Hydraulic

Gradient

(m/yr) (m) (m) (m/m)

6.31E+03 7.62E+00 6.10E+01 1.00E-03

2.40E+04 4.88E+00 2.29E+01 2.00E-03

3.00E+04 2.99E+00 1.89E+01 4.00E-03

-999 1.22E+01 6.71E+00 1.00E-03

2.52E+03 3.05E+00 2.13E+01 8.00E-07

1.10E+05 9.14E+00 2.13E+01 4.00E-03

1.33E+04 5.49E+00 1.22E+01 6.00E-03

3.78E+04 4.57E+00 9.14E+00 3.00E-03

1.26E+03 1.07E+01 -999 8.00E-03

2.21E+03 3.05E+00 2.29E+01 9.00E-04

9.78E+03 3.35E+00 1.52E+01 7.00E-04

1.89E+03 4.88E+01 3.20E+01 3.00E-02

3.44E+04 7.62E+00 2.62E+01 6.00E-03

4.42E+04 4.88E+00 1.86E+01 2.00E-03

1.58E+04 2.90E+01 2.44E+01 1.00E-03

7.25E+03 9.14E+00 3.96E+01 6.00E-04
Appendix D WMU and Hydrogeologic Environment Databases

Table D.19 Hydrogeologic Database for HG Environment 8

Subsurface Environment Description

Outwash

Hydraulic

Conductivity

Unsaturated Zone

Thickness

Saturated Zone

Thickness

Regional Hydraulic

Gradient

(m/yr) (m) (m) (m/m)

D-79

1.39E+04 1.22E+01 1.22E+02 2.00E-03

2.90E+04 2.74E+00 1.01E+01 -999

9.97E+04 2.13E+00 7.01E+00 7.00E-04

-999 4.57E+00 6.10E+00 3.00E-03

1.48E+04 1.83E+00 6.10E+01 1.00E-03

7.88E+03 2.44E+00 3.05E+00 3.00E-02

-999 1.52E+01 7.62E+01 9.00E-04

5.68E+03 2.44E+00 6.10E+00 1.00E-03

1.89E+04 4.57E+00 7.62E+00 5.00E-03

3.88E+03 3.66E+00 7.62E+00 4.00E-03

-999 2.20E+01 1.83E+01 6.00E-04

4.73E+02 6.10E+00 4.57E+00 1.70E-02

1.04E+04 7.62E+00 3.05E+01 1.00E-03

2.21E+04 9.14E+00 7.62E+00 5.00E-03

2.78E+04 7.62E+00 2.44E+01 2.00E-03

2.78E+04 7.62E+00 2.44E+01 2.00E-03

-999 6.10E+00 4.57E+00 4.00E-05

1.10E+04 1.22E+01 3.05E+00 7.50E-02

1.92E+04 5.33E+00 1.22E+01 8.00E-03

6.31E+02 9.14E-01 1.07E+01 1.00E-02

1.92E+04 1.83E+01 1.07E+01 1.30E-02

5.05E+03 6.10E-01 1.22E+01 3.00E-03

-999 7.62E+00 3.05E+01 2.00E-03

3.31E+04 1.52E+01 3.05E+01 4.00E-04

-999 4.57E+00 2.29E+01 1.00E-02

2.21E+03 2.13E+00 3.66E+00 2.00E-02

6.09E+04 2.00E+01 3.05E+01 3.00E-03

Note: -999 indicates a missing sample value.
Appendix D WMU and Hydrogeologic Environment Databases

D-80

Table D.20 Hydrogeologic Statistics for HG Environment 8

Subsurface Environment Statistics

Outwash

Mean Values

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

-3.59646 2.97372 3.92385 -5.86511

Covariance Matrix

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

Hydraulic

Conductivity

ln(cm/s) 5.02

Unsaturated Zone

Thickness ln(ft) 0.4862 0.85551

Saturated Zone

Thickness ln(ft) 0.1547 0.26963 0.75329

Regional Hydraulic

Gradient ln(ft/ft) -0.8019 0.07004 -0.62236 1.62199

Table D.21 Hydrogeological Database for HG Environment 9

Subsurface Environment Description

Till and Till over outwash

Hydraulic

Conductivity

Unsaturated Zone

Thickness

Saturated Zone

Thickness

Regional Hydraulic

Gradient

(m/yr) (m) (m) (m/m)

9.46E+02 2.10E+00 1.37E+01 5.00E-02

3.15E+02 1.37E+01 1.22E+01 1.00E-03

1.89E+01 3.66E+00 5.49E+00 8.00E-03

2.18E+04 6.10E+00 1.52E+01 4.00E-03

3.47E+03 3.96E+01 5.49E+01 1.70E-02

3.15E+03 2.13E+01 4.57E+00 1.00E-02

1.26E+02 1.00E+00 3.00E+01 -999

3.15E+01 7.62E+00 3.05E+00 9.00E-03

-999 3.05E+00 3.05E+01 5.00E-07

3.15E+01 5.18E+00 1.07E+01 3.00E-02

3.15E+02 3.96E+00 2.29E+01 7.00E-03

6.31E+01 4.57E+00 2.96E+00 2.20E-02

9.15E+02 2.44E+00 1.22E+01 7.00E-04

-999 7.32E+00 1.22E+01 -999

1.89E+03 1.83E+00 9.14E-01 5.00E-03

3.15E+03 7.62E+00 7.62E+00 -999

6.31E+02 3.66E+00 2.13E+00 -999
Appendix D WMU and Hydrogeologic Environment Databases

Table D.21 Hydrogeological Database for HG Environment 9

Subsurface Environment Description

Till and Till over outwash

Hydraulic

Conductivity

Unsaturated Zone

Thickness

Saturated Zone

Thickness

Regional Hydraulic

Gradient

(m/yr) (m) (m) (m/m)

D-81

6.31E+03 2.44E+00 9.14E+00 4.00E-08

-999 2.13E+00 7.62E+00 9.00E-03

4.10E+03 1.52E+00 6.10E+00 1.00E-02

1.26E+02 3.05E+00 4.57E+00 5.00E-02

1.26E+02 3.05E+00 7.62E+00 2.00E-02

-999 6.10E-01 1.83E+00 -999

1.26E+01 1.83E+00 -999 4.00E-02

8.83E+03 1.52E+00 1.83E+01 4.00E-03

3.15E+02 1.52E+00 6.10E+00 -999

2.84E+02 1.74E+00 9.14E+00 1.00E-02

9.46E+00 1.83E+01 2.44E+00 3.00E-03

1.58E+03 3.35E+00 6.10E+00 4.00E-06

Note: -999 indicates a missing sample value.

Table D.22 Hydrogeologic Statistics for HG Environment 9

Subsurface Environment Statistics

Till and Till over outwash

Mean Values

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

-7.67984 2.48552 3.22796 -4.68545

Covariance Matrix

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

Hydraulic

Conductivity

ln(cm/s) 11.259

Unsaturated Zone

Thickness ln(ft) 0.17085 0.87319

Saturated Zone

Thickness ln(ft) 0.72472 0.13478 0.81983

Regional Hydraulic

Gradient ln(ft/ft) -0.72109 -0.12094 -0.0043 1.28625
Appendix D WMU and Hydrogeologic Environment Databases

D-82

Table D.23 Hydrogeologic Database for HG Environment 10

Subsurface Environment Description

Unconsolidated and Semiconsolidated Shallow Aquifers

Hydraulic

Conductivity

Unsaturated Zone

Thickness

Saturated Zone

Thickness

Regional Hydraulic

Gradient

(m/yr) (m) (m) (m/m)

-999 3.35E+00 1.46E+01 3.00E-02

4.42E+03 1.16E+01 5.49E+01 5.00E-03

2.84E+02 4.57E+00 7.62E+00 1.00E-02

1.96E+04 3.96E+01 2.14E+01 3.00E-04

1.58E+02 4.57E+00 3.05E+00 6.00E-04

3.15E+02 1.52E+00 6.10E+00 4.00E-03

-999 6.10E+00 3.66E+00 1.00E-06

1.26E+02 7.62E+00 2.29E+00 5.00E-03

3.15E+02 1.52E+01 1.07E+01 1.00E-02

3.15E+01 2.74E+00 6.86E+00 1.70E-02

1.26E+02 3.05E+00 4.12E+00 3.00E-03

-999 3.81E+00 6.10E+00 1.00E-05

-999 3.66E+00 1.52E+01 1.00E-01

6.31E+02 4.57E+00 9.14E-01 5.00E-03

3.47E+03 3.05E+00 3.05E+00 2.00E-03

2.21E+03 2.59E+01 7.62E+00 1.00E-05

-999 1.52E+00 1.52E+01 2.00E-03

2.84E+03 2.74E+00 4.57E+00 -999

-999 1.83E+00 2.44E+00 8.00E-03

2.21E+03 1.37E+01 7.62E+00 1.00E-02

1.26E+02 1.22E+01 1.22E+01 2.50E-02

-999 3.81E+00 1.68E+01 2.00E-03

-999 3.32E+00 1.83E+00 6.00E-02

3.15E+00 3.66E+00 1.16E+01 1.00E-02

2.52E+01 1.83E+00 4.57E+00 9.50E-03

4.42E+03 1.07E+01 9.14E+00 1.40E-02

-999 6.10E+00 4.27E+01 1.75E-03

Note: -999 indicates a missing sample value.
Appendix D WMU and Hydrogeologic Environment Databases

D-83

Table D.24 Hydrogeologic Statistics for HG Environment 10

Subsurface Environment Statistics

Unconsolidated and Semiconsolidated Shallow Aquifers

Mean Values

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

-6.97635 2.80942 3.15655 -5.57335

Covariance Matrix

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

Hydraulic

Conductivity

ln(cm/s) 4.99889

Unsaturated Zone

Thickness ln(ft) 1.27993 0.86035

Saturated Zone

Thickness ln(ft) 0.51266 0.40799 0.8467

Regional Hydraulic

Gradient ln(ft/ft) -1.74813 -0.71454 0.03369 3.61694

Table D.25 Hydrogeologic Database for HG Environment 11

Subsurface Environment Description

Coastal Beaches

Hydraulic

Conductivity

Unsaturated Zone

Thickness

Saturated Zone

Thickness

Regional Hydraulic

Gradient

(m/yr) (m) (m) (m/m)

9.46E+02 2.13E+00 3.05E+02 1.00E-02

6.31E+01 2.74E+00 3.05E+01 3.00E-02

7.25E+03 9.14E+00 3.66E+01 6.00E-04

2.43E+04 4.57E+00 1.07E+01 6.80E-03

-999 1.52E+00 3.05E+02 1.00E-03

7.57E+03 3.05E+00 4.57E+01 6.00E-03

1.26E+04 9.14E-01 4.57E+00 5.00E-03

6.31E+02 9.14E-01 6.10E+00 1.00E-02

3.15E+03 1.52E+00 6.10E+00 -999

1.26E+03 1.22E+00 1.07E+01 2.00E-03

3.15E+01 9.14E-01 1.52E+01 5.00E-03

1.39E+04 1.52E+00 6.10E+01 2.00E-03

-999 1.68E+00 1.52E+01 2.00E-03

2.52E+03 2.00E+00 2.00E+00 2.00E-03

1.26E+03 1.22E+00 3.05E+00 1.70E-02

-999 9.14E-01 7.62E+00 -999
Appendix D WMU and Hydrogeologic Environment Databases

Table D.25 Hydrogeologic Database for HG Environment 11

Subsurface Environment Description

Coastal Beaches

Hydraulic

Conductivity

Unsaturated Zone

Thickness

Saturated Zone

Thickness

Regional Hydraulic

Gradient

(m/yr) (m) (m) (m/m)

D-84

3.15E+02 1.52E+00 1.52E+00 5.00E-02

1.58E+03 2.74E+00 4.57E+00 2.30E-02

-999 3.35E+00 4.27E+00 1.90E-02

3.15E+02 3.05E+00 2.44E+01 1.00E-03

2.84E+02 1.07E+00 3.05E+01 3.00E-03

9.46E+02 2.13E+00 1.68E+00 2.00E-04

-999 2.74E+00 2.13E+01 3.00E-05

8.17E+03 7.01E+00 6.10E+00 3.30E-03

-999 -999 6.71E+00 -999

-999 3.05E+00 4.27E+01 5.00E-04

Note: -999 indicates a missing sample value.

Table D.26 Hydrogeologic Statistics for HG Environment 11

Subsurface Environment Statistics

Coastal Beaches

Mean Values

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

-5.38023 1.8991 3.7492 -5.61773

Covariance Matrix

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

Hydraulic

Conductivity

ln(cm/s) 3.48349

Unsaturated Zone

Thickness ln(ft) 0.52513 0.46903

Saturated Zone

Thickness ln(ft) -0.00429 0.18069 2.02612

Regional Hydraulic

Gradient ln(ft/ft) -0.63963 -0.2284 -0.08327 1.97797
Appendix D WMU and Hydrogeologic Environment Databases

D-85

Table D.27 Hydrogeologic Database for HG Environment 12

Subsurface Environment Description

Solution Limestone

Hydraulic

Conductivity

Unsaturated Zone

Thickness

Saturated Zone

Thickness

Regional Hydraulic

Gradient

(m/yr) (m) (m) (m/m)

1.58E+05 3.00E+01 3.00E+01 6.00E-03

-999 5.00E+01 1.00E+01 5.00E-03

1.58E+03 5.08E+01 1.44E+02 2.30E-02

-999 1.52E+01 9.14E+01 -999

-999 3.05E+00 -999 1.20E-02

1.58E+03 4.57E+01 -999 -999

1.26E+02 3.05E+00 1.52E+01 5.00E-05

3.15E+02 1.22E+01 6.10E+01 3.30E-02

-999 3.05E+01 -999 2.00E-02

-999 3.20E+02 -999 9.00E-03

-999 5.33E+00 1.52E+01 1.00E-03

1.58E+04 2.93E+01 1.95E+01 -999

-999 1.83E+01 -999 -999

2.21E+02 -999 3.96E+01 2.00E-03

3.15E+02 3.96E+00 3.05E+00 1.80E-02

2.49E+04 1.52E+00 -999 2.00E-03

1.23E+04 3.96E+00 1.83E+01 9.00E-03

-999 3.05E+00 3.05E+02 1.00E-03

9.46E+01 7.62E+00 1.98E+01 1.00E-02

1.26E+03 4.00E+02 1.80E+01 2.00E-06

2.18E+03 1.68E+00 7.32E+00 4.20E-04

6.31E+03 1.22E+00 3.05E+00 -999

Note: -999 indicates a missing sample value.
Appendix D WMU and Hydrogeologic Environment Databases

D-86

Table D.28 Hydrogeologic Statistics for HG Environment 12

Subsurface Environment Statistics

Solution Limestone

Mean Values

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

-5.6496 3.47765 4.32063 -5.49537

Covariance Matrix

Hydraulic

Conductivity

Unsaturated

Zone Thickness

Saturated Zone

Thickness

Regional

Hydraulic

Gradient

ln(cm/s) ln(ft) ln(ft) (m/m)

Hydraulic

Conductivity

ln(cm/s) 12.0503

Unsaturated Zone

Thickness ln(ft) 1.43257 1.25667

Saturated Zone

Thickness ln(ft) 0.53279 0.99541 1.2437

Regional Hydraulic

Gradient ln(ft/ft) 0.79733 1.35511 0.81132 4.45451

Table D.29 Hydrogeologic Database for HG Environment 13

Subsurface Environment Description

Undefined Hydrogeological Region

(Parameters values represent the average of the 12 regions).

Hydraulic

Conductivity

Unsaturated Zone

Thickness

Saturated Zone

Thickness

Regional Hydraulic

Gradient

(m/yr) (m) (m) (m/m)

1890 5.18 10.1 5.70E-03