EPA’s COMPOSITE MODEL FOR LEACHATE

MIGRATION WITH TRANSFORMATION PRODUCTS

EPACMTP: USER’S GUIDE

Work Assignment Manager Dr. Zubair A. Saleem

and Technical Directions: U.S. Environmental Protection Agency

Office of Solid Waste

Washington, DC 20460

Prepared by: HydroGeoLogic, Inc.

1155 Herndon Parkway, Suite 900

Herndon, VA 20170

Under Contract No. 68-W4-0017

U.S. Environmental Protection Agency

Office of Solid Waste

Washington, DC 20460

1997
 1

 U.S. Environmental Protection Agency, Industrial Subtitle D Facility Study (Telephone Survey), October 20,

1986; U.S. Environmental Protection Agency, Solid Waste Disposal in the United States: Report to Congress, Office

of Solid Waste and Emergency Response, EPA/530-SW-88-011, October, 1988

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PREFACE

This document presents guidance for the use of EPA’s Composite Model for leachate migration

with Transformation Products (EPACMTP) computer code. EPACMTP is a simulation model for

subsurface fate and transport of contaminants released from land disposal sites. EPACMTP is designed

to predict the groundwater exposure in a domestic drinking water receptor well associated with such

releases. The model is applied to support development of regulations for management and disposal of

hazardous wastes. Simulations are performed using probabilistic input specifications based on nationwide

data. The model is designed to be used for generic, nationwide assessments using Monte Carlo simulation

techniques; it is not intended for site-specific applications. EPACMTP extends and enhances the modeling

approach adopted for the 1990 Toxicity Characteristic (TC) Rule promulgated by the U.S. Environmental

Protection Agency in March 1990. For this rule, the Agency used EPACML (EPA’s Composite Model

for Landfills) to estimate the potential human exposure to hazardous chemicals leaching from land disposal

facilities. EPACML accounts for first-order decay and linear equilibrium sorption of chemicals, but

disregards the formation and transport of transformation products. The analytical groundwater transport

solution technique employed in EPACML further imposes certain restrictive assumptions; the solution can

handle only uniform, uni-directional groundwater flow and thereby ignores the effects of groundwater

mounding caused by leakage from the waste site on contaminant migration. To address the limitations of

EPACML, the modeling approach has been enhanced and implemented in EPACMTP. The EPACMTP

modeling approach incorporates greater flexibility and versatility in the simulation capability; the model

explicitly can take into consideration: (i) chain decay reactions and transport of daughter and

grand-daughter products, (ii) the change to groundwater velocity as a result of water-table mounding, (iii)

finite source as well as continuous source scenarios, and (iv) metals transport through linking with the

MINTEQ metals speciation model. 

In addition to enhancing the simulation capabilities of the EPACMTP computer code, the Agency

has also re-evaluated and updated the data used in the nationwide Monte Carlo modeling assessment. The

Agency has evaluated additional data from surveys of actual waste sites1

 and other pertinent studies. Based

on the additional data sources, the Monte Carlo methodology as well as the frequency distributions of

individual model input parameters have been revised and enhanced. The Monte Carlo methodology

implemented in the current version of EPACMTP uses a regional, site-based approach which directly

accounts for any dependencies between the geographical location of a waste site and the corresponding

regional climatic and hydrogeological characteristics.

In parallel with enhancing the model computer code and Monte Carlo methodology, the Agency

has conducted various verification and field validation studies. Individual components and modules of the

computer code have been verified against existing analytical and numerical solutions, as documented in

the EPACMTP Background Document. The modeling approach and solution techniques have been

reviewed by the Science Advisory Board; their implementation has been reviewed and tested by the EPA’s

Office of Research and Development and outside reviewers. The Agency has field-tested the model at a

number of actual field sites for which adequate source and site characterization data, as well as plume

monitoring data, were available. These sites include the Borden landfill research site in Ontario, Canada;

a pesticide contaminated site on Long Island, New York; a pesticide monitoring field site near Kansas City,
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Kansas; and an electric utility waste disposal site in New York State. In all these cases, EPACMTP was

found to yield reasonably good predictions of actual plume concentrations. The implementation and

documentation of the model have been revised also in response to critical evaluations of the modeling

approach by various public interest and industry groups. In response to these comments, the Agency has

conducted additional testing of the model, as well as reconsidered and revised various aspects of the

modeling procedures, e.g., options for placement of the receptor well down-gradient from the waste site

were revised to remove a bias towards larger waste sites.

The present version of the model represents a development effort which has spanned more than

six years. Although a considerable effort has been expended on developing and testing the model,

EPACMTP, like any computer model, provides a simplified representation of conditions and processes that

may be encountered at actual waste sites. Although there is much ongoing research in the area of

subsurface fate and transport processes, there is no clear consensus on how to represent all of these

processes in a computationally efficient way, particularly in the framework of a generic model such as

EPACMTP. Furthermore, the lack of detailed site characterization data on, for instance, heterogeneities

and fractures on a nationwide basis, inevitably imposes limitations. EPACMTP therefore represents a

balance and compromise between the evolving understanding of subsurface fate and transport processes

and the ability to reproduce these processes in a computationally efficient model. Therefore, the use of

the model for site-specific applications, where heterogeneities and other complexities might make it

unsuitable, is discouraged.
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ABSTRACT

The EPA’s Composite Model for leachate migration with Transformation Products (EPACMTP)

code, is used by EPA (the Office of Solid Waste) to simulate the fate and transport of contaminants

leaching from a land-based waste management unit through the underlying unsaturated and saturated zones.

EPACMTP replaces EPACML as the best available tool to predict potential exposure at a downstream

receptor well. EPACMTP offers improvements to EPACML by considering: 1) the formation and

transport of transformation products; 2) the impact of groundwater mounding on groundwater velocity;

3) finite source as well as continuous source scenarios; and 4) metals transport.

Fate and transport processes simulated by the model include: advection, hydrodynamic dispersion,

linear or nonlinear sorption, and chain-decay reactions. In cases where degradation of a waste constituent

yields daughter products that are of concern, EPACMTP accounts for the formation and transport of up

to six different daughter products. The composite model consists of a one-dimensional module that

simulates infiltration and dissolved constituent transport through the unsaturated zone, which is coupled

with a three-dimensional saturated zone module. The saturated zone module consists of a threedimensional groundwater flow and a three-dimensional transport sub-module. The saturated zone

groundwater flow sub-module accounts for the effects of leakage from the land disposal unit and regional

recharge on the magnitude and direction of groundwater flow. The saturated zone transport sub-module

accounts for three-dimensional advection and dispersion, chain decay reactions with up to seven different

chemical species (i.e., parent with up to six daughter products), and linear or nonlinear equilibrium

sorption.

The fate and transport of dissolved waste constituents in the subsurface depends on the chemical

properties of the contaminants as well as on hydrogeological and other parameters. The effect of

uncertainty or variability in these parameters on receptor well exposure estimates can be taken into account

using the Monte Carlo simulation technique. The Monte Carlo simulation module used in EPACMTP is

based on the Monte Carlo module in EPACML. The Monte Carlo Methodology has been enhanced by

incorporating a site-based approach which accommodates dependencies between parameters and accounts

for regional differences in climatic and hydrogeologic conditions, and which can accommodate finite as

well as continuous sources.

This document is intended as a user’s guide for EPACMTP; for details of the mathematical

techniques employed, the reader is referred to EPACMTP background document for the unsaturated and

saturated zone and Monte Carlo modules (U.S. EPA, 1996b). Details on the finite source modeling

procedure and background and methodology for the fate and transport assessment of metals are presented

in separate background documents (U.S. EPA, 1996c and U.S. EPA, 1996d, respectively).
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DISCLAIMER

The work presented in this document has been funded by the United States Environmental

Protection Agency. Mention of trade names or commercial products does not constitute endorsement or

recommendation for use by the Agency.

WARNING

EPACMTP was developed for regulatory purposes for implementation on a

nationwide basis using the Monte Carlo simulation procedure, and the code is not

suitable for site-specific use. The model does not account for site heterogeneities,

complicated source conditions, and several other site-specific conditions which may

be encountered at actual waste sites.
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ACKNOWLEDGMENT

A number of individuals have been involved with the development of the EPACMTP model. Dr.

Zubair Saleem of the U.S. EPA, Office of Solid Waste, provided overall technical coordination and review

throughout this work.

Drs. Peter Huyakorn and Jan Kool of HydroGeoLogic, Inc. developed the unsaturated zone module

used in the composite model. Dr. Edward Sudicky, Robert McLaren and Rene Therrien of the University

of Waterloo developed the saturated zone module. Neil Blandford of HydroGeoLogic, Inc. developed the

Monte Carlo module of EPACMTP, based on a similar module in EPA’s Composite Model for Landfills

(EPACML). Dr. Carlos Marin of Ambiotec Environmental Consultants provided overall technical support

for the site-based Monte Carlo conceptualization of the model and the finite source methodology. Raj

Lingam and Omar Abdi of HydroGeoLogic, have implemented and tested the current version of the

EPACMTP model. The fate and transport methodology for metals is under development in cooperation

with the EPA ORD Environmental Research Laboratory in Athens, GA. Drs. Nam-Sik Park and Yu-Shu

Wu modified and implemented the model for metals in cooperation with Jerry Allison of Allison

Geoscience and staff at the EPA Environmental Research Laboratory in Athens, GA. 
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EPACMTP

Quick Start Guide

This Quick Start section is intended to get new users up and running with EPACMTP quickly. It is not

a replacement for the complete User’s Guide. To fully understand the model capabilities and assumptions,

and how to use EPACMTP effectively, all users should consult this EPACMTP User’s Guide, the

Background Document (U.S. EPA, 1996a, b, c).

The EPACMTP modeling software consists of:

EPACMTP: The Monte Carlo fate and transport model

POSTCMTP: A menu-driven post-processor for analyzing EPACMTP model results.

The Quick Start guide tells you how to install the software and how to use the model and the pre- and postprocessors.

Computer Requirements

To install and run EPACMTP, you must have an MS-DOS 80386 or better PC with at least eight (8)

megabytes of RAM memory. A fast Pentium computer is highly recommended. About 1.5 megabytes of

free disk space is required to install the software. Finite source modeling runs may require up to 20

megabytes of additional disk space for temporary files.

In order for EPACMTP to operate correctly, your CONFIG.SYS file should contain the following

commands:

FILES = 20 (or more)

DEVICE = ANSI.SYS

Installation Procedure

The installation is controlled through a utility program, INSTALL.EXE on the distribution disk. To install

follow these steps:

• Insert the distribution diskette in the appropriate disk drive. This is the source

drive (usually a:)

• Make the source drive the current drive, by typing ‘a:’ at the DOS prompt

• Type ‘INSTALL a: c:’ where a: represents the source drive and c: represents the

target drive.

The installation program will automatically copy the contents of the a: drive into a

directory call “EPACMTP” on you c: drive.

• That’s it!
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After installation is complete, some information on EPACMTP will be displayed on-screen. This

information can be viewed again later by typing <MODL-INFO’.

RUNNING EPACMTP

To setup an EPACMTP run you must first create an ASCII data input file. Detailed instructions for this

are provided in Appendix A. To create a new input file for another problem, you can use a text editor to

modify an existing data input file.

Sample data files are provided in the EPACMTP directory. Consult the file FILES.LST for a list of the

file names. To run EPACMTP, simply type <EPACMTP’ which will bring up the Main Menu screen.

From the Main Menu, using the arrow keys, select ‘Run’ and hit [RETURN]. This will give you the Run

Option screen. To run the model, select the (C)ommand line mode option by pressing the letter C. Then

enter the name of the input data file and press [RETURN].

• You must give complete DOS file names

• EPACMTP will use the same name as the data input file, but an extension of

<.out’, to create the model output file

When EPACMTP is running in Monte Carlo mode, an iteration counter and estimated completion time are

displayed on-screen. This will show the progress of the Monte Carlo simulation. Do not be alarmed when

a run takes a long time, especially in the case of finite source simulations.

USING THE POST-PROCESSOR

EPACMTP generates a number of output files. The main output file (extension <.out’) contains a listing

of the data input. The Monte Carlo output is stored in files with extension of <.cdf’ (for continuous source

analyses) and <.sat’. (for finite source analyses). The POSTCMTP post processor allows you to graphically

analyze the modeling results contained in these output files.

POSTCMTP Post-Processor

POSTCMTP is a menu-driven utility for graphically analyzing EPACMTP Monte Carlo results. It also

has the capability of plotting graphs on a wide variety of printers and plotters, or saving a graph on disk

in HPGL format for importing into various word processing and/or desktop publishing programs.
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To start POSTCMTP, type <POSTCMTP’ at the DOS prompt or select ‘Plot’ from the main menu of

EPACMTP. The main menu of POSTCMTP presents three primary options:

• (C)ontinuous Source Analysis

• (F)inite Source Analysis

• (I)nitialize Plotting Device

The very first time you run POSTCMTP, you will be taken automatically into the Initialization menu, so

we will discuss that first.

Initialize Plotting Device

The initialization menu allows you to select the type of printer or plotter and the parallel (LPT:) or serial

port (COM:) through which the printer or plotter is connected to your PC. If you select a printer, you will

also be asked for the desired density of the printed graph. A higher density will result in better quality,

but also slower printing. After you make the initial setup, the information is stored by POSTCMTP. To

change any of the settings, you must go through the (I)nitialize menu again.

Continuous Source Analysis

After you select (C)ontinuous Source from the main menu, you are prompted for the name of the Monte

Carlo output file. Enter the root filename only, without extension! The main options on the Continuous

Source menu are:

(G)raph: View the DAF or CDF curve, and optionally send it to a

printer or plotter

(S)pecify: Enter a probability level and get the corresponding DAF

value, and vice versa

(N)ew File: Enter a new filename to analyze

If you select the (G)raph option, the cumulative probability function (CDF) of the normalized receptor well

concentration (i.e., the inverse of DAF) will be drawn on-screen.

After the plot is completed, a number of additional options appear at the bottom of the screen. These

include (H)ard Copy, to send the plot to your printer or plotter, and (S)ave which allows you to save the

plot on disk for later viewing, or in HPGL format. The latter allows you to import the graph directly into

reports and documents by importing the HPGL plot file as a graphic into your wordprocessor. Note that

printing to a laser printer at high resolution is quite slow; it may take 5 minutes per plot.

Finite Source Analysis

After you select (F)inite Source from the main menu, you will first be prompted for the name of the Monte

Carlo output file. Enter the filename only, without extension!. The main options on the Finite Source

menu are:
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(G)raph: View the graph of leachate versus waste concentrations at

the selected protection level

(S)pecify: Select the desired protection level, or get the maximum

leachate concentration for a given waste concentration

(N)ew file: Enter a new file name to analyze.

If you select the (G)raph option, a plot of leachate versus waste concentration corresponding to the selected

protection level will be drawn on-screen. The default protection level is 85%.

After the plot is completed, a number of additional options appear at the bottom of the screen. These

include (H)ard Copy, to send the plot to your printer or plotter, and (S)ave which allows you to save the

plot on disk for later viewing, or in HPGL format. The latter allows you to import the graph directly into

reports and documents by importing the HPGL plot file as a graphic into your wordprocessor. Note that

printing to a laser printer at high resolution is quite slow; it may take 5 minutes per plot.

The (S)pecify option allows you to change the default protection level used in generating the graph of

leachate versus waste concentrations.
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TABLE OF CONTENTS

Page

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

1.1 ORGANIZATION OF THE DOCUMENT . . . . . . . . . . . . . . . . . . . . . . . . . 1-1

1.2 EPACMTP CAPABILITIES AND LIMITATIONS . . . . . . . . . . . . . . . . . . . . 1-4

1.3 CODE REQUIREMENTS AND INSTALLATION PROCEDURES . . . . . . . . . 1-8

1.4 EPA CONTACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-9

PART 1 SIMULATION OBJECTIVES

2.0 SOURCE - RELEASE SCENARIOS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1

2.1 CONTINUOUS SOURCE SCENARIO . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1

2.2 FINITE SOURCE SCENARIO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-1

3.0 METHODOLOGY OF SIMULATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-1

3.1 DETERMINISTIC MODE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-1

3.1.1 EPACMTP characteristics in deterministic mode . . . . . . . . . . . . . . . . 3-1

3.1.2 Requirements for running EPACMTP in deterministic mode . . . . . . . . . 3-1

3.2 MONTE CARLO MODE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-2

3.2.1 EPACMTP characteristics in Monte Carlo mode . . . . . . . . . . . . . . . . 3-2

3.2.2 Requirements for running EPACMTP in Monte Carlo mode . . . . . . . . . 3-3

PART 2 WASTE AND WASTE UNIT CHARACTERIZATION

4.0 SOURCE-SPECIFIC PARAMETERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1

4.1 WASTE UNIT AREA AND DEPTH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1

4.2 INITIAL LEACHATE CONCENTRATION (CZERO) . . . . . . . . . . . . . . . . . . 4-1

4.3 RECHARGE RATES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-5

4.4 INFILTRATION RATES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-5

4.5 SOURCE LEACHING DURATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-6

4.6 WASTE DENSITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-7

4.7 HAZARDOUS FRACTION OF WASTE . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-7

4.8 SOURCE TRANSFORMATION RATES . . . . . . . . . . . . . . . . . . . . . . . . . . 4-7

5.0 CHEMICAL-SPECIFIC PARAMETERS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-1

5.1 ORGANIC CONSTITUENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-1

5.1.1 Hydrolysis Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-1

5.1.2 Reference Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-4

5.1.3 Normalized Distribution Coefficient . . . . . . . . . . . . . . . . . . . . . . . . 5-4

5.1.4 Constituent Drinking Water Standard . . . . . . . . . . . . . . . . . . . . . . . . 5-4

5.2 METALS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-4

5.2.1 Soil and Aquifer pH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-4

5.2.2 Fraction Iron-Hydroxide Adsorbent . . . . . . . . . . . . . . . . . . . . . . . . . 5-5

5.2.3 Leachate Organic Matter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-5

5.2.4 Natural Organic Matter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-5
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PART 3 SUBSURFACE FATE AND TRANSPORT SIMULATION

6.0 UNSATURATED ZONE SIMULATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-1

6.1 THICKNESS OF THE UNSATURATED ZONE . . . . . . . . . . . . . . . . . . . . . 6-3

6.2 SOIL CHARACTERISTIC CURVE PARAMETERS . . . . . . . . . . . . . . . . . . 6-3

6.3 LONGITUDINAL DISPERSIVITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-3

6.4 FREUNDLICH SORPTION COEFFICIENT (DISTRIBUTION COEFFICIENT) 6-7

6.5 PERCENT ORGANIC MATTER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-7

6.6 FREUNDLICH ISOTHERM EXPONENT . . . . . . . . . . . . . . . . . . . . . . . . . . 6-7

6.7 CHEMICAL AND BIOLOGICAL TRANSFORMATION COEFFICIENTS . . . . 6-8

7.0 SATURATED-ZONE SIMULATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-1

7.1 PARTICLE DIAMETER . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-7

7.2 POROSITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-7

7.3 BULK DENSITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-10

7.4 AQUIFER THICKNESS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-10

7.5 HYDRAULIC CONDUCTIVITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-10

7.6 HYDRAULIC GRADIENT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-11

7.7 SEEPAGE VELOCITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-11

7.8 RETARDATION FACTOR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-11

7.9 DISPERSION COEFFICIENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-12

7.10 TEMPERATURE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-14

7.11 GROUNDWATER PH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-14

7.12 FRACTIONAL ORGANIC CARBON CONTENT . . . . . . . . . . . . . . . . . . . 7-14

7.13 RECEPTOR WELL LOCATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-14

7.14 CHEMICAL & BIOLOGICAL TRANSFORMATION COEFFICIENTS . . . . . 7-21

7.15 FREUNDLICH ISOTHERM COEFFICIENT . . . . . . . . . . . . . . . . . . . . . . 7-21

7.16 FREUNDLICH ISOTHERM EXPONENT . . . . . . . . . . . . . . . . . . . . . . . . . 7-22

7.17 DIFFUSION COEFFICIENT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-22

7.18 ANISOTROPY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-22

PART 4 OUTPUT INTERPRETATION

8.0 RECEPTOR WELL CONCENTRATIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-1

8.1 DETERMINISTIC MODE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-1

8.2 MONTE CARLO MODE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-1

8.2.1 Model Output Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-2

APPENDIX A SIMULATION USING EPACMTP: DATA INPUT GUIDE . . . . . . . . . . . . . . A-1

APPENDIX B EXAMPLE OF MONTE CARLO SIMULATION PROBLEM . . . . . . . . . . . . . B-1

REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R-1
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LIST OF FIGURES

Page

Figure 1.1 A Cross-Sectional View of Subsurface Modeled by EPACMTP . . . . . . . . . . . . 1-5

Figure 4.1 Waste Management Scenarios Simulated by EPACMTP . . . . . . . . . . . . . . . . . 4-3

Figure 6.1 Cross-sectional view of the unsaturated zone considered by EPACMTP . . . . . . . 6-2

Figure 7.1 A schematic view of the groundwater system simulated by the saturated zone module 

of EPACMTP. The shaded area represents the projection of the contaminant source 

area onto the top of the aquifer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-2

Figure 7.2 Groundwater temperature distribution for shallow aquifers in the United States. 

(After Collins, 1925) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-15

Figure 7.3 Schematic plan view showing procedure for determining the downstream location 

of the receptor well: (a) well location determined using radial distance, R, and angle 

off center, 2; and (b) well location generated uniformly within plume limit . . . . 7-19
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LIST OF TABLES

Page

Table 1.1 Summary of the Components of EPACMTP Model . . . . . . . . . . . . . . . . . . . . 1-4

Table 3.1 Probability distributions and their associated codes available for use in Monte 

Carlo module of EPACMTP composite model . . . . . . . . . . . . . . . . . . . . . . . 3-4

Table 4.1 Source-Specific Variables and Default Distribution Types . . . . . . . . . . . . . . . . 4-2

Table 4.2 Cumulative Frequency Distribution of Waste Unit Area for Industrial Subtitle 

D Waste Management Facilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-4

Table 4.3 Cumulative probability distribution of waste density . . . . . . . . . . . . . . . . . . . . 4-8

Table 5.1 Chemical-Specific Variables and Default Distribution Types . . . . . . . . . . . . . . 5-2

Table 5.2 Metals-Specific Variable and Default Distribution Types . . . . . . . . . . . . . . . . . 5-6

Table 5.3 Probability distribution of soil and aquifer pH . . . . . . . . . . . . . . . . . . . . . . . . 5-7

Table 6.1 Unsaturated Zone Specific Variables and Default Distribution Types . . . . . . . . . 6-4

Table 6.2 Statistical parameters for soil properties for three soil types 

(Carsel and Parrish, 1988) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-5

Table 6.3 Compilation of field dispersivity values (Gelhar et al. 1985) . . . . . . . . . . . . . . . 6-6

Table 7.1 Aquifer-Specific Variables and Default Distribution Types . . . . . . . . . . . . . . . . 7-5

Table 7.2 Regional Hydrogeologic Environments . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-6

Table 7.3 Empirical distribution of mean particle diameter (based on Shea, 1974) . . . . . . . 7-8

Table 7.4 Ratio between effective and total porosity as a function of particle diameter 

(after Mcworter and Sunada, 1977) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-9

Table 7.5 Probabilistic representation of longitudinal dispersivity . . . . . . . . . . . . . . . . . 7-13

Table 7.6 Cumulative probability of distance to nearest receptor well for landfills 

(from EPA, 1993d) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-18

Table 7.7 Cumulative probability distribution of receptor well depth . . . . . . . . . . . . . . . 7-20

Table 8.1 Monte Carlo output files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-3
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1.0 INTRODUCTION

The USEPA Office of Solid Wastes (OSW) has developed a probabilistic (Monte Carlo)

groundwater flow and transport modeling approach to assess potential exposure of groundwater to toxic

chemical constituents in wastes that are managed in Subtitle D industrial waste management units under

RCRA regulations. The exposure to groundwater is expressed as concentrations of potential contaminants

at drinking water well (receptor well) located downgradient of the waste disposal facility. This modeling

methodology has been incorporated into the EPA’s Composite Model for Leachate Migration with

Transformation Products code (EPACMTP; EPA, 1996 a,b,c,d). The OSW of the U.S. EPA has recently

applied EPACMTP, as a general fate and transport model, to establish regulatory levels for concentrations

of chemicals in the above wastes under the proposed Hazardous Waste Identification Rule (HWIR; EPA,

1995).

EPACMTP simulates a one-dimensional, vertically downward flows and transport of contaminants

in the unsaturated zone underneath a waste disposal unit, and 3-D or 2-D groundwater flow and

contaminant transport in the underlying saturated zone. The model accounts for the following processes

affecting contaminant fate and transport: advection, hydrodynamic dispersion, linear or nonlinear

equilibrium sorption, chained first-order decay reactions, and recharge dilution in the saturated zone.

EPACMTP incorporates a Monte Carlo module which allows for the assessment of uncertainty in receptor

well concentrations due to variations in the model input parameters.

This document is prepared to facilitate the use of EPACMTP as an analytical tool. Section 1.1

provides general background information to direct the user through this document. Section 1.2, outlines

the model capabilities and limitations. Practical code requirements and installation procedures are provided

in Section 1.3. To promote further utilization and future enhancements of the model, the user is

encouraged to direct questions and comments to EPA’s contact person. This information is provided in

Section 1.4.

1.1 ORGANIZATION OF THE DOCUMENT

This report is prepared to facilitate the use of EPACMTP as an analytical tool. It provides the user

a sequentially organized instructions to prepare an input file for EPACMTP. It also presents brief

discussion on some of the key concepts of the model, particularly, with regard to estimation of input

parameters as well as model output analysis. This document, alone, does not contain the background

information that is necessary for a thorough knowledge and understanding of theoretical concepts and

methodologies of EPACMTP components. Therefore, it is strongly recommended that the user read this

and all other technical documentation of EPACMTP (EPA 1996 b, c, d) to achieve a comprehensive

understanding of the model. The rest of this section provides general information to direct the user through

this document. Section 1.2, outlines the model capabilities and limitations which the user must be familiar

with before using the model for any applications. Practical code requirements and installation procedures

are presented in Section 1.3. To promote further utilization and future enhancements of the model, the

user is encouraged to direct questions and comments to EPA’s contact person. This information is

provided in Section 1.4. This report is divided into the following four parts. 
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Part 1: Simulation Objectives of the Model

Part 2: Waste and Waste Management Unit Characterization

Part 3: Fate and Transport Simulation in the Subsurface

Part 4: Model Output Processing and Analysis

These parts represent the sequence of general considerations and information gathering steps that

are required to develop an input file for the EPACMTP code. The material covered in each part is briefly

described in this section. The major components, options and considerations for each part of the process

are summarized in Table 1.1. This table also provides a reference column that gives the specific section

of this report where the user can get details on specific items. 

The first part addresses model input parameter which determine the general settings of the model

under which fate and transport simulations are performed. Among these parameters are the model’s

execution mode (Monte Carlo or deterministic), waste management unit type (e.g. landfill, surface

impoundment), source release scenario ( continuous or finite source) etc. This group of parameters are

identified in the input file by their group code, GP which stands for general parameters. Chapter two

focuses on issues related to source release scenarios and Chapter 3 addresses other parameters that

determine the general setting of the model. 

Part 2 addresses parameters required to characterize waste management unit characteristics (e.g.,

area, depth, geographical location and climatic zone) as well as waste characteristics ( e.g., volume,

density and concentrations in the waste and leachate). This group of variables are called source-specific

parameters and are identified in the input file by their code SS. Described in Part 2 of the report also are

the chemical-specific parameters identified in the input file by the code CS. This group of variables

provide constituent specific information such as hydrolysis rates, diffusion coefficient, organic carbon

distribution (koc) etc. 

 Part 3 of the document focuses on model variables that characterize unsaturated zone (US) and

saturated zone (AS) parameters. The letters shown in the brackets are the identification codes for these

two groups of parameters in the input file respectively. Unsaturated zone parameters include depth to water

table, saturated hydraulic conductivity, soil moisture characteristic parameters dispersion etc. Examples

of the saturated zone parameters include aquifer thickness, hydraulic conductivity, hydraulic gradient,

dispersivity and receptor well location. 

Part 4 of the report addresses issues regarding model output processing and analysis. It describes

how the output of the model, receptor well concentrations, are used to build probability distribution

function which defines different levels of protection.

Appendix A contains detailed instructions on how to prepare an EPACMTP input file. The

instructions are designed to guide the user, step by step, through the process of creating an input data file.

The task of input file preparation would even be easier in the near future when a Windows-based

EPACMTP preprocessor with graphical user interface is available. A DOS-based program is currently

available for post processing of model results and is also presented in Appendix A. Sample input and

output files for a Monte Carlo simulation scenario for landfills are presented in appendix B. Appendix C

provides frequency distributions for key EPACMTP input parameters.
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Table 1.1 Summary of the Components of EPACMTP Model

Component

Input File

Code* Options Consideration (s)

Reference

Section

A. Source-Release

Scenario

GP • Continuous

• Finite

• Waste management scenario of

concern

2.0

B. Methodology of

Simulation

GP • Deterministic

• Monte Carlo

• Single values for specific

parameters

• Probability distributions for

specific parameters

3.0

C. Waste and Waste

Management Unit

Characteristics

SS • Landfill

• Surface impoundment

• Waste pile

• Land application unit

• Active life

• Dimensions

• Waste value and leachate

concentration

• Climatic/hydrogeologic

Characteristics

4.0

D. Contaminant Type CS • Organic 

• Metal

• Transformation Products

• Sorption Characteristics

(linear/nonlinear)

5.0

E. Unsaturated zone

module

US Flow

• Steady-state (1D)

Transport

• Steady-state

• Transient

• Sorption

(linear/nonlinear)

• Decay

• Depth to water-table

• Soil characteristics

6.0

F. Saturated zone module AS Flow

• Steady-state (2D

or 3D)

Transport

• Steady-state

• Transient

• Linear sorption

• Decay

• Aquifer characteristics

• Saturated thickness

• Ambient groundwater gradient

7.0

G. Receptor Well Location AS • Within plume

• Anywhere

downgradient

• Along plume

centerline only

• (x) distance from waste unit

• (y) distance from plume centerline

• (z) well depth

7.13

*See Appendix A
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1.2 EPACMTP CAPABILITIES AND LIMITATIONS

The EPA’s Composite Model for Leachate Migration with Transformation Products (EPACMTP)

comprises four major components:

• A module that performs one-dimensional analytical and numerical solutions for water flow

and contaminant transport in the unsaturated zone underlying a waste management unit.

• A numerical module for steady-state groundwater flow subject to recharge from the

unsaturated zone.

• A module comprising analytical and numerical solutions for contaminant transport in the

saturated zone.

• A Monte Carlo module for assessing the effect of uncertainty or variations in model

parameters on predicted contaminant concentrations in a receptor well.

A cross-sectional view of the subsurface system modeled by EPACMTP is shown in Figure 1.1.

The subsurface consists of an unsaturated zone underneath a waste unit, and an underlying water table

aquifer. Contaminants move vertically downward through the unsaturated zone to the watertable.

EPACMTP allows for the simulation of flow and transport in the unsaturated zone and in the saturated

zone, separately or combined.

To use the model correctly, the user must be aware of the model capabilities and, perhaps more

importantly, its limitations. The EPACMTP code is capable of simulating the fate and transport of

dissolved contaminants from a point of release at the base of a waste disposal unit, through the unsaturated

zone and underlying groundwater, to a receptor well at an arbitrary downstream location in the aquifer.

The code accounts for the major mechanisms affecting contaminant migration, including: transport by

advection and dispersion, retardation due to reversible linear or nonlinear equilibrium adsorption onto the

soil and aquifer solid phase, and bio-chemical degradation processes. The latter may involve chain decay

reactions if the contaminant(s) of concern form a decay chain. As is true of any model, EPACMTP is

based on a number of simplifying assumptions which make the code easier to use and ensure its

computational efficiency. These assumptions, however, may cause application of the model to be

inappropriate in certain situations. Therefore, the user should verify whether all assumptions in

EPACMTP are appropriate before using the model for any application. The assumptions in EPACMTP

are summarized below:

1) Soil and Aquifer Medium Properties

It is assumed that the soil and aquifer are uniform porous media, and that flow and transport are

described by Darcy’s law and the advection-dispersion equation, respectively. The model does

not account for the presence of preferential pathways such as fractures and macro-pores. Although

the aquifer properties are assumed to be uniform, the model does allow for anisotropy in the

hydraulic conductivity.
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Figure 1.1 A Cross-Sectional View of Subsurface Modeled by EPACMTP.
E:\Projects\EPA\R08-99.217.wpd 1-6

2) Flow in the Unsaturated Zone

Flow in the unsaturated zone is steady-state one-dimensional vertical flow from underneath the

source towards the water table. The lower boundary of the unsaturated zone is the water table.

The flow in the unsaturated zone is predominately gravity-driven, and therefore the vertical flow

component accounts for most of fluid flux between the source and the water table. The flow rate

is determined by the long-term average infiltration rate through the waste management unit. In

surface impoundments, it is determined by the average depth of ponding.

3) Flow in the Saturated Zone

The saturated zone module of EPACMTP is designed to simulate flow in an unconfined aquifer

with constant saturated thickness. The concept is that of regional flow in the horizontal direction,

with vertical disturbance due to recharge and infiltration from the overlying unsaturated zone and

waste disposal facility. The lower boundary of the aquifer is assumed to be impermeable. Flow

in the saturated zone is assumed to be steady-state.

EPACMTP accounts for different recharge rates underneath and outside the source area.

Groundwater mounding beneath the source is represented in the flow system by increased head

values at the top of the aquifer. This approach is reasonable as long as the height of the mound

is small relative to the thickness of the saturated zone. 

4) Transport in the Unsaturated Zone

Contaminant transport in the unsaturated zone is by advection and dispersion. The unsaturated

zone is assumed to be initially contaminant-free and that contaminants migrate vertically

downwards from the disposal facility. EPACMTP can simulate both steady-state and transient

transport in the unsaturated zone, with single species or multiple species chain decay reactions, and

linear or nonlinear sorption.

5) Transport in the Saturated Zone

Contaminant transport in the saturated zone is due to advection and dispersion. The aquifer is

assumed to be initially contaminant-free and contaminants enter the aquifer only from the

unsaturated zone immediately underneath the waste disposal facility, which is modeled as a

rectangular horizontal plane source. EPACMTP can simulate both steady-state and transient

transport three-dimensional transport in the aquifer. For steady-state transport, the contaminant

mass flux entering at the water table must be constant with time. For the transient case, the flux

at the water table can be constant or may vary as a function of time. EPACMTP can consider the

transport of a single species or multiple species chain decay reactions, and linear sorption.
E:\Projects\EPA\R08-99.217.wpd 1-7

6) Contaminant Phases

EPACMTP assumes that the dissolved phase is the only mobile phase, and disregards interphase

mass transfer processes other than adsorption onto the solid phase. The model does not account

for volatilization in the unsaturated zone; this is a conservative approach for volatile chemicals.

The model also does not account for the presence of a NAPL (e.g. oil) and transport in gas phase.

When a mobile oil phase is present, significant migration may occur within it, so that EPACMTP

may underpredict the movement of hydrophobic chemicals.

7) Chemical Reactions

The EPACMTP model represents chemical reactions by adsorption and decay processes.

Adsorption

The EPACMTP assumes that sorption of organic compounds in subsurface is represented linear

adsorption isotherms in both the unsaturated and saturated zones. It is assumed that the adsorption

of contaminants onto the soil or aquifer solid phase occurs instantaneously, and is entirely

reversible.

The effect of geochemical interactions is especially important in the fate and transport analyses of

metals. For the simulation of metals, EPACMTP utilizes sorption isotherms generated by

MINTEQA2 (Allison et al., 1991, a metal speciation model.) MINTEQA2 generates

concentration-dependent effective partition coefficients, for various combinations of geochemical

conditions. This procedure is described in the background document for the modeling of metals

transport (EPA, 1996d).

Transformation reactions

EPACMTP accounts for chemical and biological transformation processes. All transformation

reactions are represented by first-order decay processes. An overall decay rate is specified for the

model, so that the model cannot explicitly consider the separate effects of multiple degradation

processes such as oxidation, hydrolysis and biodegradation. The user must determine the overall,

effective decay rate when multiple decay processes are to be represented. In order to increase its

flexibility, EPACMTP has the capability of determining the overall decay rate from chemicalspecific hydrolysis constants using soil and aquifer temperature and pH values.

EPACMTP assumes that the reaction stoichiometry is prescribed for scenarios involving chain

decay reactions. The speciation factors are specified as constants by the users (see the EPACMTP

Background Document, EPA, 1996b). In reality, these coefficients may change as functions of

aquifer conditions (for example, temperature and pH) and/or concentration levels of other chemical

components.
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1.3 CODE REQUIREMENTS AND INSTALLATION PROCEDURE

Code Requirements

In order to apply the EPACMTP code effectively the user will need:

• A thorough understanding of hydrogeological principles, 

• A thorough understanding of solute transport mechanisms, 

• An understanding of the principles of Monte Carlo analysis,

• An awareness of the code’s capabilities and limitations,

• Familiarity with FORTRAN input format conventions, and 

• Familiarity with the editor, operating system, and file handling concepts of the computer

system used.

The run-time version of EPACMTP requires an 80386/486 or Pentium based computer with an

MS-DOS operating system. A 80387 math coprocessor is required for 386 systems. The computer should

be equipped with at least eight (8) megabytes of random access memory (RAM) and a hard disk. To

accommodate temporary files created during a model run, the hard disk should have at least one megabyte

of free space for Monte Carlo simulations with the continuous source option. For model runs with the

finite source option, up to twenty megabytes of free disk space may be required by the model for

temporary files.

Users are strongly encouraged to read the entire User’s Guide before applying the model. This

manual explains the assumptions and approximations used in the model, knowledge of which is a necessary

prerequisite for using the model effectively. Instructions for setting up, executing, and analyzing a

problem are provided in appendix A.

Installation Procedure

The EPACMTP program should be executed from a hard disk. To facilitate installation of the files

from the distribution diskette onto a computer hard disk, an installation utility (INSTALL.EXE) is provided

which automatically copies the necessary files.

To install the software on your hard disk, insert the distribution diskette into your floppy drive

(usually “a”) and type:

a:\install a: c:

where a: is the drive containing the distribution disk and c: is the hard drive. 

The installation program will create a directory (default is c:\EPACMTP) in which all program files will

be installed. In order to run EPACMTP, your CONFIG.SYS file should contain the following lines:
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FILES=20 (or greater)

DEVICE=ANSI.SYS

Consult your MS-DOS manual for more information on configuring the CONFIG.SYS file. Additional

information on system configuration will be displayed during the installation procedure and is provided in

the README.1ST file on the distribution diskette. 

1.4 EPA CONTACT

For additional information or to submit comments and recommendations, please contact:

Dr. Zubair Saleem

U.S. Environmental Protection Agency

Office of Solid Waste (Mailcode 5307W)

401 M Street, SW

Washington, DC 20460

Phone: (703) 308-0467

FAX: (703) 308-0511

E-mail: saleem.zubair@epamail.epa.gov
PART 1

SIMULATION OBJECTIVES 
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2.0 SOURCE - RELEASE SCENARIOS

There are two types of source release scenarios in EPACMTP. They are continuous and finite

soures. In a continuous source release scenario, the contaminant leaches out at constant prescribed leachate

concentration for an indefinite period of time. In this case, the receptor well concentration eventually

reaches a steady-state value. For the finite-source scenario, the release of contaminants occurs over a finite

period of time, after which the leachate concentration becomes zero (i.e. all the waste inside the waste

management unit has leached out). In addition to the concentration, the receptor well concentration for

finite source scenario is also affected by the duration of the source.

The source-release parameter is one of several general parameters (GP) that are designated in the

input file. The discussion in this section in restricted to the source-release parameter since it is the most

significant general parameter in determining the methodology and approach of the simulation. The

designation of other general parameters are addressed in detail in Appendix A.

2.1 CONTINUOUS SOURCE SCENARIO

In the continuous source scenario, the fate and transport model is run in steady-state mode to

compute a Dilution-Attenuation Factor (DAF). The DAF is defined as the ratio of source concentration

to receptor well concentration. It represents the combined effects of the site, and hydrogeologic and

chemical specific parameters on the receptor concentrations. The model run can be conveniently

performed using a source leachate concentration value of one, so that the DAF becomes the inverse of the

receptor well concentration value. In order to assess the impact of varying site conditions across the

nation, the fate and transport model can be coupled to a Monte Carlo module to account for the variability

of input parameters. In this way, the model is used to calculate a series of DAF values corresponding to

a large number of different model input parameter combinations, reflecting the range of parameter values

for different possible waste sites. A probability distribution of DAF values is the result of a Monte Carlo

analysis. The resulting DAF values provide a means to identify hazardous versus non-hazardous wastes,

based on the DAF values for individual toxic constituents as well as their Health Based Numbers (HBNs)

in the waste. See Appendix B for a sample continuous source problem. 

2.2 FINITE SOURCE SCENARIO

In the case of a finite source, simulations are performed for transient conditions and the source is

assumed to be a pulse of finite duration. The length of the pulse duration, in the case of landfills, is

determined by the code based upon the initial amount of contaminant in the landfill, infiltration rate,

landfill dimensions, waste and leachate concentration and waste density (EPA ,1996c). For other waste

management scenarios (i.e. waste piles, surface impoundments, and land application units), the duration

of the leaching period is determined by the waste unit’s life time (the default is 20 years for waste piles and

surface impoundments, and 40 years for land application units). For the finite source case, the model can

calculate either the peak receptor well concentration, or it can calculate an average concentration over a

specified period of time. The finite source methodology in EPACMTP is discussed in detail in the finite

source background document (EPA, 1996c). 
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3.0 METHODOLOGY OF SIMULATION

Two modes of simulation, deterministic mode and Monte-Carlo mode, are available to the user for

applications with EPACMTP. The selection of one of these modes is dependent on: 1) simulation

objectives; and 2) the type of data available to simulate the waste management scenario(s) of concern. The

deterministic mode uses single values for various source, chemical, and subsurface parameters. This mode

is most appropriate for non-probabilistic applications, and simple sensitivity analyses. When using a

Monte-Carlo procedure, the source, chemical and subsurface parameters are represented by probability

distributions reflecting variations based on national or regional level. Specific capabilities and

requirements of EPACMTP for both of these two simulation procedures are presented in the following

sections. 

3.1 DETERMINISTIC MODE

In order to help the user to appreciate the differences between the deterministic mode and the

Monte Carlo procedure, this section describes the capabilities of the EPACMTP in deterministic mode as

well as the specific requirements for running the model in deterministic mode.

3.1.1 EPACMTP characteristics in deterministic mode

• Flow is steady-state in both the saturated and unsaturated zones.

• Transport in the unsaturated and saturated zones can be either transient or steady-state.

• If a finite source is being simulated, both the unsaturated and saturated zone transport

modules are implemented in the transient mode.

• Each input parameter is assigned a constant value or treated as a derived parameter. An

example is the calculation of the partition coefficient (kd) from the fraction organic carbon

(foc) and organic carbon distribution coefficient (koc).

3.1.2 Requirements for running EPACMTP in deterministic mode

• The logical variable, MC, in input group GP01 must be set to F(alse).

• If a transient transport in the unsaturated zone is to be simulated, the times at which the

concentration profiles in the unsaturated zone are to be written to the output file must be

specified by the user.

• If transport in the saturated zone is to be simulated, the user must specify the number of

observation wells, and their locations relative to the disposal facility. If a transient run is

selected, the user must also specify the time values at which the computed receptor well

concentrations are to be written to the output file. Details for setting up a deterministic

input data file are presented in Appendix A.
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3.2 MONTE CARLO MODE

When EPACMTP is used in the Monte Carlo mode, the primary output from the simulation model

is a sequence of receptor well concentration values, where each concentration corresponds to the results

of one model simulation. For each simulation, a different set of input parameters are generated from

appropriate distributions to calculate a receptor well concentration. The Monte Carlo output is then

analyzed to derive regulatory DAF values (waste piles, surface impoundments, and application units) or

regulatory limits on leachate and waste concentrations landfills. For the continuous source scenario, the

DAF is obtained by dividing the source leachate concentration by the receptor well concentration. Each

Monte Carlo iteration yields one DAF value for the constituent of concern (one DAF value for each of the

transformation products, if the constituent degrades to a daughter product.) Ordering the DAF values from

low to high directly yields the DAF cumulative probability distribution (CDF). If appropriate, CDF curves

representing different regional distributions may be combined into a single, weighted curve that represents

all regions. (See Part 3, Section 2.2 in the Background document for further discussion.)

For the finite source scenario, the post-processing step involves determination of the paired values

of leachate concentration, CL in the case of landfills, and total leachable waste concentration, Cw, which

satisfy a specified protection level. The procedure is described in the finite source background document

(EPA, 1996c). To facilitate the post-processing analysis of Monte Carlo simulations, a separate postprocessing program (POSTCMTP) is distributed with the EPACMTP code (see Section 8.0).

3.2.1 EPACMTP characteristics in Monte Carlo mode

• Flow in the saturated zone is steady-state in the unsaturated and saturated zones.

• Transport in the unsaturated and saturated zones can be either transient or steady-state.

• If a finite source is being simulated, both the unsaturated and saturated zone transport

modules are implemented in the transient mode.

• Prespecified input parameters are represented by probability distributions specified in the

input file. It is allowed, however, to specify that a certain parameter is to be treated as

a derived variable. An example is the calculation of the waste fraction (ratio of waste

volume to facility volume).

3.2.2 Requirements for running EPACMTP in Monte Carlo mode

• The logical variable, MC, in input group GP01 must be set to T(rue).

• Probability distributions for the stochastic or random parameters must be specified in the

EPACMTP data input file.

• If transport in the saturated zone is to be simulated, the user must specify the number of

observation wells, and their locations relative to the disposal facility.

 If the logical variables CHECK and LDRIV (see Appendix A) are set to TRUE in the Monte Carlo

input file, the generated random and derived variables, respectively, are constrained to lie within the upper

and lower bounds defined by the user. The randomly generated variables are checked at the end of
E:\Projects\EPA\R08-99.217.wpd 3-3

subroutine RANGEN, and the derived random variables are checked at the end of subroutine ASSIGN.

If any of the constrained values lie outside the specified bounds, the entire Monte Carlo run (except for

the reading of the input files) prior to the point of checking is repeated. Random and derived variables that

are generated out of bounds are written to the Monte Carlo output file {OUTPUT}.BND .

Variables that are to be treated as random must be assigned one of thirteen probability distribution

types. The distribution types and their corresponding distribution codes are listed in Table 3.1. The

default distribution type for each Monte Carlo variable is discussed in the next chapter. For further

information on the various distribution types, consult the EPACMTP Background Document (EPA,

1996b).

3.2.3 Regional Site-Based Monte Carlo Approach

The implementation of the regional site-based Monte Carlo approach in EPACMTP allowed the use of

individual waste unit characteristics as well as regional specific climatic and hydrogeologic conditions in

the fate and transport simulations. Prior to this approach, model input parameters, such as waste unit area

and depth, infiltration and recharge rates, depth to water table, aquifer thickness, etc., were generated from

national distributions in which correlation between the geographical location of the waste site and its

climatic (infiltration and recharge rate) and hydrogeologic (unsaturated and saturated zone parameters)

properties were not preserved. The regional site-based approach is discussed in detail in the EPACMTP

Background Document (EPA, 1996b); however, an overview of the methodology is presented here.

The steps involved in the site-based Monte Carlo approach are presented below. Fundamentally,

the approach consists of determining the probability distribution of DAF based on the existing Subtitle D

waste sites, on the assumption that these sites are an adequate representation of the universe of possible

waste sites in the U.S.

Since the the Subtitle D data set only includes the area, volume, location and relative weight of the

facility, other data sources are utilized to determine the additional input parameters required to estimate

the receptor well concentration for each OPPI site. 

The groundwater parameters are obtained by dividing the U.S. into the thirteen hydrogeologic

environments developed in the HGDB groundwater study (API, 1989). Each groundwater region includes

multiple site- specific combinations of hydrogeologic parameters. In order to assign the groundwater

parameters for a given waste site, the hydrogeologic environment is first determined from the geographic

location of the waste site. One of the available combinations of groundwater parameters for the

hydrogeologic environment is then assigned to the waste site. In the case where the selected groundwater

parameter combination has missing values, a joint probability distribution is derived for each groundwater

region to generate the missing value as a function of the known values. Given the location of the waste

site, the climatic parameters for the nearest climatic center are assigned. The remaining parameters needed

to determine the receptor well concentration for a given waste site are generated by using national

distributions.

Given a specific realization of input parameters representing a waste site, and the climatic,

hydrogeologic, and receptor well characteristics of that site, the corresponding receptor well concentration

can be determined. This process is repeated in an iterative manner to construct a probability distribution

of receptor well concentrations. During each iteration, a site is selected at random from the Subtitle D data

set. The sites are sampled with replacement, i.e., the same site may be selected more than once. The
E:\Projects\EPA\R08-99.217.wpd 3-4

probability of selecting a specific site depends on the relative weight assigned to that site in the data set.

. The procedure of the Monte Carlo simulation run is summarized below.

STEP 1: Select a Waste Site from Subtitle D Database

STEP 2: Generate Recharge and Infiltration for Selected Waste Site

STEP 3: Generate Hydrogeologic Variables for Selected Waste Site

STEP 4: Generate Remaining Model Input Parameters for Selected Waste Site

STEP 5: Calculate the receptor well concentration value for Selected Waste Site

STEP 6 Repeat Steps 1 through 5 for the number of interations required, and estimate the national

distribution of receptor well concentrations

After Step 5 the receptor well concentration value for a specific realization is obtained. The process

is repeated to yield concentration

 values which represent the nationwide distribution of drinking water exposure concentrations. 
E:\Projects\EPA\R08-99.217.wpd 3-5

Table 3.1 Probability distributions and their associated codes available for use in Monte Carlo

module of EPACMTP composite model.

Distribution Type Distribution Code

1. Constant

2. Normal

3. Lognormal

4. Exponential

5. Uniform

6. Log10 Uniform

7. Empirical

8. Johnson SB

9. Gelhar Empiricala

10. Area Transformationb

11. Vertical Well Positionc

12. Site-basedd

13. Derived Variable

0

1

2

3

4

5

6

7

8

9

12

99

-1

Note: All statistical parameters (mean, standard deviation, lower and upper bounds) are input in standard

arithmetic (lineas) space. Appropriate transformations are subsequently performed by the code.

a

Gelhar’s distribution applies only to saturated zone dispersivities (Gelhar et al., 1992). 

b

This distribution applies to municipal Subtitle D landfill areas only.

c

This distribution applies to the vertical position of the receptor well below the water table only; it is used

to specify that the receptor well is located at a fixed depth below the water table.

d

This distribution applies to parameters that are read directly from an ancillary data file that contains waste

locations, volume and area, and corresponding regional climatic and hydrogeological parameters

for the site-based Monte Carlo analysis.
PART 2

WASTE AND WASTE UNIT CHARACTERIZATION
E:\Projects\EPA\R08-99.217.wpd 4-1

4.0 SOURCE-SPECIFIC PARAMETERS

A list of the source-specific input parameters is provided in Table 4.1. EPACMTP can perform

Monte Carlo or deterministic analyses for four different types of waste management scenarios: landfills,

surface impoundments, waste piles, and land application units. Figure 4.1 shows a schematic, crosssectional view of the different types of waste units. In terms of the model analysis, each type of waste

management scenario is described by a relatively small number of parameters. The differences between

waste units are represented by different values or frequency distributions of the source-specific parameters.

Source-specific stochastic parameters that may be used by EPACMTP include capacity and dimensions of

the waste unit, the leachate concentration, infiltration and recharge rates, pulse duration, fraction of

hazardous waste in the waste unit, density of the waste, and concentration of the chemical constituent in

the hazardous waste. Data on the area, volume and location of waste units was obtained from the 1986

EPA Survey of Industrial Subtitle D waste facilities in the U.S. This survey is referred to as the OPPI

Survey. The derivation of these parameters for each type of waste management unit is described in the

EPACMTP background document (U.S. EPA, 1996b).

4.1 WASTE UNIT AREA AND DEPTH

The cumulative frequency distributions of the areas of landfill, surface impoundment, waste pile

and land application waste units are listed in Table 4.2. These frequency distributions are shown

graphically in Figures C1 through C15 in Appendix C. 

4.2 INITIAL LEACHATE CONCENTRATION (CZERO)

The (initial) leachate concentration for each species in the contaminant decay chain being modeled

must be provided by the user. For continuous source (steady-state) simulations, the source concentration

of the parent compound is conveniently set to 1.0 (mg/L). Initial daughter product concentrations should

be set to zero. For finite source simulations, the (initial) parent leaching concentration should be set to a

fixed value. An artificially large value (e.g. CL = 106

 mg/L) is recommended for computational

convenience. Initial daughter product leaching concentrations should again be set to zero. The actual

parent leaching concentration that results in the desired level of protection is determined as part of the postprocessing analysis conducted after the Monte Carlo simulation is completed. This procedure is used for

organic contaminants and metals with linear sorption behavior. The post processing step takes advantage

of the fact that the receptor well concentration for these chemicals varies linearly with the source leachate

concentration. For details see the finite source background document (EPA, 1996c).

In the case of metals with nonlinear sorption isotherms, relationship between receptor well

concentration and the initial source leachate concentration is nonlinear. Therefore, the model has to be run

with different initial source leachate concentrations until the desired protection level is achieved. Because

of the nonlinearity the simulation time required is significantly longer than the linear case.
E:\Projects\EPA\R08-99.217.wpd 4-2

Table 4.1 Source-Specific Variables and Default Distribution Types.

Variable Units

Distribution

Code** Default Distribution

Waste Site Area (Aw) m2 99 Regional Site-based

Waste Site Length (Xw) m -1 Derived from area 

Waste Site Width (Yw) m -1 Derived from area 

Leachate Concentration (CL) mg/l 0 Constant (1 x 10+6 for

finite source; 1 for

continuous source)

Areal Recharge Rate (IR) m/yr 99 Regional Site-based

Infiltration (I) m/yr 99 Regional Site-based

Ponding Depth* m 99 Regional Site-based

Thickness of Liner* m 0 Constant (2 feet)

Hydraulic Conductivity of the

Liner*

m/yr 0 Constant (1 x 10-7

cm/s)

Source Leaching Duration (tp) yr -1 Derived

Depth of the Waste Unit (d) m 99 Regional Site-based

Fraction of Hazardous Waste in

the Waste Disposal Unit (Fh)

4 Uniform

Density of Hazardous Waste

(Phw)

(g/cm3

) 6 Empirical

* Required only for surface impoundment if source ponding option is used, i.e. infiltration is set to be

a derived parameter.

** See Table 3.1
E:\Projects\EPA\R08-99.217.wpd 4-3

Figure 4.1 Waste Management Scenarios Simulated by EPACMTP.
E:\Projects\EPA\R08-99.217.wpd 4-4

Table 4.2 Cumulative Frequency Distribution of Waste Unit Area for Industrial Subtitle D Waste

Management Facilities.

Landfill

Surface

Impoundment

Waste

Pile

Land

Application Unit

% Area (m2

) % Area (m2) % Area (m2) % Area (m2)

1

2

5

10

15

25

35

50

65

75

85

90

95

98

99

Min

Max

44.5

72.8

141.6 

809.4 

1214

3,683

8,094

16,188

32,3766

60,705

93,081

141,645

221,371

554,439

1,049,792

40.5

3,116,190

1

2

5

10

15

25

35

50

65

75

85

90

95

98

99

Min

Max

24.3

40.5

40.5

80.9

161.9 

404.7 

849.9 

2,024

5,059

8,094

20,235

40,065

81,345

234,726

518,016

13.4

60,705,000

1.8

15.0

25.0

31.4

35.5

40.1

45.0

50.1

60.7

70.5

80.2

85.1

90.0

95.0

99.0

Min

Max

20.2

28.3

52.6

93.1

157.8 

230.7 

364.2 

465.4 

1,133

2,064

5,200

8,992

18,576

50,264

1,011,750

12.1

2,015,406

1.9

5.1

10.5

20.5

31.3

41.0

50.4

59.5

70.3

80.0

85.1

90.3

95.1

99.1

Min

Max

80.9

930.8 

3,642

10,117

21,813

40,875

97,128

161,880

273,173

465,405

472,164

105,222

1,942,560

6,879,900

5.1

8.1107

Note:

The % column denotes the cumulative frequency, i.e. P(A # Area (m2

)).
E:\Projects\EPA\R08-99.217.wpd 4-5

4.3 RECHARGE RATES

The model requires input of the net rate of vertical downward percolation through the unsaturated

zone to the water table. The model allows the flow rate through the waste source to be different from the

regional average rate. The former is referred to as (source) infiltration rate, the latter is referred to as the

recharge rate. The source infiltration rate can be different from the recharge rate for a variety of reasons,

including engineering design of the waste site, topography, land use, and vegetation. The recharge rate

depends on the regional climatic conditions based on: 1) the proximity of the waste site to one of 97

climatic centers; and 2) the prevalent regional soil type.

Details of the development of the current recharge rate database are presented below. Variations

in soil types for determining regional recharge rates have been implemented in the following manner: The

Soil Conservation Service (SCS) has a county-by-county soil mapping database. Using this 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, silt loam, and silty clay loam for the landfill cover materials. 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 thus far. The recharge rate was determined separately for each soil type and each of the 97

climatic centers using the HELP model. The recharge rate values for each climatic center are listed in the

form of EPACMTP input files at the end of the report. Frequency distributions of recharge rates for

different waste management units are provided in Appendix B. The probability of each of the three soil

types is assumed to be uniform nationwide. In other words, the soil type and corresponding recharge rate

at each modeled waste site is selected in the Monte Carlo analysis from the three different available types,

with a weighting equal to their nationwide relative frequency.

4.4 INFILTRATION RATES

Infiltration rates for landfills, waste piles, and land application units were calculated for each of

the 97 climatic centers with the HELP model using the procedure and assumptions regarding design

characteristics of different types of waste units as described in the EPACMTP background document (EPA,

1996b). In the case of landfills, if the cover type and soil type underneath the unit are the same, the

infiltration rate will be the same as the regional recharge rate for that soil type. The infiltration rate values

for the landfills, waste piles, and land application units in the modeling database are listed in the form of

EPACMTP data input files at the end of this report. The frequency distributions are shown graphically

in Appendix C.

For the surface impoundment scenario, the leachate flux rate is computed as a derived parameter,

as part of the unsaturated zone flow module. The algorithm is described in the EPACMTP Background

Document (EPA, 1996b). In essence, the leachate flux rate is calculated by applying Darcy’s law as a

function of: (i) impoundment depth, (ii) thickness of a sediment layer at the base of the impoundment, and

(iii) hydraulic conductivity of this sediment layer and the underlying soil material. 

For the HWIR analyses (EPA, 1995), impoundment depths were obtained from the Subtitle D

survey data. All impoundments were assumed to have a sediment layer of 2 feet thickness with a hydraulic

conductivity of 10-7 cm/s. Although the latter two parameters were taken to be constant, each

impoundment in the survey has its own operating depth, and consequently the variation in surface

impoundment leachate flux rates is proportional to the variation in operating depths of the impoundments
E:\Projects\EPA\R08-99.217.wpd 4-6

(4.1)

(4.2)

in the survey. The frequency distribution of the surface impoundment infiltration rate is shown graphically

in Appendix C of this document.

4.5 SOURCE LEACHING DURATION

If a finite source simulation is being performed, the duration of the leachate release period must

be specified. The duration of the leachate release period is determined in different ways for each of the

waste management units. Except for landfills, the release period is determined by the operational life (or

active life) of the unit with default values as follows:

Surface Impoundments - 20 years

Waste Pile - 20 years

Land Application Unit - 40 years

In the case of landfills, the waste is left in place after closure of the site, and may continue to leach

over a long period of time. The landfill scenario is therefore best handled as follows:

In the Monte Carlo analysis, the pulse duration, tp, is treated as a derived parameter and can be

set in one of two ways. Specifically, the amount of contaminant leached over the time period tp must be

equal to the amount of contaminant initially present in the landfill. Method 1, Eqn. 4.1 below, assumes

that source contamination, CL, is constant until an amount of mass equal to the initial mass is depleted.

where

d = Depth of waste unit (m)

Fh = Volume fraction of waste unit that contains waste of concern

Phw = Density of the waste (g/cm3

)

I = Areal infiltration rate (m/y)

CL = Leaching concentration of constituent (mg/L)

Cw = Total leachable waste concentration of the constituent (mg/kg)

Alternatively, Method 2, Eqn. 4.2 below, calculates tp from a more rigorous analysis that

considers the decrease in the source concentration, CL, due to leaching from the waste. In this case, the

leachate concentration decreases exponentially, with (EPA, 1996b):

where

CL

0

 = Initial leachate concentration (mg/L)

t = Time (yrs)
E:\Projects\EPA\R08-99.217.wpd 4-7

Information on the distributions of waste density (Phw) and fraction of the waste in the unit (Fh) for landfill

disposal units is provided in the following sections. During the Monte Carlo analysis, the model

simulations are performed for a range of different ratios of Cw/CL (or Cw/CL

0

). The specific values of Cw

and CL (or CL

0

) which correspond to a desired level of protection, such as the 90th percentile, are

determined following the Monte Carlo run as a post-processing step.

4.6 WASTE DENSITY

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 4.3. The distribution shows a

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

.

4.7 HAZARDOUS FRACTION OF WASTE

Data to determine whether a Subtitle D waste exhibits hazardous characteristics are limited. By

definition, Subtitle D waste is primarily non-hazardous. The fraction of waste contributed to Subtitle D

waste facilities that may exhibit hazardous characteristics is assumed to be randomly distributed and

simulated using uniform distribution with lower and upper bounds of 0.036 to 1.0, respectively. The lower

bound ensures that the modeled waste unit will always contain a minimum amount of hazardous waste.

The lower bound was obtained from an analysis of waste composition in municipal landfills (Schanz and

Salhotra, 1992). Note that the input values for waste density and fraction of the waste unit that is occupied

by the waste, are required only for the landfill scenario. 

4.8 SOURCE TRANSFORMATION RATES

The model has the capability to account for first-order type chain decay reactions inside the waste

source. This requires values for the transformation rate constants of the parent compound and any

daughter products. By default, however, the source transformation rate is set to zero, i.e., it is assumed

that the contaminant does not degrade inside the waste unit.
E:\Projects\EPA\R08-99.217.wpd 4-8

Table 4.3 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
E:\Projects\EPA\R08-99.217.wpd 5-1

(5.1)

5.0 CHEMICAL-SPECIFIC PARAMETERS 

Chemical-specific parameters describe the degradation, adsorptive and diffusive characteristics of

each of the chemical species being simulated. The EPACMTP accounts for processes such as decay,

adsorption, and diffusion. The model handles the chemical-specific parameters of constituents differently

depending on whether the chemical being modeled is an organic compound or a metal. Chemical-specific

parameters for the two categories are described below. Chemical-specific parameters of the two chemical

categories are described below.

5.1 ORGANIC CONSTITUENTS

For organic constituents, EPACMTP accounts for chemical and biological transformations by considering

a first order over all degradation rate which may be available directly or derived from acid, base and

neutral chemical-specific hydrolysis rates (i.e. Arrhenius equation). The model also 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. Other inputs

required by the model are reference temperature and constituent drinking water standard. In addition, if

a finite source analysis is performed, values are required for the applicable drinking water standard for

each constituent, and the exposure averaging period used in the health-risk calculations (e.g. 70 years for

a carcinogenic constituent). By default, averaging is not used and the model computes the peak exposure

concentration at a downgradient receptor well. In the event that the byproducts are hazardous and their

chemical-specific parameters are known, they can be included in the simulation by specifying them to be

part of a decay chain. Note that when a multi-species simulation is desired, the necessary chemical-specific

parameters must be repeated ,for all species in the decay chain, NSPECI times. A list of the chemicalspecific parameters is provided in Table 5.1.

5.1.1 Hydrolysis Rates

The transport of organic constituents is influenced in part by hydrolysis. Hydrolysis rate constant

for each chemical is obtained from:

EPA’s Environmental Research Laboratory, Athens, GA. (e.g. EPA, 1993 and Kollig et al., 1990)

Acid- and base-catalyzed hydrolysis rate constants are influenced by pH. The pH dependency is

included directly in EPACMTP and the rates are adjusted via the independently derived distribution for

pH.

The acid-catalyzed, neutral and base-catalyzed hydrolysis rates are all influenced by groundwater

temperature. This effect is quantified using the Arrhenius equation:
E:\Projects\EPA\R08-99.217.wpd 5-2

Table 5.1 Chemical-Specific Variables and Default Distribution Types.

EPACMTP*

Parameter Variable Units

Distribution 

Code**

Default

Distribution

RLAM 2 Sorbed phase hydrolysis

decay rate (81)

1/yr -1 Derived

RLAM 1 Dissolved phase

hydrolysis decay rate

(82)

1/yr -1 Derived

AHYDR 1 Acid catalyzed

hydrolysis rate constant

1/mol/yr 0 Constant

NHYDR Neutral hydrolysis rate

constant

1/yr 0 Constant

BHYDR Base catalyzed

hydrolysis rate constant

1/mol/yr 0 Constant

RTEMP Reference temperature °C 0 Constant (25°C)

KOC Normalized distribution

coefficient for organic

carbon

ml/g 0 Constant

DSTAR Effective molecular

diffusion coefficient

m2

/yr 0 Constant (0.0

m2

/yr)

DWS Drinking water standard

(i.e., HBL or MCL)

mg/l 0 Constant

CARC Exposure averaging

period

yr 0 Constant

* See Appendix A, Table A.2

** See Table 3.1
E:\Projects\EPA\R08-99.217.wpd 5-3

(5.2)

(5.5)

where 

J = a for acid, b for base, and n for neutral

T = temperature of the groundwater [°C] 

Tr = reference temperature [°C] 

Ka

T

,

r

b and Ka

T

,b = the second-order acid- and base-catalysis hydrolysis rate at

temperature Tr and T respectively [l/mole-yr] 

Kn

Tr

 and Kn

T = the neutral hydrolysis rate at temperatures

Tr and T respectively [1/yr].

 

Rg = universal gas constant [1.987E-3 Kcal/deg-mole] 

Ea = Arrhenius activation energy [Kcal/mole] 

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 acid-catalyzed, base-catalyzed, and neutral hydrolysis rate constants can be combined (Mills

et al., 1981) to yield a composite first order hydrolysis rate in the dissolved phase:

where

81 = decay constant for dissolved phase [1/yr] 

[H+] = the hydrogen ion concentration [mole/l] 

[OH-

] = the hydroxyl ion concentration [mole/l] 

Note that [H+] and [OH-

] can be computed from the pH of the aquifer using 

[H+] = 10-pH (5.3) 

[OH-

] = 10-(14-pH) (5.4) 

For the case of sorbed phase hydrolysis, evidence suggests that base-neutralized hydrolysis can be

neglected and that the acid-neutralized hydrolysis rate is enhanced by a factor of ". Thus, the effective

sorbed phase decay rate can be expressed as:

where K" = acid-catalyzed hydrolysis rate enhancement factor for sorbed phase with a typical value of

10.0, and 82 = decay constant for the sorbed phase [1/yr]. Ka

T

, Kb

T

 and Ka

T

 are chemical-specific constants.
E:\Projects\EPA\R08-99.217.wpd 5-4

5.1.2 Reference Temperature 

The chemical-specific hydrolysis rates are specified for a constant reference temperature, the

default value of which is 25°C.

5.1.3 Normalized Distribution Coefficient 

The normalized distribution coefficient for organic carbon (koc) is used in conjunction with the

fractional organic carbon content to obtain the distribution coefficient (kd). The koc is a chemical-specific

variable which is input as a constant. The use of koc to estimate sorption is appropriate for organic

compounds which tend to sorb preferentially on the natural organic matter in the soil or aquifer.

5.1.4 Constituent Drinking Water Standard

Two additional parameters must be specified if a finite source simulation is being performed.

These are: (1) the applicable drinking water standard for each constituent in the waste, and (2) the

exposure averaging period used in the risk calculations for determining the drinking water standard. Usual

values of the latter parameter are 70 years (lifetime exposure) or 30 years (average residence time). Note

that the drinking water standard must be expressed in the same units used for the leaching concentration,

usually mg/L. Both these parameters are entered as constants. By default, the exposure period for

averaging the receptor well concentration is set to zero; in other words, the model calculates the peak

receptor well concentration.

5.2 METALS

The sorption behavior of metals is divided into two groups. Those with linear sorption behavior

and those with nonlinear sorption. The sorption characteristics of the first group is represented by a linear

adsorption isotherm coefficient (kd) which is a function of the pH in the unsaturated zone. The relationship

with the pH is described in the EPACMTP background document for Metals (EPA, 1996d). Metals that

belong to this group are: As, Sb, Cr+6, Se, and Tl. 

The sorption behavior of the second group is characterized by nonlinear sorption isotherms.

Metals in this group are: Ba2+, Cd2+, Be2+, Cr3+, Ni2+, Pb2+, Ag2t, Zn2+, V4+. The sorption isotherms

for these metals are calculated by MINTEQA2, a metal speciation model, and are provided to EPACMTP

in tabular form as a secondary input file. The sorption isotherm data account for the effect of varying

geochemical conditions in the soil and in the aquifer on the mobility of metal species by using different

effective sorption isotherms which depend on a number of environmental master variables. These

controlling master variables are listed in Table 5.2. For Monte Carlo analyses modeling, these parameters

are treated as random variables. Sorption isotherms data are available for various combination of master

variables varying from “low”, “medium”, or “high” values. This procedure is discussed in detail in the

metals background document (EPA, 1996b). Probability distributions for the master variables are

discussed below.

5.2.1 Soil and Aquifer pH

The pH distribution was obtained by analysis of nearly 25,000 field measured pH values obtained

from EPA’s STORET database. 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 (Table 5.3). The 0th and 100th percentile
E:\Projects\EPA\R08-99.217.wpd 5-5

(5.6)

values, determined from national distribution of pH, are lower and upper bounds of pH measurements.

This distribution was derived from a literature search for reported pH values of uncontaminated

groundwater. For modeling purposes it is assumed that the unsaturated zone and the saturated zone have

the same pH value.

5.2.2 Fraction Iron-Hydroxide Adsorbent

Amorphous iron hydroxides (FeOx) represents one of the dominant adsorbents for metal sorption.

Limited available data on iron hydroxide content is used to define a uniform distribution which results in

a low value of 0.0126 and a high value of 1.115 percent iron hydroxide by weight. The values are

obtained from 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.

5.2.3 Leachate Organic Matter

The model uses a uniform distribution for the concentration of anthropogenic dissolved organic

carbon (DOCa) in the leachate. The distribution has a low value of 0.001173 mg/L, and a high value of

0.00878 mg/L. The mixture of organic compounds used to represent the leachate-derived anthropogenic

dissolved organic carbon is based on analyses of leachate samples collected by the OSW in Florida, New

Jersey, Oregon, Texas, Utah, and Wisconsin (Loux et al., 1990). 

5.2.4 Natural Organic Matter

The distribution for the unsaturated zone natural organic matter varies with soil type, and is

specified as the percent organic matter. Conversely, the natural organic matter in the saturated zone is

specified as the fraction organic carbon (foc). The saturated zone fraction organic carbon has a Johnson

SB distribution with mean and standard deviation (in arithmetic space) of 4.32 10-4 and 0.0456,

respectively, and an upper bound of 0.0638. The percent organic matter and fraction organic carbon can

be converted to fraction of organic carbon using:

where the conversion factor of 174 is the reciprocal of the average mass fraction of carbon in organic

matter (Enfield et al, 1982).
E:\Projects\EPA\R08-99.217.wpd 5-6

Table 5.2 Metals-Specific Variable and Default Distribution Types.

Variable Units

Distribution

Code* Default Distribution

Metal Identification Number --- 0 Constant

Soil and aquifer pH 6 Empirical (Table 5.3)

Fraction Iron-Hydroxide

absorbent

Weight

fraction

4 Uniform

Leachate organic matter

content

mg/R 4 Uniform

Natural organic matter Weight

fraction

7 Johnson SB 

Fraction organic carbon Weight

fraction

7 Johnson SB

* See Table 3.1
E:\Projects\EPA\R08-99.217.wpd 5-7

Table 5.3 Probability distribution of soil and aquifer pH.

Cumulative Probability

(percent) pH Value

0.0

1.0

5.0

10.0

25.0

50.0

75.0

90.0

95.0

99.0

100.0

3.20

3.60

4.50

5.20

6.07

6.80

7.40

7.90

8.20

8.95

9.70
E:\Projects\EPA\R08-99.217.wpd

PART 3

SUBSURFACE FATE AND TRANSPORT SIMULATION
E:\Projects\EPA\R08-99.217.wpd 6-1

6.0 UNSATURATED ZONE SIMULATION

A schematic view of the one-dimensional system simulated by the unsaturated zone module is

provided in Figure 6.1. 

Details on the mathematical formulation and solution techniques of the unsaturated zone flow and

transport module are provided in the EPACMTP background document (EPA, 1996b). To guide the user

in evaluating appropriate fate and transport options to simulate the processes in the subsurface, a summary

of major assumptions is provided here:

• Flow of the fluid phase is isothermal and is governed by Darcy’s law.

• Flow is one-dimensional, vertically downward, and at steady-state.

• The fluid is slightly compressible and homogeneous.

• The dynamics of a second phase (e.g., air or nonaqueous liquid) can be disregarded.

The solutions for transient and steady-state transport in the unsaturated zone are based on the

following assumptions.

• The leachate concentration entering the soil is either constant (with a finite or infinite

duration) or decreasing with time following a first-order decay process.

• Sorption of contaminants onto the soil solid phase is described by a linear or nonlinear

(Freundlich) equilibrium isotherm.

In order to simulate flow and transport in the unsaturated zone between the base of the disposal

facility and water table, the following data are required:

• Thickness of the unsaturated zone (depth to water table from base of disposal unit).

• Soil hydraulic parameters. If these parameters are not available, but the soil type is

known, the parameter values from the database of Carsel and Parrish (1988) can be used.

These data are used for Monte Carlo simulations.

• The water flow rate (infiltration rate) through the disposal unit. This input can be

determined for landfills from the long term net percolation rate (precipitation minus runoff

minus evapotranspiration). For surface impoundments, it may be determined from the

depth of water ponding in the impoundment, and thickness and saturated conductivity of

the impoundment liner. The code can derive the infiltration rate from these parameters.

• Soil transport parameters. If not available, the dispersivity can be estimated from the

unsaturated zone thickness, and the retardation and decay coefficients can be estimated

from the soil bulk density, fraction of organic matter and chemical-specific properties.

Procedures for calculating these parameters are presented in the next five sections.
E:\Projects\EPA\R08-99.217.wpd 6-2

Figure 6.1 Cross-sectional view of the unsaturated zone considered by EPACMTP.
E:\Projects\EPA\R08-99.217.wpd 6-3

(6.1)

• The leachate concentration emanating from the base of the waste site. If a finite source

is being simulated, the duration of the pulse must be specified. It is derived for landfills.

• The number of component species and decay reaction stoichiometry, in the case of chain

decay reactions.

• Organic carbon partition coefficient (Koc) for organic chemicals and the effective partition

coefficient (kd), as a function of concentration, in the case of metals with nonlinear

sorption.

A list of unsaturated zone parameters is provided in Table 6.1.

6.1 THICKNESS OF THE UNSATURATED ZONE 

The unsaturated zone thickness, or depth to the water table for each waste site is obtained from the

regional hydrogeologic data base. Based on a site’s location, the corresponding hydrogeologic region is

selected. The unsaturated zone thickness is then selected randomly from data available for that

hydrogeologic region. The frequency distribution of unsaturated zone thickness is in Appendix B.

6.2 SOIL CHARACTERISTIC CURVE PARAMETERS 

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. Probability distributions for the parameters of this model were presented by Carsel and

Parrish (1988). The variables analyzed by Carsel and Parrish include saturated hydraulic conductivity (Ks),

residual water content (2r), saturated water content (2 s), and two empirical constants (" and $). The

statistical parameters presented by Carsel and Parrish (1988) for three soil types used by EPA for Monte

Carlo simulations are presented in Table 6.2. The frequency distribution of the saturated hydraulic

conductivity, residual water content, and van Genuchten soil parameters (" and $) are also presented in

Appendix B.

6.3 LONGITUDINAL DISPERSIVITY 

The longitudinal dispersivity of the soil can be input as a distribution or it may be derived. If

derived, it is computed as a linear function of the total depth of the unsaturated zone using 

where: 

Du = total depth of the unsaturated zone [m]

"Lu = longitudinal dispersivity [m]

Equation (6.1) is based on a regression analysis of data presented by Gelhar et al. (1985), which are

provided in Table 6.3. The correlation coefficient squared (R2

) of equation (6.1) is 66 percent.
E:\Projects\EPA\R08-99.217.wpd 6-4

Table 6.1 Unsaturated Zone Specific Variables and Default Distribution Types.

Variable Units

Distribution

Code* Default Distribution

SATK Saturated hydraulic

conductivity (Ks)

cm/hr 2 Lognormal (Depends on

soil type, Table 6.2)

ALPHA Moisture retention

parameter, "

cm-1 2 Lognormal

BETA Moisture retention

parameter ($)

7 Johnson SB

WCR Residual water content

(2r)

7 Johnson SB

WCS Saturated water content

(2s)

0 Constant for each soil

type

DSOIL Thickness of unsaturated

zone

m 99 Regional Site-based

DSPR Dispersivity (") m -1 Derived based on

regression analysis of data

by Gelhar et al.

POM Percent organic matter

(% OM)

7 Johnson SB

RHOB Bulk density (Db) g/cm3 0 Constant (1.65)

UFCOF Freundlich sorption

coefficient (K1)

cm3

/gr -1 Derived from % OM and

chemical-specific Koc

UFEXP Freundlich exponent (0) 0 Constant (1.0)

UCLAM Chemical degradation

rate coefficient (8cu)

1/yr -1 Derived from chemicalspecific hydrolysis

constants

BIOU Biological degradation

rate coefficient (8bu)

1/yr 0 Constant (0.0)

* See Table 3.1
E:\Projects\EPA\R08-99.217.wpd 6-5

Table 6.2 Statistical parameters for soil properties for three soil types (Carsel and Parrish, 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

2r

" cm-1

$

% OM

Db

2s

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

2r

" cm-1

$

% OM

Db

2s

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

2r

" cm-1

$

% OM

Db

2s

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
E:\Projects\EPA\R08-99.217.wpd 6-6

Table 6.3 Compilation of field dispersivity values (Gelhar et al. 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
E:\Projects\EPA\R08-99.217.wpd 6-7

(6.2)

6.4 FREUNDLICH SORPTION COEFFICIENT (DISTRIBUTION COEFFICIENT)

For organic compounds, the user must specify two isotherm parameters: the Freundlich sorption

coefficient and the Freundlich exponent. A special case occurs when the isotherm is linear. In this case,

the Freundlich exponent is 1.0. When the isotherm is linear, the leading Freundlich coefficient is known

as the solid-liquid phase distribution coefficient (kd). The distribution coefficient may be specified directly

or as a derived parameter. In the latter case, it is computed from the fraction organic carbon and the

organic carbon partition coefficient (koc), the latter of which must be given in the chemical-specific input

group. For metals, this input parameter is not used, instead the kd is calculated either as a function of pH,

or is provided in tabular form as a function of the concentration value (EPA, 1996c).

6.5 PERCENT ORGANIC MATTER

The soil bulk density and the organic matter content for the three soil types are included in Table

6.2 These values are based on the nationwide data base developed by Carsel and Parrish (1988). The

percent organic matter is converted by EPACMTP to fractional organic carbon content through the

following equation (Enfield et al., 1982): 

where: 

foc = fractional organic carbon content,

%OM = percent organic matter, and

174 = conversion factor.

Once the fractional organic carbon content is obtained, the linear distribution coefficient can be found

using: 

kd = koc foc (6.3)

where: 

kd = distribution coefficient [cm3

/g], and

koc = normalized organic carbon distribution coefficient [cm3

/g].

Note that equation (6.3) is based on the assumption that hydrophobic binding dominates the sorption

process (Karickhoff, 1985). The frequency distribution of percent organic matter in the soil is in

Appendix C.

6.6 FREUNDLICH ISOTHERM EXPONENT

For a nonlinear isotherm, the Freundlich exponent for each chemical species must be provided in

addition to the distribution coefficient. The nonlinear isotherm is currently handled within MINTEQA2

isotherm data. 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 the case of metal transport simulation, tabulated

values of kd versus concentration are read in from an external data file, and the Freundlich isotherm

parameters are not used. 
E:\Projects\EPA\R08-99.217.wpd 6-8

(6.4)

(6.5)

6.7 CHEMICAL AND BIOLOGICAL TRANSFORMATION COEFFICIENTS

EPACMTP accounts for biochemical transformation processes using a lumped first-order decay

coefficient. The overall decay coefficient is the sum of the chemical and biological transformation coefficients.

 

where

8u = overall decay coefficient (first-order transformation) (1/yr)

8cu = transformation coefficient due to chemical transformation (1/yr)

8bu = transformation coefficient due to biological transformation (1/yr)

The coefficients 8cu and 8bu are specified in the EPACMTP data input file, either as constants or as a

distribution. By default, 8bu is set to zero and 8cu is a derived parameter, in which case it is calculated from

the chemical-specific hydrolysis constants:

where

81 = hydrolysis constant for dissolved phase [1/yr],

82 = hydrolysis constant for sorbed phase [1/yr],

Db = bulk density of the porous media [g/cm3], and

N = porosity [cm3/cm3].

Note that 81 and 82 may be temperature and pH dependent. The values of temperature and pH for the

unsaturated zone are considered to be the same as those generated for the saturated zone (see Sections 7.10

and 7.11).
E:\Projects\EPA\R08-99.217.wpd 7-1

7.0 SATURATED-ZONE SIMULATION

The aquifer system simulated by the saturated-zone module of EPACMTP is depicted schematically

in Figure 7.1. Note that the system is assumed to be symmetric in the horizontal-transverse direction about

the plane y = 0; thus only one-half of the system along the positive y-axis is simulated by the model. The

vertical coordinate (z) is taken to be positive downward with z=0.0 at the water table. The shaded area

on top of the aquifer represents the area directly underneath the waste site. Contaminants entering the

water table are assumed to be distributed uniformly over this area.

Groundwater flow in the saturated zone is simulated using a steady-state solution for predicting

hydraulic head and Darcy velocities in a constant thickness groundwater system subject to infiltration and

recharge along the top of the aquifer and a regional (ambient) gradient defined by upstream and

downstream head boundary conditions. 

As illustrated in Figure 7.1, EPACMTP simulates a portion of the aquifer with length and width

xL and 1⁄2 yL, respectively. The modeled aquifer region encompasses the waste site as well as any specified

observation wells. The value of xL and yL are determined internally by EPACMTP, based upon specified

input parameters (disposal unit area, receptor well distance, dispersivity) of the simulated problem. The

xL and yL are determined to be large enough that boundary effects will be negligible. The boundary-head

values H1 and H2 are in turn determined from the regional hydraulic gradient, r, and the selected aquifer

length, xL:

H1 = rxL

(7.1)

H2 = 0

If necessary, the regional gradient is computed from the longitudinal saturated hydraulic conductivity, Kx,

and the regional ambient groundwater flow rate per unit area, q:

r = q/Kx (7.2)

The solution for groundwater flow is based on the following assumptions:

• The aquifer is homogeneous.

• Groundwater flow is steady.

• The saturated thickness of the aquifer remains constant and mounding is represented by

the head distribution on the top boundary.

• Flow is isothermal and governed by Darcy's law.

• The fluid is slightly compressible and homogeneous.
E:\Projects\EPA\R08-99.217.wpd 7-2

Figure 7.1 A schematic view of the groundwater system simulated by the saturated zone module of

EPACMTP. The shaded area represents the projection of the contaminant source area

onto the top of the aquifer.
E:\Projects\EPA\R08-99.217.wpd 7-3

In addition to modeling fully three-dimensional (3D) groundwater flow and contaminant fate and

transport, EPACMTP offers the option to perform an efficient 2D modeling approximation. When this

option is selected, the model ignores either the flow component in the horizontal-transverse (-y) direction,

or the flow component in the vertical (-z) direction. The appropriate 2D approximation is selected

automatically by the code, based on the relative magnitude of plume movement in the horizontal-transverse

versus the vertical direction. Details of this procedure are provided in the saturated zone background

document (EPA, 1996b).

The saturated zone transport module describes the advective-dispersive transport of dissolved

contaminants in a three-dimensional, constant thickness aquifer. The initial contaminant concentration is

set to zero. The concentration gradient along the downstream boundary is zero, and the lower aquifer

boundary is taken to be impermeable. A zero concentration condition is used for the upstream aquifer

boundary. Contaminants enter the saturated zone through a patch source of either constant concentration

or constant mass flux on the upper aquifer boundary. The source may be of finite or infinite duration.

Recharge of contaminant-free infiltration water occurs along the upper aquifer boundary outside the patch

source. Transport mechanisms considered are advection, dispersion, linear or nonlinear equilibrium

adsorption, and first-order decay with daughter product formation. As in the unsaturated zone, the

saturated zone transport module can simulate multi-species transport involving chained-decay reactions.

The saturated zone transport module of EPACMTP can perform either a fully three-dimensional transport

simulation, or provide a 2D approximation. The latter approach ignores advection in either the horizontal

transverse (-y) direction, or the vertical (-z) direction. In the course of a Monte Carlo simulation, the

appropriate 2D approximations are selected automatically for each individual Monte Carlo iteration.

The major simplifying assumptions used to simulate contaminant transport in the saturated zone

are:

• The flow field is at steady state.

• The aquifer is homogeneous and initially contaminant free.

• Adsorption onto the solid phase is described by a linear or nonlinear equilibrium isotherm.

• Chemical and/or biochemical degradation of the contaminant can be described as a firstorder process.

• For a multicomponent decay chain, the number of component species (parent and

daughters) does not exceed seven.

• The mass flux of contaminants through the source is either constant or controlled by firstorder decay, until all mass has been released from the source.

• The chemical is dilute and present in the aqueous and aquifer solid phases only.

EPACMTP variables for saturated zone are listed in Table 7.1. Some of these parameters can be

input directly or can be computed by the code using the relationships shown in subsequent sections. If

a multi-species simulation is desired, the chemical-dependent parameters (e.g. decay coefficient, Freundlich

parameters) must be repeated for each of the NSPECI components in the decay chain.
E:\Projects\EPA\R08-99.217.wpd 7-4

A number of the parameters are characterized by nationwide distributions. However, the key

hydrogeological parameters: hydraulic conductivity, hydraulic gradient, saturated thickness, and depth to

water table and groundwater temperature, are defined by regional distributions obtained from the API’s

Hydrogeologic Data base for Modeling (HGDB, Newell et al., 1990). The procedure for determining

these parameters is as follows: The HGDB contains data on depth to groundwater, hydraulic conductivity,

hydraulic gradient, and saturated thickness for approximately 400 hazardous waste sites nationwide. Each

site is also classified in terms of 12 hydrogeological regions, see Table 7.2. This classification is based

on the USGS groundwater resources classification (USGS, 1984). As a result, data are available for the

above mentioned key hydrogeological parameters for each of the 12 hydrogeological environments.

Based on the locations of each of the waste management units in the EPACMTP modeling database

(see source-specific parameters), the hydrogeologic environment for each unit was determined using USGS

state-by-state water resource maps (USGS, 1984). Note that EPACMTP uses a total 13 hydrogeological

environments (Table 7.2). The hydrogeological environment no. 13 is assigned to those waste sites for

which no specific hydrogeological environment could be identified from the state-by-state USGS

groundwater maps. The aquifer parameters for this 13th environment are the mean values from the entire

HGDB database. In other words, if a waste site is not classifiable in terms of the hydrogeological

environment, it is assigned nationwide average values for hydraulic conductivity, depth to groundwater,

saturated thickness and hydraulic gradient.

During each iteration of the Monte Carlo analysis, a waste unit is first selected at random (e.g.,

from the OPPI set of waste sites). This also determines the climatic and hydrogeologic environment and,

therefore, the distribution of the key hydrogeologic parameters. It should be noted that for each

hydrogeologic environment, the correlations between the hydrogeologic parameters (which represent

measurements taken at the same region) are preserved in the analysis. This is done by selecting the HGDB

parameters together. For instance, assume that for hydrogeologic environment A, there are 20 sets of

hydrogeologic parameters, i.e. combinations of unsaturated zone depth, hydraulic conductivity, hydraulic

gradient, and saturated thickness measured at 20 locations that fall in that hydrogeologic environment. The

aquifer parameter values used in each model run for waste sites located in hydrogeologic environment A

are assigned by randomly selecting one out of the 20 parameter combinations.

If data for one or more parameters in the selected set are missing, they are generated based on the

statistical correlations among the parameters for that hydrogeological environment. As a result, regional

differences in aquifer characteristics as well as dependencies between hydrogeological parameters are

automatically accounted for in the EPACMTP Monte Carlo analysis.
E:\Projects\EPA\R08-99.217.wpd 7-5

Table 7.1 Aquifer-Specific Variables and Default Distribution Types.

Variable Units

Distribution

Code* Default Distribution

Particle diameter (d) (cm) 6 Empirical (Table 6.12)

Porosity (N) -1 Derived from d

Bulk density (Db) g/cm3 -1 Derived from 

Aquifer thickness (B) m 99 Regional Site-based

Hydraulic conductivity (K) m/y 99 Regional Site-based

Hydraulic gradient (S) 99 Regional Site-based

Seepage velocity (V) m/y -1 Derived from K, S, N

Retardation factor (Rs) -1 Derived from kd, N, and Db

Longitudinal dispersivity ("L) m 8 Empirical (Table 6.14)

Transverse dispersivity ("T) m 8 Empirical 

Vertical dispersivity ("v) m 8 Empirical 

Temperature (T) °C 99 Regional Site-based (Figure

6.2)

pH 6 Empirical

Fractional organic carbon

content (foc)

7 Johnson - SB

Radial distance of observation

well

m 6 Empirical (Table)

Angle off-center 4 Uniform (0-90°) from

plume centerline

Depth of well below water table 4 Uniform (Fraction of

saturated zone thickness)

Decay coefficient (8u) 1/y -1 Derived from T, pH, Db, N

Leading Freundlich sorption

coefficient (kd)

cm3

/gr -1 Derived from koc, foc

Freundlich isotherm exponent

(0)

0 Constant (=1.0)

Diffusion coefficient m2

/y 0 Constant (=0.0)

Anisotropy ratio (Kx/Kz) 0 Constant (=1.0)

* See Table 3.1
E:\Projects\EPA\R08-99.217.wpd 7-6

Table 7.2 Regional Hydrogeologic Environments.

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 Floodplains with Overbank Deposits

River Valleys and Floodplains without Overbank Deposit

Outwash

Till and Till Over Outwash

Unconsolidated and Semiconsolidated Shallow Aquifers

Coastal Beaches

Solution Limestone

Others (unclassified Hydrogeological Environments)
E:\Projects\EPA\R08-99.217.wpd 7-7

(7.3)

(7.4)

7.1 PARTICLE DIAMETER

For Monte Carlo analyses, porosity and bulk density are determined from the mean particle

diameter. The mean particle diameter distribution is based on data compiled by Shea (1974). Shea (1974)

presents a frequency distribution of particle sizes based on analysis of 11,000 samples. These data have

been adopted for nationwide modeling purposes, using particle sizes ranging from a lower bound of 4×10-4

cm to an upper bound of 0.8 cm. The resulting empirical distribution is presented in Table 7.3. The

frequency distribution of particle diameter of the aquifer is provided in Appendix C.

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 an empirical relationship based on data reported by Davis (1969):

where: 

d = mean particle diameter [cm]

N = porosity [dimensionless]

7.2 POROSITY 

In the absence of a user-specified distribution for porosity, porosity can be calculated from the

particle diameter by rewriting (7.3):

where N and d are are defined in Section 7.1. 

This approximation yields the total porosity of the aquifer. For contaminant transport assessments,

it is more appropriate to use effective porosity, Ne, than total porosity. The effective porosity can be

significantly smaller than the total porosity, although an exact relationship cannot be established.

Mcworter and Sunada (1977) present data on total and effective porosity for a range of aquifer materials.

Their data were used to establish ranges for the ratio between effective and total porosity as a function of

grain size (Table 7.4). For Monte Carlo assessments, it is assumed that the actual ratio varies uniformly

between the upper and lower value for Ne/N in each particle-size class. For a given value of the mean

aquifer grain size, the total porosity can thus be converted into an effective porosity. Overall lower and

upper bounds of 0.05 and 0.50 are imposed on the effective porosity. It should be noted that EPACMTP

makes the conversion from total to effective porosity only if porosity is specified as a derived parameter

(porosity is calculated from grain size), which is the default option of the model. 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 distribution for either total porosity or effective porosity directly.
E:\Projects\EPA\R08-99.217.wpd 7-8

Table 7.3 Empirical distribution of mean particle diameter (based on Shea, 1974).

Particle Diameter (cm) Cumulative Probability

3.9 10-4

7.8 10-4

1.6 10-3

3.1 10-3

6.3 10-3

1.25 10-2

2.5 10-2

5.0 10-2

1.0 10-1

2.0 10-1

4.0 10-1

8.0 10-1

0.000

0.038

0.104

0.171

0.262

0.371

0.560

0.792

0.904

0.944

0.976

1.000
E:\Projects\EPA\R08-99.217.wpd 7-9

Table 7.4 Ratio between effective and total porosity as a function of particle diameter (after

McWorter and Sunada, 1977).

Mean Particle Diameter (cm) Ne/N 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
E:\Projects\EPA\R08-99.217.wpd 7-10

(7.5)

(7.6)

7.3 BULK DENSITY 

The aquifer bulk density directly influences the retardation of solutes and is related to aquifer

porosity. An exact relationship between porosity, particle density, and the bulk density can be derived

(Freeze and Cherry, 1979). Assuming the particle density to be 2.65 g/cm3

, this relationship can be

expressed as: 

where Db is the bulk density of the soil [g/cm3

]. 

7.4 AQUIFER THICKNESS

The aquifer saturated thickness is assigned as a regional site-based parameter. The frequency

distribution of aquifer thickness is shown in Appendix C.

7.5 HYDRAULIC CONDUCTIVITY

By default, the aquifer hydraulic conductivity is assigned as a regional site-based parameter using

the procedure outlined at the beginning of this section. The frequency distribution of aquifer hydraulic

conductivity is given in Appendix C.

Alternatively, the hydraulic conductivity can be specified as a derived parameter. In this case it

is calculated directly from the particle diameter using the Kozeny-Carman (Bear, 1979) equation

where:

K = the hydraulic conductivity [cm/s]

D = the density of water [kg/m3]

g = acceleration due to gravity [m/s2

]

: = the dynamic viscosity of water [N-s/m2]

d = particle diameter [m]

In Equation (7.6) 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). Note that the particle diameter, d, must be in units of

meters, as opposed to centimeters as used in equation (7.3).
E:\Projects\EPA\R08-99.217.wpd 7-11

(7.7)

(7.8)

7.6 HYDRAULIC GRADIENT 

The hydraulic gradient is assigned as a regional, site-based parameter using the procedure outlined

in the beginning of this section. The frequency distribution of the hydraulic gradient is provided in

Appendix C.

7.7 SEEPAGE VELOCITY

The seepage velocity is related to the aquifer properties through Darcy’s law. The regional seepage

velocity may be input directly or it may be a derived parameter (default). In the latter case, it is computed

as

where

vx = regional seepage velocity in x-direction [m/y]

Kx = hydraulic conductivity in x-direction [m/y]

r = regional hydraulic gradient [m/m]

Ne = effective porosity [dimensionless]

Default lower and upper bounds for the seepage velocity are 0.1 and 1.1×104

 m/y, respectively. The

range of seepage velocity values is based on survey data reported by Newell et al (1990).

7.8 RETARDATION FACTOR

The retardation factor is defined for a linear adsorption isotherm by 

where

Db = bulk density of the porous media [g/cm3]

kd = distribution coefficient [cm3

/g]

N = porosity

When the sorption isotherm is nonlinear, R is no longer constant but depends on concentration (see

Section 2.0). In this case, R must be given as a derived variable and the kd-concentration relation must

be specified by the user in terms of two Freundlich coefficients.

For the modeling of metals, a linear sorption isotherm is used for the saturated zone. The effective

kd value is determined from the maximum contaminant concentration at the water table and values of the

four environmental master variables (pH, iron-oxide, leachate organic matter, and natural organic matter

in the aquifer), following the procedure described in the metals background document (EPA, 1996b).
E:\Projects\EPA\R08-99.217.wpd 7-12

(7.9)

(7.10)

7.9 DISPERSION COEFFICIENTS

The spreading and dilution of the contaminant plume in the saturated zone is controlled by two

mechanisms: advection and dispersion. EPACMTP allows for non-uniform groundwater flow due to

vertical recharge and infiltration from the waste site. The model simulates actual spreading mechanisms

occurring in the field. For non-degrading contaminants, the dilution caused by dispersive mixing is a

controlling factor in determining the concentration observed at a receptor well. Somewhat surprisingly

therefore is the fact, that in Monte Carlo analyses, transport is a 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, 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.

The model computes the longitudinal, lateral, 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 et al., 1992).

In the absence of user-specified values or distributions, the default model distribution is utilized

if the distribution type of dispersivities is set equal to 8, which represents a probabilistic formulation for

the longitudinal dispersivity as shown in Table 7.5 [Gelhar, 1986, Personal communication]. Within each

of the three classes, the longitudinal dispersivity is assumed to be uniform. Note that the values of

longitudinal dispersivity in Table 7.5 are based on a receptor well distance of 152.4 m. For distances other

than 152.4 m, the following equation is used:

where xt

 is the average horizontal travel distance defined as

In other words, the travel distance xt

 is equal to the distance of the receptor well (xr) from the

downgradient facility boundary, 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 minimum value of "L is 0.01 m. The input mean value for "T and "V is the ratio of "L

to "T and/or "V. Hence, the desired dispersivity is computed as the longitudinal dispersivity divided by

the user-specified mean value. The values assigned to "T and "V are based on the relationship with "L.

This option allows the user to define different values for the ratios of the longitudinal to the vertical and/or

transverse dispersivities. By default, the following ratios are used: "L/"T = 8 and "L/"V = 160. The

frequency distribution of the aquifer longitudinal dispersivity is provided in Appendix C.
E:\Projects\EPA\R08-99.217.wpd 7-13

Table 7.5 Probabilistic representation of longitudinal dispersivity.

Cumulative Probability "L (m)*

0.0

0.1

0.7

1.0

0.1

1.0

10.0

100.0

*Assumes xt

 = 152.4 m (see eq. 7.9)
E:\Projects\EPA\R08-99.217.wpd 7-14

The relationship in equation (7.9) has been derived based on an informal 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. These studies represent a wide range of spatial scales,

from a few meters to over ten-thousand meters. The data as presented by Gelhar et al. (1992) show a clear

correlation between scale and apparent dispersivity. The relationship (7.9) used in EPACMTP describes

the observed data reasonably well. The field data suggest a somewhat steeper slope of the distancedispersivity relation on a log-log scale than is used in the modeling analyses. 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

(7.9) 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.

7.10 TEMPERATURE

Groundwater temperature is assigned as a regional parameter based on the location of the waste

management unit. For each waste site, the assigned temperature is obtained from averaging the upper and

lower temperatures within a region as shown in Figure 7.2.

7.11 GROUNDWATER pH

A nationwide groundwater pH distribution was derived from EPA’s STORET data base. The

model assumes that the groundwater 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 (Table 5.3)

with a median value of 6.8 and lower and upper bounds of 3.2 and 9.7, respectively.

7.12 FRACTIONAL ORGANIC CARBON CONTENT

The organic carbon content, foc, is used to determine the linear distribution coefficient, kd. This

approach is valid for organic contaminants containing hydrophobic groups. These chemicals will tend to

sorb preferentially on non-polar natural organic compounds in the soil or aquifer. Unfortunately, few if

any comprehensive subsurface characterizations of organic carbon content exist. In general, the reported

values are low, typically less than 0.01. A low range for foc was assumed and the distribution shape was

based on the distribution of measured dissolved organic carbon recorded as entries to 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 (EPA, 1996d).

7.13 RECEPTOR WELL LOCATION

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

groundwater is measured. A receptor well can be located 1) anywhere downgradient of the waste

management unit, 2) within the areal extent of the contaminant plume, and/or 3) only along the

contaminant plume centerline. The receptor well depth can be positioned anywhere within the saturated

zone. The user specifies the receptor well location by assigning the following:
E:\Projects\EPA\R08-99.217.wpd 7-15

Figure 7.2 Groundwater temperature distribution for shallow aquifers in the United States. (After

Collins, 1925)
E:\Projects\EPA\R08-99.217.wpd 7-16

(7.11)

(7.12)

(7.13)

x, distance from the waste unit

y, distance from the plume centerline

z, well depth within the saturated zone

By default, the y-location of the receptor well is allowed to be anywhere downgradient from the waste

source, i.e, the angle off-center varies between 0 and 90 degrees.

In a Monte Carlo simulation, the primary output from the model is the exposure concentration at

receptor well located down gradient from the waste site, within a one-mile distance from the site.

Available studies and surveys suggest that on average, multiple down-gradient wells are present within this

one-mile distance. To ensure a degree of conservatism in the modeling analysis, the model computes the

concentration at the nearest down gradient well. Information on the downstream distance to the nearest

receptor well can be obtained from the OSW landfill survey (EPA, 1993). The data are presented as an

empirical distribution in Table 7.6. At most waste sites included in this survey, the direction of ambient

groundwater flow was in most cases not known exactly; it can therefore not be ascertained that 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 groundwater flow, the modeled well

is allowed to be positioned at a variable y-distance from the plume centerline. EPACMTP incorporates

two options for determining the x- and y-coordinates of the receptor well.

The first, and default, option involves determining the x- and y-coordinates of the receptor well

as a function of the radial distance, R, to the edge of the waste unit, and the angle off-center, 2, as depicted

in Figure 7.3a. In this case the x- and y-coordinate values must be specified as derived variables and are

computed as

where

R = radial distance between waste unit and well (m),

2 = angle measured counter-clockwise from the plume

centerline (degrees)

 xr, yr = Cartesian coordinates of the receptor well (m)

To include all wells located downstream of the waste units, the angle 2 is taken to be uniformly

distributed between 0 and 90°. R is determined using the empirical distribution shown in Table 6.15.

Optionally, the y-coordinate of the well can be constrained to lie within the areal extent of the main

contaminant plume as defined by

where

y0 = half-width of the waste unit in the y-direction (m)

xw = length of the waste unit in the x-direction (m)

"T = horizontal transverse dispersivity (m)
E:\Projects\EPA\R08-99.217.wpd 7-17

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 Gaussion

profile of the plume cross-section. Use of (7.13) implies that 99.7% of the contaminant mass will be

present inside the transverse plume limit.

The shaded area in Figure 7.3a indicates the area occupied by the contaminant plume. The option

to force the well location to lie within the areal plume boundaries is selected in EPACMTP by setting the

logical control parameter LYCHK = TRUE in group GP02 of the data input file.

The second method imbedded in EPACMTP to determine the receptor well location is to generate

a well position directly so that the well is located uniformly between the plume centerline and the areal

plume boundary, for any given x-distance (Figure 7.3b). With this option, a x-distance is generated from

the empirical distribution in Table 7.6. Next, the y-coordinate of the well is generated from a uniform

distribution with a minimum value of zero, and a maximum value given by Equation (7.13). To select this

option, the parameter LYCHK should be set to TRUE, the receptor well x-distance should be specified as

an empirical parameter with values as given in Table 7.6, and the receptor well y-distance should be given

as a uniform distribution. The frequency distributions of radial distance to the well and its off-center angle

are provided in Appendix C.

Several options are available for specifying the vertical position of the well intake point below the

water table. The first, and default, option is to model the vertical position of the well 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.

In the second option, data on the depth of receptor wells obtained from Agency surveys, can be

used directly in the model as an empirical distribution. The data values range from 15 ft (4.5 m) to 301

ft (90.9 m). Table 7.7 shows the distribution of well depths and the corresponding cumulative probability

values. 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.
E:\Projects\EPA\R08-99.217.wpd 7-18

Table 7.6 Cumulative probability of distance to nearest receptor well for landfills (from EPA,

1993d).

Cumulative Probability Distance (R) (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
E:\Projects\EPA\R08-99.217.wpd 7-19

Figure 7.3 Schematic plan view showing procedure for determining the downstream location of the

receptor well: (a) well location determined using radial distance, R, and angle off center

2; and (b) well location generated uniformly within plume limit.
E:\Projects\EPA\R08-99.217.wpd 7-20

Table 7.7 Cumulative probability distribution of receptor well depth.

Depth (m) Cumulative Probability

4.55

4.55

6.06

6.06

9.09

9.09

10.61

10.61

12.12

12.12

15.15

20.61

21.21

21.21

22.73

22.73

24.24

24.24

27.27

27.27

30.30

30.30

39.39

39.39

45.45

45.45

60.61

60.61

71.21

75.76

75.76

90.91

0.000

0.015

0.045

0.060

0.090

0.134

0.149

0.179

0.194

0.209

0.254

0.299

0.313

0.328

0.358

0.373

0.388

0.403

0.433

0.478

0.493

0.597

0.642

0.657

0.672

0.746

0.761

0.881

0.925

0.955

0.970

1.000
E:\Projects\EPA\R08-99.217.wpd 7-21

(7.14)

(7.15)

For both these options, 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-coordinate of the receptor well is constrained

to lie within the approximate vertical extent of the contaminant plume as defined by

where

Q1-Q4 = Components of the groundwater flow field (m2

/yr), see EPA (1996a), Part 2

Figure 2.3

B = Saturated zone thickness (m)

xw = Length of source in downstream direction (m)

xr = Horizontal distance between source and receptor well (m)

"L = Longitudinal dispersivity (m)

"v = Vertical dispersivity (m)

Do = Molecular diffusion coefficient (m2

/y)

Finally, the well position may be fixed at a constant depth. In this case a distribution code of 12

(not 0) should be entered for the vertical well position in the data input file.

7.14 CHEMICAL & BIOLOGICAL TRANSFORMATION COEFFICIENTS

The overall decay coefficient or the sum of the chemical and biological transformation coefficients

can be expressed as a distribution or a constant value. The saturated zone derivation of the overall decay

is calculated the same way as for the unsaturated zone (see Section 6.7). Although the temperature and

pH values are assumed not to vary between the saturated and unsaturated zones, the porosity and bulk

density values may differ, leading to a difference in the decay coefficients for the two zones. Note that

the biological transformation coefficient has a default value of zero and has not been used in any EPA

application to date.

7.15 FREUNDLICH ISOTHERM COEFFICIENT 

When the adsorption isotherm is nonlinear, the user must specify two isotherm parameters: the

Freundlich sorption coefficient and the Freundlich exponent (see next sub-section). A special case occurs

when the isotherm is linear. In this case, the Freundlich exponent has a value of 1.0. When the isotherm

is linear, the leading Freundlich coefficient is known as the solid-liquid phase distribution coefficient (kd).

The distribution coefficient may be specified directly, or as a derived parameter. In the latter case, it is

computed from the fraction organic carbon and the organic carbon partition coefficient. The following

relationship is used:
E:\Projects\EPA\R08-99.217.wpd 7-22

where: 

kd = distribution coefficient [cm3

/g],

koc = distribution coefficient with respect to organic carbon [cm3

/g], and

foc = fraction organic carbon.

Note: The above does not apply to simulations of metals transport. In this case, the sorption isotherm

is determined according to the setting of the input parameter KDEVAL. A detailed discussion of

metals modeling is provided in EPA (1996c).

7.16 FREUNDLICH ISOTHERM EXPONENT

When a nonlinear adsorption isotherm is used, the Freundlich exponent for each chemical species

must be given. No probability distribution data are currently available for this parameter. If the

Freundlich exponent is omitted from the data file, it is assigned a default value of 1.0. which is equivalent

to specifying a linear sorption isotherm.

7.17 DIFFUSION COEFFICIENT

The diffusion coefficient is set to a constant value of zero by default, but a distribution may be

specified if desired. 

7.18 ANISOTROPY

An anisotropy factor is used by the Monte Carlo module if the horizontal and vertical aquifer

hydraulic conductivities are different. The relationship between horizontal and vertical conductivities is:

Kz = Kx/Ar

where:

Kz = hydraulic conductivity in z direction [m/y], 

Kx = hydraulic conductivity in x direction [m/y], and

Ar = anisotropy ratio = Kx/Kz .

The default value of Ar is 1, which indicates an isotropic system. 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 1-100 may be reasonable. In EPACMTP, the horizontal transverse

hydraulic conductivity is always set equal to the horizontal longitudinal conductivity, i.e., Ky=Kx.
PART 4

OUTPUT INTERPRETATION
E:\Projects\EPA\R08-99.217.wpd 8-1

8.0 RECEPTOR WELL CONCENTRATIONS

The output of any EPACMTP run consists of predicted concentration levels, either at the water

table (output from the unsaturated zone module) and/or at a receptor well(s) in the saturated zone (output

from the saturated zone module). The methodology (deterministic or Monte Carlo) and application

(continuous or finite source) determines the method of processing predicted concentration levels for a

specific objective. The post-processing of these output results is dependent on a number of factors which

are outlined and discussed in this section.

8.1 DETERMINISTIC MODE

In the deterministic mode, EPACMTP variables are assigned constant values and the model

computes receptor well concentration which, along with the source concentration, may be used to compute

a Dilution Attenuation Factor (DAF). The DAF is defined as the ratio of source concentration to receptor

well concentration. For chemicals with linear adsorption, the model may be run using a source

concentration value of one, so that the DAF is just the inverse of the receptor well concentration value.

When a deterministic simulation is performed, the final output is single receptor concentration and

generally does not require additional post processing.

8.2 MONTE CARLO MODE

When EPACMTP is used in the Monte Carlo mode, the primary output from the simulation model

is a sequence of receptor well concentration values, where each concentration corresponds to the result of

one model simulation. The Monte Carlo output is then analyzed to derive regulatory DAF values or

regulatory limits on leachate and waste concentrations. Each Monte Carlo iteration yields one DAF value

for the constituent of concern (plus one DAF value for each of the transformation products, if the

constituent degrades to form daughter product). Since each Monte Carlo iteration has equal probability,

ordering the DAF values from low to high directly yields the DAF cumulative probability distribution

(CDF). If appropriate, CDF curves representing different regional distributions may be combined into a

single, weighted curve that represents all regions. (See Part 3, Section 2.2 in the EPACMTP background

document for further discussion, EPA 1996b.)

For a finite source scenario, the post-processing step involves determination of the paired values

of leachate concentration, CL, and total leachable waste concentration, Cw, which satisfy a specified

protection level. The procedure is described in the finite source background document (EPA, 1996b). To

facilitate the post-processing analysis of Monte Carlo simulations, a separate post-processing program

(POSTCMTP) is distributed with the EPACMTP code and discussed in Section A.5 of Appendix A.

Several types of output files are generated when the Monte Carlo option is used. The name of the

primary output file (OUTPUT.OUT) is interactively specified by the user. This file consists of two major

segments: 

(1) An echo of the input data

(2) Statistical parameters of the steady-state concentration at the receptor well (e.g., mean,

median, standard deviation, selected percentiles, etc.). 

This file is the one of primary interest to the user. 
E:\Projects\EPA\R08-99.217.wpd 8-2

The second type of output file is named {OUTPUT}.CDF where {OUTPUT} is the user-specified

primary output file name. This file contains a list of concentration values, sorted in ascending order, and

the corresponding cumulative probability values. For steady-state, continuous source analyses this output

file can be directly converted to the CDF of DAF values.

 For finite source simulations the primary output required for determining leachate and waste

concentration limits is contained in the {OUTPUT}n.SAT files. These files contain the Monte Carlo output

of receptor well concentrations of each of the n different ratios of Cw/CL that were analyzed. In other

words, EPACMTP will generate {OUTPUT}1.SAT, {OUTPUT}2.SAT, etc., corresponding to the 1st,

2nd, etc. different ratio of Cw/CL for which EPACMTP has computed the receptor well concentration

values. For a degrading contaminant, these files contain the receptor well concentrations of the parent

compound, plus all daughter products.

The third type of Monte Carlo output file is named {OUTPUT}.BND. This optional output file

contains the random variable identification code, the random variable value, and the upper and lower

bounds specified for that random variable, if the random variable is generated out of bounds in either of

the two subroutines RANGEN or ASSIGN. Subroutine RANGEN generates random numbers from

specified probability distributions, and subroutine ASSIGN computes random variables which are derived

from other random variables and constants. The {OUTPUT}.BND file is useful when a large number of

generated and/or derived random variables occurred out of bounds, and the user wishes to see which

variables these were. Note that bounds checking on the generated random variables will only be performed

if the logical variables CHECK and LDRIV are set to TRUE in the Monte Carlo input file. Therefore,

the {OUTPUT}.BND file will be empty if: (1) CHECK and LDRIV are set to FALSE, or (2) no random

or derived variables are generated out of their specified bounds. 

The fourth Monte Carlo output file type consists of files which contain the randomly generated

values used for each Monte Carlo run. There are five of these optional files, and their names and contents

are listed in Table 8.1, along with brief descriptions of the other Monte Carlo output files.

When the Monte Carlo option is used and the number of runs is greater than one, most of the

EPACMTP formatted output is suppressed to limit file size and disk storage requirements to reasonable

levels. However, data read from the EPACMTP input file is always echoed to the formatted output file.

8.2.1 Model Output Processing

POSTCMTP is an interactive, menu-driven postprocessor for EPACMTP. It reads in the

EPACMTP Monte Carlo output files, presents the results in graphical and tabular form on the screen, and

provides the option to generate hard copy output on a wide variety of printers and plotters. Details on how

to use EPACMTP postprocessor are presented in Section A.5.1, Appendix A.
E:\Projects\EPA\R08-99.217.wpd 8-3

Table 8.1 Monte Carlo output files.

Opened in Unit No. Name Description

MAIN 6 User-specified Echo of EPACMTP input, statistical

parameters of receptor well

concentration.

MAIN 8 {OUTPUT}.CDF1) Downgradient steady-state well

concentrations sorted in ascending

order and corresponding cumulative

probability. (CDF of

concentrations)

MAIN 13-40 {OUTPUT}n.SAT1) Downgradient receptor well

concentrations corresponding to the

n-th value of Cw/CL for finite source

scenario.

MAIN 7 {OUTPUT}.BND1) Randomly generated or derived

variables which were out of bounds.

MAIN 12 {OUTPUT}.CVR1) Values of chemical variables

generated for Monte Carlo

simulations.

MAIN 11 {OUTPUT}.SVR1) Values of source variables generated

for Monte Carlo simulations.

MAIN 13 {OUTPUT}.UVR1) Values of unsaturated zone flow and

transport variables generated for

Monte Carlo simulations.

MAIN 14 {OUTPUT}.AVR1) Values of aquifer variables

generated for Monte Carlo

simulations.

1) {OUTPUT} represents the file name of the primary output file. The same file name is used, but

with a different file extension to indicate the type of ancillary output file.
E:\Projects\EPA\R08-99.217.wpd R-1

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van Genuchten, M.Th., 1980. A closed form equation for predicting the hydraulic conductivity of

unsaturated soils. Soil Sci. Soc. Am. J., 44:892-898.
E:\Projects\EPA\R08-99.217.wpd R-3

Wolfe, N.L., 1985. Screening of hydrolytic reactivity of OSW chemicals. US EPA Athens

Environmental Research Laboratory, Athens, GA.
E:\Projects\EPA\R08-99.217.wpd A-1

APPENDIX A

SIMULATION USING EPACMTP: DATA INPUT GUIDE

A.1 GENERAL

Using EPACMTP to perform a fate and transport simulation involves the following three general

steps: 

1. Create input data file(s)

2. Execute EPACMTP

3. Perform post-processing output analysis

All information needed by EPACMTP to perform a simulation is read from the data input file,

which is an ASCII text file. The data input file can be created using a standard ASCII text editor (Section

A.2). Execution of EPACMTP is discussed in Section 7.3 and post-processing analysis is discussed in

Section A.5.

A.2 INPUT FILE PREPARATION

Detailed format descriptions of EPACMTP data files are provided in Section A.2.1. These format

instructions should be followed when using a text editor to create or change an EPACMTP data input file.

A.2.1 Data Input Formats

This section describes the format of data input files for EPACMTP. The data input file consists

of a collection of records (a record corresponds to one line of information in the data file). There are two

basic types of records. The first type of record is the data record. These records must follow in a

specified order and each record must conform to a prescribed format. There are various different types

of data records, each of which is distinguished by a two-character code described below. The second type

of record is the comment record. Comment records are not used by EPACMTP; their purpose is to

elucidate the meaning of the data records to the user and improve readability of the data file to the user.

Comment records may be interspersed freely with data records.

Each record type is identified by a two-character code in the left-most 5 columns of the record.

The following codes are used:
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Data —

Records

*

*

*

*

*

*

*

*

*

*

*

TI - Title records

GP - General parameter records

DC - Decay Chain data records

OT - Observation Time data records

SS - Source Specific data records

FS - Finite Source Specific data records

CS - Chemical Specific data records

MT - Metals Specific data records

US - Unsaturated Zone Specific data records

AS - Aquifer Specific data records

** - Comment records

Every record in the input file must be identified by one of the above codes. Data record groups

must also be entered in the same sequential order in which they are listed above.

The formats of the data record groups are described below. In order to become familiar with the

input formats, it is recommended that the user also study the example data files listed at the end of this

manual. 

A.2.1.1 Problem Title Records

No. of Records: As many as desired

Record Format: A5, A75

Col. Variable

1-5 GRPCOD Record identifier must be ‘TI’ always

6-80 TITLE Descriptive title for problem

A.2.1.2 General Parameter Records

Record No. GP01: Control Parameters

Format: A5, L5, 5I5, 2L5, I5

Col. Variable

 1-5 GRPCOD Record identifier; must be ‘GP’ always

 6-10 MC Monte Carlo control parameter

= F(alse) for deterministic run

= T(rue) for Monte Carlo run (Default).
E:\Projects\EPA\R08-99.217.wpd A-3

11-15 IVADOS Control parameter for unsaturated zone

simulation.

= 0 if no unsaturated zone modeling is

 required,

= 1 if unsaturated zone modeling is

 required (Default).

16-20 ISTMOD Control parameter for saturated zone 

simulation.

= 0 if no saturated zone modeling is 

 required,

= 1 if saturated zone modeling is

 required (Default).

21-25 NSPECI Number of contaminant component species in the system.

Default = 1.

26-30 KFDM Simulation method

= 0, finite element

= 1, finite difference

31-35 KFS Control parameter for selecting continuous (infinite) source or

finite source modeling option

= 0 for continuous source option

= 2 for landfill finite source option.

36-40 FULL3D Logical control parameter for selecting fully 3D or quasi-3D

saturate zone modeling option

= T(rue) for fully 3D simulation

= F(alse) for quasi-3D simulation

Note: FULL3D = F(alse) should be used for Monte Carlo

simulations

41-45 METAL Logical control parameter for metals simulation

= T(rue) for metals modeling

= F(alse) for non-metals modeling

46-50 KDEVAL Integer control parameter for selecting the scheme for

determining the metals sorption isotherm (Leave blank if METAL

= FALSE)

= 1 Use the method of Loux for calculating kd from pH

= 2 Use linearized MINTEQA2 isotherm

= 3 Use nonlinear MINTEQA2 isotherm
E:\Projects\EPA\R08-99.217.wpd A-4

51-55 LTCHK Logical variable to check minimum transmissivity

= F (alse) if no

= T (rue) if yes (default)

56-60 IFREGNL Logical variable for Regional Site-based Analysis

= F (alse) for Nationwide Analysis

= T (rue) if yes (default)

61-65 ISRC_TYP Control parameter for selecting the type of waste source

= 0 for landfill

= 1 for surface impoundment

= 2 for waste pile

= 3 for land treatment

Notes:

1) MC is a logical variable: it should be set to either ‘F’ or ‘T’ (right-justified in input field).

2) The maximum number of component species that the code can handle is seven (NSPECI=7). 

3) The default option FULL3D=FALSE reduces CPU time and memory requirements of the

EPACMTP code.

4) Finite source option A (KFS=0) selects the methodology developed for EPACML (see EPA,

1993).

Finite source option B (KFS=1) selects the methodology developed for EPACMTP (see EPA,

1992: Background document for EPACMTP: Finite Source Methodology for degrading chemicals

with transformation products).

5) The different options for metals modeling are documented and explained in the metals background

document for EPACMTP (EPA, 1996d).

6) If IFREGNL = True option is selected, regional site-based parameters must be supplied in a Input

data file. The records in the data file are arranged under the following codes:

DP contains information on number of sites, climatic and groundwater regions.

SP Contains site areas, depths, groundwater temperature and their corresponding site-climatic

regions, groundwater regions and weights

IN Infiltration rates for different soil types for different climatic regions

RE Recharge rates for different soil types for different climatic region

HG Groundwater hydrological parameters, hydraulic gradient, unsaturated and saturated zone

thickness and aquifer hydraulic conductivity
E:\Projects\EPA\R08-99.217.wpd A-5

Sample data file listing is provided in Appendix A.

Record No. GP02: Monte Carlo Control Parameters

 *** Omit this record for a deterministic *** 

 model run (MC = F(alse))

Format: A5, I5, 7L5, F10.0

Col. Variable

 1-5 GRPCOD Record identifier; must be ‘GP’ always

 6-10 NRUN Number of iterations in Monte Carlo run.

Recommended value is 1000 or greater.

11-15 ECHO Logical variable for creating output ‘VR’ files.

= F(alse) if no; VR files should not be

 created (Default),

= T(rue) if yes; VR files should be created.

16-20 CHECK Logical variable indicating if generated

random variables are restricted to lie

within specified upper and lower bounds,

= F(alse) if no,

= T(rue) if yes (Default).

21-25 CORR Logical variable indicating if

statistical correlation is to be used in

generating unsaturated zone parameters,

= F(alse) if no (Default),

= T(rue) if yes.

26-30 LDRIV Logical variable indicating if derived

Monte Carlo variables are constrained to

lie within specified upper and lower bounds,

= F(alse) if no (Default),

= T(rue) if yes. 

31-35 LYCHK Logical variable indicating if observation

well is constrained to lie within

 the approximate areal extent of the plume,

= F(alse) if no,

= T(rue) if yes (Default).
E:\Projects\EPA\R08-99.217.wpd A-6

36-40 LZCHK Logical variable indicating if

observation well depth is constrained to

lie within the approximate vertical

plume depth.

= F(alse) if no (Default),

= T(rue) if yes.

41-45 LBNDOT Logical variable indicating if the ‘.BND’ output file is to be

created,

= F(alse) if no (Default), 

= T(rue) if yes.

46-50 ALLRUN Logical control parameter to set aggregation option

= T(rue) to automatically aggregate Monte Carlo results over

all soil and cover types

= F(alse) to perform run only for the selected soil and cover

type.

51-60 TCUTOFF Value of the upper time limit, in years, for determining the

receptor well maximum concentration in finite source modeling.

Notes:

1) If the ALLRUN = True option is selected, silt-loam infiltration rate and recharge rate values in

the source-specific group must be used. The soil parameters in the unsaturated zone specific group

must also be set to the values for the silt loam soil type. ALLRUN is not used if the regional sitebased analysis is selected (IFREGNL=True).

2) The option to incorporate statistical correlation while generating unsaturated zone parameters

(CORR = (T)rue) has not been implemented in this version of EPACMTP; hence, always set

CORR = (F)alse.
E:\Projects\EPA\R08-99.217.wpd A-7

Record No. GP03: Deterministic Control Parameters

*** Omit this record if a Monte Carlo simulation ***

is performed with continuous source condition 

(MC=T(rue) and KFS=0)

Format: A5, 7I5, G10.0, 2I5

Col. Variable

 1-5 GRPCOD Record identifier; must be ‘GP’ always.

 6-10 ISBC Contaminant source boundary condition

= 0 if contaminant flux is given (Default),

= 1 if contaminant concentration is

 given.

11-15 IBAT Control parameter for decaying source boundary condition,

= 0 if no (continuous source or non-degrader infinite source)

= 1 Biochemical decay (hydrolysis)

= 2 Physical decay due to leaching (source depletion)

= 3 Combine 1+2

(IBAT >=1 for degrader finite sources)

Note: If IBAT = 1 or 3 is selected, it is assumed that the

effective hydrolysis transformation coefficients in the waste

source are the same as in the unsaturated and saturated zone.

16-20 IUSTED Control parameter indicating whether transport in the unsaturated

zone is steady-state or transient,

= 0 for transient (if KFS=1 or 2),

= 1 for steady-state (if KFS=0).

Leave blank if IVADOS (see record GP01)=0.

21-25 ISSTED Control parameter indicating whether transport in the saturated

zone is steady-state or transient

= 0 for transient (if KFS=1 or 2)

= 1 for steady-state (if KFS=0).

Leave blank if ISTMOD (see record GP01) = 0.

26-30 NUTOBS Number of time values at which concentration at the water table

is to be computed

Leave blank if ISTMOD = 1, and/or IUSTED=1, and/or

MC=T(rue).

31-35 NTS Number of time values at which receptor well concentrations in

the saturated zone are to be computed

Leave blank if ISTMOD=0, or ISSTED=1.
E:\Projects\EPA\R08-99.217.wpd A-8

Note: Set NTS = -1 or 0 to run finite source option in MonteCarlo mode.

36-40 NWELLS Number of receptor wells in the saturated zone.

Leave blank if ISTMOD (see record GP01) = 0.

41-45 QRMAX Maximum groundwater vertical flux ratio (see Eq. 2.3.34) for

selecting between analytical and numerical saturated zone

contaminant transport solution. Recommended value is 0.02. 

Leave blank if ISTMOD (see record GP01) = 0.

51-55 NRATIO Number of ratios of CW/CL to be used for finite source scenario

(KFS=2). Default value is 8.

Leave blank for a continuous source analysis (KFS=0) or a finite

source analysis with a constant source leaching duration.

56-60 ICRW Control parameter indicating the time-dependent receptor well

concentration to be computed for the finite source analysis

= 0 compute peak receptor well concentration (Default)

= 1 compute temporally averaged receptor well concentration

When ICRW=1 is used, the averaging period for each of the

species must be specified in variable CARC, in the chemicalspecific data records. The default period is 70 years.

Notes:

1) The maximum value for NUTOBS is 20. NUTOBS is automatically set to 0 if a steadystate simulation is performed (IUSTED=1).

2) The maximum value for NTS is 60. NTS is automatically set to 1 if a steady-state

simulation is performed (ISSTED=1).

3) The maximum value for NWELLS is 40.

4) The maximum value for NRATIO is 9.

A.2.1.3 Finite Source Data Records

When the finite source option is selected, with KFS=2 (see record FP01), the following additional data

record group is required. The finite group is indicated by the record identifier “FS”. The record group

contains the values of the ratios CW/CL that are to be used in the analysis.

Format: A5,8G10.0

Col. Variable

 1-5 GRPCOD Record identifier; must be “FS” always.
E:\Projects\EPA\R08-99.217.wpd A-9

 6-15, CRATIO(1) Sequential values (in increasing order) of the ratios CW/CL to be

 16-25 " used in the finite source Monte Carlo analysis.

 " "

 " "

 etc. CRATIO

(NRATIO)

Note: Up to 8 values can be entered on one line; if the value of NRATIO is greater than 8, the data

record should be repeated, but without the group code.

A.2.1.4 Chain Decay Data Records (DC)

 ******

 This entire group is used only for 

 chain decay modeling with multiple

 contaminant species (NSPECI > 1).

 Omit this group if NSPECI = 1.

 ******

The following input records, DC01 through DC03, are to be repeated a total of NSPECI-1 times, for each

of the component species in the decay chain, except the first component species.

Record No. DC01: Number of Parent Species

Format: A5, 2I5

Col. Variable

 1-5 GRPCOD Record identifier; must be ‘DC’ always.

 6-10 I Species number, from 2 to NSPECI.

11-15 NPA(I) Number of immediate parents for I-th species.

Record No. DC02: Parent Numbers

*** Omit this record if the number of 

 parents (NPA) = 0 for the current species ***

Format: 4I5

Col. Variable

 1-5 GRPCOD Record identifier; must be ‘DC’ always.
E:\Projects\EPA\R08-99.217.wpd A-10

 6-10 KPAREN(I,1) Sequential species numbers of the

 . . immediate parents of the current

 . . species, where NUMPAR = NPA(I).

 . .

21-25 KPAREN(I,NUMPAR)

Record No. DC03: Decay Speciation Factors

*** Omit this record if the number of parents

 (NPA) = 0 for the current species ***

Format: A5, 4G10.0

Col. Variable

 1-5 GRPCOD Record identifier; must be ‘DC’ always.

 6-15 APAREN(I,1) Fraction of each parent that decays

 . . into species I, where NUMPAR =

 . . NPA(I).

36-45 APAREN(I,NUMPAR)

A.2.1.5 Observation Time Records (OT)

 ******

Omit this group when a Monte Carlo

simulation is performed (MC = TRUE).

 ******

Record No. OT01: Unsaturated Zone Concentration Output Times

 *** Omit this record when unsaturated zone ***

simulation is not performed (IVADOS = 0.

see record GP01).

Format A5, 8G10.0

Col. Variable

 1-5 GRPCOD Record identifier; must be ‘OT’ always

 6-15, UTOBS(1) Time values for which concentrations 

16-25 . are to be computed.

 . .

 etc. UTOBS(NUTOBS)
E:\Projects\EPA\R08-99.217.wpd A-11

Note: The maximum allowed value for NUTOBS is 20. Up to eight time values can be entered on each

line of the input file. This record should be repeated as many times as necessary (maximum of 3)

to enter all time values.

Record No. OT02: Saturated Zone Observation Time Values

 *** Omit this record if only unsaturated zone ***

simulation is performed (ISTMOD = 0, see 

record GP02)

Format: A5, 8G10.0

Col. Variable

 1-5 GRPCOD Record identifier; must be ‘OT’ always

 6-15 T(1) Time values for which concentrations in

11-20, . saturated zone observation wells are to

 etc. . be computed.

T(NTS)

Note: The maximum allowed value for NTS is 60. Up to eight time values can be entered on each line

of the input data file. This record should be repeated as many times as necessary (maximum of

8) to enter all time values.

A.2.1.6 Source-Specific Data Records (SS)

The records in this group contain the parameters that describe the contaminant source. Records

in this group are identified by the code ‘SS’. All records in this group have a common format which is

described in Table A.6. Each record in the group corresponds to one source parameter. To indicate this

correspondence, each source parameter is assigned a number. The appropriate number is entered as the

second variable (IVAR) of each record following the record identifier.

A list of the records (parameters) in the source specific data group is given below in Table A.1.
E:\Projects\EPA\R08-99.217.wpd A-12

Table A.1 Input parameters for source-specific group. See Table 7.6 for data input formats.

IVAR

EPACMTP

Parameter Description

1 AREA Area of disposal unit (m2

)

2 XW Length (x-direction) of disposal unit (m)

3 YD Width (y-direction) of disposal unit (m)

4 CZERO(I) Leachate concentration emanating from the waste disposal

facility (mg/L). For a degrading constituent, this record

should be repeated for the parent and all daughter products,

i.e., NSPECI times. For finite source degrader simulations

CZERO represents the initial leaching concentration; the

value should be set to zero for all daughters. The value for

the parent should be set to a large value (106

 is presently

used) to avoid numerical difficulties associated with very

small concentration values for degrading constituents. The

value specified in the data input file is a dummy value only;

the Monte Carlo results are adjusted for a range of actual CL

values as a post-processing step.

5 RECHRG Areal recharge rate (m/y)

6 SINFIL Infiltration rate from disposal unit (m/y)

7 HZERO Ponding depth of surface impoundment unit (m)

8 DLINR Thickness of liner (m)

9 CLINR Hydraulic conductivity of liner (m/y)

10 TSOURC Duration of leaching period (y) for finite source option

(KFS=1)TSOURC should be specified as a derived variable

if KFS=2 (i.e. for landfills).
E:\Projects\EPA\R08-99.217.wpd A-13

Table A.1 Input parameters for source-specific group. (continued)

IVAR

EPACMTP

Parameter Description

11 DEPTH Depth of the waste disposal facility (m) for landfill finite

source option.

12 FRACT Fraction of hazardous waste in the waste disposal facility for

landfill finite source option.

13 PWS Dummy parameter.

14 CTDENS Density of hazardous waste (g/cm3

)

Notes:

1) For a deterministic simulation with decaying source conditions (IBAT=1, see group GP04), CZERO

represents the initial concentration.

2) Parameters 7-9 (HZERO, DLINR, CLINR) are required only for the surface impoundment scenario

when an unsaturated zone simulation is performed (IVADOS=1, see group GP01) and the source

ponding option is used. In this case, parameter 6 (SINFIL) should be specified as a derived

parameter.
E:\Projects\EPA\R08-99.217.wpd A-14

A.2.1.7 Chemical-Specific Data Records (CS)

The records in this group contain the parameters that describe the degradation, adsorption and

diffusion characteristics of each of the chemical species being simulated. Records in this group are

identified by the code ‘CS’. All records in this group have a common format which is described in Table

A.6. Each record corresponds to one chemical specific parameter. To indicate this correspondence, each

chemical specific parameter is assigned a number. The appropriate number is entered as the second

variable (IVAR) of each record. A list of records (parameters) in the chemical specific group is provided

below in Table A.2.

Table A.2 Input parameters for chemical-specific group. See Table A.6 for data input formats.

IVAR

EPACMTP

Parameter Description

1 RLAM2(I) Sorbed phase hydrolysis decay rate (1/y). For a multispecies

simulation, this record should be repeated for each of the

components in the decay chain, i.e., NSPECI times.

2 RLAM1(I) Dissolved phase hydrolysis decay rate (1/y). For a

multispecies simulation, this record should be repeated for

each of the components in the decay chain, i.e., NSPECI

times.

3 AHYDR(I) Second-order acid catalyzed hydrolysis rate constant at

reference temperature (1/mol-y). For a multispecies

simulation, this record should be repeated for each of the

components in the decay chain, i.e., NSPECI times.

4 NHYDR(I) Neutral hydrolysis rate constant at reference temperature

(1/y). For a multispecies simulation, this record should be

repeated for each of the components in the decay chain, i.e.,

NSPECI times.

5 BHYDR(I) Second-order base catalyzed hydrolysis rate constant at

reference temperature (1/mole-y). For a multispecies

simulation, this record should be repeated for each of the

components in the decay chain, i.e., NSPECI times.

6 RTEMP Reference temperature (°C).

7 KOC(I) Normalized distribution coefficient for organic carbon (ml/g).

For a multispecies simulation, this record should be repeated

for each of the components in the decay chain, i.e., NSPECI

times.
E:\Projects\EPA\R08-99.217.wpd A-15

Table A.2 Input parameters for chemical-specific group. (continued)

IVAR

EPACMTP

Parameter Description

8 DSTAR(I) Effective molecular diffusion coefficient (m2

/y). For a

multispecies simulation, this record should be repeated for each

of the components in the decay chain, i.e., NSPECI times.

9 DWS(I) Drinking water standard (mg/L), i.e., HBL or MCL value for

comparison against model predicted average receptor well

concentrations. For a degrader, this record should be repeated

for the parent and all daughter products, i.e., NSPECI times.

10 CARC(I) Base exposure period (y) for calculating average receptor well

concentration. Set to 70 y for carcinogens, and 35 y for noncarcinogens. Always specify this parameter as a constant. For

a degrader, this record should be repeated for the parent and all

daughter products, i.e., NSPECI times.

Notes:

1) The parameters 1-7 in this group are used to compute degradation rates and partition coefficients

for each of the contaminant component species. These parameters are required only when the

overall degradation rate and sorption parameters for the unsaturated and saturated zone, (see

groups US and AS) are given as derived parameters, otherwise this group may be omitted.

2) If variables 1-2 (RLAM2 and RLAM1) are specified as derived parameters, they will be computed

from the acid, neutral and base catalyzed hydrolysis rates (variables 3-5).

3) If variables 1-2 (RLAM2 and RLAM1) are specified as random with statistical distributions,

variables 3-6 (hydrolysis rates) are not used, and may be omitted.

4) If the adsorption isotherm is linear, the partition coefficient can be calculated from the Koc value

(variable 7). If on the other hand, the isotherm is nonlinear, the Freundlich isotherm parameters

for the unsaturated and saturated zone must be given themselves in the record groups ‘US’ and

‘AS’, respectively, In this case the Koc is not used and may be omitted.

5) For a multispecies simulation, it is required that the degradation and sorption parameters for all

species are specified in a consistent manner. For instance, if the degradation rate for the first

species is a derived parameter and computed from the acid, neutral and base catalyzed hydrolysis

rates (variables 3-5), this same procedure must also be used for the remaining species.
E:\Projects\EPA\R08-99.217.wpd A-16

6) Chemical-specific variable CARC (IVAR=10) is not required when a steady-state (infinite source)

analysis is performed, or when the finite source analysis uses the peak instead of time-averaged

receptor well concentration (ICRW=0, see input group GP03).

A.2.1.8 Metals-Specific Data Record (MT)

The records in this group contain the parameters that describe the master variables that control the

selection of the effective metals sorption isotherm. Records in this group are identified by the code <MT’.

All records in this group follow the format described in Table A.6. Each record corresponds to one

parameter. To indicate this correspondence, each metal specific parameter is assigned a number. The

appropriate number is entered as the second variable (IVAR) of each record, following the record

identifier. A list of records (parameters) in the metals-specific group is given below in Table A.3.

Table A.3 Input parameters for metals specific group. See Table A.6 for data input formats.

IVAR

EPACMTP

Parameter Description

1 METAL_ID Identification number for the metal.

2 USPH Soil and aquifer pH.

3 FEOX Weight percentage of iron-hydroxide in the soil and aquifer.

4 LOM Concentration (mg/L) of dissolved organic carbon in the

waste leachate.

5 USNOM Unsaturated zone percentage organic matter.

6 ASNOM Aquifer fraction organic carbon.

Notes:

1) This group is required only for metals modeling (METALS = True, see group GP01); the group

may be omitted if METAL = F(alse).

2) Presently the following METAL_ID codes are recognized: 1 = Barium; 2 = Cadmium; 3 =

Chromium (4+); 4 = Mercury; 5 = Nickel; 6 = Lead; 7 = Silver; 8 = Zinc (6+); 9 = Copper;

10 = Vanadium; 13=Arsenic; 14=Chromium (tb); 15=Selenium; 16=Thallium; 17=Antimony.

3) The unsaturated zone percentage organic matter varies with soil type and should be the same as

that specified under the unsaturated zone specific group (see section 6.4.5).

4) The saturated zone fraction organic carbon should be the same as that specified under the aquifer

specific group (see section 7.5.12).
E:\Projects\EPA\R08-99.217.wpd A-17

A.2.1.9 Unsaturated Zone Specific Data Record (US)

The records in this group contain the parameters that describe unsaturated zone physical and

chemical characteristics. Records in this group are identified by the code ‘US’. All records in this group

follow the format described in Table A.6. Each record corresponds to one unsaturated zone parameter.

To indicate this correspondence, each unsaturated zone parameter is assigned a number. The appropriate

number is entered as the second variable (IVAR) of each record, following the record identifier. A list

of records (parameters) in the unsaturated zone specific group is given below in Table A.4.

Table A.4 Input parameters for unsaturated zone specific group. See Table A.6 for data input

formats.

IVAR

EPACMTP

Parameter Description

1 SATK Saturated hydraulic conductivity, Ks, (cm/hr).

2 ALPHA Moisture retention parameter, ", (cm-1).

3 BETA Moisture retention parameter, $.

4 WCR Residual water content, 2r.

5 WCS Saturated water content, 2s.

6 DSOIL Thickness of unsaturated zone (m).

7 DISPR Dispersivity, ", (m)

8 POM Percent organic matter

9 RHOB Bulk density, Db, (g/cm3

)

10 UFCOF(I) Leading coefficient in Freundlich adsorption isotherm, k1.

For a multispecies simulation, this record should be repeated

for each of the components in the decay chain, i.e., NSPECI

times.

11 UFEXP(I) Freundlich exponent, 0. For a multispecies simulation, this

record should be repeated for each of the components in the

decay chain, i.e., NSPECI times.

12 UCLAM(I) Chemical degradation rate coefficient (1/y). For a

multispecies simulation, this record should be repeated for

each of the components in the decay chain, i.e., NSPECI

times.
Table A.4 Input parameters for unsaturated zone specific group. (cont)

IVAR

EPACMTP

Parameter Description

E:\Projects\EPA\R08-99.217.wpd A-18

13 BIOU(I) Biological degradation rate coefficient (1/y). For a

multispecies simulation, this record should be repeated for

each of the components in the decay chain, i.e., NSPECI

times.

Notes:

1) This group may be omitted if no unsaturated zone simulation is performed (IVADOS=0, see group

GP02).

2) If the adsorption isotherm is linear, variable 11(UFEXP) should be omitted or set to a constant

value of 1.0. In this case, variable 10 (UFCOF) corresponds to the partition coefficient, kd,

(cm3

/g).

3) IF UFCOF is specified directly (i.e., not derived), variable 8 (POM) may be omitted.

4) If the chemical degradation rate (UCLAM) is specified as a derived parameter, it will be calculated

from the chemical specific decay parameters (CS-group).

5) For a multispecies simulation, it is required that the degradation and adsorption parameters for all

species are specified in a consistent manner. For instance, if the chemical degradation rate for the

first species is specified directly instead of derived, the same procedure must be used for the

remaining species.

A.2.1.10 Aquifer-Specific Data Records (AS)

The records in this group contain the parameters that describe the saturated zone physical and

chemical characteristics. Records in this group are identified by the code ‘AS’. All records in this group

follow the format described in Table A.6. Each record corresponds to one saturated zone parameter. To

indicate this correspondence, each saturated zone parameter is assigned a number. The appropriate number

is entered as the second variable (IVAR) of each record, following the record identifier. A list of records

(parameters) in the saturated zone specific group is given below in Table A.5.
E:\Projects\EPA\R08-99.217.wpd A-19

Table A.5 Input parameters for aquifer specific group. See Table A.6 for data input formats.

IVAR

EPACMTP

Parameter Description

1 DIAM Average particle diameter (cm)

2 POR Aquifer porosity

3 BULKD Aquifer bulk density (g/cm3

) 

4 ZB Aquifer Saturated thickness (m)

5 XKX Longitudinal hydraulic conductivity, Kx, (m/y)

6 ANIST Anisotropy ratio, Kx/Kz

7 GRADNT Hydraulic gradient (m/m)

8

VXCS Regional groundwater seepage velocity (m/yr)

9 RETARD(I) Retardation coefficient. For a multispecies simulation, this

record should be repeated for each of the components in the

decay chain, i.e., NSPECI times

10 AL Longitudinal dispersivity, "L (m)

11 AT Transverse dispersivity, "T (m)

12 AV Vertical dispersivity, "V (m)

13 TEMP Temperature of ambient aquifer water (°C)

14 PH Ambient groundwater pH

15 FOC Fraction organic carbon (g/g)

16 RADIS(I) Radial distance of observation well from center of

downstream edge of waste disposal unit (m). Repeat this

record for each of the NWELLS observation wells.

17 ANGLE(I) Angle off-center of observation well measured

counterclockwise (degrees). Repeat this record for each of

the NWELLS observation wells.

18 XWELL(I) Distance in downstream direction (m) between downstream

edge of the source and observation well. Repeat this record

for each of the NWELLS observation wells.
Table A.5 Input parameters for aquifer specific group. (continued)

IVAR

EPACMTP

Parameter Description

E:\Projects\EPA\R08-99.217.wpd A-20

19

YWELL(I) Horizontal transverse distance of well from the plume

centerline (m). Repeat this record for each of the NWELLS

observation wells.

20 ZWELL(I) Depth of well below water table (m). Repeat this record for

each of the NWELLS observation wells. Note ZWELL

should be given as a fraction of the saturated zone thickness,

unless distribution type 12 (Section 6.5.13), i.e. constant well

depth, is being used.

21 SFCOF(I) Leading coefficient of Freundlich adsorption isotherm

(distribution coefficient). For a multispecies simulation, this

record should be repeated for each of the components in the

decay chain, i.e., NSPECI times.

22

SFEXP(I) Freundlich isotherm exponent. For a multispecies

simulation, this record should be repeated for each of the

components in the decay chain, i.e., NSPECI times.

23 CSLAM(I) Chemical degradation rate coefficient (1/y). For a

multispecies simulation, this record should be repeated for

each of the components in the decay chain, i.e., NSPECI

times.

24 BIOS(I) Biodegradation rate coefficient (1/y). For a multispecies

simulation, this record should be repeated for each of the

components in the decay chain, i.e., NSPECI times.

Notes:

1) This entire group may be omitted when no saturated zone simulation is performed (ISTMOD=0,

see group GP01).

2) For a Monte Carlo simulation, only one observation well is allowed.

3) The x-(longitudinal or downstream) and y-(horizontal transverse) location of the observation

well(s) relative to the source can be determined in two ways. The first way is to give the x- and

y-locations directly, through variables 18 and 19. The second way is to give these locations in

terms of the radial distance between the well(s) and the center of the downstream side of the
E:\Projects\EPA\R08-99.217.wpd A-21

source, and the angle between this radial direction and the x-direction (see figure 6.1). If the latter

option is used, the x and y locations (variables 18 and 19) should be given as derived variables.

4) If the adsorption isotherm is linear, the Freundlich coefficient, SFEXP(I), should be set equal to

1.0 or omitted. In this case, SFCOF(I) corresponds to the partition coefficient kd.

5) If the retardation coefficient (RETARD) is specified directly and not a derived parameter, then

SFEXP, SFCOF and FOC can be omitted. This is valid only when the isotherm is linear.

6) When the degradation rate is not a derived parameter, the aquifer pH is not needed.

7) For a multispecies simulation, it is required that the degradation and adsorption parameters for all

species are specified in a consistent manner. For instance, if the chemical degradation rate for the

first species is specified directly instead of derived, the same procedure must be used for the

remaining species. It is allowed that the sorption isotherm for some species is linear, while it is

nonlinear for other species. In this case the isotherm parameters SFCOF and SFEXP must be

specified for all species. 

A.3 EMPIRICAL DISTRIBUTIONS DATA RECORDS (EM)

 ******

Omit this group for a deterministic

simulation (MC=False) or if no

empirical distributions were specified

in input groups SS-AS.

 ******

(i) Header record

No. of records: 1 Format: 2A5, 2I5

Col. Variable

 1-5 GRPCOD Data input group identifier. Should be ‘EM’ always.

 6-10 EMPCOD Character variable indicating to which parameter group the

empirical distribution belongs; enter SS, CS, US or AS.

11-15 IEMP Integer variable indicating parameter number (IVAR) to which the

empirical distribution corresponds.

16-20 NPT Number of entry pairs of random values and cumulative

probabilities for empirical distribution.

(ii) Data records

No. of records: NPT Format: A5, 2G10.0
E:\Projects\EPA\R08-99.217.wpd A-22

Col. Variable

 1-5 GRPCOD Data input group identifier. Should be ‘EM’ always.

 6-15 VALUE (J,I) Value of J-th point in empirical distribution.

16-25 CDF (J,I) Cumulative probability of J-th point.

Notes:

1) Both the header and data records are to be repeated for each of the specified empirical distributions

in groups SS through AS.

2) The empirical distributions must be entered in the same consecutive order in which they appear

in groups SS through AS.

Table A.6 Data format for input records in groups SS, CS, US and AS.

Format: A5, 2I5, 4G10.0, A25

Col. 1-5 GRPCOD: Character variable code to indicate group type of random

variable; enter SS, CS, US, or AS. 

 

 6-10 IVAR: Integer variable indicating which EPACMTP input parameter the

record corresponds to. 

 

 11-15 IDIST: Integer variable indicating type of statistical distribution (see

Table 5.1). 

 

 16-25 MEAN: Specified mean of statistical distribution. 

 

 26-35 SD: Standard deviation of statistical distribution. 

 

 36-45 LOWER: Lower bound of statistical distribution. 

 

 46-55 UPPER: Upper bound of statistical distribution. 

 

 56-80 VARNAM: Character variable giving name of the EPACMTP parameter to

which record corresponds. 

Notes:

1) The first variable of each record is a two-character string that identifies the input group, e.g. ‘CS’.
E:\Projects\EPA\R08-99.217.wpd A-23

2) The second variable gives the parameter number. Each EPACMTP parameter has a number that

is unique within each group. This number is used by the code to identify the correct model

parameter. 

3) The third variable determines whether the parameter should be held constant (IDIST=0), or be

considered a Monte Carlo variable (IDIST$1). A negative value indicates that the parameter is

derived, i.e., computed from another EPACMTP input parameter. The codes used are described

in Table 5.1. This variable is ignored during a deterministic simulation, unless the parameter is

derived (indicated by a negative distribution code).

4) The fourth variable gives the mean of the probability distribution for a Monte Carlo simulation,

and the actual parameter value to be used for a deterministic simulation, or when the parameter

is held constant. This variable is not used when the parameter is derived.

5) The fifth variable gives the standard deviation of the probability distribution for a Monte Carlo

simulation. This variable is not used when the parameter is held constant or for a deterministic

simulation.

6) The sixth and seventh variable correspond to the lower and upper bounds, respectively, of the

probability distribution of the parameter. Setting both to zero means that the bounds will be

ignored by EPACMTP. They are not used for a deterministic simulation or when the parameter

is held constant.

7) The eighth and final variable for each record is and optional 25-character string that may be used

to identify the model parameter corresponding to the input record.

8) The input records and parameters for each of the source specific (SS), Chemical Specific (CS),

Unsaturated zone Specific (US), and Aquifer Specific (AS) input groups are listed in Tables A.1

through A.5.

It is useful to note that often, especially while performing deterministic simulations, the model may

not require input records for each and every parameter described above. For instance, the source

area can be omitted if the x- and y-dimensions of the source are given individually. If an input

parameter is not actually used by EPACMTP, and its corresponding record is still present in the

data file, EPACMTP will simply skip this record. To determine whether an input record is

required or not, the user must be aware of the possible dependencies between input parameters.

This is especially important for derived parameters. Failure to enter all necessary

records/parameters may lead to unpredictable results!

A.4 RUNNING EPACMTP

EPACMTP can be used to simulate either a single problem at a time, or to process a number of

problems in batch mode. When EPACMTP is started, the code will first ask the user whether a batch run

is desired. If the user returns N(o), a single problem (either Monte Carlo or deterministic) will be

simulated. The user is then prompted by EPACMTP to provide the name of the input data file containing

the problem definition, and the name to be given to the output file. 
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If a batch run is selected, the user must provide the name of the batch file. The batch file is simply

a separate file containing a list of all the EPACMTP data input files that are to be processed in the batch

run. EPACMTP will then sequentially execute all the input data files in the batch file. The output files

for each problem will be created automatically; they will have the same file name as the data input file,

but with different extensions. 

A.5 MODEL OUTPUT POST PROCESSING

The output from EPACMTP consists of predicted concentration levels, either at the water table

(output from the unsaturated zone module), and/or at observation wells located in the saturated zone

(output from the saturated zone module). When a deterministic simulation is performed, all output is

written to the primary output file, and generally does not require additional post processing. When a

Monte Carlo simulation is performed, the output of interest consists of the receptor well concentration

values generated by each individual simulation. For continuous source runs, the entire cumulative

distribution function (CDF) of the receptor well concentrations is written to the {OUTPUT}.CDF file. 

For finite source runs, the Monte Carlo output is written to a series of {OUTPUT}n.SAT files, with

each file corresponding to a different value of the ratio between total waste and leachate concentration.

These files are subsequently used by POSTCMTP post-processor to provide the regulatory limits on waste

and leachate concentration for any protection level. It may be noted that the finite source option of

POSTCMTP does not allow aggregation of Monte Carlo results. Rather, it is assumed that the aggregation

has already been performed inside EPACMTP, using the ALLRUN option of the model. ALLRUN option

is set to FALSE when regional site-based analysis is performed, i.e. IFREGNL=TRUE.

A.5.1 Using POSTCMTP

POSTCMTP is an interactive, menu-driven postprocessor for EPACMTP. It reads in the

EPACMTP Monte Carlo output files and presents the results in graphical and tabular form on the screen,

and also provides the option to generate hard copy output on a wide variety of printers and plotters.

To use the postprocessor, simply type #POSTCMTP’. The first time you run the program, you

will automatically be taken into the setup menu to select the type of printer you have and to specify how

it is connected to your PC. After completing the initial setup, you can always change the configuration

by selecting the #(I)nitialize Plotting Device’ option from the main menu. The main menu also allows you

to select either #(C)ontinuous Source Analysis’ or #(F)inite Source Analysis’. You must select the analysis

type that corresponds to the EPACMTP Monte Carlo simulation that you want to analyze. For example,

it is not valid to select (F)inite Source Analysis if a steady-state Monte Carlo run was performed.
E:\Projects\EPA\R08-99.217.wpd A-25

Continuous Source Analysis

After selecting the (C)ontinuous Source option, you will be prompted to provide the name of the

EPACMTP output file. You must enter the file name only, without an extension. After entering the

filename, select the (G)raph option to view the simulated DAF curve. After the graph has been drawn on

the screen, you can either save the graph on disk using the (S)ave option, or send the graph to your printer

or plotter using the (H)ard Copy option. Please note that printing on a laser printer is quite slow; it may

take more than 5 minutes to complete the plot.

From the (C)ontinuous Source menu, you may also press the (S)pecify option. This allows you

to compute the DAF at any arbitrary level of probability, or to compute the probability that the DAF will

exceed a specified value.

Press (E)xit to return to the POSTCMTP main menu.

Finite Source Analysis

After selecting the (F)inite Source Analysis option from the main menu, you will first be asked to

supply the name of the EPACMTP output file you want to analyze. This file name must be entered without

the file extension. After reading in the files, the program will perform the finite source post-processing

analysis. By default, it will compute the values of total waste concentration (Cw) and leachate concentration

(CL) that correspond to an 85th percentile protection level. To change this, select the (S)pecify option, and

enter the desired protection level.

To view the post-processing results graphically, select the (G)raph option. After the graph has

been drawn on the screen, you may (S)ave the graph on disk, or print it on you printer or plotter using the

(H)ard Copy option. Please note that printing to a laser printer is quite slow; it may take more than 5

minutes to complete the plot.

Press (E)xit to return to the Main POSTCMTP menu.
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APPENDIX B

INPUT AND OUTPUT FILES FOR A MONTE CARLO ANALYSIS SAMPLE PROBLEM
E:\Projects\EPA\R08-99.217.wpd C-1

APPENDIX C

FREQUENCY DISTRIBUTIONS OF MONTE CARLO INPUT PARAMETERS

This Appendix contains frequency distribution plots of EPACMTP input parameters. The plots

are represented in the form of histograms that display different intervals of parameter values and the

corresponding frequency of observation. The observation frequency is given as a fraction of the total

population. For example, a normalized frequency of 0.50 means that the corresponding interval contains

half of the total population. The length of each interval is the distance between the mid points of two

successive bars. 

A log scale axis has been used in some plots in order to achieve appropriate representation of the

range of values for some of the input parameters such as area, hydraulic conductivity, and hydraulic

gradient.

The data used to plot the frequency distributions of the source related parameters (area, depth,

infiltration, and recharge) is unique for each waste management scenario (landfills, surface impoundments,

and land application units). Data for the area and depth were obtained from the OPPI Survey database.

Infiltration and recharge rates were computed by the HELP model for individual waste management

scenarios. The data for unsaturated and saturated zone parameters is the same for all waste management

scenarios and represent nationwide distributions, obtained through aggregation of the distributions of the

twelve individual hydrogeological environments. The values were generated by running EPACMTP in

Monte Carlo mode.