rB7J- inD?.jr
EPA/600/R-93/082
May 1993
0
1995
J
1ZC3 Six^h Avenue. Seatlte, IVA 93? 31 f
A SUBTITLE D LANDFILL APPLICATION MANUAL
FOR THE MULTIMEDIA EXPOSURE
ASSESSMENT MODEL (MULTIMED)
by
Susan Sharp-Hansen1
Constance Travers1
Paul Hummel1
Terry Allison2
AQUA TERRA Consultants1
Mountain View, CA 94043
Computer Sciences Corporation2
Athens. CA 30605-2720

JMN 191995
]
IfflOSirthAwnmSirtfcWBgiiifll
Project Monitor
Gerard Lanlak
Environmental Research Laboratory
U.S. Environmental Protection Agency
Athens, GA 30605-2720
ENVIRONMENTAL RESEARCH I-ABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION ACENCY
ATHENS, GEORGIA 30605-2720
REPRODUCED BY
U.S. DEPARTMENT OF COMMERCE
NATIONAL TECHNICAL INFORMATION SERVICE
SPRINQFIELD, VA. 22161

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DISCLAIMER
The work presented in this document has been funded by the United.States
Environmental Protection Agency under Contract No. 68-03-3513 to AQUA TERRA
Consultants and 68-01-7176 to Computer Science Corporation, Athens, CA. It
has been subject to the Agency's peer and administrative review, and has been
approved as an EPA document. Mention of trade names or commercial products
does not constitute endorsement or recommendation for use by the U.S. Environ-
mental Protection Agency.
ii
Kniim!l£K.HGI0N '0MA1WWIS
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FOREWORD
As environmental controls become more costly to implement and the penalties of
judgment errors become more severe, environmental quality management requires
more efficient management tools based on greater knowledge of the environ-
mental phenomena to be managed. As part of this Laboratory's research on the
occurrence, movement, transformation. Impact and control of environmental
contaminants, the Assessment Branch .develops management or engineering tools
to help pollution control officials assess the risk to human health and the
environment posed by land disposal of hazardous wastes.
EPA's Multimedia Exposure Assessment (MULTIMED) simulates the transport and
transformation of contaminants released from a hazardous waste disposal
facility into the multimedia environment. MULTIMED Includes contaminant
release to either air or soil and possible interception of the subsurface
plume by a surface stream. An important application of MULTIMED would be che
prediction of pollutant movement in leachate from a Subtitle D landfill, a use
that requires only a subset of the model's full capabilities. This manual,
then, provides instruction for Inexperienced as well as experienced model
users who seek to study or design waste disposal facilities.
Rosemarie C. Russo, Ph.D.
Director
Environmental Research Laboratory
Athens, GA
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ABSTRACT
The Environmental Protection Agency's Multimedia Exposure Assessment Model
(MULTIMED) for exposure assessment simulates the movement of contaminants
leaching from a landfill. The model consists of a number of modules that
predict concentrations at a receptor due to transport in the subsurface,
surface water, or air. This report is an application manual for the use of
MULTIMED in modeling Subtitle D land disposal facilities.
When applying MULTIMED to Subtitle D facilities, the landfill, surface water,
and air modules In the model are not accessible by the user; only flow and
transport through the unsaturated zone and transport in the saturated zone can
be considered. A steady-state, one-dimensional, semi-analytical module
simulates flow in the unsaturated zone. The output from this module, water
saturation as a function of depth, is used as input to the unsaturated zone
transport module The latter simulates transient, one-dimensiona1 (vertical)
transport in the unsaturated zone and Includes the effects of longitudinal
dispersion, linear adsorption, and first-order decay. The unsaturated zone
transport module calculates steady-state or transient contaminant concentra-
tions. Output from both unsaturated zone modules is used to couple the
unsaturated zone transport module with the steady-state or transient, semi-
analytical saturated zone transport module. The latter includes one-dimen-
sional' uniform flow, three-dimensional dispersion, linear adsorption, first -
order decay, and dilution due to direct infiltration into the groundwater
plume.
The fate of contaminants in the various media depends on the chemical pro-
perties of the contaminants as well as a number of media- and environment-
specific parameters. The uncertainty in these parameters can be quantified in
MULTIMED using the Monte Carlo simulation technique.
To enhance the user-friendly nature of MULTIMED, a preprocessor, PREMED, and a
postprocessor, POSTMED, have been developed. The preprocessor guides the user
In the creation of a correct Subtitle D input file by restricting certain
options and parameters and by setting appropriate defaults.
This report was submitted in partial fulfillment of Contract Number 68-03-3513
by AQUA TERRA Consultants and Contract Number 68-01-7176 to Computer Sciences
Corporation, under the sponsorship of the U.S. Environmental Protection
Agnncy. This report covers the period March 1990 to July 1991, and work was
completed as of July 1991.
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TABLE OF CONTENTS
Section	Page
Disclaimer		 ii
Foreword		ill
Abstract	 iv
Figures		 ix
Tables		xii
Acknowledgements	!		xvi
1.0 INTRODUCTION			
1.1	Overview of MULTIMED	
1.1.1	Model Capabilities	
1.1.2	Interaction Framework (AIDE)	
1.2	Application of MULTIMED to Subtitle D Land Disposal
Facilities		
1.3	Report Organization	
1.4	How to Use this Manual	
2.0 PROGRAM INSTALLATION AND EXECUTION	
2.1	System Requirements	
2.1.1	Hardware	
2.1.2	Software	
2.2	Loading the Executable Code	
2.3	Executing and Verifying Test Sessions	
3.0 FORMAT AND OPERATION OF THE PRE- AND POSTPROCESSOR		0
3.1	Screen Format		10
3.1.1	Data Window		10
3.1.2	Assistance Window			li
3.1.3	Instruction Window		15
3.1.4	Command Line		19
3.2	Interaction Modes			19
3.3	Screen Movement		21
3.3.1	Movement within Screens		22
3.3.2	Movement between Screens		23
3.3.3	Screen Path		2U
4.0 USE OF THE PRE- AND POSTPROCESSORS		2 5
4.1	The Preprocessor (PREMED)		25
4.1.1	Use of the Preprocessor		2 5
4.1.2	The PREMED Tutorials	
4.2	The Postprocessor (POSTMED)			42
4.2.1 Use of che Postprocessor		42
5.0 MODEL APPLICATION		52
5.1 MULTIMED Capabilities and Limitations		51i
5.1.1	Solution Techniques	,		53
5.1.2	Spatial Characteristics of the System		55
5.1.3	Steady-state Versus Transient Flow and Transport..	56
5.1.4	Monte Carlo Versus Deterministic Simulations		56
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5.1.5 Boundary Conditions		5 7
5.2	Subtitle D Applications of MULTIMED		57
5.2.1	Summary of EPA Requirements for MULTIMED
Simulations of Leachate Migration from Subtitle D
Facilities		57
5.2.2	Active Modules		58
5.2.3	Boundary Conditions		56
5.2.4	Procedures for Application of MULTIMED to
Subtitle D Facility Design		59
5.3	KULTIMED Input Requirements		61
5.3.1	Parameter Requirements Summarized by Module		62
5.3.2	Parameter Requirements Summarized by Data Group...	62
6.0 PARAMETER ESTIMATION	!		82
6.1	Chemical-SpecifIc Parameters		8?
6.1.1	Overall Chemical Decay Coefficient (Saturated
Zone)		fl?
6.1.2	Solid-Phase and Liquid-Phase Decay Coefflclencs
(Saturated Zone)		8"!
6.1.3	The Acid-Catalyzed and Base-Catalyzed Hydrolysis
Rates and the Neutral Hydrolysis Rr.ie			83
6.1.4	Reference Temperature		83
6.1.5	Distribution Coefficient (Saturated Zone)		83
6.1.6	Normalized Organic Carbon Distrioution
Coefficient		84
6.1.7	Blodegradation Coefficient (Saturated Zone)		86
6.2	Source-Specific Parameters		85
6.2.1	Recharge Rate		85
6.2.2	Infiltration Rate		85
6.2.3	Area of the W.-*ste Disposal Unit		85
6.2.<»	Length Scale ot the Facility		85
6.2.5	Width Scale of the Facility		85
6.2.6	Initial Concentration at Uaste Disposal Facility..	86
6.2.7	Source Decay Constant		86
6.2.8	Duration of Pulse		86
6.2.9	Spread of Contaminant Source		86
6.3	Unsaturated Flow Parameters		8$
6.3.1	Saturated Hydraulic Conductivity		8>
6.3.2	Unsaturated Zone Porosity		8.'
6.3.3	Air Entry Pressure Head		87
6.3.':	Number of Layers, Thickness of Layers		87
6.3.5	Residual Water Content		90
6.3.6	Brooks and Corey Exponent		91
6.3.7	Van Genuchten Parameters		92
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6.4	Unsaturated Transport Parameters		92
6.4.1	Number of Layers, Thickness of Layers		92
6.4.2	Longitudinal Dispersivity of Each Layer		92
6.4.3	Percent Organic Matter		94
6.4.4	Bulk Density of Soil for Layer		97
6.4.5	Biological Decay Coefficient		97
6.5	Aquifer-Specific Parameters		97
6.5.1	Aquifer Porosity			97
6.5.2	Particle Diameter				97
6.5.3	Bulk Density		97
6.5.4	Aquifer Thickness		98
6.5.5	Source Thickness (Mixing Zone Depth)		9fl
6.5.6	Hydraulic Conductivity		103
6.5.7	Hydraulic Gradient		103
6.5.8	Groundwater Seepage Velocity		104
6.5.9	Retardation Coefficient		104
6.5.10	Longitudinal, Transverse, and Vertical
Dispersivlties . .		104
6.5.11	Aquifer Temperature		105
6.5.12	pH		105
6.5.13	Organic Carbon Content (Fraction)		107
6.5.14	Well Dlstan< •> from Site, Angle off Center, and
Well Vertical Distance		108
7.0 EXAMPLE PP.OBLEKS		110
7.1	Example 1		110
7.1.1	The Hypothetical Scenario		110
7.1.2	Input		Ill
7.1.3	Output		114
7.2	Example 2		114
7.2.1	The Hypothetical Scenario		114
7.2.2	Input		114
7.2.3	Output		114
7 . 3 Example 3			128
7.3.1	The Hypothetical Scenario		128
7.3.2	Input		128
7.3.3	Output		133
8.0 REFERENCES			
APPENDIX A - CODE STRUCTURE AND INPUT DATA FORMAT		151
A.l Model Structure		15)
A. 2 Input and Output File Units		'51
A. 3 Common Blocks and Parameter Statements		154
A.4 Structure of the Input Files		154
A.4.1 Comment Cards		157
A.4.2 Data Group/Subgroup Specification Card, End Card
and Data Cards		157
A.4. 3 Specification of Parameter Values		157
A.4.4 The Array Subgroup		160
A.4. 5 The Empirical Distribution Subgroup		161
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A. 5 Format of the Data Groups		162
A.5.1 General Data Group		162
A. 5. 2 Source Data Group		162
A. 5. 3 Landfill Data Group		166
A. 5.4 Chemical Data Group		171
A. 5. 5 Unsaturated Flow Data Group		173
A.5.6 Unsaturated Transport Data Group		187
A.5.7 Aquifer Data Group		189
A. 5.8 Surface Water Data Group		192
A. 5. 9 Air Emissions and Dispersion Data Croup		195
APPENDIX B - SUBROUTINES IN MULTIMED			204
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FIGURES
£fl&s
2.1 Preprocessor screen after installation		9
3.1	Screen format utilized by the pre- and postprocessor		11
3.2	Example of a two window, one command line screen		12
3.3	Example of u three window, one command line screen		13
3.4	Example of a HELP assistance window		16
3.5	Example of a LIMITS assistance window	 			17
3.6	Example of information contained in a STATUS assistance window..	18
3.7	Example of an ERROR message in the Instruction window		20
4 . 1 Opening screen of the preprocessor		26
4. 2 Build/Modify screen of the preprocessor		27
4.3	Edit screen of the preprocessor		28
4.4	Create screen of the preprocessor		28
4.5	General-1 screen of the preprocessor		30
4.6	General-2 screen of.the preprocessor		31
4.7	Edit screen of the preprocessor		31
4.8	.'.Quifer screen of the preprocessor		33
4.9	SOurce screen of the preprocessor		34
4.10	Chemical screen of preprocessor		34
4.11	Unsaturated Flow (Funsat) screen of the preprocessor		35
4.12	Unsaturated Transport (Tunsat) screen of the preprocessor		35
4.13	The Depth screen of the preprocessor		37
4.14	The Porosity screen of the preprocessor for a deterministic
simulation		38
4.15	Screen for specification of aquifer porosity for a
deterministic simulation		38
4.16	Porosity screen of Che preprocessor for a Nonce Carlo
simulation		39
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4.17	Screen shoving required parameters for a Lognormal
probability density distribution		39
4.18	The Return screen of the preprocessor			41
4.19	The Save screen of the preprocessor		41
4.20	Example of a tutorial screen		43
4.21	Opening screen of the postprocessor		44
4.22	Data-1 screen of the postprocessor		46
4.23	Data-2 screen of the postprocessor		46
4.24	Specs screen of the¦ postprocessor				4?
4.25	Titles screen of the postprocessor		49
4.26	Example of a cumulative frequency plot			50
4.27	example of a frequency plot		50
4.28	Example of screen showing a TEXT file		51
5.1 Procedure for using MULTIMED to assist in the design of
Subtitle D f.
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TABLES
fege
3-1	Commands fcr Application of PREMED		,	 21
5-1	Issues Co be Considered before Applying KULT1HED	 54
5-2	Primary Parameters Used In the Saturated Zone Transport
Module for Subtitle D Applications of MULTIMED	 63
5-3 Parameters Used to Derive Other Saturated Zone Transport
Module Parameters Needed in Subtitle D Applications of
MULTIMED	 64
5-4	Parameters Required in the Unsaturated Zone Flow Nodule for
Subtitle D Applications of MULTIMED	 66
5-5	Parameters Required In the Unsaturated Zone Transport
Module for Subtitle D Applications of MULTIMED	 67
5-6	Parameters in the Chemical (Chemical) Data Croup	 69
5-7	Parameters Required for Selected Probability Density
Distributions	 72
5-8	Parameters In the Contaminant Source (SOurce) Data Group	 73
5-9	Parameters in the Aquifer (AQuifer) Data Group	 75
5-10 Parameters In the Unsaturated Zone Flow (Funsat) Data Group.. 77
5-11	Parameters In the Unsaturated Zone Transport (Tunsat)
Data Group	 80
6-1	Range of Hydraulic Conductivity Values for Various
Geologic Materials	 88
6-2	Descriptive Statistics for Saturated Hydraulic Conductivity.. 89
6-3	Total Porosity of Various Materials	 90
6-4	Descriptive Statistics for Saturation Water Content and
ReBldual Water Content	 91
6-5	Descriptive Statistics for van Cenuchten Water Retention
Model Parameters			 93
6-6	Compilation of Field Dispersivity Values	 	 95
6-7	Descriptive Statistics and Distribution Model for Organic
Mttter (Percent by Weight)			 96
6-8	Mean Bulk Density for Five Soil Textural Classifications	
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6-9	Descriptive Statistics for Bulk Density		100
6-10	Range of Soil Particle Sizes for Various Materials		101
6-11	Range and Mean Values of Dry Bulk Density for Various
Geologic Materials		102
6-12(a)	Alternatives for'Including Dlsperslvities in the Saturated
Zone Module		J 07
6-12(b)	Probabilistic Representation of Longitudinal Disperslvity
for a Distance of 152.4 m		107
7-1	Input Sequence for Example 1		112
7-2	Output File for Example 1		115
7-3	SAT.OUT File for Example 1		118
7-4	Input Sequence for Example 2		119
7-5	Main Output File for Example 2		123
7-6	SAT.OUT File for Example 2		127
7-7	Monte Carlo Distribution Values In Example 3		128
7-8	Input Sequence for Example 3		129
7-9	Main Output File for Example 3		134
7-10	First Page of the SAT1.0UT File for Example 3		144
7-11	STATS.OUT File for Example 3		145
A -1	Input Files Needed In HULTIMED		154
A-2	Output Files Generated by MULTIKED		155
A-3	Input Data Groups and Subgroups in MULTIMED		159
A-4	Distributions Available and their Codes		160
A-5	Contents and Format of a Typical Array Subgroup		161
A-6	Contents and Format of a Typical Empirical Distribution
Subgroup						163
A-7	Contents and Format of the General Data Group		164
A-8	Example of a Typical General Data Group		168
A-9	Contents and Format of the Source-Specific Data Group		169
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A-10 Variables in the Source-Specific Array Subgroup	 170
A-11 Concents and Format of the Landfill Module Control Data
Group	 172
A-12	Contents and Format of the Landfill Module Layer
Thickness and Material Data Subgroup	 173
A-13 Contents and Format of the Landfill Module Liner Property
Subgroup		 174
A-14 Variables in the Landfill Liner Property Array Subgroup	 175
A-15 Contents and Format of the Landfill Module Material
Property Subgroup	 176
A-16 Variables in the Landfill Material Property Array Subgroup... 17?
A-17 Contents and Format of the Landfill Module Hydrology
Subgroup	 178
A-18 Variables in the Landfill Hydrology Array Subgroup	 179
A-19 Contents and Format of the Chemical-Specific Data Group	 180
A-20 Variables in the Chemical Array Subgroup	 181
A-21 Contents and Format of the Unsaturated Zone Flow
Module Control Data Croup	 182
A-22 Contents and Format of the Unsaturated Flow Module Layer.
Thickness and Material Data Subgroup	 184
A-23 Contents and Format of the Unsaturated Zone Flow Module
Material Property Subgroup	 185
A-24 Variables in the Unsaturated Flow Material Property Array
Subgroup	 186
A-25 Contents and Format of the Unsaturated Zone Flow Module
Moisture Data Subgroup	 187
A-26 Variables in the Unsaturated Flow Moisture Data Array
Subgroup	 188
A-27 Contents and Format of the Unsaturated Zone Transport
Module Control Data Subgroup	 	 190
A-?.8 Contents and Format of the Unsaturated Zone Transport
Module Properties Subgroup	 192
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A-29 Variables in the Unsaturated Transport Properties Array
Subgroup		194
A-30 Contents and Format of the Aquifer-Specific Data Group		195
A-31 Variables in the Aquifer Data Array Subgrov- 		196
A-32 Contents and Format of the Surface Water Data Group...!		197
A-33 Variables in the Surface Water Data Array Subgroup		199
A-34	Contents and Format of the Air Emission and Dispersion
Data Group		200
A-35 Variables in the Air Emission and Dispersion Data Array
Subgroup		201
A-36 Contents and Format of the Air Dispersion Control Data
Subgroup		202
A-37 General Structure of the Wind-Stability Frequency File
(FREQ . IN)	 		203
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ACKNOWLEDGEMENTS
This document was prepared under Work Assignment No. 32 of Contract No. 68-03-
3513 by AQUA TERRA Consultants for the U.S. Environmental Protection Agency
Office of Research and Development. Gerard Lanlak of the Environmental
Research Laboratory in Athens, Georgia was the Technical Project Monitor and
Robert Carsel was the Project Officer. We thank them for their continuous
technical and management support throughout the course of this project.
At AQUA TERRA Consultants, the report was co-authored by Constance Travers and
Susan Sharp-Hansen, the Project Manager. Anthony Donigian supplied technical
and administrative guidance and he and John Kittle reviewed the document.
Word processing was performed by Dorothy Inahara. The material in Appendix A,
which summarizes the code structure and input format, and in Appendix B, which
lists the model subroutines, is based on a report by Salhotra and Mlneart
(1988).
A number of individuals were involved in the development and implementation of
the MULTIMED computational codes. Key individuals include Jan Kool and Peter
Huyakorn of HydroGeoLogic Inc., Terry Allison of Computer Sciences Corpora-
tion,- Barry Lester of Geotrans Inc., Michael Ungs of TetraTech, Inc., Bob
Ambrose of U.S. EPA, John Kittle of AQUA TERRA Consultants, and Rob Schanz,
Yvonne Meeks, and Peter Mangarella of Woodward-Clyde Consultants.
The pre- and postprocessor for MULTIMED were developed by John Kittle and Paul
Hummel at AQUA TERRA Consultants. Paul Hummel and Constance Travers created
the tutorials for the preprocessor.
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SECTION 1
INTRODUCTION
This document provides Information needed to apply the U.S. Environmental
Protection Agency's Multimedia Exposure Assessment Model (MULTIMED) to
scenarios related to the study and design of Subtitle D land disposal faci-
lities. Application of KULTIMED to Subtitle D facilities requires the use of
only a subset of the model's capabilities. MULTIMED's model theory documenta-
tion (Salhotra et si., 1993) provides detailed information about the model's
full capabilities. In this section, the model's full capabilities are first
briefly addressed (Section 1.1). A summary of the methods used for applica-
tion to the design of Subtitle D facilities follows (Section 1.2).
1.1 OVERVIEW OF MULTIMED
MULTIMED simulates the ".ransport and transformation of concaminants released
from a waste disposal facility into the multimedia environment. Release Co
either air or soil, including the unsaturated and the saturated zones, and
possible interception of the subsurface contaminant plume by a surface stream
are included In the model. Thus, the model can be used as a technical and
quantitative management tool to address the problem of the land disposal of
chemicals in the multimedia environment. At this time, the air modules of the
model are not linked to the other model modules. As a result, the estimated
release of contaminants to the air is independent of the estimated contaminant
release to the subsurface and surface water.
MULTIMED utilizes.analytical and semi-analytical solution techniques to solve
the mathematical equations describing flow and transport. The simplifying
assumptions required to obtain the analytical solutions limit the complexity
of the systems that can be represented by MULTIMED. The model does rot
account for site-specific spatial variability, the shape of the land disposal
facility, site-specific boundary conditions, or multiple aquifers and pumping
wells. Nor can MULTIMED simulate processes, such as flow in fractures and
chemical reactions between contaminants, which can have a significant effect
on the concentration of contaminants at a site. In more complex systems, it
may be beneficial to use MULTIMED as a "screening level" model that would
allow a user to obtain an understanding of the system. A numerical model
could then be used if there are sufficient data and necessity to justify the
use of a more complex model.
1.1.1 Model Capabilities
During the development of this model, emphasis was placed on the creation of a
unified, user-friendly software framework, with the capability to perform
uncertainty analysis, that can be easily enhanced by adding modules and/or
modifying existing modules.
To enhance the user-friendly nature of the model, separate interactive
preprocessing and postprocessing software has been developed for use in
creating and editing input and In plotting model output. The pre- and
postprocessors, PREMED and POSTMED, have not been Integrated with MULTIMED
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because of the size limitations of personal computers. Therefore, after using
the preprocessor to create or modify input-, the model is run in batch mode.
Afterwards, the postprocessor can be used to produce plots of the Monte Carlo
output or plots of concentration versus time for transient outpu...
The fate of contaminants critically depends on a number of media-specific
parameters. Typically, many of these parameters exhibit spatial and temporal
variability as well as variability due to measurement errors. MULTIMED has
the capability to analyze the impact of uncertainty and variability in the
model inputs on the model outputs (concentrations at specified points In the
multimedia environment), using the Monte Carlo simulation technique.
The major functions currently performed by this model include:
•	Allocation of default values to some input parameters/variables.
•	Reading of the input data files.
•	Echo of Input, data to output files.
•	Derivation of some parameters, if specified by the user.
•	Depending on user-selected options:
simulation of leachate flux emanating from the source
simulation of unsaturated zone flow and transport
simulation of saturated zone transport only computation of in-
stream concentrations due to contaminant loading assuming
complete interception of a plume in the saturated zone
computation of the rate of contaminant emission from the waste
disposal unit into the atmosphere
simulation of dispersion of the contaminants in the atmosphere
•	Generation of random input values for Monte Carlo simulations.
•	Performance of statistical analyses of Monte Carlo simulations.
•	Writing the concentrations at specified receptors to output files
for deterministic runs. In the Monte Carlo mode, writing the
cumulative frequency distribution and selected percentiles of
concentrations at receptors to output files.
•	Printing the values of randomly generated input parameters anc! the
computed concentration values for each Monte Carlo run.
1.1.2 Interaction Framework (AIDE1
The pre- and postprocessor for MULTIMED have been developed using the ANNIE
Interaction Development Environment (A1DF.) (Kittle et al., 1989).	Consequent-
ly, the construction of input and the analysis of output is standardized in
terms of screen formats, movement within and between screens, and methods of
entering data, seeking on-line assistance and invoking commands.	A full
explanation of the conventions used is provided in Section 3.
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1.2 APPLICATION Or KULTIMED TO SUBTITLE D LAND DISPOSAL FACILITIES
The U.S. EPA has developed several restrictions for Subtitle D applications of
MULTIMED. These restrictions were made in an effort co develop a conservative
approach for simulating leachate migration from Subtitle D facilities.
•	Only the Saturated and/or Unsaturated Modules may be active in
Subtitle D applications, because the Surface Water, Landfill and Air
Modules have not been sufficiently tested at this time.
•	Although MULTIMED can simulate either steady-state or transient
transport conditions, only steady-state transport simulations are
allowed for Subtitle D applications. No decay of the source term is
allowed; the concentration of contaminants entering the aquifer
system must be constant in time. The contaminant pulse is assumed
continuous and constant for the duration of the simulation.
•	The receptor must be located directly downgradient of the facility,
so that it intercepts the center of the contaminant plume. In
addition, the contaminant concentration must be calculated at the top
of aquifer. Therefore, the angle from the plume centerline to the
receptor and the vertical distance to the receptor roust be specified
as zero in Subtitle D applications.
Thus, MULTIMED can be applied at many Subtitle D land disposal facility sites
to simulate the transport of contaminants from the source, through the satu-
rated and/or unsaturated zones by groundwater, to a receptor (i.e., a well)
UTien MULTIMED is used in conjunction with a separate source model, such as
HELP (Schroeder et al., 1984), it can be used In a variety of applications.
These applications include 1) development and comparison of the effects of
different facility designs on groundwater quality, 2) prediction of the
results of different types of "failure" of the landfill, and 3) if leachate
migration into the groundwater below an existing waste disposal facility
occurs, prediction of the fate and transport of tht contaminants in the
subsurface. The user should bear in mind, however, that MULTIMED may not be
an appropriate model for application to some sites. This issue, which is
discus.ed in Section 5.1, should be considered before modeling efforts
proceed.
As stated above, MULTIMED can be used in the design process to demonstrate
that a particular design will adequately prevent contaminant concentrations in
groundwater from exceeding health-based thresholds. In o.ther words, MULTIMED
combined with a source model can be used to demonstrate that either a landfill
design, or tne specific hydrogeologic conditions present at a site will pre-
vent the migration of significant quantities of contaminants from the land-
fill. Procedures have been developed for the application of MULTIMED to the
design of Subtitle D facilities. These procedures are outlined In Section
5.2.4 and are briefly summarized here.
•	Collect site-specific hydrogeologic data
•	Determine the contaminant to be simulated and the active modules In
MULTIMED and the point of compliance
•	Propose a landfill design and determine the corresponding infiltra-
tion rate
3

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•	Run MULTIMED and calculate the dilution attenuation factor (i.e., the
factor by which the concentration is expected to decrease between the
landfill and the point of compliance)
•	Based on the resulting dilution attenuation factor, determine whether
the design is acceptable
1.3 REPORT ORGANIZATION
This report contains the information needed to apply MULTIMED, In conjunction
with another model, such as HELP (Schroeder et al., 1984 a and b), to Subtitle
D land disposal facilities. Section 2 contains information about installation
and execution of the code. In Section 3, general information about the format
and operation of the pre- and postprocessors Is provided and Section U de-
scribes how to use the pre- and postprocessors for Subtitle D applications of
the model. Section 5 discusses the development of a conceptual model for
Subtitle D applications, the limitations and capabilities of MULTIMED, and
details about the input required to run each model module. Help in estimating
some of the model parameters Is contained In Section 6. In Section 7, appro-
priate example problems are included. Finally, contained in Appendices are 1.)
detailed Information on the structure of the code and the format of data In
the input files, and 2) a listing of the subroutines in the code.
\.k HOU TO USE THIS MANUAL
This application manual for the MULTIMED model and its pre- and postproces-
sors, PREMED and POSTMED, is designed to be used by inexperienced as well as
experienced users. Instructions are suggested for two types of Inexperienced
users: the "hands-on. learn-as-you-go" user and the "read the document first"
user, as well as for the experienced user. An experienced user is defined as
one who Is already familiar with the basic capabilities and operational
aspects of PREMED, MULTIMED and POSTMED, and wants to use the programs to
perform simulations. These Instructions are based on a similar set of
Instructions found in Imhoff et al. (1990).
"Hands-on. Learn-as-vou-po" Users
1.	Read Sectior, 2 for instructions on model installation and execution.
2.	Install PREMED, MULTIMED, and POSTMED. Execute the tests provided
with the code and/or described in Section 2 to verify that PREMED and
POSTMED are properly installed.
3.	From the DOS operating system, execute PREMED by typing  (do
not type the brackets). The opening screen will appear. Utilize one
of the two tutorials by typing either <@DETER.L0G> for a determi-
nistic Subtitle D application or <(3MONTE. LOO for a Monte Carlo
Subtitle D application.
A. Use the completed input sequence generated by the selected tutorial
to run MULTIMED. The input sequence created by the <@DETER.LOG>
tutorial is the same as that used in Example 2 in Section 7. The
input generated by the <@M0NTE.L0G> tutorial corresponds to Example 3
in Section 7.
t»

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5.	Examine the output generated by the MULTIMED model. Because new
versions of MULTIMED may be released after publication of this
document, the output may not be identical to the output shown in
Section 7. Therefore, compare the output generated by MULTIMED with
the appropriate output file provided with the code. This will allow
you to verify that the MULTIMED model Is properly insralied.
6.	Try the other example problems described in Section 7 to become more
familiar vith KULTIMED.
7.	Practice producing plots using POSTMED and the SAT1.0UT file genera-
ted when the Example 3 input is run.
8.	Proceed with suggestions 2 through 5 provided below for 'experienced
users."
"Read the Documentation First" Users
1.	Read Section 1 to familiarize yourself with the basic capabilities
and framework of the MULTIMED model. If you need more detailed
information on the capabilities and limitations of MULTIMED to
determine if the model will be suitable for your needs, read Section
5.1.
2.	Read Section 3 which discusses the format and basic operation of the
preprocessor, PREMED.
3.	Read Section 2 for instructions on model installation and execution.
U.	Install PREMED, MULTIMED, and P0ST!IED. Execute the tests provided
with the code and/'ir described in Section 2 to verify that PREMED and
POSTMED are properly Installed.
5.	From the DOS operating system, execute PREMED by typing  (do
not type the brackets). The opening screen will appear. Utilize one
of the two tutorio-s by typing either <@DETER.LOO for a determines
tic Subtitle D application or <@M0NTE.L0C> for a Monte Carlo Subtitle
D application.
6.	Section U discusses the use of the pre- and post-processor. Read
Section 4.1 in conjunction with the tutorial to provide a complete
description of PREMED.
7.	Use the completed Input sequence generated by the selected tutorial
to run MULTIMED. The input sequence created by the <@DETER.LOG>
tutorial is the same as that used in Example 2 in Section 7. The
input generated by the <@MONTE,LCG> tutorial corresponds to Example 3
in Section 7.
8.	Examine the output generated by the MULTIMED model. Because new
versions of MULTIMED may be released after publication of this
document, the output may not be identical to the output shown in
Section 7, Therefore, compare the output generated by MULTIMED with
the appropriate output file provided with the code. This will allow
you to verify that the MULTIMED model ts properly installed.
5

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9. Try che other example problems described in Section 7 to become more
familiar with MULTIMED.
10. Practice producing plots using POSTMED and the SAT1.0UT file genera-
ted when the Example 3 input is run.
31	Proceed with suggestions 2 through .5 provlJed below for "experienced
users."
Experienced Users
1.	Read Section 2 and Install PREMED, MULTIMED, and POSTMED. Execute
the tests provided with the code and/or described in Section 2 to
verify that PREMED and POSTMED are properly Installed, and execute
the test run for PREMED.
2.	Read Section 5.2 which discusses applying MULTIMED Co Subtitle D
facility problems. Refer to Section 5.1, which Includes a discussion
of issuer related to conceptualization of the system, and the capa-
bilities and limitations of MULTIMED, as needed.
3.	Read Section 6 as needed to estimate parameters required by MULTIMED.
4.	Try using MULTIMED to simulate actual scenarios.
5.	If you wish to make changes to input files without using the prepro-
cessor, refer to Appendix A which discusses the format for input
flies.
Obtaining MULTIMED Software
The MULTIMED computer code may be obtained by sending a request to: Model
Distribution Coordinator, Center for Exposure Assessment Modeling, Environmental
Research Laboratory, U.S. Environmental Protection Agency, Athens GA 30605-2720.
The req ett should include either five 5.25-in (double-sided, double-density,
DS/DD 360Kb) diskettes or two 3.5-in (double-sided, high-density, DS/HD 1.44KB,
error free) diskettes. The MULTIMED code will be copied to the diskettes and
returned.
6

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SECTION 2
PROGRAM INSTALLATION AND EXECUTION
This section describes how to install and test MULTIMED and the related pre-
and postprocessor software on the user's computer. Hardware and software
requirements are discussed. Exact details of installation are included with
the software when it is distributed by the EPA Center for Exposure Assessment
Modeling (CEAM) at the Environmental Research Laboratory in Athens, Georgia.
If problems are experienced, the user should contact CEAM for support.
2.1	SYSTEM REQUIREMENTS
2.1.1	Hardware
MULTIMED and the related pre- and postprocessors, PREMED and POSTMED. were
designed to be used on an IBM-PC compatible computer. The PC must have 6A0 KB
of rcer.-.ory, a math coprocessor, and approximately 4 MB of fr«.e disk space.
Additional machines which should run the software include Digital Equipment
Corporation VAX computers running the VMS operation system, Prime 50 Series
computer running PRIMOS and Sun Microsystems workstations running UNIX.
Contact CEAM for details.
2.1.2	Software
MULTIMED and its related software are written in FORTRAN 77. If compilation
of the code is required, a FORTRAN compiler and linker are needed. In addi-
tion, compilation of the preprocessor, PREMED, and postprocessor. POSTMED,
requires the use of ANNIE-IDE software (Kittle et al., 1989), which is avai-
lable from CEAM. Graphics in the model postprocessor use the ANSI Graphical
Kernel System (GKS). If the graph features of the postprocessor are to be
used, then GKS device drivers are required for the user's output and Input
devices. Consult CEAM for additional information about obtaining these device
drivers.
2.2	LOADING THE EXECUTABLE CODE
Included with the distribution media for MULTIMED and its related pie- and
postprocessing software is a README.1ST document and file that provides
detailed instructions for installing the programs. It is recommended that
data files be maintained in directories separate from the code.
2.3	EXECUTING AND VERIFYING TEST SESSIONS
Sample input data files and the related output files are distributed with the
model. In order to test the installation of MULTIMED, the user should run
these example problems and compare the output generated by the code with the
output files supplied with the crde. The code is executed on a PC by typing
MULTIKEIXCR> ( is the enter key). The model will query the user for the
name of the input file and the name of the file to which output should be
written. Be careful not to overwrite existing output files.
7

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In order to test the Installation of the preprocessor, perform the following
check. First, execute the program (on a PC type PREMEDMFURRYRY
Note that  is the F2 function key. The screen in Figure 2.1 should appear
on the display screen. To return to the operating system, type the key R.
The best test of the installation of the postprocessor is to plot the results
of the Monte Carlo simulation distributed with the model. The output file is
called EX3SAT1.0UT. First, execute the program (on a PC type POSTMED).
Next, for plotting results to the screen type the following sequence of keys:
DEX3SAT1.0UTP
A cumulative frequency plot will appear on the computer screen. This plot
should be the same as the cumulative frequency plot found in the main ouLput
file for the same problem. After examining the plot, press the Escape key,
Esc, to clear the plot from the screen. To return to the operating sy.sterr.,
type the key R.
For computers without graphics capabilities, the following check can be
performed. After executing the program (on a PC type POSTMED), type the
following sequence of keys:
DEX3SAT1.0UTS
At thJs point, hit Che down arrow key once, then type PRP. The cumulative
frequency plot will be sent to the printer. After the plot has been sent,
return to the operating system by typing the key R.
If there is a problem with any of the three software components of KULTIMED,.
review the installation instructions carefully before calling CEAM for
support.
8

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mo.cos to ntma, iaa wmaiw ra* mtims 
Tw« 'Brm.lOS' far • datanrinUtle ifpltcatlan Marlal, w
'¦om.UB1 for • acnu carta implication tutorial


t*l*Ct «l aptltnf


UaauU HAT 1MB Nadal
Mm to iparatlni iy>M


|-«t*TW
¦dfttaa • m« 'Ha
Iffllutln typat lubtltla • landfill
¦canarlai Unaaturatad and laturatad In aadria


•alaat an aptlm ualna arrau kaya
than Mftf Ira Niaaiia) iridi Ow n Uy, w
Typa tka Ifrat I attar af an aptlan.

m„n »*un fei.t.B **>¦ M
Flgura 2.1 Praprocaaaor aeraan after lnatallaclon.
9

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SECTION 3
FORMAT AND OPERATION OF THE PRE- AND POSTPROCESSOR
A pre- and a postprocessor, PREMED and POSTMED, have been developed for
MULTIMED in order to improve the ease with which input can be created and/or
edited and output can be analyzed. The pre- and postprocessors have been
developed using the ANNIE interaction Development Environment (Annie-IDE)
(Kittle et al., 1989). Consequently, user interaction within the program is
standardized in terms of screen formats, movement within and between screens,
and methods of entering data, seeking on-line assistance and invoking com-
mands .
Two tutorials are distributed with the preprocessor (see Section 4.1.3 for
information about running the tutorials). These tutorials familiarize the
user with the operation and features of the preprocessor and are recommended
for new users. Although no tutorial exists for the postprocessor, its format
and operation are Identical to that of the preprocessor.' To complement the
tutorials, the format and operation of the screens are described in detail
below. The summary is taken, with minimal adaptation, from the manual for
another Annie-IDE application, called DBAPE (Imhoff et al., 1989).
3.1 SCREEN FORMAT
Figure 3.1 defines the basic layout of a preprocessor screen. The layout is
consistent for all screens used by PREMED, with specific kinds of informscion
always located at the same region of the screen. Screen information is
divided into four components: three windows (data window, assistance window,
instruction window) and the command line. For convenience, the dimensions,
content, and important features of the four screen components are summarized
along the periphery of the screen area in the figure.
3.1.1 Data Window
The top portion of the screen is the data window. The data window contents
consist of one or more of the following.
(1)	Prompts for user-supplled decisions by means of menu selection
(2)	Prompts for user-supplied data by means of form fill-in
(3)	Echoes for current state of data
Two user-controlled sizes for the data window are used. In the default
layout, the assistance window is not displayed, resulting in a two window, one
comraandllne screen (see Figure 3.2 for example). If the user desires any of
the forms of assistance described In Section 3.1.2, then the data window is
reduced in size to accommodate the assistance window (see Figure 3.3).
Conversely, the assistance window can be eliminated from the screen, thus
expanding the data window, by invoking the QUIET command (). The pre- and
postprocessors accommodate up to 50 lines of data and enable scrolling In the
10

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MUMMI
lllil (•«»(
i mm fitiM m lima on Murui hot
m matnm a* ««• manasi
I MlM MTHM MOITMa IM HIM
n ¦ « port Mwufl mm ««v)
m mt« rut m mm
l« i «• nn i
• ub m m <
r-iwvwcYiai mm firu-
Mill "alUlf
mlua
TmHTS i ¦ m
mm i
•wan ifit4
cans* i iMMtra monam m mmm
WAMn,miHi mm mu
m» • irniiB an wtivraca rai ac
OHM • MflttTIQi m tMiumt COOM
vuun • mam m tomnma «un
mm - ma rb §m mutu
Mllfl
axm «* i
mnicai inwa
umgi^rag|
muiwiiT ¦ i
MUM 
-------
-Cpanlna icrM»-
MICM 19 Htm, T< WMam rat NJLTIW (««rilon 1.0)
Typ* 'SDTH».UX' for • fettralnUtlc tutorial, w
'¦ttTl.lK1 far • Mi ear la loatlan tutarltl
Ulact an option?
Amlyia Mdil raaulU
LucuU MJLlim Nodal
latum ta aparatlna ayttaa
—IWTtUCT-
lalact an apt Ion win) arrow Uyi
tfxn cviflra aalactlan altti tfca tt tar,
rypa tha flrat lattar o* an optlan.
KalfuQ laitiB Kpadig Cm*
Flfur* 3.2 buopl* of a Ore window, ona oovundlliva tcraan.
12

-------
i-Cpanlnt atraaw
HUM TO MUD, !¦ PtMKItm M> MJLTIMD (mlw 1.0)
Tyf» 'MTU.LOS' far • tfatanlnlatla alpllutlan tutorial, or
•aani.LOC' for • mu urlo application tuter 1*1
taloet an eptlenT
lucutl NULTIMS Nodal
latum (• aporatlnf iyim
i-4TATU>
Ultliw • rm III*
Application typoi tubtltl* D landfill
Icanarloi Ikoaturatad and Utiratad bra aodala
•-iitTiueT	
talKt m option uslnp mtcm kaya
than ocnflra aoloatlan wltk tko Ukay, or
Typa Dm flrtt tattar af in eptlsn.
Mlpill »a»l|fl| ItatuaiP artwiR «podi|| t*rd Orp»	
Flgur* 3.3. Luapli of « tbxao window, on* cocmandllna tcraon.
13

-------
data window by using cursor keys when Che data size exceeds the window size.
The title of the window and a series of one letter codes which identify the
sequence of screens which have led up to the current screen is displayed on
the upper left hand border of the data window. Further explanation of the
"screen path" feature is provided in Section 3.3.3.
3.1.2 Assistance Window
Several types of user assistance are available within the pre- and postproces-
sors. A layered approach to assistance is used as follows.
(1)	Use of descriptive and unique words or abbreviations for field
or menu option names in the data window always provides
"first-cut" definitions.
(2)	When space allows, additional information in the data window
near the data field or menu option clarifies the desired
information.
(3)	If additional parameter- or screen-specific assistance is
available, it is supplied, upon request by the user, in the
assistance window. Two types of screen-dependent assistance
can be displayed in the assistance window: HELP and LIMITS.
(4)	If assistance of a global nature (i.e., independent of indi-
vidual screens) is available, it, also, is displayed in the
assistance window upon request by the user. The three types
of global assistance which can be displayed in the assistance
window are CMND, STATUS and XPAD.
The layered "help" in PREMED and POSTMED is designed so that the user must
specifically request the higher levels of assistance; consequently, experi-
enced users are not subjected to unnecessary information.
As specified above, the assistance window, which is located directly below the
data window (Figure 3.1), Is used to display the more detailed levels of
assistance (HELP, LIMITS, CMND, STATUS and XPAD). All types of detailed
assistance are further described later in this section. The user selects one
assistance type at a time and the available assistance of that type is
displayed in the assistance window. The title of the window (i.e., HELP,
LIMITS, CMND, STATUS or XPAD) is displayed on the left portion of the upper
border for the window and corresponds to the type of assistance which has been
requested by the user. The types of assistance which are available for a
particular screen are Indicated by the options listed in the command line
(Section 3.1.A). If the amount of available assistance exceeds the window
size, scrolling in the window by using cursor keys is allowed.
An example of screen layout for a three-window screen is shown in Figure 3.3.
Details on each of the assistance types which may be displayed within the
assistance window follow.
14

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HELP
HELP assistance provides further information on model and system parameters
and menu options (see Figure 3.4). As noted above, HELP text is specific to a
particular screen and can be scrolled in the assistance window.
LIMITS
LIMITS displays the allowable values for a specific field in the data window.
LIMITS information may be (1) maximum and minimum acceptable numeric values or
(2) a list of acceptable alphanumeric values. LIMITS text is specific to the
field currently highlighted in the data window, and it, also, can be scrolled.
Figure 3.5 shows the type of information displayed in the assistance window
when LIMITS has been selected.
CMND
CMND displays the names and definitions of all active commands at the current
location. The command definitions never change. It should be noted, however,
that the list of available commands varies according to location within the
program. For example, the STATUS command is available only at certain program
"levels." CMND text can be scrolled in the assistance window.
STATUS
STATUS assistance displays system status messages that summarize previous
actions and indicate the relative location of the user within the program
structure. A maximum of 10 lines of STATUS assistance may be viewed by the
user at any point within an application; STATUS assistance cannot be scrolled.
Figure 3.6 illustrates the type of information disvlayed in the STATUS
message. The st '^en contains the following information.
(1)	Whether a file is being created or edited. If editing an
existing file, the file name is given.
(2)	The type of application (i.e., a generic model application or
a Subtitle D application).
(3)	The scenario being modeled (i.e., the MULTIKED modules which
have been selected by the user).
XPAD
Scratch pad (XPAD) assistance allows the user to write notes and reminders
during an interactive session. The user may record information in a single
XPAD with a maximum width of 78 characters and length of 10 lines. Regardless
of where the user is located within the interactive session, a request for
XPAD assistance will call up the same XPAD with the same information. XPAD
information in the assistance window can be scrolled. New notes can be added
to existing notes, and existing notes can be overwritten.
3.1.3 Instruction Window
The instruction window is always present on every screen. In the screen
layout, it is located below the data and assistance windows and directly above
15

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rtorural (UKH
ttotfHy 4t*tiUl» of a KELP *«*lat*nc« window.
16

-------
ritiurmd (imu	
lit kplfRillc conduct Icmflw)
Ui«t It ttM nay vtlvjaT MB
r-ClMllt
Oafaulti ran*
Nlnlauw S.lOOat-10 Aula
0. IOOO£+«
HOtfWCT-
bittr dtt* In	fltlilCal.
uat urrlava nrturn or mrnm key* to «nt*r 
-------
(—0«r*r»M (&60)	—¦———¦				
Till* <2 I Inn)
tfflKB
CAM
Option? onUUtlllTlC rrtn*(*nt or Uaadrltata cult IT£A0T-2UT(
Actlv* vdula • lurfaca Hlir MD	*lr	NO
Unaat. tona rtl	Landfill 10
lituritid >on» Tff
,-tuna
Idlilng mii.lrp
Application typo tubtltla ft landfill
¦canrigi unaaturacad M laturatad Ion* Mdala
r-1 W1CUCT	
tatar data In M|hlltfitad flald.
U*a carrltta raturn ar arrow kaya ta antar data and aova faatvaan flalda.
Uaa *laxt' caaaand to as to nact tcraan Hhan dona Marina data.
lalpiQ lutiQ (.taltaiQ ttatuaiQ aulatijf XpadiQj M Oepa
Ft (jura 3.6. Exjiapl* of lnforaaelon contained In a, STATUS ajalatanca window.
18

-------
the command line (see Figure 3.1). Two types of Information are provided In
the window: instructions for the user's next keystroke or error messages
reporting incorrect keystrokes with instructions fir corrective actions.
Depending on which type of information is displayed by the system, the window
title on the screen will be either "INSTRUCT" or "ERROR." Figure 3.5 gives an
example of the type of information commonly provided in an INSTRUCT-type in-
struction window, and Figure 3.7 illustrates an ERROR-type instruction window,
3.1.6 Command Line
The final component of the standard pre- and postprocessor screen is the
command line (Figure 3.1). The command line is restricted to one line. It
contains a menu of abbreviations for the available commands at the user's
current location within the program structure. Definitions of the abbreviated
commands are available by invoking the CMND assistance in the assistance
window.
Table 3,1 lists the commands available in PREMED, the function keys used to
invoke commands, and command definitions. Inspection of the command line in
Figure 3.1 shows that some of the commands are associated with the PC func-
tions keys and some are not. Instructions on the alternate methods for
invoking the various commands are provided in Section 3.3.
A final feature of the command line is mentioned here to avoid confusion. As
will be explained in the following section, three interaction modes can be
utilized: data mode, command mode, and assist mode. The command line appears
on the screen when the user is utilizing either the data mode or the command
mode. When the user has invoked the assist mode, the command line is removed
from the screen to avoid confusion, and command instructions are displayed in
the instruction window. When the user leaves the assist mode to return to
either of the other two modes, the command line reappears.
3.2 INTERACTION MODES
User interaction is organized into three "modes," each with a specitic
function:
(1)	Use data mode to enter data or select from menu options in
data window.
(2)	Use command mode to invoke commands or functions listed in the
command line; commands perform three functions:
(a)	Allow exit from screens (NEXT, PREV).
(b)	Manage assistance window (HELP, LIMITS, XPAD, STATUS,
CMND, QUIET).
(c)	Manipulate data window (OOPS).
(3)	Use assist mode to provide supplemental information in the
scratch pad (XPAD) on which to base subsequent actions or to
scroll up or down in the assistance window.
Note that most tasks performed will only require use of the data and command
modes.
19

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ft^iffar Uiletaww <¦>


U« I* th# mh mlutf HQ



Idltlng tMtt.lnp
Application rypti Ufetltl* o landfill
Se*n»rt»i Uhuturattd and ItturMid Zona aodiU



Invalid dita Input Inb1*ll*tad fl*M.
Um 'Haiti' raMnd t* acuptabl* rangt, or
'¦alp' coaand U Mt ftald dtflnlllan.

¦uttB l.la
-------
TABLE 3-1. COMMANDS FOR APPLICATION OF PREMED
Command
Name
CMND
Function
Kev
Command Definition
Display definitions of commands in assis-
tance information window
DNPG
HELP
LIMITS


Display next page in data window.
Display HELP information in assistance
information window
Display limits of current field in assis-
tance Information window
NEXT
OOPS
PREV
QUIET



Go to next screen (sets screen exit status
code to 1}
Reset data values in data window to values
when screen was first displayed
Go to previous screen
Turn off assistance information window to
allow more- room for data
STATUS

Display system status in assistance infor-
mation window
XPAD

Display users scratch pad, allow changes
Movement from each of the interaction modes to the other modes can be accom-
plished as follows.
data mode to command mode
data mods to assist mode
press  key
press function key associated with
appropriate type of assistance or
enter command mode and select appro-
priate assistance from options in
command line
command mode to data mode
command mode to assist mode
assist mode to data mode
assist node to command mode
3.3 SCREEN MOVEMENT
press  key
select appropriate type of assis-
tance from options in command line
preas  key
press <6 8c> key twice (goes through
data mode)
Commands may be invoked either by pressing designated function keys or by
typing the first letter of a conmand name. Likewise, menu options may be
21

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selected either by moving the cursor to the selection field and confirming, or
by typing the first letter (or letters, if needed) of the menu item.
Several general features of user communication should be noted:
(1)	There are no restrictions to upper- or lower-case mode.
(2)	A key or command is always used to invoke the same function.
(3)	Function keys are only used to invoke commands.
3.3.1 Movement Within Screens
Movement within screens may consist of (1) movement between interaction modes,
(2) movement between the three windows and the command line, or (3) movement
within a window or command line. The first type of movement, between inter-
action modes, has already been described in Section 3.2 and will not be
further considered here. Procedures which cause movement within and between
the three windows and the command line of a screen are outlined below. For
organization, the procedures which cause movement are categorized in terms of
the three interaction modes.
Data Mode--
In data mode, screen movement and operations may be accomplished by pressing
either printable character keystrokes, the  or  key, the cursor
keys or selected function keys. However, the result of pressing some of these
keys depends on the type of screen which Is presently displayed.
If one is prompted for decisions by means of a menu (i.e. a menu screen),
keystrokes cause the following results.
(1)	Type the first letter (or more, if needed) of any option in
the menu in order to select the option.
(2)	Use cursor keys to move between highlighted menu options.
(3)	Press function keys designated on the command line to invoke
the following commands.
 - HELP  - NEXT  - PREV  - XPAD
If one is prompted for data by means of form fill-in (i.e., a data screen),
keystrokes cause the following results.
(1)	Type alphanumeric characters needed to correctly fill in the
data screen; the characters will be inserted in the screen at
the cursor position.
(2)	Press  or  to end entry in one data field and
move to another,
(3)	Use cursor keys to move within and among data screen fields as
needed.
(4)	Use function keys to invoke the following command functions.
22

-------
 - HELP  - NEXT  - PREV  - LIMITS
 - XPAD
Command Mode--
In che command mode, three categories of keystrokes cause movement within
screens.
(1)	All commands, with the exception of NEXT and PREV (see Section
3.3.2), cause movement within screens. Type the first charac-
ter of any of these commands to invoke the command and cause
activity in either the data or the assistance window. The
activity caused by invoking each command is summarized in
Table 3-1. As described In Section 3.1.2, the commands CMND,
HELP, LIMITS, STATUS, QUIET and XPAD cause activity in the
assistance window. The command OOPS, which resets values in
data screen to the values present when the screen was first
displayed, causes activity exclusively in the data window.
(2)	Press the  or  key to execute the command
currently highlighted in the command line.
(3)	Use the right or left cursor keys to move the highlighting Co
another command along the command line.
Assist Mode--
While the user is in the assist mode, keystrokes cause no actions whatsoever
unless (1) the scratch pad (XPAD) is active or (2) information which can be
scrolled is contained in the assistance window. If the scratch pad is active,
typed characters are inserted into the scratch pad at the current location of
the cursor. Thd cursor can move in all directions, and pressing the 
or  key causes the start of a new line. Cursor keys can be used to
scroll up or down in any assistance window when the available assistance
exceeds the window height,
3.3.2 Movement Between Screens
A user can leave one screen and move on to another either by (1) selecting a
menu option in the data window or (2) Invoking commands displayed on the
command line.
Menu Options--
Selection of a menu option always leads to a new screen. From the data mode,
menu selections can be made by one of two methods.
(1)	Type the first letter (or letters, if needed) of the menu
item.
(2)	Move che cursor by use of cursor keys to the selection field
and confirm by typing  N.
23

-------
Command Options
Invoking either the NEXT or the PREV command results In movement to another
screen. From the command mode, command selections can be made by one of three
methods.
(1)	Type the first letter of the command.
(2)	Move the cursor by use of cursor keys to the selection field
in the command line and confirm by pressing .
(3)	For commands which are associated with a function key (as
Indicated in the command line), press the appropriate function
key.
3.3.3 Screen Path
During an interactive session, an aid is provided for remembering the sequence
of screens which have led. up to the screen which is currently being displayed.
The screen path is connoted along the upper left hand border of the data
window following the window title (see Figure 3.7). The screen path Is a
series of or.; or two ?.e*:ter codes which Identify both (1) the type of opera-
tions and (2) the sequnuce of operations which have occurred from the time the
user leaves the opening screen until arriving at the current screen. For
example, a screen path "BCS" in the preprocessor signifies that the current
screen is a result of (1) selecting the Build option on the opening screen,
(2) opting to Create a new input file, and (3) selecting a Subtitle D applica-
tion.
As the user branches downward, a letter is added to the screen path each time
an operation is performed which results in the display of a new screen. The
letter corresponds to the first letter of the option selected In the pr_/ious
screen. In the case of some menus two letters are needed to differentiate
between options. In such cases, both letters are added to the screen path.
Conversely, upward movement, which is accomplished by using the Return option
in any menu, results in the elimination of a letter from the screen path.
It should be noted that familiarity with screen sequencing can also speed up
the time it takes to perform frequent tasks. After memorizing the screen path
needed to perform a sequence of operations and, hence, arrive at a particular
location in the program, one may type ahead and pass quickly over Intermediate
screens.
2 U

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SECTION 4
USE OF THE PRE- AND POSTPROCESSORS
The preprocessor, PREMED, allows the user to easily create an Input file for
use In MULTIMED. The postprocessor, POSTMED, provides a means of generating
graphs of concentration versus time and the results of Monte Carlo analysis.
Both of these programs are designed to be fully interactive and easy to use.
Many of the features and options available in the pre- and postprocessors are
discussed In Section 3.
4.1 THE PREPROCESSOR (PREMED)
4.1.1 Use of the Preprocessor
Before using the preprocessor, read the section on installation and execution
of MULTIMED (Section 2).
To execute the preprocessor, move to the directory which contains Che prepro-
cessor and type  (do not type the brackets). After a moment the
Opening screen will appear, as shown in Figure 4.1.
If you are unfamiliar with PREMED, it is strongly recommended that you utilize
the tutorials which are Included with the preprocessor. These tutorials can
be accessed from the Opening screen by typing either <@DETER.LOO or <@MON-
TE.LOO (do not type the bmckets). The tutorials are discussed in Section
4.1.3.
The Opening screen displays several options. At this time, only the Build/
Modify and Return (to operating system) options can be used. Currently it is
not possible to analyze model results or execute MULTIMED from the prepro-
cessor. You can analyze the results from Monte Carlo simulations using the
postprocessor, POSTMED. Viewing results or executing MULTIMED requires that
you return to the operating system.
You must use the Build/Modify option to create or edit an input file for
MULTIMED. Select this option by typing  (do not type the brackets). The
Build/Modify screen will now be displayed as shown in Figure 4.2.
From this screen, you may either create, edit, or save an Input sequence for
use in MULTIMED. If you select the Edit option (by typing ) you will be
prompted for the name of a preexisting input file (Figure 4.3). Type the name
of a file, and select the "Next" option by pressing  to continue with the
program.
If you select the Create option, the Create screen will be displayed. Figure
4.4 shows the Create screen. This screen displays options for either a
Cenerlc or a Subtitle D application of MULTIMED. Only Subtitle D applications
are discussed in this manual. Since it Is intended for regulatory applica-
tion, the Subtitle D application of MULTIMED restricts the options available
for simulation to those which have been thoroughly tested. Therefore, only
the scenario involving the Unsaturated Zone and Saturated Zones may be
25

-------
r-opantra acraan-
tCLCBM to mm. vm puncatsm rat uriMO (version i.o>
Typa ' awn*. LOO1 for • dataralnlatlc appl (cation tutor I tl, or
I.LOO1 lor • BOM* carta «ppllea11 on tutorial
Ml act «n option!
Analyta nodal raaulta
bacuta MTIICD Mod*I
Kfturn to gpirttlni ayataa
riitrtun		
Ml act an option ualnf trm kayo
than confirm Ml act ton Mitfe tha 12 kay,
Typa t>ia flrat lattar of an apt I on.
NalpiQ NaxtiQ XpadiQj Caid
Flgur* 4.1. OpanLng aeraan of tha praprocaaaor.
26

-------
(-•uMd/Hodl/y-
tatlch lulld/Modlfy option?

Idle mi ultilnp Input Mquanca
lev* porMotor* on o fll*
koturn to Qpanlng Icroon
—IMITtyCT-
Sotoct «n option uilnf arroM toy*
than confIra aoloctlon ultt tfto M tiy,
Typo tho flrtt lotm of in option.
NdpiQ M«xtiQ xpodi|| Qnd
Figaro 4.2 Bulld/Kodlfy icroon of tho proprocaaaor.
27

-------
rIMTWei	
tntar diti In k10ill|M*4 flaldta).
Um carrliga ratum or rrw luyt t» «nt«r diti and ww* htwin flald*.
Vm 'Rut' toaand to ie to nut Krwn ifan don* vittrlnt dit*.
«alpi|| awt>B oravtB Maluifli Xpadifil Omd C**»
Figura 4.3. Edit «er««n of th« praproeaaaor.

-Crtitt (W)


Uut typt of ippHcatlen do you Mnt to craaUT


Gamrlt
BKEBBEBMBBBI


plMtaKT ——	—	—I
talaat m option mini arron k«ya
than canffra MlKtlen tilt* ttM FJ kat, or
Typa tha flrat lattar af an aptlin.

MiitiS *r«vi|| Xpadiflj tad
Figura 4.4. Craata accaan of tha praprocaaaor:
28

-------
executed, and the Landfill, Surface Water, or Air Modules may not be used.
Furthermore, the Subtitle D-speclflc applications may only be run In steady-
state mode.
The next screen which will be displayed by PREMED is the General-1 (BEG)
screen. This screen allows input of information in the General Data group.
Figure 4.5 shows the appearance of the General-1 screen when the user has
chosen to create a Subtitle D input sequence. If a Ceneric application is
selected on the Create screen, then the default values on the General-1 screen
will be different.
The Run Title is allowed a maximum of two lines. You may use any title for
your simulation that you want. In Subtitle D applications, the Run Option may
be either deterministic or Monte Carlo, but the simulation must be run ir,
stendy-statc. Factors which should be considered when selecting these options
ore discussed in Section 5.
The various modules in MULTIMED which will be active in the simulation must be
selected. The Subtitle D application may Include only the Saturated 7.one
and/or Unsaturated Zone Modules. The Saturated Zone Module should be used
alone only if the water table is located directly below the bottom of the
waste disposal facility. In all other cases, the effects of unsaturated flow
and transport from the bottom of the facility to the water table cannot be
considered negligible, and the Unsaturated Zone Modules should be included in
the simulation. At this time, the other modules shown in Figure 4.5 (Surface
water, Air and Landfill) have not been sufficiently tested. Subtitle D appli-
cations must be run in steady-state, After the General-1 parameters have been
specified, press  for "Next" to move to the next screen.
If the Monte Carlo option is selected, the Ceneral-1 (BEC) screen will be
followed by the General-2 (BEG) screen (Figure 4.6). This screen requires the
following input: the number of Monte Carlo simulations, the desired output
from the model, and the confidence level (in %) for the 80th, 85th, 90th and
95th estimated percentiles. Estimation of the number of Monte Carlo simula-
tions and confidence levels are discussed in Section 6.6. The amount of
output is related to the number of output files which are opened by the model
LOTS	- Opens all ".VaR" and ".OUT" files (i.e., writes the Monte Cailo
variables for each simulation and the corresponding output) and
the main output file.
SOME	- Opens only the main output file, "STATS.OUT" and "SAT1.0UT"
NONE	- Opens only the main output file and "STATS.OUT". Note that the
postprocessor cannot be used if this amount of output is selected,
since POSTMED requires the "SATl.OUT" file for the simulation.
After the General-2 (BEG) screen parameters have been set as desired, press
the  to move to the next screen.
The Edit (BE) screen will now be displayed as shown in Figure 4.7. This
screen allows access to Che nine data groups Included in MULTIMED. the
General, AQulfer, Air, SOurce, SUrface, Chemical, Funsat, Landfill and Tunsat
data groups. Not all of these data groups are required for a specific
simulation. For example, if the Air Module was not selected as an active
29

-------
r-Canaral-1 (BEG)	
Run lllll (2 Una*)
CAJf
*un Option? 0ETEAM1WISTIC Trana Iant	or ttaady-Stata caaa? STEADY¦S>AFE
Actlva oodulai Jurfaca uatar no	Air NO
Unaat. tone TEI	Landfill HO
Situratad ion* Til
pITATUS	
Editing taata.lnp
ApplIcat Ion typai Subtitle D landfill
Scanarloi Unaaturatad and Saturatad Zona Modal*
pIKITKUCT	
(ntar data In hl^illghtad flald(a).
Uaa carrltg* rtturn or arrow kay# to entar data and aova batwaan fi«lo».
Uia *
-------
Oantrat-2 (Ha)		—
It* aany Mont* Carlo (IwUtlarwf QQJ
low Mich output do you want from
aach Mont* Carlo rinT	(OMi
*AlPd- corif(danca I aval (In X) for
tha four attlaatad pareantllaa > 90.
p»TA rus	
Editing ¦ now fll*
Application typai Subtltla C landfill
Scanarlot Unaaturatad and laturatad Zona andala
ptUtTSUCT	:	
lour dot* In hlghllghtad flaldd).
Uaa carrlae* raturn or *rro* keys to artar data and ant batwaao flaid*.
u>a 'lUxt' cemmrd to go to nut acraan t*ian don* attarIng data.
Nalp:fJ NaitigJ 'ravtfg U«lt*:|J ttatuaiQ 0ulatif| ipad.fil Qand Oopa
Flgur* 4.6. Cener*L-2 acratn o£ th« pr«proc«»aor. This acreen la only
•ctlvatod If ch« almulaelon. Is run In Monc* Carle aoda.
i~«d(t CSC)	
Edit tiilch aodal paraaatarat
Raturn
Undaf
mmes
SJrfaea
flMtt
ftlWat
to lulId acraan
• llat indallnad data
Vy-!>«»rv
irot^i
turfata aatar paraaatara
iviaaturatad ten* flott
tmaturatod ion* tranaport
AOulfar aaturatad xona paraaatara
Air air dfaparalon paraaatara
(Ource contaminant aourca data
Chaatcal propartlaa of tontaalnant
Iwdflll propartla* definition
,-ITATU*	
Editing a nan fll*
Application typa: liAtttla D landfill
Icanarlsi Un*atur*tad and (aturatad Jon* aodtli
(-IHfTIUCT'
lalact an option u*lng arrou kaya
than conftra talactlon alth tha rz kay,
Typa tha flrat lattar of an option.
Hal pi It aa»t»tt itatuaiH CulttiH UpadiHI Card
Flgur* 4.7. The Edit acrean of tha praprocaaaor.
31

-------
module or the General-1 (BEG) screen, then the Air data group option on the
Edit (BE) screen does not need to be selected. To determine which parameters
are required for a particular scenario (i.e., combination of MULTIMED mod-
ules), refer to the section in the MULTIMED model theory documentation
(Salhotra et al., 1990) which describes the module.
The parameters in the General data group have already been specified on the
General-1 (and General-2) screens. However, if you wish to make changes to
this data group, type  to select this option.
The Undef option on the Edit (BE) screen lists the data groups which contain
undefined parameters. This option is selected by typing . The data groups
displayed contain undefined parameters which will need to be defined before
the input sequence is complete for use in MULTIMED. To return to the Edit
screen, press the  function key.
The other data group options on the Edit (BE) screen can be selected by typing
enough characters to make the selection ur.lque. For example, there are two
options which begin with "A", so if you wish to select the AQuifer data group,
you must type . Selection of a data group will be followed by a screen
which is specific to that data group, and contains a list of parameters nr
parameter groups which are contained In that data group.
Six data groups contain parameters which are used in simulations of Subtitle D
facilities: General, AQuifer, SOurce, Chemical, Funsat and Tunsat. The
General data group has already been discussed. The data group-spec Ific
screens for each of the other groups are shown in Figures A.8 through 0.12.
Each of these screens contains a Return (to Edit screen) option, and an option
to list Undefined parameters within the data group. Undefined parameters are
those which do not have a data value assigned to them. They are designated by
a -999 In the input file.
The rest of the options shown in the data-group specific screens are either 1)
parameter names or 2) sub-data groups which contain additional parameters.
For example, selection of the Type option on the AQuifer screen (Figure 4.8)
will be followed directly by a screen where a parameter value Is specified.
In this case, the Type of source for the saturated zone model is specified.
However, selection of the Depth option on the AQuifer screen will be followed
by another screen which contains several parameters related to the size and
particle characteristics of the aquifer: PArtlcle diameter, POroslty of
aquifer. Bulk density. Depth of aquifer and Mixing zone depth. You will need
to select one of these options to specify actual values for the parameters.
Any of the options may be selected by typing enough characters to make the
selection unique.
The specification of a parameter value is similar for all ot the parameters in
the data groups. Therefore, specification of the aquifer porosity will be
used as an example. The other parameters can be specified In a similar
manne r.
From Table 5-8, It can be determined that the aquifer porosity Is part of the
Depth and Particle Characteristics sub-data group which is part of the AQuifer
data group. Therefore, the AQuifer option should be selected from the Edit
(BE) screen by typing . PREMED will now display the AQuifer (BEAq) screen
as shown In Figure 4.8. This screen contains five sub-data groups: the Depth,
Type, Hydraulic, Misc and Times data groups. The aquifer porosity is included
32

-------
H»ulf«r (UAq)					
laIact in Aqulfar option.
Undaf	¦ IUI widifliwd p*r«Ml«r«
Doptfc	and part tela ckirKKrtiltci of
TTpa	of aourca for taturatad ton* Bodal
Hydraulic tnd dltpartlcn ralatad parmttrt
HIM	¦ twp*ratur*, pA, and organic carbon of aqulfar
W«l I	¦ wll-riltttd ptriMttM
flat*	at rfileA to caleulata concantratlona
rtHTM	
(dltln« • now fI la
Application typoi tubtltla 0 landfill
tcararloi Unaaturatad and taturatad Zona aodtU
pIMTIUCI	
lalact an option ualng arrou kayo
(Nan conflra aalactlon with tha fi kay, or
Typo tha flrat lattar of an option.
Halpiltf Maxtitt ttatuaiH aulatiBI Kpadiil Old
Tlgura 4.8. AQuifor acrsan of tha praprocaaaor.
33

-------
i-Murc* -
Select • Source option.
Ll«t praaent value*
llndef • Hit undeflnad parameters
{Iff 11 - fnfltcretfon ret*
Area of Miti dlapoaat utlt
Duration of pull*
tfrwd •< MAtalnm tourci
tCQierp* rata
SOurct dKiy canatarit
Ittltlel concentration
Itngth seel* of facility
Wldtti Kill of facility
r-STATW
Idltlng e new flit
Aj>pllcotlon typei tifctitlo D landfill
teener I«i Umaturatad and Saturated Zona aodale
rl*3I»UCT-
Salact an option using arrow key*
than confirm utactI on with tha fz kay.
Type tha flrat lattar of an option.
Mantitl ttatuaiHI OuUtiH ltpadtfj C»nd
Figure 4.9. SOurca screen of tha preprocessor.
r-tiiaalcal (BECi-
talact a Chaalcal option.
Undaf - 11 at wideflned paraaatara
Neaa • (pacify diaalcel to tot eodtlad
Pecey coefficients (eeltd, dluolvad, overall)
Kydrol • hydrolysis rat* constant* and rafarance twpereture
Coaff - various coefficient! and temperature for air diffusion
Hols • aslKultr definitions, wtut* rapor preature and Nanry'a constant
-STATUS—:	
editing a rw (lit
Application type! Subtitle D landfill
Scenario) Unsaturated and laturated Ion* aodala
H*»TIUCT-
lalect an option using arrow key*
than conflra salectlen with tha fZ kay,
Typa the Mrtt lattar af an option.
N.lpitt	St»tua:E)| Oulat:BI »padi|> Card
Figure	Chemical acraon of preprocessor.
34

-------
rflflMI (ifF»-
Wki an maturated flow pirwtif option.
Undaf - li»t mdaftnad paraaatara
Control paraaatar
Spatial dlteratliatlon piriaiiin
Material proper tin
national coefficients
I-STAIU*	
(dlttng • new fit*
Application types kfctltla 0 landfill
Scenarios Unsaturated and Saturated Zona aodels
rlHSTRUCT-
Salect m option using arrow keya
than corf1 r* talactlon with the rj key, or
Typa the flrat letter of an option.
Halpijf M*»tiH »tatua;Hf BulatiH Xpad:|jjf Omd
Figure 4.11. Unsaturated Flow (Funsat) screen of tha preprocessor
rTunaat (»ET)-
Salect an weatureted Tranaport paraaatar option.
Undaf - Hat undefined paraaatara
Control paraaatar
Property paraaatar*
l-ITAIUI	——	
tdltlng a new (lie
Application typat Subtitle 0 landfill
Scenario! Uneaturatad and Saturated Zona aodels
rIMST*UCT-
Select an option using arrow keys
than conflrai selection with tha 12 kay, or
Type tha firat (attar of an option.
	H»!p:H Meat iff Statuet)H Qulaufl Kpad iHf C**
Figure 4.12. VJnaaturated Tranaport (Tunaat) screen of the preprocessor.
35

-------
in che Depth (and particle characteristics of the aquifer) sub-data group.
Select this option by typing .
The Depth (BEAqD) screen will now be displayed. Figure 4.13 shows this screen
which contains five parameters for which values may be specLfied: rho PArtl-
cle, POrosity, Bulk, Depth, and Mixing. Select the POrosity option on ih^
Depth (BEAqD) screen by typing . The screens which follow this seleci in;,
will differ for the Deterministic and Monte Carlo simulations. Both types n'
simulations are discussed below.
Deterministic simulation:
Some of the parameters in MULTIMED may be derived from other para-
meters instead of being specified directly by the user. The aquifer
porosity is one of these parameters which can be derived. Therefore,
the Depth screen is followed by the POrosity (BEAqDPo) screen, shown
in Figure 4.14, which provides two options: 1) DerLve the aquifer
porosity value from other parameters in MULTIMED or 2) Specify the
value of the aquifer porosity. If the Derive option is selected,
PREMED will return to the Depth (BEAqD) screen. However, if che
Specify option Is chosen, the preprocessor will display che screen
shown in Figure 4.15. The value of the aquifer porosity should be
entered on this screen. After the porosity has been specified, pi-pss
 to return to the Size screen.
Monte Carlo simulation:
The screens which will be displayed for a Monte Carlo simulation are
Identical Co those for a deterministic simulation until the value for
a specific parameter is to be input. In a Monte Carlo simulation,
the probability density distribution for each parameter required by
MULTIMED must be specified.
In the example discussed above, when the POroslt> option is selected
from the Depth (BEAqD) screen, the screen which follows is shown in
Figure 4.16. The probability density distribution for the POrosity
is specified on this screen. It is very Important that the distribu-
tion selected adequately reflects the actual probability density
distribution for che parameter. A discussion of probability density
distributions is included in the MULTIMED model theory documo.i'.ta.. i r."
(Salhotra et al., 1990).
Each of che distributions requires that some characteristics of che
distribution be specified. For example, if a LOCNormal distribution
is selected for the POrosity, che minimum and maximum values, che
mean and che standard deviaclon are required, as shown in Figure
4.17. The requirements for the different distributions are discussed
i.i Section 9 of the MULTIMED model theory documentation (Salhotra et
al., 1990).
36

-------
r-Oapth (8EA*»	
lalact • Depth and Partlcta Charactarlttlca option.
PArtlcl*	dlMMttf
Mroalty	of Mfitfar
hlk	danalty
Oaptfc	of aquifer
Mining	too* depth
r-mTLK
editing • ntu file
Application typai Subtitle 9 landfill
Icmrloi Untaturatad vd Saturated Zona aodel*
—IHITKUCT-
Salact an opt
-------
r-POroa I ty (UAcpPo)'
Aqulfar porosity
Mo« do you want to daflne thlt paraaatarT
".VH	V*V:;T1
Specify tha value for this paraaatar
r—•TATU$-
Edftlng a mw flla
Application typai Subtitle 0 landfill
Scenario: Unsaturated and Saturated Zona aodala
r—IKITIUCT-
Salect an option using arrow kayi
than conflr* aalactlon with the F2 key, or
Typa the first lattaf of an option.
Figure 4.16
•lmulation.
Melp;Ej( iwnlH Pr«vi)M( Statuailf Oulatiti Xpedijl Card	
> 4.16. The POroslty screen of the preprocessor for a deterministic
ition.
Aqulfar poroelty
What la tha new value? ffiFjf
r—STATUS	
idltlr* a rmi flla
Application typaj Subtitle 0 landfill
Scenario: Unsaturated and taturatad Zona Models
,-INtTIUCr-
Cntar data In highlighted flald(i).
Uta carriage return or arrow koyt to antar data and aova between flalda.
Uaa 'Maxt' cca—nd to go to naxt acraan titan dona antarlng data.
MantiWI PreviM ll«lt«iH| Statue »)j1 Quleofl Xpedi|| Cand Oopa
Figure 4.13. Scroan for apeclfLcaclon of Aquifer porosity for a
determiniatic simulation.
38

-------
i-POrosity (SEAcpPo)-
*<^jif«r porosity
What distribution do you want to use?
Conj>t«ri't
Norwil "
lOCNormal
exponential
Uniform
LOGIOuni fort*
CMplrlcal
St> dlstr
Oarlvad
—ITATUt-
CdItIng • ney flic
Application type: Jiiititts 0 landfill
Scenario: Unsaturated and Saturated Zona rode I a
i—IMITBUCT-
lelect an option using arrow keya
than eonflna selection with the P2 key, or
Typa tha first letter of an option.
Malp:|.1 Nait:F2 P rev:M ltatua:f? OulecfjS Xp*d:f? Cnnd
Figure 4.16. Porosity screen of cha preprocessor for & HonCe CarLo
simulation.
pPOroslty (BEAt^Po)-
Aqulfar porosity
Mreneter langes
Maui mi*?
Na«n7
ltd Dev?
f—ITAlUt	
Id I ting a nay fI la
Application typai Subtitle 0 landfill
Sctnarlo: Unsaturated and Saturated Zona models
,-instruct-
fntar data in highlighted flald(a).
Usa carriaga raturn or arrow kaya to enter data and aova batwaan fields.
Use 'Hast' coomnd to go to next scraan when don* antaring data.
Na*t:F3 Pre*:}1* U«itsif5 ttatua:F7 Oul*l:fQ Xpedi§9 Cnrid Oopa
Figure 4.17. Screen showing required parameters for a Lognornal
probablllcy denslcy distribution.
39

-------
Eventually, you will wish to exit the preprocessor. If you do not wish to
save any of the changes you have made to the Input file, you may simply type
 at any point and the program will be terminated. However, If you
would like to save your changes you will need to exit the program In the
following manner:
1.	Select the Return option from the screen menus until you return to
the Edit (BE) screen.
2.	Select the Return (to Build screen) option from the Edit screen.
3.	If undefined parameters exist, the Return (BER) screen will be
displayed as shown in Figure 4.18. This screen lists the data groups
which contain undefined parameters. At this point, you may either ]>
Return to the Edit screen and specify the remaining undefined para-
meters or 2) Return to the Build screen and ignore these undefined
parameters.
.	From the Build/Modify screen (Figure 6.2), select the Save option by
typing .
5.	The Save (BS) screen will now be displayed as shown in Figure 6.19.
The name of the input file for use in MULTIMED should be specified on
this screen. Note that you should use a name which is compatible
with your computer system. For example, the DOS operating system on
an IBM PC will allow at most 8 characters in the main filename and 3
characters in the extension on the filename. Other operating systems
may have different restrictions. Press  to return to the
Build/Modify screen.
6.	To exit the program, select the Return (to Opening screen) option
from the Build/Modify screen by typing .
7.	The execution of MULTIMED must be done from the operating system of
your computer. Therefore, select the Return (to operating system)
option from the Opening screen.
6.1.2 The PREMED Tutorials
Two tutorials are included with the preprocessor. These tutorials are
intended to familiarize a user with the options and utilization of PREMED. It
is strongly recommended that an inexperienced user take advantage of the
tutorials provided with MULTIMED. Completion of these tutorials creates
complete input files for use in MULTIMED.
The tutorials are specific to the application of MULTIMED to Subtitle D
facilities. One tutorial generates an input file for deterministic, steady-
state simulation of flow and transport in the unsaturated zone, and transport
in the saturated zone. Tho second tutorial is similar to the first tutorial
except that it is run in a Monte Carlo framework. The input generated by the
Deterministic tutorial, and the corresponding MULTIMED output, are discussed
In Section 7.2. Input and output for the Monte Carlo tutorial are presented
In Section 7.3.
To utilize either of these tutorials, you must first begin the preprocessor
program by typing  (do not type the brackets) from the DOS operating
60

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-Return (BE 8)—	
fhe following data group* contain undefined pirmtiri:
UK SAT HOW (f)	UNSAf IRAtf CT]
AQUIFER (AO)	SOURCE [So]
CHEMICAL (C)
Undefined data eilitt, cure you want to Return from the Edit icraen?
Tat - Return back to luiid screen and ignore mfeffniid par acne tar a
.-STATUS	
(dltlng • new flit
Application typei Subtitle 0 landfill
Scenario: Unsaturated and Saturated Zone eodels
r-lNSTItUCT-
Select an option uilng arrow key*
then confine selection with the f2 key.
Type the first letter of en option.
Help:Ff Next:Ft Statua:l7 GuletiFS Xped:Ff Cand
Figure <*.18. The Return screen of che preprocessor.
¦-Save (B5)-
Naaa of file to save input onl
.-STATUS				—
Editing • new 411a
Application typei Subtitle D landfill
Scenerlo: Unaaturatad and Saturated Zone ¦odeIa
r-INITRUCT-
'Kait1 cemend tc go to next screen
	K««t;» lt»tm:F7 flulet:F8 Kped;'ri> Ceni	
FLgure 6.19. the Save screen of preprocessor.
41

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system. After a few seconds, the Opening screen for the preprocessor will
appear. To activate the tutorials you must type either <@DETER. LOO for the
Deterministic tutorial, or <@MONTE.LOC> for the Monte Carlo tutorial.
The tutorial will be presented in a small box on the right hand side of the
screen. An example of a tutorial screen is shown in Figure 4.20. Directions
for completing the tutorial will appear in this box. In the tutorial, you
will edit a pre-existing input file which is almost complete. This input file
has been specially designed to contain a small r.umber of parameters which
still need values. These are called "undefined' parameters, and will need to
be supplied to the preprocessor in order to complete the Input file. The
tutorial will provide instructions so that you can complete the file. In the
process, many of the options in the preprocessor will be demonstrated.
Successful completion of the tutorials will generate the completed input
sequence shown in Tables 7-4 and 7-7. These input sequences can then be used
to run MULTIMED and generate the output in Tables 7-5 and 7-8. Output from
the Monte Carlo tutorial, can be used with the postprocessor, POSTMED.
4.2 - THE POSTPROCESSOR (POSTMED)
The postprocessor can be used to generate plots to show the results of Monr.e
Carlo analyses or concentration versus time. These plots are generated from
the main output file and "SATl.OUT" which are generated by MULT1MED during
execution. For comparison of different simulations, POSTMED allows up to
three different data files to be plotted on the same graph. Output from
POSTMED may be written to the screen, to a printer, to a plotter, or to a file
in text form.
4.2.1 Use of the Postprocessor
Before using the postprocessor, read the section on installation and execution
of MULTIMED (Section 2).
In order to use POSTMED, you must copy the appropriate MULTIMED output file
into the directory which contains the postprocessor. For Monte Carlo Analyses,
the MULTIMED output file "SATl.OUT" is used, which is generated automatically
during execution of MULTIMED. Note that the "SATl.OUT" file will be over-
written each time the model is run. Therefore, if you wish to save this file
for use with the postprocessor, you should rename it. This is particularly
important if you want to plot the results from more than one simulation on the
siune graph; the "SATl.OUT" files for each simulation must be given a different
name. For Concentration versus Time plots, the file which should be copied
into the POSTMED directory is the main output file. POSTMED will select, the
information necessary for generating Concentration versus Time plots froin this
file.
To execute the postprocessor, move to the directory which contains the
postprocessor and type  (do not type the brackets). After a moment
the Opening screen will appear, as shown in Figure 4.21. Use the Data option
of the Opening screen to provide the postprocessor with information about;
MULTIMED data files which you wish to plot. Type a  (do not type the
brackets) to select this option.
42

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r-Opanlng teraan-
UCLCOME TO PREMEO, THE f
Typ• '2JETCI.LOG1 for a
•3MONTE.IOC1 for •
Salact an option?
Build / Modify Input taquane
Analyza aodtl rasulta
mfSm* ¦

itauMc*

Return to operating lyataa
r-lNSTKUCT-
talact an option ua1ng trrou kiyi
than conflra talactlon with tit* »l key, or
Typ* the flrtt (attar of an option.
Xpadijjj} Cand
Figure 4.20. Example of a tutorial screen.
43

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¦-Opening icrMrv
UEICOHI TO POSTMEfi, THC POJTPIKIKM lot MULT I KB) (v«ralon 1.0)
• plot option.
••turn to operating ayataa
(SBEZCBIXlSBBaaSel
Specs of plot
Tit In on plot
Plot aska plot
rlNSTIUCT-
•eloct on option using arrow kaym
than confirm selection with the fl key, or
Type the flit lattar of on option.
Xpedi|j| M
Figure 4.21. Opening screen of th« postprocessor.
44

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POSTMED will now display the Data-1 (D) screen. The number of Multimedia
Model runs which you wish to plot should be entered on this screen. The valid
values which may be entered on this screen can be seen by pressing the 
key. The limits for the parameter will then be displayed Ln the center.
assistance window, as shown in Figure 4.22. As you can see, a minimum of 1
and a maximum of 3 runs may be plotted on a single graph.
After entering a value on Data-1 (D) screen, select the "Next" option by
pressing  to go to the next screen. The Data-2 (D) screen will now be
displayed (Figure 4.23). This screen is used to enter the name of the tile(s)
which contain MULTIMED results to be plotted. This screen will appear once
for each run. After entering the name of the file, press  to go to the
next screen.
After entering the last file, the postprocessor returns to the Opening screen.
Type  to describe Che specifications of the plot. POSTMED will now display
the Specs (S) screen as shown in Figure 4.24 Several options are available
on this screen.
1.	The Graphics device must be specified. You may send the plot gener-
ated by POSTMED to the screen (DISPLAY), a printer or a plotter. If
your computer will not support graphics, it may be desirable to send
the plot directly to a printer. Alternatively, the coordinates used
to generate the plot may be sent either to the screen or to a TEXT
file.
2.	The X- and Y-axis types must be specified. Either arithmetic or
logarithmic scales may be used. Note that logarithmic scales can not
be used with FREQUENCY plots. If a logarithmic scale is selected,
the number of logarithmic cycles for each axis must be specified.
3.	The location of the legend on the plot must be specified. The
options are: UL (upper left), LL (lower left) , UR (upper right), I.R
(lower left).
U.	You must specify the type of plot you wish to create. Three choices
are allowed: a cumulative frequency plot (CUMULATIVE), a frequency
plot (FREQUENCY) or a concentration versus time plot (TIME). The
FREQUENCY [lot provides information about the number of times a
particular concentration was obtained, which is displayed in histo-
gram format. Selection of the CUMULATIVE option will generate a plot
showing the cumulative frequency of concentration values. The TIME
option plots concentration versus time for transient runs.
5. The Y minimum and Y maximum (in percent) of the plot should be
specified. The minimum value must be less than the maximum.
To move between options, press Ccarrlage return>. To select an option, type
enough characters to make the selection unique. For example, the Craphics
device options (Figure 4.24) are: DISPLAY, PRINTER, PLOTTER, TEXT, SCREEN. If
you wish to select DISPLAY, you may type only . However, if you want to
send your results to a printer, you must type two characters. , since
there are two options beginning with "P". Once you have selected the desirod
options on the Specs (S) screen, press  to return to the Opening screen

-------


Man atnf MATIND run da you uant to pi act fgf



Oaf »ol« i 1 Mlnlui 1 Nulaua: )



Intar data In hlghllghttd fl*ld(a).
Uaa carrlaga raturn or arrow kaya to «nt*r data md aova batwaon flatda.
Ul« 'Hwt' c«MMnd to 10 to nut Kmn titan don* «r\ taring data.

Nutijjjl Pr«v:Q| OuUtiQ *p«d:g| Card Oo
Figura 4.22. Data-1 acraan of tha postproceaaaor.
r-Oita-2 (0)-
r-UHITt-
Aiv eharictar ttrlng (i tceaetabU.
r-IMTIUCT-
Intor data In highlighted Mald(a).
U*t carrU(« ratum or arrow k»y» t« antar data and aev*	Halda.
lit* 'Nut' eommrd to 00 to n»t (croon t*an dsn* wearing data.
VwcjH	ll»lla:j| 9ul«t;J| Xpodi|I ted Oopa
Figura ti. 21. Daca-2 acrean of tha poacprocaaior.
46

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<»>-
Type of plot
Graphlea device
X Axle type
X aln
x lila type
> fgHmni
Character height
>
0.16
» DISPLAY
Legend location
k
I*
> MITN
T Axle type
>
Ml TN
» 0.
T aln
>
¦ 0
> 0.01
Y aax
>
100
> 4
T nua log cyctaa
>

f—INSTRUCT	
Enter data In hlghllghtad flald(a).
Uaa carrlag* raturn or arrow kaya to antar data and boot batwean flaldi.
Uaa 'Next1 coaeund to 90 to na*t acraan Mhan dona entering data.
Halp:$J HaatiH Previ$$	Xped:jg| Oand Oope
Figure U.2U. Specs screen of the postprocessor.
47

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Titles for the Graph, the x- and y-axis, and the different runs can be enter'c..
on the Titles (T) screen. From the Opening screen, type  for this selec-
tion. This screen is shown in Figure 4.25. Any character string may bp used
as a title. Use the  to move between options. Press  Co
return to the Opening screen.
Now you are ready to generate a plot. If you wish to make any changes to the
any of the screens, type the first letter of the menu item to select the
option, make the necessary changes, and return to the Opening screen by
pressing . Otherwise, type 
 to generate the plot. The plot will then
be sent to the Graphics device that you specified on the Specs (S) screen. A
cumulative frequency plot showing the results of the simulation of an example
problem Is presented In Figure 4.26. The corresponding frequency plot is
shown in Figure 4. 27. Figure 4.28 shows the first screen of the text file
generated by selecting the SCREEN option for the same example problem.
Selection of the TEXT option will send the same file to a specified file.
Now, you may either repeat the process described above and generate addi i i r
plots, or type  to return to the operating system.
48

-------
r-Tlttea (T)	
Main title:
T Axil I aba11
Cuajlatlvt Frequency
X Axil labeli
Coneantral Ion
Curve label*:
1i Str 1	2: Run 2	Ji Run 3
rUSTRUC1-
(ntar data In highlighted flald(a).
Uta carriage ratum or arrou keya to enter data and aova between field*.
Uta 'Next' toanand to go to next screen when done entering data.
Next:{| Previ£$ llalteijj| Xpad:J$ Cand Oopa
Figure 4.25. Tides screen of che postprocessor.
49

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Ml
Figure 4.26 Example of a cumulative frequency pi
01
nuLiann run
Figure 4.27 Example of a frequency plot
50

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r-Qptnfng ictmo-
-USTRUCT-
CURVE NUMBER:
1 Rlfl 1
CONC
PEICEN?
0.S5923E-05
0.400
0.I0J7CE-M
0.800
0.12763E-M
1.200
0.19671C-04
1.600
0.19701^^
mmm
0.21278E-04
2.400
0.21J45E-04
2.BOO
0.2U96E-04
3.200
U.2S470C-04
3.600
0.290321*04
4.000
0.32460E-04
4.400
0.UJ41I-04
4.S00
0.36069E-04
5.200
*N«xt1 command to fo to nixt »erMn
N«xt:0j Prtv:j| Xpad:|jf Cm*
Figure 4.28. Exaople of screen showing a TEXT file (corresponds to
cumulative frequency plot shown in Figure 4.26).
si

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SECTION 5
MODEL APPLICATION
The large number of interrelated physical, chemical and biological processes
involved in the migration of leachates from waste disposal facilities makes
the prediction of groundwater contamination from these facilities a complex
Cask. Mathematical models are useful tools which provide insight Into Che
effects on groundwater quality of facility design, operation and failure.
All models are simplified representations of the real system; no model will
ever reproduce the exact characteristics of a site. Therefore, model result
should always be interpreted as estimates of groundwater flow and con tarn i nan.:,
transport, and not as exact predictions. Bond and Hwang (1988) recommend that
models be used for comparing various cases or scenarios, since all cases are
subject to the same limitations and simplifications. Furthermore, models are
useful for sensitivity analysis, determining the effects of varying one
parameter on the model results. It is important to understand the limitations
of mathematical models, and to use chera correctly in evaluation of actual
environmental conditions.
Several recent reports present detailed discussions of the issues related to
model selection, application, and validation. Donigian and Rao (1988) address
each of these issues. Issues related to model selection and application are
addressed in detail by Boutwell et al. (1986). Weaver et al. (1989) discuss
the selection and field validation of mathematical models. In addition, a
report by the National Research Council (1990) discusses model application find
validation and provides recommendations for the proper use of groundwater
models. Model users, particularly those who are relatively inexperienced, arc
encouraged to read these and similar reports before beginning a modeling
s tudy.
The validity of the results from mathematical models depends to a large extern
on the proper application of the model. The application of a model to a
leachate migration problem requires several steps. Firsc, the modeling needs
and the objectives of the study should be determined. Next, data should be
collecced for characterization of che hydrological , geological, chemical ap.d
biological conditions present in the system. These data should assist in thr
development of the "scenario" to be modeled, which provides the framework 1c;
the conceptual model of the system. The conceptual model and data are used
verify that the selected model is appropriate. During model application,
results should be calibrated to obtain che best fit to observed data.
Finally, these results should be validated by comparing them to independently
derived data or observations,
In order co apply a model to a specific site, it is necessary to describe ihe
"scenario" Co be represented by the model. A scenario is essentially a des-
cription of all the important processes and characteristics of a particular
site. Although it may be possible to describe the "average" characteristics
of a Subtitle D landfill or surface impoundment, it would be dangerous co
assume that this description adequately describes all such facilities. Each
52

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sice is unique, and must be characterized separately. This section describes
some of the issues which should be considered when developing a scenario and
using MULTIMED to represent the conceptual model of the site.
One of the most severe limitations to modeling is insufficient data. Uncer-
tainty in model predictions results from our inability to characterize a site
in terms of the boundary conditions or the key parameters describing the im-
portant flow and transport processes (National Research Council, 1990). The
results of MULTIMED are highly dependent on the quantity and quality of the
available data. The application of MULTIMED to a site requires the collection
of a large amount of data, and the process of applying MULTIMED to a scenario
may reveal data deficiencies which.require additional data collection.
Based on the available data and the judgement of the modeler, values of the
required parameters should be determined. Parameter values which must be
determined for Subtitle D applications are discussed in Section 5.3. Section
6 of this manual provides guidance for estimation of parameters for use in
MULTIMED. Inexperienced modelers may attempt to apply the model when the lack
of site-specific data causes the model results to be highly speculative. It
must be emphasized that a mathematical model should never be used as a substi-
tute for data in site-specific applications.
As stated above, the conceptual model and data should be used to determine
whether or not a mathematical model is appropriate for representing the sub-
surface system and which options in the model should be utilized. The model
should:
•	Allow the objectives of the study to be achieved
»	Adequately simulate the significant processes present in the actual sy:-:i
•	Be consistent with the complexity of the study area
•	Be appropriate for the amount of available data
Some of the factors which should be considered before applying MULTIMED to a
particular site are summarized in Table 5-1. This list is not exhaustive, and
Ls meant only to provide guidance. The factors in Table 5-1 are addressed in
terms of MULTIMED's capabilities and limitations in the following section.
5.1 MULTIMED CAPABILITIES AND LIMITATIONS
5.1.1 Solution Techniques
MULTIMED utilizes analytical and semi-analytical solution techniques to solve
the mathematical equations describing flow and transport. These solution
techniques have advantages and disadvantages over fully numerical models.
Analytical solutions are computationally more efficient than numerical simu-
lations and are more conducive to uncertainty analysis (i.e. Monte Carlo
techniques). Typically, input data for analytical models are simple and they
do not require detailed familiarity with the code or extensive modeling ex-
perience. Analytical solutions are typically the most efficient alternative
when data necessary for the characterization of the system are sparse (Jav-
andel et al., 1984). The limited data available in most fLeld situations may
not justify the use of a detailed numerical model; in some cases, results from
simple analytical models may be just as meaningful (Huyakorn et al., 1986).
53

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TABLE 5-1. ISSUES TO BE CONSIDERED BEFORE APPLYING MULTIMED
Objectives of the Study
•	Is a "screening level" approach appropriate?
•	Is modeling a "worst case scenario" acceptable?
Slenlflcant Processes A:~J.i^'~ 	'..nan1' Transport
•	Does MULTIMED simulate ai.1 U.o ^'.gnif leant processes occurring
at the site?
•	Is the contaminant soluble in water and of the same c'ensity
as water?
Accuracy and Availability of the Data
•	Have sufficient data been collected to obtain reliable results?
•	What is the level of uncertainty associated with the data?
•	Would a Monte Carlo simulation be useful? If so, are the
cumulative probability distributions for the parameters with
uncertain values known?
Complexity of the Hvdropeoloplc System
•	Are the hydrogeologic properties of the system uniform?
•	Is the flow in the aquifer uniform and steady?
•	Is the site geometry regular?
•	Does the source boundary condition require a transient
or steady-state solution?
However, analytical models require simplifying assumptions about the system
which are not necessary for numerical models. These simplifications result In
models which include relatively few processes and a limited number of parame-
ters which are often required to be constant In space and time (van der Heijde
and Beljin, 1988). MULTIMED Is no exception; the representation of the system
simulated by the model is simple, and little or no spatial or temporal
variability is allowed for the parameters In the system.
54

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Bond and Hwang (1988) present guidelines for determining whether Che assump-
tion of uniform aquifer properties is Justified at & particular site. In rnor.
complex systems, it may be beneficial to use MULTIMED as a "screening level'
model which would allow a user to obtain an understanding of the system. A
numerical model could then be used if there are sufficient data and necessity
to justify the use of a more complex model.
A highly complex hydrogeological system cannot be accurately represented with
MULTIMED. Heterogeneous or anisotropic aquifer properties, multiple aquifers
and complicated boundary conditions cannot be simulated using this model.
MULTIMED cannot simulate processes, such as flow in fractures and chemical
reactions between contaminants, which can have a significant effect on the
concentration of contaminants at a site. Since each site is unique, it must
be left to the modeler to determine which conditions and processes are
important at a specific site, and to determine the suitability of applying
MULTIMED.
5.1.2 Soatlal Characteristics of the System
Although actual landfills and groundwater systems are three-dimensional, it is
common to reduce the number of dimensions simulated in a mathematical model t.o
one or two. Two and three-dimensional models are generally more complex and
computationally expensive than one - ditnens tonal models, ar.d therefore require
more data. In some instances, a one - dimensional model may adequately repre-
sent the system. Furthermore, the available data may not warrant the use of
multidimensional model.
However, modeling a truly three-dimensional system using a one-dimensiona1
model may produce Lnaccurate results. Three-dimensional effects are often
very significant in describing processes such as contaminant plume migration.
The choice of the number of dimensions in the model should be made for a
specific site, based on the conditions present at that site. The information
which Is desired from the model output should also be considered.
MULTIMED has the following spatial characteristics'.
•	The Unsaturated Flow Module simulates vertical, one-dimensional flow.
« The Unsaturated Transport Module simulates vertical, one-dimensional
transport. Dispersion is only considered in the longitudinal (vertical)
direction.
•	The Saturated Transport Module assumes one-dimensional, horizontal flov.
However, three-dimensional dispersion may be simulated since the effoo.i.=
of lateral or vertical dispersion may significantly affect the model
results ,
These spatial assumptions should be considered when applying MULTIMED to a
site. The assumption of flow only in the vertical direction may be valid foi
facilities which receive uniform areal recharge. The assumption may not be
valid in facilities where surface soils (covers or daily backfill) or surface
slopes result in an Increase of runoff in certain areas of the facility and
ponding of precipitation in others (Kirkham et al., 1986).
The simulation of one - dimensional, horizontal flow In the saturated zone
requires several assumptions. The saturated zone is treated as a single,
55

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horizontal aquifer with uniform properties. The effects of pumping or
discharging wells on the groundwater flow system cannot be considered, These
assumptions should be considered when applying MULTIMED to a site.
5.1.3	Steady-State versus Transient Flow and Transport
The MULTIMED model assumes steady-state flow in all applications. Some
groundwater flow systems are in an approximate "steady-state" , tn which the
water entering the flow system is balanced'by¦the water leaving the system.
There is no significant temporal variation in the system. The assumption of
steady-state conditions in a model generally simplifies the mathematical
equations used to describe processes, and reduces the amount of input data,
since no information about temporal variability is necessary.
However, assuming steady-state conditions in a system which exhibits transient
behavior may produce inaccurate results. For example, climatic variables,
such as precipitation vary in time and may have strong seasonal components
In such areas, the assumption of constant recharge of the groundwater system
is incorrect. In general, this assumption will cause underestimation of
contaminant concentrations in the subsurface, since steady-state models can
not simulate the effects of individual storms, which can provide a substantial
driving force for contaminant transport.
MULTIMED can simulate either steady-state or transient transport conditions.
The assumption of steady-state transport requires that the contaminant source
has a sufficiently large mass to ensure that the downgradlent concentration,
once reached, will be maintained (Mulkey et al., 1989). It must be assumed
that the source is continuous and constant. If these assumptions can not be
made at a particular site, inaccurate results will be produced by a steady-
state transport model. Steady-state models are also inappropriate when the
simulation includes chemicals which sorb or transform significantly (Mulkey pt
al., 1989). Note that although the steady-state model can be very conserva-
tive, this may be appropriate for some applications. The choice of simulating
steady-state or transient conditions should be made based the objectives of
the study and on the degree of temporal variability in the system.
5.1.4	Monte Carlo versus Deterministic Simulations
MULTIMED may be run in either a deterministic or a Monte Carlo framework. In
a deterministic simulation, exactly one model result is determined for a given
set of input values. All of the input variables are assumed to have a fixed
mathematical relationship with each other, which completely define the system.
Monte Carlo simulations, however, consider the intrinsic randomness and uncer-
tainties inherent in the system. The Monte Carlo method provides a means of
estimating the uncertainty in the results of a model, if the uncertainty of
the input variables is known or can be estimated. For each of the uncertain
variables, a cumulative probability distribution must be determined. The
Monte-Carlo technique involves running a model a large number of times with
different values of input parameters, which are determined from probability
distributions, and then analyzing the results. The Monte Carlo option is
discussed in Section 9 of the MULTIMED model theory documentation (Salhotra et
al., 1990).
There are many sources of uncertainty in the prediction of leachate migration'
in the subsurface. Uncertainties may be due to measurement error In parame-
ters which describe the physical and chemical properties of the system, Llie
56

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presence of spatial and temporal variability in the parameters, or incomplete -
ly understood processes which are simulated by the mathematical model. There
may be some uncertainty associated with extrapolating data from one set of
conditions to a different set of conditions. Therefore, it may be more
appropriate to express these uncertain input parameters in terms of a proba-
bility distribution rather than a single deterministic value and to use an
uncertainty propagation model to assess the effect of the variability on the
model output {Salhotra and Mineart, 1988).
The specified uncertainty in the input parameters for MULT1MED is highly site-
specific. Available data for many sites are scarce and even sites which are
very well-characterized may exhibit a substantial amount of variability in
measured parameter values. Most of the parameters in the MULTIMED model may
be assigned a Monte Carlo distribution. It must be left to the user of the
MULTIMED model to determine which input parameter values are uncertain at a
particular site.
Although the Monte-Carlo method can be a useful tool for quantitatively
evaluating uncertainty in a model, it is not without problems. One difficulty
is related to determining the cumulative probability distribution for a given
parameter. These distributions must be determined from a large amount of
data, which may not be available. Assuming a parameter probability distribu-
tion when the distribution is unknown does not help reduce uncertainty, as Un-
certainty of the output is then a function of the assumed certainty of the
input parameter (U.S. EPA, 1988). Furthermore, in order to obtain a valid
estimate of the uncertainty In the output, the model must be run numerous
times (typically at least several hundred times) which can be computationally
expensive. These issues should be considered before utilizing the Monte-Carlo
technique.
5.1.5 Boundary conditions
The source boundary condition for MULTIMED relates to the introduction of the
contaminant to the aquifer system. MULTIMED is limited to relatively simple
representations of the source of groundwater contamination. Only two types of
source geometries can be simulated by MULTIMED: a patch source or Gaussian
distributed source. Temporally, these source geometries may be described as
either: 1) continuous 2) exponentially decaying or 3) a non-decaying pulse of
finite duration. These types of sources are discussed in Section 5 of the
MULTIMED model theory documentation (Salhotra et al., 1990).
5.2 SUBTITLE D APPLICATIONS OF MULTIMED
5.2.1 Summary of EPA Requirements for MULTIMED Simulations of l.eachate
Migration from Subtitle D Facilities
The U.S. EPA has developed several restrictions for Subtitle D applications ot
MULTIMED. These restrictions were made in an effort to develop a conservative
approach for simulating leachate migration from Subtitle D facilities.
•	Only the Saturated and/or Unsaturated Modules may be active in Subtitle
D applications, because the Surface Water, Landfill and Air Modules
have not been sufficiently tested at this time.
•	Although MULTIMED can simulate either steady-state or transient trans-
port conditions, only steady-state transport simulations are allowed
57

-------
for Subtitle D applications. No decay of the source term Is allowed;
the concentration of contaminants entering the aquifer syscem must be'
constant in time. The contaminant pulse is assumed continuous and
constant for the duration of the simulation.
•	The receptor must be located directly dovngradient of the facility, so
that it intercepts the center of the contaminant plume. In addition,
the contaminant concentration must be calculated at the top of aquifer.
Therefore, the angle from the plume centerline to the receptor and the
vertical distance to the receptor must be specified as zero in Subtitle
D applications.
•	Only the Gaussian source geometry is allowed in SubtitleaPplications.
The application of MULTIMED to Subtitle D facilities simulates the transport
of contaminants from the source, through the saturated and/or unsaturated
zones by groundwater, and to a receptor (i.e. a well). Although the LandfiLL
Module in MULTIMED. can not be used at present because it has not been suffi-
ciently tested, MULTIMED can be used in conjunction with another source
model, such as HELP (Schroeder et al., 1984), to develop and compare the
effects of different facility designs on groundwater quality. MULTIMED
combined with a source model could be used to demonstrate that either the
landfill design, or the specific hydrogeologic conditions present at the sIlc
will prevent the migration of significant quantities of leachate from ihe
landfill. Furthermore, MULTIMED could be used to predict the results of
different types of "failure" of the landfill. If leachate migration into the-
groundwater below a waste disposal facility occurs, MULTIMED could be useful
in predicting the face and transport of the contaminants in the subsurface.
5.2.2	Active Modules
FLow and transport in the subsurface typically occurs through the unsaturated
zone, to the water table and into the saturated zone. However, in some
instances, the water table may be located just below the waste disposal
facility, so that only saturated flow and transport away from the facility
need to be considered. Therefore, two basic simulation options are allowed
for Subtitle D applications of MULTIMED: 1) flow and transport in the unsatu-
rated zone coupled with transport in the saturated zone or 2) saturated
transport only. The simulation of the system should accurately represent the
moisture conditions present at the site.
Simulation of these options in MULTIMED requires that the Saturated Zone
Module, and, if the water table is located at a significant depth below the
waste disposal facility, the Unsaturated Flow and Transport Modules, be
active. Use of the Saturated Zone Module requires four data groups: the
General, Chemical, Source, and Saturated Zone Data Croups. If the Unsaturated
Flow and Transport Modules are active, two additional data groups must be
used: the Unsaturated Flow and Transport Data Croups. The parameters required
in each of these data groups are discussed in Section 5.3.2.
5.2.3	Boundary conditions
A1 though MULTIMED can simulate two source geometries, only the Gaussian
distributed sou.ee is allowed in Subtitle D applications. Temporal variation
in the source term boundary conditions in MULTIMED are not allowed for
Subtitle D applications, which must be run in steady-state. Therefore,
58

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although constant pulse and exponential decay boundary conditions are allowed
for generic applications of MULTIMED, only a constant source is allowed in
Subtitle D applications.
5.2.4 Procedure for Application of MULTIMED to Subtitle D Facility Design
MULTIMED can be used to assist in the design of Subtitle D landfills (Figure
5.1). As the flowchart shows, the role of MULTIMED in the design process is
to evaluate Che ability of a particular design to insure that groundwater
concentrations of chemicals expected to exist in Subtitle D landfills do not
exceed health based thresholds. A step-wise procedure for determining the
minimum design necessary to protect groundwater at these levels and keyed to
the flowchart shown in Figure 5.1 follows:
1)	Collect site-specific hydrogeological data. These data may Include
aquifer particle size, porosity, bulk density, hydraulic conductivity and
gradient, groundwater velocity, dispersIvities, and thickness. Lists and
discussion of the parameters required for Subtitle D applications of
MULTIMED are presented in Section 5.3. See Section 6 for guidance In
parameter estimation.
2)	Based on water level measurements, determine whether or not the Unsaturr.t:
ed Zone Modules should be active In the simulation. If the unsaturated
zone will be simulated, collect site-specific data on the properties of
the unsaturated zone.
3)	Determine contaminant which will be simulated. The selection of the
contaminant to be simulated may be based on a variety of factors or it ran
be prescribed. It may be a chemical which is particularly persistent in
the subsurface environment, or is present in high concentrations in the
specific Subtitle D facility. Determine chemical properties for the
selected contaminant (see Section 6).
h) Propose landfill design and determine the infiltration rate at the site.
This can be done using a water balance model, such as HELP (Schroeder el
al., 198^»), which includes representations of engineering controls Noie
that infiltration rate as used here means the volumetric flow rate in
meters per year from the bottom of the landfill into the unsaturated zonr.
or aquifer. Obviously, the attenuation of this flow Is the objective of
landfill engineering controls. For each specific landfill design, there
is a resulting steady-state infiltration rate.
5)	Run KULTIMED using the Subtitle D application type, the hydrogeologi c. ai
data collected in Step 1, the infiltration rate determined in Step 2, and
with the point of compliance set to the required location. As discussed
above, the Subtitle D application assumes steady-state conditions and t hr
point of compliance (POC) must be along the plume centerline. You may
wish to set the input leachate concentration to 1.0 mg/1 for convenience,
in later calculations (see step 6).
6)	The EPA-recommended criteria for establishing whether or not a particular
design is acceptable is based on the dllution-attenuation factor (DAK).
This method Is based on Che fact that che model estimate of concentration
at the point of compliance is linear with respect to the input concentra-
tion. Therefore, the DAF is the factor by which the concentration is
expected to decrease between the landfill and the point of compliance.

-------
no
DAF i loor
Run MUU1MED
Calculate DAF
Collect Site-Specific
Hydrogeological Data
Propose Landfill Design and
Deteraine Infiltration Rata
Deteraine Active Module*
in HULT1MED; Contaninant
to Be S inulated
Acceptable
Design
Figure 5.1 Procedure for using MULTIMED Co assise in the
design of Subtitle D facilities.
60

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Using the concentration predicted by MULTIMED at the point of compliance,
the dilution-attenuation factor (DAF) for the landfill/aquifer system may
be calculated using the following equation:
DAF - leachate concentration / concentration at the POC
or, if the leachate concentration is 1.0 mg/1 in the model,
DAF - 1.0 / concentration at the POC
7) If the DAF is equal to or greater than 100, the design is acceptable (see
discussion below). Otherwise, the landfill design must be made more
stringent by increasing the number or effectiveness of engineering con-
trols so that the infiltration rate is reduced. To evaluate Che new de-
sign, repeat Steps 2-5. Continue until an acceptable design is reached
(DAF is equal to or greater than 100).
The threshold DAF of 100 is used to define an acceptable design because the
maximum allowable leachate concentration of chemicals expected to exist in a
Subtitle D landfill is 100 times the Maximum Contaminant Level (MCL) for each
chemical (U.S. EPA, 1990). This approach to determining the expected concen-
tration of constituents in leachate from a Subtitle D landfill is attractive
because of its consistency with other regulations and its generic nature. If
site-specific conditions permit the use of other approaches which are accep-
table to an approved state, these may be used.
5.3 MULTIMED INPUT REQUIREMENTS
As discussed above, the MULTIMED code consists of seven modules which are
described in Salhotra et al. (1990). Only three of the modules can be used
for Subtitle D applications of the model: the Saturated Zone Transport Module,
the Unsaturated Zone Flow Module, and the Unsaturated Zone Transport Module.
The Saturated Zone Transport Module is required for all Subtitle D applica-
tions and can be applied independently of the Unsaturated Zone Modules.
Depending on site-specific conditions, the Unsaturated Zone Modules may or may
not be needed. Note that the two Unsaturated Zone Modules must be used in
conjunction with each other and with the Saturated Zone Module.
The operation of each module requires specific input, which is organized into
data groups. The General Data Group, which is required for all simulations,
contains flags and data which describe the scenario being modeled. The input
parameters needed for the Saturated Zone Transport Module are found in three
additional data groups: the Chemical Data Croup, the Source Data Group, and
the Aquifer Data Group. Use of the Unsaturated Zone Modules requires input
found in the same data groups, as well as two others: the Unsaturated Zone
Flow Data Croup and the Unsaturated Zone Transport Data Group.
In this section, parameter requirements are discussed in two stages. Section
5.3.1 Introduces the input parameters required by each of the three modules
which can be active in Subtitle D applications. In Section 5.3.2, the
parameters in each data group are presented and the options available for
specifying their values in the code are summarized. Help in estimating these
parameters is provided in Section 6.
61

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5.3.1	Parameter Requirements Summarized bv Module
5.3.1.1	The Saturated Zone Transport Module--
The primary Input parameters required to compute a contaminant concentration
in the saturated zone for Subtitle D applications are shown In Table 5-2,
organized according to the data group In which they are found. A number of
the parameters listed in Table 5-2 can be derived using other variables and a
sev of empirical, semi-empirical, or exact relationships. Note- that some of
the parameters used to derive the primary parameters can also be derived.
Table 5-3 indicates which parameters can be derived and lists the additional
variables needed. The methods used to derive the parameters are described i n
Section 6 of this document or in Section 5.5 of Salhotra et al. (1990). Note
that both particle diameter and porosity can not be simultaneously derived,
since one is derived from the other.
5.3.1.2	The Unsaturated Zone Flow Module--
The input parameters required to compute flow in the unsaturated ?.one are
shown in Table 5-<4. Note that only one input variable in the Source Data
Group is needed. The remaining variables are all located in the Unsaturated
Zone Flow Data Group. None of these parameters can be derived.
5.3.1.3	The Unsaturated Zone Transport Module--
Table 5-5 lists the parameters used to compute contaminant transport in the
unsaturated zone. The variables are located in five different data groups.
Note that an overall chemical decay coefficient and distribution coefficient
for the unsaturated zone can not be entered directly, as they can in the
saturated zone module. Rather, they are calculated in the code using methods
described in Section 5.5.2.1 of Salhotra et al. (1990). Of the parameters
shown in Table 5-5, only the longitudinal dispersivity can be derived.
5.3.2	Parameter Requirements Summarized bv Data Group
This section is written with the assumption that the modeler will use the
preprocessor, PREMED, to create and modify input files for Subtitle D applica-
tions (see Section i»). Thus, the organization of the information in this
section is compatible with that of the preprocessor. The parameters are
listed in tables according to data group. Further, the parameters listed in
each of the data group tables are organized according to the preprocessor
screen in which they can be found. Advanced users, who choose to modify input
files directly without the use of the preprocessor, will notice that there is
some discrepancy between the organization of data in the preprocessor (and
this section) and the structure of the input file, which is discussed in
Appendix A.
5.3.2.1 Ceneral Data Group--
The General Data Croup screens of tho preprocessor contain flags which allow
the user to specify the run options and active modules for the input file.
The choices made in this data group determine which parameters must be
specified in the rest of the input. Therefore, the General Data Group should
always be completed first. The information which needs to be supplied £or all
model applications is:
62

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TABLE 5-2. PRIMARY PARAMETERS USED IN THE SATURATED ZONE TRANSPORT MODULE
FOR SUBTITLE D APPLICATIONS OF MULTIMED
Parameters	Units
Source Data Group Parameters
Area of the land disposal facility	|ai2]
Leachate concentration at the waste facility	(mg/1, g/nv3]
Recharge rate into the plume	(m/yr)
Infiltration rate from the facility	(m/yr]
Standard deviation (i.e., spread) of the
source	(m)
Aouifer Data Croup Parameters
Type of source geometry (only Gaussian allowed)
Porosity	[cc/ccj
Thickness of the aquifer	[m]
Thickness of source (I.e., mixing zone depth)	-[m)
Seepage velocity	(m/yr)
Dispersivities (longitudinal, transverse,
vertical)	(raj
Retardation coefficient [dimensionless ]
Radial distance from the site to the receptor	[m]
Chemical Data Group Parameters
Effective first-order decay coefficient	[1/yrJ
Distribution coefficient	[cc/g]
63

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TABLE 5-3. PARAMETERS USED TO DERIVE OTHER SATURATED ZONE TRANSPORT
MODULE PARAMETERS NEEDED IN SUBTITLE D APPLICATIONS OF MULTIMED
Parameters	Units
Overall Chemical Decay Coefficient
Biodegradation rate	(L/yr]
Solid phase decay coefficient	[1/yr]
Dissolved phase decay coefficient	(1/yr]
Bulk density	[g/cc ]
Distribution coefficient	[cc/g)
Porosity	[cc/cc]
Solid and Dissolved Phase Decay Coefficients
Reference temperature	[°C)
Aquifer temperature	[°C]
Second-order acld-catalysis hydrolysis rate
constant at reference temperature	[P/mole-yr]
Second-order base-catalysis hydrolysis rate
constant at reference temperature	(P/mole-yr]
Neutral hydrolysis race constant at reference
temperature	[1/y r J
pH of the aquifer	[pH units)
Retardation Coefficient
Bulk density	[g/cc]
Distribution coefficient	[cc/g]
Porosity	(cc/cc1
Bulk Density
Porosity	(cc/cc)
Poros 1 tv
Mean particle diameter of the porous medium	[c.m]
Particle Diameter
Porosity	[cc/cc]
(cont i nued)
64

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TABLE 5-3. PARAMETERS USED TO DERIVE OTHER SATURATED ZONE TRANSPORT
MODULE PARAMETERS NEEDED IN SUBTITLE D APPLICATIONS OF
MULTIMED (concluded)
Parameters	Units
Distribution Coefficient:
Normalized distribution coefficient
for organic carbon, Koc	[cc/g)
Fractional organic carbon content [dimensionless|
Seepage Velocity
Hydraulic gradient	{m/m)
Hydraulic conductivity	(m/yr)
Porosity	(cc/cc)
Hydraulic Conductivity
Porosity	[cc/cc]
Mean particle diameter of the porous medium	(cm)
Thickness of the Source (Mixing Zone Depch)
Length of the land disposal facility	[m]
Thickness of the aquifer	[m]
Seepage velocity	[m/yr]
Porosity	(cc/cc|
Infiltration rate through the facility	(m/yr)
Vertical disperslvity	[m]
Standard Deviation of the Source
Width of the land disposal facility	[m)
Leneth and Width of the Facility
Area of the land disposal facility	[mz]
Dlsperslvltles
Radial distance from the site to the receptor	[m]
65

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TABLE 5-4. PARAMETERS REQUIRED IN THE UNSATURATED ZONE FLOW MODULE
FOR SUBTITLE D APPLICATIONS OF MULTIMED
Parameter
Units
Source Data Group Parameters
Infiltration rate from the facility
Unsaturated Zone Data Group Parameters
Number of physical flow layers
Number of porous materials
Thickness of each layer
Material associated with each layer
For each material:
Air entry pressure head
Poros i ty
Saturated hydraulic conductivity
Residual saturation (water content)
Ei ther:
van Genuchten alpha coefficient
van Genuchten beta coefficient
or
Brooks and Corey exponent '
van Genuchten alpha coefficient
van Cenuchten beta coefficient
[ra/yr]
[dimens ionless]
[dimensionless]
(m)
[dimens ionlessI
[dimens ionless]
(cm/hr J
[dimens ionless]
[1/cm)
[dimens ionless)
[dimens ionless)
[1/cm]
[dimens ionlessI
Note: The model provides the option to use either van Genuchten's or Brooks
and Corey's constitutive relationship for relative permeability versus
water saturation. However, the relationship between pressure head and
water saturation is expressed in terms of van Genuchten parameters.
66

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TABLE 5-5. PARAMETERS REQUIRED IN THE UNSATURATED ZONE TRANSPORT MODULE
FOR SUBTITLE D APPLICATIONS OF MULTIMED
Parameters	Units
Source Data Group Parameters
Source concentration at top of unsaturated zone
Unsaturated Zone Transport Data Group Parameters
Control parameters related to.the evaluation
schemes used in the module
Number of layers used to simulate transport
For each layer:
Thickness
Longitudinal dispersivity
Bulk density of the soil
Biodegradation rate,
Percent organic matter
Unsaturated Zone Flow Data Group Parameters
Porosity of the unsaturated zone
Aquifer Data Group Parameters
Temperature of the aquifer"
pH of the aquifer*
Chemical Data Group Parameters
Normalized distribution coefficient (i.e., Koc)
Reference Temperature
Acid and base hydrolysis rates at reference
temperature
Neutral hydrolysis rate at reference temperature
(mg/e)
(dimensionle!;s ]
Im I
I m ]
[g/cc]
(1/yr]
[dimensionless I
(cc/cc ]
(°C)
[pH units]
lcc/g]
(°C)
[ t/mo 1e-y r
(1/yrI
" Note: the temperature and pH used in calculating the unsaturated zone
ovcrull chemical decay rate are the temperature and pH specified for the
aqulfer.
67

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Title--Two lines of text can be entered. The text, which is used to label the
input and output, can consist of two character strings, each up to 78 charac-
ters in length.
Run Option--The default run option is Deterministic. However, the user I.as
the option of selecting a Monte Carlo run instead. Issues related to the
choice between these two options are addressed in Section 5.1.4. In addition.
Monte Carlo simulations are discussed in Section 9 of Salhotra er. al. (1990)
Active Modules--For Subtitle D applications, the default for active modules ir
Unsaturated Zone/Saturated Zone. However, the user can choose that the
Saturated Zone alone be active. The Air, Landfill, and Surface Water Modules
can not be accessed for Subtitle D applications.
Transient versus Steady-state--For Subtitle D applications, the user has no
choice for this flag. Simulations must be steady-state.
For Monte Carlo simulations, additional information is required In the Geneini
Data Group. The additional Information is:
Number of Monte Carlo Simulations --Typically hundreds to thousands of Monte
Carlo simulations are needed to obtain meaningful results. Section 9.9 of
Salhotra et al. (1990) provides information on the estimation of this value.
Level of Output from Monte Carlo Runs--The default for this flag is SOME,
which means that the main output file and the STATS.OUT and SAT1.0UT files are
created (see Section A.2 for a description and listing of the output files).
The two other options available to the user are LOTS, which opens the maximum
number of output files, and NONE, which opens only the main and STATS.OUT
files. Note that in order to use the postprocessor to create frequency and
cumulative frequency plots, the file SAT1.0UT is needed and thus, this flag
must be set to either LOTS or SOME. A few of the files created using the LOTS
flag can be very large, depending on the number of Monte Carlo simulations.
On many PC computers, these files can fill all available disk space and cause
the simulation to fail. Thus, on PC's the default of SOME Is recommended.
Confidence Level (in percent) for the Four Estimated Percentiles-•In Monte
Carlo mode, MULTIMED calculates confidence bounds for the 80th, 85th, 90th,
and 95th percentiles. The confidence bounds- are discussed in Section 9.8 of
Salhotra et al. (1990).
5.3.2.2 Chemical Data Croup--
The MULTIMED parameters contained in the Chemical Data Group are shown In
Table 5-6. Note that some of the parameters are associated with the Surface
Water and Air Modules of MULTIMED and thus, are not used for Subtitle D
applications of the model. Further, note that five of the parameters (I.e.,
the solid phase, liquid phase, and overall decay coefficients, the distribu-
tion coefficient, and the blodegradation coefficient) are used only In the
Saturated Zone Module. Other parameters may be used by more than one model
module.
68

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TABLE b-6. PARAMETERS IN THE CHEMICAL (Chemical) DATA GROUP
Parameter Units
Der1ved



Spec i fled



Default
Cocmen is


C
N
Ln
U Lo&,.U
Emp
SB
G


D*c«v CoeffictcnU:










Solid phase decay coeff.
(s«t. rcme) (1/yr)
¦
¦
•
¦
¦ ¦ ¦
¦
¦



Dissolved phase decay
(Ml. cone) 11/yr I
¦
¦
¦
¦
¦ ¦ ft
¦
¦



Overall chemical decay
(sat. zone) ll/yr)
•
¦
¦
¦
¦ ¦ ¦
¦
¦



Brdrolnis Rate Cautanta and Reference
TanraLtura:









Acid catalyzed
hydrolyaift (I/M-yrI

¦
¦
¦
¦ ¦ ¦
•
¦

0

Neutral catalysed
hydrolysis [1/yr)

¦
¦
¦
• ¦ ¦
m
¦

0

Base catalyzed
hydrolysis fl/M-yr)

¦
¦
•
mm m
¦
m

0

Ttaferenca
temperature J*C]

¦
¦
¦
mm m
¦
¦



7«riou0 Coefficients;










Bormolned distribution
coitt. [ml/ft]

m
m
¦
mm m
¦
s



Distribution coeff.
(sat. zone] I tr 1 / g. |
¦
¦
m
¦
m m





C • Constant
H ~ formal
Ln " Loftnornwl


Erp
U
Log lsu
-
Exponential
Uni for®
Log^Uni foro

Eenp
SB
G
-
Empi rica 1
Johnson SE
Galher


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Paruw'.tr Units	Derived	Specified	Default.
			.	 Value
C	N	Ln	E*p	U	t-og,%U Eop	SB	G
Bi©c«gradat1 on coeff.	•	¦	•	¦	•	¦	¦
(sat. ton*) ll/yrl
Asx diffusion coeff.
[CttVs]
Not used in Subtitle
applications.
D
Teenferature for Air
diffusion ("CJ
Mot used in Subtitle
applications.
D
Nolvojiu Definitions. Solut* Vauor Prnsuri. Banrr's Cotutaot:


Molecular wei&ht
[g/tsol*)
Not uteil in Subtitle
applications.
D
Hole fraction of
solute (- -|
Mot used in Subtitle
applications.
D
Solute vapor
pressure [na/H&]
Not used is Subtitle
•pplicetiobi.
D
B«nry's Lew
const. (eL»-*r*/Wl
Not used in Subtitle
applications.
D
C - Constant	Lxp	- Exponent i a 1	Emp ¦ Effipi r i c a 1
M - Hormal	U	- Itolfons	SB - Johnson SB
Ln - Lognomil	Log ,,u	• Log^lfni form	G	¦ Gelher

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Table 5-6 indicates that four of the parameters in the Chemical Data Group can
be derived. If the user chooses to have the code calculate the values of
these parameters, additional parameters are needed (see Table 5-3). All of
the Chemical Data Group parameters can be assigned a constant value or, in
Monte Carlo mode, can be assigned one of seven Monte Carlo distributions. If
a Monte Carlo distribution is selected for any of the parameters, additional
information defining the distribution must be entered for that parameter (see
Table 5-7). The Monte Carlo distributions are described in Section 9.5 of
Salhotra et al. (1990). Also, limited help in determining the appropriate
Monte Carlo distribution for a particular parameter is provided In Section 6.
Most of the parameters are undefined initially in the preprocessor and muse
have a value assigned to them before an input file can be completed. Note
chat three of the parameters have a default value of zero assigned initially.
The default values can be changed at the user's discretion.
5.3.2.3	Source Data Croup--
Table 5-8 lists the parameters in the Source Data Group. Note that in
Subtitle D applications the source Is assumed to be continuous and non-
decaying. Therefore, two of the parameters, the duration of the pulse and the
source decay constant, can not be modified by the user. Refer to Tables 5-2
through 5-5 In order to determine which of the remaining parameters are needed
for specific model applications.
The values specified for the Infiltration rate and the Initial chemical con-
centration entering the subsurface from the facility are difficult to deter-
mine and yet are critical ro the modeling effort. Refer to Section 5.2.^ for
information about the values to use for these parameters when designing
Subcltle D facilities. Some general information is also provided In Section 6.
Three of the parameters listed in Table 5-8 can be derived. The derivation of
these parameters Is described in Section 6 and Table 5-3 summarizes the para-
meters needed for the derivations. All of the Source Data Group parameters
can be assigned a constant value or, In Monte Carlo mode, can be as-signed one
of seven Monte Carlo distributions described In Section 9.5 of Salhotra et al.
( ICJ 9 0) . Refer to Table 5-7 for a list of the additional para-meters required
when a Monte Carlo distribution Is specified for an Input parameter.
5.3.2.4	Aquifer Data Croup--
The parameters in the Aquifer Data Group of the preprocessor are shown in
Table 5-9. This data group contains the largest number of parameters of' all
(he data groups, but many of thein are "secondary" parameters (I.e., parameters
used to derive the "primary" parameters or other "secondary" parameters). De-
pending on selections made by the user, some of these "secondary" parameters
may not be used by the code. Refer to Tables 5-2 and 5-3 and to Section (> in
order to understand the relationships between these parameters and parameters
in oilier data groups.
The parameters used to specify well location are restricted in Subtitle D ap-
plications. Only the downgradlent distance from the site can be Input by the
user. Otherwise, it is assumed that the well is on the pl^ine centerline and
screened at the top of the aquifer. The well angle off center and vertical
distance can not be modified, nor can they be assigned a Monte Carlo distribu-
tion.
7 1

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TABLE 5-7. PARAMETERS REQUIRED FOR SELECTED PROBABILITY DENSITY DTSTRIBUTTONS
Distribution
Required Parameters
Norm>11
minimum, maximum, mean, standard deviation
Lognorma1
minimum, maximum, mean, standard deviation
Exponent ial
minimum, maximum, mean
Unlform
minimum, maximum
Log10uniforra
minimum, maximum
Johnson SB
minimum, maximum, mean, standard deviation
Empirical
minimum, maximum, up to 20 pairs of data
defining the probability and associated
value (which describe the distribution)
In the prepr jessor, the geometry of the source boundary condition for the
aquifer is specified in the Aquifer Data Croup. For Subtitle D applications,
only a Gaussian source is allowed which is described in Section 5 of Salhotra
et al. (1990). Therefore, default value set in the preprocessor is Gaussian.
All of the Aquifer Data Croup parameters which are not being derived can be
assigned either constant values or, in Monte Carlo mode, one of seven
distributions (see Table 5-9). Note that an eighth distribution type is
available in Monte Carlo mode for the longitudinal, transverse, and vertical
dispersivities--the Celhar distribution. This special distribution Is
described in Section 6.5.10 and summarized In Table 6-12(a).
5 - i.2.5 Unsaturated Zone Flow Data Croup--
Table 5-10 shows the parameters in the Unsaturated Zone Flow Data Croup. The
parameters listed under the heading "Control Parameters" will influence the
type of data which can be input in this data group. Thus, these three
parameters should be specified first. Each has been assigned a default value
which can be changed based on site-specific Information. The dei^ult values
are 1 flow layer, 1 material type, and the use of van Ge'nuchten parameters Co
determine the relationship between relative permeability and water saturation.
Note that the number of materials can never be greater than the ntunber of
layers. Also note that the same material type can be assigned to more than
one layer.
When only one layer Is modeled, Its thickness is equal to the depth of the
unsaturated zone and the depth can be assigned a Monte Carlo distribution.
When multiple layers are simulated, their thicknesses must be assigned
constant values.
Parameters related to material properties and functional relationships must he
spec 1 fled lor each material type being modeled. All of these parameters can
be assigned a constant value or, In Monte Carlo mode, one of seven Monte Carlo
72

-------
TABLE 5-6. PARAMETERS IN THE CONTAMINANT SOURCE (SOurce) DATA CROUP
FaratMtt: Uri
1
0« r\ved



Spec x iied



Default
Consents



c
H
Ln
Exp U LogloU
Eap
SB
G


Ir.f i 1 tr *t ion rate
[m/yrJ


¦
¦
¦
¦ ¦ ¦
¦
¦



Axes of waste unit
ImVyr)


•
-¦
•
¦ ¦ ¦
¦
¦



Duration of puis*
lyrl










Ret needed because
Subtitle D applications
amt be steady-state
Spread of souxct
[a]

m
•
¦
¦
¦ ¦ •
¦
•



Recharge rate
[m/yr ]


¦
¦
¦
¦ ¦ ¦
¦
¦



Source Decmy constant
11/yr]


¦






0
Set ¦ 0 for Subtitle D
applications
Initial concentration
[e*/l]


¦
¦
¦
• . ¦ ¦
•
¦



Length scale [n]

¦
¦
¦
¦
¦ ¦ ¦
'¦
¦



Width seal* (d)

¦
¦
¦
¦
¦ ¦





iii
U«-5
Constant
Honu 1
Lognomwil


E*p
U
Loft.e"
¦
Exponential
Uni forre
Lo$,#Un i form

Efflp
SB
0
'
Empirical
Johnson SB
Gelhar


-------
TABLE 5-9. PARAMETERS IN THE AQl't FER (AQuifer) DATA GROUP
F&ratse*..*: Units
Der:ved



Spec ifled



Default
Comments


C
N
Ln
£xp U Los,gU
Eop
SB
G


Pupth and Particle Characteristics:










Particle
di«n*t«r [cm]
¦
¦
¦
¦
¦ ¦ ¦
¦
¦


Cannot be derived if
aquifer porosity is
derived.
Porosity |--3
¦
¦
¦
¦
¦ ¦ ¦
¦
¦


Cannot be derived if
particle diameter is
derived.
BuLk Density (s/cc 3
¦
¦
¦
a
¦ ¦ ¦
¦
¦



Aquifer thickness
la]

¦
B
¦
¦ ¦ ¦
¦
¦



Source thickness
[a]
m
¦
¦
m
¦ ¦ ¦
¦
¦



Type of Soarc* (Saossla or Patch) :








Gaussian

BrdmLlc md DisDonloa-Relatad Pu
Meiers :









frydiaulic Conductivity
[a/yr 1
¦
c
¦
•
¦ ¦ ¦
¦
¦



Bycireulic gradient
t-M

¦
¦
9
¦ ¦ ¦
¦
¦



Seepage velocity
!m/yr]
¦
¦
¦
¦
¦ ¦





C • Constant
K • Horoal
Ln ¦ Lognormai


Exp
U
Log ,#u
-
Exponential
Uniform
Log, .Uni form

Eop
SB
G
-
Eopi r i ca1
Johnson SB
Gelhar


-------
TABLE b-° PARAMETERS IN THE
AQUIFER
(AQuifer) DATA
GROUP





raracteter Units
Dcr ivad



Specifi ed



DefeuJ.l
Coomerits


c
N
Ln
Exp U
LosiaU
Entp
SB C


Retardation coaff.
{"J
¦
¦
¦
¦
¦ ¦
¦
¦
¦


L&ngxtudinal
Disp«raivity (0)
¦
¦
¦
¦
¦ ¦
¦
¦
¦


?ransv«rae
Dispcraavity (to]
¦
¦
¦
¦
¦ ¦
¦
¦
¦


Vertical
Disperaivity (a]
¦
¦
¦
¦
¦ ¦
¦
¦
¦


Sourca thicknaaa
[»]
¦
B
¦
¦
¦ ¦
¦
¦
¦


WiMliWBCIl Paj—a tara •










Taoparatur# l"C)

¦
¦
¦
¦ ¦
¦
¦



pB ("I

¦
¦
¦
¦ ¦
¦
¦



Organic carbon
content (fraction)

¦
¦
¦
¦ ¦





C • Constant
N ¦ Hortnal
Ln - Lo&nonaal


Erp
U
Loft„u
-
Exponential
Uni form
Log iaUnl form


Cop m
SB
G
Ecopi ricol
Johnson SB
Gaihar


-------
TABLE 5-9
PARAMETERS IN THE AQUIFER (AQuifer) DATA GROUP (concluded)
Derived Specified Default
		1	—	 Va lue
C	S	Ln	Exp	U	Loft,eU	Emp	SB	G
U«li-telat«d DtraeUn:











Receptor distance
froci sive [id]

• .
¦
¦
¦
¦
¦
¦
¦


An&le off center

¦







0
Set ¦ 0 for Subtitle D
applications.
Well verticle
distance (fraction)

¦







0
Set • 0 for Subtitle D
applications.
Flo^ to reject wells
outside plxsse










Not used in Subtitle D
applications.
Source thickness
(«1
¦
¦
¦
¦
¦
¦
¦
•
¦


Hi Ktllmoos ParMitn:











Teapereture (*C)

¦
¦
¦
¦
¦
¦
¦



pfl {"}

¦
¦
¦
¦
¦
¦
¦



Organic carbon
content (fraction]

¦
¦
¦
¦
¦





C • Cons tant.	Exp	¦ Exponential	Emp - Empirical
ft - normal	U	- Uniform	SE - Johnson SB
Ln * Lognormal	Lo&„u	" Lo^Uni form	G	¦ Gelhar

-------
TABLE 5-10. PARAMETERS IN THE UNSATURATED ZONE FLOW (FunsaC) DATA GROUP
P«racaeier Unics Derived



Spec i f i ed



Default
Coanonts

C
N
Ln
Exp U lofiITU
Enp
SB
G


Ccntrol Pwtcrs.









Umber of porcua
materials
¦






1

van Genuchten or
Brook, a/Corey







van
Genuchten

Ihabtr of phrtical
'flew layers
¦






1

L»r«r ThickiMJia ami NiUrlal for E*ch Lmjmr:









For 1 layer:
Depth of the unael. zone
¦
¦
¦
¦ ¦ ¦
¦
¦
¦


For > 1 Layer:
Thicknesa [b]
¦








For > 1 layer: ¦
Materiel ntixber ot layers







0

Hatarial Prooertia (for Cadi Material}:









Saturated hydraulic ¦
conductivity (cm/hr]
¦
¦
¦
¦ ¦ ¦
¦




Porosity [--]
¦
¦
¦
B ¦ ¦
¦




C ¦ Constant
N ¦ Normal
Ln " Lo&no nu 1

Exp
U
Lo6,»u
-
Exponential
Uni form
Log10Uni form

Emp
SB
G
-
Empirical
Johnson SB
Gelhar


-------
TABLE 5-10. PARAMETERS IN THE UNSATURATED ZONE FLOW (Funsat) DATA CROUP (c oneluded )
Fftraacic; Units Derived



Spec:
f i ed



Default
C cements

C
H
Ln
Exp U
LoBi„U
Enip
SB
G


Mr entry pressure
heed («nl
¦
¦
¦
m ¦
¦
¦
¦



FuzkLIomI Coefficients (for each ul«rial);










RtaidutL water
content [--)
¦
¦
¦
¦ •
¦
¦
¦



Brooks and Corey
'exponent I --]
¦
m
¦
¦ ¦
¦
¦
¦


Rot needed if van
Genuchten is specified
in control parameters.
Alpha vsd Genuchten
cceff. [1/ca]
¦
¦
¦
¦ ¦
¦
¦
¦



Bete van Genuchten
coeff f--]
¦
v
¦
¦ ¦
¦
¦
¦



C • Constant
R ¦ Normal
Ln " Lo&normal

Exp
U
Los,*u
-
Exponential
Uni form
LogloUni forte


Ezup
SB
G
-
Empirical
Johnson SB
Gelhar


-------
distribution types, The specification of a Monte Carlo distribution requites
additional data defining the distribution be input (see Table 5-7). None of
the Unsaturated Zone Flow Data Group parameters can be derived.
5.3.2.6 Unsaturated Zone Transport Data Croup--
The parameters contained in the Unsaturated Zone Transport Data Group are
found in Table 5-11. All of the parameters listed under "Control Parameters"
have default values associated with them. The number of layers is defaulted
to 1, which corresponds with the number of layers in the Unsaturated Flow Data
Group. However, under most conditions the number and thickness of transport
layers need not correspond to the number and thickness of flow layers. There
are a couple of restrictions: 1) the sura of the transport layer thicknesses
must equal the sum of the flow layer thicknesses, and 2) if the depth of the
unsaturated zone is assigned a Monte Carlo distribution in the Unsaturated
Zone Flow Data Croup (see Table 5-10), only one transport layer is allowed.
Unless the modeler has a good understanding of the other "Control Parameters,
it is recommended that the default values be used.
For each transport layer being simulated, five parameters need to be speci-
fied. The thickness of each layer must be assigned a constant value. The
other four parameters can have distributions assigned to them in Monte Carlo
mode. Remember that the specification of a Monte Carlo distribution requires
that additional data be supplied (see Table 5-7). The longitudinal dispersi-
vity of each layer can be either specified or derived. The derivation of this
parameter is described in Section 6.4.2.
79

-------
TABLE 5-11. PARAMETERS
IN THE UNSATURATED
ZONE
TRANSPORT
(Tunsat) DATA GROUP




Parameter Units
Der ived


Spec ified


Default
Comaenta

C
N
Ln
Exp U Lofc.JJ Emp
SB
G


Control PtrMlen:








Rvnber of layers
¦





1
Tbe number of layers
need not correspond to
the nuaber of layers in
Unsaturated Flow.
Seheoke for evaluation






Stehfest

Runbtr of tarns for
schsee
¦





16
16 is recocaaetided value
lor Stehfest scheme
(the default]
Ihnber of points used for
interpolating cones.
¦





3

_ Ihasber of Gaussian
00
o points
¦





104

Convolution integral
•assents
¦





2

Property Ft—tan (for each transport lirtr):
Thickness of the layer	•
[ml
Longitudinal
diapersivlty
[m]

¦ ' •
m
¦
¦ . ¦
¦
¦

Percent organic
cutter


m
¦
¦
• ¦
¦
¦

C
H
Ln
-
Constant
Normal
Lognormal

Erp
U
Log ,eu
¦
Exponent!al
tlni form
Log„.Uni form


Eorp • Empirical
SB • Johnson SB
G ¦ Galhar

-------
TABLE 5-11. PARAMETERS IN THE UNSATURATED ZONE TRANSPORT (Tunsat) DATA GROUP (concluded)
Parameter Units	Derived	Specified	Default	Coex&enta

C
N
Ln
Exp
u
LeaIOU
Eftp
SB
G
Bulk density |$/cc)
¦
¦
¦
¦
¦
¦
¦
¦

Biological decay
coeff. [1/yrJ
¦
¦
¦
V
¦
¦
¦
¦

C - Constant	Exp	- Exponential	Eop • Empirical
H ¦ Ron«l	U	* Uniform	SB • Johnson SB
Ln - Lognormal	Log„u	¦ Log „ltoi Corn	G	* G«lhar

-------
SECTION 6
PARAMETER ESTIMATION
This section is intended to provide guidance for estimating parameters
required by MULTIMED for Subtitle D land disposal facility applications. It
is not intended in any way to be used as a substitute for data collection.
Reported values are presented to demonstrate appropriate ranges of values for
particular parameters. For easy reference, the parameters are grouped
according to the model data group with which they are associated.
The most accurate model results will be obtained from simulations which are
based on site-spec ific data collection. In some cases, however, it Is noL
feasLble to measure certain parameters, and satisfactory results have been
obtained using estimated values. The code contains the option to Internally
derive some parameters based on other input parameters. It is recommended
thac this option be used with caution and only when values from measurements
at the site are not available. The parameters that can be derived are
identified in this section. The methods used in the code to calculate the
derived parameters are summarized briefly in this section, and are discussed
in more detail in the MULTIMED model theory documentation (Salhotra et al. ,
1990).
There are many sources of uncertainty in the prediction of contaminant migra-
tion in the subsurface. Utilizing the Monte Carlo option In the model is a
method to determine the effect of uncertainty in the model input on the model
results. In this option, a parameter is assigned a distribution and Its value
is then randomly generated. It is often difficult to determine the cumulative
probability distribution for a given parameter. These distributions must be
determined from a large amount of data, which may not be avail-able. Assuming
a parameter probability distribution when the distribution is unknown does not
help reduce uncertainty, as the certainty of the output is then a function of
the assumed certainty of the input parameter (U.S. EPA, 1988).
Some guidance on determining an appropriate probability density distribution
for specific parameters is provided in this section. When possible, tables of
descriptive statistics are also given. This Information can be ignored If the
model is run in a deterministic framework. General information related to the
probability distributions andhelp In determining the number of Monce Carlo
runs needed is provided in Section 9 of the MULTIMED model theory documenta-
tion (Salhotra et al., 1990).
6.1 CHEMICAL-SPECIFIC PARAMETERS
6.1.1 Overall Chemical Decay Coefficient (Saturated Zone) 11/vrl
This parameter can be derived by the code, which computes it by summing the
solid and liquid phase decay coefficients for the saturated zone. Note that
the overall chemical decay coefficient does not include biological decay; the
biodegradation coefficient must be specified separately. If the value, for the
overall chemical decay coefficient is specified by the user as a constant or a
distribution, the solid and dissolved phase decay coefficients are not needed.
82

-------
In general, che overall decay coefficient for the saturated zone will be
smaller in value Chan for the unsaturated zone.
6.1.2 Solid-Phase and Liquid-Phase Decay Coefficients (Saturated Zone) ll/vrl
These decay coefficients represent the hvdrolvsls rate constants for the
saturated zone. They do not include biological decay, which Is discussed In
Section 6.1.7. Hydrolysis is a potentially significant elimination pathway
for many organic chemicals (Lyman ec al., 1982). For compounds which are
easily blodegraded, however, hydrolysis may be insignificant relative to
biodegradation (see Section 6.1.7). The hydrolysis of organic che.nlcals can
be described as a first-order rate process with respect to the concentration
of the organic species (Faust and Goraaa, 1972; Wolfe et al., 1977; 1978) and
is dependent on temperature, pH, adsorption, and the presence of organic
solvents. Methods for estimating the rate constant for the hydrolysis process
are presented in Lyman et al. (1982).
The solid-phase and liquid-phase hydrolysis race constants can he derived In
the code, using input for Che acid, base, and neutral hydrolysis rate con-
stants, the reference temperature, and the temperature and pH of che aquifer
The method used by the code to derive these parameters is discussed in Section
5.5.2.1 of the MULTIMED model theory documentation (Salhotra ec al., 1990).
The use of acid, base, and neutral hydrolysis rates takes into account the
scrong pH dependence of this process.
If the values of both the ftolld and dlfisolvod phfiRtt decay coi> f [ I c I rnt >i hit
s|)uc1tled by the user, thun che saturated transport module does not use the
values of the acid, base, and neutral hydrolysis rate constants. They are
needed, however, if unsaturated transport and/or surface water transport are
also being simulated.
6.1.-3 The Acid-Catalvzed and Base-Cata 1vzed Hvdrolvsls Rates [f/M-vrl and
the Neutral Hvdrolvsls Rate ll/vrl
These three parameters are used in the code to calculate che overall chemical
decay coefficient for the unsaturated, saturated, and surface water modules.
The use of these parameters in the unsaturated and saturated transporc modules
is described in Seccion 5.5.2.1 of Salhotra et al. (1990). For Che surface
water module, refer to Section 6.2.1 of the same document. Values of these
hydrolysis rate constants are available in a large number of references,
including Lyman et al. (1982), Mabey et al. (1982), and Mills et al . ( 1985a).
6.1.4	Reference Temperature I°C1
The reference temperature is the temperature at which k* b and K^r were
calculated and is normally provided along with the hydrolysis race constant
da ca .
6.1.5	Discributlon Coefficient (Saturated Zone) fml/el
Sorption refers to the accumulation of a chemical in the boundary region of a
solid-liquid interface (Mills et al., 1985a). Because sorption retards
chemical transport in the subsurface, the fate of a chemical is highly
dependent on its sorptive characteristics (i.e.. the distribution between the
sorbed and dissolved phases). MULTIMED assumes chat a linear equation can
describe the relationship.between the equilibrium concentrations of the
83

-------
dissolved and adsorbed phases. The linear relationship requires knowledge of
the chemical distribution coefficient, K,,. A number of studies have developed
empirical relationships for the partition coefficient. The relationship most
suited for relating the chemical distribution coefficient to soil or porous
medium properties is discussed in detail by Karickhoff (1984).
In the absence of a user-supplled value, the chemical distribution coefficient
for the saturated zone, Kd, can be derived by the code. Hydrophobic binding
is assumed to dominate the sorption process and thus, the distribution
coefficient is related directly to soil organic carbon content using:
~	Kocfoc	(61)
where
Koc -	normalized distribution coefficient for organic carbon [m?/g]
foc "	organic carbon content in the saturated zone [dimensionless fraction]
The estimation of the normalized distribution coefficient for organic carbon
Is discussed below.
6.1.6	Normalized Organic Carbon Distribution Coefficient (ml/pl
The normalized organic carbon distribution coefficient, Koc, is used in the
i ode to calculate the chemical distribution coefficient in the unsaturated
transport and the surface water modules. It is also used In the saturated
transport module when the user chooses to derive the chemical distribution
coefficient. There are many published lists of values for Koc. Data are
available primarily for pesticides and. to a lesser degree, aromatic and
polycyclic aromatic compounds. Lyman et al. (1982) recommend ten different
references which contain values of Koc.
If data on Kcc are not available for a particular chemical, a value can be
estimated from empirical relationships between Koc and some other property of
the chemical such as the water solubility, S, the octanol-water partition
coefficient, Kow, or the bloconcentrat ion factor for aquatic life, BCF. Lyinan
et al. (1982) tabulate 12 such regression equations obtained from data sets of
different classes of chemicals, and present guidelines for selecting an
accurate and applicable equation for a particular chemical. Values for the
uctanol-water partition coefficient and solubility of priorIty.pollutants are
available in many references, Including Mabey et al. (1982) and MiD.s et al.
( 1985a).
6.1.7	Biodep.radation Coefficient (Saturated Zone) H/vrl
Biodegradation, along with hydrolysis, is one of the decay pathways considered
by MULTIMED. For many contaminants, biodegradation is the most significant
means of removal from the subsurface environment. However, the biodegradation
of chemicals in the environment is complex, depending on a number of variable
and/or unknown factors, such as the number of microorganisms present, the
availability of oxygen and other nutrients, and the pH and temperature of the
system.
A first-order kinetic relationship is normally used to represent b'.odegrada-
tlon In the natural environment. It is difficult to estimate the biodegrada-
tion coefficient needed in this relationship. Although attempts have been made
8U

-------
Co correlate the biodegradability of a compound with its molecular character-
istics, such as solubility, these generalizations are applicable only to the
specific chemicals investigated, and are not recommended estimation techniques
for other chemicals (Lyman et al., 1982). A significant amount of work is
needed to validate the extension of these techniques to other chemicals and
condi tions.
A compilation of laboratory-derived biodegradation rate constants reported in
the literature, along with the test conditions when available, is presented In
Ly.nan et al. (1982). The tables include rate constants for several organic
compounds in both aqueous environments and soils. However, since these con-
stants were determined under laboratory conditions, they may be inapplicable
to a field situation. Additional data are available in Mills et al. (1985a)
and Mabey et al. (1982). Care should be taken in extrapolating the results
shown in any of these tables co actual environmental situations.
6.2 SOURCE-SPECIFIC PARAMETERS
6.2.1 Recharge Rate fm/vrl
The recharge rate in this model is the net amount of water that percolates
directly into the aquifer system outside of the land disposal facility. The
recharge is assumed to have no contamination and hence dilutes the groundwater
contaminant plume. The recharge rate into the plume can be calculated in a
variety of ways. One possibility is to use a model, such as HELP (Hydrologic
Evaluation of Landfill Performance) (Schroeder et al., 1984), without any
engineering controls (leachate collection system or a liner) to simulate the
water balance for natural conditions. Results of such an analysis have been
presented by E.C. Jordan Co. (1985. 1987).
6.22 Infiltration Race [m/vrl
The infiltration rate is the net amount of leachate that percolates into che
aquifer system from a land disposal facility. Because, of the use of engineer-
ing controls and the presence of non-native porous materials in the landfill
facility, the infiltration rate will typically be different than the recharge
rate. However, it can be estimated by similar methods as those discussed for
estimation of the recharge rate.
6.2.3	Area of Waste Disposal Unit fm21
The area of the waste disposal unit will vary significantly from site to site.
The area should be directly measured and input by the user.
6.2.4	Lenpth Scale of Facility fm1
The length of the waste disposal facility should be measured at che sice.
However, this parameter can be derived by the code. The derivation is based
on the assumption that the waste disposal facility has a square shape.
Therefore, the code takes the square root of the area:
L - (Aw)^	(6.2)
6.2.5	Width Scale of Facility (ml
The width of the waste disposal facility should be measured at the site.
However, as was true for the lengch scale of the facility (Section 6.2.'''),
this parameter can be derived by che code, which calculates the width of the
facility as the square root of the area.
85

-------
6.2.6 Initial Concentration at Waste Disposal Facility lm^/11
When possible, site-specific data should be used. However, the user should
bear in mind that concentrations are quite variable over time and thus, a li-
mited set of data may not be representative of conditions at the facility. If
data are not available, a conservative approximation would be the solubility
of the contaminant In water.
When using the model for the design of Subtitle D facilities, a value of 100
times the Drinking Water Standard can be used (see Section 5.2.4). If the
concentration at the well (I.e., point of compliance) is at or below the
Drinking Water Standard, the design may prove acceptable. Since the model
response is linear with this parameter, It Is convenient to use 1.0 mg/1 as
the initial concentration and to calculate a dilution-attenuation factor (DAF)
as discussed in Section 5.4.2.
6.2.7	Source Decay Constant fl/vrl
The source decay constant Is used for simulation of an exponentially decrea-
sing (in time) boundary condition (see Section 5.2 of Salhotra et al., 1990).
However, the source is assumed to be constant in Subtitle D applications of
MULTIMED. Therefore, for Subtitle D applications the preprocessor sets a
default value of 0 for the source decay rate.
6.2.8	Duration of Pulse Ivrl
The duration of the contaminant pulse is not required In steady-state applica-
tions of MULTIMED. Therefore, this parameter does not need to be estimated
for Subtitle D applications, which must be steady-state.
6.2.9	Spread of Contaminant Source [ml
The standard deviation of the gaussian source is a measure of the spread of
the source. It can be estimated or derived by the code as:
o - W/6	(6.3)
where
W -• the width scale of the fac i 1 i ty - - i . e . , the dimension of the facility
orthogonal to the groundwater flow direction [m]
Dividing by 6 implies that 99.86 percent of the gaussian source spread is
within the facility.
6.3 UNSATURATED FLOW PARAMETERS
6.3.1 Saturated Hydraulic Conductivity fcm/hrl
Hydraulic conductivity expresses the ease with whi^h a fluid can be transpor-
ted through a porous medium and is a function of properties of both the porous
medium and the fluid (Mills et al., 1985b). Note that for some materials,
such as alluvium, the vertical hydraulic conductivity is significantly smaller
than the horizontal hydraulic conductivity. Mills et al. (1985b) state that
the ratio of horizontal to vertical conductivity is from 2 to 10 for alluvium
and glacial outwash and from 1.5 to 3 for sandstone. In the unsaturated zone
86

-------
module, flow, is one-dimensional in the vertical direction, so the vertical,
hydraulic conductivity should be input. Note that in the saturated zone,
horizontal hydraulic conductivity is required.
One of the most widely-used tables of hydraulic conductivity values is
presented in Table 6-1. Note that the use of the values in this table vil)
require a conversion to the units of cm/hr In addition, descriptive statis-
tics for a variety of soil types are given in Table 6-2. The values for Che
coefficients of variation in column three are determined from many soils
nationwide which fall into each texture group. The coefficient of variation
for a single soil is likely to be lower.
The lognormal distribution is likely to be an appropriate probability density
function for saturated hydraulic conductivity (Dean et al., 1989).
6.3.2 Unsaturated Zone Porosity f--l
Porosity is a measure of the relative volume of void space in a rock or soil.
Porosity is dimensionless and is expressed as a fraction or a percentage. The
total porosity of a rock or soil is comprised of primary porosity, which is
due to the shape, sorting and packing of the grains in the matrix, and
secondary porosity, which is due to phenomena such as cracks and fractures.
MULTIMED requires the effective porosity of the rock or soil as input. The
effective porosity is that part of the total porosity which is effective at
transmitting water. The effective porosity is typically lower than the toca]
porosity, due to the presence of pores which are not interconnected or the
preser-.e of an immobile water film bound to soil grains. In general, labora-
tory measurements obtain values for total porosity, since effective porosity'
is difficult to measure directly.
Typical total porosity values for a variety ot geologic materials are present-
ed in Table 6-3. Jury (1985) states that & normal distribution is an appro-
priate probability density function for effective porosity.
6.3.3 Air Entry Pressure Head [ml
The air entry pressure head is the threshold at which air starts to penetrate
saturated soil. It is typically a very small negative value for fine-grained
materials or zero for coarser soils. Its value can be estimated from the
water retention curves of specific soils (Freeze and Cherry, 1979).
6.3.^» Number of Layers. Thickness of Layers I ml
The unsaturated zone extends from the land surface or the bottom of a waste
disposal facility to the top of the water cable. This distance will vary
significantly from site to site. An estimate of this depth can be determined
from water level measurements in the area of the site.
87

-------
TABLE 6.1. RANGE OF HYDRAULIC CONDUCTIVITY VALUES FOR VARIOUS GEOLOGIC
MATERIALS (Freeze and Cherry, 1979)
Rocht
UnronidMattd
dtpeiirt
:!J
i
* * K K	K
(dorqr) (cm*) (on/UtmA) (gol/dor/ll*)
-JO*
r«r»
10*
r 1

¦10*
¦tor*
-10
-10"'
-10*
•I01
¦kr1
-i
¦IO*1
-10*
¦to*
¦xr*
tor*
to-1
-IO4
-10
¦KT?
iff*
¦to"*
¦ 10*
¦ 1
¦tor*
ior*
-10**
¦to1
-tor*
¦10"*
iff*
-XT*
•10
IO"4
¦\a*
tor*
•Iff'
¦ 1
¦i
fi*
dwcy

HA
U-t. gtUtof/W
cm*
1
MX x 10-1
1.01 x IV
• JO K 10*
U2 x I0»
I .I J x 10*
ft'
Mix 10*
1
Ml * I0«*
».ll K 10*
2.99 X 10*
I.TI x 10">
dirty
9.17 » lfr»
I.M x I0-"
1
1M x icr«
1.17 x |
i
U1
2.12 x 10*
fi/i
3.11 m 10-*
XIS » 10-'
J.IJ x JO*
J.0J Kio-I
1
6.44 x 10'
U S. i»l/djjr/nij.4j x IO-i»
J.I) x IO-»
3.49 x 10-*
4.71 x (0*T
I.Ji x 10**
1
"To obula k fa (l1, multiply k Incm> by t J6t * 10">.
88

-------
TABLE 6-2. DESCRIPTIVE STATISTICS FOR SATURATED HYDRAULIC CONDUCTIVITY
(era hr"1)


Hydraulic Conductivity (K„)*

Soil Type
X
s
CV
n
Clay**
0.20
0.42
210.3
114
Clay Loam
0.26
0.70
267.2
345
Loam
1.04
1.82
174.6
735
Loamy Sand
14.59
11. 36
77.9
315
Silt
0.25
0.33
129.9
88
Silt Loam
0,45
1.23
275.1
1093
Silty Clay
0.02
0.11
453.3
126
Sllty Clay Loam
0.07
0.19
288.7
592
Sand
29. 70
15.60
52.4
246
Sandy Clay
0.12
0.28
234.1
46
Sandy Clay Loam
1.31
2.74
208.6
214
Sandy Loam
4.42
5.63
127.0
1183
n - Sample size, x - Mean, s - Standard deviation, CV - Coefficient of
variation (percent)
Agricultural soil, less than 60 percent clay
Sources: From Dean et al. (1989),
Original reference Carsel and Parrlsh (1988).
89

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TABLE 6-3. TOTAL POROSITY OF VARIOUS MATERIALS
Material
No. of
Analyses
Range
Arithmetic
Mean
Igneous Rocks
Weathered granite
Weathered gabbro
Basalt
8
4
94
0,34-0.57
0.42-0.45
0.03-0.35
0.45
0.43
0 17
Sedimentary Materials
Sandstone
Siltstone
Sand (fine)
Sand (coarse)
Gravel (fine)
Gravel (coarse)
Silt
Clay
65
7
243
26
38
15
281
74
74
0.14-0.49
0.21-0.41
0.26-0.53
0.31-0.46
0.25-0.38
0.24-0.36
0.34-0.61
0.34-0.57
0.07-0.56
0. 34
0 . 35
0.43
0. 39
0. 34
0.28
0.46
0.42
0. 30
Limestone
Metamorphic Rocks
Schist
18
0.04-0.49
0.38
Sources: From Mercer et al. (1982),
McWhorter and Sunada (1977),
Original reference Morris and Johnson, (1967).
In MULTIMED, the unsaturated zon>_ can be modeled with up to 20 layers which
have distinct physical characteristics. Information about the layers, which
should be relatively homogeneous and distinguishable from adjacent layers,
must be determined on a site-specific basis. Note that more than one layer
can be assigned the same material properties. When one homogeneous layer is
modeled, the layer thickness Is equal to Che depth of r.he unsaturated zone and
the depth of the unsaturated zone can have a Monte Carlo distribution assigned
to it. Refer to Section 6.4.1 for more information.
6 3.5 Residual Water Content f--l
The residual water content Is that amount of the total water content which can
not be removed from the soil, even under large suction pressure, because it
adheres to the soil grains. Descriptive statistic? for residual water content
for a variety of types of soils are presented in Table 6-4. In addition, the
residual water content for a large number of soils can be estimated using the
interactive computer program, DBAPE, which Is a soils data base analyzer and
parameter estimator (Imhoff et al., 1990). DBAPE is available from the U.S.
EPA Center for Environmental Assessment Modeling (CEAM) at the Environmental
Research Laboratory In Athens, Georgia.
90

-------
TABLE 6-4. DESCRIPTIVE STATISTICS FOR SATURATION WATER CONTENT (0,)
AND RESIDUAL WATER CONTENT (0r)
Saturation Water Content (9,) Residual Water Content (fir)
_	Statistic*
Soil Type	x	s	CV	n	x	s	CV	n
Clay"
0.38
0.09
24.1
400
0.068
0.034
49. 9
333
Clay Loam
0.41
0.09
22.4
364
0.095
0.010
10. 1
363
Loam
0.43
0.10
22 .1
735
0.078
0:013
16. 5
735
Loamy Sand
0.41
0.09
21.6
315
0.057
0.015
25. 7
315
Silt
0.46
0.11
17.4
82
0.034
0.010
29.8
82
Silt Loam
0.45
0.08
18,7
1093
0.067
0.015
21.6
1093
Silty Clay
0.36
0.07
19.6
374
0.070
0.023
33.5
371
Silty Clay Loam
0.43
0.07
17.2
641
0.089
0.009
10. 6
641
Sand
0.43
0.06
15.1
246
0.045
0.010
22. 3
246
Sandy Clay
0.38
0.05
13.7
46
0.100
0. 013
12. 9
46
Sandy Clay Loam
0.39
0.07
17 .5
214
0.100
0.006
6.0
214
Sandy Loam
0.41
0.09
21.0
1183
0.065
0.017
26.6
1183
n - Sample size, x - Mean. . - standard deviation, CV - coefficient of
variation (percent)
Agricultural soil, less than 60 percent clay.
Source: Dean et al. (1989)
Original source Carsel and Parrish (1988)
6.3.6 Brooks and Corev Exponent I - -1
The Brooks and Corey exponent, n, is an empirical parameter used' in an
equation which describes the relationship between relative permeability and
water saturation (see Section 3.2 of the MULTIME15 inodel theory documentation
(Salhotra et al., 1990)). The exponent can be determined from experimental
data for a soil's capillary pressure-desaturation curve. Brooks and Corey
(1966) present experimental results for several porous mac'la. The porous
media investigated by the authors had values of n ranging t'rom 3.27 for glass
beads to 4.11 for a silt loam. Soils composed of single-grained material with
no secondary porosity (e.g., sands) tend to have smaller exponent values.
Soils with structure or secondary porosity have larger exponent values.
In MULTIMED, the relationship between relative permeability and water satura-
tion may be described using either the Brooks and Corey (1966) or the van
Genuchten (1976) relationship (see Section 3 of Salhotra et al. (1990)). The
Brooks and Corey exponent.is not required when the use of the van Cenuchten
relationship is specified in the input. However, both the Brooks and Corey
<31

-------
exponent and the van Cenuchten parameters are required when the use of the
Brooks and Corey relationship is specified.
6.3.7 Van Cenuchten Parameters, a 11/cm): 3 f--l
In the code, the relationship between relative permeability and water satura- .
tion may be described using either the Brooks and Corey (1966) or the van
Cenuchten (1976) relationship. However, the pressure head versus water
saturation relationship is described using van Genuchten parameters (see
Section 3 of the MULTIMED model theory documentation (Salhotra et al.. 1990)).
Therefore, the van Cenuchten parameters must be input to simulate unsaturated
flow in the .code. Descriptive statistics for these empirical parameters have
been reported by Carsel and Parrish (1988) for a variety of soil types (see
Table 6-5).
6.4 UNSATURATED TRANSPORT PARAMETERS
6.4.1	Number of Layers. Thickness of Layers
The number of layers specified for transport in the unsaturated zone will
depend on the specific conditions present at the site. Layers should repre
sent zones that are relatively homogeneous with regard to the properties
affecting transport and that can be distinguished from adjacent layers by
changes in these properties. Note that the number and thickness of layers
specified in the transport module need not correspond to the number and
thickness of layers in the unsaturated flow module (see Section 6.3.4).
However, the sum of the Individual layer thicknesses in the two modules must
equal each other (i.e., the total depth of the unsaturated zone must agree in
the two modules). If the depth of the unsaturated zone is assigned a Monte
Carlo distribution in the unsaturated flow module, then only one unsaturated
transport layer is allowed.
6.4.2	Longitudinal Dlsperslvltv of Each Layer Iml
Hydrodynamic dispersion refers to the spreading and mixing caused by molecular
diffusion and mechanical dispersion (Freeze and Cherry, 1979). For many field
problems, molecular diffusion is small relative to mechanical dispersion and
can be ignored. Molecular diffusion is not considered in MULTIMED, which
calculates the longitudinal dispersion coefficient as the product of the
seepage velocity and longitudinal (aL) dlspersivlty. Note that longitudinal
dispersion is the dispersion in the predominant direction of flow, which is
vortical in the unsaturated zone.
Dispersivity is a difficult parameter to determine. Table 6-6 provides a
compilation of dispersivity values appropriate for the unsaturated transport
module. Research has shown that the values for longitudinal dispersivity are
scale dependent. In an unsaturated transport layer, if a value for the
longitudinal dispersivity is not input, the user can specify that the para-
meter be derived. The equation used in the model to calculate dispersivity is
based on regression analysis of the data ?'i Table 6-6. The following rela-
tionship between dispersivity and the depth of the unsaturated zone, L, was
developed:
av - 0.02 +0.022L,	R2 - 66%	(6.4)
92

-------
TABLE 6-5.
DESCRIPTIVE STATISTICS FOR VAN GENUCHTEN WATER RETENTION MODEL PARAMETERS, a, fl, and y (Carsel and
Parrish 1988)
Parameter o. cm"1	 	Parameter fl	Parameter y
Soil Type
X
SD
CV
N
X
SD
CV
N
X
SD
CV
N
Clay"
0.008
0.012
160.3
400
1.09
0.09
7.9
400
0.08
0.07
82. 7
400
Clay Loan
0.019
0.015
77.9
363
1. 31
0.09
7.2
364
0.24
0.06
23.5
364
Loan
0.036
0.021
57 .1
735
1.56
0.11
7.3
735
0.36
0.05
13.5
735
Loamy Sand
0.124
0.043
35.2
315
2.28
0.27
12.0
315
0.56
0.04
7.7
315
Silt
0.016
0.007
45.0
88
1.37
0.05
3.3
88
0.27
0.02
8.6
38
Silt Loam
0.020
0.012
64.7
1093
1.41
0.12
8.5
1093
0.29
0.06
19.9
1093
Silty Clay
0.005
0.005
113.6
126
1.09
0.06
5.0
374
0.09
0.05
51. 7
3 74
Silty Clay Loam
0.010
0.006
61.5
641
1.23
0.06
5.0
641
0.19
0.04
21.5
641
Sand
0.145
0.029
20.3
246
2.68
0.29
20.3
246
0.62
0.04
6.3
246
Sandy Clay
0.027
0.017
61.7
46
1.23
0.10
7.9
46
0.18
0.06
34.7
46
Sandy Clay Loam
0.059
0.038
64 .6
214
1.48
0.13
8.7
214
0.32
0.06
53.0
214
Sandy Loam
0.075
0.037
49 .4
1183
1.89
0.17
9.2
1183
0.47
0.05
10.1
1183
X - Mean. SD - Standard Deviation, CV - Coefficient of Variation (percent), N - Sample size
4 Agricultural Soil, Clay 60 percent

-------
To avoid excessively high values of disperslvity for deep unsaturated zones, a
maximum disperslvity of 1.0 a is used.
Distributional properties for longitudinal disperslvity are unknown (Dean et al.,
1989).
6.A.3 Percent Organic Matter f--l
Guidance in estimating the percent organic matter is provided in Table 6-7. Values
are given for the four Hydrologic Soil Groups and for four ranges of depth. From
Appendix B of the users manual for PRZM, Release I (Carsel et al., 1984) or from
Section 4 of the SCS National Engineering Handbook (Soil Conservation Service, 1972),
the hydrologic soil group for the particular soil that is in the area under consider-
ation can be found. There are four different soil classifications (A, B, C, and D),
and they are in the order of decreasing percolation potential and increasing slope
and runoff potential. Soil characteristics associated with each hydrologic group are
as follows:
Group A: Deep sand, deep loess, aggregated silts, minimum infiltration of
0.76 - 1.14 (cm hr'1)
Group B: Shallow loess, sandy loam, minimum infiltration 0.38 - 0.76 (cm
hr'1)
Group C: Clay loams, shallow sandy loam, soils low in organic content, and
soils usually high in clay, minimum infiltration 0.13 - 0.38 (cm
hr'1)
Group D: Soils that swell significantly when wet, heavy plastic clays, some
saline soils, minimum infiltration 0.03 • 0.13 (cm hr'1)
Carsel et al. (1988) state that a Johnson SB distribution is most appropriate for the
data in Table 6-7. Note that the percent organic matter typically decreases with
depth. More detailed data on percent organic matter are available through the
interactive computer program DBAPE discussed in Section 6.3.5 (Imhoff et al., 1990).
If the percent organic matter is not known, but the fractional organic carbon content
is given, the following equation can be used to estimate the percent organic matter:
172.4 fn
(6.5)
where
foe ~
172.4 -
fractional organic carbon content [dimensionless]
percent organic matter [dimensionless]
conversion factor from percent organic matter content to frac-
tional organic carbon content
94

-------
TABLE 6-6. COMPILATION OF FIELD DISPERSIVITY VALUES
Longitudinal
Type of	Vertical Scale	Dlsperslvlty
Author	Experiment of Experiment (a)	(m)
Yule and Gardner
(1978)
Laboratory
0.23
0.0022
Hlldebrand 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
Brlssaud 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
Blggar and Nielsen
(1976)
Field
1.83
0.05
Kles (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
* From Dean et al. (1989),
Original reference Gelhar et al. (1985).
95

-------
TABLE 6-7. DESCRIPTIVE STATISTICS AND DISTRIBUTION MODEL FOR ORGANIC
MATTER (PERCENT BY WEIGHT)
Stratum	Sample 	Original Data	 Distribution Model
CV
(m)	Size Mean Median s.d.	(X)	Mean	s.d.
Class A







0.0-0.3
162
0.86
0.62
0.79
92
-4.53
0.96
0.3-0.6
162
0.29
0.19
0.34
114
-5.72
0.91
0.6-0.9
151
0.15
0.10
0.14
94
-6.33
0.83
0.9-1.2
134
0.11
0.07
0.11
104
-6.72
0.87
Class B







0.0-0.3
1135
1.3
1.1
0.87
68
-4.02
0.76
0.3-0.6
1120
0.50
0.40
0.40
83
-5.04
0.77
0.6-0.9
1090
0.27
0.22
0.23
84
-5.65
0.75
0.9-1.2
1001
0.18
0.14
0.16
87
-6.10
0.78
Class C







0.0-0.3
838
1.45
1.15
1.12
77
-3.95
0.79
0.3-0.6
822
0.53
0.39
0.61
114
-5.08
0.84
0.3-0.9
780
0.28
0.22
0.27
96
-5.67
0.83
0.9-1.2
672
0.20
0.15
0.21
104
-6.03
0.88
Class D







0.0-0.3
638
1.34
1.15
0.87
66
-4.01
0.73
0.3-0.6
617
0.65
0.53
0.52
80
-4.79
0.78
0.6-0.9
558
0.41
0.32
0.34
84
-5.29
0.82
0.9-1.2
493
0.29
0.22
0.31
105
-5.65
0.86
CV - coefficient of variation
s.d. - standard deviation
Source: Dean et al. (1989), Original reference Carsel et al. (1988)
* Johnson sB transformation Is used for all cases In this table.
96

-------
6.4.4 Bulk Density of Soil for Laver fg/ccl
Bulk density can be defined as the mass of a unit volume of dry soil (Mercer et al.
1982). The soil bulk density directly Influences the retardation of solutes and is
related to the structure and-texture of a soil. The bulk density of soils typically
range between 1.3 and 2.0 g/cc, but Mercer et al. (1982) state that the bulk density
can be as low as 0.3 g/cc for soils high in organlcs or aluminum and iron hydroxides.
Representative values for five different types of soils are shown in Table 6-8. In
addition, values of bulk density for a large number of soils can be obtained from
DBAPE, discussed in Section 6.3.5 (Imhoff et al., 1990).
Descriptive statistics for bulk density are given in Table 6-9 for the four Hydrolo-
gic Soil Groups (A, B, C, and D) and for four ranges of depth. (A brief description
of the soil groups in given in Section 6.4.3.) The most appropriate probability
density distribution for bulk density is typically a normal distribution (Jury,
1985).
6.4.5 Biological Decay Coefficient fl/vrl
Estimation of the biodegradatlon rate constant is discussed in Section 6.1.7.
6.5 AQUIFER-SPECIFIC PARAMETERS
6.5.1	Aoulfer Porosltv f--l
Porosity is also discussed in Section 6.5.1 and values of porosity for various
materials are given in Table 6-3. It is an important parameter, Influencing the
velocity and retardation of contaminants transported in an aquifer (Mills et al.,
1985b). In the absence of a user-specified distribution for the aquifer porosity, it
can be derived by the code. It is calculated from the particle diameter using the
following empirical relationship (Federal Register Vol. 51, No. 9, p. 1649, 1986):
9 - 0.261 - 0.0385 ln(d)	(6.6)
where d is the mean particle diameter [cm].
6.5.2	Particle Diameter fcml
The particle diameter can be determined by methods such as sieve analysis (Freeze and
Cherry, 1979). Table 6-10 shows the range of soil particle sizes for a variety of
soil materials. If the porosity is known, the particle diameter can be derived using
Equation 6.6. Note that both porosity and particle diameter can not be derived in
the same simulation (i.e., at least one must be input by the user).
6.5.3	Bulk Density fg/ccl
Bulk density is discussed in Section 6.4.4 and Tables 6-8 and 6-9 provide data on the
bulk density of soils. However, the bulk density of aquifer materials may differ
significantly from that of soils. Therefore, data on the ranges of bulk density for
various geologic material are presented in Table 6-11.
97

-------
TABLE 6-8. MEAN BULK DENSITY (g/cms) FOR FIVE SOIL TEXTURAL
CLASSIFICATIONS*-*
Soil Texture
Mean Value
Range Reported
Silt Loams
Clay and Clay Loams
Sandy Loams
Gravelly Silt Loans
Loams
All Soils
1.22
1.32
1.30
1.49
1.42
1.35
1.16 - 1.58
0.86 - 1.76
0.86 - 1.67
0.94 - 1.54
1.25 - 1.76
1.02 - 1.58
a Baes, C.F., III and R.D. Sharp. 1983. A Proposal for Estimation of
Soil Leaching Constants for Use In Assessment Models. J. Environ.
Qual. 12(1):17-28 (Original reference).
b From Dean et al. (1989)
If site-specific data are not available, the bulk density of the saturated zone can
be derived by the model using an exact relationship between porosity, particle
density and the bulk density (Freeze and Cherry, 1979). Assuming the particle
density to be 2.65 g/cc, this relationship can be expressed as:
6.5.4	Aquifer Thickness fml
The estimation of the thickness of the aquifer is site-specific, and should be based
on available geologic data.
6.5.5	Source Thickness (Mixing Zone Depth) fml
Percolation of water through the facility (and unsaturated zone, if it exists)
results in the development of a contaminant plume below the facility (see Figure
6.1). The thickness, H, of this plume depends on the vertical dispersivity of the
media. If a value for H is not known, it can be derived in the model using the
following relationship:
pb - 2.65(1 - 9)
(6.7)
where pb - the bulk density of the soil [g/cc].
H - (2ov L)» + B(1 - exp (-
(6.8)
98

-------
Well Location
xr« Rcos^
yf » R sin V
Pl^N VIEW
Waste Facility

Ground Surface


¦
-nT"*
i i
H
xxxxxxxd
B
wxxxxxxx>
u
i
X
i
z,
'
>000
SECTION VIEW
Figure 6.1 Schematic of the source thickness and the well
location (from Salhotra et al., 19901.
99

-------
TABLE 6-9. DESCRIPTIVE STATISTICS FOR BULK DENSITY (g cm*3)
Stratum	Sample	CV
(m)	Size	Mean	Median	s.d.	(X)
Class A
0.0-0.3	40	1.45
0.3-0.6	44	1.S0
0.6-0.9	38	1.57
0.9-1.2	34	1.58
Class B
0.0-0.3	459	1.44
0.3-0.6	457	1.51
0.6-0.9	438	1.56
0.9-1.2	384	1.60
Class C
0.0-0.3	398	1.46
0.3-0.6	395	1.58
0.6-0.9	371	1.64
0.9-1.2	326	1.67
Class D
0.0-0.3	259	1.52
0.3-0.6	244	1.63
0.6-0.9	214	1.67
0.9-1.2	180	1.65
1.53	0.24	16.2
1.56	0.23	15.6
1.55	0.16	10.5
1.59	0.13	8.4
1.45	0.19	13.5
1.53	0.19	12.2
1.57	0.19	12.3
1.60	0.21	12.9
1.48	0.22	15.0
1.59	0.23	14.5
1.65	0.23	14.2
1.68	0.23	14.0
1.53	0.24	15.9
1.66	0.26	16.0
1.72	0.27	16.3
1.72	0.28	17.0
CV - coefficient of variation
s.d. - standard deviation
Sources: From Dean et al. (1989),
Original referance Carsel et al. (1988).
100

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TABLE 6-10. RANGE OF SOIL PARTICLE SIZES FOR VARIOUS MATERIALS
	Size Range		Approximate Sieve Mesh
Openings
Class name	Millimeters	Inches	Tyler United States Standard
Very large boulders
4,096-2,048
160-80


Large boulders
2,048-1,024
80-40


Medium boulders
1,024-512
40-20


Small boulders
512-256
20-10


Large cobbles
256-128
10-5


Small cobbles
128-64
5-2.5


Very coarse gravel
64-32
2.5-1.3


Coarse gravel
32-16
1.3-0.6


Medium gravel
16-8
0.6-0.3
2-1/2

Fine gravel
8-4
0.3-0.16
5
5
Very fine gravel
4-2
0.16-0.08
9
10
Very coarse sand
2.000-1.000

16
18
Coarse sand
1.000-0.500

32
35
Medium sand
0.500-0.250

60
60
Fine sand
0.250-0.125

115
120
Very fine sand
0.125-0.062

250
230
Coarse silt
0.062-0.031



Medium silt
0.031-0.016



Fine silt
0.016-0.008



Very fine silt
0.008-0.004



Coarse clay
0.004-0.0020



Medium clay
0.0020-0.0010



Fine clay
0.0010-0.0005



Very fine clay
0.0005-0.00024



Reference: Modified from Vanonl (1975).
101

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TABLE 6-11. RANGE AND MEAN VALUES OF DRY BULK DENSITY FOR VARIOUS GEOLOGIC
MATERIALS
Material
Range (g/cm3)
Mean (g/cm3)
Clay
1.18-1.72
1.49
Silt
1.01-1.79
1.38
Sand, fine
1.13-1.99
1.55
Sand, medium
1.27-1.93
1.69
Sand, coarse
1.42-1.94
1.73
Gravel, fine
1.60-1.99
1.76
Gravel, medium
1.47-2.09
1.85
Gravel, coarse
1.69-2.08
1.93
Loess
1.25-1.62
1.45
Eollan sand
1.33-1.70
1.58
Till, predominantly silt
1.61-1.91
1.78
Till, predominantly sand
1.69-2.12
1.88
Till, predominantly gravel
1.72-2.12
1.91
Glacial drift, predominantly silt
1.11-1.66
1.38
Glacial drift, predominantly sand
1.36-1.83
1.55
Glacial drift, predominantly gravel
1.47-1.78
1.60
Sandstone, fine grained
1.34-2.32
1.76
Sandstone, medium grained
1.50-1.86
1.68
Siltstone
1.35-2.12
1.61
Claystone
1.37-1.60
1.51
Shale
2.20-2.72
2.53
Limestone
1.21-2.69
1.94
Dolomite
1.83-2.20
2.02
Granite, weathered
1.21-1.78
1.50
Gabbro, weathered
1.67-1.77
1.73
Basalt
1.99-2.89
2.53
Schist
1.42-2.69
1.76
Reference: Morris and Johnson (1967); Mills et al. (1985b)
102

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where
Qt
Oy
L
B
V.
the vertical dlspersivlty [m]
the length scale of the facility--!.e., the dimension of the
facility parallel to the flow direction [a] (if L is not known,
an estimate can be obtained from Equation 6.2)
the thickness of the saturated zone [m]
one-dimensional, uniform seepage velocity in the x direction
(n/yr)
percolation rate [m/yr]
In Equation 6.8 the first term represents the thickness of the plume due to vertical
dispersion and the second term represents the thickness of the plume due to the
vertical velocity below the facility resulting from percolation. While implementing
this alternative, the code checks that the computed value of the thickness of the
source, H, is not greater than the thickness of the aquifer, B. If it is, the source
thickness is set equal to the aquifer thickness.
6.5.6 Hydraulic Conductivity trn/vrl
Hydraulic conductivity estimates should be based on site-specific data collection,
such as piezometer tests (bail tests or slug tests) and/or pumping tests. Some
typical hydraulic conductivity values for various materials are shown in Tables 6-1
and 6-2 and discussed in Section 6.3.1. Note that the units of hydraulic conducti-
vity are m/yr in the saturated zone, but cm/hr elsewhere in the code.
An alternative, though often a poor one, la to allow the code to derive a value for
hydraulic conductivity. The'code uses an approximate functional relationship, the
Kozeny-Carman equation (Bear 1979):
In Equation 6.9, the constant 1.8 includes a unit conversion factor. Both the
density of water, p, and the dynamic viscosity of water, p, are functions of
temperature and are computed using regression equations presented In CRC (1981).
Note that at 15*C, the value of [pg/1¦8p) is about 478.
6.5.7 Hydraulic Gradient Im/ml
The hydraulic gradient is the change in water level elevation over a given distance.
In general, it is a function of the local topography, groundwater recharge volume and
location, and the volume and location of groundwater withdrawals. Further, it may
also be related to the porous media properties.
The gradient can often be estimated from water level measurements in the area sur-
rounding the site or from a map of water table or potentiometric surface elevations.
K _ Pg	d2
" it (l^)2 1.8
(6.9)
where
K
P
g
»
d
the hydraulic conductivity [cm/s]
the density of water [kg/msj
acceleration due to gravity [m/s2]
the dynamic viscosity of water [N-s/m2]
mean particle diameter [cm]
103

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The average gradient under natural conditions should be input in the model.
Therefore estimates should not include the effect of pumping. The data used to
estimate the hydraulic gradient can also be used to determine the direction of
groundwater flow.
6.5.8 Groundwater Seepage Velocity fm/vr1
The groundwater velocity is needed to quantify transport by advection. Because
groundwater velocities are difficult to measure directly, they are often determined
indirectly, using the fact that seepage velocity is related to the aquifer properties
through Darcy's Law. Assuming a uniform, saturated porous medium, the seepage
velocity can be expressed as:
V, - KS/tf	(6.10)
where
K - the hydraulic conductivity of the formation [m/yr]
S - the hydraulic gradient [m/m]
MULTIMED allows the user to derive the seepage velocity by means of Equation 6.10
instead of directly entering a value.
Note chat the hydraulic conductivity of the aquifer is used by the code only to
calculate the seepage velocity. Therefore, if the groundwater seepage velocity is
specified by the user, the hydraulic conductivity will not be used.
6.5.9 Retardation Coefficient f--l
The retardation factor is used to determine the retardation, due to adsorption, of a
contaminant relative to the bulk mass of water transporting the contaminant (Freeze
and Cherry, 1979). In addition to delaying the arrival time of a contaminant at a
receptor, retardation together with dispersion can lower the peak concentration. In
MULTIMED, the retardation factor can be input directly or derived by the code using:
R, - 1 + pMB	(6.11)
where
pb - . bulk density [g/cc]
Kd - contaminant distribution coefficient [cc/g]
6 - saturation water content [-•]
Estimation of the bulk density, distribution coefficient, and saturation water
content has been discussed in earlier sections. Note that a value of one for the
retardation coefficient means that the contaminant does not interact with the solid
phase, but acts as a conservative tracer. An example of a conservative tracer is
chloride.
6.5.10 Longitudinal. Transverse and Vertical Dlspersivltles fml
The aquifer longitudinal (aL), transverse (aT), and vertical (ay) dlspersivltles are
used in the model to calculate hydrodynamic dispersion (i.e., the spreading and
mixing caused by mechanical dispersion). The spreading of a contaminant caused by
molecular diffusion is assumed to be small relative to mechanical dispersion and Is
ignored in the model. The estimation of longitudinal dlspersivity In the unsaturated
104

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zone Is discussed In Section 6.4.2. Note that the longitudinal dispersivlty Is
oriented In the vertical direction for the unsaturated zone, while it is oriented In
the horizontal direction for the saturated zone.
The values for dispersivlty are difficult to determine. Research has shown that the
values for these parameters are strongly scale dependent (EPRI, 1985). This can be
seen in Figure 6.2. In general, dispersion is determined by adjusting the disper-
sivlty values until modeling results match historical data (Mercer et al., 1982).
In the absence of user-specified values, the model allows two alternatives for
deriving the aquifer dlsperslvities. Alternative one is based on values presented In
Celhar and Axness (1981). Dlsperslvities are calculated as a fraction of the
distance to the downgradient receptor well, as follows:
oL - 0.1 xt
°i ~ ®l/3 .0
cty - 0.056aL
(6.12)
(6.13)
(6.1<0
where xr is the distance to the receptor well [m]. This option is summarized in
Table 6-12(a).
Alternative two allows a probabilistic formulation for the longitudinal dispersivlty
as shown In Tables 6-12(a) and 6-12(b) [Gelhar (personal communication), 1986) . The
longitudinal dispersivlty is assumed to be uniform within each of the three intervals
shown in Table 6-12(b). Note that these values of longitudinal dispersivlty shown
are based on a receptor well distance of 152.4 m. For other distances, the following
equation is used:
°l(*«> - Pt(xr - 152.4)(xr/152.4)0-5	(6.15)
The transverse and vertical dispersivlty are assumed to have the following values:
<*l - at/8	(6.16)
av ~ <*l/160	(6.17)
The distributional properties for the longitudinal and transverse dlsperslvities are
unknown (Dean et al., 1989).
6.5.11 Aquifer Temperature (°C1
This parameter is site-specific and should be measured at the site. Note that
MULTIMED does not take into account any seasonal variation in temperature in the
uppermost portions of the aquifer. Instead, an average value should be used. The
average temperature of shallow groundwater in the United States is shown in Figure
6.3.
6.5.12 oH foH unitsl
The pH values of groundwater In the United States typically range between 6.0 and
8.5. However, values as high as 11.0 for alkali-spring water and as low as 1.8 for
acid hot-spring water have been determined (Mercer et al., 1982). The pH can be
measured from groundwater samples in the field. For some aquifers, data may be
105

-------
O
9 «UU
0	(MalM
1	•*!>(••
o
m I'inl
• im4
-------
TABLE 6-12(a). ALTERNATIVES FOR INCLUDING DISPERSIVITIES IN THE SATURATED ZONE MODULE
Alternative 1 Alternative 2
Plmrslvjty	Exlatlng VfllMCfl Celhar's Recommendation
Ql tml	0.1 xr	Probabilistic Formulation
(See Table S-3(b))
aT (m)	0.333 ai/8
av [m]	0.056 oL Ol/160
<*i/aT	3 8
aL/av	approx. 18 160
TABLE 6-12(b). PROBABILISTIC REPRESENTATION OF LONGITUDINAL DISPERSIVITY FOR A
DISTANCE OF 152.4 m
Clasa
aL (m) 0.1-1	1-10	10-100
Probability	0.1	0.6	0.3
Cumulative	0.1	0.7	1.0
Probability
available from the U.S. Geological Survey, the U.S. Environmental Protection Agency,
or from state and local agencies.
6.5.13 Organic Carbon Content (Fraction) f--l
The fractional organic carbon content can be estimated from the percent organic
matter by the following relationship:
foe " W17 2.4	(6.18)
where
f00 - fractional organic carbon content [dlmensionless]
fm - percent organic matter [dlmensionless]
172.4 - conversion factor from percent organic matter content to
fractional organic carbon content
107

-------
Information about the percent organic natter In soils Is provided In Section 6.4.3.
Typically the value of the percent organic matter (and hence, the fractional organic
carbon content) Is smaller for an aquifer than for near-surface soils.
6.5.14 Well Distance from Site fml. Angle off Center fdegrees 1. and Well
Vertical Distance fml
A schematic of the receptor well location relative to the waste facility was
presented In Figure 6.1. The location of the well Is determined by specifying the
radial distance to the well, the angle between the plume centerllne and the radial
location of the well measured counterclockwise and the depth of penetration of the
well. The well screen depth Is specified as the fraction (I.e., a value between 0
and 1) of the total aquifer thickness and is measured downward from the water table.
The well is assumed to have a single opening at the depth specified. The code uses
the input to calculate the cartesian coordinates of the well location as discussed in
Section 5.2.3.
For Subtitle D applications pf the model, a conservative approach is required. Thus,
the well is assumed to be located on the contaminant plume centerllne (i.e., the
angle off center is fixed at zero degrees) and the well vertical distance is also
fixed at zero (i.e., the contaminant concentration is predicted at the water table).
108

-------
Figure 6.3 Average temperatures of shallow groundwater in
the continental United States (from Geraghty
et al., 1973).
109

-------
SECTION 7
EZAHPLB PROBLEMS
Three example problems are presented in this section. These problems are designed to
demonstrate the application of KULTIMED to a variety of scenarios which might be
encountered while studying Subtitle D facilities. Example 1 is a deterministic,
steady-state simulation of transport in the saturated zone. The second example is
identical to Example 1, but includes flow and transport in the unsaturated zone.
This example Is included in the deterministic tutorial for the preprocessor, PREMED,
and can be accessed from the opening screen of the preprocessor by typing ^DE-
TER. LOO (do not type the brackets). Example 3 is similar to Example 2, but it Is
run in Monte-Carlo mode. This example Is the same as the input generated by the
Monte Carlo tutorial, which is accessed from the preprocessor opening screen by
typing <@MONTE. LOO.
Because new versions of the MULTIMED code may be released after the publication of
this document, the results presented in this section may differ from the result
obtained from using the Input generated by the tutorials. Therefore, these examples
should not be viewed as validation data sets. Input, and output for model validation
are distributed with the code.
Note that the scenarios represented by these simulations are hypothetical, and are
not intended to resemble any actual sites. The values used In these example problems
are not EPA-recommended values for use in MULTIMED.
7.1 EXAMPLE 1
7.1.1 The Hypothetical Scenario
A well which supplies drinking water to a small community is located 152 meters
directly downgradient from a waste disposal facility. The members of the community
want to predict the effect of the waste disposal facility on the water quality in the
well.
The bottom of the waste disposal facility is located just above the water table.
Therefore, simulation of flow and transport In the unsaturated zone is unnecessary,
and only saturated transport is simulated.
One contaminant has been selected by the community for simulation, based on its
unusual persistence In the subsurface environment. This contaminant is not biode-
gradable , and has an overall chemical decay coefficient which is so small it can be
assumed to be zero (this Is a conservative approach). The normalized distribution
coefficient for the contaminant Is also assumed to be zero, so the chemical will not
be removed from the groundwater by the process of adsorption. For convenience in
calculating the dilution attenuation factor (DAF), discussed in Section 5.2.4, the
concentration of the contaminant at the bottom of the facility is assumed to be 1.00
mg/1. This source concentration is constant in time. The area of the waste disposal
site is approximately 400 m2 and it is square in shape. The infiltration rate Into
the aquifer beneath the facility Is .007 m/yr, and the recharge rate into the aquifer
110

-------
downgradient of the facility is slightly higher at .0076 m/yr. No temporal variabi-
lity in these rates has been observed.
The aquifer is 78.6 meters thick and the hydraulic gradient within the aquifer is
constant at 0.0306. The estimated longitudinal dlspersivlty in the aquifer is 160 n,
the transverse dlspersivlty is 15.2 m and the vertical dlspersivlty Is 8 m. The
fraction of organic carbon in the aquifer Is .00315. The pH of the groundwater in
the aquifer is typical of many groundwaters in the United States and has been
measured to be 6.20. The average annual temperature in the aquifer is 14.4 °C.
The lack of temporal variability in this system indicates that a steady-state
simulation is appropriate. Furthermore, the values of the parameters are known with
a high degree of certainty, so a deterministic simulation was selected.
7.1.2 Input
MULTIMED input for Example 1.1s shown in Table 7-1. It consists of the title for the
Example 1 simulation, followed by several data groups. The values assigned to
specific parameters are clearly labeled for all of the data groups except the General
data group. The parameters in the Ceneral Data Group and the format of the entire
input sequence are discussed in Appendix A. Since only the saturated transport
module is used in this example, the General Data Group is followed by three data
groups: the Chemical, Source and Aquifer Specific Variable Data. In these data
groups, the name of the input parameter and the units for the parameter are in the
left hand column. The values listed under nDistributionn indicate whether the
parameter is to be derived from other parameters (-1 or -2) or read from the input
sequence (0). Since this is a deterministic simulation, only the values listed in
the "Mean" column will be used by the model (the standard deviation, and the minimum
and maximum limits are applicable only in a Honte Carlo simulation).
All of the Chemical Specific Parameters used by MULTIMED are ' isted in the input
file. However, not all of these parameters are used in the Example 1 simulation. A
discussion of which parameters are required by the saturated zone transport module
can be found in Section 5.3. To avoid obtaining values for unnecessary parameters
when developing an input-sequence for MULTIMED, refer to Section 5.3, which discusses
the parameters required for specific modules, and Section 6, which discusses the
estimation and/or derivation of these parameters..
Values for some parameters may be listed as -999. These parameters are undefined.
Files generated by the preprocessor list some of the parameters which are not used by
the code as -999. PREMED will check that all of the necessary values for a particu-
lar simulation have been defined before saving an input file. If a value of -999
appears in the input sequence for a parameter which ia required by the code, this
parameter will be listed as "Undefined", and must be specified to complete the input
sequence for use in MULTIMED. The specification of "Undefined" parameters is clearly
demonstrated in the PREMED tutorials.
Ill

-------
TABLE 7-1. INPUT SEQUENCE FOR EXAMPLE 1
riiii. l.
mwn MTl
**• CHEMICAL UIC FCEMM(BOAl)
DEFAULT CHEMICAL
APPTYP
LAIIDF COMPLETE
0 2 1
"• XST
QO GEBQAL
nrntrrAi SHUIll vaptaw k TUfA
*nn*T VALUES
** ranmir	route irr ircax palpe
-apnoB opiate ed	mcbte i stead iofoi izcek
ioo DExaaansTic i i l l o o o 90.0
CHEMICAL SPECIFIC VARIABLES
VARIABLE MM	OTITS DISTRIBOTIQB	PARAMETERS	LIMITS



KEAH
STD DZV
m
MX
1 Solid pbasa tfaur coafflciant
I/yr
-1
0. OOOE+OO
0.OOOE+OO
0.OOOE+OO
0.100E+11
2 Dlsaolvad jbasa dacay coafflciant
1/yr
-1
0. OOOE+OO
0. OOOE+OO
0.OOOE+OO
0.100E+U
9 Ovarall ilf Iral dtugr CMltlclol
i/y*
-1
0. OOOE+OO
0.OOOE+OO
0. OOOE+OO
0.100E+11
~ Acid ciuljiad brdzolyili rat*
l/M-yx
0
0. OOOE+OO
0.OOOE+OO
0.OOOE+OO
-999.
S luitril hydro ljr»l» rata constant
1/yr
0
0. OOOE+OO
0.OOOE+OO
0.000E+00
-999.
6 Basa catalysad bydrolyai* rata
l/M-yr
0
0. OOOE+OO
0.OOOE+OO
0.OOOE+OO
-999.
7 Rafarwca I1»nliil«
C
0
23.0
0.OOOE+OO
0.OOOE+OO
100.
• Bni—111 ill dlatrlbotien coafflciant
nl/s
0
0. OOOE+OO
0.OOOE+OO
0.OOOE+OO
-999.
9 DKtiUntlia coafflclaot
—
-2
0.219
0.OOOE+OO
0.OOOE+OO
0.100E+11
10 II1 odatrartat.tm maffldant (lit. ro
oa) 1/yr
0
0. OOOE+OO
0.OOOE+OO
0.OOOE+OO
-999.
11 Alz iUfftnlm coafflciant
aft*
0
0. OOOE+OO
0.643E-02
0.OOOE+OO
10.0
12 Itbian tibial aim a for air diffusion C
0
0. OOOE+OO
0.OOOE+OO
0.OOOE+OO
100.
13 Holacalar wl|ht

0
-999.
0.OOOE+OO
0.OOOE+OO
-999.
14 (tola fraction of aoluta
—
0
-999.
0.100E-01
0.100E-08
1.00
15 Solnta vapor prasaoxa
— Hg
0
-999.
0.230E-01
0.000E+00
100.
16 Ibniy'a lav r
-------
TABLE 7-1. INPUT SEQUENCE FOR EXAMPLE 1 (concluded).
SOURCE SPECIFIC VARIABLE
ARRAI VALUES
SOURCE SPECIFIC VARIABLES
VARIABLE MIC
idiits
DISTRIBUTION'
PARAMETERS
LIMITS



MEAH STD OEV
Mil
MAX
1 Infiltration rat*
n/yx
0
0.700E-02 -999.
0.100E-09
0.100E+11
2 Am of «uu 4iip nit
m'Z
0
400. -999.
0.100E-01
-999.
3 Duration of polM
yr
0
-999. -999.
0.100E-06
-999.
4 Spread of ccntaimt arc*
a
-1
-999. -999.
0.100E-08
0.100E+11
5 fiMhart* i«U
n/yr
0
0.760E-02 -999.
0.100E-09
0.100E+11
6 Soarc* diciy caMtot
i/yr
0
0.OOOE+OO -999.
0.OOOE+OO
-999.
7 Inlt codc «t lsndflll
m/i
0
1.00 -999.
0.OOOE+OO
-999.
8 Langfth tcilt of facility
m
-1
-999. -999.
0.100Z-08
0.100E+11
9 Width seal* of facility
a
-1
-999. -999.
0.100E-08
0.100E+11
ED ARRAY
eito sodsce awufu: variable data
aquifer specific variable data
arrax values
AQUIFER SPECIFIC VARIABLES
VARIABLE UM	DIITS DISTHIBUTIC*	PARAMETERS	LIMITS
HEAR STD OEV Hill	MAX
1 Fartlcla dl»Ur
cm
0
Q.630E-03 -999.
0.100E-08
100.
2 Aqolfar porosity

-2
-999. -999.
0.100E-08
0.990
9 Balk density
g/cc
-2
-999. -999.
0.100E-01
3.00
4 Aqalfar thickness
a
0
70.6 -999.
0.100E-08
0.100E+06
3 Mixing una dapih
a
-1
-999. -999.
0.100E-08
0.100E+06
6 Bydraollc cmdoctlvlty
a/yr
-2
-999. -999.
0.100E-06
0.100E+09
7 Hydraulic Gradlant

0
0.306E-01 -999.
0.1001-07
-999.
8 OmAisI ar aaap velocity
a/yr
-2
-999. -999.
0.100E-09
0.100E+09
9 Retardation eoafflclsnt

-1
-999. -999.
1.00
0.100E+09
10 Lomltodlntl dispersivity
¦
0
160. -999.
0.100E-02
0.100E+03
11 Trmvtni dltparslrity
a
0
13.2 -999.
0.100E-02
0.100E+03
12 Vartlcal dlsparalvlty
a
0
8.00 -999.
0.100E-02
0.100E+03
13 Ti^aratura of aquifer
C
0
14.4 -999.
0.OOOE+OO
100.
14

0
6.20 -999.
0.300
14.0
13 Organic carbon contant
tract
0
0.315E-02 -999.
0.100E-03
1.00
16 Racaptor distance fron alta
a
0
132. -999.
1.00
-999.
17 Aagla off enter
dagraa
0
0.OOOE+OO -999.
0.OOOE+OO
360.
16 Hall vart dlst fron watsr tabl

0
0.OOOE+OO -999.
0.OOOE+OO
1.00
ESD ARRAY
ESD AQUIFm SPECIFIC VARIABLE DATA
ERD ALL DATA

-------
7.1.3 Output
The output for example 1 consists the main output file, the SAT.OUT file, and files
with a *.VAR extension, which are not shown. For deterministic simulations, the
*.VAR files echo the values of the constant parameters and list the values calcula-
ted by the code for the derived parameters. Table 7-2 presents the main output
file, which consists of an echo of the input and the predicted contaminant concen-
tration at the well. The SAT.OUT file, shown in Table 7-3, lists the predicted
contaminant concentration at the well.
7.2 EXAMPLE 2
7.2.1	The Hypothetical Scenario
The second example is identical to the first with one exception: the water table is
located at a depth of 6.1 meters below the bottom of the waste disposal facility.
Therefore, unsaturated flow and transport must also be simulated.
In this example, the unsaturated zone consists of one homogeneous layer with the
following known values for material and transport properties. The saturated
hydraulic conductivity is .017 cm/hr, the porosity is 0.43 and the bulk density Is
1.67 g/cm3. The percent organic matter is 0.026 and the Brooks and Corey exponent is
0.5. The van Genuchten parameters, a and fi, which describe the relationship between
the pressure head and water saturation, are .009 and 1.23, respectively. The
residual water content is .088 and the longitudinal dispersivlty is .4 m.
7.2.2	Input
The chemical, source, and aquifer specific parameters are the same as those de-
scribed in Example 1. However, simulation of the unsaturated zone requires addi-
tional data groups in the input file including soil moisture parameters and unsatu-
rated zone transport parameters. The input for Example 2 is shown in Table 7-4.
7.2.3	Output
The output for Example 2 is similar to that described for Example 1. In addition to
the main output file, shown in Table 7-5, the SAT.OUT file, presented in Table 7-6,
and the *.VAR files, tvo additional files, VFLOW.OUT and VTRNSPT.OUT, are created.
VFL0U.0UT contains output for the Unsaturated Zone Flow Module, Including the depth
of each node and the Darcy velocity, water saturation, and head at each node. (Note
that the number and location of nodes is determined by the MULTIMED code.) VTRNSPT-
0UT lists the steady-state concentration at the water table.
114

-------
TABLE 7-2. OUTPUT FILE FOR EXAMPLE 1.
U. S. ENVIRONMENTAL PROTECTION AGENCY
EXPOSURE ASSESSMENT
MULTIMEDIA MODEL
VERSION 3.3, DECEMBER 1988
Developed by Phillip Mlneart and Atul Salhotra of
Voodvard-Clyde Consultants, Oakland, California
In cooperation with:
Hydrogeologic, Inc., Herndon, Virginia,
Ceotrans, Inc., Herndon, Virginia,
and
Aqua Terra Consultants, Mountain View, California
1
Run options
Subtitle D landfill application.
Chealcal simulated is DEFAULT CHEMICAL
Option Chosen	Saturated zone model
Run was	DETERMIN
Infiltration input by user
Run was steady-state
Reject runs if Y coordinate outside plume
Reject runs if Z coordinate outside plume
Gaussian source used in saturated zone model
1
1
(continued)

-------
TABLE 7-2. OUTPUT FILE FOR EXAMPLE 1.
CHEMICAL SPECIFIC VARIABLES
VARIABLE NAME
UNITS
DISTRIBUTION
PARAICTERS
LIMITS



MEAN
STD DEV
M1N
MAX
Solid phase decay coefficient
1/yr
DERIVED
0.0006*00
0.0006*00
0.0006*00
0.1006*11
Dissolved phase decay coefficient
1/vr
DERIVED
0.0006*00
0.0006*00
0.0006*00
0.1006*11
Overall cheatcaI decay coefficient
Vyr
DERIVED
0.0006*00
0.0006*00
0.0006*00
0.1006*11
Acid catalyzed hydrolysis rate
l/N-yr
CONSTANT
0.0006*00
0.0006*00
0.0006*00
-999.
Neutral hydrolysis rate constant
1/yr
CONSTANT
0.0006*00
0.0006*00
0.0006*00
-999.
Base catalyzed hydrolysis rate
l/M-yr
CONSTANT
0.0006*00
0.0006*00
0.0006*00
-999.
Reference temperature
C
CONSTANT
25.0
0.0006*00
0.0006*00
100.
Moraalized distribution coefficient
¦l/g
CONSTANT
0.0006*00
0.0006*00
0.0006*00
-999.
Distribution coefficient
--
DERIVED
0.219
0.0006*00
0.0006*00
0.1006*11
Biodearadit ion coefficient (sat. zone)
' 1/yr
CONSTANT
0.000E«O0
0.0006*00
0.0006*00
-999.
Air diffusion coefficient
ca2/s
CONSTANT
o.oooe+co
0.MSE-02
0.0006*00
10.0
Reference temperature for air diffusion C
CONSTANT
0.0006*00
0.0006*00
0.0006*00
100.
Molecular might
B/*
CONSTANT
-999.
0.0006*00
0.0006*00
-999.
Hole fraction of solute

CONSTANT
-999.
0.1006-01
0.1006-08
1.00
Vapor pressure of solute
¦i Hg
CONSTANT
-999.
0.2306-01
0.0006*00
100.
Henry's law constant
at»-afJ/N
CONSTANT
-999.
0.0006*00
0.1006-09
1.00
RFD value for drinking water
¦g-kg/day
CONSTANT
1.00
0.0006*00
0.0006*00
1.00
ADIF valut for fish cormaptlon
¦g-kg/day
CONSTANT
1.00
0.0006*00
0.0006*00
1.00
CCC for aquatic organisas
¦g-kg/day
CONSTANT
1.00
0.0006*00
0.0006*00
1.00
1
SOURCE SPECIFIC VARIABLES
VARIABLE NAME
UNITS
DISTRIBUTION
PARAICTERS
LIMITS



MEAN
STD DEV
Mil
MAX
Infiltration rate
m/yr
CONSTANT
0.700E-02
-999.
0.1006-09
0.1006*11
Area of waste disposal unit
¦T2
CONSTANT
400.
-999.
0.1006-01
-999.
Diratlon of pulse
V
CONSTANT
-999.
-999.
0.1006-08
-999.
Spread of contaainant source
¦
DERIVED
-999.
-999.
0.1006-08
0.1006*11
Recharge rate
m/vr
CONSTANT
0.760E-02
-999.
0.1006-09
0.1006*11
Source decay constant
1/yr
CONSTANT
0.000E*O0
-999.
0.0006*00
-999.
Initial concentration at landfill
¦8/1
CONSTANT
1.00
-999.
0.0006*00
-999.
Length scale of facility
¦
DERIVED
-999.
-999.
0.1006-08
0.1006*11
Width scale of facility
¦
DERIVED
-999.
-999.
0.100E-08
0.1006*11
Near field dilution

CONSTANT
0.000£*00
0.000E*00
0.0006*00
0.0006*00
(continued)

-------
TABLE 7-2. OUTPUT FILE FOR EXAMPLE 1 (concluded).
AQUIFER SPECIFIC VARIABLES
VARIABLE HAKE	UHITS DISTRIBUTION	PARAMETEBS	LIMITS



KEA>
SID DEV
MM
MAX
Pamela dlanatar
cm
CtJRSTAHT
0.630E-03
-999.
0.100E-08
100.
Aqulf.r porosity
—
DERIVED
-999.
-999.
0.100E-08
0.990
Balk danslty
B/cc
DERIVED
-999.
-999.
0.100E-01
3.00
Aqulf.r tMcknasa
m
CCBSTAHT
78.6
-999.
o.iooE-oa
0.100E+06
Sourca thlckaaaa (alTlm zona daptfc)
B
derived
-999.
-999.
0.100E-08
0.100E+06
Conductivity (hydraulic)
mjjx
OERlViD
-999.
-999.
0.100E-06
0.100E+09
Gradlant (hydraulic)

COHSTAHT
0.306E-01
-999.
0.100E-07
-999.
Groundvatar aaapaga velocity
n/yr
derived
-999.
-999.
0.100E-09
0.100E+09
Ratardatlan coafttclant
—
DERIVED
-999.
-999.
1.00
0.100E+09
Longitudinal, diaparslvity
n
CCBSTAHT
160.
-999.
0.100E-02
0.100E+OS
Tranavaraa dlaparalvlty
a
CCBSTA5T
13.2
-999.
0.100E-02
0.100E+05
Vartlcal dlaparalvlty
B
CCHSTAHT
S.OO
-999.
0.100E-02
0.100E+03
Taftntnn of aqulf.r
C
Q0VS1AHT
1*.*
-999.
O.OOOE+OO
100.
PB
—
COBSTAHT
6.20
-999.
0.300
14.0
Or|mlc cadm contant (fraction)

COMSTACT
0.315E-02
-999.
0.1002-03
1.00
Wall dlataoca (rea alt*
B
OOBSTABT
132.
-999.
1.00
-999.
£214la off cantar
dagraa
OOBSTAHT
o.eooE+oo
-999.
O.OOOE+OO
360.
Hall vartlcal dlatanca
¦
COBSTAHT
O.OOOE+OO
-999.
O.OOOE+OO
1.00
COBCECTRATIO0 AFTER SATURATED ZOWE MODEL 0.5736E-03

-------
TABLE 7-3. SAT.OUT FILE FOR EXAMPLE 1.
1
STEADY STATE SATURATED ZONE TRANSPORT RESULTS
At 0.1000E+04 TEAKS. COKEHTRATIOH IS 0.57J6E-03

-------
TABLE 7-4. INPUTE SEQUENCE FOR EXAMPLE 2.
Test input s«qu«oc« for HOLT IKED.
m 2.
Q1WAI RATA
CHBOCAL IMC FGBM&K80A1)
DEFAULT CSZMCIAL
1SOURCZ	ROUTE	«I	ITCHK	PALPH	APPTtP
*»«OfUOI	OPTAXB KOI	nam	instead	ioidi	izcek	lakdp	complete
2o	o	uuuauiMii l l l	l o	o o	90.0 021
XST
no uimM
nmfTTAL SPECIFIC	n»TA
1BUI »»inw
MwmcAi. araciva; variables
imc	HUTS DisnuBonoa	pa&mctebs	limits
tCA> STD DEV	MH	MAX
1 Solid phase diciy coifflcltnt
1/yr
-1
O.OOOE+OO
O.OOOE+OO
O.OOOE+OO
0.100E+11
2 Dluolvtd phase dec«y cMttlci«t
l/yr
-1
0.000E+00
0.0001+00
O.OOOE+OO
0.100E+I1
3 Ornall rh—Ifil dtcay coefficient
i/rt
-i
O.OOOE+OO
O.OOOE+OO
O.OOOE+OO
0.100E+11
4 Acid cattlytad hydrolysis rcU
l/H-yr
0
O.OOOE+OO
0.0001+00
O.OOOE+OO
-999.
3 Beotral hydrolysis r«U constant
l/yr
0
O.OOOE+OO
O.OOOE+OO
O.OOOE+OO
-999.
6 Bit* cattln*d hydrolysis rtU
l/H-yr
0
O.OOOE+OO
O.OOOE+OO
O.OOOE+OO
-999.
7 Reference tMptratiirt
c
0
23.0
O.OOOE+OO
O.OOOE+OO
100.
0 toraallud distribution coefficient
¦1/8
0
0
1
i
0
O.OOOE+OO
O.OOOE+OO
-999.
9 Distribution coefficient
-•
•2
0.219
O.OOOE+OO
O.OOOE+OO
0.100E+11
10 Biodesradation coefficient (set. zone)
l/yr
0
O.OOOE+OO
O.OOOE+OO
O.OOOE+OO
-999.
11 Air diffusion coefficient
€¦* / s
0
O.OOOE+OO
0.645E-02
O.OOOE+OO
10.0
12 Reference ts^eratoxe for sir diffusioi
B C
0
O.OOOE+OO
O.OOOE+OO
O.OOOE+OO
100.
13 Molecular wi^ht
8/M
0
-999.
O.OOOE+OO
O.OOOE+OO
-999.
14 Mole fraction of solute
—
0
-999.
0.100E-01
o.iooE-oa
1.00
13 Solute vspor pressure
M Bft
0
-999.
0.230E-01
O.OOOE+OO
100.
16 Henry's Ism constant sti
s-*~3/H
0
-999.
O.OOOE+OO
0.100E-09
1.00
17 lot in use

0
1.00
O.OOOE+OO
O.OOOE+OO
1.00
18 Bot in use

0
1.00
O.OOOE+OO
O.OOOE+OO
1.00
19 Bot in use

0
1.00
O.OOOE+OO
O.OOOE+OO
1.00
EHD AKRAT
EKD CHEMICAL SPECIFIC VARIABLE DATA
(cooLlnu*d)

-------
TABLE 7-4. INPUT SEQUENCE FOR EXAMPLE 2.
source specific variable data
arrat values
SOURCE SPECIFIC VARIABLES
VARIABLE IATC
OH ITS
DISTRIBOTIO*
PARMETERS
LOOTS



(CAR STD DEV
Mm
MAE
1 lalilttiUn rata
o/yr
0
0.700X-02 -999.
0.1001-09
0.100E+11
2 Araa of naata dlap unit
d"2
0
*00. -999.
0.100E-01
-999.
3 Duration of polaa
rr
0
-999. -999.
0.100E-08
-999.
4 Spraad of rmf Inanl area
a
-1
-999. -999.
0.1002-08
0.100E+11
3 Badiat|« rata
n/yr
0
0.760E-02 -999.
0.1001-09
0.100E+11
6 Score* d*c«y constant
1/yr
0
. 0.000X400 -999.
0.000E+O0
-999.
7 Inlt canc at landfill
ae/1
0
1.00 -999.
O.OOOE+OO
-999.
8 LaDgth acala of facility
m
-1
-999. -999.
o.iooE-oe
O.lOOEtll
9 Width acala of facility
a
-1
-999. -999.
0.1002-08
0.100E+11
BD ABRAT
DD SOOCZ SHJUIFIC VARIABLE DATA
vn. aasATUKAiEO fuh nuel nuumzRS
OORROL MSAICIQB
oomt mat ratop Dow nruur
7	12	11
ESD UIHIHH MBHSIE83
MATERIAL KMER FCK EACH LATER
6.10	1
CD MATERIAL HUKIDS
SATURATES MATERIAL HIUHIIT1 PARAWTERS
ARRAI VALUES
SATURATED IMTT8TH VARIABLES
AQCIFER SPECIFIC VARIABLES
VARIABLE UK	WITS
1	Sat Igpdrnllc conduct	ca/hr
2	Dnaaturatad son* poroaity
3	Air watrj praasura haad	¦
« Dapth of tfca tmaat sona b
EXD ARRAT
ERD MATERIAL 1
EKD
DISTRIBUTION	PARAWTERS	LIMITS
WAR STD DEV	HXR	MAX
0	0.170E-01	-999 .	0.100E-10	O.IOOE+OJ
0	0.430	-999.	0.100E-08	0.990
0	O.OOOE+OO	-999.	O.OOOE0	-999.
0	6.10	-999.	0.100E-08	-999.

-------
TABLE 7-A. INPUT SEQUENCE FOR EXAMPLE 2.
SOIL K>ISTUHE PARAieTERS
*** FUXCTIOHAL COEmCIDTTS
ACTAT VALUES
FTOCTIOBAL C06FPICI2 VARIABLES
VARIABLE bak
DH1TS
DISTRIBUTIO0
PARAMETERS
MEAH STD DEV
LIMITS
HZH
MAX
1	KnldB«l viut content
2	Brooks and Corey expooent,, D
3	ALFA van Genochtan co«fllci«ot
4	BETA Van fitwuJiUn coefficient
0.6B0E-01 -999.
0.300 -9W.
0.900E-02 -999.
1.23 -999.
0.100E-08
0.000E+00
O.OOOE+OO
1.00
1.00
10.0
1.00
9.00
EXD ARRAY
EXD MATERIAL 1
EXD
EXD USAHBAIZD FLOW
VTP HXSATURATEP TRABSFGKT MODEL
PARAteXESS
¦LAX OHM	1ADD	XS0L	*	BTEL EKSPTS	BIT Ddtff DOHff
1	20	1	1	16	3	104	2	1	1
umm
1.200
EXD OORSfiL PARIII llll I
TRANSPORT PARMCIER
VALUES
UBSAIQRAXB) TRAXSPQB VARIABLES
VARIABLE BAKE
UVITS
DISTRIBUTION
PARAMETERS
LIMITS



MEAB . STD DEV
nib
MAX
1 Thickness of layer
¦
0
6.10 -999.
0.100E-08
-999.
2 Lflo< dispsr of Layer
B
0
0.400 -999.
0.1OOE+0O
0.100+03
3 Percent organic ntt«r
CD
0
0.260E-01 -999.
O.OOOE+06
100.
4 Balk dans of soli layer
ft/cc
0
1.67 -999.
0.100E-01
3.00
3 Biological decay coeff
1/yr
0
0.000E+O0 -999.
0.000E+O0
-999.
EXD ARRAY
EXD LATER 1
EXD UBSATURATZD TRABSPGBT PARAMETERS
EXD TRABSPGBT MODEL
(continued)

-------
TABLE 7-4. INPUT SEQUENCE FOR EXAMPLE 2 (concluded).
MjUUUt SPECIFIC VARIABLE DATA
ABfiAT VALUES
AQUIFER SPECIFIC VARIABLES
VARIABLE SAME
iraiis
DISTHXBUTIOH
PAHAMETZBS
LIMITS



(CAR
STD D2V
KOI
MAX
1 Futlcla di—t«i
cat
0
0.6302-03
-999.
0.1002-08
100.
2 Aqoifu porosity
—
-2
-999.
-999.
0.1002-08
0.990
3 Balk tetslty
ft/cc
-2
-999.
-999.
0.100E-01
5.00
4 Aqai|«r thidoMt
m
0
78.4
-999.
0.100E-08
0.1002+06
5 Sourct tMckima (¦itlng tone dapth)
B
-1
-999.
-999.
0.100E-08
0.1002+06
6 CopdoctlTity n^drnllc)
n/yr
-2
-999.
-999.
0.100E-06
0.1002+09
7 Gradient Oordraolic)

0
0.306E-01
-999.
0.100E-07
-999.
0 Gnwidirtir nipi|» nloclty
m/yr
-2
-999.
-999.
0.100E-09
0.1002+09
9 BtUrdiblcn coitflclnt
—
-1
-999.
-999.
1.00
0.1002+09
10 Lomltadlntl dliptrtlvlty
¦
0
160.
-999.
0.100E-02
0.1002+05
11 Tramrt* dlipirtivlty
¦
0
15.2
-999.
0.100E-02
0.1002+05
12 Vartlul dlaparsivity
n
0
e.oo
-999.
0.100E-02
0.1002+05
13 Teaparatora of aqolfir
c
0
14.4
-999.
0.0002+00
100.
14 |fl
—
0
6.20
-999.
0.300
14.0
15 Organic citon content (fraction)

0
0.31SB-02
-999.
0.1002-05
1.00
16 Baceptor dlitnca fron slta
a
0
152.
-999.
1.00
-999.
17 off centar
dasraa
0
0.0002+00
-999.
0.0002+00
360.
16 Wall vertical dittawa fna watar
m
0
0.0002+00
-999.
O.OOOE+OO
1.00
OD »»»"
dd Auuirat amiiyic variable data
EK> ALL DAXA

-------
TABLE 7-5. MAIN OUTPUT FILE FOR EXAMPLE 2.
U. S. ENVIRONMENTAL PROTECTION AGENCY
EXPOSURE ASSESSMENT
MULTIMEDIA MODEL
VERSION 3.3, DECEMBER 1988
Developed by Phillip Mineart and Atul Salhotra of
Woodward-Clyde Consultants, Oakland, California
In cooperation with:
Hydrogeologic, Inc., Hemdon, Virginia,
Geotrans, Inc., Herndon, Virginia,
and
Aqua Terra Consultants, Mountain View, California
Run options
Subtitle D landfill application.
Chenical simulated is DEFAULT CHEMICAL
Option Chosen	Saturated and unsaturated zone models
Run was	DETERMIN
Infiltration input by user
Run vas steady-state
Reject runs if Y coordinate outside plume
Reject runs if Z coordinate outside plume
Gaussian source used in saturated zone model
1
1
UNSATURATED ZONE FLOW MODEL PARAMETERS
(input parameter description and value)
NP - Total number or nodal points	240
NMAT - Number of different porous materials	1
KPROP - Van Genuchten or Brooks and Corey	2
IMSHGN - Spatial discretization option	1
OPTIONS CHOSEN
Brooks and Corey functional coefficients
User defined coordinate system
1
(continued)

-------
TABLE 7-5. MAIN OUTPUT FILE FOR EXAMPLE 2.
Layar Information
LATEX BO. LATER HUmHESS MATERIAL PRDPQOT
1	6.10	1
DATA FOR MATERIAL 1
vadgse zobe material variables
. VARIABLE bake
UBITS
DISTRIBUTION
. PARAMETERS
HEAR STD DEV
LIMITS
MM
MAX
Saturated l^dmllo conductivity
Unsaturated um porosity
Air entry praaaora baad
Depth of tha unsaturated cooa
ca/hr
OCaSTABT
COBSTABT
COBSTAHT
COBSTABT
0.170E-01 -999.
0.430 -999.
0.000E+00 -999.
6.10 -999.
0.100E-10	0.100E+03
0.100E-08	0.990
O.OOOE+OO	-999.
0.100E-08	-999.
OHSATURATED ZOBE TXABSPCBT MODEL PARAMETERS
¦LAX - Biafcex of dlffersnt layera uaad	1
RSTFS - luAei of tlaa values concentration calc	20
DOMS - lot presently used	1
ISQL - Type of scbsae oaad la unsaturated sane	1
¦ - Stahfaat taras or tn^wr of incraasnts	18
¦TEL - Points In LaSranglsn Interpolation	3
¦GFTS - hsftai of Gauss points	104
¦IT - Convolution integral ¦¦leant!	2
tfiuusu - Type of boundary condition	1
ITSISI - Tiaa values generated or Input	1
ntX - Hsz siaulstlon tiaa —	0.0
tfima - Halshtlns factor —	1.2
0PTI08S CBQSEa
Stablest moarlcal inversion iliorltln
¦oadscsyin* continuous sourca
Cooputer generated times for coaputint coneantratIons
1
(continued)

-------
TABLE 7-5. MAIN OUTPUT FILE FOR EXAMPLE 2.
DATA FOR LAYER 1
VADOSE TRANSPORT VARIABLES
VARIABLE SAME
UHITS
DISTRIBUTE*
PARAMETEHS
LIMITS



KEAH
STD DEV
KIR
MAX
Ihlcknni of Lajtt
o
CO*START
6.ID
-999.
0.100E-08
-999.
Longitudinal dlsparalvlty of 1>;«
D
COHSTAHT
0.400
-999.
O.OOOE+OO
0.100E+03
Faretat organic oattar
—
COHSTAHT
0.260E-01
-999.
O.OOOE+OO
100.
Bulk danslty of soil for layar
B/cc
COHSTAHT
1.67
-999.
0.100E-01
S.OO
Biological dacay coafflclant
1/7*
COHSTAHT
O.OOOE+OO
-999.
O.OOOE+OO
-999.

chdhcal
SPECIFIC VARIARI.PS




VARIABLE HAKE
TOUTS
DISTRIBUTION
PARAMETERS
LIMITS



KEAN
STD DEV
KIR
MAX
Solid ffcama dacay coafflclant
1/yr
DERIVED
O.OOOE+OO
O.OOOE+OO
O.OOOE+OO
0.100E+11
Dlasolvad jtuia dacay coafflclant
l/7r
DERIVED
O.OOOE+OO
O.OOOE+OO
O.OOOE+OO
0.100E+U
Overall dualcal dacay coafflclant
i/yr
DERIVED
O.OOOE+OO
O.OOOE+OO
O.OOOE+OO
0.100E+11
Acid catalysad hydrolysis rata
l/M-yr
COBSTAHT
0.OOOE+OO
0.000E+O0
O.OOOE+OO
-999.
Rautral hydrolysis rata conatant
1/yr
COBSTAHT
O.OOOE+OO
O.OOOE+OO
O.OOOE+OO
-999.
Sua catalysed hydrolysis rata
1/M-y*
COBSTAHT
O.OOOE+OO
O.OOOE+OO
O.OOOE+OO
-999.
Safaranca t«qparatara
C
COBSTAHT
25.0
0.000E+00
O.OOOE+OO
100.
¦owllcad distribution coafflclant
ml/g
CCBSTABT
O.OOOE+OO
O.OOOE+OO
O.OOOE+OO
-999.
Distribution coafflclant
—
DERIVED
0.219
O.OOOE+OO
O.OOOE+OO
0.100E+11
Blodasradatlcn coafflclant (aat. tone!
1/yr
COBSTAHT
O.OOOE+OO
O.OOOE+OO
O.OOOE+OO
-999.
Air diffusion coafflclant
ea2/s
COHSTAHT
O.OOOE+OO
0.645E-02
O.OOOE+OO
10.0
Rafaranca taaparatura for air diffusion C
COBSTAHT
O.OOOE+OO
0.000E+00
O.OOOE+OO
100.
Molacular aalght
«/h
COBSTAHT
-999.
O.OOOE+OO
O.OOOE+OO
-999.
HoIa fraction of aoluta
—
COBSTAHT
-999.
0.100E-01
0.100E-08
1.00
Vapor prasiura of aoluta
a, Hg
COHSTAHT
-999.
0.2J0E-01
O.OOOE+OO
100.
Banry'a last constant
atan»~3/M
OOBSTAHT
-999.
O.OOOE+OO
0.100E-09
1.00
RFD valua for drinking water
ag-kg/day
COBSTAHT
1.00
O.OOOE+OO
O.OOOE+OO
1.00
AD IF valua for flsb consumption
as*kft/day
COKSTAHT
1.00
O.OOOE+OO
O.OOOE+OO
1.00
COC for aquatic organisms
ni-kg/day
CORSTART
1.00
0.000E+00
O.OOOE+OO
1.00
(continued)

-------
TABLE 7-5. MAIN OUTPUT FILE FOR EXAMPLE 2 (concluded).
SOURCE SPECIFIC VARIABLES
VARIABLE IMS	OMITS DISTRIBUTION	PARAMETERS	LIMITS
HEAR STD DEV Hill	MAX
Infiltration rat*
m/yr
CORSTAOT
0.700E-02
-999
0.100E-09
0.100E+U
Arti of wast* disposal unit
m"2
COVSTAHT
400.
-999.
0.100E-01
-999.
Duration of puis*
yr
COBSTABT
-999.
-999.
0.100E-08
-999.
Spread of cnnf Irisnt source
ffl
OERIVED
-999.
-999.
0.100E-06
0.100E+11
Recharge rate
m/yx
COSSTABT
0.760E-02
-999.
0.100E-09
0.100E+11
Source decay constant
l/yr
aVSTAITT
O.OOQE+OO
-999.
O.OOOE+OO
-999.
Initial concentration at landfill
ag/1
CCBSIABT
1.00
-999.
O.OOOE+OO
-999.
Length scale of facility
m
DQIIVQ)
-999.
-999.
o.iooe-os
0.100E+11
Width acale of facility
¦
OERIVED
-999.
-999.
o.iooE-oe
0.100E+11
Hear field dilution

COOSTAVT
O.OOOE+OO
O.OOOE+OO
0.000E+O0
O.OOOE+OO

AQUIFER SPECIFIC VARIABLES




variable hake
UBITS
DISTRIBUTICH
PARAMETERS
LIMITS



MEA0
STD DEV
KB
MAX
Particle dianeter
cm
COOSTAVT
0.630E-03

0.100E-08
100.
Aquifer porosity
--
DERIVED
-999.
-999.
0.100E-08
0.990
Bulk density
g/cc
DERIVED
-999.

0.100E-01
3.00
Aquifer thickness
¦
COBSTABT
78.6
-999.
o.iooE-oe
0.100E+06
Source thickness (airing tone depth)
¦
DERIVED
-999.
-999.
o.ioos-oe
0.100E+06
Conductivity (hydraulic)
n/yr
DERIVED
-999.
-999.
0.100E-06
0.100E+09
Gradient (hydraulic)

catSTAjrr
0.306E-01
-999.
0.100E-07
-999.
Groundwater seepage velocity
a/yr
DERIVED
-999.
-999.
0.100E-09
0.100E+09
Retardation coefficient
—
DERIVED
-999.
-999.
1.00
0.100E+C9
Longitudinal dlspersivlty
¦
CORSTABT
160.
-999.
0.100E-02
0.100E+05
Transverse disperslvity
¦
CORSTAVT
13.2
-999.
0.100E-02
0.100E+05
Vertical disperslvity
B
CCWSTAHT
6.00
-999.
0.100E-02
0.100E+03
Temperature of aquifer
c
CCWSTAHT
14.4
-999.
O.OOOE+OO
100.
PB
—
COISTAFT
6.20
-999.
0.300
14.0
Organic carbon content (fraction)

CONSTANT
0.315E-02
-999.
0.100E-03
1.00
Well distance fron site
a
OWSTAin
152.
-999.
1.00
-999.
Angle off center
degree
CORSTAITT
O.OOOE+OO
-999.
O.OOOE+OO
360.
Well verticel distance
n
COfSTAKT
0.000E+00
-999.
O.OOOE+OO
1.00
COBCEKTRATIOI AFTER SATURATED ZORE MODEL 0.57361-03

-------
TABLE 7-6. SAT.OUT FILE FOR EXAMPLE 2.
l
STEADY STATE SATURATED ZOSE TBAKSFGRT RESULTS
AT 0.1000E+04 TEARS. COHCEVTRATICH IS 0.S736E-03

-------
7.3 EXAMPLE 3
7.3.1	The Hypothetical Scenario
The third example Is similar to Example 2. The difference Is that Example 3 Is
run In Monte-Carlo mode Instead of In a deterministic framework. In this exam-
ple , spatial variability Is observed In the measured values for two parameters,
which introduces uncertainty Into the model. Therefore, It Is necessary to
utilize the Monte Carlo option in MULTIMED.
In Example 3, all but three of the parameter values are constant or derived and
are identical to those In Example 2. The three parameters have some uncertainty
associated with their values. Thus, they are described in terms of probability
density functions which represent the uncertainty in the parameter value. The
theory behind the Monte Carlo analysis technique, and the probability density
distributions included in MULTIMED, are discussed in Section 9 of Salhotra et al.
(1990).
The three uncertain parameters in Example 3 are the unsaturated zone hydraulic
conductivity (cra/hr), the unsaturated zone porosity, and the aquifer pH. In this
example, the probability density distribution is lognormal for the hydraulic
conductivity, normal for the unsaturated zone porosity, and uniform for the aqui-
fer pH. The normal and lognormal distributions both require specification of a
mean, standard deviation, and minimum and maximum limits. The uniform distri-
bution requires only the minimum and maximum limits of values. Values for these
parameters are shown in Table 7-7.
7.3.2	Input
The input sequence for Example 3 is shown in Table 7-8. It is Identical to the
input file for Example 2 except for changes in the General Data Croup related to
running the model in a Monte Carlo framework, and differences in the input for
the three parameters which have been assigned Monte Carlo distributions.
TABLE 7-7. MONTE CARLO DISTRIBUTION VALUES IN EXAMPLE 3
Parameter
Distribution
Mean
Standard	Limits
Deviation Hln.
Saturated hydraulic
conductivity (cm/hr)
for the unsaturated zone Lognormal
.017
.020
.001 .250
Unsaturated zone
porosity
Normal
.330
.100
.200 .450
Aquifer pH
Uniform
NA
NA
5.80 6.90
128

-------
TABLE 7-8. INPUT SEQUENCE FOR EXAMPLE 3.
ExaspL* 3 Input
Subtitl* D application
GEXEBAL DATA
••• CHDdCAL IAME FCB4AT(B0A1>
DEFAULT CHEMICAL
••• TgTHDT
•~•OPTIC* OPTAIH BOS
zoo mrrc
route irr
NORTE ISTEAD
500 1 1 1
ITCHX PALPH
IOPES IZCSK
10 0 90.0
APPTTP
LAHDF COMPLETE
0 2 1
EST
En
CHEMICAL SPECIFIC VARIABLE DATA
tPPAT VALUES
CHEMICAL SPECIFIC VARIABLES
VARIABLE MC
urns
DxsnuBunoa
PAHAtCTEBS
LXKRS

•

KEAI
SID DEV
HIS
na
X Solid phut decay coefficient
1/yr
-l
0.OOOE+OO
0.OOOE+OO
0.OOOE+OO
0.100E+11
2 Dissolved phtit dteajr coefficient
l/yr
-l
0.OOOE+OO
0.OOOE+OO
0.OOOE+OO
0.1O0E+11
3 Onrtll chaadcal decay coefficient
i/yr
-l
0.OOOE+OO
0.000E+O0
0.OOOE+OO
0.100E+11
4 Acid catalyxad bydrolyiia rtlt
1/H-yr
0
0.OOOE+OO
0.OOOE+OO
0.OOOE+OO
-999.
3 Heotral hydrolysis rate constant
l/yr
0
0.OOOE+OO
0.000E+O0
0.OOOE+OO
-999.
6 But ctUlyt^ hydrolysis rats
1/H-yr
0
0.OOOE+OO
0.OOOE+OO
0.OOOE+OO
-999.
7 Reference taaparatora
C
0
23.0
0.OOOE+OO
0.OOOE+OO
100.
6 Itonealited distribatlon coefficient
nl/ft
-2
140
0.OOOE+OO
O.OCOE+OO
-999.
9 Distribution coefficient
--
0
0.219
0.OOOE+OO
0.OOOE+OO
0.100E+11
10 Biodetredation coefficient (sst. sons) 1/yr
0
0.OOOE+OO
0.OOOE+OO
0.OOOE+OO
-999.
11 Air diffusion coefficient
caZ/s
0
0.OOOE+OO
0.64SE-02
0.OOOE+OO
10.0
12 Reference Uep«rttur« for sir diffusion C
0
0.OOOE+OO
0.OOOE+OO
0.OOOE+OO
100.
13 HoltcuUr might
ft/H
0
-999.
0.OOOE+OO
0.OOOE+OO
-999.
14 Hols traction of aolute

0
-999.
0.100E-01
0.100E-08
1.00
15 Vapor pressure of solute
(OB Hg
0
-999.
0.230E-01
0.OOOE+OO
100.
16 Henry's Ism constant
aUtt-m"3/M
0
-999.
0.OOOE+OO
0 -10QE-09
1.00
17 RFD value for drinking water
mg-kg/day
0
1.00
0.000E+00
0. OOOE+OO
1.00
18 AD I? value for fish consiasption
Bg-kg/d«y
0
1.00
0.OOOE+OO
0. OOOE+OO
1.00
19 CCC for aquatic organism*
og-kg/dsy
0
1.00
0. OOOE+OO
0.OOOE+OO
1.00
EHD ARRAY
END CHEMICAL SPECIFIC VARIABLE DATA	(cootlnuMi)

-------
ABLE 7-8. INPUT SEQUENCE FOR EXAMPLE 3.
OURCE SPECIFIC VARIABLE DAIA
BRAY VALUES
SOURCE SPECIFIC VARIABLES

VARIABLE HAME
UHITS
DISTRIBUTION
PARAMETERS
LIMITS




MEAH STD DEV
Mil
MAX
1
Infiltration rat*
ta/yr
0
0.700E-02 -999.
0.100E-09
0.100E+11
2
Atm of vast* disposal unit
aTZ
0
400. -999.
0.100E-01
-999.
3
Duration of pulse
yr
0
-999. -999.
0.100E-09
-999.
4
Spread of contaninant source
a
. -1
-999. -999.
0.100E-08
0.100E+11
5
Radtttt* rate
«/yr
0
0.760E-02 -999.
0.100E-09
0.100E+11
6
Source decay constant
1/yr
0
0.000E+O0 -999.
0.000E+O0
-999.
7
Initial concentration at landfill
os/L
0
1.00 -999.
0.000E+O0
-999.
8
Length scale of facility
m
-1
-999. -999.
o.iooE-oe
0.100E+U
9
Width scale of facility
m
-1
-999. -999.
o.iooE-oe
0.100E+11
EK> ARRAY
CRD SOURCE SPECIFIC VARIABLE DAIA
U)
O
VFL USSATURATED FLOU MODEL PARAMETERS
UMIifllt PARAWTERS
*** DOM MAT	KROP DDKff HVFLAY
7	1J11
EHD OGRROL PARAMETERS
SATURATED MATERIAL PROWOT PARAMETERS
ARRAY VALUES
SATURATED MATERIAL VARIABLES
VARIABLE HAKE
UNITS
DISTRIBUTION
PARAMETERS
MEAH STD DEV
LIMITS
MIR
MAX
SaturaUd hydraulic conductivity
Unsaturated son* porosity
Air entry praasura haad
Depth of tha unsaturated toot
cm/hr
EHD ARRAY
0.170E-01 -999.
0.330 -999.
O.OOOE+OO -999.
6.10 -999.
0.100E-03	0.230
0.200	0.430
O.OOOE+OO	-999.
0.100E-08	-999.
EHD MATERIAL 1
EHD
(continued)

-------
TABLE 7-8. INPUT SEQUENCE FOR EXAMPLE 3.
son. MOISTURE PARAMETERS
*" FUBCTIORAL COEFFICIErrS
ARRAY VALUES
FU1ICTIOHAL COEFFICIE VARIABLES
VARIABLE RAKE
CHITS
DISTRIBUTION
PARAMETERS
KEA> STD DEV
LIMITS
MM
MAX
EBD ARRAY
¦ 1 tnldul oUr coolant
2	Broaka and Coray exponent. EH
3	ALFA na CamliUa coefficient
4	BETA V«i Ganochtan coefficient,
0.880E-01 -999.
O.SOO -999.
0.900E-02 -999.
1.23 -999.
0.100E-08
O.OOOE+OO
0.000E+00
1.00
1.00
10.0
1.00
3.00
ED hahhial 1
EBD
ED UBSATURATED FL0H
VTF DHSATUSAIZD TRABSFGKT MODS.
OCBTBCL PARMCnSS
*** KLAY 00HS IADO ISO.	¦ HTEL RGPIS	BIT DOMff DOMI
120	1	118	3	10*	2	11
•" witob
1.200
EBD OOVTBQL PARAKETBB
TEAKS PCRT PARAMETER
»im»T VALUES
OBSATURATED TRABSFCR VARIABLES
VARIABLE HAKE
CHITS
DISTRIBUTION
PARAMETERS
KEAM STD DEV
LIMITS
KM MAX
1 Thickness of layer
a
0
6.10 -999.
0.1Q0E-C8
-999.
2 LaoglL diaper of Layer
¦
0
0.400 -999.
0.100E+00
0.100+05
3 Percent organic ntur
B
0
0.260E-01 -999.
0.OOOE+OO
100.
4 Bulk dens of soil layer
S/cc
0
1.67 -999.
0.100E-01
5.00
5 Biological docay coeff
i/yr
0
0.Q00E+O0 -999.
O.OOOE+OO
-999.
EBD ARRAY
EBD LAYER 1
EBD UNSATURATED TRABSFORT PARAMETERS
EBD TRABSFORT MODEL
(continued)

-------
TABLE 7-8. INPUT SEQUENCE FOR EXAMPLE 3 (concluded).
AQUIFER SPECIFIC VARIABLE DATA
VALUES
AQUIFER SPECIFIC VARIABLES

VARIABLE NAME
UHITS
DISTRIBUTION
PARAMETERS
HEAR STD DEV
LIMITS
KIR MAX
1
Ptriicl* dlmUr
CB
0
0.630E-03
*999
0.100E-08
100.
2
Aqalfw porosity
—
-2
-999.
-999.
0.100E-08
0.990
3
Balk (Unilty
«/ec
-2
-999.
-999,
0.100E-01
5.00
4
Aqai far thlckMM
¦
0
78.6
-999.
0.100E-08
0.100E+06
S
Soviet tblckit—¦ (nizlnft son* depth)
a
-1
-999.

0.100E-08
0.100E+06
6
Conductivity (hydraulic)
m/yz
-2
-999.
-999.
0.100E-06
0.100E+09
7
Gradient (hydraulic)

0
0.306E-01
-999.
0.100E-07
-999.
8
GrowknUr a»«p«gt velocity
¦/yr
-2
-999.
-999.
0.100E-09
0.100E+09
9
Ratardatian eotf£lcl«it
—
-1
-999.
-999.
1.00
0.100E+09
10
Longitudinal diaparaivity
a
1
160.
-999.
50.0
200
11
Tr«tv«r«« dlaparsivity
a
0
15.2
-999.
0 100E-02
0.100E+03
12
Vtrtictl diaparaivity
a
0
8.00
-999.
0.100E-02
0.100E+03
13
of aquifar
C
0
14.4
-999.
O.OOOE+OO
100.
14
pfl
—
4
-999.
-999.
5.60
6.90
IS
Organic carbon contaat (fraction)

0
0.315E-02
-999.
0.100E-05
1.00
16
fcacaptor distanca froa aita
a
0
152.
-999.
1.00
-999.
17
Ant la off cantar
dagraa
0
0.oooz+oo
-999.
O.OOOE-H)0
360.
16
Hall irart diat fron watar tabl
a
0
O.OOOE+OO
-999.
O.OOOE+OO
1.00
EBD A8KAI
OB> AQOma SPECIFIC VARIABLE DATA
no ALL DATA

-------
The type of distribution associated with each parameter is indicated in the
"Distribution" column. The number assigned to each of the distribution types is
shown in Table A-*». A value of 0 in the "Distribution" column indicates a
constant value for the parameter. A value of -1 or -2 indicates that the
parameter is derived from other parameters in the code. As Table A-4 Indicates,
other values are used for Monte Carlo distributions. For example, the saturated
hydraulic conductivity for Material 1 in the unsaturated zone has a value of 2 In
the "Distribution" column, which indicates that a lognormal probability density
distribution has been assigned to the parameter.
7.3.3 Output
The output from MULTIMED is presented in Tables 7-9 through 7-11. Because the
General Data Croup flag for the level of output from Monte Carlo runs was sec to
SOME for this example problem (see Section 5.3.2.2), the output consists of the
main output file, the STATS.OUT file, and the SAT1.0UT file. The main output
file consists of an echo of the input parameters, selected statistical results,
and printer plots of frequency and cumulative frequency. The STATS.OUT file
contains a summary of the statistical analyses resulting from the Monte Carlo
simulations. The cumulative distribution function of well concentrations (i.e.,
well concentrations in ascending order) is listed in the SAT1.0UT file. This
file can be used by the postprocessor, POSTMED, to produce frequency and cumula-
tive frequency plots of higher quality than those found in the main output file.
Examples of these plots are shown in Section 4.2.
133

-------
TABLE 7-9. MAIN OUTPUT FILE FOR EXAMPLE 3.
U. S. ENVIRONMENTAL PROTECTION AGENCY
EXPOSURE ASSESSMENT
MULTIMEDIA MODEL
VERSION 3.3, DECEMBER 1988
Developed by Phillip Mineart and Atul Salhotra of
Woodward-Clyde Consultants, Oakland, California
In cooperation with:
Hydrogeologic, Inc., Herndon, Virginia,
Geotrans, Inc., Herndon, Virginia,
and
Aqua Terra Consultants, Mountain View, California
1
Run options
Example 3 input
Subtitle D application
Chemical simulated is DEFAULT CHEMICAL
Option Chosen	Saturated and unsaturated zone no dels
Run was	MONTE
Infiltration input by user
Number of monte carlo simulations	500
Run was steady-state
Reject runs if Y coordinate outside plume
Reject runs if Z coordinate outside plume
Gaussian source used in saturated zone model
1
1
UNSATURATED ZONE FLOW MODEL PARAMETERS
(input parameter description and value)
NP - Total number of nodal points	240
NMAT - Number of different porous materials	1
KPROP - Van Genuchten or Brooks and Corey	1
IMSHGN - Spatial discretization option	1
1	(cont

-------
TABLE 7-9. MAIN OUTPUT FILE FOR EXAMPLE 3.
OPTIOBS CHJbUI
Van GwochUp toaetlcnil co«tflcl«nta
Our doflaod coordinate «yitM
Laytr lufnr—tlm
uns m. uam inii.mta material nonxn
1	0.00	1
DATA FOE MATERIAL 1
VADOSE ZDHE MATERIAL VARIABLES
VARIABLE
OBITS
DISTRIBUTION
SttcrtUd hydraulic conductivity
OnMtnraUd toot porosity
Air antry prttsar* btad
Dayth of tba UMtoraUd son*
an/hr
LOG KSMAL
B06MAL
COBSTAWT
COBSTAVT
FARMCTERS
SID DEV
LIMITS
Mil
MAX
0.170Z-01 0.200E-01
0.530 0.100
O.OOOE+OO -999.
6.10 -999.
0.100E-03
0.200
O.OOOE+OO
o.iooE-oe
0.230
0.430
-999.
-999.
DAZA FOB MATERIAL 1
VADOSE SOU FOTCTIOB VARIABLES
VARIABLE RAKE
UHITS
DISTRIBUTION
FARAMETESS
STD DEV
LIMITS
HOI
MAX
Raaidnal water content
Brook nd Cozmj aspanast,EH
ALFA coefficient
Van Gamichtan expoeieot, EHV
1/ca
O0RSTA1VT
C0HSTAHT
cohst/jtt
CONSTANT
0.600E-01 -999.
0.300 -999.
0.900E-02 -999.
1.23 -999.
0.100E-06	1.00
O.OOOE+OO	10.0
O.OOOE+OO	1.00
1.00	3.00
(continued)

-------
TABLE 7-9. MAIM OUTPUT FILE FOR EXAMPLE 3.
tBSATORATED XOKZ 1M5FCKT HQOZL PARAWHBS
Ril - Biabtr odt diCf«r«t Uytri os«d	I
¦ISIK - l^tr of Um v«lMt ecBe«BtrttloB (tie	20
DKHCI • lot prtsMily aMd	1
JSOL - Trpm of udbmm oil! in azuataritad sons	1
¦ - SUUHt tana or nafcu of lner—nta	18
ITU - hlBU la Lagrangian lBtazpolaU.au	3
EPI3 - >»lm of Gaama pointa	104
BR - Cocnmlnt lrr lntagral itsantl	2
HIIW - Typa of txuduy condition	1
1UUI - Tiaa valuta ganaratad or input	1
KB - Ite um	0.0
farm - factor	1.2

Stahfaat maxlcal invaraien aljorltha
¦ondacagrlns eontiaoooa mica
Goapntar faratad U'^a for rnayrit. i ng concantraticos
1
DATA FOB LATZB 1
VA0CGZ TSARS FCKT VARIABLES
VARIABLE
rams
DISTHIKHI0B
PABAKETEBS
HEAD STB DEV
LIMITS
HOI
MAX
Tt>l¦*¦¦¦¦ of Layar
Longitudinal diaparaivity of Layar
Parcant organic aattar
Bulk taaity of Mil for liyn
Biological dacay coafficiant
g/cc
1/7*
COBSTAKT
CQBSTAJTT
CGKSTAHT
CCBSTAHT
C0HSTAHT
6.10 -999.
0.«00 -999.
0.260E-01 -999.
1.43 -999.
0.OOOE+OO -999.
0.100E-08	-999.
Q.OOOE'HJO	0.100E-W5
O.OOOE+OO	100.
0.100E-01	S.00
O.OOOE+OO	-999.
(contlnaad)

-------
TABLE 7-9. MAIN OUTPUT FILE FOR EXAMPLE 3.
CHEMICAL SPECIFIC VARIABLES
BAIS	OTITS	DISTRIBUTION	PAEWCTEES	LOOTS



HEAK
STD DEV
Mil
MAX

Solid pbaaa dacay coefficient
l/yr
DERIVED
O.OOOE+OO
O.OOOE+OO
O.OOOE+OO
0.100E+11
Dlasolvad it>n dacmy mffidat
i/y*
DERIVED
0.OOOE+OO
O.OOOE+OO
O.OOOE+OO
0.100E+11
Orsrmll rlwl t «1 dacay coi
ifflclaot
l/yr
DERIVED
O.OOOE+OO
O.OOOE+OO
O.OOOE+OO
0.100E+11
Acid uUljnt t&drolyala rata
1/H-yr
OOBSTATT
O.OOOE+OO
O.OOOE+OO
O.OOOE+OO
-999.
¦antral tiydrolyals rata cc
nataat
l/yr
CCBSTAHT
O.OOOE+OO
O.OOOE+OO
O.OOOE+OO
-999.
Baaa catalyxad hydrolysis rata
1/H-yr
CCKSTAirr
O.OOOE+OO
O.OOOE+OO
O.OOOE+O0
-999.
Kifiram ta^aratora

C
CCRSTACT
23.0
O.OOOE+OO
O.OOOE+OO
100.
Ini—lmfl distribution c«
¦officiant

COKSIART
140.
O.OOOE+OO
O.OOOE+OO
-999.
BtitritnUm coafflclaot

—
DERIVED
0.219
O.OOOE+OO
O.OOOE+OO
0.100E+11
Tllnrtagiartal lm coafflclan]
1 (aat. sana)
fyr
COVSTAVT
O.OOOE+OO '
O.OOOE+OO
O.OOOE+OO
-999.
Alx dlffoslcB coafflclaot

cm2J%
COBSTACT
O.OOOE+OO
0.64SE-O2
O.OOOE+OO
10.0
Btftfam ta^aratora for

c
COBSTAVT
O.OOOE+OO
O.OOOE+OO
O.OOOE+OO
100.
Hslacalar aal|1il

«/H
OGBSTAVT
-999.
O.OOOE+OO
O.OOOE+OO
-999.
Hola fractko of aolmta

—
CCBSTAHT
-999.
0.100E-01
O.IOOE-OS
1.00
Vapor luamauia of aolnta

— e»
CCBSTAVT
-999.
0.230E-01
O.OOOE+OO
100.
Haoiy'a lav mnatant.

ata-a~3/M
COST ART
-999.
O.OOOE+OO
0.100E-09
1.00
BFD valna for drlaklog «a1
tar
¦B-ks/day
COBSTABT
1.00
O.OOOE+OO
O.OOOE+OO
1.00
ADU nlaa for flab const*
Vtloo
ag-kg/day
C08STAITT
1.00
O.OOOE+OO
O.OOOE+OO
1.00
CCC for agnatic nfgant—a

¦S-kc/day
coBSTAjrr
1.00
O.OOOE+OO
O.OOOE+OO
1.00
1
SOPBTF SPECIFIC VARIABLES
rarTAiajt mm
ovxts
DISTRIBUTION
PARMCTISS
UNITS



KEAH STD DEV
KOI
MAX
Tnftitration rat*
¦/T*
COBSTAJri
0.700E-02 -999.
0.100E-09
0.100E+11
Aim of vast* disposal unit
wTZ
COBSIAVT
400. -999.
0.100E-01
-999.
Duration of piltt
yr
COBSTAHT
-999. -999.
o.ioos-oe
-999.
Spread of caotalDnt soorct
¦
DEH1VLD
-999. -999.
0.100E-06
0.100E+-11
Kachart* rat*
¦/T*
coKSTAirr
0.160E-01 -999.
0.100E-09
0.100E+11
Soarca dac ay constant
l/yx
COBSTAKT
O.OOOE+OO -999.
O.OOOE+OO
-999.
Initial ecocantration at landfill
¦ft/i
OOBSTAHT
1.00 -999.
O.OOOE+OO
-999.
Lansth icali of facility
¦
DERIVED
-999. -999.
0.100E-06
0.100E+-11
Width acala of facility
¦
DERIVED
-999. -999.
0.100E-0S
0.100E+11
laar fiald dilation

CONSTANT
O.OOOE+OO O.OOOE+OO
O.OOOE+OO
O.OOOE+OO
(continued)

-------
tBLE 7-9. MAIN OUTPUT FILE FOR EXAMPLE 3.
AQUIFER SPECIFIC VARIABLES
VARIABLE WC	OTITS	DISTRIBUTIM	PAUtCRSS	LIMITS
MEAS SID DEV HO!	HAX
FvtlcU di—tir
ca
COBSTAR
0.630E-03 -999.
0.100E-08
100.
AqnlCiX panflty
—
DERIVED
-999. -999.
0.100E-08
0.990
Balk danslty
B/cc
DERIVED
-999. -999.
0.100E-01
3.00
Aqalfcr thlckMM
m
C0*SIAVT
78.6 -999.
0.100E-08
0.100E+06
Souiu thickam (¦lying sod* dtpfch)
m
DERIVED
-999. -999.
0.100E-08
0.100E+06
CoDdactiv&ty (hydraulic)
¦/yr
DERIVED
-999. -999.
0.100E-06
0.1Q0E+O9
Gradiant O^dmllc)

COSSTAR
0.306E-01 -999.
0.100E-07
-999.
Gnatetn oooposa valocity
m/yx
DERIVED
-999. -999.
0.100E-09
0.100E+09
Bttintotlm cottflclot
—
DERIVED
-999. -999.
1.00
0.100E+09
difptnlvlty
m
UBUL
160. 15.0
30.0
200.
TnemrM ditptttlvlty
m
OOBSIAR
13.2 -999.
0.100E-02
0.100E+03
Vertical dltpartlTlty
¦
C0KS1AR
8.00 -999.
0.100E-02
0.100E+03
Toptrttarf of aqulfar
C
ccbstabt
14.4 -999.
O.OOOE+OO
100.
PB
—
wimw
-999. -999.
3,80
6.90
Organic rtrton content (Crutloo)

CORAH
0.313E-02 -999.
0.100E-03
1.00
Hall diiUnct troi alto
¦
COBSIAVT
132. -999.
1.00
-999.
ta|l> ott cantor
dograa
COVSIAK
O.OOOE+OO -999.
O.OOOE+OO
360.
Hall varticol dlatanco
¦
CGBSIABT
O.OOOE+OO *999.
O.OOOE+OO
1.00
1 0 Ttlaa |«n«ciUd Wilcb rrr«»it»J Um apaclftsd bound*.
1		 RESULTS	
SATURATED son nuursrcBT
3 Input
Sditltla D application
90. mean cnmumj ibtesval
B	- 300
KEAB
0.373E-03


STANDARD DEVIATIGB
0.346E-04


COEFFICIENT Of VARIATION
0.604E-01


KIVIKJH VALUE
0.473E-03


MAXIMUM VALUE
0.637E-03


30th PERCENTILE
0.373E-03
0.370E-03
0.576E-03
80th PBtCBTTILE
0.602E-03
0.399E-03
0.603E-03
83th FOtCEHTILE
0.608E-03
0.603E-03
0.614E-03
90th PERCEirTILE
0.619E-03
0.614E-03
0.623E-03
95th PERCEHTILE
0.63AE-03
0.626E-03
0.640E-03
(coBlimttd)

-------
TABLE 7-9. MAIN OUTPUT FILE FOR EXAMPLE 3.
-999 UNABLE TO COMPUTE CONFIDENCE BOUND DUE TO INSUFFICIENT DATA
VALUE
2 OF TIME EQUALLED
OR EXCEEDED
X OF TIME IN INTERVAL
0.100E-03
100.000
0.000
0.156E-03
100.000
0.000
0.211E-03
100.000
0.000
0.267E-03
100.000
0.000
0.323E-03
100.000
0.000
0.378E-03
100.000
0.000
0.A3AE-03
100.000
0.800
0.490E-03
99.200
21.400
0.546E-03
77.800
56.800
0.601E-03
21.000
20.800
0.657E-03
0.200

1
(continued)

-------
TABLE 7-9. MAIN OUTPUT FILE FOR EXAMPLE 3.
IOO +	+-
-+
t

80
+•
F

;
R

i
E

!
Q
60
+•
u

!
E

i
N

I
C
40
+
Y

i


!
Z

I

20
+


!


!


!

0
+









!
!









!
!
!









!
!
!









!
!
!




» !
1 1
1 1




!
1
!
0.100 0.156 0.211 0.267 0.323 0.378 0.434 0.490 0.546 0.601 0.657
* 0.1E-02
CONCENTRATION
(continued)

-------
TABLE 7-9. MAIN OUTPUT FILE FOR EXAMPLE 3.
1
C 100 +-	+	+	+	+	+		+	+-	+	**
U !	*** !
M !	* !
U !	* !
L 80 +	+	+	+	+	+	+	+	+-	*	+
A !	!
T !	*	!
I !	*	!
V	60 +	+	+	+-	+	+	+	+	+	+	+
E !	*	!
! !
F !	*	!
R 40 +	+	+	+	+	+-	+	-+	+-*	+	+
E !	I
Q !	*	!
U •	!
E 20 +	+	+	+	+	-+	+	-+	*	+	+
M !	*	!
C !	*	!
Y	! ** |
0 	+	+	+
0.100 0.156 0.211 0.267 0.323 0.378 0.434 0.490 0.546 0.601 0.657
* 0.1E-02
CONCENTRATION
(continued)

-------
TABLE 7-9. MAIN OUTPUT FILE FOR EXAMPLE 3.
FOLLOWING GRAPHS ABE FOR THE TOP 20Z OF THERESULTS
100
80
F
&
B
Q 60
U
B
H
C 40
20 +
.+—*-.+
t
-+	+-
-+	-+	+	-+	+-	+-
.+	+-	+	+	-+	+	+	+-	+-
-+	+	+-
-+	+-
-+	+	+	+	+-
0 •<	*	V	*--+	*- - +	*- -H	*- H		*-- +	*- - +	*--+	*-- +
0.100 0.156 0.211 0.267 0.323 0.378 0.434 0.490 0.546 0.601 0.657
* 0.1E-02
CONCENTRATION
(continued)

-------
TABLE 7-9. MAIN OUTPUT FILE FOR EXAMPLE 3 (concluded).
c
100
+-
u


M

•
u

!
L
80
+-
A

!
T

!
I

i
V
60
+-
E

!


!
F

!
R
40
+-
E

!
Q

!
D

!
E
20
+-
N

!
C

!
Y

!

n

.+	+	+	+	+	+	*
*

	+
0.100 0.156 0.211 0.267 0.323 0.378 0.434 0.490 0.546 0.601 0.657
* 0.1E-02
CONCENTRATION

-------
TABLE 7-10. FIRST PAGE OF THE SAT1.0UT FILE FOR EXAMPLE 3.
0.47457E-03
0.47974E-03
0.48608E-03
0.48800E-03
0.49012E-03
0.49224E-03
0.49897E-03
0.49929E-03
0.49976E-03
0.50186E-03
0.50328E-03
0.50413E-03
0.50599E-03
0.50715E-03
0.50830E-03
0.50845E-03
0.50892E-03
0.50896E-03
0.S0899E-03
0.50927E-03
0.50953E-03
0.S1086E-03
0.51110E-03
0.51265E-03
0.51344E-03
0.51375E-03
0.51534E-03
0.51589E-03
0.51801E-03
0.51807E-03
0.51846E-03
0.52211E-03
0.52246E-03
0.52261E-03
0.52275E-03
0.52347E-03
0.52361E-03
0.52425E-03
0.52430E-03
0.52450E-03
0.52490E-03
0.52494E-03
0.52552E-03
0.52583E-03
0.52599E-03
0.52603E-03
0.52615E-03
0.52751E-03

-------
TABLE 7-11. STATS.OUT FILE FOR EXAMPLE 3.
Exanple 3 input
Subtitle D application
INTERVAL
	 RESULTS 	
SATURATED ZONE TRANSPORT
H	500
MEAN	-	0.573E-03
STANDARD DEVIATION	-	0.346E-04
COEFFICIENT OF VARIATION -	0.604E-01
MINIMUM VALUE	-	0.475E-03
MAXIMUM VALUE	-	0.657E-03
50 th PERCENTILE	-	0.573E-03
80th PERCENTILE	-	0.602E-03
85th PERCENTILE	-	0.608E-03
90th PERCENTILE	-	0.619E-03
95th PERCENTILE	-	0.634E-03
90. PERCENT CONFIDENCE
0.570E-03
0.599E-03
0.605E-03
0.614E-03
0.626E-03
0.576E-03
0.605E-03
0.614E-03
0.623E-03
0.640E-03
-999 UNABLE TO COMPUTE CONFIDENCE BOUND DUE TO INSUFFICIENT DATA
VALUE
Z OF TIME E
OR EXCE
QUALLED
ED ED
* OF TIME IN INTERVAL
0.100E-03
100.000

0.000
0.156E-03
100.000

0.000
0.211E-03
100.000

0.000
0.267E-03
100.000

0.000
0.323E-03
100.000

0.000
0.378E-03
100.000

0.000
0.434E-03
100.000

0.800
0.490E-03
99.200

21.400
0.546E-03
77.800

56.800
0.601E-03
21.000

20.800
0.657E-03
0.200



-------
SECTION 8
REFERENCES
Bear, J. 1979. Hydraulics of Groundwater. McGraw Hill, New York, New York.
569 p.
Bond, F., and S. Hwang. 1988. Selection Criteria for Mathematical Models
Used in Exposure Assessments: Groundwater Models. EPA/600/8-88/075, U.S.
Environmental Protection Agency, Washington, DC.
Boutwell, S.H., S.M. Brown, B.R. Roberts, and D.F. Atwood. 1985. Modeling
Remedial Actions at Uncontrolled Hazardous Vaste Sites. EPA/540/2-85/001,
U.S. Environmental Protection Agency, Washington, DC.
Brooks, R.H. and A.T. Corey. 1966. Properties of Porous Media Affecting
Fluid Flow. ASCE J. Irrlg. Drain Div. 92 (IR2):61-68.
Carsel, R.F., C.N. Smith, L.A. Mulkey, J.D. Dean, and P. Jowise. '1984.
User's manual for the Pesticide Root Zone Model (PRZM): Release 1. EPA-
600/3-84-109, U.S. Environmental Protection Agency, Athens, Georgia.
Carsel, R.F. and R.S. Parrish. 1988. Developing Joint Probability Distribu-
tions of Soil-Water Retention Characteristics. Water Resour. Res. 24(5):
755-769.
Carsel, R.F., R.S. Parrish, R.L. Jones, J.L. Hansen, and R.L. Lamb. 1988.
Characterizing the Uncertainty of Pesticide Leaching in Agricultural
Soils. Journal of Contam. Hydrol. 25:111-124.
Dean, J.D., P.S. Huyakorn, A.S. Donigian, Jr., K.A. Voos, R.W. Schanz, and
R.F. Carsel. 1989. Risk of Unsaturated/Saturated Transport and Transfor-
mation of Chemical Concentrations (RUSTIC). Volume II: User's Guide.
EPA/600/3-89-048b. U.S. Environmental Protection Agency, Athens, Georgia.
Donigian, A.S., and P.S.C. Rao. 1988. Selection, Application, and "Nidation
of Environmental Models.	Proceedings of the International Symposium
on Water Quality Modeling of Agricultural Non-Point Sources, D.G.
DeCoursey (ed.). ARS-81, U.S. Department of Agriculture, Washington, DC.
E.C. Jordan Co. 1985. Analysis of Engineered Controls of Subtitle C Facili-
ties for Land Disposal Restrictions Determinations. Prepared for Office of
Solid Waste, U.S. Environmental Protection Agency. Washington, DC. 45 pp.
E.C. Jordan Co. 1987. Technical Memorandums dated June 2, 1987, and Septem-
ber 1987, submitted to the Office of Solid Waste, U.S. Environmental
Protection Agency, Washington, D.C.
Electric Power Research Institute. 1985. A Review of Field Scale Physical
Solute Transport Processes In Saturated and Unsaturated Porous Media.
EPRI EA-4190, Project 2485-5, Palo Alto, California.
146

-------
Faust, S.D., and H.M. Gomaa. 1972. Cheoleal Hydrolysis of Some Organic
Phosphorus and Carbamate Pesticides in Aquatic Environments. Environ.
Lett., 3. p. 171-201.
Federal Register. 1986. Hazardous Waste Management System: Land Disposal
Restrictions. U.S. Environmental Protection Agency, Vol. 51, No. 9.
Freeze, R.A. and J.A. Cherry. 1979. Groundwater. Prentice-Hall, New Jersey.
604pp.
Fuller, E.N., P.O. Schettler, and J.C. Glddlngs. 1966. A New Method for
Prediction of Binary Gas-Phase Diffusion Coefficients. Ind. Eng. Chem.,
58: 19-27.
Gelhar, L.W. and C.J. Axness. 1981. Stochastic Analysis of Macro-Dispersion
In Three-Dimensionally Heterogenous Aquifers. Report No. H-8, Hydraulic
Research Program. New Mexico Institute of Mining and Technology,
Soccorro, New Mexico, 140 p.
Gelhar, L.W., A. Mantoglou, C. Welty, and K.R. Rehfeldt. 1985. A Review of
Field Scale Subsurface Solute Transport Processes under Saturated and
Unsaturated Conditions. Electric Power Research Institute, Palo Alto.
107 p.
Ceraghty, J.J., D.W. Miller, F. van der Leeden, and F.L. Troise. 1973. Water
Atlas of the United States, Water Information Center, Inc., Port
Washington, New York.
Horton, R.E. 1916. Some Better Kutter's Formula Coefficients. Eng. News,
75:373-374.
Huyakorn, P.S., H.O. White, Jr., V.M. Guvanasen, and B.H. Lester. 1986.
TRAFRAP: A Two-dimensional Finite Element Code for Simulating Fluid Flow
and Transport of Radionuclides in Fractured Porous Media. FOS-33,
International Groundwater Modeling Center, Holcomb Research Institute,
Butler University, Indianapolis, Indiana.
Imhoff, J.C., R.F. Carsel, J.L. Kittle, Jr., and P.R. Hummel. 1989. Database
Analyzer and Parameter Estimator, DBAPE (User's Manual). EPA/600/3-89/
083, U.S. Environmental Protection Agency, Athens, Georgia.
Javandel, I., C. Doughty, and C.F. Tsang. 1984. Groundwater Transport:
Handbook of Mathematical Models. Water Resources Monogram 10, American
Geophysical Union, Washington, DC. 228 pp.
Jury, W.A., W.F. Spencer and W.J. Farmer. 1984. Behavior Assessment Model
for Trace Organic! in Soil: III. Application of Screening Model. 13:573-
579.
Jury, W.A. 198S. Spatial Variability of Soil Physical Parameters in Solute
Migration: A Critical Literature Review. Report No. EA-4228. Electric
Power Research Institute, Palo Alto, California.
Karlckoff, S.W. 1984, Organic Pollutant Sorption In Aquatic Systems. J.
Hydraulic Eng. (ASCE) 110:707*735.
147

-------
Kirkham, R.R., S.U. Tyler, and G.W. Gee. 1986. Estimating Leachate Produc-
tion from Closed Hazardous Waste Landfills. EPA/600/2-86/057, U.S.
Environmental Protection Agency, Cincinnati, Ohio.
Kittle, J.L., P.R. Hummel, and J.C. Imhoff. 1989. ANNIE-IDE, A System for
Developing Interactive User Interfaces for Environmental Models (Program-
mers Guide). EPA/600/3-89-034, U.S. Environmental Protection Agency,
Athens, Georgia.
Lallemand-Barres, A., and P. Peaudecerf. 1978. Recherche des relations entre
la valeur de la dlsperslvlte macroscoplque d'un milieu aquifere, ses
autres caracteristiques et les conditions de mesure. Bull. B.R.G.M. Fr.,
Section III, Series 2, pp. 277-284.
Llnsley, R.K., M.A. Kohler, and J.L.H. Poulhua. 1949. Applied Hydrology.
McCrw-RlU, Rm Toik.
Lyman, W.J., U.F. Reehl, and D.H. Rosenblatt. 1982. Handbook of Chemical
Property Estimation Methods: Environmental Behavior of Organic Compounds.
McGraw-Hill, New York. 960 pp.
Mabey, W.R., J.H. Smith, R.T. Podoll, H.L. Johnson, T. Mill, T.W. Chou, J.
Gates, I. Ualght Partridge, J. Jaber, and D. Vandenberg. 1982. Aquaclc
Fate Process Data for Organic Priority Pollutants. EPA/440/4-81-014,
U.S. Environmental Protection Agency, Washington, DC.
McKoy and Associates. 1986. Predicting Volatile Organic Emissions through
Soil Covers. The Hazardous Waste Consultant, September 1986 issue.
McWhorter, D. and D.K. Sunada. 1977. Groundwater Hydrology and Hydraulics.
Water Resources Publications, Fort Collins, Colorado.
Meeks, Y., P. Mangarella, C. Palhegyl, and A.M. Salhotra. 1988. Landfill
Source Module Progress Report. Woodward-Clyde Consultants. Contract No.
68-03-6304. Prepared for U.S. Environmental Protection Agency, Athens,
Ceorgla.
Mercer, J.U., S.D. Thomas, and B. Ross. 1982. Parameters and Variables
Appearing in Repository Siting Models. NUREG/CR-3066. Prepared for U.S.
Nuclear Regulatory Commission, Washington, DC.
Mills, W.B,, D.B. Porcella, M.J. Ungs, S.A. Gherinl, K.V. Summers, L. Mok,
G.L. Rupp, G.L. Bowie, and D.A. Halth. 1985a. Water Quality Assessment:
A Screening Procedure for Toxic and Conventional Pollutants in Surface and
CroundWater: Part I. EPA/600/6-85/002a, U.S. Environmental Protection
Agency, Athens, GA.
Mills, W.B., D.B. Porcella, M.J. Ungs, S.A. Gherinl, K.V. Summers, L. Mok,
G.L. Rupp, G.L. Bowie, and D.A. Halth. 1985b. Water Quality Assessment:
A Screening Procedure for Toxic and Conventional Pollutants in Surface and
CroundWater: Part II. EPA/600/6-85/002b, U.S. Environmental Protection
Agency, Athena, GA.
Mockus, V. 1972. Estimation of Direct Surface Runoff from Storm Rainfall.
iD National Engineering Handbook. Section IV, Hydrology. U.S. Soli
Conaervatlon Report NEH-Notlce 4-102. August.
148

-------
Morris, D.A., and A.I. Johnson. 1967. Summary of Hydrologlc and Physical
Properties of Rock and Soil Materials as Analyzed by the Hydrologlc
Laboratory of the U.S. Geological Survey. U.S. Geological Survey Water
Supply Paper 1839-D, 1967.
Mulkey, L.A., and T. Allison. 1988. Transient versus Steady-State Land
Disposal Model Comparisons. Report prepared for the Office of Solid
Waste, U.S. Environmental Protection Agency, Washington, DC.
Mulkey, L.A., A.S. Donlgian, Jr., T.L. Allison, and C.S. Raju. 1992.
Evaluation of Source Tern Initial Conditions for Modeling Leachate
Migration from Landfills. EPA/600/R-92/233, U.S. Environmental Protection
Agency, Athens, Georgia.
National Resource Council. 1990. Ground Water Models: Scientific and
Regulatory Applications. National Academy Press, Washington, DC. 320 pp.
Perry, R.H., and C.H. Chilton. 1973. Chemical Engineer's Handbook. McGraw-
Hill, New York, New York.
Salhotra, A.M., and P. Mlneart. 1988. Multimedia Exposure Assessment Model
For Evaluating the Land Disposal of Hazardous Wastes, Volume 2: Users'
Manual for the EPAMMM Code Including the Source Module. Woodward-Clyde
Consultants. Contract No. 68-03-6304. Prepared for U.S. Environmental
Protection Agency, Athens, Georgia.
Salhotra, A.M., P. Mineart, S. Sharp-Hansen and T. Allison. 1993. MULTIMED,
The Multimedia Exposure Assessment Model for Evaluating the Land Disposal
of Wastes--Model Theory. U.S. Environmental Protection Agency, Athens,
Georgia.
Schnoor, J.L., C. Sato, D. McKechin and D. Sahoo. 1987. Processes, Coeffi-
cients, and Modelc for Simulating Toxic Organics and Heavy Metals in
Surface Waters. EPA/600/3/3-87/015, U.S. Environmental Protection Agency,
Athens, Georgia.
Schroeder, A.C., A.C. Gibson, and M.D. Sraolen. 1984. The Hydrologlc Evalua-
tion of Landfill Performance (HELP) Model, Volumes I and II. EPA/530/SW-
009 and EPA/530/SW-010, U.S. Environmental Protection Agency, Cincinnati,
Ohio.
Soil Conservation Service. 1972. Hydrology. Section 4, SCS National
Engineering Handbook. U.S. Department of Agriculture, Washington, D.C.,
NEH-Notice 4-102.
Tchobanoglous, G., and E.D. Schroeder. 1985. Water Quality. Addlson-Wesley
Publishing Co. Reading, Massachusetts.
United States Environmental Protection Agency. 1987. Hazardous Waste
Treatment, Storage, and Disposal Facilities (TSDF)--Alr Emission Models.
EPA-450/3-87-026. Research Triangle Park, North Carolina.
United States Environmental Protection Agoncy. 1988. Superfund Exposure
Assessment Manual. EPA/540/1-68/001, Washington, DC. 157 pp.
149

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United States Environmental Protection Agency. 1990. Final Rule. Federal
Register, Vol. 55, No. 61, March 29th.
U.S. Food and Drug Administration. 1969. Fish and Shellfish. Vol. 1,
Section 202.14, pp. 3-5.
van der Heijde, P.K., and M.S. Beljin. 1988. Model Assessment for Delineat-
ing Wellhead Protection Areas. EPA-440/6-88-002, U.S. Environmental
Protection Agency, Uashlngton, DC.
van Genuchten, M.T. 1976. A Closerf-?«rm Equation for Predicting the Hydrau-
lic Conductivity of Unsaturated i >• ^oil Sci. Soc. J. 4:892-898.
Vanoni, V.A., ed. 1975. Sedimen:ation	ing. American Society of
Civil Engineers. New York, NY. 745
Weaver, J., C.G. Enfield, S. Yates, D. Kreamer, and D. White. 1989. Predict-
ing Subsurface Contaminant Transport and Transformation: Considerations
for Model Selection and Field Validation. U.S. Environmental Protection
Agency, ADA, Oklahoma.
Wllke, C.R. and C.Y. Lee. 1955. Estimation of Diffusion Coefficients for
Gases and Vapors. Ind. Eng. Chem. 47:1253-1257.
Wolfe, N.L., R.G. Zepp, J.A. Gordon, G.L. Baughman, and D.M. Cline. 1977.
Kinetics of Chemical Degradation of Malathlon in Water. Environ. Sci.
Technol. 11:88-93.
Wolfe, N.L., R.G. Zepp, and D.F. Paris. 1978. Use of Structure Reactivity
Relationships to Estimate Hydrolytic Persistence of Carbamate Pesticides.
Water Res. 12:561-563.
150

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APPENDIX A
CODS STRUCTURE AND INPUT DATA FORMAT
MULTIMED consists of a number of nodules, the theoretical details of which are
described In Salhotra et al. (1990). It is important for the user to under-
stand the capabilities and limitations of these modules. However, because an
interactive preprocessor, FREMED, has been developed to create or edit input,
the average user need not understand the format of the input files or the
structure of the code. For advanced users, who wish to modify the code or to
examine the input files without the use of the preprocessor, this chapter
provides an overview of the code structure and input file format. Much of the
information in this appendix is based on material in Salhotra and Mi« 'art
(1988). No information about the pre- and postprocessors for MULTIMED is
included.
A.1 MODEL STRUCTURE
The code consists of a number of subroutines. The organization of the subrou-
tines is shown in Figure A.l. In addition, a list of all the subroutines, the
calling subroutine/program, and a brief description of the subroutines is
included In Appendix B. Each subroutine Includes several comment statements
that describe the function of the subroutine. The arguments of each sub-
routine are divided into three categories: 1) arguments that are passed to
the subroutine by the calling program, 2) arguments that are modified within
the subroutine, and 3) arguments returned by the subroutine to the calling
program.
A.2 INPUT AND OUTPUT FILE UNITS
To run the model, one or two Input files are needed, depending on the options
selected by the user. The location of the open statements for these files,
the default unit numbers, file names, and contents are shown in Table A-l.
The model generates a number of output files. The location of the open state-
ments for these files, the associated default unit numbers, file names, and a
brief description are given in Table A-2.
The user specifies the name of the main output file. In deterministic mode,
this file contains an echo of the input data and the calculated contaminant
concentrations) at the receptor(s) of interest. In Monte Carlo mode, the
file consists of an echo of input parameters, selected statistical results,
and printer plots of frequency and cumulative frequency.
Two additional types of files are also generated. These are designated as the
*. VAR and *.0UT files, where the refers to a specific type of data for the
.VAR files and a specific module for the .OUT files. The *.VAR files contain
the values of the randomly-generated variables, any derived variables used for
each Monte Carlo simulation run, and the values of any deterministic
variables. The .OUT files contain the model results for each Monte Carlo
151

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- PRTINP-
— OUTPUT-
OPENF
SOPEN
COUNT
MODCHK
RANSET
PRTOUT-
AQNAMS
ARNAMS
CUNAMS
LFNAMS
SONAMS
STNAMS
VFNAMS
VTNAMS
DEFAULTS
INITGV
INITAR
INITVF	
h INITVT-
INITST-
UNCPRO-
r ADPRNT
- PRNEMP
PRHEMP
PRINTO
r
FRQTAB
FRQPLT
DISC
INITLF-
r- LINV	
-	LAYAVE
TMQEN1
-	TMOEN2
-	TMGEN3
REOX
CALLS-
PRNTVZ-
t
PRINTO
PRNEMP
LINER1
FACTR
TRNLOO
TRANSB
EXPRND-
-	NORMAL-
-	LOGNOR-
-	EMPCAL-
- LOOIOU-
EXPRN—
ANRMRN—
UNIFRM—
UNIFRN
Figure A.1 Subroutine organization tree for MULTIMED (from Salhotra
and Mineart, 1988).
(continued)
152

-------
MAIN-
— BATIN-
ARCALC
AIRIN—
— AIRDIS-
pr ADISRD-
LEFTJT
h CHKEND-
r
COMRD
VIRT
SIGMAZ
KEAS2-
READ3-
COMRD
ICHECK
- LFCALC-
- GVCALC-
- VTCALC-
— patch-
VFCALC-
h PERC	
EVPT
1- RUNOFF
C0NV02-
L- GV3DPT-
CPCAL-
L- OV3DFS
ADVECT
-	ADISPR
-	COEF
-	STEHF
WCFUN
RAPSON-
GV2DFT
GV2DFS-
—	oicnr	»—
-	S0LAT1	EXP ERF-1
DERFC
EXPD
- C0NV01
L- SOLBT-
H
FPSIl
GV3DPT
QROMB—-j— TRAPZD—|
FUNCTI
-	EVAL
LACRNO
-	S0LAY1— EXP ERF—p- DERFC
L EXPD
I
STEADY-
TRANSP-
L DBK1
L erfc
- DGAUSS
- 8WCALC-
r CINTER
-	CM IX
TRANS
-	DRINK
L FISH
Figure A.1 Subroutine organization tree for MULTIMED (from Salhotra
and Mineart, 1988).	(concluded)
153

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TABLE A-1. INPUT FILES NEEDED IN MULTIMED
Opened In
Unit
Name
Description
MAIN
IOUT7-7 USER-SPECIFIED Main Input file. Required
to run the model.
ADISRD
IUNT28-28 FREQ.IN
Contains Information
describing the wlnd-stabillty
Joint frequency distribution
for contaminant transport in
the air (Bee Section A.5.9.1)
simulation. Thus, for typical Monte Carlo simulations, these files will
contain 500 to 2000 values. Results of statistical analyses (mean, median,
and percentiles) of the values In the *.0UT files are Included in the main
output file and in the file STATS.OUT.
The BATCH.ECH file contains an echo of all the data in the input file and
Includes any error messages generated while reading the data. Errors in
reading the data will stop execution of the program.
Two of the output files may be used with the postprocessor, POSTMED. The data
in SAT1.0UT can be used by the postprocessor to generate frequency and
cumulative frequency plots. For transient, deterministic simulations, plots
of concentration versus time can be generated by the postprocessor using data
in the main input file.
A.3 COMMON BLOCKS AND PARAMETER STATEMENTS
Most variables are passed between subroutines through the use of common
blocks. There are a total of 54 common blocks In the model (I.e., excluding
those associated with the pre- and postprocessors), each containing a related
set of variables. The common blocks are contained in files which are accessed
by the code during compilation through the use of INCLUDE statements located
at the beginning of each subroutine.
Parameter statements are used to define all I/O (Input/Output) unit numbers
and array dimensions in the model. Any array dimensions or I/O numbers can be
changed by assigning a new value to the variable in the appropriate parameter
statement. The entire code must be recompiled and linked if changes are made
to any parameter statement.
A.4 STRUCTURE OF THE INPUT FILES
The overall structure of the main Input file is shown in Figure A.2. The
first two cards contain the title of the simulation. The remaining cards in
the file contain the data necessary to run MULTIMED. These data are clustered
Into a number of groups, each of which contains a specific type of data that
Is input using one or more DATA CARDS. The data groups are divided into
154

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TABLE A-2. OUTPUT FILES GENERATED BY MULTIMED
Opened In Unit
Name
Description
MAIN	I OUT - 1
SOPEN	IUNT8 - 8
user-specified
AQUIFER.VAR
SOPEN
SOPEN
SOPEN
SOPEN
SOPEN
SOPEN
BAT IN
SOPEN
SOPEN
IUNT13 - 13 CHEMICAL.VAR
IUNT14 - 14 SOURCE.VAR
IUNT15 - 15 SURFACE.VAR
IUNT16 - 16 VFLOW.VAR
IUNT17 - 17 VTRNSPT.VAR
IUNT18 - 18 AIR.VAR
BATOUT - 19 BATCH.ECH
VFOUT - 20 VFLOW.OUT
VTOUT - 21 VTRNSPT.OUT
Main output file.
Values of aquifer variables
generated for Monte Carlo
simulations.
Values of chemical variables
generated for Monte Carlo
simulations.
Values of source variables
generated for Monte Carlo
simulations.
Values of surface water
variables generated for Monte
Carlo simulations.
Values of unsaturated zone
material variables and
functional parameters generated
for Monte Carlo simulations.
Values of unsaturated zone
transport variables generated
for Monte Carlo simulations.
Values of Air Emissions and
Dispersion Module variables
generated for Monte Carlo
simulations.
Echo of the batch input file
and list of any errors in the
input data.
Results from the Unsaturated
Zone Flow Module.
Concentrations at the water
table computed by the
Unsaturated Zone Transport
Module.
(continued)
155

-------
TABLE A-2. OUTPUT FILES GENERATED BY MULTIMED (concluded)
Opened In
Unit
Name
Description
SOPEN
STOUT - 22 SAT.OUT
Downgradlent well
concentrations computed by
Saturated Zone Transport
Module.
SOPEN
SOPEN
AROUT - 23 AIR.OUT
STOUT2 - 24 SURFACE.OUT
Results from Air Emissions
Module and the receptor
concentrations for the Air
Dispersion Module.
Results from the Surface
Water Module.
MAIN
MAIN
SOPEN
I STAT - 25 STATS. OUT
IUNT27 - 27 SATI.OUT
IUNT29 - 29 LANDFM.VAR
Summary statistics of the
receptor concentrations
(groundwater, atmosphere,
surface stream).
Downgradlent well
concentrations sorted in
ascending order (CDF of
concentrations).
Values of landfill material
parameters generated for
Monte Carlo simulations.
SOPEN
IUNT30 - 30 LANDFL.VAR
Values of liner properties
generated for Monte Carlo
simulations.
SOPEN
IUNT31 - 31 LANDFH.VAR
Values of hydrology para-
meters generated for Monte
Carlo simulations.
subgroups, with each subgroup containing a set of data specific to the group
within which the subgroup Is located. The structure of each data
group/subgroup is illustrated in Figure A.2. In addition to the DATA CARDS,
the input file contains DATA CROUP/SUBGROUP SPECIFICATION CARDS, END CARDS,
and if desired, one or more COMMENT CARDS.
The data for the model are divided into nine major groups. These groups are
listed In Table A-3 along with the appropriate code for the GROUP SPECIFI-
CATION CARD. Each data group is read in as a unit, with the beginning
identified by the GROUP SPECIFICATION CARD and the end by the END CARD. The
data cards are sandwiched between these two cards. Further, the data group
may contain one or more subgroups that are also listed in Table A-3. Note
that the structure of a subgroup is exactly the same as that for a group--
156

-------
I.e., a subgroup is identified by a SUBGROUP SPECIFICATION CARD and terminated
by an END CARD, with the subgroup data sandwiched between the two cards. A
data file need contain only those data groups (and subgroups within a data
group) that are necessary.to run the options selected by the user.
The options selected by the user and indicated in the General Data Group will
determine which additional groups of data are necessary. For example, if the
user has specified within the General Data Group that only the Saturated Zone
Transport Module will be run, the Unsaturated Zone Flow and Transport Data
Groups (VFL, VTP) are not necessary. Also note that the structure of the
input file allows the required data groups to be arranged in any order.
A.4.1 Comment Cards
COMMENT CARDS are indicated by the presence of three asterisks, '***'. The
group of '***' can be input starting at any column of the card but must be the
first three non-blank characters. The COMMENT CARDS are useful for separating
data types and can be used to Include other helpful comments. Note that there
are no restrictions as to the location and number of COMMENT CARDS, except
that they cannot be the first two cards in the data file.
A.4.2 Data Group/Subgroup Specification Card. End Card, and Data Cards
The DATA GROUP/SUBGROUP SPECIFICATION CARD indicates the beginning of a
specific data group and Includes the Croup (Subgroup) Specification Code
(Table A-3) in columns 1 to 3. For example, If the DATA GROUP SPECIFICATION
CARD contains the letters 'AQU' In columns 1 to 3, it implies that the
following cards, up to and including the corresponding 'END' card, contain
aquifer data.
With the exceptions discussed in Section A.5, each DATA CARD contains
information about one variable only. Typically the card will contain the
variable specification index, variable name, Monte Carlo distribution type,
distribution parameters, and the upper and lower bounds of the distribution.
To the extent possible, consistent formats for the DATA CARDS have been
maintained for the different data groups.
The termination of a data group and/or a subgroup is Indicated by the END
CARD, which contains the word END in the first three columns.
A.4.3 Specification of Parameter Values
Within each group, except the General Data Group, there are a number of
variables whose value can be specified in one of three ways: 1) the variable
may be assigned a constant value, 2) the variable may be derived within the
code using functional relations--for example, the aquifer porosity may be
derived from the particle diameter, or 3) the variable may be assigned a
distribution and the value randomly generated in the Monte Carlo simulation.
The numerical codes associated with each distribution type are listed in Table
A-4. Depending on the distribution selected for a particular variable, the
required input data will vary. Refer to Section 9.4 of Salhotra et al. (1990)
for information about the seven Monte Carlo distribution options. Section
5.5.3,5 of Salhotra et al. (1990) or Section 6.5.10 of this document explain
the Gelhar distribution and the derivation of dlsperslvity.
157

-------
STRUCTURE OF
INPUT DATA FILE
STRUCTURE OF
EACH GROUP OR SUBGROUP
Group 1 Data
Title Cad
Continuation ol
Hie Card
Group 2 Data
I
i
Group N Data
i
f
End Card
Group/Subgroup
Specification Card
Data Card 1
Data Card 2.
T
I
End Card
Oala Card M
rigure A.2 Structure of the input date file, data groups,
•nd eubgroups (from Salhotra and Mineart, 1998).
158

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TABLE A-3. INPUT DATA GROUPS AND SUBGROUPS IN HULTIMED
Data Group	Group Specification Code
1.
General Data
GEN
2.
Source Data
SOU
3.
Landfill Data
LFL
4.
Chemical Data
CHE
5.
Unsaturated Zone Flow Data
VFL
6.
Unsaturated Zone Transport Data
VTP
7.
Aquifer Data
AQU
8.
Surface Uater Data
SUR
9.
Air Emissions and Dispersion Data
AIR
Subgroups	Subgroup Specification Coda
1.
Array Data
ARR
2.
Empirical Distribution Data
EMP
3.
Control Data
CON
U.
Spatial Discretization Data
SPA
5.
Material Property Data
SAT
6.
Material Specification Data
MAT
7.
Unsaturated Zone Moisture Data
SOI
8.
Unsaturated Zone Transport Properties
Data TRA
9.
Unsaturated Zone Time Stepping Data
TIM
10.
Landfill Liner Data
LIN
11.
Layer Identification Data
LAY
12.
Hydrology Data
HYD
159

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TABLE A-4. DISTRIBUTIONS AVAILABLE AND THEIR CODES
Distribution Type	Distribution Code
Constant
0
Normal
1
Lognormal
2
Exponential
3
Uniform
4
LoglO Uniform
5
Empirical
6
Johnson SB
7
Gelhar*
8
Derived Dlspersivity1'
10
Derived Variable0
-1
* Gelhar's distribution applies only to the saturated zone disperslvitles.
For details, refer to Section 6.5.10.
b The derivation of the saturated zone disperslvitles using distribution
code 8 is described in Section 5.5.3.5 of Salhotra et al. (1990).
0 For parameters other than the spread of the source or the source
thickness (mixing zone depth), a -2 is interchangeable with a -1.
Note: The seven Monte Carlo distributions (distribution code 1-7) are de-
scribed in Section 9.4 of Salhotra et al. (1990).
A.4.4 The Array Subgroup
The contents and format for the Array Subgroup are shown in Table A-5. The
first card is the SUBCROUP SPECIFICATION CARD, with the code ARR in the first
three columns. This card is followed by one card for each variable in the
group. Those cards contain values/distributions, and lover and upper bounds
for the indicated variables. For example, when the ARR subgroup is Included
within the Aquifer Croup Data, the subgroup will contain cards describing the
aquifer-specific variables such as porosity, disperslvitles, etc. The speci-
fic variables within each group are discussed in Section A.5. Note that the
number of cards within the Array Subgroup varies because the various groups
and subgroups have different numbers of input variables. The variable being
input is identified by the value of the Index I.
The value of the integer variable NDSTPRM(I) in Table A-5 indicates the type
of distribution chosen for the variable identified by the index I. The
available options and values of the Integer variable NDSTPRM(I) are listed in
Table A-4. If any of the variables are specified to have an Empirical
distribution (NDSTPRM(I) - 6), then it Is necessary to include the EMPIRICAL
SUBCROUP, the details of which are described In Section A.4.5. Note that If
the variable is specified to be a constant (NDSTPRM(I) - 0), the value input
as mean for the corresponding variable (ARRPRM(I.l)) is used in the
simulations. The end of the Array Subgroup is Indicated by an END CARD.
160

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TABLE A-5. CONTENTS AND FORMAT OF A TYPICAL ARRAY SUBGROUP
Card	Contents	Format
A1	"ARR"	A3
A2	I, NAME(I), NDSTPRM(I), ARRPRM(I.l)	12, IX, ASO, 7X,
ARRPRM(I,2), BOUND(I.l), BOUND(I,2)	110, 5X, 4F10.0
A3	"END"	A3
Note: Card/line A2 is repeated for each variable within the group.
Definition of Contents
"ARR"	Subgroup Specification Card indicating the start of the Array
Subgroup.
I	Integer which identifies the variable being Input. See the
individual data group tables for the values of I for specific
variables. Note that I is not a counter.
NAME(I) Name of variable I. It is used to Identify the variables In the
output files.
NDSTPRM(I) Integer which identifies the type of distribution used for
variable I (e.g., constant, derived, or one of the Monte Carlo
distributions). See Table A-4.
ARRPRM(I,1) Mean value for variable I.
ARRPRM(I,2) Standard deviation for variable I.
BOUND(I,1) Minimum allowed value (lower bound) for variable I.
B0UND(I,2) Maximum allowed value (upper bound) for variable I.
"END"	End Card Indicating the end of the Array Subgroup.
A.l*. 5 The Empirical Distribution Subgroup
The contents and format for the Empirical Distribution Subgroup are shown in
Table A-6. The first card Is the SUBGROUP SPECIFICATION CARD, with the code
EMP in the first three columns. The next card identifies the variable (using
the Index I) that has an empirical distribution and the number of coordinates
of the empirical cumulative distribution function that are being input. A
maximum of 20 coordinates can be input.
161

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The next sec of cards (two cards, If fewer than 10 coordinate pairs are input,
or four cards, If more than 10 coordinate pairs are input) contain the
probabilities (in ascending order) and the corresponding values of the
variable. Variable values corresponding to cumulative probability values of
zero and unity must be provided. Note that all the cumulative probability
coordinate values are first input, followed by an equal number of the
corresponding variable values. The above procedure Is repeated for each of
the variables that have empirical distributions. The end of the subgroup is
Indicated by the END CARD.
A.5 FORMAT OF THE DATA CROUPS
As was stated above, DATA CARDS 1 and 2 contain the title of the run, with a
maximum of 80 columns per card. DATA CARDS 3 through the end contain data
specific to one or more groups/subgroups. The specific formats for each data
group are described below. The data groups do not have to be input in the
order in which they are discussed. However, It is recommended that the
General Data Group be input first, An END CARD must be put at the end of the
data file following the end of the last data group.
A.S.I General Data Group
The contents and format of the Ceneral Data Croup are shown in Table A-7.
This group can contain up to six cards. The first card is the GROUP
SPECIFICATION CARD and has the code GEN in the first three columns. The
second card contains the name of the chemical being simulated. Card three
contains a number of variables that enable the user to select the model
options. A schematic showing key options pertaining to the Saturated Zone
Module is indicated in Figure A.3. If transport in a stream (Surface Water
Module) is simulated, the variable XST is the fourth card and indicates the
distance from the point of groundwater plume interception to the water supply
Intake. The next card, i.e. values of TPSTN(I), is necessary only If the
Saturated Zone Module is run in the unsteady state and contains the time
values at which the saturated zone results are to be computed. The final card
Is the END CARD that indicates the termination of this set of data. Table A-8
Is an example of a typical Ceneral Data Croup.
A.5,2 Source Data Group
The contents and format for the Source Data Croup are shown In Table A-9.
This group describes the contaminant source-specific data. The first card is
the CROUP SPECIFICATION CARD, with the code SOU in the first three columns.
This is followed by the Array Subgroup, which la Indicated by the SUBGROUP
SPECIFICATION CARD with the code ARR in the first three columns. Details of
the Array Subgroup were presented in Tabla A-5 and Section A.4.4. This
subgroup contains an array of lnforaatlon about the values and/or the
distributions and lover and upper bounds of (up to) nine source-specific
162

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TABLE A-6. CONTENTS AND FORMAT OF A TYPICAL EMPIRICAL DISTRIBUTION SUBGROUP
Card	Contents	Format
El	-EMP"	A3
E2	I. ICOUNT	2110
E3	EMPPRM(J,2,1),	J- 1,ICOUNT	10(F8.0, 2X)
E4	EMPPRM(J,1,I),	J- 1,ICOUNT	10(F8.0, 2X)
E5	"END"	A3
Note: Card/lines E3 and E4 are repeated twice If more than 10 coordinates are
input. Card/lines E2, E3, and EA are repeated If more than one variable
has an empirical distribution.
Definition of Contents
Subgroup Specification Card Indicating the start of the Empirical
Distribution Subgroup.
Integer which Identifies the variable being input. See the
Individual data group tables for the values of I for specific
variables. Note that I is not a counter.
Number of coordinates of the empirical cumulative frequency
distribution.
Cumulative probability (coordinate) values for the empirical
distribution for variable I.
Corresponding variable values associated with the above probabili-
ties.
End Card indicating the end of the Empirical Distribution
Subgroup.
163
"EMP"
I
ICOUNT
EMPPRM
(J,2,1)
EMPPRM
(J.l.D
"END"

-------
TABLE A-7. CONTENTS AND FORMAT OF THE GENERAL DATA GROUP
Card
Concent*
Format
CI
C2
C3
G4
C5
C6
"CEN"
CHEMICAL
OPTION, ISOURC, OPTAIR,
RUN, MONTE, ROUTE, ISTEAD,
NT, IOPEN, IYCHK, IZCHK
PALPH, LANDF, APPTYP, COMPLETE
XST
TPSTN(I), I - 1, NT
"END"
A3
S0A1
315, 5X, Al3, 2X,
715, F5.0, 315
F10.0
10(F8.0, 2X)
A3
Definition of Contents
"GEN"	Group Specification Card Indicating the start of the Ceneral Data
Group.
CHEMICAL Name of chemical being simulated.
OPTION	Integers defining which scenario to run.
1	Saturated Zone Transport Module only
2	Unsaturated and Saturated Zone Modules
3	Unsaturated, Saturated and Surface Water Modules
4	Saturated Zone and Surface Water Modules
6 Air Modules only
ISOURC
condition.
OPTAIR
0
1
2
RUN
DETERMINISTIC
MONTE
MONTE
Flag Indicating the type of saturated zone boundary
Gaussian source
Patch source
Flag Indication which air modules to run.
No air modules are run
Air Emissions Module run
Air Emissions and Air Dispersion Modules run
Flag Indicating the type of run.
The number of Mont* Carlo simulations to be performed.
1(4

-------
TABLE A-7. CONTENTS AND FORMAT OF THE GENERAL DATA GROUP (continued)
Definition of Contents
ROUTE	Flag indicating the exposure route for the Surface Water
Module. (This parameter is ignored if not running the
Surface Water Module.)
1	Human exposure through drinking water
2	Human exposure through fish consumption
3	Exposure to aquatic organisms
ISTEAD	Flag indicating unsteady- or steady-state simulation of the
unsaturated and saturated zone transport.
0	Unsteady-state
1	Steady-state
NT
IOPEN
XST
the
TPSTN(I)
IYCHK
value
IZCHK
value
PALPH
LANDF
Number of time steps for which unsteady-state saturated zone
transport results are required.
Integer flag indicating the information to be output.
0	Opens all *.VAR and *.OUT files
1	Opens only the main output file, STATS.OUT, and SATl.OUT
2	Opens only the main output file and STATS.OUT
Instream distance between the point of groundwater loading to the
downstream water supply intake. Include only when running
Surface Water Module.
Times at which unsteady-state transport results for the
saturated zone are required (Needed only when ISTEAD - 0).
Flag for rejecting well locations outside of the groundwater plume
width when in Monte Carlo mode.
0	Rejects the generated receptor well location y-coordinate
1	Does not reject the generated y-coordinate value
Flag for rejecting well locations outside of the groundwater plume
depth when in Monte Carlo mode.
0	Rejects the generated receptor well location z-coordlnate
1	Does not reject the generated z-coordlnate value
The selected confidence level, In percent, for the four estimated
percentiles (80th, 85th, 90th, 95th).
Flag for running the Landfill Module.
0	Do not run the Landfill Module
1	Run the Landfill Module
163

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TABLE A-7. CONTENTS AND FORMAT OF THE GENERAL DATA GROUP (concluded)
Definition of Contents
APPTYP
Flag for the type of application being simulated.
1	Generic MULTIMED application
2	Subtitle D MULTIMED application
COMPLETE
Flag indicating whether all the necessary input parameters
have been defined (parameter used in the preprocessor).
0	Undefined parameters exist in the input
1	No undefined parametero exist in the input
"END"
End Card indicating the end of the General Data Subgroup.
variables. The variables associated with each index I are listed in Table A-
10.
If any of the variables are specified to have an empirical distribution
(NDSTPRM(I) - 6), then it is necessary to include the Empirical Distribution
Subgroup discussed in Section A.4.5. If none of the source-specific variables
have an empirical distribution, this subgroup is not necessary.
Of the nine variables Included in this group, three can be derived. These are
the spread of input source, the length scale, and the width scale of the
facility. Thus, NDSTPRM(4), NDSTPRM(8), and NDSTPRM(9) can have values less
than zero (see Table A-4). The methods used to derive these variables are
discussed in Section 5.5.1 of Salhotra et al. (1990) or Section 6.2 of this
manual.
Note that if the user specifies LANDF-1 in the General Data Croup (i.e., uses
the Landfill Module to compute infiltration) the value of infiltration
specified in the Source Data Group (Table A^-10) is Ignored.
An END CARD Indicates the end of the Source Data Group.
A.5.3 Landfill Data Group
This group contains data required by the Landfill Module and consists of four
subgroups. It is required only if the infiltration la not Input by the user
in the Source Data Croup. The subgroup* and the associated codes are listed
below:
A.5.3.1 Landfill Control Data Subgroup-
Table A-11 describes the landfill control subgroup and the default values.
Data In the other subgroups vary depending on the values specified in this
subgroup.
166

-------
GAUSSIAN
PATCH
STEADY STATE
UNSTEADY STATE

KMUKMM
REJECT WELL LOCATIONS
OUTSOE PLUME M VERTICAL AND
TRANSVERSE OWECTION



REJECT WELLS SCREENS0
BELOW PLUME M VERTICAL DIRECTION
LOCATION OF
WBL
\ KMUllKMUl

REJECT WELLS OUT StOE
PUJME IN TRANSVERSE DIRECTION



\ IVCMMKMUI
DO NOT REJECT ANY
WELL LOCATIONS
Figure A.3 Kay options available in the general data group pertaining
to the saturated zone transport nodule (from Salhotra and
Mineart, 1988) .

-------
TABLE A-8. EXAMPLE OF A TYPICAL GENERAL DATA GROUP
general data
*** CHEMICAL NAME FORMAT ( 8OA 1)
DEFAULT CHEMICAL
*** ISOORC	ROUTE
~~~OPTION OPTAIR RUN	MONTE
3 0 0 DETERMINISTIC 500 1
***XST
1000.00
EHD GENERAL
IYCHK PALPH	APPTYP
IOPEN IZCHK LANDF COMPLETE
0 0 1 90.0 110

-------
TABLE A-9. CONTENTS AND FORMAT OF THE SOURCE-SPECIFIC DATA CROUP
Card	Coolants	Format
SI	-SOD"	A3
Array iMbump	{Smm Table A-))
K-n	L^lrlctl Dliullntlai Subgroup	(Sm Table A-6)
si	-no-	A3
Definition of Contents
""S00~	(ka^ Specification Card Indicating the (tart of tha Source Data Group.
U|nv Mmuuy defining the Mote variables,
fcjlrteil	SiAgiuup defining any eaplrlcal dlitrlbatlou.
Bid Card Indicating tba and of the Source Data Group.
Specification Coda	Rafar to Table
Control Bate	COM	A-ll
ad	LAI	A-12
Halei lal Date
LIS	A-13
Landfill Ifetarlal	SAT	A-15
Hydmlnglr Data	BTD	A-17
The first card of this group Is the (SOUP SPECIFICATION CABD and Includes tha code LFL In tha first three colims. Tha next card Is the first
s«*group opertflretlon card and Infinites tba appropriate code sham above. Data for each of the subgroups of tha Landfill Module are described belov.
¦one at Urn variables In this g^oup can be derived (I.e.. they cannot have a distribution type of -1).
¦ote that eone of the input mita for the Landfill Module are non-metric. These data are automatically converted frata tha input units to tha metric
eyeten of mite by the code before ccaputatlans era performed.

-------
TABLE A-10. VARIABLES IN THE SOURCE-SPECIFIC ARRAY SUBGROUP
Mil 1 SPECIFIC VMUABU MIA
ABAI »"
SOURCI SPECIFIC VARIABLES
m.	VMIAMJ BMC	UMTS	DISTRIKTTIOB PARAMETERS	LIMITS
—	HEAH	STD DEV HOI	MAX
1 hfllUatloD rtU
m/jr
0
-999. -9
9. 0.1002-09 0.1002+11
2 Am of «nu dlsp tult
mT2
0
-999. -9
9. 0.1002-01 -999.
3 Oortllai of pol —
T*
0
-999. -9
9. 0.1002-08 -999.
4 S^ntd of i ibiI mIiimiI m«
¦
-1
-999. -9
9. 0.1002-08 0.1002+11
3 l»rhii|> rtU
¦/yr
0
-999. -9
9 . 0.1002-09 0.1002m
6 Soif canUet
1/yr
0
-999. -9
9. 0.0002+00 -999.
7 hit cone «t Undfill
¦l/l
0
1.00 -9
9. 0.0002+00 -999.
S Uo|th >fil» of facility
¦
-1
-999. -9
9. 0.1002-08 0.1002*11
9 Width ifil» of facility
•
-I
-999. -9
9. 0.1002-08 0.1002+11
OB MUX
OD SOOKX MllUlL TMITAW ¦ MIA

-------
A.5.3.2 Layer Thickness and Material Data Subgroup--
Table A-12 describes the layer thickness and material data necessary for the
Landfill Module. The data consist of the layer thickness and the material
number associated with each layer. The material numbers correspond to the
order in which the material properties are read in as part of the Material
Properties Subgroup described in Section A.5.3.4.
A.5.3.3 Liner Property Data Subgroup-•
Liners are low permeability sheets of rubber or plastic materials which are
used as barriers to vertical flow. A description of the liner property data
can be f< and in Table A-13. There should be one set of data for each liner
(LFCP(4)) In Table A-ll. These data include the liner thickness, liner
hydraulic conductivity, percent failure of the liner and the layer number
containing the liner. The variables in this subgroup are presented in Table
A-14.
A.5.3.4 Landfill Material Property Data Subgroup--
The landfill can consist of a number of different materials (the number
specified by the value of LFCP(2) In Table A-ll) with different hydrogeologi-
cal properties. The properties for each of the materials are included in this
subgroup. Details of the contents and formats of this subgroup are shown in
Tables A-15 and A-16. When Che landfill consists of more than one material,
information about each material is Input using an Array Subgroup. These
materials are subsequently identified by the order in which the Array Sub-
groups appear. Thus, material number 4 would refer to the material that has
properties Included in the fourth Array Subgroup. The termination of data for
each material is indicated by an END CARD. The end of the Landfill Material
Property Data Subgroup is also Indicated by an END CARD.
A.5.3.5 Hydrologlc Data Subgroup••
A water balance approach is used to estimate the average infiltration rate
over the duration of an "event." An event is defined as the typical period
between the start of two sequential storms, and includes both the storm
duration and the inter-storm interval. Table A-17 describes the contents and
format of the Hydrologlc Data Subgroup required to perform this balance. The
hydrologlc parameters are presented in Table A-18.
A.5.4 Chemical Data Croup
The concents and format of the Chemical Data Group are shown in Table A-19.
The first card Is the GROUP SPECIFICATION CARD, with the code CHE In the first
three columns. The second card Is the SUBGROUP SPECIFICATION CARD, with the
code ARR in the first three columns. This subgroup contains the array of
information about the values and/or the distributions and upper and lower
bounds of up to 16 chemical-specific variables. The variables being input are
identified by the value of the index I. The variables associated with each
index I are shown in Table A-20. For example, a data card with 1-6 indi-
cates that the card contains information about the base catalyzed hydrolysis
rate constant for che chemical being simulated.
If any of the variables are specified to have an empirical dlstrlbudon
(NDSTPRM(l) - 6), then it is necessary to Include the empirical distribution
171

-------
TABLE A-11. CONTENTS AND FORMAT OF THE LANDFILL MODULE CONTROL DATA GROUP
Card	Concents	Formac
VI
C02
C03
C04
"LFL"
"CON"
CURVE. LFCP(l), I - 1,6
"END"
A3
A3
F10.0, 6110
A3
Definition of Contents
"LFL"	Croup Specification Card indicating the start of the Land-
fill Module Data Croup.
CON	Subgroup Specification Card indication the start of the
Landfill Module Control Data Subgroup.
CURVE	SCS curve number for moisture condition AMC-II.
LFCP(l)	Number of layers in the Landfill Module.
LFCP(2)	Number of different porous materials. Maximum permissible is
20.
LFCP(3)	Parameter indicating the type of relationship used for
relative permeability versus saturation.
1	van Cenuchten functional parameters
2	Brooks and Corey functional parameter
LFCP(4)	Number of liners in the landfill.
LFCP(5)	Number of •easons.
LFCP(6)	Parameter indicating method for calculating evapotransplra-
tion. (Only one option la available in the current version
of the code.)
0 Seasonal potential evapotransplradon read in
LFCP(7)	Number of Che layer which la Che laCeral drainage layer.
Enter 0 if chere la no lateral drainage layer.
"END"	End Card indicating Che end of Che Landfill Module Control
Data Subgroup.
172

-------
TABLE A-12. CONTENTS AND FORMAT OF THE LANDFILL MODULE LAYER THICKNESS AND
MATERIAL DATA SUBGROUP
Card
Contents
Format
LAI
LA2
LA 3
"LAY"
LFLAYR(I), LPROP(I)
"END"
A3
C10.0, 110
A3
Note: Card/line LA2 is repeated for each layer in the Landfill Module (LFCP(l)
In Table A-11).
Definition of Contents
"LAY"
LFLAYR(I)
LPROP(I)
"END"
Subgroup Specification Card Indicating the start of the
Landfill Layer Thickness and Material Subgroup.
Thickness of layer I.
Material number for layer I corresponding to data read as
part of the Material Properties Subgroup (see Section
A.5.3.4).
End Card indicating the end of this subgroup.
subgroup, discussed In Section A.4.5. If none of the chemical-specific
variables have an empirical distribution, then this subgroup Is not necessary.
A.5.5 Unsaturated Zone Flow Data Croup
This group contains data required by the Unsaturated Zone Flow Module and
consists of five subgroups. The Control Data Subgroup should be the first
subgroup in the Unsaturated Zone Flow Data Group. The subgroups and the
associated codes are listed below:
173

-------
TABLE A-13. CONTENTS AND FORMAT OF THE LANDFILL MODULE LINER PROPERTY
SUBGROUP
Card
Contents
Format
LI	"LIN-
LAI	"LAY"
LA2	LINER(I)
LA3	"END"
A1-A3	Array Subgroup
E1-E5	Empirical Distribution Subgroup
LI2	"END" (Material)
LI 3	"END"
A3
A3
15
A3
(See Table A-S)
(See Table A-6)
A3
A3
Note: Cards/lines A1-A3 and El-ES need to be repeated for each liner (i.e.,
LFCP(4) number of times). The Empirical Distribution Subgroup Is needed
only if one or more variables in the Array Subgroup has an empirical
distribution.
Definition of Contents
"LIN"
"LAY"
LINER(I)
Array Subgroup
Empirical
Distribution
Subgroup
"END"
Subgroup Specification Card indicating the start of the
Landfill Liner Properties Data Subgroup.
Subgroup Specification Card indicating data containing layer
number associated vir.h liner properties.
Layer number associated with the following data.
Subgroup defining the landfill liner properties variables.
Subgroup defining any empirical distributions.
End Card indicating the end of data for a liner (one such
end card Is required for each liner).
'END"
End Card indicating the end of this subgroup.
174

-------
TABLE A-14. VARIABLES IN THE LANDFILL LINER PROPERTY ARRAY SUBGROUP
ipp»t VALI1ES
LMDFIU. I,im VARIABLES
VABIABLE ¦««	QUITS	DISTUXOTICd PAHAKETEBS	LIMITS
tCAl	STB 10 HD	MAX
1 IhltkMU Of
mill*
0
-999.
-999.
0.100E-00 -999.
2 Bydmlic cooAictlTlty
cm/hr
0
-999.
-999.
0.100 10.0
) Ftilnn ret* of 1 inmr
X
0
•999.
-999.
O.OOOE+OO 100.
ED ABUT
no libs i
~D LOOl DATA

-------
TABLE A-15. CONTENTS AND FORMAT OF THE LANDFILL MODULE MATERIAL PROPERTY
SUBGROUP
Card
Contents
Format
SA1	"SAT"
A1-A3	Array Subgroup
E1-E5	Empirical Distribution Subgroup
SA2	"END" (Material)
SA3	"END"
A3
(See Table A-5)
(See Table A-6)
A3
A3
Note: Cards/lines A1-A3 and E1-E5 need to be repeated for each material (I.e.,
LFCP(2) number of times). The Empirical Distribution Subgroup is needed
only If one or more variables In the Array Subgroup has an empirical
distribution.
Definition of Contents
"SAT"
Array Subgroup
Empirical
Distribution
Subgroup
"END"
Subgroup Specification Card indicating the start of the
Landfill Material Data Subgroup.
Subgroup defining the landfill material variables.
Subgroup defining any empirical distributions.
End Card indicating the end of data for a material (one such
end card Is required for each material).
"END"
End Card Indicating the end of this subgroup.
176

-------
TABLE A-16. VARIABLES IN THE LANDFILL MATERIAL PROPERTY ARRAY SUBGROUP
SATURATED MATERIAL FBOPEBTT PARAMETERS FOB LANOFIU
ARRAY VALUES
LANDFILL MATERIAL VARIABLES
•••	VARIABLE RMS	UHITS	DISTRIBUTION PARAMETERS	LIMITS
***	MEAN	SIODEV H>	MAX
1 Sat hydraulic conduct
cm/hx
0
-999.
9. 0.100E-10
0.100E+05
2 Porosity

0
-999.
9. 0.100E-06
1.00
3 Rnidotl Mtu content

0
-999.
9. 0.100E-06
1.00
4 Brooks cr»d Corey exponent

0
-999.
9. 0.QOOE+OO
10.0
5 ALFA coeff for Lendfill
1/cm
0
-999.
9. O.OOOE+OO
1.00
6 BRA - Van Csnuchten exponent

0
-999.
9. O.OOOE+OO
10.0
EXD ARRAY
ESQ MATERIAL 1
E*D SATURATES MATERIAL HgtfUtTT DATA

-------
TABLE A-17. CONTENTS AND FORMAT OF THE LANDFILL MODULE HYDROLOGY SUBGROUP
Card Ccnttnts	Format
BY	"ETD"	A3
&1-A3	Array Subgroup	(Saa Tabla A-5)
E1-E5 Ekqiirlcal Distribution Subgroup	(Saa Tabla A-6)
BY2	"EBD" (Saaaon)	A3
HT3	-BE)-	A3
Iota:	Cards/linos A1-A3 and E1-E5 naad to b« rapaatad for aacb muod (I.a., LfCPO) mabar of timas). Tha Empirical Distribution Subgroup la
nisdad only if ooa or nora variables	In tha Array Subgroup has an aopirleal distribution.
Definition of Contants
"HYD"
Array Subgroup
E^>lrical
Distribution
Subgroup
"ETO"
-EMD"
Subgroup Spacification Card indicating tha start of tha Landfill Hydrology Data Subgroup.
Subgroup dafining tha landfill hydrology varlablas.
Subgroup dafining any anplrlcal distributions.
End Card indicating tha and of data for a saason (ooa such and card is rsqulrad for aacb ssason).
End Card indicating tha and of this subgroup.

-------
TABLE A-18. VARIABLES IN THE LANDFILL HYDROLOGY ARRAY SUBGROUP
HYDROLOGY PARAMETERS
ARRAY VALUES
HYDROLOGY VARIABLES
VARIABLE NAME
UNITS
DISTRIBUTION PARAMETERS
KEAJf	STD DEV
LIMITS
MIS MAX
1
Pr«clpilAtian
cm
0
-999.
-999.
O.OOOE+OO *999
2
Duration of «v«nt
days
0
-999.
-999.
O.OOOE+OO -999
3
Pan itiporatlon
ca
0
-999.
-999.
O.OOOE+OO -999
EK> ARRAY
EBD SLASCB 1
EKD HYDGOLOGY DATA

-------
TABLE A-19. CONTENTS AND FORMAT OF THE CHEMICAL-SPECIFIC DATA GROUP
Card
Contents
Format
CI	"CHE"
A1-A3	Array Subgroup
E1-E5	Empirical Distribution Subgroup
C2	"END"
A3
(See Table A-5)
(See Table A-6)
A3
Definition of Contents
"CHE"
Array Subgroup
Empirical
Distribution
Subgroup
"END"
Group Specification Card indicating the start of the Chemi-
cal Data Group.
Subgroup defining the chemical variables.
Subgroup defining any empirical distributions.
End Card indicating the end of the Chemical Data Group.
Subgroup
Specification Code
Refer to Table
Control Data
CON
A- 21
Layer Thickness and
MAT
A- 22
Material Data


Unsaturated Material
SAT
A- 23
Property Data


Soil Moisture Data
SOI
A- 25
The first card of this group is the GROUP SPECIFICATION CARD and includes the
code VFL in the first three columns. The next card is the first subgroup
specification card. Data for each of these subgroups are described below.
The end of this group is indicated by an END CARD.
A.5.5.1 Unsaturated Zone Flow Control Data Subgroup-
Table A-21 describes the Unsaturated Zone Flow Control Data Subgroup
parameters. Data in the other subgroups vary depending on the options
specified in the Control Data Subgroup. The termination of this subgroup is
indicated by the END CARD.
180

-------
fABLE A-20. VARIABLES IN THE CHEMICAL ARRAY SUBGROUP
CHEMICAL SPECIFIC VARIABLE DATA
ABRAY VALUES
CHEMICAL SPECIFIC VARIABLES
VARIABLE HAKE	CHITS	DISTRIBUTION PAR*
MEAB
1 Solid pbut decay coaf f
1/yr
-I
-999.
2 Diss pbasa dacay eoaff
1/yr
-1
-999.
3 OrtrtU chan dcy coaff
1/yr
-1
-999.
4 Acid cataly hydro I rta
1/H-yr
0
-999.
5 Itatrtl hydro1 rata ecus
i/yr
0
-999.
6 B«m citily tajdrol rta
L/H-yr
0
-999.
7 Bafract U^iratart
C
0
-999.
B lomil 1 Ttd distrib coaff
¦1/B
0
-999.
9 Distribution coefficient

-2
-999.
10 Biodagrad cotf(s«t cod*)
1/yr
0
-999.
11 Air diffusion coaff
ea*/a
0
-999.
12 Rot t«p Cox sir diffusion
C
0
-999.
13 NoIkuIat N»i|bt
ft/aola
0
-999.
14 Holt fraction of solata

0
-999.
IS Solnto vapor prassora
— H*
0
-999.
16 Baftry'i lsw coos
ata^i*3/M
0
-999.
17 Bot in osa

0
-999.
10 lot in osa

0
-999.
19 Bot in ssa

0
-999.
ED
EXD CHEMICAL SPECIFIC VARIABLE DATA
IRS	UMTS
STD DEV mi	MX
-999.
O.OOOE+OO
0.100E+U
-999.
O.OOOE+OO
0.100E+11
-999.
O.OOOE+OO
0.100E+11
-999.
O.OOOE+OO
-999.
-999.
O.OOOE+OO
•999.
-999.
O.OOOE+OO
-999.
-999.
O.OOOE+OO
100.
-999.
O.OOOE+OO
-999.
-999.
O.OOOE+OO
C.100E+11
-999.
0.000E+00
-999.
-999.
O.OOOE+OO
10.0
-999.
0.000E+00
100.
-999.
O.OOOE+OO
-999.
-999.
0.100E-08
1.00
-999.
O.OOOE+OO
100.
-999.
0.100E-09
1.00
-999.
O.OOOE+OO
1.00
-999.
O.OOOE+OO
1.00
-999.
O.OOOE+OO
1.00

-------
TABLE A-21. CONTENTS AND'FORMAT OF THE UNSATURATED ZONE FLOW MODULE CONTROL
DATA GROUP
Card
Contents
Format
VI
C02
C03
C04
"VFL"
"CON"
VFCP(I), I - 1,
"END"
A3
A3
5110
A3
Definition of Contents
"VFL"
CON
VFCP(l)
VFCP(2)
VFCP(3)
VFCP(4)
VFCP(5)
Group Specification Card Indicating the start of the
Unsaturated Zone Flow Module Data Group.
Subgroup Specification Card Indicating the start of the
Unsaturated Zone Flow Module Control Data Subgroup.
Number of nodes In the Unsaturated Zone Flow Module. The
value of this parameter is currently generated in the code.
Thus, the value in the input file is ignored.
Number of different porous materials up to a maximum of 20.
If the depth of the unsaturated zone is randomly generated
in Monte Carlo mode, VFCP(2) must equal 1.
Parameter Indicating the type of relationship of relative
permeability versus saturation,
van Genuchten functional parameters
Brooks and Corey functional parameter
Parameter indicating the method of generating vertical
discretization when the depth of the unsaturated zone is
constant. This parameter Is Ignored in the current version
of the code.
Number of layers in the unsaturated flow system (up to a
maximum of 20). If the depth of the unsaturated zone is
randomly generated In Monte Carlo mode, VFCP(S) must equal
1.)
-END"
End Card indicating the end of this subgroup.
182

-------
Note chat in Monte Carlo mode, the total depth of the unsaturated zone can be
randomly generated by setting VFCP(2) and VFCP(5) to a value of one. VTCP(l)
In Table A-27 must also be set to a value of one. In other words, only one
homogeneous layer can have a Monte Carlo distribution associated with it.
A.5.5.2 Unsaturated Flow Module Layer Thickness and Material Data Subgroup--
Table A-22 describes the layer thickness and material data necessary for the
Unsaturated Zone Flow Module. The data consist of the layer thickness and the
material number associated with each layer. When only one layer Is simulated,
the layer thickness is equal to the total depth of the unsaturated zone and
this parameter can have a Monte Carlo distribution assigned to it. The
material numbers correspond to the material properties which are read in using
the Material Properties Subgroup described in Section A.5.5.3.
A.5.5.3 Unsaturated Zone Flow Material Property Subgroup--
The unsaturated zone can consist of a number of different materials (the
number specified by the value of VFCP(2) in Table A-21) with different
hydrogeological properties. The properties for each of the materials are
input using the Array and Empirical Subgroups in the Unsaturated Zone Material
Property Subgroup, which is Identified by the code SAT. Details of the
contents and format of this subgroup are shown in Table A-23. The variables
Included in this subgroup are shown in Table A-24. Note that none of these
variables can be derived (i.e., none have a distribution type of -1).
When the unsaturated zone consists of more than one material, information
about each material is input using an Array Subgroup. These materials are
subsequently identified by the order in which the Array Subgroups appear.
Thus, the fourth Array Subgroup (after the Subgroup Specification Card)
contains information about the properties of material number U. The termina-
tion of data for each mnterial is indicated by an END CARD. The end of the
unsaturated materials data is also indicated by an END CARD.
A.5.b.k Unsaturated Zone Flow Moisture Data Subgroup--
In order to solve the unsaturated zone flow problem, both the relationship
between the relative permeability and water concent and the relationship
between pressure head and water content need to be specified for each material
(refer to Section 3 of Salhotra et al. (1990)). The information needed to
Uescrlbe these relationships is provided in the Unsaturated Zone Moisture Data
Subgroup, identified by the code SOI. The contents and format of this
subgroup are described in Table A-25.
The van Cenuchten parameters, alpha and beta, are required by the code to
calculate the pressure head versus water content curve. The same parameters
can be used Co describe Che relationship between relacive permeability and
water content by setting VFCP(3) equal to one In Table A-21. However, the
code contains the option of using the Brooks and Corey relationship instead
(VKCP(3) equal to 2 in Table A-21). If the Brooks and Corey option is select-
ed, the exponent, n, muse be specified in addiclon co che van Genuchcen
parameters.
The subgroup specification card is followed by VFCP(2) number of the Array
Subgroups, one subgroup for each material. Table A-26 presents the definl
183

-------
TABLE A-22. CONTENTS AND FORMAT OF THE UNSATURATED FLOW NODULE LAYER THICKNESS
AND MATERIAL DATA SUBCROUP
Card	Contents	Format
Ml	"MAT"	A3
M2	VFLAYR(I), IPROP(I)	GIO.O, 110
M3	"END"	A3
Note: Card/line M2 is repeated for each layer in the	Unsaturated Flow Module
(VFCP(5) in Table A-21).
Definition of Contents
"MAT"
VFLAYR(I)
IPROP(I)
Subgroup Specification Card Indicating the start of the
Unsaturated Flow Module Layer Thickness and Material Sub-
group .
Thickness of layer I.
Material number for layer I corresponding to data read as
part of the Material Data Subgroup (see Section A.5.5.3).
•END"
End Card indicating the end of this subgroup.
184

-------
TABLE A-23. CONTENTS AND FORMAT OF THE UNSATURATED ZONE FLOW MODULE MATERIAL
PROPERTY SUBGROUP
Card
Contents
Format
SA1	"SAT"
A1-A3	Array Subgroup
E1-E5	Empirical Distribution Subgroup
SA2	"END" (Material)
SA3	"END"
A3
(See Table A-5)
(See Table A-6)
A3
A3
Note: Cards/lines A1-A3 and E1-E5 need Co be repeated for each material.
Definition of Contents
" SAT"
Array Subgroup
Empirical
Distribution
Subgroup
"END"
Group Specification Card Indicating the start of the Unsatu-
rated Zone Flow Module Material Subgroup.
Subgroup defining the material property variables.
Subgroup defining any empirical distributions.
End Card Indicating the end of data for a material (one such
end card Is required for each material).
"END"
End Card Indicating the end of this subgroup.
tlons of the variables Included In the Array Subgroup. None of the variables
in this group can be derived (i.e., none have a distribution type of -1).
Note that the data for each material are read in the same sequence as in Table
A-23. After the data for each material has been input, an END card is
inserted. Finally, the end of the subgroup Is also indicated by an END CARD.
185

-------
TABLE A-24. VARIABLES IN THE UNSATURATED FLOW MATERIAL PROPERTY ARRAY SUBGROUP
SATURATED MATERIAL PROPERTY PARAMETERS
ARRAY VALUES
SATURATED MATERIAL VARIABLES
• ••
• ••
•*•*****•«***•<
VARIABLE RAKE
UNITS
DISTRIBUTION PARAMETERS
MEAN	STD DEV
LIMITS
MIH	MAX
1	Sat bydxculic conduct
2	UosatoriUd coo« porosity
3	Air entry pr#s«ur« h«*d
* Depth of tb« unsat ran*
EZD ARRAY
ciB/hr
0	-999. -999.
-999. -999. O.IOOE-06 0.990-
0	-999. -999.
-999.
-999.
0.100E-10 0.100E+03
O.OOOE+OO -999.
O.IOOE-08 -999.
E*D MATERIAL 1
EKD

-------
TABLE A-25. CONTENTS AND FORMAT OF THE UNSATURATED ZONE FLOW MODULE MOISTURE
DATA SUBGROUP
Card	Contents	Format
511	"SOI"	A3
A1-A3	Array Subgroup	(See Table A-5)
512	"END" (material)	A3
513	"END"	A3
Note: Card/line A1-A3 need to be repeated for each material.
Definition of Contents
"SOI"	Group Specification Card indicating the start of the Unsatu-
rated Zone Flow Module Moisture Data Subgroup.
Array Subgroup Subgroup defining the molature-related variables.
"END"	End Card indicating the end of dAta for a material (one such
end card is required for each material).
"END"	End Card indicating the end of this subgroup.
A.5.6 Unsaturated Zone Transport Data Croup
The data required for the Unsaturated Zone Transport Module aro divided into
two subgroups. Each subgroup is handled in the same manner as was described
for the subgroups of the Unsaturated Zone Flow Data Group. The subgroups
included in the Unsaturated Zone Transport Data Group are:
Subgroup	Specification Code	Refer to Table
Control Data	CON	A-27
Transport Properties	TRA	A-28
Tho first card of this group is the GROUP SPECIFICATION CARD and includes the
code VTL in the first three columns. The next card is the first SUBGROUP
SPECIFICATION CARD. The contents and format of each of these subgroups are
described below. The termination of the Unsaturated Zone Data Croup is
Indicated by an END CARD.
A. 5.6.1 Unsaturated Zone Transport Control Data Subgroup--
The contents and format of the Control Data Subgroup are shown in Table A-27.
The Control Data Subgroup should be the first subgroup included in the Unsatu-
rated Zone Transport Group. Note that VTCP(l), the number of layers, in set
187

-------
TABLE A-26. VARIABLES IN THE UNSATURATED FLOW MOISTURE DATA ARRAY SUBGROUP
SOIL MOISTURE PABAICTERS
fotctiobal cuuncinrre
AKRAT values
nnCTIORAL COOTICIE VARIABLES
VARIABLE MIC	UNITS	DISTRIBUTION FARMCTZRS	LIMITS
VCAM	STD OCV HIi	MAX
1
IttldMl
««ur coo tacit
0
-m.
•W.
0.100E-08
1.00
2
Brooks m
ad Coray axpooaot. CI
0
•w.
-999.
O.OOOE+OO
10.0
3
ALFA van
Gaouchtao coafficiant
0
-999.
-999.
0.OOOE+CO
1.00
4
BETA Van
Caottchtan coafflclant
0
-9M.
-999.
1.00
5.00
ZMD ARRAY
en material i
E»
EK> UNSATURATED FI0W

-------
equal to 1 If the depth of the unsaturated zone is generated from a Monte
Carlo distribution in the Unsaturated Zone Flow Module. The end of this
subgroup data is indicated by an END CARD.
A.5.6.2 Unsaturated Zone.Transport Properties Subgroup--
The contents and format of the Transport Properties subgroup are described in
Table A-28. Following the SUBGROUP SPECIFICATION CARD is one or more Array
Subgroup that contains the values of the unsaturated zone transport variables.
An Array Subgroup is required for each material layer. If anv of the
variables are specified to have an empirical distribution, then it is
necessary to include the Empirical Distribution Subgroup (for details see
Section A.4.5). An END CARD is used to indicate the end of data for each
layer.
The multiple layers option is available only when the depth of the unsaturated
zone is constant (i.e., not a Monte Carlo variable) in the Unsaturated Zone
Flow Module. In the event that there is more than one transport layer, the
sum of the Individual layer thicknesses must equal the sum of the layer
thicknesses specified in the Unsaturated Zone Flow Module. However, note that
the number of layers and the corresponding thicknesses can differ between the
two modules.
The definitions of the specific variables that comprise this subgroup are
shown in Table A-29. Of the five variables shown, only the longitudinal
dlspersivity of the soil can be derived. The method by which it is derived is
discussed in Section 4.4:3.1 of Salhotra et al. (1990). An END CARD Indicates
the end of the Transport Data Subgroup.
A.5.7 Aaulfer Data Group
The contents and format of the Aquifer Data Group are shown In Table A-30.
The first card is the GROUP. SPECIFICATION CARD, with the code AQU Included in
the first three columns. Following this is an Array Subgroup, which contains
information about the values and/or distributions of up to 18 aquifer-specific
variables. The variables included In this subgroup are shown in Table A-31.
Ulth the exception of the source thickness, the variables are used only in the
Saturated Zone Transport Module. The source thickness is used to satisfy the
mass balance between the Unsaturated Zone (or the Source when the unsaturated
zone is not simulated) and the Saturated Zone Transport Modules.
Ten of the aquifer variables can be either derived or directly Input. These
variables are the particle diameter, porosity, bulk density, source thickness,
hydraulic conductivity, seepage velocity, retardation coefficient, and the
longitudinal, lateral, and vertical disperslvities. The available options and
the algorithms for each of them are explained in Section 5.5.3 of Salhotra et
al. (1990).
If any of the variables in this group are assigned an empirical distribution
(NDSTPRM(I) - 6), then it Is necessary to include the Empirical Distribution
Subgroup (see Section A.k. 5). END CARDS are required to indicate the
termination of both the Array and the Empirical Subgroups. A final END CARD
Indicates the end of the Aquifer Data Croup.
189

-------
TABLE A-27. CONTENTS AND FORMAT OF THE UNSATURATED ZONE TRANSPORT MODULE
CONTROL DATA SUBGROUP
Card	Contents	Format
VI	"VTL"	A3
TCI	"CON"	A3
TC2	VTCP(I), I - 1,10	10110
TC3	WTFUN	F10.0
1CU	"END"	A3
Definition of Contents
"VTL"	Group specification card Indicating the start of the Unsaturated
Zone Transport Group.
"CON"	Control card Indicating the start of the Unsaturated Transport
Control Subgroup.
VTCP(l) Number of layers used to simulate transport In the unsaturated
zone (up to a maximum of 20). Note that the number of layers
specified in the Unsaturated Zone Transport Module can be
different from the number of layers specified In the Unsaturated
Flow Module. VTCP(l) must be set equal to one if the depth of the
unsaturated zone in the Unsaturated Flow Module is to be randomly
generated in Monte Carlo mode.
VTCP(2) Number of time values at which concentration in the unsaturated
zone is to be evaluated. This variable, which corresponds to the
number of control points In the convolution integral for coupling
the unsaturated and saturated zones, is not used when the model is
run In steady-state. In the current version of the preprocessor,
this value is set to 20.
VTCP(3) Dummy integer. Not used in the current version of the model.
VTCP(4) Type of scheme used to evaluate transport In the unsaturated zone.
Note that the Stehfest algorithm is recommended when the ratio of
layer thickness to longitudinal dlsperslvity Is less than 20.
1	Stehfest numerical inversion algorithm
2	Convolution Integral approach
(continued)
190

-------
TABLE A-27. CONTENTS AND FORMAT OF THE UNSATURATED ZONE TRANSPORT MODULE
CONTROL DATA SUBGROUP (concluded)
Definition of Concents
P(5)
VTCP(6)
VTCP(7)
VTCP(8)
VTCP(9)
VTCP(IO)
WTFUN
For VTCP(4) - 1, the number of terms governing the accuracy of the
Stehfest algorithm. It must be a positive even integer. A value
of 18 is suggested as an initial trial value.
For VTCP(A) - 2, the number of Increments used in the temporal
discretization of convolution integral approach (a value of 10 is
recommended).
Number of points in the Lagrangian scheme used for Interpolating
concentration values (a value of 3 is recommended).
Number of Gauss points used in Gauss-Legendre numerical integra-
tion of the convolution values (a value of 104 is recommended).
Number of segments for the numerical approximation of the convolu-
tion integral (a value of 2 is recommended).
Type of source boundary condition. In the current version of the
code, the value of this parameter is automatically set in subrou-
tine DEFAULTS.FOR, based on the values of other input parameters.
Parameter indicating if time values for computing concentration in
the unsaturated zone are to be generated. This variable is not
used when the model is run in steady-state. It is automatically
set to 1 (i.e., yes), the recommended value, in the current
version of the preprocessor.
Value of weighting factor used to generate time step values for
evaluating concentration in the unsaturated zone. This variable,
which is not used when the model is run in steady-state, is
automatically set to 1.2 in the current version of the
preprocessor.
"END"
End Card indicating the end of this data subgroup.
191

-------
TABLE A-28. CONTENTS AND FORMAT OF THE UNSATURATED ZONE TRANSPORT MODULE
PROPERTIES SUBGROUP
Card	Contents	Format
T1	"TRA"	A3
A1-A3	Array Subgroup	(See Table A-5)
E1-E5	Empirical Distribution Subgroup	(See Table A-6)
T2	"END" (Layer)	A3
SA3	"END"	A3
Note: Cards/lines A1-A3 and E1-E5 need to be repeated for each layer.
Definition of Contents
"TRA"
Array Subgroup
Empirical
Distribution
Subgroup
" END"
Group Specification Card Indicating the start of the Unsatu-
rated Zone Transport Module Data Subgroup.
Subgroup defining the transport variables.
Subgroup defining any empirical distributions.
End Card indicating the end of data for a layer (one such
end card is required for each layer).
"END"
End Card indicating the end of this subgroup.
A.5.8 Surface Water Data Group
The contents and format of the Surface Water Data Group are shown in Table A-
32. The first card is the GROUP SPECIFICATION CARD with the code SUR in the
first three columns. This is followed an Array Subgroup that contains
information about the values/distributions of 13 variables, two of which are
not used In the current version of the model (see Table A-33). If any of
these variables are specified to have an empirical distribution, then it is
necessary to include the Empirical Distribution Subgroup. When running the
Surface Water Module, the user must chose an exposure route. Figure A.k shows
the three options available. The choice is specified in the General Data
Group. The end of the group is indicated by an END CARD.
192

-------
ROUTE-1
ROUTE-2
ROUTE-3
EXPOSURE TO AQUATIC
ORGANISMS
HUMAN EXPOSURE THROUGH
DRINKING WATER
HUMAN EXPOSURE THROUGH
FISH CONSUMPTION
EXPOSURE
ROUTE
Figure A.4 Kay options available in the surface water module
(from Salhotra and Mineart# 1966).
193

-------
TABLE A-29. VARIABLES IN THE UNSATURATED TRANSPORT PROPERTIES ARRAY SUBGROUP
TBABSH33T htfUKHQ
AWPAV VALUES
UHSATTIRATED TRAKSPCXR VARIABLES
VARIABLE OAKZ	UHITS	DISTRIBUTION PARAMETERS	LIMITS
MEAH	STL DEV MIS	MAX
I iefmrvftn |qyqy
m
0
-999.
9. 0.100E-06
-999.
2 LaQ^it dlopor of layor
D
-1
-999.
9. O.OOOE+OO
0.100E+OS
9 Porccst oracaic eatto*

0
-999.
9. O.OOOE+OO
100.
4 BnlTr tfirntt e£ soil loyor
g/cc
0
-999.
9. 0.100E-01
3.00
3 Biological docay cootX
1/yr
0
-999.
9. O.OOOE+OO
-999.
rrn AwwflY
F1TI TA7TO 2
rrn (ESAHQASD TRADSRZ3T PflHflKZIERS
ECD	ttnnm.

-------
TABLE A-30. CONTENTS AND FORMAT OF THE AQUIFER-SPECIFIC DATA CROUP
Card	Contents	Format
Q1	"AQU"	A3
A1-A3	Array Subgroup	(See Table A-5)
E1-E5	Empirical Distribution Subgroup	(See Table A-6)
Q2	"END"	A3
Definition of Contents
Group Specification Card indicating the start of the Aquifer
Data Group.
Subgroup defining the aquifer variables.
Subgroup defining any empirical distributions.
End Card indicating the end of this data group.
"AQU"
Array Subgroup
Empirical
Distribution
Subgroup
"END"
A.5.9 Air Emissions and Dispersion Data Group
The Air Emissions and Dispersion Data Group may consist of up to three
subgroups. The Array and Empirical Subgroups are used to specify values and
distributions for air emissions and dispersion model variables. The third
subgroup, the Air Dispersion Module Control Subgroup discussed in Section
A.5.9.1, defines control options when the air dispersion model is used.
The first card of this group is the GROUP SPECIFICATION CARD and Includes the
code AIR in the first three columns. The next set of cards, shown in Table A-
34, includes an Array Subgroup that contains Information about the values -
/distributions of up to 18 variables (shown in Table A-35). Note that If any
of these variables are specified to have an empirical distribution, then it is
necessary to Include the empirical subgroup.
195

-------
TABLE A-31. VARIABLES IN THE AQUIFER DATA ARRAY SUBGROUP
AQUIFER SPECIFIC VARIABLE DAXA
ARRAY VALUES
AQUIFER SPECIFIC VARIABLES
VARIABLE HAKE	UHITS	DISTRIBUTION PARAMETERS	LIMITS
MEAN	STD DEV Mil	MAX
1 PtrtlcU dlaNUr
ca
0
-999.
-999.
0.100E-08
»****«••**#
100.
2 Aquifer porosity

-2
-999.
-999.
0.100E-08
0.990
3 Bulk density
g/cc
-1
-999.
-999.
0.100E-0I
5.00
A Aquifer thicknns
B
0
-999.
-999.
0.100E-08
0.100E+06
3 Mixing sone depth
B
-1
-999.
-999.
0.100E-08
0.IOOE+06
6 Hydraulic conductivity
n/yr
-2
-999.
-999.
0.100E-06
0.100E+09
7 Hydraulic Gradient

0
-999.
-999.
0.100E-07
-999.
6 Grndvater seep velocity
n/yr
-2
-999.
-999.
0.100E-09
0.100E+09
9 Retardation coefficient

-1
-999.
-999.
1.00
0.100E+O9
10 Longifrwdinsl dispersivity
a
0
-999.
-999.
0.100E-02
0.100E+05
11 Transverse dispersivity
B
0
-999.
-999.
0.100E-02
O.IOOE+OS
12 Vertical dispersivity
B
0
-999.
-999.
0.100E-02
0.100E+05
13 Tenperatore of aquifer
c
0
-999.
-999.
O.OOOE+OO
100.
14 pfl

0
-999.
-999.
0.300
14.0
15 Organic carbon content
fract
0
-999.
-999.
0.100E-05
1.00
16 Receptor distance fzos site
ra
0
-999.
-999.
1.00
-999.
17 Angle off center
degree
0
-999.
-999.
O.OOOE+OO
360.
18 Well vertical distance
B
0
-999.
-999.
O.OOOE+OO
-999.
Ok	EHD ABPAY
EXD AQUIFER SPECIFIC VARIABLE *****

-------
TABLE A-32. CONTENTS AND FORMAT OF THE SURFACE WATER DATA GROUP
Card
Contents
Format
SU1	"SUR"
A1-A3	Array Subgroup
E1-E5	' Empirical Distribution Subgroup
SU2	"END"
A3
(See Table A-5)
(See Table A-6)
A3
Definition of Contents
•SUR"
Array Subgroup
Empirical
Distribution
Subgroup
"END"
Group Specification Card indicating the start of the Surface
Water Data Group.
Subgroup defining the surface water variables.
Subgroup defining any empirical distributions.
End Card indicating the end of this data group.
A.5.9.1 Air Dispersion Module Control Data Subgroup--
The Control Data Subgroup Is identified by a SUBGROUP SPECIFICATION CARD with
the code CON In the first three columns. The contents and format of the
subgroup are shown in Table A-36. The subgroup is required only if the air
dispersion module is used. Note that the values for wind speed and the value
for FMAT are only read when IFREQ equals 1. The available options are shown
in Figure A.5.
If the frequency-weighting approach Is used to calculate long-term dispersion
(IFREQ - 1), frequency data are read from the file FREQ.IN. The file contains
joint frequencies for all combinations of wind speed, direction, and stabi-
lity. For the usual configuration of 16 wind direction sectors, 6 wind
speeds, and 6 stability classes 576 (i.e., 16 x 6 x 6) Joint frequency entries
are required. Typically this joint frequency distribution is available as
STAR (Stability Array Data) summaries for airports. The general structure of
the data is illustrated in Table A-37. Since users may have this matrix of
data in different formats, MULTIMED allows some flexibility in the format.
The formats for each line of data are specified by the variable FMAT on Card
AR5 (Table A-36). The end of this subgroup Is indicated by the END CARD. The
completion of the Air Emissions and Dispersion Data Group is indicated by the
END CARD.
197

-------
LAMOFU. AMD EST MATE
ATMosneneasPERsoN
vO
00
TERRAIN
COHHECTCN
STABU1Y OCPENOENT
NOT STABUIY DEPENDENT
VERTtCAL
OSPERSION
CALCULATION
PASOUtl-CffTORO
xcnco
TURBULENCE
NTENSfTYMElHOO
METEOROLOGY
CONSTANT WIND
ANO STAOMTY CONOTTIOH
RESULTS WEIGHTED BY JONT
FREQUENCIES OF WWD
ANO STABILITY
Figure A.5 Key options available in the air modules (from Salhotra and
Hineart, 1980).

-------
TABLE A-33. VARIABLES IN THE SURFACE WATER DATA ARRAY SUBGROUP
SURFACE WATER MOOULE VARIABLE DATA
ARRAY VALUES
••• SURFACE HATER MODULE VARIABLES
VARIABLE SAME	UBITS DISTRIBUTION	PARAMETERS	LIMITS
MEAB	STD DEV M3N	MAX
1	Chwmtl slope	(a/a)	0
2	Strata depth	Cm)	0
3	unuaed at present	0
4	Mszmi._&s roughness
coefficient	0
5	Temperature of stream (C)	0
6	Sediment concentration
7	Strea pB	0
8	Frect organic carbon in iwfat	0
9	Wind speed at elev x (o/s)	0
10	Elev of wind apeed aeasure
11	Fract of fish «*<'¦*' is lipid	0
12	unuaed at present	0
13	Streaa flow	V3/a >	0
EHD ARRAY
-999.
-999.
-999.
-999.
-999.
-999.
-999. -999.
-999. -999.
(nft/D
-999.
-999.
-999.
(a)
-999.
-999.
-999.
-999.
-999.
-999.
-999.
-999.
-999.
0.100E-08 -999.
0.300E-01 -999.
0.OOOE+OO 0.OOOE+OO
0.100E-08
0.COOE+OO
0
0.300
0.100E-06
0.OOOE+OO
0
0.100E-00
1.00
100.
14.0
1.00
200.
1.00
0.OOOE+OO 0.OOOE+OO
0.100E-08 -999.
-999.
-999.
0.100E-08 -999.
0.100E-06 -999.
EXD SURFACE HATES NOODLE VARIABLE DATA

-------
TABLE A-34. CONTENTS AND FORMAT OF THE AIR EMISSION AND DISPERSION DATA GROUP
Card
Contents
Format
AIR
-AIR-
A3
AR2-AR6
Air Dispersion Control Subgroup
(See Table A-36)
A1-A3
Array Subgroup
(See Table A-5)
E1-E5
Empirical Distribution Subgroup
(See Table A-6)
AR7
"END"
A3
Definition of Contents
"AIR"
Array Subgroup
Empirical
Distribution
Subgroup
Group Specification Card indicating the start of the Air
Emission and Dispersion Data Group.
Subgroup defining the air variables.
Subgroup defining any empirical distributions.
¦END"
End Card indicating the end of this daca group.
200

-------
TABLE A-35. VARIABLES IH THE AIR EMISSION AND DISPERSION DATA ARRAY
AIR mou variable data
array values
AQUIFEB SPECIFIC VARIABLES
VARIABLE MIC	UHITS	DISTRIBUTION PARAMETERS	LIMITS
MEAH	STD DEV MM	MAX
1
of soil corn
CD
0
-999.
-999.
O.OOOE+OO
O.OOOE+OO
a

r of waU dlsp nit
C
0
-999.
-999.
O.OOOE+OO
O.OOOE+OO
3
Forotity of nit

0
-999.
-999.
O.OOOE+OO
O.OOOE+OO
4
Him
rnnt ant

0
-999.
-999.
O.OOOE+OO
O.OOOE+OO
S
Gmm
factor

0
-999.
-999.
O.OOOE+OO
O.OOOE+OO
t
Ma «]


0
-999.
-999.
0.000E+00
O.OOOE+OO
7
Sl«M
apaDMt

0
-999.
-999.
O.OOOE+OO
O.OOOE+OO
a
AtBBO
pan cometlso factor

0
-999.
-999.
O.OOOE+OO
O.OOOE+OO
9
Bvldul «h«f —n» faetor

0
-999.
-999.
0.000E+00
O.OOOE+OO
10
S mfs
htlgM ef ciM
¦
0
-999.
-999.
O.OOOE+OO
O.OOOE+OO
11
Dmt
cooff 1b tlx

0
-999.
-999.
O.OOOE+OO
O.OOOE+OO
12
BiHjil
tar diet txm landfill
¦
0
-999.
-999.
0.000E+00
O.OOOE+OO
13
Rocapl
tor a|l fa URizct
rad
0
-999.
-999.
O.OOOE+OO
O.OOOE+OO
14
ELml
LIan of roeoptor
¦
0
-999.
-999.
O.OOOE+OO
O.OOOE+OO
15

I hal|ht
¦
0
-999.
-999.
O.OOOE+OO
O.OOOE+OO
14
Std div of wind •lav an
rad
0
-999.
-999.
O.OOOE+OO
O.OOOE+OO
17
Coast*
Bt wind ipMd
a/a
0
-999.
-999.
O.OOOE+OO
O.OOOE+OO
U
Const*
Bt stability condition

0
-999.
-999.
O.OOOE+OO
O.OOOE+OO
EH)
EH> AQUIFER &H10FIC VARIABLE DATA
EX)
ESD AIR —*1F VARIABLE p*ta

-------
TABLE A-36. CONTENTS AND FORMAT OF THE AIR DISPERSION CONTROL DATA SUBGROUP
Card	Contents	Format
AR2	"CON"	A3
AR3	ISTBL, ISIGZ.'IFREQ	315
AR4	(U(I), I - 1,6)	6F10.0
AR5	FMAT	A80
AR6	"END"	A3
Definition of Contents
"CON"	Control card Indication start of the Air Dispersion Control
Subgroup (required only if air dispersion Is simulated).
ISTBL	Flag Indication If terrain correction is stability
dependent.
0	Stability-Independent terrain correction
1	Stability-dependent terrain correction
ISICZ	Flag for vertical dispersion coefficient method.
0	The Pasqulll-Gifford method
1	The turbulence-intensity method
IFREQ	Flag indicating mode for calculation of oncentratlons.
0	Concentrations are calculated assuming a constant wind in
the direction of the receptor
1	Wind-stability frequency-weighting approach used
U(I)	Vlnd speeds for each wind speed class
(required only If IFREQ - 1).
FMAT	Format for the data in the file containing wind-stability
frequency data (required only if IFREQ - 1). The general
structure of this file is illustrated in Table A-37.
"END"	End Card indicating the end of this data subgroup.
202

-------
TABLE A-37. GENERAL STRUCTURE OF THE WIND-STABILITY FREQUENCY FILE (FREQ.IN)
Wind Direction SecCor
1
Frequencies
for
six wind speed classes,
sector 1,
stabl
ity
class
A.
2
Frequencies
for
six wind speed classes,
sector 2,
stabl
ity
class
A.
3
Frequencies
for
six wind speed classes,
sector 3,
stabi
ity
class
A.
U
Frequencies
for
six wind speed classes,
sector 4,
stabl
ity
class
A.
5
Frequencies
for
six wind speed classes,
sector 5,
stabl
ity
class
A.
6
Frequencies
for
six wind speed classes,
sector 6,
stabi
ity
class
A.
7
Frequencies
for
six wind speed classes,
sector 7,
stabl
ity
class
A.
8
Frequencies
for
six wind speed classes,
sector 8,
stabi
ity
class
A.
9
Frequencies
for
six wind speed classes,
sector 9,
stabl
ity
class
A.
10
Frequencies
for
six wind speed classes,
sector 10,
stabi
ity
class
A.
11
Frequencies
for
six wind speed classes.sector 11,
stabl
Ity
class
A.
12
Frequencies
for
six wind speed classes,sector 12,
stabl
ity
class
A.
203

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APPENDIX B
SUBROUTINES INCLUDED IN KULTIHED
Subroutine Called Bv
Input/Output Routines
ADISRD	BATIN
AIRIN
BATIN
CHKEND
COMRD
FRQPLT
FRQTAB
ICHECK
LEFTJT
MODCHK
OPENF
OUTFOR
MAIN
MAIN
BATIN, READLF
ADISRD, AIRIN
OUTFOR
OUTFOR
READZ, READ3
PRTINP, BATIN
MAIN
MAU
MAIN
Subroutine Cflllcfl By
PRINTO	MAIN, PRTOUT,
Description
Reads Input data necessary to run the
Air Emissions Module and the Air
Dispersion Module.
Interactive preprocessor for Air
Dispersion Module.
The batch-run Input processor that reads
from a user-specified file the values of
variables and parameters updated from
their default values.
Checks for the end of a data group.
Searches for data lines In Input file.
Separates connects from data Input
data file.
Prints a CDF and/or PDF to output file.
Prints a table of statistics to the
output file.
Separates data for connections In input
BATIN, READLFdata file.
Left Justifies character variables.
Flags which modules are to be run for
Monce Carlo simulations.
Opens files. Checks to see if they
exist.
Outputs single statistics, frequency
distribution tables, CDF tables, and
printer plots.
Description
Outputs the distribution type, mean,
PRNTVZstandard deviation, and maximum and
minimum allowed values for all the
variables which can be generated by
Monte Carlo routines.


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PRNEMP	PRTOUT, PRNTVZ
PRNTIN	PRTINP, PRTOUT
PRNTVZ	PRTINP
PRTINP	MAIN
PRTOUT	MAIN
READ2	BATIN, ADISRD,
READ3	BATIN, ADISRD,
READLF	BATIN
SOPEN	MAIN
Saturated Zone Module
DBK1	STEADY
C0NV02	GWCALC
CPCAL	C0NV02
Prints empirical distributions to output
file.
Writes out General Data Group to the
output file.
Outputs model parameters for the
Unsaturated Zone Flow and Transport
Modules to the computer-generated batch
input file.
Outputs model parameters to the
computer-generated batch input file.
Outputs Monte Carlo information to
output file.
Reads in array values as part of the
READLFbatch input preprocessor.
Reads in empirical distributions as part
READLFas the batch input preprocessor.
Reads in Landfill Source Data.
Open output files containing Monte
Carlo output. These are the *.VAR and
*.OUT files.
Calculates the modified Bessel function.
Couples Unsaturated Zone and Saturated
Zone Modules using the convolution
approach.
Evaluates saturated zone concentrations
at time 'T minus tau' for the
convolution integral approach.
205

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ERFC
TRANSP
Computes the complementary error
function.
Subroutine Called Bv
FUNCTl	GW2DFT, QROMB,
GWCALC	MAIN
GU2DFS	GWCALC, GU3DPS
GW2DFT	GWCALC, CPCAL,
GW3DPS	GWCALC
CW3DPT	GWCALC, CPCAL
PATCH	MAIN
QROMB	GW2DFT
STEADY	PATCH
Description
Evaluates the Integrand in the
TRAPZDanalytlcal solution.
Main calling routine for saturated zone
model. Sudlcky's analytical solution
for three-dimensional mass transport
problem with a gaussIan-distributed
source.
Analytic solution to the saturated
steady-state, two-dimensional, transport
model with a continuous gaussian source
using the Gauss-Legendre quadrature
integration scheme.
Analytic solution to the saturated,
GW3DPTunsteady-state, two-dimensional,
transport model with a continuous
gaussian source using the Gauss-Legendre
quadrature integration scheme.
Evaluates saturated, steady-state,
three-dimensional transport from a
continuous gaussian source. Allows for
the effects of partial penetration.
Evaluates saturated, unsteady-state,
three-dimensional transport from a
continuous gaussian source. Allows for
partial penetration effects.
Solves for transport in the saturated
zone assuming a patch source.
Preforms integration using Romberg's
method of order 2K (e.g., K - 2 is
Simpson's rule).
Steady-state solution for contaminant
transport in the saturated zone when
using a patch source.
206

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TMGEN1
INITVT
Subroutine Called Bv
TMGEN2	INITVT
1MGEN3
TRANSP
TRAPZD
INITVT
PATCH
QROMB
Unsaturated Zone Transport Module
ADISPR	VTCALC
COEF
CONVOl
DERFC
VTCALC
VTCALC
EXPERF
DCAUSS	SOLBT, CW2DFS,
Legendre
EVAL
SOLBT
Evaluates tines used in convolution
Integral to couple the unsaturated zone
and saturated zone transport solutions
(for constant source).
P99CriPtl9H
Evaluates times used In the convolution
Integral to couple the unsaturated zone
and saturated zone transport solutions
(for pulse source).
Evaluates tines used In the convolution
Integral to couple the unsaturated zone
and saturated zone transport solutions
(for decaying source).
Transient solution for contaminant
transport In the saturated zone while
using a patch source.
Computes the nth stage of refinement of
an extended trapezoidal rule.
Computes concentrations based on the
steady-state, advectlve dispersive
equation with first order decay.
Generates coefficients of transformed
solution for each layer.
Evaluates layered unsaturated zone
transport solution by the convolution
method.
Computes complementary error function
with real arguments.
Computes the first N roots and weight
STEADY, TRANSPfactors for the Gauss-
quadrature integration scheme.
Evaluates functional values at Gauss
integration points.
207

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EXPD
EXPERF
FACTR
EXPERF
S0LAY1
LINV
Subroutine Called Bv
LAGRNG	SOLBT
LAYAVE	INITVT
LINV	INITVT
SOLAY1	VTCALC, SOLBT
SOLBT	VTCALC, CONVOl
STEHF	VTCALC
VTCALC	MAIN
Computes Che exponential function. Set
function to zero for agreements less
than -170.
Evaluates the product of an exponential
function and the complementary error
function with real arguments.
Function which calculates the factorial
of a number.
Description
Lagrangian interpolation scheme.
Evaluates average saturation and
porosity for each layer in the
Unsaturated Transport Module.
Evaluates coefficients for Stehfest
algorithm.
Analytical unsaturated transport
solution for the first layer.
Evaluates unsaturated zone
concentrations at the bottom of each
layer at specific time intervals.
Evaluates the inverse of the Laplace
transform for solute transport in
layered media.
The main calling routine for the
analytical solution of transport through
the unsaturated zone.
Unsaturated Zone Flow Module
FPSI1	RAPSON
Evaluates pressure head based upon
relationship between pressure head and
hydraulic conductivity and water
content.
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RAPSON
VFCALC
WCFUN
VFCALC
MAIN
VFCALC
Determines pressure head corresponding
Co specific flux using modified Newton-
Raphson iteration.
Main calling routine for the one-
dimensional Unsaturated Zone Flow Module.
Evaluates the water content-pressure
head relationship.
Air Emission and Dispersion Module
AIRDIS	MAIN
Computes the ground-level concentration
at receptors located downwind of the
landfill.
ARCALC
VIRT
MAIN
Subroutine Called Bv
SIGMAZ	AIRDIS
AIRDIS
Calculates the emission rates from the
waste disposal unit to the atmosphere.
Description
Computes vertical dispersion
coefficient.
Computes effective source area and
locates the virtual source.
Surface Water Module
CINTER	SUCALC
CMIX
DRINK
FISH
REOX
SWCALC
SUCALC
SUCALC
SUCALC
INITST
MAIN
Computes the fraction of the steady-
state continuous mass leaching out of
the waste disposal unit that enters
the stream.
Calculates the lnstream dilution due to
complete near-field mixing of the
groundwater plume.
Calculates the reduction in stream
contaminant concentration due to
sedimentation in a water treatment
plant.
Calculates the bloaccumulatlon of toxics
in fish.
Calculates the reaeratlon coefficient,
using either the Owens, 0'Conner-Dobbins
or Churchill formula, depending on the
stream depth and/or velocity.
Main calling routine for Surface Water
Module.
209

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Landfill Source Module
DISC
INITVF
Dlscretizes the landfill layers and
unsaturated zone layers Into a one
dimensional grid for computing pressure
head.
EVPT
LFCALC
LINER1
LFCALC
MAIN
INITLF
Computes actual evapotranspiratlon using
a limiting soil moisture calculation.
Main calling routine for the Landfill
Module.
Computes the effective permeability of a
landfill layer with a synthetic liner.
Subroutine Called Bv
PERC	LFCALC
RUNOFF
LFCALC
Initialization Routines
TRANS	SWCALC
INITAF
MAIN
INITCW
MAIN
INITLF
INITST
INITVF
MAIN
Description
Computes pressure head, water content,
and saturation distribution below a
lateral drain.
Computes runoff by SCS curve number
method modified to include the soil
moisture.
Calculates the contaminant concentration
in the stream at the location of the
drinking water treatment plant intake.
Assumes first order decay.
Assigns the input values or values
generated by the Monte Carlo routines
to the variable names used in the air
emissions and dispersion models. Also
calculates coefficients needed by the
models.
Assigns the input variables or values
generated by Monte Carlo routines to the
variable names used in the saturated
zone model. Calculates aquifer,
chemical, and source constants.
Assigns the input variables or values
generated by Monte Carlo routines to the
variable modes used in the Landfill Model.
Assigns the input values or values
generated by the Monte Carlo routines to
the variable names used in the Surface
Water Module. Also calculates
coefficients needed by the module.
210

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INITVF
MAIN
Assigns Che input variables or values
generated by the Monte Carlo routines to
the variable names used in the
Unsaturated Flow Module. The initial
conditions and coordinate system for the
Unsaturated Flow Module are defined here.
INITVT
MAIN
Subroutine Called Bv
Monte Carlo Routines
ANRMRN
NORMAL
LOGNOR
Assigns the Unsaturated Transport input
variables or values generated by Monte
Carlo routines to their variable names.
Assigns retardation and saturation to the
appropriate transport variables.
Description
Generates a (0,1) normally distributed
random number.
CALLS
COUNT
EMPCAL
UNCPRO
MAIN
CALLS
EXPRN
EXPRND
Calls the prescribed random number
generator for each parameter which Is
used In the Monte Carlo simulation.
Count the number of parameters which
are to be Monte Carloed.
Generates a random number from an
empirical distribution. EMPCAL
generates a uniform random number
between 0-1 and uses it to interpolate
for a value using the piecewlse linear
cumulative frequency distribution input
by the user.
Generates an exponentially distributed
random number with a mean of 1.
EXPRND
CALLS
Generates an exponentially distributed
random number with a specified mean.
211

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LOGNOR
CALLS
LOGIOU
NORMAL
PRMLIS
values
the user-
RANSET
TRANSB
Subroutine
TRNLOG
UNCPRO
UNFRN
UNIFRM
CALLS
CALLS
CHMOD, AQMOD,
MAIN
CALLS
Called Bv
CALLS
MAIN
ANRMRN, LOGIOU
CALLS, EMPCAL
Generates a lognormally distributed
random number with a specified mean and
standard deviation. The Input mean and
standard deviation are in arithmetic
space.
Generates uniformly distributed loglO
numbers between 0-1, then transforms
them to a range specified by the user.
Generates a (x,a)normally distributed
random number where x is the mean and a
is the standard deviation.
In the interactive mode, lists the
SOMOD, VTMOD,present, minimum, and maximum
VFMOD, ARMOD.and distribution values for
STMODspecifled variables.
Initializes the random number generator.
Transforms a number from SB space to normal
space or from normal space to SB space.
Description
Transforms the mean and standard
deviation in the arithmetic space (original
data) to mean and standard.deviation in
logarithmic (normal) space.
Generates random values for the model
parameters. It also writes to the
output file if any errors occur when
generating the random values.
Generates a (0,1) uniformly distributed
UNIFRM, EXPRNrandom number.
Cenerates a uniformly distributed random
number between a user-specifled minimum
and maximum.
Subroutines to Set Default Values and Interactive Routines
AQNAMS
ARNAMS
CHNAMS
MAIN
MAIN
MAIN
Sets Aquifer Data Group variable and label
names.
Sets Air Data Group variable and label
names.
Sets Chemical Data Group variable and label
names.
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Sees special default values co lock out
certain functions.
Sets Landfill Data Croup variable and label
names.
Sets Source Data Croup variable and label
names.
Sets Surface Water Data Group variable and
label names.
Sets Unsaturated Flow Data Group variable
and label names.
Sets Unsaturated Transport Data Group vari-
able and label names.
Used when reading batch files.
213

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