&EPA
United States
Environmental Protection
Agency
Roberts Kerr Environmental Research EPA-600/8-78-012
Laboratory june 1973
Ada OK 74820
/ //
slopment
Utilization
of Numerical
Groundwater Models
for Water Resource
Management
EJBD
ARCHIVE
EPA
600-
8-
78-
012
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RESEARCH REPORTING SERIES
Research reports of the Office of Research and Development, U.S. Environmental
Protection Agency, have been grouped into nine series. These nine broad cate-
gories were established to facilitate further development and application of en-
vironmental technology. Elimination of traditional grouping was consciously
planned to foster technology transfer and a maximum interface in related fields.
The nine series are:
1. Environmental Health Effects Research
2. Environmental Protection Technology
3. Ecological Research
4. Environmental Monitoring
5. Socioeconomic Environmental Studies
6. Scientific and Technical Assessment Reports (STAR)
7. Interagency Energy-Environment Research and Development
8. "Special" Reports
9. Miscellaneous Reports
This report has been assigned to the "SPECIAL" REPORTS series. This series is
reservecj for reports targeted to meet the technical information needs of specific
user groups. The series includes problem-oriented reports, research application
reports, and executive summary documents. Examples include state-of-the-art
analyses, technology assessments, design manuals, user manuals, and reports
on the results of major research and development efforts.
This document is available to the public through the National Technical Informa-
tion Service, Springfield, Virginia 22161.
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EPA-600/8-78-012
June 1978
UTILIZATION OF NUMERICAL GROUNDWATER MODELS
FOR WATER RESOURCE MANAGEMENT
by
Yehuda Bachmat
Barbara Andrews
David Holtz
Scott Sebastian
Holcomb Research Institute
Butler University
Indianapolis, Indiana 46208
Grant No. R-803713
Project Officer
Jack W. Keeley
Ground Water Research Branch
Robert S. Kerr Environmental Research Laboratory
Ada, Oklahoma 748020
ROBERT S. KERR ENVIRONMENTAL RESEARCH LABORAOTRY
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
ADA, OKLAHOMA 74820
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DISCLAIMER
This report has been reviewed by the Robert S. Kerr Environmental
Research Laboratory, U. S. Environmental Protection Agency, and approved
for publication. Approval does not signify that the contents necessarily
reflect the views and policies of the U. S. Environmental Protection Agency
nor does mention of trade names or cotmercial products constitute endorse-
ment or recommendation for use.
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FOREWORD
The Environmental Protection Agency was established to coordinate
administration of the major Federal programs designed to protect the
quality of our environment.
An iinportant part of the Agency's effort involves the search for
information about environmental problems, management techniques, and new
technologies through which optimum use of the Nation's land and water
resources can be assured and the threat pollution poses to the welfare
of the American people can be minimized.
EPA's Office of Research and Development conducts this search through
a nationwide network of research facilities.
As one of these facilities, the Robert S. Kerr Environmental Research
Laboratory is responsible for the management of programs to: (a) investi-
gate the nature, transport, fate, and management of pollutants in ground
water; (b) develop and demonstrate methods for treating wastewaters with
soil and other natural systems; (c) develop and demonstrate pollution con-
trol technologies for irrigation return flows; (d) develop and demonstrate
pollution control technologies for animal production wastes; (e) develop
and demonstrate technologies to prevent, control or abate pollution from
the petroleum refining and petrochemical industries; and (f) develop and
demonstrate technologies to manage pollution resulting from combinations
of industrial wastewaters or industriaVinunicipal wastewaters.
This report contributes to that knowledge which is essential in order
for EPA to establish and enforce pollution control standards which are
reasonable, cost effective, and provide adequate environmental protection
for the American public.
William C. Galegar
Director
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ABSTRACT
The objective of the SOCPE International Assessment Project on Ground-
water Model Modeling is an evaluation of the present status of numerical
models as a tool for groundwater-related water resource management. During
the course of the project, four major problem areas ware identified:
1. Accessibility of models to users. Top priority should be given to
making existing models more accessible to potential users as the most neces-
sary immediate improvement. Increasing the accessibility of models consists
not only in improving the quality of information about models and making
this information and the models more available, but also in improving the
training of those persons who use models.
2. Communications between managers and technical personnel. Measures
must be taken to improve the links between management and those who provide
technical services employing models. This will involve designing model out-
puts to be more responsive to management needs as well as more interactive
participation by managers and technical personnel in problem definition and
model applications.
3. Inadequacies of data. Solutions to problems of data will require
increased attention to the identification of those data critical to the
solution of groundwater management problems. Improved methods of data col-
lection, storage, and retrieval are needed.
4. Inadequacies in mo^*>iing. in certain areas models still do not
exist or are considered inadequate. The development or improvement of these
models should be encouraged; in many instances, however, models will have to
be preceded by improved scientific understanding of the fundamental pro-
cesses which the models are to describe.
Specific recommendations for action have been formulated in each of
these areas and are presented in the report.
This report was submitted in fulfillment of Grant No. R-803713 by the
Scientific Committee on Problems of the Environment (SOCPE) under the sponsor-
ship of the U.S. Environmental Protection Agency. This report covers a period
from June 1975 to September 1977. Work was completed as of September 30, 1977.
iv
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TABLE CF CONTENTS
Foreword iii
Abstract iv
Acknowledgments viii
CHAPTER 1 EXECUTIVE SOWAR* 1
CHAPTER 2 CONCLUSIONS AM) RECOMMENDATIONS 3
Accessibility 4
Cormunications 5
Data 7
Modeling 9
Concluding Remarks 11
CHAPTER 3 DESCRIPTION OF THE PROJECT 12
Statement of the Problem 12
Origins and Organization of the Project 13
Project Aim and Scope 14
Project Audience 15
Project Methodology 15
Survey of Groundwater Models 16
Survey of Needs Related to Models and Their
Use in Solving Groundwater Problems 16
Organization of the Report ,18
CHAPTER 4 MANAGEMENT AND MODELING 19
Groundwater-Related Problems 19
Supply 20
Contamination 21
Environmental Impact 21
Planning and Management Issues 22
Types of Management Decisions 23
Levels of Management Decisions 24
Management Levels and Modeling 27
Groups Involved in Modeling for Management 28
The Processes of Scientific Research, Model
Building, and Model Application 29
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CHAPTER 5 THE GROUNDWATER SYSTEM AND GROUNDWATER MODELS 35
Basic Characteristics of the Groundwater System 35
Man's Effect on the Groundwater System 40
Models Related to the Groundwater System 41
Prediction Models 42
Resource Management Models 43
Identification Models 43
Data Manipulation Codes 43
additional Comments 44
CHAPTER 6 OVERVIEW OF EXISTING MODELS 45
Introduction 45
Model Characteristics 47
General Garments 47
Prediction Models 49
Flow Models 50
Mass Transport Models 52
Heat Transport Models 54
Deformation Models 54
Other Prediction Models 55
Management Models 55
Groundwater Alone 56
Groundwater and Surface Water 56
Identification Models 57
Data Manipulation 59
Model Usability 59
Concluding Remarks 60
CHAPTER 7 GAPS IN MODEL APPLICATIONS TO MANAGEMENT NEEDS 63
Sources of Information 63
Categories of Gaps 64
Accessibility of Models to Users 64
Model Documentation 65
Model Distribution 66
Training of Model Users . 67
Communications between Managers and Technical Personnel . . 68
Model Credibility 69
Education of Managers 70
Problem Definition 71
Acceptability of Management Models 71
Models in the Political and Legal Context 71
Deficiencies in Data 72
Data Collection . 73
Parameter Identification Models 74
Data Manipulation 74
Data Storage 75
Simple versus Complex Models 75
vi
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CHAPTER 7 Deficiencies in Modeling 76
Improvements in Existing Models 76
Prediction Models 76
Stochastic versus Deterministic Models 78
General versus Specific Models 78
The Role of Analog and Hybrid Models 79
Institutions for Model Development 79
Basic Research and Model Development 80
Establishing Priorities 80
APPENDICES
Appendix A REVIEW OF SURVEYED NUMERICAL MODELS 82
Appendix B LIST OF MODELERS 143
vxi
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AC^OWLEDGEMENTS
Holccrnb Research Institute gratefully acknowledges the work of Dr.
Yehuda Bachmat, who served as project leader for this study while on leave
for a year from the Hydrological Service of Israel. Dr. Bachmat, a ground
water modeler, cataloged the models as they appear in Appendix A.
The Institute is particularly indebted also to Barbara Andrews, David
Holtz, and Scott Sebastian for designing the project, and for researching
and writing the report of the project with Dr. Bachmat. Barbara Goldberg,
Bonnie HavhoM, Carol Qualkinbush and Barbara Whitcraft ably assisted in
all phases of the project.
The following members of the Steering Committee provided major contri-
butions, active support, sustained interest, and valuable guidance to the
project staff:
John D. Bredehoeft, U.S. Geological Survey, Reston, Virginia, CHAIRMAN
Harvey 0. Banks, Consulting Engineer, Belmont, California
Jacob Bear, Israel Institute of Technology, Haifa, Israel
Patrick Domenico, University of Illinois, Urbana, Illinois
German E. Figueroa Vega, Comision de Aguas del Valle de Mexico, Mexico, D.F.
Yaoov Y. Haimes, Case Western Reserve University, Cleveland, Ohio
Luis Ippez Garcia, INTECSA, Madrid, Spain
Don Lennox, Environment Canada, Ottawa, Ontario
Ghislaih De Marsily, Ecole Nationale Superieure des Mines de Paris, France
George B. Maxey, Desert Research Institute, Reno, Nevada (deceased)
Jerome Milliman, University of Florida, Gainesville, Florida
R, William Nelson, Boeing Computer Services, Richland, Washington
David B. Oakes, Water Research Centre, Buchinghamshire, England
John R. Philip, Division of Environmental Mechanics-CSIRO, Canberra,
Australia
Thomas A. Prickett, Illinios State Water Survey, Urbana, Illinois
Jehoshua Schwarz, TAHAL-Consulting Engineering Ltd., Tel Aviv, Israel
Tatsuo Shibasaki, Consulting Geologist, Tsurugashima, Saitama, Japan
Robert G. Thomas, Food and Agricultural Organization, United Nations, Rone,
Italy
John Wilson, Massachusetts Institute of Technology, Cambridge, Massachusetts
Arnold Verruijt, The University of Technology, Delft, The Netherlands
Thomas F. Malone, Director, Holconb Research Institute, Indianapolis,
Indiana, (Ex Officio)
Ted Munn, Atmospheric Environment Service, Downsview, Ontario (Ex Officio)
Francois N. Frenkiel, Naval Ship Research and Development Center, Bethesda,
Bethesda, Maryland, (Ex Officio)
viii
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CHAPTER 1
EXECUTIVE SUMMARY
The objective of the SCOPE International Assessment Project on Ground-
water Modeling is an evaluation of the present status of numerical models
as a tool for groundwater-related water resource management. Recommenda-
tions resulting from the project have been formulated to provide guidance
to those persons and agencies interested in improving the utility of models
to management. In the hope of reaching as wide an audience as possible,
this report is directed toward the nontechnical reader.
The principal conclusions and recommendations of the project are set
forth in Chapter 2. Four major problem areas are identified, and ranked
by the staff and steering cotmittee in the following order of importance:
1. accessibility of models to potential users
2. ccmnunications between managers and technical personnel
3. inadequacies of data
4. inadequacies in modeling
The project makes specific recommendations for action in each of these
areas that are considered to be generally applicable to both developed
and developing countries.
A complete statement of the project objectives as well as a history
of the project and a discussion of its methodology is contained in
Chapter 3. The project was carried out primarily through a series of
surveys of two groups: 1} those most actively involved in development
of models and 2) those active in application of models to management
problems. The project staff also initiated a series of workshops which
promoted discussion by professional experts of barriers to the more
effective use of groundwater models. An international steering ccmnittee
composed of scientists prominent in the development and application of
models assisted the staff in these efforts. In addition the steering
ccmnittee provided continuous guidance to the staff throughout the
course of the project.
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Chapter 4 describes groundwater-related problems and relevant manage-
ment issues, and emphasizes the levels of management and the management
decisions for which models are most appropriate. The chapter then explains
for the benefit of the nontechnical reader, how the processes of scientific
research and model building proceed and interrelate to produce models which
can be applied to specific field situations. The relationships between
scientific researchers, model builders, technical modeling experts, and
managers are discussed.
For those readers unfamiliar with the field of groundwater modeling,
Chapter 5 contains a simplified description of the natural physical systems
which are described by models as well as a discussion of the impacts of
various kinds of human activities on groundwater systems. The major cate-
gories of models which are used to describe and predict the behavior of
groundwater systems are also introduced. The primary intent of this
chapter is to help the nonspecialist become familiar with certain technical
terms which may aid in understanding the project findings.
Chapter 6 presents a description and overview of the 250 existing
models which were submitted in response to the project survey. The purpose,
status, and application of models in each category are reviewed and
summarized in a nontechnical manner. For professionals who are active in
model development or who require models for the solution of management
problems, a more detailed technical review of the surveyed models is pre-
sented in an appendix. In addition, a complete set of the responses to
the model survey will be available from the National Technical Information
Service in Springfield, Virginia.
Chapter 7 presents project findings regarding barriers to the ef-
ficient use of models as they are viewed by model users. This chapter
also lays the ground for the project's conclusions and recommendations
which represent a synthesis of the project findings by both the project
staff and steering committee.
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CHAPTER 2
CONCLUSIONS AND REJCOMMENDATICNS
The recommendations of this report are intended to provide guidance to
governmental and nongovernmental agencies at both a national and inter-
national level on measures necessary to inprove the utility of models in
groundwater management. During the course of the project, four major
problem areas have been identified. These problem areas have been ranked
by the project staff and steering committee in the following order of
importance:
1. Accessibility of models to users. Top priority should be given to
making existing models more accessible to potential users as the most
necessary immediate improvement. Increasing the accessibility of models
consists not only in improving the quality of information about models and
making this information and the models more available, but also in improving
the training of those persons who use models.
2. Communications between managers and technical personnel. Measures
must be taken to improve the links between management and those who provide
technical services employing models. This will involve designing model out-
puts to be more responsive to management needs as well as more interactive
participation by managers and technical personnel in problem definition and
model applications.
3. Inadequacies of data. Solutions to problems of data will require
increased attention to the identification of those data critical to the
solution of groundwater management problems. Improved methods of data
collection, storage, and retrieval are needed.
4. Inadequacies in modeling. In certain areas models still do not
exist or are considered inadequate. The development or improvement of these
models should be encouraged; in many instances, however, models will have
to be preceded by improved scientific understanding of the fundamental
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processes which the models are to describe.
Specific recamendaticns for action have been formulated in each of
these areas and are presented in the following sections. The recommenda-
tions have been conceived as broadly as possible and are intended to
disprove the utility of models in both the developed and developing nations.
ACCESSIBILITY
Difficulties in the accessibility of existing models to potential users
appear to be the roost serious impediment to the effective use of models in
groundwater management. Improved accessibility cannot be brought about
through further research. Rather, shifts in the incentive structure of
institutions or even modifications of the institutions themselves may be
required, m general, the most important problems of accessibility revolve
around issues of model documentation, model distribution, adequate training
in the use of models, and in improving the simplicity of certification for
the user. Each of these problems must be addressed in a different way.
Lack of adequate documentation emerges repeatedly as the primary
stumbling block to more widespread and effective use of models in manage-
ment. If a model is to be applied to more than one problem, a well-written
and complete user's manual is essential. Unfortunately, the preparation of
documentation is not necessary for the use of a model by its developer. In
addition, documenting a model is a boring and usually unrewarding task.
Finally, the preparation of documentation is a time-consuming and con-
sequently costly task for which moneys are seldom available.
Recommendation 1
A:prerequisite- for the funding of model develop-
ment by any public agency should be adequate
documentation of a model produced. The documen-
tation should include a description of the model,
a listing of the code, and a user's manual.
Complementary to improved documentation of models is the need to de-
velop means to distribute this documentation and to make potential users
aware of what is available to them. Thus, some sort of central facility
for providing information on the available groundwater models is necessary.
Such a facility should ideally be internationally based with continued
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long-term financial support. If this proves impracticable, national centers
should be encouraged. The consulting functions of such an organization
should be limited; these can be provided by existing institutions.
Recommendation 2
Models developed by public funds should be
available to public agencies. A central
"clearinghouse" should be established, to in-
clude all forms of documentation, information
on the number and kind of problems for which
the models have been tested and successfully
used, as well as information on models
commercially available.
The accessibility of models is constrained not only by the lack of
proper documentation and inadequate distribution, but also by insufficient
understanding on the part of technical personnel — often referred to as
field hydrologists — of the capabilities of models. To some extent this
deficiency is the result of the inevitable time lag between the develop-
ment of a new tool and its widespread use. Models have been developed
rapidly in recent years and the education of practicing hydrologists has
not kept pace. This should be remedied through "short courses" and training
programs.
Recatmendation 3
Encourage the development and/or expansion of
programs designed to teach technical person-
nel how to better select and use models for
addressing field problems as well as the
capabilities and limits of newly developed
modeling techniques. These programs should
be especially directed at persons already
practicing in the field.
O2MJNICATIONS
In improving the utility of models for groundwater management applica-
tions,, better communication is an important priority. Three areas for
improved conrtiunication have been highlighted: 1) between managers and
technical personnel, 2) output of models, and 3) management models.
A gap in ccnnunications between managers and technical personnel is
often found in the field of water resources which may cause unrealistic
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appraisals of model results. In these cases, two kinds of attitudes about
models may be encountered among water managers. On the one hand, managers
may be willing to accept any output of a model unquestioningly; on the
other hand, they may distrust the model completely. The former attitude is
bound to lead to disillusionment; the latter never gives the model a chance.
Such attitudes about models would appear to have three causes. First,
there is considerable misunderstanding among managers about the way in which
models work and consequently about the reliability and limits of model out-
put. Second, managers are not easily able, and are sometimes unwilling, to
state their problems to technical personnel in terms simple and concise
enough to enable the proper use of a model to reach a solution. Third,
modelers may be unable to contnunicate effectively with managers.
Generalized solutions to difficulties of misunderstanding and problem
formulation are difficult to find; however, there are means to ameliorate
the situation. Perhaps the most important of these is the increased in-
volvement of managers in the process of modeling their problems. Managers
will naturally develop more understanding and confidence in those problem-
solving tools which they have helped to develop or apply. This is not to
say that an attempt ought to be made to teach managers about the equations
underlying the models or about computer programming. Rather, managers
should be consulted frequently during the process of applying a model on
such questions as the formulation of objectives and constraints, and the
relative importance of various inputs or parameters. Equally important is
the (xranunication by technical personnel of relevant model results in
language understandable by managers.
*. Recommendation 4
Encourage the interactive participation of
managers and technical personnel in addressing
groundwater management problems. In certain
cases outside consultants may facilitate such
interaction.
Often a barrier to the more effective utilization of models is their
output. Managers need to have model results presented in a way that is
meaningful to and compatible with decisions that must be made. The
uncertainties contained in various decision alternatives are especially
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important to assess. The form of the output is also important. Careful use
of graphics and other displays may greatly enhance the utility of model
results.
Reconroendation 5
The output of models needs to be formulated
in ways that are useful to managers and
which indicate the uncertainties contained
in model results.
To date, the most effective management use of models has been in what
might be termed "engineering decisions." On the other hand, the use of
models in the formulation of policies and regional programs has in most
countries been minimal. Nonetheless, management models for policy formula-
tion do exist and have been used efficiently in some places. The fact that
these models are not often used is largely due not to their lack of
sophistication or accuracy, but rather to the fact that they are commonly,
at least at the present time, not considered acceptable. This lack of
acceptability is closely related to the institutions of water management and
to the political context in which they function. However, as the scale and
complexity of water problems increases there is clearly a growing need for
the use of these models for policy decision making.
Reconrnendation 6
Encourage the utilization and further develop-
ment of management models for the formulation
of policies and regional programs where they
are acceptable. Special emphasis should be
placed on the participation of management in
the formulation and utilization of such policy
and management models,
DATA
It is generally recognized that the reliability of the output of a
model cannot exceed the reliability of the input data. These are often
considered by model users to be seriously inadequate. On the other hand,
there can never be enough data for a totally accurate prediction, and a
supposed scarcity of data may serve to obscure a number of other difficul-
ties in model application. Chief among these is the failure to consider
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what degree of accuracy in prediction is required of the model. This fact
is particularly important in view of the typically high costs of data
collection in cccnparison to other activities related to model development
and operation due to the diminishing added benefit from collecting addition-
al data.
Poor data do not make it iirpossible to use a modelj they only influence
the quality of the output. In those cases where a high degree of accuracy
of prediction is not called for/ a model with a miniinum of data input may
be sufficient. Where greater accuracy is required, sensitivity analysis
can be conducted to determine which data are critical. The necessary money
may then be spent on collecting these data.
Recommendation 7
Data collection for modeling purposes should
be conducted in response to sensitivity
analyses. Such analyses should include the
value of benefits derived from collecting
additional data.
Once critical data have been determined, these data should be
collected at the least possible cost. As already mentioned, the cost of
data collection represents a large, often the largest, single item in the
budget for the analysis of a field problem. Thus, more cost-effective
means of data collection could lead to substantial savings. Furthermore,
data collection is, or ought to be, a continuous process for the updating
or improving of a model over time. Eventually the sheer volume of data
acquired for a region becomes cumbersome, and some form of centralized
storage and retrieval becomes useful. Within the United States, the U.S.
Geological Survey is developing a centralized computer-based cataloging
and storage facility for data related to groundwater. The development and
operation of such a facility should be encouraged in other places.
Beconmendation 8
Improved methods of data collection on a
routine basis should be developed. Particu-
lar attention should be given to the
establishment of centralized storage and
retrieval facilities.
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MODELING
The project finds that a surprising amount of activity has been
directed, especially in recent years,- toward the solution of a great many
problems related to the modeling of groundwater systems. Models for most,
although not all, problems that are of interest to groundwater management
have been built. Naturally, sane of these models are more satisfactory
than others, but on the balance, the range of existing models shows a high
degree of sophistication; most of the remaining problems in the description
of physical systems are being investigated.
Several areas have been identified in which improvement of existing
models is desirable. In general, these areas pertain to the modification
of codes to facilitate their use and to allow greater transferability among
users. Thus some models, although well documented, contain so many options
that only a user very familiar with the program can use it effectively.
Other programs are not easily understandable which precludes a user from
modifying them for his particular case. Often including an example problem
in the documentation of a code makes it more readily usable. Imaginative
/<
input and output routines facilitate use as well. Output routines which
make the results easy to visualize and understand also increase the
usefulness of a model.
Recommendation 9
Every effort should be made to develop codes
which are easy for the user to both under-
stand and use. Improvement of existing codes
is required in the following areas:
* simplicity of structure and use
* flexibility and visual illustration of
outputs
* stability of outputs
* adaptability to other computers and codes
* computer storage and time requirements
Due to the volume of ongoing research and development in the field of
groundwater modeling, it has proved difficult to evaluate just which kinds
of models are now developed to a satisfactory stage. Furthermore, the de-
termination of what is "satisfactory" is in part related to the particular
field problem being solved and in part a matter of professional judgment.
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Nonetheless, it has been possible to arrive at sane consensus among at least
a large number of professionals that certain kinds of models are missing or
inadequate.
Although most problems of saturated flow can be regarded as solved,
two special cases remain to be adequately modeled. The first of these is
flow through a media of secondary porosity such as the fracture systems or
karstic formations; the second is flow for iirmiscible fluids such as oil
and water. The oil, water, gas problem has received extensive considera-
tion in petroleum engineering. These results can be transferred with some
modification to groundwater problems. Flow models are also needed that
better integrate surface flow and flow through the unsaturated zone with
saturated groundwater flow. Contaminant transport models have advanced
rapidly in recent years, but there is still a need for models which handle
better both chemical and biological reactions. Also, the inclusion of
socio-economic and ecological aspects will greatly improve the usefulness
of models to management. Finally, the inclusion of random or stochastic
aspects, particularly in regard to aquifer parameters, is important in
assessing the reliability of model outputs.
Rscommendation 10
Further model development is called for in the
following areas:
* flow in media of secondary porosity
* flow for immiscible fluids
* fully integrated surface, unsaturated,
and saturated flow
* contaminant transport with chemical
and biological reactions
*. socic>-ecohanic aspects
* ecological aspects
* consideration of stochasticity
* parameter identification
In the case of a few phenomena, the development of models is being
hindered by a lack of understanding of the physical processes to be modeled.
That is to say, once these processes are adequately understood and de-
scribed, their introduction into a model should present no insuperable
difficulties. Several such phenomena have been identified, but among
these the most important are in the area of the kinetics of chemical and
10
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biological processes, the transport of pollutants through the unsaturated
zone, and effects of scale and heterogeneity on transport phenomena.
Recommendation 11
Further research is needed to describe:
* the kinetics of chemical and biological
processes in groundwater
* mass transport in the unsaturated zone
* the quantification of management objectives
* parameter identification methodologies
* the effect of scale and heterogeneity on
transport phenomena
CONCLUDING REMARKS
The preceding recommendations are not the only ones that could have
been formulated on the basis of the information and opinions collected over
the course of the project. Chapter 7 of this report presents the findings
of the project and elaborates upon the basis for these recommendations.
There are, no doubt, other extremely interesting problems for further
investigation. Nonetheless, the staff and steering committee have made a
careful effort to address reconmendations to what they feel are the most
central problems in the use of models for groundwater management; further-
more , we have attempted to rank these problems in the approximate order of
importance.
This project has been primarily directed toward the improvement of
groundwater management, not toward the advancement of science and technology.
We hope the recommendations will assist others in formulating their
objectives, and more importantly, that they will serve to increase the
benefits from the world's groundwater resources.
11
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CHAPTER 3
DESCRIPTION OF THE PROJECT
In recognition of the significance of groundwater problems, the SCOPE
International Groundwater Modeling Assessment Project began in June, 1975,
to assess the status of numerical models as an aid in groundwater-related
water resource management. This chapter contains a statement of the
problems associated with the utilization of models in groundwater resource
management, followed by an overview of the project's organization, aims,
scope, audience, and methodology.
STATEMENT OF THE PROBLEM
The enlightened management of water resources is becoming increasingly
important as shortages of water and deterioration in water quality affect
growing segments-of the world's population. Groundwater is being in-
creasingly exploited as both a primary and supplemental source of supply
in a variety of regions and nations. The attractiveness of groundwater is
due in part to: the capacity of aquifers to store large quantities of
water commonly with minimal loss; the reliability of groundwater for long-
term or supplemental supply; the potential for subsurface storage of
hazardous wastes? and the use of groundwater as a hedge against drought.
However, because groundwater is essentially a hidden resource, its proper
management is often difficult to achieve.
In view of the mounting importance of groundwater and the uncertainties
associated with its use, the development and use of improved formal or
mathematical tools are necessary to foster more efficient groundwater-
related resource management. Numerical computer models represent one such
tool which has considerable capability for aiding managers in making
decisions related to the various uses, both actual and potential, of
groundwater systems.
12
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Numerical modeling of groundwater is a relatively new field which was
not extensively pursued until the mid-1960s. Since that time, significant
progress has been made in the development and application of numerical
models for groundwater-related resource management. (Management is here
defined to include planning, implementation, and adaptive control of
policies and programs related to the exploration, inventory, development,
and operation of water resources containing groundwater.) However, in
spite of this progress, gaps still exist between the need for, and the
existence and actual use of, groundwater models in management. The
closing of these gaps can serve to improve the management of groundwater
resources.
Consequently, it is necessary to identify those models which management
needs but does not have, and to examine the reasons why management does not
use certain available models, or does not find useful other models which
are both available and applied. Accomplishing these tasks requires both a
detailed examination of the intrinsic strengths and deficiencies of the
models themselves, as well as consideration of a variety of other factors
or circumstances which are not directly related to the models but which
affect model use. This report undertakes to lay the foundations for a
unified effort on the part of those who fund the development of groundwater
models, researchers, practitioners, and users, to improve groundwater-
related resource management.
ORIGINS AND ORGANIZATIONS OF THE PROJECT
Initiative and partial funding for the groundwater modeling assessment
project was provided by the U.S. Environmental Protection Agency (EPA) 1
The EPA's interest in evaluating groundwater models was an outgrowth of the
agency's jurisdiction over activities affecting groundwater quality. While
its responsibility for groundwater is confined to the United States, the
EPA was aware of the desirability of drawing upon the experiences of other
countries. Therefore, to add a meaningful international dimension to the
assessment effort, the project was sponsored by the Scientific Committee on
Problems of the Environment (SCOPE), a subcommittee of the International
Council of Scientific Unions (ICSU).
13
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The Holcomb Research Institute (HRI) of Butler University, Indianapolis,
Indiana, was charged with the responsibility of carrying out the modeling
assessment project, as a result of the Institute's wall-established working
relationship with SCOPE. The Institute was an appropriate organization in
which to house the project, since it had just completed a critical evalua-
tion of the role of modeling in environmental decision making in the United
States. The groundwater modeling assessment study was viewed as a logical
continuation of, this joint SCOPE/HRI effort.
Staff leadership for the groundwater modeling project was provided by
Dr. Yehuda Bachmat, who came to the Institute on a year's leave fron his
position as Director of Research of the Hydrological Service of Israel. To
guide the HRI staff and to insure adequate international representation in
the development of the project, an international steering committee was
assembled and first convened in Indianapolis, in June, 1976. The committee
was composed of twenty-two groundwater modelers and water resource con-
sultants and managers from the United States, Israel, Australia, Canada,
France, Japan, Mexico, The Netherlands, Spain, the United Kingdom, and the
Food and Agriculture Organization of the United Nations. The committee
was chaired by John Bredehoeft of the U.S. Geological Survey. (A roster
of the project steering committee and staff can be found in the Acknowledge-
ments of this report.)
PROJECT AH1 AND SCOPE
The objective of the project was to assess the utilization of numerical
models in groundwater resource management. To achieve this objective, the
project was directed toward answering faro major questions:
1. What are the needs for numerical models to address
significant groundwater problems and related
management decisions?
2. What are the existing groundwater models, and
to what extent are the models meeting these
needs?
1 Holcomb Research Institute, Environmental Modeling and Decision Making:
The United States Experience. A Report for the Scientific Committee on
Problems of the Environment. New York: Praeger Publishers, 1976.
14
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By answering these questions, the project hoped to arrive at recommendations
and priorities concerning measures to enhance the use and utility of models
in groundwater-related water resource management. The scope of the project
was confined largely to investigating those countries and agencies repre-
sented by the members of the steering committee.
PROJECT AUDIENCE
While the immediate recipient of the report is the U.S. Environmental
Protection Agency (EPA), it is expected that its contents will be of inter-
est to model builders, model users, and decision makers in governmental as
well as private organizations throughout the world concerned with ground-
water resource management. Major users of the report will be the first
two groups — model builders and model users — who desire access to infor-
mation on the extensive work which has already been undertaken in ground-
water modeling. However, this report is also addressed to a wider
audience, including both water resource managers and others interested in
the subject. In an effort to make the report more understandable to non-
scientific readers or individuals not directly involved in modeling, an
attempt has been made to restrict technical details to Chapter 6, which
reviews existing groundwater models.
PROJECT METHODOLOGY
The objective of the project, as previously described, was to review
the present utilization of models in groundwater resource management.
Meeting this objective required an examination of the current groundwater-
related problems, the decisions involved in solving those problems, the
needs for models to aid in making those decisions, and the existing models.
The project was thus designed to gather information, through surveys and
interviews, from three groups of individuals: those responsible for ground-
water-related management problems and decisions (managers); those applying
models to the analysis of problems in groundwater management (technical
experts); and those developing models to help solve groundwater-related
problems (modelers). Some individuals belong to more than one of these
three groups. The difficulties in surveying the members of the first
group — the decision makers or managers — are apparent; in view of limits
15
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in both time and resources, the efforts of the project staff were primarily
directed toward gathering information from the technical experts and the
modelers.
Survey of Groundwater Models
The project's primary activity, a survey of the existing groundwater
models, was based upon a questionnaire designed to facilitate an analysis
of the capabilities of existing models. Each questionnaire requested de-
tailed information on the particular model being described: general
identification characteristics, the model's conceptual and mathematical
framework, the ccmputer program, documentation and availability of the pro-
gram, past applications of the model.
The model questionnaire was widely distributed to groundwater modelers
throughout the world. From this effort, 250 completed questionnaires were
received, a figure judged to represent a reasonably comprehensive and
illustrative coverage of the population of existing numerical groundwater
models in the Western World. The results of the survey are presented in
Chapter 6. A detailed review of the models is included in Appendix A.
Survey of Needs Related to Models and Their Use in Solving Groundwater
Problems
In addition to the inventory of models, the project placed emphasis
on examining the application of models to tasks and decisions for solving
groundwater problems. As part of this activity, inquiries were addressed
to hydrologists, engineers, planners, consultants, and other technical
experts involved in the analysis of existing groundwater problems. While
occupying a variety of professional roles, these individuals provide a
functional interface between the model developers on one hand, and the
groundwater resource managers or policy makers on the other. Some of
these technical experts are model developers themselves; some apply their
own models to field problems.
In the United States, the survey of technical experts was undertaken
in two ways. The first approach utilized a brief questionnaire designed
to solicit evaluations and recommendations relating to both modeling needs
16
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and uses in water resource management (see AppendixB). Nearly 2,500 of
these questionnaires were distributed in a mailing which covered federal
agencies (U.S. Geological Survey, Bureau of Reclamation, Army Corps of
Engineers, Environmental Protection Agency, Soil Conservation Service),
state agencies in the water resources and related environmental fields, in-
terstate river basin commissions, and professional societies (Technical
Division of the National Water Well Association and Hydrology Section of
the American Geophysical Union). Of the forms distributed, approximately
10 percent were returned and analyzed by the staff.
The second survey approach used an the U.S. involved an in-depth
discussion of modeling needs and uses through a series of three workshops
held in different regions of the United States. The first workshop was
held in Las Vegas, Nevada, on March 2-4, 1977; the second in Denver,
Colorado/on March 24-25; and the third in Tampa, Florida, on April 6-8.
Each workshop was arranged by the Holconib Research Institute in cooperation
with: the Desert Research Institute of the University of Nevada for the
Las Vegas workshop; the Denver office of the U.S. Geological Survey, Water
Resources Division for the Denver workshop; and the Tampa office of the
Southwest Florida Subdistrict of the U.S. Geological Survey, Water Resources
Division for the Tampa workshop.
Several factors were considered in the selection of the workshop loca-
tions, such as the variety of groundwater'-related resource problems in the
area, the level of modeling activity being directed toward solving these
problems, and the nature of the groundwater decision-making structure, in
each region considered as a workshop site. Workshop participants were in-
vited from universities, private consulting firms, and government agencies
at all levels. In all, approximately 150 professional model users from
30 states were consulted regarding their views on modeling and model
application to groundwater resource management.
While the technical experts in the United States were surveyed directly
in the workshop and by questionnaire mailings, the task of corresponding
with such individuals in other countries was undertaken by the appropriate
member of the project's international steering committee. A workshop
similar to those held in the United States was arranged for The Netherlands,
France, and surrounding countries in April, 1977. Committee members in
17
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other countries were asked to conduct in-person interviews or distribute the
survey questionnaire by mail. Approximately 85 professional model users and
managers from 22 countries expressed their views regarding modeling needs
and applications to groundwater resource management.
Organization of the Report
Chapter 4 presents a general description of groundwater resource pro-
blems and associated levels of management and decisions, along with a brief
explanation of the processes of scientific research, model building and the
application of models to real systems. In Chapter 5, a relatively non-
technical introduction to the physical groundwater system and groundwater
models is provided. An intensive technical analysis of existing models
follows in Chapter 6. Finally, based on the various surveys, the identifi-
cation and analysis of gaps related to the use and utility of models in
groundwater resource management is discussed in Chapter 7. From this
discussion the project's conclusions and reconroendations are deduced and
presented in Chapter 2.
18
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CHAPTER 4
MANAGEMENT AND MODELING
This chapter examines, in a nontechnical manner, the relationship be-
tween the various management decisions and the uses of models as a tool for
decision making. A brief description of general categories of groundwater
problems is followed by a review of the different types of management
decisions which must be made in addressing these problems. The different
levels of hierarchy at which decisions are made is discussed and those
levels of management for which models have been most effectively utilized
are suggested. Finally, we discuss the several groups involved in the
development and application of models to problems, and how the processes
of scientific research, model building, and model application, are
generally conducted.
GROUNDWATER-RELATED PROBLEMS
Water problems in general and groundwater problems in particular con-
tinue to grow in complexity and significance as population, agriculture,
and energy development expand. For purposes of discussion, groundwater
problems may be divided into three principal categories: supply, con-
tamination, and other environmental impacts. Planning and management
issues add a fourth important dimension to groundwater-related problems.
In fact, most groundwater problems fall under more than one of these
categories. Furthermore, groundwater problems are linked with more general
water resource considerations and with legal, economic, and political
influences. Therefore, an effective response on the part of management to
groundwater problems must be based upon the recognition of the relation-
ships among problems and the associated impacts which any given decision
may generate.
The order in which the problems are discussed in the following
19
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paragraphs does not indicate any particular priority among the problem
categories. Furthermore, although the text mentions specific localities
as illustrative examples, it should be noted that all of the problems
discussed occur in many areas around the world.
Supply
Provisions of water is basic to nearly any organized water resource
management effort. Problems of water supply arise from the need to provide
water users with a safe and adequate amount of water at all times or upon a
particular schedule of demand. Certain cities or regions rely on ground-
water exclusively as a source of supply. Surface sources in many areas
have provided the bulk of the water for man's use. Recently, however, in-
creases in demand for water have gone beyond the capabilities of these
surface sources and have led to a growing reliance on groundwater as either
a primary or supplementary source of supply.
Groundwater reservoirs conmonly provide a dependable source of supply
due to their large reserves. However, a prolonged pumpage from a ground-
water reserve well in excess of its renewable yield may result in the
situation known as groundwater mining. Within the United States, ground-
water mining is especially prevalent in parts of the Wast, Southwest, and
High Plains where the annual replenishment of the groundwater system is
greatly exceeded by pumpage to meet the water demands of growing urban
communities and heavily irrigated agriculture.
Under conditions of groundwater mining an ultimate shortage of ground-
water is possible, and indeed inevitable. However, even in the absence of
mining, there may be other problems which restrict the development of
groundwater supplies. For instance, difficulties in gaining access to
existing groundwater supplies may have several causes. The first of these
is the fact that groundwater reservoirs are hidden from view and may in
some cases be difficult to locate, map, or describe with regard both to
capacity and spatial extent. Second, even if the location and character-
istics of the groundwater system are known, the groundwater may be of
naturally poor quality requiring costly treatment processes before it can
be used.
Most importantly, economic considerations may constrain access to
20
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groundwater through the costs incurred by land acquisition, well con-
struction, and other activities associated with development. Problems of
groundwater utilization may be the result of political or social resistance.
This resistance often arises out of a general preference for traditional
surface sources, proprietary rights, or a lack of understanding of the
potential of groundwater for expanding existing conraunity water supplies.
Contamination
Contamination problems are related chiefly to the pollution of ground-
water by man. Groundwater pollution is caused by waste disposal activities
such as landfills, contaminant holding ponds, septic tanks, and deep well
waste injection. Pollution also results from area-wide groundwater re-
charge from urban and agricultural areas. The actual constituents polluting
groundwater include toxic chemicals, brines, chlorides, nitrates/ oil,
trace metals, and radioactive substances.
Another source of contamination, saltwater intrusion into coastal
aquifers and the upward migration of natural salt water can be caused by
groundwater pumping. Pumping lowers the freshwater head in the groundwater
reservoir and allows saltwater to enter. Coastal saltwater intrusion is a
serious problem along the coasts of many countries such as Mexico, Israel,
Japan, and the United States, and its adverse effects may range from the
pollution of an individual well to the destruction of entire coastal
agricultural systems or urban water supplies.
Environmental Impact
Several .kinds of iinpacts on the environment are caused by extensive
groundwater exploitation; these comprise a third major category of ground-
water-related problems. A substantial environmental impact associated with
the use of groundwater, and caused by overpumpage, is land subsidence.
Subsidence is a gradual collapse of the land surface resulting from the
lowering of groundwater heads by pumping. Subsidence is of special concern
in urban areas where it may damage buildings, roads, and water and sewer
mains, and cause increased flood and hurricane hazards.
A second type of groundwater-related environmental impact is water-
logging of soils. Waterlogging is comtroi with irrigation. While this
21
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particular problem may not be as dramatic as land subsidence, it is still a
nuisance which afflicts many areas. Irrigation projects throughout the
world are plagued by drainage problems.
A third type of environmental impact relates to the general ecosystem.
Groundwater provides the base flow to streams and often plays a predominate
role in determining the quality of surface-water, especially at low flow.
Thus, groundwater can have an important and direct influence on the health
of vegetation and other living organisms over a wide area.
Planning and Management Issues
An institutional framework for the planning and management of ground-
water is essential in addressing those physical problems presented in the
previous sections. These institutions must deal not only with the physical
problems of groundwater but with the related economic, legal, social and
political issues as well. Although water supply, groundwater contamination,
and environmental impacts all obviously have planning and management com-
ponents, it is instructive to examine as a separate category institutional
aspects of groundwater management. It is more difficult to deal
effectively with the institutional barriers which comprise planning and
management problems than it is to find sound scientific solutions to
physical groundwater problems.
In the area of water supply, political constraints may determine the
feasibility of developing groundwater as a usable water resource. Legal
restrictions also may hamper the efficient use of groundwater; in the
United States, for example, outmoded water laws still fail to acknowledge
the fundamental physical interconnection between surface and groundwater
systems; ccmmooLy the present laws and/or their enforcement regulate the
groundwater system as if its use had no effect on surface water.
In the area of groundwater quality, at least in the United States,
current regulatory measures place considerably greater emphasis on con-
trolling pollution in surface water than on protecting groundwater supplies.
Relatively little action has been taken to ameliorate environmental impacts,
although these problems have been extensively studied from a scientific
perspective in those areas where they pose the greatest hazards to human
welfare.
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TYPES CF MANAGEMENT DECISIONS
In managing groundwater resources and solving groundwater problems, the
groundwater manager is typically confronted with making some or all of five
hey interrelated decisions, namely: feasibility, investment, policy, de-
velopment, and operations.
In determining the feasibility of a particular groundwater development,
the manager must consider the natural groundwater system and its response to
stress. He must then decide whether or not the groundwater system can
support, for example, a given level of pumpage for the time planned. In a
case of groundwater quality, the manager may have to decide the least harm-
ful area on which to establish a landfill. For this decision the manager
needs a variety of information, including of course, whether or not the
landfill might contaminate an associated groundwater system.
Based on the determination of physical feasibility/ the manager must
consider economic feasibility. For example, he must determine if the
benefits of having groundwater as a source of water supply are greater than
the costs of drilling and maintaining a groundwater supply. Next, he must
determine what the investment should be. Once groundwater is established
as a supply source, the manager cormonly continues to be faced with
decisions concerned with when and how large to make additional investments
to further exploit a given groundwater supply.
After the feasibility of a particular management action has been
determined and an appropriate investment decision made, the manager must
formulate a policy to establish viable institutional channels or frameworks
within which his actions can be undertaken. If developing groundwater as a
source of supply is the issue under consideration, a policy must be
established to state the conditions under which groundwater may be with-
drawn. Additional policy questions might involve controlling interference
effects on a nearby community's well field, or providing accompanying re-
gulations to ensure the quality of the groundwater supply.
Finally, once a policy for groundwater exploitation is established,
either the manager, or, more likely, technical personnel on his staff,
must make detailed plans concerning how best to develop and operate the
system with a view toward maximizing benefits or minimizing costs. Such
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decisions might include the preparation of an engineering design for a new
field, as well as stipulations for running the system once it is constructed.
Maintenance and follow-up activities such as monitoring and system control
also fall under the category of operations-type management decisions.
It should be recognized that the manager, in formulating decisions re-
lating to feasibility, investment, policy, development, and operations, is
always faced with numerous constraints. In general, legislation sets the
basic framework within which the manager must make his decisions. He must
then contend with outside political pressures. Cortnonly, the public
vocalizes its opinions and places constraints on decisions.
Once the manager arrives at a decision which may or may not satisfy
the majority of those groups expressing their views, he is often still
faced with such cannon constraints as limited funds, inadequately trained
personnel, and insufficient time. This variety of constraints, in sum,
limits the manager's ability to implement technically feasible solutions
to groundwater problems.
IEVELS OF MANAGEMENT DECISIONS
The management decisions affecting water resources are made by in-
dividuals as well as by a full spectrum of government agencies ranging from
the local to the national and even international levels (Figure 1).
While the jurisdictions of these agencies inevitably overlap, certain
generalities can still be made regarding the nature of the decisions made
at each of the levels. In general, any coherent scheme for managing water
resources must constructively integrate the effects of decisions made at
these various levels.
An example of a decision made at the individual level is the decision
by a fanner whether or not to drill a well to ensure an adequate and
dependable water supply for his crop. This decision will be based mainly
on the farmer's previous experience with weather conditions, and on his
weighing of the risk of drought against the capital expenditure required
for the development of an irrigation system. An individual decision by
itself does not normally have much impact on the total water system of an
area, but a large number of individual actions may combine to affect the
groundwater system in significant ways. The individual may be subject to
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National
State
Regional
Area
Local
Individual
Modeling Rarely Utilized
At the Present Time
Modeling Generally Accepted
And Utilized
Modeling Usually Uneconomic
Figure 1. MANAGEMENT LEVELS
(archers
Figure 2. PROFESSIONAL GROUPS INVOLVED IN
MODELING FOR MANAGEMENT
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a variety of constraints: well spacing regulations, well standard regula-
tions, and water rights.
At the local level, decisions concerning groundwater resources are
generally made by small-scale water suppliers. For example, a local water
supplier nay need to decide how best to operate his well field or whether
or not to add another well to the system. Again, one such decision taken
individually probably will not substantially affect the groundwater system
.significantly. The aggregate iirpact on many such local decisions may, how-
ever, adversely influence groundwater supplies over a relatively large area
extending beyond local jurisdictional boundaries.
Decisions pertaining to an area-wide level are generally made by large
cities, counties, or districts, and thus concern planning which is more
comprehensive than that which occurs on a local basis. For example, a
large city may need to decide whether or not to continue to rely on its
surface water sources, or to begin to develop groundwater supplies if these
are available. This level of management must make decisions such as where
to develop the next well field, or where a major landfill might be sited so
as to minimize the possibility of groundwater contamination.
At the next management level, regional authorities make decisions
covering several county areas. Regional decisions affect mainly the
impact of large-scale development projects or activities within an entire
watershed. One relevant issue of concern at this level is methods of
wastewater treatment. For example, a decision may need to be reached on
the restriction of the number of areas relying on septic tank systems in
order to protect groundwater resources as well as perhaps limit the
haphazard expansion of cities into outlying areas.
At the rstate and national levels, government agencies in large
countries deal chiefly with broad policy questions concerning their re-
spective jurisdictions. A state water agency may thus issue guidelines
and regulations concerning both quantity and quality aspects of ground
and surface waters within the state. A state department of natural re-
sources may decide whether or not groundwater is to be mined within the
state, and what the lifetime of such a mining project might be expected
to be.
National decisions consider such issues as interbasin transfers of
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water, and groundwater quality legislation which is binding on each in-
dividual state. It is important to note that the inpacts of decisions made
on one level on those of another level are not always recognized.
MANAGEMENT LEVELS AND MODELING
The use of numerical models as an aid in decision making is more use-
ful and effective at some decision-making levels than at others. For both
the individual and the local water supplier, the commission of a modeling
study to determine where to locate the next well is usually an
uneconomical proposition. The individual or local supplier will under-
standably be unable or unwillijig to expend thousands of dollars to model
such a small-scale problem. He may, however, have access to a model main-
tained by an organization such as a university or extension service, which
could be applied to his situation at a relatively modest cost. Nonethe-
less, in general, the use of models at the individual and local levels is
uncommon.
At the present time, models are most widely applied to management
decisions at the area and regional levels. - Both the government agencies
at these levels, and the groundwater issues with which they deal, are of
a scale which makes computer modeling economically viable. To date, most
groundwater modeling performed at these levels has pertained to engineering
considerations affecting feasibility, investment, and operations decisions
relating to particular, site-specific problems.
Modeling on a statewide and national basis is rare, but for obviously '
different reasons than those which explain the infrequent use of models by
individuals and localities. The major cause of the infrequent use of
models at the highest management levels is that the associated decisions
deal primarily with policy rather than the more straightforward engineering
problems. The formulation of policy necessitates interrelating physical
or engineering factors with a variety of other considerations such as legal,
economic, and political constraints. Models exist which attempt to do
this, but, with the possible exception of Israel and France, they have not
achieved widespread acceptance.
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GROUPS INVOLVED IN KEELING FOR MANAGEMENT
It is useful to consider the professional groups involved in developing
and applying models, m general, four such groups can be identified, al-
though considerable overlap may occur among them, and additional groups
or "sub-groups11 may also be present. These four groups are the managers
or decision makers, the technical experts who use models, the model
builders, and the scientific researchers (Figure 2).
The manager is the individual who is charged with solving a particular
problem; ultimately, it is he who is responsible for commissioning and
for paying the bill for a modeling study. The manager himself may decide
that a model is necessary, or he may endorse a modeling study based on the
advice of his technical staff. Many managers find it time-consuming or
unnecessary to understand the technical aspects and implications of a
modeling effort.
Because the manager may have little technical expertise in modeling
or in the scientific aspects of a decision concerning the groundwater
system, he must rely on a second group of professionals: the technical
experts. The manager presents to the technical expert the problem at
hand and the questions he would like addressed by the modeling study.
The technical expert, who may be a member of the manager's staff or an
outside consultant, chooses an appropriate model, applies it to the
manager's problem, and interprets and presents to the manager the results
of the modeling study. The interpretation of the model results is based
upon the professional judgment of the technical expert, and thus the
model results are only a component of his advice.
The technical expert, in adapting an existing model to a designated
field situation, is actually dependent upon the original model builder who
is a member of a third professional group. In relatively infrequent cases,
occurring most ccmmonly in private consulting firms, the model builder and
the technical expert is a separate individual who relies on written
documentation of certain models or on personal communication with the
model builder himself.
Just as the technical modeling expert usually needs a model builder,
so does the model builder require the input of a fourth professional group:
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the scientific researchers. Normally the model builder and theoretical
researcher are distinct individuals who cone into contact either through
established publications or personal interaction. The need for inter-
disciplinary cooperation is especially significant in scientific research
on groundwater because such research requires inputs from a diversity of
fields including geology, hydrology, chemistry, physics, civil engineering,
and ecology.
The above discussion illustrates that the process of creating and
applying a model to a management problem involves a series of groups. The
links between these groups are not always good, and the failure of any one
of them may adversely affect the utility of a model.
THE PROCESSES OF SCIENTIFIC RESEARCH, MODEL BUILDING, AND MODEL APPLICATION
The preceding section describes and comments upon the relationships
between four key groups involved in the use and development of models:
managers, technical modeling experts, model builders, and scientific re-
searchers. It is thus appropriate at this point to examine in a more de-
tailed but nontechnical manner how the procedures of scientific research,
model building, and the modeling of a real system, actually operate and
interrelate. These procedures are discussed in an order opposite from
that used to describe the four groups, since scientific research usually
precedes model building which itself must occur before the modeling of
a real system in the field can actually take place.
It should be noted that a fourth procedure — that of the manager
actually utilizing the information generated by the modeling of a real
system or problem — is not specifically treated in this discussion,
although references to the use of model results by managers have been
made in preceding sections of this chapter. The fourth procedure is not
explicitly treated here because model information is utilized in such a
variety of ways, situations, and contexts, that no one standard method
for incorporating model output into decisions exists. This does not
inply, however, that managers would not benefit from the development
of such methodologies.
The procedure of scientific research and the knowledge derived
therefrom lie at the basis of any model building and application effort.
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Scientific research begins with observations of a process to produce in-
formation on that process. This information, in turn, leads to sane level
of understanding of the process, on the basis of which a conceptual model
of the process can be formulated or the original observations corrected or
adjusted.
The conceptual model is, in essence, a theory of how the process
operates in a certain environment. To gain more refined insights into the
process, an analytical tool or device may be utilized, which in some cases
may be a mathematical model. By means of this device or model, the
scientific theory can be tested. The testing procedure, in turn, provides
information or "feedback," which is used to modify the original observa-
tions and theory.
The various steps in the basic procedure of scientific research are
outlined in Figure 3. It should be noted that the procedure is ordinarily
repeated many times before a satisfactorily tested description of the
process under study is achieved.
Once the process is understood it may be incorporated into a mathe-
matical model; the next step is the construction of that model, again
according to a series of several major, definable steps CFigure 3). Model
building at this level should be regarded not as the creation of a specific
model for a specific problem, but rather as the development of a general
computer code which is based on the conceptual model. Once the computer
code is developed, it is tested against hypothetical data, as well as
against the underlying theory itself* The testing procedure yields feed-
back which is used to modify not only the code, but in some cases also the
original theory as derived through the scientific research. After the
code has been tested, it becomes operational, and can be further applied
to selected field situations. Once a code has been made operational, it
still must be made available through the production of documentation,
that is, of adequate published material which describes the code and
provides guidelines for its application to real-world problems.
At the present time, many of the existing groundwater models are in
the stages of code development or testing; however, where testing has
red, it typically has been undertaken only once or twice per model.
OCCUEXt
Only a minority of models have been utilized for the analysis of several
30
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Scientific Research:
Feedback
Feedback
Observations
(Data)
Understanding
of Process
(Conceptual Model)
Choice of
Analytical
Device
(Mathematical
Model)
Testing
(of
Model)
Model Building (Code Development);
Feedback
Feedback
Development
of
Code
Testing of Code
Production of
Operational Model
(Code)
Involving Several Test
Runs
Documentation
of
Model (Code)
Figure 3: SCIENTIFIC RESEARCH AND MODEL BUILDING
-------
field situations, and the number of models which are fully documented is
even smaller. This situation is a probable result of the fact that, in
general, model builders are more interested in code development and testing
than in documenting and in widespread applications of their models.
Cn.ce a general code has been developed by the model builder, either
the model builder himself or a technical modeling expert may apply that
code to the modeling of a real system in the field. The procedure of
modeling a real system (Figure 4) basically parallels that of performing
scientific research. Data on the system are collected and analyzed to
provide a conceptual model or idea of how the system operates. Based on
this concept of the system, the modeler chooses an appropriate analytical
tool — in this case, a particular model or code which fits the situation
to be analyzed. Before applying a model to a problem, it must be cali-
brated against data from the system under investigation. Following this,
the application of the model to the problem will generate a prediction
concerning the system which in turn may lead to revisions in the original
concept, or mathematical model and additional data collection. The
modeling of a real system is thus an iterative process in which each
successive step provides feedback by which previous steps can be readjusted
to produce a final predication of desired accuracy.
Data play a central role in the application of a model to a field
problem. Initially, the technical expert usually has access to at least
seme data on the surface geology of the field situation. To refine this
data, to obtain a three-dimensional view of the groundwater system, and
to ascertain key characteristics of that system, the expert must rely on
drilling wells and conducting pump tests. Since the response of ground-
water systems is dynamic, pump tests are useful in providing information
on how the groundwater system responds to development pressures exerted
over time. In the calibration phase of the modeling procedure, the
model's results are compared against the known history of development.
Furthermore, a validation of the model by comparing its predictions against
data which have not been used in the calibration is especially useful in
refining the original conceptual model and in allowing the modeler to have
confidence in values assigned to key parameters which characterize the
groundwater system under study. In general, the longer the time response
32
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Sensitivity Runs - Use of Model to Guide Data Collection
Feedback
Data
* Geology-Surface
* Geology-Test Holes
* History of Development
(System Time Response)-
Pumping Tests
Feedback
Conceptual Model
of How System
Operates
Choice of
Analytical -
Tool (Model
Selection
and Revision)
Feedback on Groundwater System Dynamics
Calibration-
and
Validation
Predic-
tion
Figure 4. MODELING A REAL SYSTEM (APPLYING THE COMPUTER CODE)
-------
car development history available to the modeler, the more confidence one
has in the predictions generated by the model.
The preceding sections have attempted to provide a framework for
understanding the processes of modeling, the application of models to
groundwater problems, and the institutional context in which these
occur. The following chapter describes the physical systems which are
the object of management and modeling activities.
34
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CHAPTER 5
THE GRDUNDWATER SYSTEM AND GROUNDWATER MODELS
Before the technical description of existing groundwater models is
presented in the next chapter, it is instructive to review the basic
characteristics of the groundwater system itself. The review should help
the nontechnical reader to gain a better understanding of the physical
entities and processes which apply to groundwater systems and to familiar-
ize himself with the most important technical terms used in groundwater
hydrology. Figures 5 and 6 present simplified diagrams which should help
clarify further the nature of the groundwater system and man's influence
upon it. Following this overview, the general types or categories of
groundwater models themselves are introduced, along with an explanation
of some further technical terms commonly used in discussing models. This
chapter should, in sum, enable the reader to perceive more clearly the
relation of models to the management of the groundwater system.
BASIC CHARACTERISTICS OF THE GRDUNDWATER SYSTEM
Groundwater is found at various depths below the earth's surface, in
a variety of geologic formations which may serve as underground reservoirs.
These reservoirs are known as aquifers, and it is toward the description
and management of aquifers that all groundwater modeling is ultimately
directed. While aquifers are useful to man chiefly because of their
ability to store water, it is important to realize that the water in an
aquifer is in constant motion. Both the amount of water stored in an
aquifer and the rate of flow through the aquifer will be directly related
to the kinds of materials of which the aquifer is composed. These
materials range from unconsolidated sediments to bedrock, and include
gravel, sand, sandstone, and limestone. Thus, aquifers exhibit a variety
35
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Ul
1,11
Rtchorgt Arta of
Confined Aquiftr
I Transpiration
f
Gaining
Stream
__Unsaturattd Zone
^ "" ~ *T* — _
7 \ V Wottrtablt"" ~""
Losing Strtam
Evaporation
Soturatod Zone - Groundwottr
(Uneonfintd Aquiftr)
Frtsh Wottr, '
Inttrfact
Confining Laytr
Stmi-Confining Laytr
Ltaky Aquiftr
Saturattd Zont - Groundwattr
(Confintd Aquiftr)
Saltwattr
Frtsh wattr xx
Inttrfact xxStowottr
Imptrvious Btd
Figure 5 - The Groundwater System
-------
\ I \
Deep-well injection
of wastes pollutes
ground water
Landfill, agricultural runoff,
and contaminated stream
pollute groundwater
Development
inttrftrts with
natural recharge
area
Ul
-vl
Pumped wt 11
(Discharge)
Pumping causes cone of
depression lowering the
water table
Builds up water levels
and prevents further
seawater intrusion
,'Pumping from
"well field near
causes salinity
increase
Figure 6 - MAN'S INFLUENCE ON THE GROUNDWATER SYSTEM
-------
of characteristics and conditions which render the description of any one
aquifer a difficult and time-consuming task.
Despite the wide variation among aquifers, they are generally sub-
divided into two general categories or types: confined and unconfined.
These terms have nothing to do with the geological properties of the
aquifer itself, but are related rather to the permeability of the strata
bounding the aquifer. Confined aquifers are bounded by less permeable
rocks. The well-known phenomenon of an artesian well may result from
the tapping of a confined aquifer. Unconfined (or phreatic) aquifers are
overlain by a permeable layer through which water is able to percolate
downward into the aquifer. The upper surface of water in an unconfined
aquifer is known as the water table.
The region between the water table and the surface of the earth is
known as the unsaturated zone. The unsaturated zone may be no different
geologically from the aquifer or saturated zone. In fact, the level of
a water table will tend to fluctuate over time. The unsaturated zone does
contain some moisture, but it contains air and water vapor as well.
It should be noted that not all aquifers can be strictly categorized
as confined or unconfined. Some aquifers are called semi-confined or
"leaky" and are bounded by material which is partially permeable. Such
aquifers are held at greater than atmospheric pressure, but some water
does enter or leave the aquifer through the confining layer. Virtually
all confining layers are leaky to some extent; there are almost no
natural materials which are truly impermeable. Figure 5 schematically
depicts the different types of aquifers as just discussed, and their
relation to one another and to the unsaturated zone.
Aquifers.are further described by certain general characteristics
which are related directly to their geology. These characteristics are
normally referred to as parameters, and they describe the physical
properties of aquifers. A number of different parameters are used to
describe aquifers? it is not necessary here to discuss them all. How-
ever, parameters are extremely important to groundwater hydrology, and
one example should serve to clarify their significance.
Transmissivity describes an aquifer's capacity to transmit water
throughout its total thickness and is directly related to both an
38
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aquifer's thickness and its ability to conduct water. Thus, the trans-
missivity of an aquifer has a great influence on the amount of water
potentially available from the aquifer.
Beyond the determination of aquifer parameters, the analysis of
groundwater systems also requires the establishment of boundary conditions,
which are critical factors in determining how a groundwater system
functions naturally and responds to development or other outside influences,
stresses. Boundary conditions depend upon the configuration and hydrologic
conditions at permeable or semi-pervious boundaries, surface water bodies,
and other free surfaces. For the groundwater modeler or technical expert,
the identification and assignment of appropriate boundary conditions is in-
strumental in selecting the proper model which provides an approximate
description of the aquifer for analytical purposes.
The foregoing discussion of the groundwater system should make it
evident that, strictly speaking, groundwater management involves the move-
ment and storage of water in aquifers. However, the groundwater system
is not an isolated entity, and groundwater management must thus be con-
cerned with the hydrologic interconnections'between water in the ground
and water at the earth's surface. In essence, ground and surface water
are interrelated through two processes: recharge and discharge. There
are two major sources of natural recharge to an aquifer. The first of
these is precipitation which percolates through the unsaturated zone
to the aquifer. The second is freshwater inflow from surface water bodies
such as streams, rivers and lakes. Natural discharge from an aquifer may
occur through several possible outlets. Among these are springs, streams,
rivers, lakes, and the ocean. Discharge also occurs through evaporation
and through transpiration from plants known as phreatophytes whose roots
extend to the water table. Under natural conditions natural recharge and
discharge are commonly in balance.
The processes of recharge and discharge intimately link the ground-
water system with the rest of the hydrologic cycle, and consequently,
the groundwater system can be accurately described as dynamic. Within
the aquifer itself, the dynamics of the system revolve around the process
of flow, or the movement of water through the porous medium of the aquifer.
39
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Ill general, groundwater moves under the influence of gravity and pressure
in the direction of declining head which is measured in terms of water
levels in wells. The specific rate and direction of water movement in an
aquifer can be expressed by a set of equations. Rates of groundwater flow
are typically in the range of meters per day or year and are far lower than
normal rates of surface water flow which are in the range of meters per
second. However, the wide variety of conditions present in aquifers in-
evitably entails a corresponding wide variation in groundwater flow
rates.
MAN'S EFFECT ON THE GRDUNDWATER SYSTEM
The dynamic processes of the groundwater system are not only relatively
complex natural phenomena which challenge scientific understanding; they
are also significantly affected by the activities of man. One of man's
greatest impacts on the groundwater system is through the pumping of
water from wells which constitute a major source of artificial discharge
from the aquifer. The immediate effect of pumping is to lower the head
in the iirmediate vicinity of the well and to produce drawdown in the form
of a cone of depression around the well. Major pumping developments thus
commonly disturb the balance of inflow and outflow in an aquifer.
As noted in Chapter 4, if groundwater is continuously removed at a
rate which exceeds the net recharge (recharge minus natural discharge), a
situation of groundwater mining prevails. Mining of groundwater is a
common situation in most regions undergoing development and must ultimately
deplete the resource unless the water can be replenished through artificial
recharge.
Besides withdrawing water from the groundwater system, man may also
add materials, usually pollutants, to the system. The common sources of
groundwater pollution are illustrated in Figure 6. The range of problems
associated with inadequate distribution of pumpage, over-exploitation of
an aquifer, and the pollution of groundwater have already been presented
in Chapter 4.
40
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MODELS RELATED TO THE GRDUNDWATER SYSTEM
Man's extensive and varied interference with the groundwater systems,
as well as the complexities which characterize the response of the ground-
water system to that interference, have fostered the development of math-
ematical tools to aid in the analysis of groundwater conditions and pre-
dicting system response. At the simplest level, these mathematical tools
include analytical methods, "models", which deal with idealized aquifers
assumed to exhibit uniform parameters, simple flow, and regular geometrical
boundaries. Analytical solutions to groundwater problems can be carried
out with the aid of paper and pencil and perhaps a calculator and generally
do not require expensive hardware such as computers. More recently,
numerical integration methods have broadened the range of the analytical
methods.
For more complex aquifer situations the use of more sophisticated
techniques and technology is necessary. Historically, the first such
technique to be developed was the analog model. For example, analogues
which have been employed for the analysis of groundwater systems include
the flow of viscous fluids between plates, or the passage of electrical
currents through resistance-capacitance networks.
While the introduction of analog models enabled the analysis of
nore complex groundwater problems, they generally required a large
centralized facility with a large investment in hardware. With the wide-
spread availability of digital computers, analog models have been largely
replaced by numerical models which depend on the solution of algebraic
equations on the digital computer. Numerical models are capable of
analyzing more complex situations with greater ease than the analog models.
In addition, numerical models have proved to be far more versatile than
their predecessors. Research in the late 1960s produced hybrid models
vihich attempted to combine the best features of the digital computer with
the visual display and immediate outputs of the analog model. Hybrid
models have not, however, been widely used largely because they have not
kept pace with the rapid advances in digital technology.
Among the numerical groundwater models — the focus of this assessment
study — models with four different major purposes can be distinguished.
41
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These are: 1) prediction models., which simulate the behavior of the
groundwater system and its response to stress; 2) resource management models,
which integrate prediction with explicit water management decision pro-
cedures; 3) identification models, which determine input parameters for
both of the above; 4) data manipulation and storage procedures which
process and manage input data for all the above.
Prediction Models
Most of the models produced to date are prediction models which may
be subdivided into four major categories: flow, subsidence, mass transport
and heat transport.
Flow models utilize information on aquifer parameters, boundary
conditions, and man-induced development, to solve mathematical equations
for determining quantitative aspects of groundwater flow such as direction
and rate of flow, changes in water level, stream-aquifer interactions
and interference effects of wells. While most of these models simulate
flow in aquifers, flow models have also been developed for the unsaturated
zone, and for coupled saturated-unsaturated-surface systems. Flow models
are the most commonly used, as well as, the best developed of the ground-
water models.
Subsidence or deformation models describe the phenomenon of land sub-
sidence which is caused by withdrawals of groundwater. Subsidence models
are needed to predict deformation-related impacts of various pumping
schemes in affected areas.
Mass transport models deal primarily with questions of groundwater
quality. They are used to predict the movement and concentration in the
aquifer of various pollutants including radionuclides, leached solids
from landfills and irrigated areas, and salt water intruding in
coastal areas. To accomplish this, the models incorporate mathematical
approximations of the transport, by means of fluid flow (convection),
and/or mixing of one or more chemical constitutents in the groundwater.
Because of these considerations, mass transport models in general tend to
be more complicated than flow models. Transport models that describe
the movement of pollutants without reactions are called conservative;
models that also take into account reactions are termed nonconservative.
42
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The oil industry has been active in developing transport models for
immiscible substances, oil and water.
Heat transport models couple the flow of heat with water or steam for
problems where thermal effects are important. In practice these models
have been applied to problems associated with hot springs, geothermal
reservoirs and heat storage.
Resource Management Models
Management models have been developed in an attempt to indicate
courses of action which will be consistent with stated management objectifies
and constraints. The objectives may be, for example, to maximize net
economic benefits, to minimize costs, or to ensure adequate water supply
at all times for all users. Management models may employ the techniques
of both simulation and optimization in deriving their outputs. In
contrast to purely physically-based prediction models, management models
incorporate economic, technological, political and institutional aspects
of the problem being analyzed.
Identification Models
Parameter identification models have been developed in response to
the need to provide improved estimates of parameters. Although
engineering techniques have long existed for calculating parameters through
pump tests, the identification of parameters for regional groundwater
systems must be augmented by regular observations of wells throughout the
regional system. As a result, parameter identification models are being
developed which attempt to derive parameter values for regional groundwater
models through the analysis of long-term historical data.
The task of an identification model can be defined as one of solving
a problem which is the inverse of that of prediction, namely: given the
historical input to a real system and given a model for predicting its
performance, find those parameter values of the model which ensure that
the predicted output is as close to the observed one as possible.
Data Manipulation Codes
The difficulties involved in estimating parameters are closely linked
43
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with the more general issue of data collection for groundwater models. As
noted in the preceding chapter, while models can be run with any amount
of available data, the actual amount and quality of these data directly
affect the reliability of the model's results. The task of collecting
appropriate amounts of accurate data to ensure model reliability thus
implies the need for a fourth class computer code — data manipulation.
These codes can be used in various ways, including specifying data
collection procedures, designing data collection networks, identifying
critical data, and storing and processing data for use in other models.
Additional Comments
Related to all of the models treated above is the question of the
reliability of model outputs. The factors which affect the reliability
of prediction are generally uncertainties about equations, parameters
and data used to describe the groundwater system. Uncertainties in
some data may be caused by unpredictable future events such as rainfall,
demand for water or prices of water. Groundwater modelers are currently
divided over the level of effort which should be devoted to incorporating
uncertainty in inputs into their models. Ways of incorporating parameter
uncertainties into prediction models are being investigated actively at
the present time.
The four major classes of groundwater models — prediction, resource
management, identification, and data manipulation — have been introduced
along with their key characteristics in relatively nontechnical language
in this chapter. This material should be sufficient for understanding
the overview of existing models which is presented in the next chapter
along with project findings which are presented in Chapter 7.
44
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CHAPTER 6
OVERVIEW OF EXISTING MODELS
MTRDDOCTION
One of the major tasks of this project was to conduct a survey of
numerical models related to groundwater management, to provide a basis for
identifying future needs in model development and use. The present chapter
presents an overview of the results of this survey. It is based primarily
on 250 model reports collected from 14 countries as outlined in the
following Table.
While reports collected do not provide a complete inventory of the
existing numerical models which are related to groundwater management,
they probably represent a large percentage of the models currently avail-
able, perhaps as large as 80 percent of the total population. It is
apparent that the major effort in numerical modeling is concentrated in
a relatively small number of developed countries. This, however, does
not reflect the geographical scope of application of these models, which
is much larger. Indeed, developing countries in various parts of the
world benefit from the models through the professional services rendered
to them by international organizations (e.g., FAQ, UNDP, World Bank) as
well as by private and/or government firms which are involved as con-
sultants in water projects around the world.
As indicated earlier, the model reports were presented in the form
of responses to a relatively detailed questionnaire concerning the
identification of the model and the modeler, the purpose of the model,
the conceptual and mathematical framework, the computer code and its
applications, and an evaluation of the model based on the modeler's
experience.
Two hundred thirty-four of the reports have been forwarded by the
modelers themselves. The remaining 16 model reports are based on a review
45
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TABLE 1. SUMMARY OF COLLECTED MODEL REPORTS
Country
U.S.
France
Israel
U.K.
Netherlands
Canada
West Germany
Japan
Australia
Argentina
Spain
Belgium
New Zealand
India
Total
Number of Model Reports
Total
112
47
21
21
13
11
6
5
5
5
1
1
1
; 1
250
Prediction
Flow
44
31
7
18
12
8
4
2
5
3
1
1
1
1
138
Mass
Trans-
port
22
5
7
2
2
1
39
Heat
Trans-
port
5
4
9
Defor-
mation
4
1
3
8
Other
5
1
6
Identi-
fication
9
1
2
1
1
1
1
16
Manage-
ment
21
4
4
29
Data
Manip-
ulation
2
1
1
1
5
46
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of the literature of management models for the past three years prepared
by Y. Haimes and P. Das.
MODEL CHARACTERISTICS
An overview of the surveyed models can, in principle, be based on a
variety of model characteristics. However, for the convenience of the
reader, this chapter considers only those characteristics which are of
common interest to all groups involved, namely managers, model users and
model builders. These characteristics include the purpose of the model
in terms of the categories described above; the water system treated,
whether groundwater alone, or groundwater and surface water; the level of
spatial detail (lumped or distributed type models), and the management task
which the model addresses. The management tasks have been grouped in
accordance with three of the problems outlined in Chapter 4, namely,
water supply (quantity); contamination (quality); and environmental iitpact.
The surveyed models are also reviewed in terms of their accessibility
including documentation, availability to potential users and past applica-
tions. In this context a model is defined as useable if it is fully
documented, available and has been applied to a field case once or more.
Further details on the surveyed models which may be of interest to
technical experts and/or modelers are presented in Appendix A.
GENERAL COMMENTS
Table 2 summarizes the surveyed models in terms of the characteristics
described above. A relatively large number of groundwater models address
various types of water supply (quantity) problems. A smaller, yet still
sizable number of models exists for predicting contaminant levels and
the temperature of groundwater (quality). The environmental impact of
land subsidence is covered by several models, whereas ecosystem impacts
have not been reported.
Only a few models have been developed for coupled groundwater-surface
water systems. Of these the majority are management models, with the
remainder treating flow and mass transport.
Only a few of the surveyed models consider uncertainties in an
effort to provide an estimate of possible error in the output. Similarly,
47
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TABLE 2. OVERVIEW OF SURVEYED MODELS
Model Category
Prediction
Flow
Water
Water &
other fluids
Mass transport
Conservative
Nonconservative
Heat transport
Deformation
Others
Management
Identification
Data manipulation
Total
Number
of
Reports
127
11
20
19
9
8
L 68
29
16
5
250
Groundwater
Quantity
Lumpec
2
2
Distrib-
uted
l!9**b
5*
10*
14*
Quality
Lumpec
2a
*
2
Distrib-
uted
2*e
6e
17**f
17**d
9*c
3a
Environ-
mental
Impact
8
Groundwater & Surface Water
Quantity
Lumped
7
Distrib-
uted
*
4
6*
Quality
Lumpec
l*a
2
Distrib-
uted
1
Environ-
mental
Impact
00
"usable" model in group.
Two or more "usable" models in group.
.Treats waste disposal and reclamation.
Sixteen models treat coupled saturated-
unsaturated systems.
Treats thermal problems 2 of which are
geo thermal.
Two models treat biochemical reactions.
-Treats interface.
Two models treat interface.
Includes 1 frost propagation, 1 coupled heat-mass
transport, 2 coupled subsidence and heat transport
models and 1 general purpose code.
-------
only 12 percent of the models surveyed can be classed as useable. Out of
250 surveyed models only 30 have been completely documented, are available
and have been applied at least once to a field case, and only 13 of
these treat problems other than groundwater flow. This situation seems
to result from restrictions on availability of codes developed by private
and semipublic agencies, poor documentation of codes developed at univer-
sities, and difficulties in applying existing codes to field problems.
The following sections review each category separately.
PREDICTION MODEIS
Prediction models constitute nearly 80 percent of the surveyed models
(199 out of 250). The purpose of prediction models is to forecast spatial
and temporal changes in the movement of water, contaminants, heat and land.
the following diagram shows the distribution of these models.
Distribution of Prediction Models
(69%)
(19%)
(5%X
(4%)
(3%)
Flow
Mass Heat Deformation Other
Transport Transport
138 Reports 39 Reports 9 Reports
8 Reports 6 Reports
49
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A common feature of all prediction models is that their forecasts
are deterministic (one value) rather than probabilistic (a range of
values of varying probability). In most cases the predictions are also
unconditional, implying that the models do not contain any restrictions
on acceptable values or operations. However, some of the prediction
models have provisions for including operating rules as well as constraints
on water levels, water quantity and/or quality. Such models are useful in
predicting effects of alternative policies of groundwater-related management
of water resources.
Some prediction models, especially flow models, contain nonhydrologic
elements such as crop production, and thus can be used to assess the
hydrologic effects of nonhydrologic activities and vice versa. Such
prediction models are also used in conjunction with optimization routines
in management models.
Flow Models
Almost any modeling activity related to groundwater starts with a flow
model. For example, since quality and quantity are intimately related,
flow is an essential ingredient of any water quality or deformation model.
Therefore, many models in other categories contain a flow submodel. As
indicated in Table 2, 127 models handle the flow of water only and 11
models consider the flow of water and some other fluid such as steam in
a geothermal reservoir, air in the unsaturated zone or seawater.
All but two of the flow models are of the distributed type, namely
they have spatial components. Most common are two-dimensional models
which consider the flow in an aquifer as essentially horizontal C95 models).
These models, sometimes referred to as hydraulic or aquifer flow models
have been reported by each of the surveyed countries. They can handle
flow in various kinds of aquifers: phreatic, confined, leaky and nonleaky.
Twenty of them can handle multiple or itultilayered aquifers and some even
contain a submodel of vertical flow through the unsaturated zone (5 models).
The surveyed hydraulic flow models can serve a variety of purposes.
Most of them are capable of predicting the variations in head in aquifers
and evaluating rates of water flow under differing patterns of recharge
and withdrawal. Some also serve special purposes such as predicting the
50
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amount of flow between aquifers and streams (19 models), determining the
flow pattern or the location of boundaries between native and injected
water bodies as well as travel times of water particles (9 models), pre-
dicting the movement of the interface between fresh and salt water (8
models), and determining spring flow, water levels in wells, evapotranspira-
tion and others (5 models). In general, most of these models have been
applied to solving field problems and many of their codes have been
sufficiently well documented and are flexible enough to be utilized by
others.
Less frequent are the 29 models which are three-dimensional or two-
dimensional in the vertical plane which can predict head in an aquifer
as a function of depth. These models are capable of taking into account
the depth of penetration of wells and the configuration of boundaries.
They are powerful in determining flow patterns around wells and surface
water bodies as well as the configuration of the water table in phreatic
aquifers. They can also be used in making a first order evaluation of the
spread of contaminants from disposal or recharge sites or the concentration
of such contaminants in wells on the basis of the flow pattern only. Some
of these models have been applied to field studies and are available.
A few one-dimensional flow models have been used to study flow from
aquifers toward rivers or oceans with approximately straight shorelines.
Some of the freshwater-seawater interface models as well as one of the
groundwater-surface water flow models are of this kind.
Some of the limitations and deficiencies of the surveyed flow models
are worth noting. In contrast to the relatively large number and variety
of models which can handle flow in aquifers and in the unsaturated zone,
only four models have been surveyed which can handle both groundwater and
surface water. The surveyed flow models do not explicity handle flow in
aquifers dominated by fractures, joints or solutions caverns. Neither do
they handle moving boundaries. The major technical difficulties reported
by modelers were obtaining numerical solutions in the case of drastically
varying flow conditions, and trying to find an appropriate compromise
between the desired level of model accuracy and the amount of data and
computer capacity available.
51
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Mass Transport Models
As indicated in Table 2, the number of surveyed mass transport models,
39, is much smaller than that of the flow models, 138. Whereas, flow
models were reported by all fourteen countries which have been surveyed,
mass transport models came from six countries only, mostly from the
United States. Also, while flow models were usually the work of one
individual, the surveyed mass transport models have in at least half of
the cases been developed by a team of two or more. All of the reported
models have been developed during the last five years and many of them
are still undergoing improvements.
Mass Transport models are more complex than flow models in that they
consider quality in conjunction with quantity. In principle, a mass
transport model contains a flow submodel which computes the flow velocity
of the water and thus utilizes these velocities in a quality submodel
which transports the contaminant in the flow field allowing for additional
spreading (dispersion) and transformations by reactions. Under certain
circumstances such as low concentrations of contaminants, flow and quality
submodels can operate independently. In other cases, however, their mutual
effects cannot be separated. Thus, relatively high contaminant concentra-
tions in wastewater or saltwater affect the flow pattern of the groundwater
which in turn affects the movement and spreading of the contaminants,
this requires a more intimate interactive coupling between the flow and
quality submodels. Cnly two of the surveyed models have fully coupled
flow and quality submodels which account for the effects of varying
density upon the flow field.
As indicated in Table 2, there are almost equal numbers of mass trans-
port models which consider contaminant transport by flow only (conserva-
tive mass transport] and those which consider reactions as well (non-
conservative mass transport). The latter include primarily adsorption
and radioactive decay, the mathematics of which is relatively easy. Some
of the multiconstituent models also consider chemical reactions under
simplified assumptions. However, only two of these models handle the
more complicated biochemical transformations of nitrogen compounds which
are important in modeling the effects of contamination by organic waste
52
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products and the efficiency of waste treatment.
The desired level of detail of a mass transport model is of major
importance in water quality planning. Thus, lumped mass transport models
which may consider a large portion of an aquifer as a single unit can be
useful in predicting long term regionwide trends of contamination from
surface sources or by geochemical processes. Unfortunately, only five
such models have been reported. Most of the surveyed mass transport models
are of the distributed type, 22 models of which predict concentration of
contaminants in the saturated zone, 7 in the unsaturated zone, and 5 in
both zones. About half of the distributed models handle two-dimensional
horizontal mass transport, one quarter can handle more complicated geo-
metries, and one quarter are one-dimensional.
Several difficulties impair both the credibility and the efficient
use of mass transport models. A technical difficulty is "numerical
dispersion" in which the actual physical dispersing mechanisms of the
contaminant becomes negligible in comparison to that caused by the
computational scheme. A conceptual difficulty is that of incorporating
the effect of the unsaturated zone on the concentration and arrival time
of contaminants reaching the groundwater. The heterogeneity of this
zone, and the complex transformations undergone by contaminants in this
soil-plant-water-air environment contribute to this difficulty.
There are also difficulties with water quality predictions in the
saturated zone. Typically, horizontal mass transport models are used in
conjunction with, hydraulic aquifer flow models. However, these models
tend to underestimate peak values and thus may fail to predict dangerous
concentration levels in the neighborhood of surface sources of contamina-
tions' and critical arrival times of pollutants in wells. Density
differences between heavy wastewater and lighter groundwater which may
enhance the propagation of pollutants in the neighborhood of large scale
waste disposal sites and the bacteriological aspects of contaminations
have not as yet been adequately treated.
Finally, there are difficulties related to computer capacity and
data requirements. While there are relatively simple and inexpensive
field methods for determining parameters for flow models, no such
cotparable methods have as yet been developed for mass transport models.
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In conclusion, it is fair to say that the existing mass transport
models are adequate for obtaining first order estimates of contaminant
movement.
Heat Transport Models
The temperature of groundwater is usually of lesser importance to
the water resource manager than its chemical or bacteriological quality.
However, heat transport models have recently grown in importance as
underground storage of heat, thermal pollution as an environmental factor,
and exploitation of geothermal energy have become more common.
Heat transport models are conceptually similar to mass transport
models in that a flow submodel is coupled with a heat flow submodel
which incorporates various mechanisms of heat transfer. The problems
faced by heat transport models are similar to those discussed for
mass transport models.
Only nine heat transport models were reported in this survey, five
of which have been recently completed. All of the reported models are
of the distributed type, and all but one deal with the saturated zone.
Three of the models predict the temperature in wells and have been
applied primarily to feasibility studies of heat storage. More recent
•axlels consider coupled flow and heat transport. Two of them handle
temperature as well as vertical or horizontal flow of water and steam
in geothermal reservoirs, one is concerned with the effect of temperature
en evaporation losses, and the remaining three are multipurpose
three-dimensional models. To summarize, at present, for heat transport
models, field application significantly lags model development. There
are only a handful of places around the world where data sufficiently
adequate to provide field validation of the available models have been
collected.
Deformation Models
Unlike the previous models which predict water quantity and quality,
the surveyed deformation models are concerned with the effect of pumpage
or recharge on the deformation of the land surface. Usually the land
surface deformation is computed on the basis of the change in head or
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pressure obtained from a flow submodel under various assumptions regarding
the relationship between the change in pressure and the deformation of
the aquifer.
Eight deformation models have been surveyed in this study. Six of
them predict subsidence or uplift, two also predict lateral displacements.
Four of those predicting subsidence use a hydraulic flow model coupled
with a linear deformation submodel. These models operate with easily
accessible flew parameters and have had many field applications. The
other four models are more detailed and complicated and it is unlikely
that they will be applied to actual field problems in the foreseeable
future.
Other Prediction Models
Recently attempts have been made to standardize computational tech-
niques for prediction models and to broaden the scope of their capabilities.
Six models of this kind have been reported. They include two general
purpose computer codes for flow and transport phenomena, a code for
predicting frost propagation used in the design of roads, two coupled
heat and deformation codes for predicting pressure and temperature in
accumulating sediments or in a geothermal reservoir, and one coupled
heat and mass transport code for predicting pressure, contaminant concen-
trations and temperature in an aquifer.
MANAGEMENT MODELS
All of the surveyed management models deal primarily with engineering
decisions and a single economic or physical objective. Management models
are conceptually more complex than prediction models because they contain
additional aspects of decision making. This introduces more submodels
and data, as well as additional computation.
Usually a management model contains four elements: a submodel for
finding the most appropriate decisions (e.g., location of wells, pumping
ratesl; a submodel for predicting the outcome of a decision (e.g., water
levels,, salinity); a set of rules and constraints on admissible decisions
and/or outcomes (e.g., maximum pumping rates, drawdowns, salinity, water
rights, well regulations); and a so-called objective function which
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evaluates a decision (e.g., cost, benefit, yield).
Twenty-nine management models have been surveyed in the course of this
study. Fifteen of them have been reported by the modelers themselves,
whereas fourteen are based on a review of the water resource management
literature over the past three years.
Groundwater Alone
As Table 2 indicates, models exist for the management of quantity
and quality of either groundwater alone or of both groundwater and
surface water. All of the groundwater management models are of the
distributed type and most of them deal with the management of water
quality in a single aquifer containing a well field. Usually the
objective is to distribute the pumpage so as to satisfy a given demand
at nunimum cost or to maximize benefits from the use of the pumped
water. Other models address decisions for agricultural production,
fiscal policies to encourage efficient basinwide use of groundwater,
and cost-benefit evaluation of collecting additional data.
Only three of the surveyed models deal with the management of ground*
water quality. One of them couples groundwater allocation for irrigation
with salinity control while attempting to maximize the net benefit
associated with water use. The other two consider wastewater disposal
through wells in conjunction with groundwater supply and surface
treatment of wastewater. Unfortunately, only a few of the above models
have been applied to actual management tasks and only one of those is
documented and available for use.
Groundwater and Surface Water
The conjunctive groundwater-surface water management models are
distinct in considering a variety of multicomponent systems such as
resources, supply use, production, and in addressing management tasks at
a regional level. Most of them deal with quantity management and at two
levels of detail; lumped and distributed. One of the lumped models
seeks to optimize the price of water, taking into consideration the
relationship between demand, supply, and price. Other lumped models seek
to optimize development and operation while either maximizing expected
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benefits or minimizing costs. Two of the lumped regional quantity manage-
ment models are actually used for regional management of water resources
in Israel.
Some of the distributed quantity management models are distinct in
treating stream-aquifer interactions and in addressing coordinated multi-
level management. The latter is a recently developed methodology which
can serve the needs of decentralized water resource management. By this
methodology, several independent agencies which administer different
parts of a regional water resources system can enjoy the benefit of
coordinating their activities so as to best utilize the limited water
resources of the region. Another advantage of this methodology is the
decomposition of large scale complex water systems into smaller ones,
while seeking a regionally optimal scheme of operations and/or development.
Cue such multilevel management model is useable.
Finally, quality management of a groundwater-surface water system is
handled by three of the surveyed models. Two lumped models determine an
optimal pattern of pumpage, of wastewater treatment and of resource
allocation so as to meet a desired quantity and quality of the supplied
water at a given reliability level. The third model is distributed and
aims at operating available local surface and groundwater resources in
conjunction with water importation so as to satisfy agricultural water
demand in terms of quality and salinity at minimum cost.
In conclusion, it is fair to say that so far the contribution of
the management models has been primarily in the area of research and
development. Regardless of whether a water resources management system
is centralized or decentralized, it is obvious that existing management
models can in certain cases be useful in enhancing management practices
and in screening decision alternatives. The application of existing
management models to real problems will foster the development of
better techniques to address multiple objectives and nonengineering
decisions.
IDENTIFICATION MODELS
An adequate estimation of parameters is probably the major stumbling
block to efficiently utilizing the already available prediction and
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management codes. Much current modeling effort is directed towards de-
veloping calibration techniques which are both conceptually sound and
computationally efficient.
All of the sixteen identification codes which have been surveyed
estimate parameters related to groundwater quantity only, primarily for
distributed horizontal flow models. Unfortunately, only one of the
surveyed models is both domumented and available. Ten, however, have
been applied to field data at least once.
Two methods of calibration are commonly used. For the indirect
approach, a succession of model outputs is used to successively improve
parameter values. For the direct approach parameter values are computed
from the given input and output data without utilizing a succession of
model runs. Both approaches have been widely applied and most of the
surveyed models find the best values of parameters by optimization
techniques. A few models, however, still employ "trial by error"
methods. The direct approach of calibration is attractive as it usually
saves computer time and its results do not depend on the initial guess
of the parameters. Past difficulties with computer storage requirements
for this method seem to have been resolved by using new mathematical
techniques.
Two identification models are distinct in deriving response coeffi-
cients or functions rather than single parameter values. One of them
is a statistical regression model the coefficients of which link draw-
down to pumpage, the other one, which transforms aggregated inputs
into aggregated outputs is suitable for calibrating lumped parameter
prediction models. Finally, one of the distributed identification models
yields in addition to parameter estimates their standard error and other
statistical characteristics.
Despite the progress made in the development of identification codes,
some basic conceptual and methodological questions require further
attention. These include the definition of "best" parameter values and
the selection of such values. Other issues include the updating of
parameter values as new information becomes available and addressing the
uniqueness and dynamic character of parameter values. To conclude,
although some parameter identification models have been made operational,
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they have not in general been widely applied to practical problems.
DATA MANIPULATION
Each of the model categories reviewed utilized data of various kinds
such as water levels, contaminant concentrations, pumpage, recharge, and
many others. These data, most of which are collected in the field, are
ccranonly placed in primary data files. They are then processed in various
ways such as sorting, interpolation, aggregation, and statistical analysis,
before being placed in secondary data files for use in the modeling
process. Many of these tasks are performed by data manipulation codes.
In addition, such codes, with output that may be in the form of tables,
contour maps, and plots, are used for producing status reports on
groundwater levels and quality in aquifers.
Cnly five data manipulation codes have been surveyed. Two of them
may be of general interest. One handles error detection in groundwater
head data, and the other interpolates between point data and assess its
error. The remaining three codes deal with the retrieval of data fron
groundwater data bases and with the preparation of input data to flow
models. Many of the models discussed above contain special data
manipulation routines for the display of their output.
Of interest is that the United States Geological Survey is operating
a national water data storage and retrieval system (WATSTORE). The
system is operated and maintained through fifty terminals located in
major cities throughout the United States. The system contains, among
others( a groundwater file in which can be stored physical, hydrological
and geological data. A user's guide for the preparation and submission
of groundwater data as well as for the retrieval of such data is in the
process of publication. Steps are currently underway to include in
WATSTORE data on water use in addition to existing data on water levels
and water quality.
MODEL USABILITY
The survey of the existing models contained questions regarding the
state of documentation, availability and past applications of such models.
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Although most of the modelers have responded to these questions, some have
answered just a part of them and some have ignored them altogether. Table
3 summarizes the collected information.
Documentation. Oily 30 percent of the surveyed models have available
a description of the model, a listing of its code and a user's manual and
thus can be considered as fully documented. The percentage of fully
documented models is about the same for the major model categories.
Availability. Cnly 42 percent of the surveyed models are available
to potential users free or at nominal cost. Most of these have been
developed at universities and some at state agencies. Models which have
been developed and documented by the U.S.G.S. are usually available.
Models developed by consulting firms are usually available only as part
of their consulting service. Identification models, which are still
largely in a research stage of development/ are the least available
category of models.
Applications. Sixty-eight percent of the surveyed models have been
applied to a field case at least once. Models developed and operated
by consulting firms as well as state agencies and the U.S.G.S. have
usually been applied many times. Most of the models which have not
been applied in the field come from universities. The applied prediction
models which make up 71 percent of the total, have the greatest rate of
field applications; management models, with 41 percent, have the smallest
rate.
Usability. A model was earlier defined as useable if it is fully
documented, available at no cost, and applied once or more in the field.
Oily 14 percent of all the surveyed models fall in this category.
CONCLUDING REMARKS
In principle the existing numerical models are capable of handling
most groundwater-related management problems, m practice, however,
their successful application to such problems varies from one model
category to another.
Water quantity models, and in particular hydraulic aquifer flow
models, are operational and widely applied. In contrast, coupled
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TABLE 3. STATE OF USABILITY OF THE SURVEYED MODELS
MODEL CATEGORY
Prediction
Flow
Mass Transport
Heat Transport
Deformation
Others
Management
Identification
Data Manipulation
TOTAL
Percent
NUMBER OF MODELS
TOTAL
138
39
9
8
6
29
16
5
250
100
DOCUMENTED
41
11
4
3
8
5
3
75
30
AVAILABLE
61
17
4
2
4
10
4
2
104
42
APPLIED
106
23
4
6
2
12
10
5
169
68
USABLE
22
3
1
0
2
3
3
1
35
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groundwater-surface water flow models are scarce and models of flow in
aquifers with secondary porosity such as karst are lacking.
Water quality models, which are more difficult to develop, have
been developed in only a few countries. Despite some field applications
of distributed water quality models, their utility is lessened by a
variety of difficulties. On the other hand, lumped water quality models,
which are easier to develop and which could be useful in evaluating
long term regional trends, are scarce.
A number of management models have recently been developed which
primarily address engineering decisions and a single econanic or physical
objective. While most of these models have been developed in the United
States, only in Israel, and to some extent, France, are management models
utilized on a routine basis.
The reliability of prediction and management models would be improved
by better parameter estimation. While relatively simple and inexpensive
field methods exist for the evaluation of parameters for aquifer flow
models, such methods are not available for water quality models. At the
same time, regional identification codes need further conceptual and
technical improvements before they can become operational.
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CHAPTER 7
GAPS IN MODEL APPLICATIONS TO MANAGEMENT NEEDS
The previous chapter presents the findings of the project related to
the existence and degree of development and application of models for
various management problems as they were reported by model developers.
The central purpose of this chapter is the presentation of findings
related to barriers to the efficient use of such models in groundwater
resource management as they are viewed by model users.
SOURCE OF INEX)FMATION
The findings contained in this chapter are the result of an intensive
effort on the part of the project staff and steering committee to gather
information on "the needs of managers and the difficulties of technical
experts in applying models to management problems. While an attempt was
made to address some managers directly, the major portion of this
information was obtained from those individuals identified as technical
experts. These include persons active in engineering/ planning, and
consulting.
The technical experts were surveyed extensively by mail through
short questionnaires, and more intensively through workshops in the
United States and Europe. The workshops involved the discussion of the
participant's specific problems, tasks related to those problems, and
the kinds of models needed to perform those tasks. The participants
were divided into small groups which focused on difficulties both in
the available models and in the application of models to management
problems. The exchange of opinions during these group sessions proved
to be the project's most valuable source of information concerning gaps
in modeling and model application.
In addition to the surveys of technical experts, supplementary
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information on gaps was drawn from a section on evaluation and recommenda-
tions which was included in the questionnaire sent to groundwater modelers
throughout the world. A more detailed description of the process by
which information was collected is to be found in Chapter 3 of this report.
For the purpose of identifying gaps, four major categories have been
defined under which the various issues regarding models and their
applications have been ordered. The first of these categories,
accessibility of models to users, was deemed to be the most serious
barrier to the successful use of models to solve management problems.
The other categories, in order of importance, are: lack of conrunications
between managers and professional experts, inadequacies of data, and
inadequacies in the models.
UMer each of the categories a series of topics is discussed. These
topics emerged as major concerns of those involved in using models in
groundwater resource management. Different groups had diverging opinions
of the real nature of the needs of management and the deficiencies of
models, and thus the relative importance of the various areas of concern
was difficult to evaluate. The following discussion presents consensus
where it emerged and, where consensus was not reached, attempts to present
the important positions and to attribute these positions to specific
groups where possible.
ACCESSIBILITY OF MODELS TO USERS
Of all the areas of concern identified over the course of the project,
difficulties in gaining access to models appeared to be the most serious.
Individuals needing models are often not aware of what models are available
to them, nor do they know where to turn to find this information. While
the project did not reach a clear consensus on priorities, it can be
safely stated that all of the factors affecting accessibility which are
discussed in the following paragraphs were considered to be of major
concern.
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Model Documentation
The lack of adequate documentation of existing models was repeatedly
identified in project workshops and questionnaires as a major deficiency.
Proper documentation should include a description of the model, a listing
of the code, and a user's manual. The first of these provides a brief
description of a model's general characteristics, capabilities, and
range of possible applications. When such documentation exists, it is
typically not written in a consistent format and is scattered throughout
the literature. Consequently, potential users often have little informa-
tion concerning the models which are available. This report, through
its catalog of existing numerical groundwater models, should provide a
first step toward filling this documentation gap.
Documentation should provide an easy means of running the model on a
computer. Unfortunately, a listing of the model's code is not always
easily accessible. The documentation should also provide specific
technical instructions that may assist in the utilization of the model's
code. Unfortunately, a satisfactorily detailed user's manual which would
allow a model to be applied by individuals other than the model developer,
usually has not been prepared.
A number of reasons have been put forward for the inadequacy of present
documentation. The most important among these is that documenting a model
is the last step in the modeling process, and is in fact not necessary for
the immediate solution of the problem for which a model is built.
Typically, most available funds are exhausted in the building of a model,
and little money may be left for the preparation of a user's manual.
Furthermore, documentation is expensive and time-consuming, and is not
readily written by model builders who may have little training or interest
in detailed expository writing. Finally, modelers may have insufficient
incentive to document since they may be reluctant to expose particular
features, uncertainties or assumptions which the models may contain.
It is significant that the quality or extent of model documentation
tends to vary with the type of institution in which model development
takes place. At present within the United States, the most complete
documentation of groundwater models is available from the U.S. Geological
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Survey, a federal agency which considers as part of its mission to develop
and distribute models for the analysis of field problems. Private con-
sulting firms, on the other hand, develop proprietary models for specific
clients and generally do not find it in their interest to distribute their
work widely at low cost. The least extensive documentation is developed
in the university ccranunity where much modeling is commonly undertaken in
conjunction with doctoral programs or research grants which generally
do not require the preparation of user's manuals.
Model Distribution
Closely linked to documentation is the distribution of models; a
well-documented model must be publicized and distributed to be of any
value to prospective users. At present, there is no readily available
service for the systematic collection and dissemination of information
on models as they become available or as they are applied to different
situations. While this project represents a first step toward filling
this gap, no provision has been made for continuing a service to model
users on a periodic and updated basis. Moreover, information on the
existence of a computer code is not enough to make it available to a
potential user. Public funds spent on model development are wasted if
public agencies in need of such codes have no access to them.
What seems necessary to solve this problem is a central facility or
"clearinghouse" which would be responsible not only for the collection
of information pertaining to models, but would also engage in an active
program of making this information available to users. It is desirable
to establish such a center on an international basis. The development
of models is expensive; unnecessary duplication of effort as well as
international cooperation would be promoted by creating an international
information center. Perhaps more importantly, such a center is most
needed by those developing nations which have little modeling expertise
of their own and limited resources upon which to draw.
An information facility of this nature might be most appropriately
lodged in some branch of the United Nations, or it could become the
responsibility of some other scientific organizations which is inter-
nationally based. If an international center should prove infeasible,
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such information centers should be encouraged on a national basis. Within
the United States any of several agencies of the federal government might
be appropriate for this purpose; alternatively a university or non-profit
organization could house such a facility. Unfortunately, a number of the
potential institutions which might house an information center have been
involved in model building; this makes them subject to bias. Whether
true or not they vjould be suspected of promoting their own models. The
U.S'. Geological Survey, one agency which might house such a service, is
reluctant because of its own involvement in model building.
One problem inherent in the idea of a central facility for the
collection and distribution of model information is the potential conflict
with consulting firms. The precise functions of the facility would have
to be carefully considered and defined if it is to complement rather than
ocnpete with existing institutions.
Training of Model Users
Although many project respondents laid strong emphasis on gaps in
documentation and distribution, others expressed the view that the closing
of these gaps will not make models more accessible. Rather, these actions
must be coupled with the training of those professionals who use models.
Access to models is often inhibited by limited understanding on the part
of technical experts concerning the models that are available, which of
those models are best suited to particular problems, and how the
appropriate models, once identified, should be applied or modified to
fit their needs.
Beyond the consideration of a variety of available models, once a
user has chosen a particular model he must understand; 1) its structure,
2) underlying assumptions, and 3) its limits if he is to ensure
successful application of the model to the problem under study. Because
model builders cannot possibly be involved in all the applications of
their models, training of technical personnel for this job is necessary.
The lack of field personnel with adequate training in the application
of models is due at least in part to the rapid development of modeling
in recent years, a process with which many field personnel have not managed
to keep up.
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Universities have taken steps to improve the education of professionals
in the use of models; training programs have been extended to include
"short courses" and seminars for those field practitioners who wish to learn
more about the applications of models. Such programs, particularly
those directed toward field practitioners, should be encouraged and
expanded.
Ideally, technical experts trained in the use of models should be
part of the management organization which is responsible for solving the
problems to which the model is to be applied. In this case there may be
the greatest possible incentive for the expert to use the model properly,
and there is also a good possibility that the model will be updated and
improved. Ihe use of outside consultants may, however, be more reliable
and efficient for an agency which finds it difficult or undesirable,
especially for financial reasons, to maintain a skilled in-house staff
of modelers and related experts.
Within the United States, the U.S. Geological Survey has filled the
role of providing centralized groundwater modeling expertise to a variety
of public agencies at state and local levels. The scarcity of trained
personnel is a more acute problem for the developing world. In fact, the
lack of adequate expertise and technical knowledge appears in many cases
to be the most serious limiting factor in the distribution and use of
models in the Third World.
CO*«JNICATIONS BETWEEN MANAGERS AND TECHNICAL PERSONNEL
Communication issues have consistently emerged as important in improving
the utility of models for addressing groundwater management problems. It
is far easier to identify communications problems than it is to propose
measures for their solution. In fact, such problems cannot, by their very
nature be "solved;" they can only be ameliorated. Lack of adequate
communications is a widespread source of difficulties in model application
and may take many forms. The following test presents a range of topics
which have consistently emerged as major themes in discussions of these
problems.
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Model Credibility
One of the more common and better publicized factors which has
hampered the utility of models in groundwater management, is the lack of
confidence on the part of managers in models as decision-making tools.
This credibility gap may in sane cases be more apparent than real.
Managers must respond to a great many political pressures and consequently
may have reasons for not wanting to use a model even if they have confidence
in its output. In such a situation they might find it easier to ignore the
model than to overcome political barriers to its use.
Where credibility is indeed a problem, one of the most important
reasons for it may be the fact that groundwater modeling is becoming an
increasingly sophisticated science which has developed rapidly in recent
years. Many persons currently occupying management positions are thus
unfamiliar with modeling techniques and have no feel for the application
of models to their particular problems. While managers do not have to
be well-versed in the technical details of models in order to accept
them, they do need some appreciation of the conceptual framework and the
inherent capabilities, limitations, and assumptions of models.
This lack of understanding on the part of management gives rise to
what is known among professionals as the "black box" phenomenon. While
some managers are willing at the outset to accept practically any model
output uncritically, this initial enthusiasm often leads to disappointments
and consequent distrust. Often, however, a manager will tend to view
models as technological mysteries which operate in unknown and unknowable
ways. As a result, a manager may reject models as machines which
unnecessarily complicate, and may even threaten his job. Managers may
also distrust model outputs that contradict their intuitive preconceptions
about the phenomena under study.
A lack of trust in models by managers may, on the other hand, be due
to causes other than insufficient understanding. The fault may lie with
the professionals who build and apply models. One serious problem of this
kind has been the "overselling" of models, whereby modelers have claimed
that their models can perform more than is actually possible, or have
otherwise misrepresented the true capabilities of models. Closely
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related to this problem has been the practice of "overmodeling," which is
the application of a model which is too sophisticated for the task being
performed. Both overselling and overmodeling have led to understandable
disillusionment on the part of managers, and to the consequent impression
that models do not produce efficient, reliable, or useable results for
decision-making purposes. A manager who is responsible for justifying the
allocation of limited funds will naturally be cautious about using models
if he has the impression that they constitute a risky experiment.
Often a barrier to the more effective utilization of models is their
output. Managers need to have model results presented in a way that is
both meaningful and compatible with decisions that nust be made. The
uncertainties contained in various decision alternatives are especially
important to assess. The form of the output is also important. Careful
use of graphics and other displays may greatly enhance the utility of
model results.
Education of Managers
Technical experts often state that their problems in applying models
would be greatly reduced if managers would learn more about modeling.
While this is no doubt true, it may place unfair blame on managers. It
is equally tame that modelers and technical experts often fail to convey
clearly to managers model results, the range of applicability, the
limitations, and the degree of reliability of models. Unfortunately, the
technical expert's abilities in inter-personal comrainication are often
thwarted by his lack of attention to management needs and by the use of
technical jargon. Terms such as "dispersion coefficients" and "piezo-
metric heads" may be trade words of the modeler but are essentially
meaningless to many managers.
While in general it is not reasonable to expect managers to enroll in
courses in modeling, it is possible for managers to learn something about
models through, more active participation in the application of models to
their problems. Involvement of managers in discussions of the relative
iitportance of model inputs and of the necessity of defining constraints
should lead to benefits of two sorts. First, the accuracy and value of
the model output itself is likely to be iitproved, and second, the manager
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is more likely to make increased use of its output.
Problem Definition
The concise statement of a problem is a prerequisite step in that
problem's solution. However, the precise formulation of a management
problem can be an extremely difficult task. Both managers and technical
personnel often experience difficulty in isolating those factors which
are critical for the application of a model to a problem and in
formulating those factors in the precise terms required by models.
Nonetheless, the way in which a problem is defined affects how the
professional expert approaches a solution. Thus, what general type of
model is chosen — provided, of course, that a model is deemed a proper
analytical tool in the first place — is determined by the problem
definition. Improved problem definition is likely to result from more
interactive participation of managers and technical personnel in model
design and application.
Acceptability of Management Models
Models for groundwater resource management ranked second in priority
to prediction models among the needs expressed by the technical modeling
experts surveyed by the project. Such models can be a productive method
of gaining a better understanding of the system under study. Managers
often find it difficult to state their objectives explicitly and quanti-
tatively because of the multitude and noncommensurability of such objectives
and because of political and institutional constraints. Similar difficul- ,
ties preclude managers from utilizing the outputs of such models. Nonethe-
t
less, the potential utility of these models is great; the frequent requests
for more management models indicate a growing interest in their application.
Models in the Political and Legal Context
Models have become widely accepted and quite useful as tools for
making engineering decisions. However, with the possible exception of
Israel and France, models have not yet achieved great acceptance in the
formulation of public policy in most countries. There are several reasons
for the failure of policy-makers to utilize models. Individuals at higher
71
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levels of decision-making where policies are formulated often have less
familiarity with models than the operations managers who use them for
engineering decisions. There may also be institutional obstacles to the
transfer of model-based decisions to policy decisions.
Model results may becone embroiled in the inevitable conflicts that
accompany matters of policy choice. In the United States many of these
conflicts are resolved either politically or in the courts. The
difficulties of using models as evidence in a court of law vary with the legal
system; within the United States the legal system is not homogeneous.
Much legislation regarding water is formulated at the state level; states
differ on issues so apparently simple as the definition of groundwater.
Furthermore/ judges and lawyers alike are generally unfamiliar with the
limits and capabilities of models, as well as with the technicalities of
the problems which warrant model use. Resulting uncertainty makes the
presentation of model results in court a generally risky and undependable
undertaking.
Perhaps the most important factor inhibiting the effectiveness of
models in the legal context is an apparently fundamental incompatibility
between the models in their present state and the nature of the evidence
required by a court of law. As mentioned earlier, models are built upon
calculated assumptions and parameters at which a range of acceptable values
may be given. In the courtroom, however, this lack of definitive output
provides ample grounds for questioning the reliability of the model in
use. An additional drawback is that technical witnesses are often un-
schooled in oourtroon techniques or in the convincing rebuttal of objections
to the models which are bound to be raised by skilled lawyers.
DEFICIENCIES IN DATA
Inadequate or insufficient data were identified by many project re-
spondents as being an important limiting factor in the use of models for
groundwater resource management. While problems related to data are
unquestionably of significance, it would also appear that data problems
may obscure other difficulties in model use. A major reason for the
emphasis on data among project respondents is the fact that data are
frequently the largest single factor influencing the cost and benefits
72
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of losing a model.
Data Collection
Data receive a great deal of attention in part because they are recog-
nized as the key factor limiting the kinds of models that can be applied
to a problem and the degree of reliability of the model output, and
because the acquisition of data on groundwater systems is a relatively
expensive undertaking. In determining whether insufficient data are a
real barrier to the successful application of a model to a problem, it
is necessary first to determine the degree of accuracy that is required
in the solution of the problem. In many cases it is not necessary to
have highly accurate information to answer simple questions about a ground-
water system. This is particularly true in regard to the initial develop-
ment of an aquifer. As development proceeds, the degree of sophistication
and accuracy of the model becomes more important. At the same time the
amount of data available about the groundwater system will, or at least
should increase.
In short, it is not fair to say that inadequate data preclude the
use of a model. Nonetheless, these constraints may be serious. An
important observation regarding data is that the progress in the use of
computers to simulate groundwater systems has not been accompanied by
parallel developments in data collection techniques. Data on groundwater
systems are still collected largely by drilling wells — a costly and
time-consuming activity. Improved methods of data collection would
unquestionably be of great value to the management of groundwater and '
would probably significantly reduce the costs of applying models.
An important process in data collection is the determination of which
data are necessary to improve the reliability of model output. Thus,
after a model has been run, it should be tested through sensitivity analysis
in an effort to discover which are critical data to a particular applica-
tion, that is, to discover what data most critically affect the model
output. The results of this sensitivity analysis, coupled with the value
of the expected improvements in model results, will determine what data
are necessary to be collected for improving the model analysis.
73
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Parameter Identification Models
Closely related to collection of the input data is the determination of
model parameters. These parameters are required for the calibration and
validation of a model prior to its application to a particular field
problem. A relatively new focal point of modeling research has been the
development of models to deal specifically with parameter identification,
or to solve what is technically known as the "inverse problem."
Considerable disagreement exists concerning both the reliability and
utility of these models. On the one hand, seme researchers maintain that
expensive data collection efforts and time-consuming trial-and-error
procedures could be circumvented by the development of reliable direct
methods for parameter identification. Others feel that more effort should
be directed toward the determination of parameters through field tests.
In general, existing solutions to the inverse problem leave something to
be desired — and at present do not exist in a sufficiently sophisticated
form to allow their widespread use.
Data Manipulation
Another relatively new kind of model has been developed in an effort
to design optimal data networks and data banks. Such models, as well as
data manipulation codes, are particularly appropriate for situations in
which long-term, comprehensive management of groundwater resources is
envisioned. Data manipulation codes can also contribute to modeling
efforts where large amounts of data already exist and require efficient
organization and processing to prepare model inputs.
In spite of the frequently expressed needs concerning data, models
for data manipulation were not often requested by technical experts in
the project surveys. This may be due in part to an insufficient under-
standing of the models' potential utility, or to a lack of awareness of
the models' existence. It is also possible that many professionals
concerned with solving groundwater management problems, particularly
those with consulting firms, must provide answers according to a demanding
or short-term schedule. They thus have neither the time nor financial
resources to be concerned with additional data collection which may be
74
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necessary for the long-term management of groundwater systems.
Data Storage
As groundwater resources are increasingly developed, a considerable
amount of data are amassed. These data are often collected by different
agencies for a broad range of purposes, some of them totally unrelated to
the management of the resource. Nevertheless, these data have great
potential value for groundwater management both in terms of the description
of the physical system and the history of its response to development.
Thus, apart from programs for the design of data collection networks and
the manipulation of data, there are also problems involved in the proper
storage and retrieval of various kinds of information pertinent to ground-
water management.
For this reason, it may be useful to have a centralized facility for
the storage and retrieval of this information. Within the United States,
the Water Resources Division of the U.S. Geological Survey has undertaken
to develop such a central facility and to catalog the information for
retrieval by interested agencies. Other countries may also find it useful
to develop such facilities for the inventory of resources and the
monitoring of their development.
A word of caution regarding data banks is in order. Experience has
shown that some care must be taken that such facilities not become an
expensive "dumping ground" for information. Some sort of screening of
data must be undertaken to assure that they are both relevant and reliable.
To this end, guidelines must exist on the kinds of data which should b6
stored and on standards for their validation.
Simple versus Complex Models
Disputes over the relative merits of using simple or complex models
to solve problems are not unconmon among those involved with groundwater
management. It would appear that the level of sophistication of a
model applied to a specific problem will be determined largely by the pre-
existing constraints upon that problem. As a rule the dominant constraint
is data, or from another point of view, the costs of acquiring data.
75
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There are of course other possible constraints, such as lack of credibility
of models to managers or the time in which the problem must be solved.
In some cases simpler models may be justified. In others the
technical expert may cctnpmid.se by opting for simple models in the initial
stages of analysis, and then progressively escalating to more complex
models to reach more sophisticated levels of problem understanding, when
economically justified. In any case situations should be avoided in which
existing models preclude improved data collection or available data hamper
the development of new models.
DEFICIENCIES IN MODELING
A great deal of energy and resources have been directed in recent
years to the field of groundwater modeling by government agenices,
universities, and consulting firms. As a consequence, there are relatively
few kinds of models that are both urgently needed and missing or
seriously deficient. There are, nonetheless, areas where improvements in
existing models are warranted, development of new models deserves further
discussion and further basic research regarding models is desirable.
Improvements in Existing Models
Respondents to the model surveys consistently identified several areas
in which existing models could be improved for management applications.
The transferability and flexibility of codes is often a barrier to utiliza-
tion of models. A model, which is suitable by other criteria, may not
be used because its code is not easily transferred from one computer to
another or because its code is not easily integrated with other existing
codes. Other barriers include computer storage and time requirements,
and the instability, flexibility and utility of outputs. With proper
effort, the codes of many existing models could be improved so as to
overcome many of these problems.
Prediction Models
Prediction models are well developed and considered to be reliable
for most purposes, particularly the simulation of groundwater flow.
During the course of the project, survey respondents frequently encourage
76
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the development of models that do in fact already exist. The fact that
the existence of these models was not known to many technical experts
highlights the problems discussed earlier in this chapter concerning the
lack of accessibility of models to potential users.
Nevertheless, in spite of the relatively advanced level of development
of prediction models, certain kinds of models are in fact missing or
unsatisfactory. The use of the word "unsatisfactory" introduces a strong
element of professional judgment into the identification of those model
types which require further refinement. An attempt has been made here to
find whatever consensus may be reached in such matters.
A great many project respondents expressed a desire to have models
which fully integrate subsurface flow, and flow through the unsaturated
zone. Such models do exist, but there is some dispute over their
success in describing these phenomena and their ease of application.
Models which describe flow and mass transport through media of secondary
permeability, such as the fractured or karstic formations, were also
identified as missing. Such models would be extremely useful in certain
regions, and there is general agreement that existing solutions to the
problems are inadequate.
In general, the unsaturated zone is a problem area. Models of un-
saturated flow have been built, but they are not yet universally regarded
as adequate. A complete understanding of the movement of pollutants in
the unsaturated zone is lacking and of considerable importance. As
previously noted, such models may have to await improved scientific
understanding of the physical phenomena involved.
Contaminant transport models that include chemical and biological
reactions are needed. Such non-conservative transport models are currently
being developed, but they have not been adequately tested, at least in
the opinion of some professionals.
Finally, models describing the flow of two immiscible fluids are felt
to be missing for the groundwater profession. These models would be
particularly useful for the analysis of the effects of waste disposal on
the groundwater regime. The petroleum industry has conducted extensive
research in this area, as well as developed sophisticated models of the
process. These models may need to be adapted for groundwater problems.
77
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Stochastic versus Deterministic Models
An important issue in the current discussions of approaches to modeling
is whether models of groundwater systems should contain randomly
fluctuating variables known technically as stochastic inputs. While in
recent years some models have been developed which contain stochastic
inputs, particularly for variables such as recharge, model users disagree
on the overall need for stochasticity in groundwater models.
Professionals arguing against the basic need for stochasticity main-
tain that the groundwater system acts to dampen these inputs to such an
extent that their effects are negligible. They further maintain that the
data available for many models is not sufficiently accurate or complete
to justify a stochastic approach. Other model users, in contrast,
point out that stochastic inputs may be extremely valuable in some
situations, such as closely connected stream-aquifer systems and arid
regions where a major portion of the 100-year recharge may come in a
single season. Furthermore, stochasticity may be an important attribute
of model parameters. Most experts, regardless of which side of the
argument they support, agree that stochastic inputs are not adequately
handled by existing models.
General versus Specific Models
There appears to be little consensus among model users on the value of
. "generic models," or models which are intended for application to many
different problems. While in theory such models are desirable, in
practice they are difficult to develop and susceptible to misuse. To
be utilized effectively, generic models ought to be relatively simple
and well documented, since as the models become more complex, it becomes
difficult for the uninitiated user to understand and use them properly.
Generalized models may, however, be rather cumbersome and a model user
may consequently prefer to modify a simpler model to a new problem.
This can often be accomplished with relative ease, at low cost, and in a
reasonable amount of time.
78
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The Role of Analog and Hybrid Models
The focus of this report is on numerical models which are now almost
universally preferred for solutions to management problems demanding a
more sophisticated approach than can be provided by simple analytical
models. However, two other kinds of models are available: analog
models and hybrid models.
Analog models were the first kinds of models of groundwater systems
to be developed, and although they are no longer widely used for manage-
ment, it appears that they still have a role to play in education. They
are useful, not only for classroom purposes, but also for explaining
groundwater phenomena to groups involved in or affected by water manage-
ment decisions.
The coupling of an analog model, usually a resistance-capacitance
network, with a digital computer to create a hybrid model can give
excellent results. Fran the standpoint of performance, hybrid models
may be preferable to purely numerical solutions for such problems as
coupled surface/subsurface flow. The technological improvements in
digital computers has outstripped the improvements in analog and other
calculating techniques.
Institutions for Model Development
Currently, models are being developed in several different institu-
tional contexts including universities, consulting firms, and government
agencies at a number of levels. Such dispersal of modeling activities ,
inevitably leads to sane duplication of effort. This duplication could
be reduced, if not eliminated through better description of existing models
and current modeling work in the literature. Qi the other hand, the
diversity of types of organizations involved in modeling work is generally
viewed as a strength in that the differing needs and approaches of various
institutions probably encourage greatly the development of new methods
and modeling techniques which in turn may lead to increased overall
efficiency. Modeling involves the education of a group of technical
experts. This widespread activity generally leads to better education of
the modelers.
79
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Basic Research and Model Development
The fact that certain types of models have not been developed or are
not considered reliable may be caused by factors not intrinsic to the
models. Rather, the underlying theory concerning the systems to be
modeled may not yet have been adequately described. In other words,
there is a gap in our scientific understanding of certain physical and
methodological phenomena. This gap will have to be filled through
further observation of the phenomena in question and the development of
adequate theories to describe them. Once these phenomena have been
described, the incorporation of the necessary equations into models
should provide to be a tractable problem.
There is not complete agreement about where these research gaps lie.
However, four areas of particular concern did emerge during the course of
the project: 1) an adequate description of the kinetics of chemical
and biological processes; 2) the movement of pollutants through the
unsaturated zone; 3) the quantification of management objectives; and
4) better parameter methodologies. Some of these gaps may be filled by
a transfer of knowledge from other disciplines rather than by new
research.
ESTABLISHING PRIORITIES
The preceding sections of this chapter have presented in a discursive
manner the findings of this project and have outlined some general
conclusions concerning the difficulties and gaps in the use of models for
groundwater management. Clearly, many of the problem areas that have
been identified are interrelated; attempts to reach solutions should be
pursued on a variety of fronts. On the other hand, it is not possible
to move toward solutions on all fronts simultaneously. Sane priorities
must be established in order that the most serious problem areas may
be addressed first. The recommendations of the project are presented
in Chapter 2 of this report and reflect basic priorities as determined
by the project steering committee and. staff.
The intent of this report has not been to further scientific research
or to improve upon existing technologies. Rather, the central focus of
80
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the project has been to increa.se the benefits to be derived from
improved groundwater resource management, it is in this light of improved
resource management that this state-of-the-art evaluation of groundwater
models has been undertaken, and the project's recommendations are
directed primarily toward this goal.
81
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APPENDIX A
REVIEW OF SURVEYED NUMERICAL MODELS
Introduction
The objective of this review is to familiarize the technical reader with
the essential conceptual and mathematical details and the state of usability
of each of the surveyed models. The information is discussed within the
framework of the model taxonomy presented in Figure A-l and is based on the
following descriptors:
Systems
Processes
Purpose and/or Output
Geometry
Method
Special Features
Documentation
Availability
Past Applications
Most of the information is contained in a series of 26 tables which are
summarized in Figure A-2. Ihe order and form of presentation vary slightly
from one model category to another. In general, the level of detail in-
creases with the complexity of the models. A descriptive summary of each
model category follows.
PREDICTION MODELS
Conceptual framework.
•flie surveyed prediction models serve the purpose of predicting the
state of a single or multiphase hydrologic system, one phase of which is
82
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PREDICTION (200)
FLOW (138)
SINGLE PHASE (127)
SATURATED (107)
jumped (2)
_Hydraulic (84)
_single aquifer (64)
joultiple aquifer (20)
_Hydrodynamic (21)
2 dimensional (13)
3 dimensional (8)
JJNSATURATED (3)
SATURATED- --,,
NSATURATED UJ;
SUBSURFACE-SURFACE (4)
MULTIPHASE (11)
TRANSPORT (39)
__LUMPED (5)
1 DISTRIBUTED (34)
CONSERVATIVE (17)
NONCONSERVATIVE (17)
HEAT TRANSPORT (9)
DEPCPMaTICN (8)
OTHERS (5)
(29)
IATER (13)
_QUANTITY ( 10)
JQUALITY & QUANTITY ( 3 >
GROUNDWATER AND SURFACE WATER (16)
_QUANTITY (13)
_QUALITY & QUANTITY (3)
IDENTIFICATION (")
' - DATA MANIPULATICfl (5)
(The number in parentheses indicate the
number of model reports)
REFERENCE
TABLE
A-l
A-2a
A-2b
A-3a
A-3b
A-4
A-5
A-6
A-7
A-9
A-lOa & b
A-ll
A-13
A-15
A-17
A-19
A-20
A^la & b
A-22
A-24a & b
A-26
Fiqure A-l. TfXOKIW OF SURVEYED MXELS
83
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A-l. Single Phase Saturated Flow - Lumped Models
A-2. Single Phase Saturated Flow - Hydraulic Flow Models ~ a,. Single Aquifer
tu Multiple Aquifer
A-3. Single Phase Saturated Flow^Hydrodynamic Flow Models-a. 2-Dimensional
b. S^Dimansional
A-4. Single Phase Uhsaturated Flow Models
A-5. Single Phase Saturated-Uhsaturated Flow Models
A-6. Single Phase Subsurface-Surface Flow Models
A-7. Multiphase Flow Models
A-8. The Present Status of Surveyed Flow Models
A-9. Lutrped Mass Transport Models
A-10. Distributed Conservation Mass Transport Models-^a. Single Homogeneous
Phase
b. Single Nanhonogeneous
Phase
A-ll. Distributed Nonconservative Mass Transport Models-Single Honogeneous
Phase
A-12. The Present Status of Surveyed Heat Transport Models
A-13. Sunroary of the Surveyed Heat Transport Models
A-14. The Present Status of Heat Transport Models
A-15. Deformation Models
A-16. The Present Status of Deformation Models
A-17. Other Prediction Models
A-18. The Present Status of Prediction Models
A-19. Groundwater Management Models: Quantity
A-20. Groundwater Management Models; Quality and Quantity
A-21. Conjunctive Groundwater and Surface Water Management Models: Quatity-
a. Lumped
b. Distributed
A-22. Conjunctive Groundwater and Surface Water Management Models:
Quantity and Quality
A-23. The Present Status of Management Models
A-24. Identification Models - a. Direct Calibration
b. Indirect Calibration
A-25. The Present Status of Identification Models
A-26. Data Manipulation Models
Figure A-2. LIST OF TABLES
84
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usually moving groundwater. Other fluid phases comprising the system may be
either mobile or immobile, yet the terms single or multiphase pertain to the
mobile phases only. A fluid phase is referred to as homogeneous if its
density and viscosity are uniform in space. Otherwise it is nonhomogeneous.
The processes described by the prediction models include flow of fluid,
transport of mass and/or heat, and deformation. Transport processes
are nonconservative if transformations by reactions and phase change are
involved; otherwise the processes are conservative. Immiscible transport
occurs by convection alone, miscible transport occurs by convection with
dispersion and/or conduction, as well. Processes may be defined as either
steady or nonsteady. Mass, heat transport, and deformation are usually
considered as nonsteady.
The spatial domain in which the processes occur may include the
saturated zone, the unsaturated zone and/or the zone of surface water. The
subsurface part of the domain is heterogeneous with regard to the hydrologic
parameters, unless otherwise stated. It may also be anisotropic. The
external boundaries of the domain are considered to be immobile unless
otherwise specified. The representation of the spatial domain may be
lumped or distributed. In the later case the domain is considered as an
assembly of discrete interconnected cells or blocks. Sources and sinks of
fluid volume, mass or heat, if present, are aggregated over a cell and/or
over a time step if the process is nonsteady.
The comnon output of a prediction model includes values of state
variables, such as head for flow models, head and concentration of consti-
tuents for mass transport models, head and temperature for heat transport,
and displacement of the ground surface for deformation models. Additional
output variables for special purpose models are noted in the tables. The
input and output of all prediction models are deterministic. The majority
of the models pertain to nonsteady processes. Each transport model in-
cludes a flow submodel. Figure A-3 summarizes the tasks which the surveyed
distributed prediction models can address and relevant typical outputs.
Efathematical framework.
The output of a prediction model usually results from solving field
equations under given boundary and initial conditions. The field equations
85
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CD
Area
General
Stream-aquifer
relation
Flow Pattern
Interface
(fresh-salt
water)
Free surface
Well per-
formance
Geothermal
reservoirs
Deformation
of land surface
Aid in manage-
ment
Water & crop
relationship
Accumulation
of sediments
Flow in Karst
Frost propa-
gation
Prediction &
calibration
Total
Typical
Output
Head
concentr.
Temperature
combinations
of the above
Head &
flow
Streamlines,
fronts, travel
times
Position
Dispersion
zone
Position
Drawdown
concentr ».
Temperature
Pressure,
saturation
temperature
Subsidence
Subsidence &
lateral dis-
placement
Response coeffic
Head & flow
Evapotranspir-
ation
Pressure
temperature
Discharge
Frost
line
Error
>er
of
Mod-
els
7
ii
4
•)
19-
9
i)
2-
- 8
• 6-
1
4
4
f>
2
5
4
1
1
, 1
5
193
Distribution by Model Categoric*
Flow
Single Phase
Un-
sat.
2
1
3
Sat.
57
16
7
2
;
_5..
4
1
5
105
Sat.
Un-
sat.
9
1
3
13
Sub-
sur-
face
& sur
1
3
4
Mul-
ti-
Phase
}
2
6
1
1
11
Mass Transport
Conservative
Homogeneous
Un-
sat.
3
3
Sat.
9
9
Sat.
Un-
sat.
2
2
Non-
Homo-
gene-
ous
2
1
3
ttonconserrative
Homogeneous
Un-
sat.
4
4
Sat.
10
10
Sat.
Un-
set.
3
3
Heat Transport
Conservative
Un-
sat.
1
1
Sat.
3
3
1
7
Non-
con-
lerva-
tive
1
1
De-
for-
ma-
tion
6 '
2
8
ther*
3
1
1
1
6
Figure A-3. PURPOSE AND OUTPUT OF SURVEYED DISTRIBUTED PREDICTION MODELS
-------
are tented transport equations for mass and heat transport and flow equations
for fluid volume transport. Any field equation is a combination of a balance
equation of the transported or transformed entity (fluid volume, mass, heat)
and phenomenological equations which relate the process undergone by the
entity to the properties of the material in which it occurs. The equations
and conditions are usually based on a conceptual model of a physical system.
However, a few of the codes contain transformation functions of a parametric
nature (e.g. lumped input-output functions).
Models are classified as linear or nonlinear according to the mathe-
matical relationship betveen the field equation and the relevant output
variable. Thus, a linear flow model implies that the flow equation is
linear with respect to the head. Usually, the equations and the conditions
contained in a model are given in a differential form. Various numerical
methods can then be used to transform the field equations into a set of
algebraic equations with one equation required for each node or cell and/or
time step. The most common numerical methods employed are finite
differences (F.D.) and finite elements (F.E.). Other less common numerical
methods include characteristics and random walk, which are used for mass
transport models.
Once the set of algebraic equations is established it is then solved
for the output variable. Various techniques are used for solving the large
sets of simultaneous equations generated by either one of the above methods.
Iterative techniques such as successive overrelaxation, Gauss-Siedel and
iterative ADI are the most common. Direct matrix inversion techniques such
as trLdiagonal algorithms and Gauss elimination are also used. In some
cases special equation-solving algorithsm have been designed. They are
indicated in the review tables under "special features."
Most of the numerical solutions become unstable under extreme con-
ditions and convergence of the numerical solution to an exact solution can-
not in general be assured. For some iterative methods the change in the
output between consecutive iterations is used as a criterion for the con-
vergence of the computational scheme.
Some of the surveyed codes bypass the need to form and solve equations
by adopting existing analytic solutions and performing only a numerical
87
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approximation of such solutions. This method is usually applied to models
which assume an ideal homogeneous and istropic medium and linear processes.
Extensive use of the principles of superposition and images is common in this
group of codes.
Figure A-4 summarizes the mathematical methods used in the various
categories of prediction models surveyed.
Specific Model Characteristics.
Flow. Only the flow of homogeneous fluids has been considered. The flow of
nonhonogeneous fluids is treated with the mass and/or heat transport models.
The terms single phase, multiphase, saturated, unsaturated, saturated-un-
saturated, subsurface and surface flow refer to the type of phases or
hydrologic domains for which flow equations are present in the model.
All flow models, but one, are based on the Darcy law. Those distribut-
ed flow models which are also based on the Dupuit approximation are termed
hydraulic flow models. To this group belong one-dimensional and two-dimen-
sional models of horizontal flow in a single or multiple leaky or non-leaky
aquifer system, with a vertical leakage component. Saturated-unsaturated
flow models with horizontal flow in the saturated zone and vertical flow in
the unsaturated zone are also considered hydraulic flow models.
The hydraulic flow equations are linear with respect to head and have
constant transmissivity for confined or semiconfined flow conditions. Under
phreatic flow conditions the hydraulic conductivity is assumed constant
whereas the transmissivity is head dependent and adjustable at each time
step. For both conditions the storativity is assumed constant in time.
Some codes automatically change the value of storativity on passing from
confined to phreatic conditions and vice versa.
Distributed flow models which do not use the Dupuit approximation are
termed hydrodynamic. Models with two-dimensional flow in the vertical
plane or three-dimensional flow belong to this group.
For single phase models covering the unsaturated zone it is assumed
that the air phase in that zone is immobile and under atmospheric pressure
and that the hydraulic conductivity and the capillary pressure are
functions of the water content. For joint multiphase flow models, both the
water and the air phases are assumed to be mobile and to occupy the same
-------
CD
VO
Purpose and Output
General: Head
Concentration
Temperature
Combinations of
the above
Stream- aquifer relation
Flow Pattern
T . ,. Position
Interface Dispersion Zone
Free Surface
Wells Drawdown
Concentration
Temperature
Geothermal reservoirs
Subsidence
Aid in management
Water and Crop
Sediment Accumulation
Flow in Karst
Frost Propagation
Prediction & Calibration
TOTAL
Total
Number
or
Reports
70
31
4
3
19
9
8
2
8
6
1
3
4
8
5
4
1
1
1
5
193
Methods of distributed prediction models
..
Analytic
Approxi-
mation
4
1
1
4
2
12
F.D.
47
13
3
1
15
2
5
2
6
1
1
3
5
5
3
1
1?
1
5
LI 7
F.E.
17
8
1
2
3
1
2
2
3
3
45
F.D.
or
F.E.
1
3
1
5
Charact-
eristics
5
5
F.D.
or
Char.
1
1
Hybrid
1
1
Random
Walk
1
1
Others
2
2
1
1
6
Figure A-4. MATHEMATICAL METHODS USED IN SURVEYED DISTRIBUTED PREDICTION MODELS
-------
domain. For disjoint multiphase flow models such as those which handle the
movement of the interface between moving fresh and salt water in a coastal
aquifer, the phases are assumed to occupy separate domains with distinct
macroscopic boundaries between them. A detailed summary of the flow models
is given in Tables A-l - A-7. Information on additional lumped flow submodels
can be found in Table A-9 (lumped mass transport models) and in Tables A-21
and A-22 (conjunctive management of groundwater and surface water). Additional
distributed flow submodels can be found in Tables A-10 and A-ll (mass transport
models), in Table A-13 (heat transport models), in Table A-17 (other prediction
models) and in Tables A-19 through A-22 (management models).
Mass Transport. Mass transport models solve the mass transport equation for
each constituent in each phase with a velocity input from a flow model. If
the phase is nonhcmogeneous the velocity is concentration dependent and hence
flow and mass transport have to be coupled at each time step. If the phase
is homogeneous the two are independent and if flow conditions are steady the
velocity field can then be derived in one step. Nonisothermal mass transport
is considered in the context of a mass and heat transport model under the
category of "other prediction models."
A weakness of the numerical mass transport models, especially of those
employing finite differences, is the phenomenon of numerical dispersion
which results from the spread of a constituent entering a cell instantaneously
over the entire cell. The numerical dispersion of immiscible transport models
overshadows the physical dispersion of miscible transport models while ana-
lytical solutions are free of this problem. Sane lumped models attempt to
reduce the effect of numerical dispersion by introducing an effective
mixing depth. Some distributed models use the method of characteristics
whereby individual particles rather than the total mass are moved between
cells in order to reduce the effect of numerical dispersion.
A detailed summary of the surveyed mass transport models is given in
Tables A-9 - A-ll. Other models which include a mass transport component
can be found in Table A-17 (Other prediction models) and in Tables A-20 and
A-22 (Quality management models).
90
-------
Heat transport. Unlike mass, heat can also be transmitted through the solid
phase and/or stored in it. Also, in addition to the mass transport
mechanisms, heat can be transferred by conduction and radiation. However,
the surveyed heat transport models consider convection and conduction only.
Flow and heat transport are coupled whenever the density and/or viscosity of
the fluid phase is temperature dependent.
A detailed summary of the surveyed heat transport models is given in
.Table A-13. Additional models containing a heat transport submodel are
listed in Table A-17 (Other prediction models).
Deformation. A deformation model computes the deformation of the solid
Matrix of a porous medium by using the change in stress or head in that
medium obtained from a flow model. The deformation may be either elastic or
nonelastic and accordingly the mathematics required will vary from relatively
simple to complex.
In the simplest version of a deformation model the flow parameters are
considered constant. In this case, the flow and deformation submodels can
be uncoupled. A more realistic version assumes that the flow parameters are
stress-dependent through changes in porosity. In this case the two sub-
models have to be coupled for each time step.
A detailed summary of the surveyed deformation models is given in Table
A-15. Additional deformation submodels can be found in Table A-17 (Other
prediction models).
Coupled and other processes. Codes have recently been developed which deal
with coupled mass and heat transport, transport in a deformable medium, and
for solving multipurpose flow or transport problems. These codes, together
with others which do not belong to any of the categories listed above, are
classified as "other prediction models" and are summarized in Table A-17.
Evaluation
A matrix of model space was prepared for each subcategory of prediction
models and models surveyed were superimposed on that matrix. The results
are presented in Tables A-8, A-12, A-14 and A-16.
Models surveyed in a given area are identified by their respective
91
-------
numbers or by an X in the case of the flow models. Circles indicate usable
models, namely models which are fully documented, available and have been
applied to a field problem once or more. Blank spaces in each table indi-
cate areas for which models do not exist. It must be emphasized that the
existence of a blank space does not necessarily indicate that models of that
type are needed to improve groundwater-related water resource management.
A summary of the present status of prediction models follows.
Flow models (Table A-8): Missing completely are stochastic flow, determinis-
tic non-Darcian flow, and multipurpose conjunctive subsurface and surface
flow. Within the area covered by existing models, some models are missing
for special tasks such as wall hydraulics in single and multiple aquifers
as well as flow patterns and interfaces in multiple aquifers.
Mass transport (Table A-12): Adequately treated are conservated and noncon-
servative miscible transport processes in a single homogeneous phase con-
taining one or more constituents undergoing first order reactions under
equilibrium conditions. Nonhcmogeneous phases, nonlinear reactions and
biochemical reactions in particular are just beginning to be considered.
Nonequilibrium conditions, multiphase transport phenomena and stochasticity
of transport processes have not as yet been considered.
Heat transport (Table A-14): The major area of development is that of con-
servative linear heat transport in a single homogeneous or nonhanogeneous
fluid phase. Nonconservative and nonlinear heat transport as well as
transport of heat in a multiphase fluid system have just begun. Heat
transport in a disjoint multiphase system and stochasticity have not been
considered as yet.
It is worthwhile noting that while mass transport covers both the
saturated and saturated-unsaturated zones, all but one of the heat transport
models are confined to the saturated zone and to a nonconducting solid phase.
Deformation (Table A-16): Most of the deformation models have been developed
and applied to elastic subsidence in conjunction with a hydraulic flow
model. In addition, one deformation model treats elastic and nonelastic
92
-------
subsidence which is coupled with flow. Another model treats subsidence
with lateral displacement in a vertical plane which is uncoupled with flow.
The next steps would be to consider coupling for the later and three-
dimensional deformation.
Concluding remarks. Table A-18 summarizes the present status of the pre-
diction models. It shows that flow and mass transport phenomena are re-
latively well covered, but only at the distributed level and for a
homogeneous single phase. Both the saturated and saturated-unsaturated
zones, have been treated whereas few examples of conjunctive surface-
subsurface transport models exist.
Sane beginnings have been made in treating nonhomogeneous as well as
multiphase and multioomponent transport phenomena, both linear and non-
linear. However, these areas call for further and more active development.
MANAGEMENT MODELS
Conceptual framework:
Management models are a category of numerical models which serve the
purpose of selecting decisions pertinent to the management of water re-
sources containing groundwater. The relevant management tasks may include
supply, water quality control, wastewater disposal and reuse, and protection
of the environment. The decisions addressing these tasks include
engineering (development, operation) and economics (resource allocation,,
prices, taxes and rebates).
Dynamic decisions are made for each time step within a given planning
horizon. They are given either as sets of values of decision variables
or as a policy (operating rules) whereby a decision is a function of the
state of the systems concerned (e.g. water levels, level of development
of the water supply system). The latter usually apply to cases where the
input to the system is stochastic.
The hydrologic system (groundwater or groundwater and surface water)
is a component of the surveyed management models. A technologic system
is also present, ranging from water supply to water use and production of
93
-------
goods. The common state variables of the hydrologic system are storage,
head, salinity and surface water flow rates. Examples of decision variables
are location and capacity of wells (development), pimping and recharge
rates (operations), and acreage of crops (production). Economic decision
variables include investment, prices and taxes.
Constraints on admissible decisions and/or outcomes include levels of
water supply or disposal, sources of supply, water rights, capacities of
facilities, water levels and salinity and acreage of crops. While objective
functions are usually economic, some models address physical or technical
objectives such as maximum yield, maximum water levels, and satisfaction of
water quality standards or demand.
Mathematical framework.
The majority of the management models employ optimization techniques.
Policy decisions with stochastic inputs are usually handled by stochastic-
dynamic programming. Operational decision models which are usually
deterministic employ other programming techniques, both linear and nonlinear.
Some of them combine an optimization submodel which produces a decision at
any time step, with a simulation submodel which predicts the resulting
state as an input to the next decision. Others incorporate a simulation
submodel in the formulation of the constraints, thus ensuring an overall
optimum. The utilization of the so-called algebraic technological
functions (ATF) makes these computations simpler.
Recently techniques of decomposition have been introduced for treating
large scale systems. Multilevel optimization with an iterative
coordinating algorithm has also been introduced as a methodology to ensure
the compatibility of decisions made at different management levels. An-
other development is the use of decision theory to rank data by importance
to management.
Further details of the surveyed management models are given in
Tables A-19 - A-22.
Evaluation
An evaluation of the surveyed management models is presented in
94
-------
Table A-23. Mast of the models address water supply problems from an
engineering perspective. The majority of the models consider a distributed
hydraulic system under deterministic conditions. Although sane lumped
models do exist for managing groundwater and surface water under stochastic
conditions, they are dimensionally restricted.
Table A-23 indicates that water quality management models are in their
infancy as are multilevel management decision models. Both lumped and
hydrodynatnic groundwater management models are lacking. The former are
important for evaluating regional planning and the latter are important for
evaluating water quality projects. Finally, models for addressing multiple
objectives are lacking and would be useful for a variety of planning
situations.
IDENTIFICaTICN MODELS
Conceptual framework.
Identification models attempt to find optimal estimates of unknown
parameters and/or terms in a field equation of a prediction model. Such
estimates are obtained by finding the extreme value of a norm of
optimality often referred to as an objective function. "Best" estimates
of parameters imply that the error of prediction resulting from these
estimates can be assumed to fall within a prescribed interval at a given
confidence level. The difficulties involved in obtaining them are both
conceptual and technical. Among these are the inadequacy of available
data, the lack of knowledge on the probability distribution and dynamic
character of the estimated parameters, the application of constraints to
parameter values, error criteria to be employed in determining the
"best" values and the methods of optimization.
Mathematical framework.
Two approaches to calibrating a prediction model are commonly utilized.
In the direct method the input and output data are taken as given and the
field equation is solved for the unknown parameters. In the indirect method
the input data and the parameters are taken as known and the field equation
is solved for the output in a succession of steps while correcting the
95
-------
parameters after each step. The indirect approach is by definition iterative
and uses gradient search techniques. The direct approach may use either
noniterative or iterative algorithms, the parameter values may be constrained
or unconstrained and the optimization methods employed usually include
least squares and mathematical programming.
The surveyed direct identification codes are usually calibrated using
a volume balance equation, whereas the indirect codes are calibrated using
a head prediction equation. An exception of this regard are three direct
identification codes which calibrate equations with lumped response co-
efficients or functions. Further details of the surveyed identification
codes are presented in Table A-24.
Evaluation
Table A-25 presents an evaluation of the surveyed identification models.
The models address parameter calibration for flow models only. Moreover,
only one model (70-13) is able to provide statistical error information re-
garding parameter estimates. Another model (70-6) seems to have overcome
by decomposition and iteration the difficulty of directly calibrating a
multicell aquifer model. Three models (70-7, 70-8, 70-9) employ response
functions which are important because of their potential for management
and reduced computational requirements. Further progress depends on re-
solving the conceptual and computational difficulties discussed above.
DATA MfiNIPUIATICN MXELS
The details of the surveyed data manipulation models are presented in
Table A-26. The small sample indicates that this area is still in its
initial stage of development.
96
-------
TABLE A-l. SINGLE PHASE SATURATED FLOW: LUMPED MODELS
Purpose or
Output
Calculation
of water bal-
ance and pre-
diction of
piezometric
head
Prediction
of head,
flow, and
components
of water
balance
System
Unit
basin
One replen-
ishable
free
surface
reservoir
drained
through
three
parallel
confined
and linear
reservoirs
Processes
Pumpage
and
recharge
Infiltra-
tion,
evaporation
and
discharge
Methods
F.D.
Numerical
approxi-
mation
of an
analytical
solution
with an
exponential
decay
function
Documen-
tation
Complete
(Japanese)
Complete
(French)
Avail-
abil-
ity
Yes
Yes
Past
Applications
Field
(subsidence,
irrigation,
sea water
intrusion)
Field,
karstic
aquifer
Identification
Model
No.
11-1
11-2
Country
Japan
France
Institution
Private
Government
Reporter
(Year)*
Shibasaki
(67)
Bezes
(76)
*The number in the parentheses indicates the year of development of the model.
-------
TABLE A-2a. SINGLE PHASE SATURATED FLOW: HYDRAULIC FLOW MODELS - SINGLE AQUIFER (continued)
Purpose
Prediction
of
Head
Dynamics
2
2
2
2
2
2
3
2
2
2
1
2
2
2
2
2
2
2
Flow
(Hydraulics)
2
3
4
4
4
5
5
5
5
5
6
6
6
2
2
2
2
2
Con-
straints
0
0
1
0
0
0
0
1
1
0
0
0
0
0
0
0
1
1
Method
6
6
6
6
6
7
6
6
6
Hybrid
7
6
6
6
6
6
6
6
Documen-
tation
1 Ditni
Avail-
ability
anslonal
, ! o
2 Tl-Jm
3
5
3
4
2
2
4
4
3
1
3
1
3
4
3
4
3
ns1 pn^l
0
2
3
2
1
0
0
0
2
2
2
2
2
0
0
2
2
Appli-
cations
2
2
2
2
1
2
2
2
2
2
1
2
2
2
2
2
2
2
Identification
Model
No.
12-1
12-2
12-3
12-4
12-5
12-6
12^7
12-8
12^-9
12-rlQ
12-11
12'12
12-13
12-14
12-15
12-16
12-17
12-18
Country
U. K.
France
U. S.
Japan
Canada
U. S.
France
U. K.
U. K.
U. K.
Netherlands
U. S.
India
Israel
U. K.
France
U. S.
U. K. •
[nstitution
Geo. Sci.
SCET-
nternationa
Govt.
Govt.
Govt.
'rinceton U.
SGAL
Govt.
Private
Univ.
Delft
Univ.
Govt.
Govt.
Private
Govt.
Govt,
Govt,
Univ.
Reporter
Kitching
Bonnier
Prickett
Shibasaki
Vandenberg
Finder
Vancon
Bibby
Ashley
Rushton
Verruijt
Prickett
Shah
Shamir
Davis
Wolsack
Knowles
Rushton
vo
00
-------
TABLE A-2a. SINGLE PHASE SATURATED FLOW: HYDRAULIC FLOW MODELS - SINGLE AQUIFER (continued)
Purpose
Dynamics
2
2
2
2
3
3
3
3
2
1
2
2
2
2
2
2
2
2
Flow
(Hydraulics)
2
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
1
1
Con-
straints
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
Method
6
6
7
1
6
6
7
7
6
7
6
6
6
6
6
6
1
1
Documen-
' tation
7
3
3
7
1
3
7
3
4
1
3
4
1
9
3
3
3
3
Avail-
ability
0
0
0
0
0
2
0
0
2
2
9
2
0
3
9
9
2
2
Pa o f-
c cLS t
Appli-
cations
2
2
2
2
2
0
9
2
2
3
2
2
2
2
0
2
2
2
Identification
Model
No.
12-19
12-20
12-21
12-22
12-23
12-24
12-25
12-26
12-27
12-28
12-29
12-30u
12-31
12-32
12-33
12-34
12-35
12-36
Country
France
U. K.
Germany
France
France
N. Z.
France
Germany
U. K.
Netherlands
U. S.
U. K.
U. K.
Belgium
U. K.
U. S. '
.Australia
Australia
Institution
ARLAB
Ceo. Scl.
Univ.
ARLAB
Univ.
Univ.
ARLAB
Govt.
Univ.
Private
Univ.
Battelle
Govt.
Univ.
Govt,
Univ.
Govt.
Govt.
Reporter
Blanc
Adams
Klenke
Baradat
Cazal
Hunt
Blanc
Briechle
Chidley
Olsthoorn
Sunada
Kipp
Aldrick
Bast in
Keating
Claborn
Colville
Colville
ID
ID
-------
TABLE A-2a. SINGLE PHASE SATURATED FLOW: HYDRAULIC FLOW MODELS - SINGLE AQUIFER (continued)
Purpose
Stream
Aquifer
Relation
Prediction
and
Calibration
Dynamics
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
Flow
(Hydraulics)
1
1
2
2
2
2
3
4
5
5
6
2
2
2
5
.
9
Con-
straints
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
0
Method
6
6
6
6
6
7
6
6
6
6
1
6
6
6
6
6
Documen-
tation
3
3
3
3
9
3
3
4
3
3
3
2
2
3
5
2
Avail-
ability
2
2
2
9
9
2
2
2
9
9
9
2
2
0
0
2
1
Past
Appli-
cations
1
2
0
2
2
2
2
2
2
2
2
2
2
2
2
1
Identification
Model
No.
12-37
12-38
12^39
12-40
12-41
12
-------
TABLE A-2a. SINGLE PHASE SATURATED FLOW: HYDRAULIC FLOW MODELS - SINGLE AQUIFER
Purpose
Response
Coefficients
Stream-
lines
Fronts
Karst
Interface
Dynamics
2
2
3
1
1
2
3
1
2
Flow
(Hydraulics)
2
2
2
4
6
6
1
Pipe
flow
1
Con-
straints
0
0
1
0
1
0
0
0
0
0
0
0
Method
6
6
6
1
1
1
6
1
6
1
6
6
Documen-
tation
3
4
3
4
2
2
5
4
5
7
4
4
Avail-
ability
2
2
9
2
2
2
0
2
2
0
9
9
Past
Appli-
cations
9
0
2
2
2
3
2
2
1
2
2
2
Identification
Model
No.
12-53
12-54
12-55
12-56
12-57
12-58
12-59
12-60
12-61
12-r62
12-63
12-64
Country
U. S.
U. S.
Israel
Netherlands
Netherlands
Netherlands
U. S.
U. S.
Canada
France
U. S.
Argentina
Institution
U.S.G.S.
Univ.
TAHAL
Govt.
Govt.
Govt.
Battelle
Boeing
Govt.
ARLAB
Univ.
Govt.
Reporter
Haddock
Morel-Seytoux
Schwarz
Van Den Akker
Van Den Akker
Van Den Akker
Friedrichs
Nelson
Vandenberg
Baradat
Thrailkill
Navarro
-------
TABLE A-2b. SINGLE PHASE SATURATED FLOW; HYDRAULIC FLOW MODELS - MULTIPLE AQUIFER (continued)
Purpose
Prediction
of
Head
Dyrtamics
2
3
3
2
1
2
2
2
2
2
2
2
2
2
3
2
Vlow
Hydraulics)
2
2
2
2
5
5
5
5
5
5
5
5
5
5
5
5
Con-
tra in ts
1
0
o
1
0
0
0
0
1
0
0
0
0
0
0
0
lethod
6
6
6
6
7
6
6
6
6
7
6
7
6
6
6
6
)ocumcn-
tation
1
7
7
4
7
2
2
2
5
4
3
1
2
3
1
3
Avail-
ability
0
9
0
0
0
0
0
0
2
2
0
0
2
0
0
0
Pa.st
ppli-
atious
2
2
2
2
2
2
2
2
2
0
9
2
2
2
2
2
Idcn c i f ica t ion
lodcl
No.
3-1
3-2
3-3
3-4
3-5
13-6
13-7
13-8
L3-9U
L3rlO
L3-11
.3-12
.3-13U
.3-14
13-15
13-16
Country
UI.S.
Germany
France
U.K.
Netherlands
Institution
Private
Govt,
Private
Govt.
Govt.
France Private
France Gfeohydrauliqu
France "
U.S. Govt.
Canada
U.S.
Netherlands
Spain
France
France
U.K.
Univ.
Univ.
Govt,
Govt.
Private
Govt.
Geo. Sci.
Reporter
Kleinecke
Giesel
Clouet
D'Orval
Liddament
Fillekes
Carriere
> Prudhomme
Prudhomme
Prickett
Chorley
Sal earn
Fillekes
Gracia
de Lamina t
Landel
Kitching
-------
TABLE A-2b. SINGLE PHASE SATURATED FLOW: HYDRAULIC FLOW MODELS - MULTIPLE AQUIFER
Purpose
Special
Dynamics
3
Flow
Hydraulics)
2
5
5
2
Con-
trainls
0
1
0
0
cthod
6
6
6
6
Documen-
tation
1
2
5
7
Avail-
ability
3
0
2
9
Past
Appli-
cations
0
2
2
2
Identification
Model
No.
13-17
13-18
13-19
13-20
Country
Australia
Argentina
U.S.
U.S.
nstitution
Govt.
Govt.
Battelle
Private
Reporter
Seldel
Navarro
Cole
Kleinecke
o
GJ
-------
CODE SHEET FOR TABLE A-2a. & A-2b.
Code
Descriptor Options Number
Dynamics Steady 1
Nonsteady 2
Both 3
Flow Phreatic 1
(Hydraulics) Phreatic + confined 2
Phreatic + semiconfined 3
Confined + semiconfined 4
Phreatic, confined and semiconfined 5
Confined 6
Others or not specified 9
None 0
Constraints None 0
Constraint present 1
Method Numerical approximation of analytic solution 1
Finite differences 6
Finite elements 7
Documentation Listing 1
Listing + manual 2
Listing + description or references 3
Listing + manual + description 4
Listing + manual + description + references 5
Not existing 6
Not specified 7
Under development 9
Availability Restricted 1
Unrestricted 2
Not available 0
Unknown or not specified 9
Available after publication 3
Past applications Research 1
Field problems 2
None 0
Unknown 9
104
-------
TABLE A-3a. SINGLE PHASE SATURATED FLOW: HYDRODYNAMIC FLOW MODELS - 2-Dimensional (continued)
Purpose and/
or Output
Prediction
of Head
Stream-
Aquifer
Interaction
Free
Surface
Process
Flow
Characteristics
Steady (phre-
atic, confined,
possibly leaky)
steady or non-
steady ( " )
it
Nonsteady,
partially pene-
trating river
Nonsteady
(phreatic and/
or confined)
Steady state
(phreatic or
confined)
Nonsteady
(phreatic)
Method
F.E.
F.E.
F.D.
F.D.
F.E.
F.E.
F.E.
Docu-
ment-
tation
Complete
Complete
Complete
References
?
Complete
Complete
Avail-
abil-
ity
Yes
Yes
Yes
?
No
Yes
Yes
(guid-
ance
needed)
Past
Appli-
cations
Field
Field
Field
(many)
Field
(1)
Evalu-
ation of
para-
meters
(field)
Field &
Research
(many)
Little
Special Features
hydraulic flow op-
tion, Boulton delay-
ed yield, user
oriented
hydraulic flow op-
tion, nonlinear,
user oriented
hydraulic flow op-
tion, evapotranspir-
ation, storativity
of aquitard, user
oriented
Constraints on river
stage
free surface, two-
level grids
seepage faces, flux
through free surface,
deformable grid,
versatile, user
oriented, option of
axial symmetry
time dependent boun-
dary conditions , de-
formable mesh, arbi-
trary anisotropy,
user oriented,
option of axial
symmetry
Identification
Model
No.
14-1U
14-2
14-3
14-4
14-5
14-6
14-7
Coun-
try
U.S.
ft
11
If
France
U.S.
ii
Insti-
tution
U.S.G.S.
tl
tl
Univ. of
Missouri
BURGEAP
Univ. of
Calif.
Berkeley
ii
Reporter
(year)
Cooley (70)
Cooley (74)
Trescott
(76)
Sharp (76)
Clouet
D'Orval (77)
Neuman (69)
Neuman (70)
o
Ul
-------
TABLE A-3a. SINGLE PHASE SATURATED FLOW; HYDRODYNAMIC FLOW MODELS - 2-Dimengional
Purpose and/
or Output
Free
Surface
Flow In the
vicinity of
a well
Upconing of
the inter-
face under
a pumping
well
Process
Flow
Characteristics
Steady or non-
steady
(phreatic)
Steady or non-
steady
Nonsteady
(phreatic)
Nonsteady
(phreatic or
confined)
Nonsteady
(phreatic or
confined and
leaky)
Nonsteady
(phreatic)
Meth9d
F.E.
F.D.
F.D.
F.D.
F.D.
F..E.
Docu-
ment-
tat ion
?
?
?
Descrip-
tion &
listing
Descrip-
tion &
listing
Complete
Avail-
abil-
ity
No
No
No
No
Yes
Yes
Past
Appli-
cations
some
Pumping
test in-
terpreta-
tion
pump test
analysis
Field:
analyses
of com-
plex
pumping
tests
Field
(many)
(well
losses,
pumping
rates)
Field
Special Features
arbitrary anisotropy,
seepage boundary
condition, option
of axial symmetry
automatic matching,
axisymmetric
storage of large
diameter well,
axisymmetric
layered aquifer,
axisymmetric ,
increasing time
step
multilayered, well
losses, constraints
on groundwater level
and pumping rate,
logarithmic mesh,
small program,
axisymmetric
Constraint on thick-
ness of fresh water
lerise, saltwater
under constant po-
tential, nonuniform
mesh size, aniso-
tropy, local coordi-
nates, axisymmetric
Identification
Model
No.
14-8
14-9
14-10
14-11
14-12
14-13
Coun-
try
France
France
Prance
U.K.
U.K.
Canada
Insti-
tution
ARLAB
II
BURGEAP
Insti-
tute of
Geol.
Sciences
Univ. of
Birming-
ham
govt.
Quebec
Reporter
(year)
Blanc
ft
Clouet
D'Orval (77)
Kitching
(76)
Rush ton (77)
Sylvestre
(73)
-------
TABLE A-3b. SINGLE PHASE SATURATED FLOW: HYDRODYNAMIC FLOW MODELS - 3-Dimensional
Purpose
Prediction
of
Head
Stream-
aquifer
Relationship
Flow
Dynamics
Steady
X
X
X
X
X
X
Nonstead>
X
X
X
X
Method
F.E.
F.E.,
F.D.
F.D.
F.D.
F.D.
F.E.
Docu-
ment-
tation
In progress
Not
Specified
Listing
manual
?
Complete
Poor
Avail-
abil-
ity
Yes
No
No
No
Yes
Yes
Past
Appli-
cations
Field
Field
(some)
Field
(many)
?
Field
(many)
Field
(little)
Special Features
Core and Mass
Storage
Free surface,
flexible mesh size
and configuration
Free surface,
user oriented
Free surface,
hierarchy of grids
Multilayered,
storativity of
aquitards,
user oriented
Versatile multi-
layered
Identification
Model
No.
14-14
14-15
14-16
14-17
14-18
14-19
14-20
14-21
Coun-
try
Austra-
lia
France
France
France
U.S.
U.S.
Insti-
tution
Govt.
ARLAB
Govt.
BURGEAP
U.S.G.S.
Govt.
Reporter
(year)
Wilsdon (76)
*
Blanc
' '
Prudhomme
(70)
Clouet
D'Orval (77)
Trescott (76)
Kuiper (76)
o
-J
-------
TABLE A-4.
SINGLE PHASE UNSATURATED FLOW MODELS
Purpose
and/or
Output
Evapo-
trans-
piration
satura-
tion
deficit
Water
capillarj
haaH
ncaQ )
water
balanc e
Water
content,
capillary
head.
Spatial
Charac-
teristics
1 dimen-
sional (?)
2-dim. In
vertical
plane
1-dim. ,
vertical
System
Unsaturated
zone, crop
homogeneous
isotropic
soil
Irrigation
aultilayerec
imsaturated
I Processes
Capillary
flux,
evapotrans-
poration
irrigation
evaporation
uptake by
roots , flow
Ponding,
runoff, in-
filtration,
flow
Method
Successive
approxi-
nation
F. D.
Integrated
Darcy
equation
for each
layer
Documen-
tation
In prepara-
tion
Description
(in French)
References
Listing
Avail-
ability
No
No
Yes
Past
Applica-
tions
Regional
investiga-
tion
Research
simulation
of laboratory
experiments
(40 times)
Not
Specified
Special
Features
Small
storage
(HP
computer)
Automatic
time step,
varifica-
tion of
analytic
solutions,
user
oriented,
large com-
puter time
Constraint'
on
minimal
capillary
head, user
oriented
IDENTIFICATION
Model
No.
15-1
15-2
15-3
Country
Netherlands
France
Netherlands
Institution
Govt.
Govt.
Govt.
Reporter
(year)
van der
Weert
(76)
Wolsack
(72)
Wind
(73)
o
00
-------
TABLE A-5. SINGLE PHASE SATURATED-UNSATURATED FLOW MODELS (continued)
Hydraulic
Hydro-
dynauic
Spatial
Characteristics
2d horizontal-
saturated zone
Id vertical -
unsaturated zone
H
ti
2 dlaensional
In vertical or
horizontal
plane
2 dimensional
In vertical
plane
F
tynamlcs
tonstead)
n
n
Monstead
or
Steady
Non-
steady
M
ow
Hydraulics
Phreatlc
& leaky
Phreatlc,
confined
& leaky
'hreatic
it
Phreatlc
confined
& leaky
Phreatlc
Output
H
X
X
X
X
X
X
X
X
Q
X
X
X
*
X
X
X
X
B
X
X
X
1C
ETI
X
X
X
!etho<:
F.E.
F.D.
F.D.
F.D.
F.E.
F.E.
F.E.
Documen-
tation
In Prepa-
ration
Complete
Complete
Complete
In Prepa-
ration
tomplete
[n Prepa-
ration
Avail-
ability
Not
Specified
Yes
Yes
No
After
publica-
tion
Yes
After
Prepara-
tion
Past
Applications
Field: effect of
pumpage on draw-
down, crop pro-
duction and water
balance .
Field: response to
river stage
vegetation and
pumpage
1
Field: water
supply to
development
None
Research, Field :
dam and reservoir
design
Field: Waste
disposal sites
Research: Flow
to tile drains
Special
Features
Roots, evapotrans-
piration, land use,
Hysteresis, user
oriented
specific stora-
tlvity, roots,
river, aqultard,
iser oriented,
Lumped unsaturated
zone, flexible
Land use, Irriga-
tion rules, con-
straints, lumped
delayed vertical
transfer function,
flexible, error
prediction for
calibration, user
oriented
Specific stora-
tivity, versatile,
flexible, tested
Plants, evapotran-
splration, seepage
phases, user
oriented
Specific stora-
tlvlty, seepage
phase, user
oriented,
arbitrary
inlsotropy
Identification
Model
No.
16-1
16-2
16-3U
16-4
L6-5
.6-6
16-7
16-8
Coun-
try
lethl.
U.S.
I.S.
"ranee
U.S.
Israel
Canada
Insti-
tution
Govt.
uses
Auburn
Univ.
SOGREAH
tniv.
lerkeley
Govt.
Univ.
Water-
loo
Reporter
(vear)
Nat 1. Ins t.
Water
Supply (73
PJM de
Laat(76)
Reed (74)
Molz(74)
Barriere
(75)
Naraslmhan
(75)
)euman(74)
'ickens
(75)
-------
TABLE A-5. SINGLE PHASE SATURATED-UHSATURATED PLOW MODELS
Hydro-
dynamlc
Spatial
Characteristics
2 dimensional
In vertical
plane
ti
"
3 dimensional
it
Flow
tynaraics
Non-
steady
ti
11
Steady
and
Non-
steady
it
Hydraulics
-
Output
H
X
X
X
X
X
q
X
*
X
X
X
X
X
u
X
X
X
ETI
lethod
F.E.
F.D.
F.D.
[nte<-
jra^
ted
F.D.
F.E.
Documen-
tation
No
Listing
Refer-
Complete
Complete
Complete
Avail-
ability
No
Yes
Not
Specified
Yes
Yes
Fast
Applications
Research
Research :
infiltration and
drainage
Research: travel
time through
unsaturated zone
None
Field: flow in
vicinity of a
facility
Special
Features
Specific Stora-
tivlty, seepage
>hase
Uxlmum 5 different
soil types, user
oriented
lomogeneous,
tsotroplc, rigid
aquifer
Elastic or non-
elastic deforma-
tion, hysteresis,
versatile
Several unsaturated
itrata, specific
irbltrary
misotropy, user
irlented
Identification
Model
No.
16-9
16-10
16-11
16-12
16-13U
Coun-
try
U.S.
U.S.
'ranee
U.S.
Canada
Insti--
tutlon
uses
NM
Tech.
Mecan-
ique
Irevobli
Univ.
(erkelej
Univ.
Water-
loo
Reporter
(year)
ooley
(74)
rut^ert
Vauclln
(75)
Narasimhan
(75)
Verge(75)
List of symbols:
H - Plezomctric head
Q - Discharge
!f> - Capillary head
6 - Water content
ETP - Evapotransplration
-------
TABLE A-6. SINGLE PHASE SUBSURFACE-SURFACE FLOW MODELS
Subsurface
Elements
Saturated
and un-
saturated
zones
Single-
layered
phreatlc
aquifer,
springs,
wells
Ground-
water
basin,
phreatic 01
confined
Soil water
zone , homo-
geneous
Isotropic
aquifer
Spatial
Charac-
teris-
tics
3-dim.
2-dim.
hori-
zontal
2-dlm
hori-
zontal
l-dim.
lori-
zontal
flow
In
vertical
>lane
Process
Darcian
nonsteady
flow, any
replenish-
ment and
exploita-
tion
Nonsteady
linear
flow
(hydraulit
pumpage
infiltra-
tion
Nonsteady
linear or
nonlinear
[hydraulic
flow
Transfer
through
unsaturate
zone, flow
through
aquifer
[hydraulic
Output
H,i|i,e
general
H
H
draw-
down
H,8
Surface
Elements '
Stream
connected
to grocnd-
water
system
River fed
by
springs
River,
lakes in
direct
contact
jith the
aquifer
leservoir
Spatial
Charac-
teris-
tics
l-dim.
l-dim.
Process
Open
Channel
Flow
(hydrau-
lic)
Pumpage
artifi-
cial
recharg<
seepage
Flow
[hydrau-
lic)
Preci-
pita-
tion,
evapo-
ration
drain-
age
Output
Water
depth,
velo-
city
Rate
of
Flow
Depth,
rate
of
flow
Method
F.D,
F.D.
for
jround-
water,
ac-
count-
ing foi
river
F.D.
Analy-
tic
Documen-
tation
Complete
Complete
Not
specified
Reference
Avail-
ability
Yes
No
Yes
?
Past
Applications
Research . Field-
once on an ex-
perimental water
shed
Field (40 times)
augmentation of
river flow during
droughts by
pumping from
groundwater
Field-Impact of
sewering Long
Island, NY on
groundwater levels
and stream flow
Field-evaluation
of recharge
Special
Features
No overland flow,
storativity, soil
moisture reten-
slon, versatile,
large computer
time and storage
requirments
Storativity,
impervious aquifer
boundaries , con-
straint on head,
small computer
storage
Storativity, evapo-
transporatlon
constraint on head
large data -re-
quirements
Linear transfer
f unct Ions , spec if ic
usable for cali-
bration
IDENTIFICATION
Model
No.
17-1U
17-2
17-3
17-4
Coun-
try
U.S.
U.K.
U.S.
France
Insti-
tution
IBM
Govt.
Private
Govt.
Reporter
(year)
Breeze
(71)
Oakes
(73)
Chen
(77)
De^
gall-
ier
(72)
List of symbols: H - Piezometric head
iji - Capillary head
8 - Water content
-------
TABLE A-7. MULTIPHASE FLOW MODELS
Purpose and/
or Output
Head and/or
position of
interface
between
fresh and
saltwater
Head,
flow net,
interfaces
General
F16V of air
and water a-
round a pum-
ping well
Gas & water
Pressure &
phase satu-
ration
Phases
Disjoint
Joint
low
Spatial
Dimen-
sions
1
in
verti-
cal
plane
2
in
verti-
cal
plane
2
2 or 3
2
rertical
plane
3
Method
F.D.
it
Euler
F.E.
F.D.
Analytic
functions
F.E.
F.E.
F.D.
F.D.
Docu-
men-
tation
Hebrew
Listing &
public
Comnents
Sdescrip-
tion
?
?
Complete
Complete
?
No
Complete
Aval-
abil-
ity
Yes
?
?
Yes
No
No
Yes
?
No
No
No
Past
Appli-
ations
Field
Field
Field
Research
?
?
Field
Field
?
Not yet
?
upult assumption,
mall computer &
storage
Parabolic Interface
multilayered aqui-
fer, calibration &
forecasting
homogeneous , iso-
troplc aquifer. In-
put: velocity
free surface
general, little
storage & data
variety of options
steady & nonsteady
steady or nonsteady
user oriented
2 modifications: geo
thermal model, frac-
tured matrix model
user oriented
Identification
Model
No.
18-1
18-2
18-3
18-4
.18-5
18r6
18^7U
18-8
18-9
ISrlO
18-11
Coun-
try
srael
ii
it
ether-
ands
U.S.
France
Nether
lands
it
U.S.
U.S.
U.S.
nsti-
ution
Univ.
ahal
II
Univ.
•Prince-
ton U.
BURGEAP
govt.
Prince-
ton U.
Univ.
INTER-
COMP
Reporter
Shamir
Schwarz
Kapuler
Haitjema
Finder
Clouet
D'Orval
van der
Veer
Barends
Huyakorn
Brutsaert
Lantz
-------
p
U)
TABLE A-8. THE PRESENT STATUS OF SURVEYED FLOW MODELS
1 DETERMINISTIC
[STOCHASTIC
Darclan Flow
[Non-Darcian Flow
Head
Stream-
Aquifer
Pattern
Interface
Free
Surface
Well Flow
Geotherma!
reservoir
Head
LUMPED
Gro
_SMt
Sin-
gle
com-
po-
nent
df
und
Nultl
com-
po-
nent
CD*
Ground
and
Sur-
face
Water
Hydro-
logic
& non-
hydro-
logic
compo-
nents
DISTRIBUTED
Single Phase
Saturated
Hydraulic
1
X
2H
Single
Aqui-
fer
X
X
X
X
Multi-
ple
Aquifer
X
Hydro-
lynamlc
2V
©
X
©
(l)
X
3
©
X
Satur.-Nonsaturated
Hydraulic
1
2H
Sin-
gle
Aqui
fer
(T)
tilti-
ple
Aqui-
fer
Hydro-
lynamlc
2V
Q
3
©
Subsurface-Surface
Hydraulic
1
Sin-
gle
Aqui-
fer
X
Multi
pie
Aqui-
fer
2H
Sin-
gle
Aqui-
fer
Multl
Pie
Aqui-
fer
X
Hydro-
dynamic
2V
3
sr
Multiphase
Subsurface
Disjoint
Hydrau-
lic
1
X
2H
y
X
2V
T
X
3
X
Jol
1
2H
nt
2V
X
X
3
X
JDocumentation in French x Indicates existence of models 'Applied only once
"Documentation in Japanese clrcled numbers Indicate number of usable models + Valid for 2H and 2V
Subsurface
and
Surface
-------
JABLE A-9. LUMPED MASS TEANSPORT MODELS
Processes
Mass Transport
Conservat ive
Complete mixing
Complete mixing
partial convection
Effective mixing
depth
Nonconservative
Precipitation,
dissolution and
ion exchange
Complete mixing
Chemical equilib-
rium reactions,
Precipitation,
dissolution
Flow
Non-
Steady
Non-
Steady
Steady
Steady
Steady
Hydrologic Elements
Zone & Aquifer
Aquifer connected
Saturated.
Network of Aquifer
comparments .
Aquifer and non-
saturated zone
Saturated &
unsaturated zone
Saturated &
unsaturated zone
surface water
Constitu-
ents
Single
Single
Multiple
Multiple
lultiple
Non-
hydrologlc
Systems
Water Sup-
ply, Pum-
page, Re-
charge
Irrigation
Import
Export
Agriculture
Industry
Household
Reclamation
Agriculture
(Irrigated)
Output
Concen-
tration
&
Head
Total
Salinity
Concen-
tration
Concen-
tration
Concen-
tration
Documen-
tation
Listing
anH
ana
refer-
ences
No
(Hebrew)
(Hebrew)
Report
&
Listing
Aval 1-
ability
Yes
'TJBbJno\
Discing/
No
No
Yes
Yes
Fast
Applications
(problem)
Land appli-
cation of
sewage
Effect of
water supply
alternatives
on groundwater
quality
(California)
Contamination
trends due to
waste water
reuse under
various oper-
ating rules
Changes in
groundwater
quality relatec
to the car-
bonate system
Effect of
irrigation on
surface &
groundwater.
quality
Model
Number
21-1
21-2
21-3
21-4
21-5
Country
U.S.
U.S.
Israel
Israel
U.S.
Insti-
tution
New Hex.
Tech . &
MIT
Govt.
&
Consult.
Tahal
Tahal
MM Tech
Reporter
(year)
GELHAR
&
WILSON
(74)
KLEINECKE
(74)
Water
Quality
Section
(75)
HERCADO
(76)
GELHAR
(76)
-------
TABLE A-lOa. DISTRIBUTED CONSERVATIVE MASS TRANSPORT MODELS - SINGLE HOMOGENEOUS PHASE
* + indicates an advantage
Process
Immiscible
(Convection
Miscible
(Convection
&
Dispersion)
Hydrologlc
Zone
Saturated
Unsaturated
Saturated
Sat-Unsat
Sat-Unsat
Unsat.
Spatial
Dimensions
2 horizontal
1 Vertical
3
2 horizontal
2 vertical
1 horlz. or
jffirtical
1 vertical
Method of
Solution
F.D.
II
F.E
ti
ftaracterls-
tics
ii
F.D. -Hybrid
F.D.
F.E.
F.D.
Characteris-
tics
Availability
Yes
No
Limited
Documentation
Yes
No
Limited
No
In Prepara-
tion
No
Yes
Cn Preparation
[n Preparation
No
No
Past
Applications
Field
Field
Research
Field
7
Research
Field
In test
Field
Field
Special
Features*
+User Oriented
- Numerical
dispersion
+ User Oriented
Data
-Stability undei
extreme condi-
tions. +Multi-
layered aquifer
•(•Special
Equations
Solver
-Stability
-Computer time
•l-User Oriented
^Variety of
sources & sinks
(Point & areal)
•f Correction for
for local values
- Computer Time
Model
Number
22-1
22-2
22-3
22-4
22-5
22-6
22-7
22-8
22-9
22-10
22-11
.22-12
22-13
22-14
I D
Country
U.S.
Israel
U.S.
U.S.
U.S.
U.S.
France
U.S.
Israel
Germany
U.S.
U.S.
Israel
U.K.
Institution
University
Tahal
University
University
University
University
University
U.S.G.S.
IBM - Tahal
University
University
University
Tahal
Water Research
Center
No. in Team
2
2
2
3
2
1
2
2
1
1
1
1
1
Reporter
(year)
Sunada
(77)
Schwarz
Hanks (75)
Gupta (75)
Finder (74)
Pinder
(77)
Lessl (76)
Konlkow
(76)
IBM (77)
Thiem
(75)
Shapiro
(70
Van Genuchten
(76)
W1
Oakes
(76)
-------
TABLE A-lOb. DISTMTOTm CMI8ni»*TTVE MASS TBAHSMHT mPH.fi - 9BMLB
PHAS«
Purpose
and
Output
Sea water
Intrusion
*P, C
MoVCMnt Of
salt water
interface
towards a
pimping
well
*P, C
Quality of
water puaped
fron a
single
well
*P, C
Systn
Coastal aquifer,
Single consti-
tuent
Single well in
confined aquifer,
Single consti-
tuent
Partially pene-
trating well In
a confined
vertically
heterogeneous
aquifer,
Multiple
constituents
Process
Convection
and
Dispersion
ii
Convection
only
+ nixing
in the well
Cnatial
3pStlS4
Dimensions
"
2 dlaens. in
vertical plane
Caxlsynnetrlc)
ii
Method
P.E.
Block
direct
solution
ii
F.D.
20
separate
layers
of a
fixed
chemical
profile,
•oved
verti-
cally
after
each
step
Aval 1_
AVailT
ability
Yes
Yes
(United)
Not
Docu-
mented
Pmmf
asc
Applications
7
?
Field
Project
Identification
Model
No.
22-15
22-16
22-17
Country
U.S.
U.S.
U.S.
Institution
Princeton
University
ii
Illinois
State
Water
Survey
No.
in
Ten
2
1
2
Reporter
Year
SEGOL (74)
HSIEH (76)
PR1CKETT (73)
*P - pressure
C - concentration
-------
p
-s]
TABLE A-ll. DISTRIBUTED NOMCONSERVATIVE MASS TRANSPORT MODELS - SINGLE HOMOGENEOUS PHASE (continued)
Transport
Mechanism
Immiscible
(convec-
tion)
Miscible
(convection
and
dispersion
Consti-
uents
Single
Single
Hydrologic
Zone
Saturated
nsaturated
Sat. &unsat .
Saturated
Unsaturated
ii
Spatial
Dimensions
2horizonta:
, vertical
3
3
2 h or v
2
1 h
2 v, 1
1
BEAr
dsor
X
X
X
X
X*
X
X*
ecay
X
X
X
X
X
firms
Nitro-
ther
X
X
lethod of
Solution
E.D.
..
F.E.
F.D. or
character-
istics
F.E.
character-
istics
F.D.
..
ti
Availabi-
lity
No
No
Yes
No
Yes
?
?
?
Yes
Past
pplicatfe
ield
(many)
Field
None
Field
(many)
Field
tests (3)
Research
it
Research
Research
Special
Features **
^Hierarchical
grid
convergence
under extreme
conditions
length of time
step
•HJser oriented
-element size
+User oriented
-convergence
under extreme
conditions
+User oriented
-stability
+adsorbed con-
centration
-Boundary con-
ditions in ex-
treme cases
+User oriented,
quadratic ad-
sorption
-Stability and
convergence,
computer time
Model
Number
23-1
23-2
23-3
23-4
23-5
23-6
23-7
23-8
23-9
Country
France
Israel
anada
U.S.
Canada
U.K.
France
France
France
Insti-
tution
Univ.
Tahal
Univ.
,
Intera
Univ.
?
Govt.
Govt.
Univ.
No. in
Team
5
1
1
?
3
3
2
Reporter
(year)
Ledoux
(76)
Avron
(75)
Segol
(76)
Lantz
(75)
Pick ens
(74)
Schwartz
(Modeler)
Reporter)
(75) .
Brlssaud
(76)
Couchat
(76)
Caudet
(77)
-------
TABLE A-ll. DISTRIBUTED NONCONSERVATIVE MASS TRANSPORT MODELS - SINGLE HOMOGENEOUS PHASE
Transport
Mechanism
Mlsclble
{convec-
tion and
dispersion
Consti-
tuents
ultiple
Hydrologic
Zone
Sat.&unsat.
(, perched
Sat.&unsat.
Saturated
11
it
it
Saturated
or surface
Unsaturate
Spatial
Dimensions
2 h
2 h or v
and 3
1
2 h
ii
1
1
REA
Adsoi
ptior
X
X
X
X
X
X
ecay
X
X
X
X
x
TIONS
itro-
en
X*
X*
ther
X
X
X
X
X
ethod of
Solution
F.D.
andon walk
Analytical
\aracteris-
tlcs
F.D.orF.E.
F.E.
F.D.
"
vai labi-
lity
Yes
Yes
Not Docu-
mented
?
Not Docu-
mented
No
Listing
Yes
Fast
pplicatb
Field (1)
Waste
disposal)
Field
Field
(Waste
disposal.
" (many)
Field
(many)
None
Res earch
Research
Special
Features **
•(•variety of
options
-stability,
computer time
+User oriented
-computer time,
stability
•(•User oriented
-precision
-(•variety of
options
-extreme condi-
tions
-Tine step,
stability
-(•Hierarchy of
grids
-stability
•(•generalized
model, non-
linearity
-numerical
dispersion
•(•variety of
options
nonllnearlty
odel
umber
3-10
3-11
23-12
23-13
23-14
23-15
23-16
23-17
untry
U.S.
U.S.
U.S.
U.S. '
U.S.
U.S.
Israel
U.S.
Insti-
tution
^ —
.S.G.S
attell
Battell
U.S.fi.S
U. S.G.S
Inter-
comp
Govt.
Univ.
No. in
Team
2
3
2
2
1
3
2
Reporter
(year)
bertson
(75)
Ahlstrom
(76)
urkholder
(75)
obertson
/7A\
Jrove
(77)
Lantz
(77)
lachmat
&
ftetboun
(76)
Sellm
(76)
00
*dcnotoo nonlinoarity option
** -(-indicates an advantage
-indicates a difficulty
-------
TABLE A-12. THE PRESENT STATUS OF SURVEYED MASS TRANSPORT MODELS
STATISTICS 1
DETEBMINISTIC
1 STO-
1 CHASTIC
CHEMISTRY
LINEAR
NON-LINEAE
Equilibrium
Nonequ.
j=
•H
f-l
fH
1
SPATIAL DIMENSIONS 1
(00
Lumped)
a
*
fl
o
-1
ol
c*>
o
H
N
m
i 3
j°- S
SINGLE PHASE
HOMOGENEOUS
Single Constituent
Immiscible
Conser-
vative
22-3«
22-2 •
22-1 •
Nonconservat Ive
Chem.
23-2 •
23-1 •
Blochem.
Mlsclble
Conser-
21-2
21-1
23-13 u
22-12 ..u
22-11 ii
2J-|' 22-11*
e>:
.
i :
i
.
l
:
1
Nonconservat ive
Chem.
2J-7S
2J-» u
G^5>*
23-3 I. y
Biochem.
j
(53).. 2i-t
-
MfiltlConstituent
Immiscible
Con-
va-
tive
Nonconservat.
Chen
Biochem.
Mlsclble
Conser-
vative
21-3 .. u
I
Nonconservat ive
Chem.
21-4
21-3
23-12
23-13 23-ll.u
23-10 23-15 >
•a 23-11*
Biochem.
2
-
21-16.. 23-17 „
i
NONHOMOGENPOUS
Single
Constltu.
Immiscible
Mtsc-
7~T
01 O
CO . U >
a c t-
50 a
S.S
i j
I-1T
t
22-11
22-11
;
1
j '•
.
C
i Immiscible
Multi
jnstitu
[Conserv
Non-
conserv
23-4 **
MULTIPHASE
1
unsaturated
saturated
Circled models are usable. Numbers Indicate numbers of model reports
* Mass or heat transport in a deforraable medium.
** Massandheat transport model.
-------
TABLE A-13. SUMMARY OF THE SURVEYED HEAT TRANSPORT MODELS (continued)
Purpose and/
or Output
Evolution
of water
temperature
In wells
Distribution
of head and
temperature
of water
(a) unsa-
turated
zone
System
Single aquifer, pumping
wells. Time-varying heat
source at the boundary.
Single infinite homogene-
ous isotroplc aquifer,
natural uniform flow.
Pumping and recharge wells.
Single homogeneous
confined aquifer, single
Injection - withdrawal
well.
Rigid and homogeneous
porous medium
Processes
Heat
Transport
Conserva-
tive,
convection
Conserva-
tive,
convection
and con-
duction
M
Flow
Coupled
with
flow
Spatial
Dimen-
sions
2 Hori-
zontal
ti
1 Hori-
zontal
radial
1 Verti-
cal
Method
F.D. '
Analytic
Analytic
(approxi-
mate)
F.D.
Docu-
men-
tation
1
Complete
(French)
Internal
Report
Reference
(French)
Aval-
abil-
ity
No
No
No
Listing
Fast
Appli-
cations
7
Field
(Many)
Field
Field
Special Features
^imputation of tem-
erature on an
xternally given flow
at tern.
etri Input. Mixing In
ells. Output option*
f streamlines and
:emperature fronts.
Iser oriented.
Input: Front of
heated water,
Injection - with-
drawal schedule.
Conduction at
moving front and
confining layers.
User oriented Input
Connection with an
atmospheric surface
layer model .
Interdependent flow
and heat parameters.
Time s tep dependent
stability.
Identification
Model
No.
30-1
30-2
30-3
30-4
Coun-
try
ranee
'ranee
.
U. S.
France
Insti-
tution
URGEAP
RGM
G.E.-
TEMPO
Instltut
de
Mecan-
ique
Reporter
(year)
BURGEAP
irlngarten
Landel
(74)
AK
(75)
Vauclln
(76)
-------
TABLE A-13. SUMMARY OF THE SURVEYED HEAT TRANSPORT MODELS
Purpose and/
or Output
(b) satura-
ted zone
Pressure
water con-
tent and
temperature
in a
geothermal
reservoir
with
(a) flow of
steam
(b) joint
flow of
steam
& water
Sy s terns
Multllayered aquifer.
wells
Porous medium with double
porosity: fractures &
pores ,
Heterogeneous isotropic,
compressible porous me-
dium. No sources or
sinks. Conductive solid
phase . Nonhomogeneous
liquid.
Stationary water.
Flowing nonhomogeneous
steam.
, Compressed water,
two-phase mixtures.
Superheated steam.
Heat
Transport
Conserva-
tive,
convection
and con-
duction
it
ii
Won— con-
servative,
convection
and con-
lucCion
Conserva-
tive,
convection
and con-
duction
Flow
Jon-
coupled
Coupled
Coupled
Coupled
Coupled
Spatial
Dimen-
sions
3
3
1 or 2
or 3
1 Ver-
tical
2 Hori-
zontal
Method
F.D.
F.E.
Inte-
grated
F.D.
F.D.
F.D..F.E
Docu-
men-
tation
Hone
In prep-
aration
Complete
Open file
repor t
without
opera-
tional
instruc-
tions
Open-file
report
Avai-
attl-
ity
Ho
Aftar
publica-
tion
Yes
Yes
Yes
Past
Appli-
cations
None
None
Special Features
Steady state.
Instability for
extreme parameter
contrasts.
Temperature and flow
coupled through vis-
cosity/Speclal solution scheme
lifferent velcosity in pores &
ractures .
Research
& Field
None
Initial
stage
Thermal equilibrium
letween solid & llqu
lumerical dispersion
restricts step size.
User oriented.
Phase change.
thermal equilibrium
among phases.
Vertical heat leakage
>y conduction. Con-
it rain ts on pressure
•ange and saturation
:hange. Possible
:on version from sing
ihase flow to 2-phas
flow. User oriented
Identification
Model
No.
30-5
30-6
30-7
d.
30-8
30r9
!
Coun-
try
ranee
. S.
U. S.
u. s.
U. S.
Insti-
tution
niv.
de
Bordeaux
III
Yale
Univ.
U.S.G.S
U.S.G.S.
U.S.G.S
Reporter
(year)
Cazal
(77)
O'Neill
(77)
Sorey
(74)
Moench
(76)
Faust
and
Mercer
(77)
-------
TABLE A-14. THE PRESENT STATUS OF HEAT TRANSPORT MODELS
3
4J
CO
01
4J
01
p
&:
Si
scace 1
Functions |
•H
Non- 1
Linear |
S -H
> 41
gj
rH W
0
o
r-l
ad
-------
TABLE A-15. DEFORMATION MODELS (continued)
Purpose and
Output
SUBSIDENCE
AH, AZ
H, AZ
H, AZ
H, AZ
0, Az
p, AZ
System Elements
Single Pumped Aqui-
fer
2Pumped & Recharg-
ed Aquifers. De-
fornable Aquitard
Multiple Aquifer-
Aqultard System
Multilayered Aqui-
fer
Multiple Aquifer-
Aqultard Series.
Deformable Aqui-
tards
Saturated zone
compressible
groundwater
Processes
Flow
Spatial
Dim. S
Flow Flam
2 Horizon-
tal
11
II
2 Verti-
cal
1 Verti-
cal
3
Deformation of
Porous Medium
Elastic
Uncoupled
"
it
M
Coupled
„
Non-
Elastic
Coupled
ii
Method
F.D.
F.D.
F.E.
F.D.
F.D
F.D. in-
tegrated
Documen-
tation
teferences
leferences
(Japanese)
ii
„
References
Manual &
References
Availa-
bility
Yes
After
publica-
tion
»
,,
After
publica-
tion
Yes
Past
Applica-
tions
Field
Field
(many)
Field
(many)
Field
(many)
Field
no tie
Special
Features
Storativlty of aqui-
tard. Han tush Leak-
age Function
Storativity of aqul-
tard
Calibration Option
Pressure dependent
permeability & stor-
ativity. Modified
Terzagi theory for
to loading and un-
loading. Input:
Stress history.
Calibration option
Nonlinear state
functions. Stress
dependent permea-
bility & void ratio
Arbitrary sources &
sinks, General coor-
dinates
Identification
Model
No.
40-1
40-2
40-3
40-4
40-5
40-6
Coun-
try
U.S.
Japan
Japan
Japan
U.S.
U.S.
Insti-
tution
Mexico
Tech.
com-
pany
com-
pany
com-
pany
JSGS
Univ.
(Berk-
eley)
Reporter
(vpnr)
Gelhar
(75)
Shibasakl
(70)
Shibasakl
(76)
Shibasakl
(72)
Helm
(71)
Narasimhan
(76)
to
-------
TABLE A-15. DEFORMATION MODELS
Purpose and
Output
SUBSIDENCE AND
p, AZ, Ax
p, AZ, Ar
System Elements
Saturated zone
compressible
fluid
Saturated zone
Processes
Flow
Spatial
Dim. &
Flow Plane
2 Vertical
2 Vertical
Deformation of
Porous Medium
Elastic
Uncoupled
Uncoupled
Non-
Elastic
Uncoupled
Method
F.E.
F.E. +
Laplace
Transform
Documen-
tation
In pre-
paration
7
Availa-
bility
After
public-
ation
No
Fast
Applica-
tions
Field
7
Special
Features
Blot's equations
Linear state func-
tions. Time varying
loading
Axisymmetrlc,
Viscoelastic option
Identification
Model
No.
40-7
40-8
Coun-
try
Neth-
er-
Lands
U.S.
Insti-
tution
Univ.
(Delft)
Univ.
[Prince
ton)
Reporter
(year)
Verrui j t
(75)
Safal
- (76)
to
List of Symbols:
H plezometrlc head
AH drawdown
p pressure
a effective stress
AZ vertical displacement
(compaction or expansion)
Ax, Ar horizontal displacement
(lateral or radial, respectively)
-------
TABLE A-16. THE PRESENT STATUS OF DEFORMATION MODELS
State Functions
Linear
Nonlinear
Flow Dimensions
r-l
a
CM
CO
rH
CM
ft'
Single
Aauifer
Multiple
Aauifer
Saturated Zone Saturated-
„ . . . . Unsaturated
Single Fluid Phase Multiple Zoneg
Subsidence
Elastic
Un-
Coupled
40-1
40-2
40-3
40-4
Coupled
40-5
41-6
Nonelastic
Un-
Coupled
40-5
AQ-6
Subsidence And Lateral Displacement
2 Dimensional 3
_, , . Dimensional
Elastic Nonelastic
Un-
coupled
40-7
40-8
tn
-------
K
TABLE A-17. OTHER PREDICTION HOOtLS
PURPOSE
AND/tlR
OUTPUT
solving
aubsurface
flow and
transport
equation*
Concen-
tration of
a consti-
tuent or
tempera-
ture
Pressure
and tem-
perature
in
accumula-
ting sedi-
Pressure
and tem-
perature li
a liquid
dominated
g«o thermal
Pressure,
contaminant
concentra-
tion and
temperature
In a het-
erogeneous
Frost pro-
pagation
and frost
heaving In
a water
saturated
porous
SPATIAL
DIMENSIONS
ANU FLAME
2 or 3
2
1 D
Vertical
3 D
J D
__ Hyj"
Saturated-
Una* t-
urated
Saturated
OLOCIT SYSTE
WIPERS —
)eformable
Deformable
porous
matrix
let erogen-
ous confin-
•d aquifer
Homogeneous
Isotropic
squlfcr
M
FRASES
lomogeneoua
Fluid
Fluid. Solid
Single
phase com-
>res*ible
fluid
Single fluid
Solid
FLOV
Steady or
unsteady
Nonsteady
only
PROCES
DEFORMATION
X
Compaction
;>f Sediment i
Vertical
:oopac t Ion
elastic or
lonelastic)
;ES
MASS TRANS-
PORT
Convection,
Diffusion,
Dispersion,
First order
decay and
BOTption
Convection,
Dispersion,
radioactive,
dacsl,
adsorption,
desorption
HEAT
RAHSPORT
X
^induction,
lepers ion,
orced con-
vection
Conduction,
:onvectlon
Forced &
natural
convection,
dispersion,
conduction
METHOD
•eneral F.E.
.•tad with
block
teratlve
qua t ion
F.E.
P.D.
ntegratad
.D. , accel-
erated
Iterative
ichema
F.D., linear
successive
over- relaxa-
tion or
direct In-
version
'.D. itera-
Ive, com-
uitatlon of
ftmpsrature
Isplaceuen
if frost
Ine
DOCUMEN-
TATION
(?)
Listing
•nd
Referenc.
Complete
(theals)
Complete
Complete
AVAIL-
ABILITY
Ye.
Ye.
Yes (I)
las
!>>
FAST
J-PLIC X-
10MS
lono
Fi.ia
(OHM)
Hon.
?
(Ro.d
dnlgn)
.
Special Feature.
Ceoerel purpose code ror solving
transient nonlinear partial
differential equations in one or
two dependent variables
steady or transient noncoiiservatlve
best or Htass trsneport In a variably
saturated deforawble porous Bedliav
'or a (tlven velocity field. Adept-
able to verlous computers. Numerical
dispersion In highly convectlve
Arbltrery heterogeneity, ieotropy.
Nonlinear state fvnctlona. Coupled
flow, heat end deformation. Auto-
matic adjustment of tlmr >tep.
;-icentratlon and temperature de-
pendent density and vlicosity, new
option of K constituent., first
on enthatpy. User-oriented.
Phase change, transient, free
surface, front line (Stefan's
problem) conditional stability.
User oriented.
odtl
o.
1-1
0-i
50-3
50-«
50-
iO-6
Identl
un-
y
.5.
cation
eti-
tlon
n
iver-
ty
nford
iera-
ons
Company
nlver-
Ity of
Inlver-
llty of
Calif-
ornia
Centra]
les
'onta
ind
;hau»e
porter
ear)
74)
77)
herp
74)
simhan
(76)
(75)
it
tatheMa-
tlquea
(75)
-------
TABLE A-18. THE PRESENT STATUS OF PREDICTION MODELS
Statistics
Deterministic
Mathematics
Linear
Nonlinear
Process
Flow
Mass Transport
Heat Transport
Deformation
Heat & Deformation
Mass & Deformation
Mass & Heat
Mass, Heat &
De>f orina t ion
Flow
Deformation
Mass Transport
Stochastic
Single Phase
Homogeneous
Conservative
Saturated
Lum-
ped
X
HDL
X
X
X
X
X
HDN
X
X
X
X
X
10-6
X
Sat. - Unsat.
Lum-
ed
X
HDL
X
X
HDN
X
X
Sub. - Sur.
Lum-
ped
HDL
X
HDN
X
Nonconservatlve
Saturated
Lum-
ped
X
HDL
X
23-1
23-5
X
HDN
X
6
\1
Sat. - Unsat.
Lum-
ped
X
HDL
X
iO-2
,U-2
HDN
X
Sub, -Sur.
Lum-
ped
X
Dis-
tri.
Nonhomogeneous
Conservative
Saturated
Lum-
ped
HDL
HDN
2-1
2-1
X
Sat.
Sat.
5
>
Sub
Sur.
Nonconserv.
Subsurf .
Dum-
ped
Dis-
trl.
iO-5
X
Sur.
Sub.
Multiphase
Homogeneous
Disjoint
Sat
8-7
8x5
Sat.
Un-
Sat
i
Sur
Sub
Joint
Sat.
|18-9
18-1
X
Sat.
Un-
Sat
L
Sur
Sub
?
00
§
!t>
o
c
CD
to
Abbreviations: HDL - Hydraulic
HDN - Hydrodynamlc
Numbers are Model Numbers.
Sat. - Saturated Sur., Surf. - Surface
Uneat. - Unsaturuted Sub. - Subsurface
-------
TABLE A-19. CROUNOWATER MANAGEMENT MODELS: QUANTITY (continued)
..„,,>„,,
Diatrlbution
of pumpage
under given
rules
Optimal
location and
cpcratlon of
wells
"
Optimal
operation of
a well field
System
yilrulo-
ir
Aquifer
Cells
ingle
Aquifer
D
hqulfer
Homoge-
neous
or
letero- .
•eneotis )
Aquifer
21) or
3D
Aquifer
2D
Single
or
Multiple
kquifer
frliiiti-
Water
supply
system
1.1 10
ii indies
allnity,
later Leve
Depth of
Sea vat or
ntruslon
None
Head or
Drawdown
In well
Head
Head,
Drawdown
Decision S|J)IP
Variable!
Pumpage. Level
Lacking
Capacity of
punpage and
conveyance
Well location
Pumping rate
lead
Well location
'limping rate
'•
of
state
vari-
ables
Draw-*
down
Lower
lound)
lumping rate
Draw-
down
H-ci-
; Ion
Opera-
tional
rules
Heed
Lower
Bound
,
lepth.
iiame-
;er
Pum-
ping
capa-
bound)
nihcTB
Total
Pumpagf
(Output
from a
Lumped
Model)
Total
net pu»
page
Fotal
>unpage
-
'•
Object Jvc
k"iinr(Jon
Sum of hea
at node
points at
each tine
Interval
Cost
Cost
Discounted
operating
cost
(concave)
Linear
combina-
tion of
pumping
rates
H.Hluul
)pe ra-
tional
Algori-
thm
s
L.P.
Simu-
lation
and
flttin
L.P,
Conca->
progra
mmlng,
upper
linear
constr
ints
(TUI
Method
L.P.
Jufti-
cnlnr Ion
Descrlp-
ion
Hebrew)
Refer-
ences
Refer-
ence +
lisserta-
tlon
(Bostock:
7
?
Complete
vaijn-
11 Hy ••
Yes
Yes
7
1
Yes
»««l
\pplJ cat k>iv
Field:
Planning
of pumpage
distribu-
tion
'leld (once)
'easiblllty
typothetica;
Examples
?
lypothetlcal
Field
Special Features
Operational rules depend on
priority levels of demand and
critical levels of hydrologlc
monitors. Policy matrix
corresponding to the above.
Single time step operation.
Conjunctive with simulation
model.
Simulation vlthln optimization
framework. Physical Objective.
Solution at each interval used
ss initial condition for next
interval. Static option.
Uncertainty in estimating hy-
draulic conductivity of hetero-
geneous aquifer. No specific
Algorithm for curve fitting.
Cost Includes construction.
replacement, energy and water
deficit. Dynamic
Cost Includes Drilling, pumps
and surface network. Conjunc-
tive simulation and optimiza-
tion. Static.
Discounted operating cost
only. Dynamic planning model
formulated as a discrete time
control problem.
Influence coefficients computed
by simulation as input to
optimization. Programmer
oriented.
Identification
Model
Number
61-1
61-2
61-3
61-4
61-5
61-6U
•Repo
Coun-
try
Israel
U.S.
U.S.
France
U.S.
France
rted by
Insti-
tution
Tahal
Stanford
univ.
Univ.
of
Arizona
Arlab
Cornell
Univ.
Ecole
de
Mines
Haimes ai
Modeler
Schwartx(73)
Alley *
Aguado (76)
Bostock *
Simpson (77)
Roeffs
Baradat
Blanc
Willis
Newman (7?)
Levassor
(75)
id Das.
to
00
-------
to
vo
TABLE A-19. CROUNDWATER MANAGEMENT MODELS: QUANTITY
'urpnsc
Optimal
Operation of
a well field
Optimal
Mining of A
Basin
Optimal
Cropping
and Pumping
Psttern
Economic
Incentives
for Efflcle
Msnagement
System
lyd ru lo-
gic
Ground-
water
2D
Linear
Ground-
water
Basin
2D
Linear
Single
Aquifer
Linear
t
fell no-
logic
Water
Supply
Pumping
Wells,
Farms
(Irriga-
ted)
Irriga-
ted Farm
Wells
later
Supply,
Irriga-
ted
Farms
UltC
.n r tables
rawdown
or
Head
rater Level
Drawdown
Drawdown
Decision
Variables
Seml-Annual
Pumping
Pattern
Pumping ,
rate in each
tljne step
Irrigated
Acreage of
Pumpage,
Acreage of
Crops
Pumpage,
Drawdown,
Acreage ,
Taxation
and Rebate
Stale
later
.evel
lelow
fhlch
nils
ire
ixcluc
>raw-
lown,
icre-
ige
Jraw-
down
ion
Veil-
pum-
ping
capa-
cltle
Acre-
age
of
crops
Con-
sump-
tive
use
of
crops
Acre-
age
mini-
water
qu
ping
Tllicrs
Total
Pumpage
Objective
'luict ion
Cost
NET Bene-
fit for
Each farm
[Annual)
Net Bene-
fit for
Entire
Basin
(Long Ten
Net
Benefit
from
Fsrmlng
Net
Revenue
(2 levels)
Baalnwlde
Each Farm
cthotl
Imula-
lon
T.B.)
Opti-
1 ratio
Q.F.
imula-
.on
ollowet
y L.P.
teach
olnt
Slmu-
.atlon
[re-
sponse
func-
tions)
follow
)ecom-
posltl
Optiml
zation
by Q.P
cu-
nt.it ion
T
eference
No
teference
i Report
va 1 la-
ill ty.
7
Yea
No
Yea
Past
\ppHcntlonr.
Hypothetical
Case
Research
Model was
developed
for Research
only
Hypothetical
Case
Special Features
ATF -which relatea pumpage
(or Recharge) to Drawdown at
locations where pumpage (or
Recharge) are Decision
Variables. Dynamic.
Steady Recharge. Evapotrana-
plratlon. Crop Production
Function. Depth-dependent
water cost.
Regret Function as a measure
of Economic loas given aa
Incorrect decision because
mation. In combination with
Bayeeian Deciaion Technique
this function Is used to rank
data by priority for further
data collection. Dynamic.
Large storage requirement,
Algebraic Technological Func-
tion. Quotas, Taxes, and
Rebates. Pumpsge below the
Quota entitles to a Rebate,
Pumpage above the Quota Is
Taxed. Each Year Taxes are re-
distributed among users with
Optimisation and Coordination.
LaGrange Multiplier aa cost or
savings per unit digresalon
from quota. Dynamic.
Identification
Model
Number
61-7
61-8
61-9
61-10
Coun-
try
U.S.
U.S.
U.S.
U.S.
Insti-
tution
U.S.G.S
U.S.G.S
U.S.G.S.
U.S.C.S.
Modeler
(year)
Haddock*
(72)
Bredehoeft
Young
(72)
Haddock
(73)
Haddock *
and
Haimes
(75)
*Reported by Haimes i Das
-------
TABLE A-20. CKOUNDUATBR MANAGEMENT MOORLS-. QUALITY AND QUANTITY
Groundweter
Supply and
Salinity
Control
Waste Water
Disposal
Through Wella
A« A Component
Of A Regional
WaatB Treat-
ment Sy»t»
Waste Water
Disposal
Supply
Syst
Aquifer
Under-
lying
Irri-
gation
District
2D
Ground-
water.
Imported
water
Croynd-
watar,
conser-
vative
Pollu-
tant*
..
Irri-
gation
Supply
Waste
Diapo-
G round-
est r.
Was e
vat r
r*c a-
Cround-
water
Storage
Salinity
tanta
Head,
Pollutant
t rat ton*
Capital for con-
struction and
Equipment. Water
for Leaching.
Uatar for Irri-
gation
of Dilution Water
of known Quality.
Uaate water to
injection wellt.
level before in-
lond distribution
[o Injection well*,
lead and concen-
tration In wells.
Puttpage dlicrlbu-
tlon.
Salin-
ity
Storage
conctn-
toni train
PM«plng
Capacity
Wat«
Qual ty
L«ve .
Cape Ity
of 1 Jec-
tlon
w«lla
of wella
t«
upply
ot«l
aate
la-
harge
Function
Dlicounted
Net Benefit
Aaaoclattd
with Uat«r
Ua* and
Salinity
Total Covt
(Inclvding
removal by
surface
Treat awn t 4
Importation
of Dilution
water
Mlntoiun
co»t
coat of
punpage,
wante Injec-
tion and
•urface
tr«ata*nt)
Method
Nonlinear Progra*ln|
(Lagranglan Formu-
lation.)
SlnuUtlon, MiMd
element }. Twp-atage
Concave Prograaing):-
(I) Opt Ml Pumping
and Waa a Injection
(Quantl y Aspect)
(2) Opt aial Surface
Traatw* t (Quality
Aspect)
tat ion
R*f«r«nc«
ReEtrenc*
ability
?
?
Past
cations
T
Hypo-
thetical
case
Field
Analytical framework for *n integrated
approach to the Hater Uae-Salialty Problem.
Dynamic.
Regiontl Msste TrcatMtnt Syetm Including
Haste Water Treatment Plant and External
Sources of Dilution water.
Given injection rate* through wells snd
piaiplng pattern. fVo PiaansionsL
Steady Plow and Haas Transport Equations
Optiaitatlon model for conjunctlv* long
range Hanageaent of Croundvatcr Quantity
aaslaiilative capacity of a Groundwater
basin. Operational policy for a Multi-
coaponent Pollutant iyates> Including well
injection* surface treatMnt, and water
supply. Hase Tranaport by H lepers ion and
Convection. Hon-coave*. problem.
Dynaaic
Mo.
#2-1
61-3
Identification
(y«r>
U.S. University Cunsiinga*
of HcFtrland
Rhode (74)
Island
University (76)
U.S. Cornell Willis*
University (75)
i
1 Reported by Haiswa and Dae.
-------
TA1LC A-21*. COIUlmCTlVE GROUTOVATER AND SURFACE WATER MANAGEMENT HODELS: QTANTITY - UIMPET, HOOE1.S
Policy
planning
- Develop-
ment and
Operation
Policy
planning
- Operation
Policy
planning
- Ope rat lor
and pricing
Syatem
Hydrolo-
Ground-
water &
•urface
water
baa Ins
••
"
..
Cround-
wate
surf ce
wate
Inpo ted
wate
Techno-
Supply,
uae and
produc-
tion
••
"
«
Supply
and uae
State
Storage.
Level of
develop-
ment
Storage
Storage
Available
water
Stochaatic
replenish-
ment
Stochaatic
demand
StOCMtlC
replenish-
ment and
• treaofloif
Stochastic
recharge
tic
"
Determinis-
tic
Dec iff ion
Capacities
Recharge
Withdrawal
Water Al-
location
alte
Import.
Allocation
P«W
Allocation
recharge
Source of
•upply
Pumpage
Price of
Conatra
Stat*
a tor-
capa-
city
a tor-
age t
capa-
city
city
O.C1-
• llo-
c.tlon
D.v.1-
opncnt
Site
of
f.cll-
Itles,
.upply
tog
r.t.
,
t
upply
1
igher
models
.upply prlc.
1
nte
Othere
Demand
ating
rulta
Demand
Objective
Expected
discounted
net benefit
Expected
•upply
discounted
net benefit
..
Minimum
Cost
Net benefit
Method
Stochae-
tic
D.P.
Itera-
tive
L.P.
Stochaa-
tic
D.P.
«
(a)Konte
Carlo
simula-
tion
(b)Honte
Carlo
linear
program-
ing
Out of
kilter
algor-
ithm
Segmen-
•trained
mlnimi-
DocuMncation
Complete
(Hebrew)
Reference
(Enall»h>
Listing mod
Hone
Hot epeclfied
Report
'
Av«ll-
ty
»••
V..
Past
App
Field
Research
no
unknown
Field
(once)
Special Feature*
Part of an integrated planning ache**.
Loae due to deficit In aupply. com-
pensation for cutback in allocation.
Salvage value. Multiple sources and
user*. **P.d. of etate * oblectlve
Given demand. Nonlinear ptmrnilnf
cost. Linear decision rule. Chance
constraints. Random parameters
Value - Iterative method (or Markov
chain. **P.d. of atate k objective
Field
(one.)
Quadratic benefit function. Inter-
water
Mnn
j (many) 'Carlo methods. Part of an Integrated
I Mostly ) planning achem*
simulation '
yea Caae itudy
(example)
Network analysis as a screening tool
and tttucturea In a multiaourca and
multiuser ayatem. Shadow prices
T Research
Multiple coureea. Relatlonahlp
between demand, supply and price.
* Reported by Halmes and D*a
** P.d. - Probability density
Identification
Model
M-1U
M-2
63-3
*3-A
Counttj
tirail
U.S.
U.S.
U.S.
63-5 T.r..]
Institution
Irt.1
Hew Mexico
Tech
Modeler
Schvari
<76>
1
Montane
State Ifnlv,
Univ.
Illinois
Butt
Saleem
(7»)
[
U.S. Univ. Hmmtm .*
(75)
M-7
U.S.
UCLA
Hobuaherl*
Grant
(73)
-------
TABtE A-2U. eOMJUMCTIVE CROUNDUATER AMD SURFACE WATER MAKACEMENT MODELS: QUAKTITT - DISTRIBUTED MODELS (continued)
I'ur.iOHu
Oper«tlon of
A Strctw-
Aqulfer
System under
Optimal Water
allocation
for agricul-
ture from a
Stream aquifei
system
OptiMl
Operation of
e Stream-
Syetem under
Stochaetic
Maximization
of yield from
a water
system
System
yslrolo-
ic
Inter-
con-
nected
Aquifer
&
Stream
Ivapo—
transpi-
ration
Coupled
2D
iround-
water
and
St react
'low
Coupled*
2D
Ground-
water *
Stream
flow
Ground
Water-
2D, Sur-
face
Water,
Water
cclino-
Io8lc
Wells.
lanals.
Leser-
volrs.
Irri-
gation
rrl-
gated
gricul-
ure
Irri-
gated
Agrlcul
ture
tatc
ariablcs
:orage '
Stream
Flow
Ground-
water
level
Stream
flow
Ground
Water
Level J
or their
Gradients
Dec ia ion
variable!
ftrnpag* Surface
tater Delivery
to Canals.
Uservolr Opera-
tion
Pumpage, Recharge.
Downstream eupply,
Acreage of crop*
cream withdrawal,
roundveter pump-
age & recharge.
o stream
Pumpaga
cute
Ca-
pac-
.tles
down
ccl-
lon
Dper-
tlon-
1
ules
ur-
ace
ater
or
rri-
atlon
Trans-
:er
'roai
icrea
to Aq
uifer
Reuse
ping
capac
Ity,
Annu-
al
Pun-
page
Lhors
rior
ppro-
rla-
lon.
nter-
t«te
Coet-
acts.
Demand
iaxlBMn
.creagc
Punpln)
^»ac-
ltrr
Down-
stream
flo.,
•t«r
right!
Right..
Satis-
faction
of
expect-
ed Dc-
und
Ilnlenim
(uppiy,
iblllt
>f IB-
lorted
later
bjcctlvc
:tinetlon
ttean
Annual
aliu &
tandard
ivlatlon
f Supply
Met
B.nefit
Froei
Agricul-
ture
Expected
Total Die
counted
Operating
Cost
Total
Punpage
over
Planalng
Period
,
clhoit
Slew-
atlon
«
Ac-
tuat-
ing
Simu-
lation
&
Simu-
lation
&
Q. P.
L.P.
ou-
ntntion
None
-
Refer-
ence
Refer-
ence
7
alla-
lity-
Yea
lea
7
>t
plJcatinn
Imlatlona
f Water
Management
IternetlTea
i River
alleya
(Many)
Field
once)
Exaeqile
Special tVaturca
Raaponae Function!. Operational
Rulea. Prograiaeer Oriented.
Dynaailc.
Static and dyneBlc optlone. Two
Linear Progreaeilng Routlnee. One
deteralnee Cropping Pattern. The
other ellocatee avalleble weter.
Optlnal lolutlon not guaranteed ae
j.nput to optimisation la obtained
from emulation, Inatead of almulte-
neoua coupling of the two.
Algebraic Technological Function from
Croundweter Simulation. Minimum coat
Management Rule. Senaltlvlty of Die-
counted expected coat and Operating
Rule to the Variation In Parameter
Value. Stochaattc demand and
Drawdown.
Linear Syetem. Influence
Coefficient! which are evaluated
only Cor tinea and location of
Intereat. Maximization of yield aa
an adequate objective for planning
long tern Aquifer exploitation when
no conitralnta on budget and demanda
are conaldered.
Identification
Ho Jo I
Number
63-5
Coun-
try
U.S.
U.S.
63-9
63-10
«-ll
U.S.
Iirael
Insti-
tution
u.s.c.s.
Keaourcei
for
future
U.S.G.S.
TAHAL
Modeler
Oreer)
Taylor
Luekey
•
(73)
Young
Bredehoeft
(72)
Haddock*
(74)
(73)
•reported by Halua 1 Du
UJ
10
-------
TABLE A-21b. CONJUNCTIVE CROUNDUATER AND SURFACE WATER MANAGEMENT MODELS: QUANTITY - DISTRIBUTED MODELS
I'urjxvii'
Optimal
Operation of
Limited Re-
gional Hater
Resource! by
a Decentral-
ized Manage-
ment SyBten
Optimal
Operation of
System
Hydrulo-
r.ic
Ground-
water
Surface
water
Linear
2D
Multi-
Aquifer
Coupled
with
Multi-
JotU:
Agricul-
ture &
[ndua-
trtal -
municipal
rater
Supply
Multiple
Users
i ;i If
firJflhlt-A
Head
Ground-
water
Stream-
flow
Rate
Decision
variable*
Regional Authority
Dec IB ions i Inter-
sub regional
Boundary Water
Levels; Artificial
Recharge in Sub-
regions. Pumping
Tax Rate. Local
Agency Decisions:
Flows across Sub-
regional Boundary
Pumpage la Sub-
region. Import
Groundvater
Pumpage. Surface
Artificial Surface
water Recharge
_.'.Ci"
SL.'ilC
Water
Level,
Pum-
ptog
Capac-
ity
Draw-
down
st rnin
!Vci-
sion
Im-
ported
Water,
Capac-
ity of
re-
charge
Facll-
ty.
*ro
low
nter-
ubre-
*
u
londl-
:lon
Pum_
.Ing
Ity.
*-
:harge
Opac-
ity.
iur-
:ace
rater
flth-
drawa
ihcrs
rtlfi-
lal
harge
-ost
ust
qual
ax
He venue
Demand
(?)
Mini-
aid
Fenalt
for
De-
pletin
Surfac
Stream
Objective
function
Cost of
Water
Supply
net
Benefit
C til 0(1
tecom-
posl-
lon.
imu-
atlon,
tera-
ive
wo-
Optlml-
atioo,
tera-
tive
~
Decom-
posl-
Slnu-
latlon
Optimi-
zation
Reduced
3radi-
;nt
\atlon
)I1CU-
it'iiliit inn
?
Complete
valln-
llity •
?
Yes
.u;t
\pjil Jc;it inn
Hypothetical
^ase
Field:
Once
Special Features
Coordinated Planning Methodology for a
Decentralized Water Management in a
region Water Supply administered by
several Local Agencies, each control-
ling the development and Operation
within a subregion, except for inter-
subreglonal Boundary Conditions,
Artificial Recharge Rate and Pumpiug
Regional Authority. The Tax Revenue
is spent on an Artificial Recharge
Facility for the Region. Decomposition
provides for Independent Optimization
of each Local Agency's cost Function
which is not released to the Regional
Authority. Computational efficiency
needs improvement.
Hethodolgy for Analyzing a Complex
Water Resource System. Algebraic
Aquifer System. Stream-Aquifer
Response Functions. Hierarchy of
Simulation Models. Iterative Coor-
dination.
Convergence of Hierarchical Co-
ordination Scheme not guaranteed.
Computational limitations due to
high dimensionality. User
oriented.
Identification
Model
Number
63-12
Coun-
try
U.S.
Israel
Vene-
zuela
"
11
Insti-
tution
Case
Western
Reserve
Univ.
u
Univ.
"
*'
Modeler
(yaar)
Yu
Halmes
(74)
Haimes
Das
Drelzln
Garay
Sarkar
Beconegra
00
CO
-------
Ueitvwater
Treat Man t t
Waatewater
Treatment t
Water Supply
Croutid-
water
Supply
and
Salinity
Control
Syat
ground-
wnter &
weter +
weate
water.
.u»f>ed
iround-
(.t*r. 2ft,
urface
wtar.
loported
rater
eet
Supply,
uae.
duct Ion
treat-
Kent
hgricul-
tural
'tctduc-
lon.
r rl-
at loo.
Quantity
and quallt;
biological
Aa above
plua
thermal
Ground-
water
Salinity
Datenlnia-
tlc
-
Ih
Wa^cr
worke
Puiep-
«8«
«f
rcat-
etant
Mod-
\fu!:"Jl
Source
of
tl
of
»uppl)J
R round
water
PUBf-
P«I«<
Sur-
face
Mter
With-
drawal
Hater
Trana-
nort
W-.tcr
ler-
port
t'N
Econa-
o.
De-
alr«d
Ity*
uant-
ty
Ity &
ual-
ty ol
water
F"
rrl-
traln-
llic-r*
ell*-
lllty
level
Irri-
tation
Ohjc^Uvt-
•imrrlon
lack be-
tween de-
eached
evela of
tate
arUblei
lack be-
tween plan
ed policy
leple-
•entation
Coat
otliml
Ixed
nteger
•Ing
.Inear
ilng
lotl-
lon
if Salt
rena-
10 rt b
Follow
y De-
ailed
lmt~
at Ion
Char-
cter-
•nuitfoii
In
ranch
In
rench
Refer-
ence
fllty
no
no
,M
oet
once)
landing
f river
aeln
panaga-
Mnt
Onco 01
A Field
Cat*
*"*""
Special Faaturea
ultlple cholcca of eotircae and treatOMnt
y atendard package*. Calibration of econoeiic
eraawtere.
upply. ftrrv*nln|i madvl Cor aan aging large
ialt Tranaport by Convection and Dlaperalon
^oat Coat CoMblMtlon of Dlatrlbutlng Ground-
wter and Surface Water over the Baaln within
treacrtbad Salinity and Irrigation RequlraMnta.
:round and Surface Water* not Connected.
todel
lUBbCt,
»*-!
U-2
^>untry
Franc*
U.S.
Inacl-
Ecole d*
Hlnaa de
Parla
Hlnea de
Parla
Colorado
State
Unlvcrelty
Unlveralty
of
California
Modeler
Hubert
(76)
(H)
He 1 wag
Lebadle
(76)
-------
TABLE A-23. THE PRESENT STATUS OF MANAGEMENT MODELS
Management Aspects
Number &
Kind of
Manage-
ment
Oblectives
Single
(Physical
or
Economic)
Multiple
Number
of
Manage-
ment
Levels
Single
Multiple
Area
Water
Quantity
Water
Quality
&
Quantity
Quantity
Quality
Quantity
Task
Supply
Salinity
Control
Waste
water
Disposal
Waste
Water
Disposal
and Water
SuDDlv
Environ-
mental
Protection
Supply
Decisions
Development
Operation
Operation & Productta
Operation & Economics
Development
Operation
Operation & Economics
Development
Operation
Engineering & Economic!
Development
Operation
Engineering & Economics
Development
Operation
Operation & Economics
Oper. * Prod. & Econom:
Hydrologic System
Single Phase
Homogeneous
Conservative
Saturated Zone
Dumped
cs
Distributed
Hydrau 1 Hydro-
-lic dynamic
r ,i-i
C 61-j
c "->
«-l«
CP feUQ
C 61-7
B 61-8
B "-'
B 62-1
C 62-! 1
B 61-10
C 61-* l
Satu-
rated-
Uhsatu-
rjated
Subsurface & Surface
Lurape
S^r
TS1-3
,6J-»3
B63-5
C63-6
M3-7
P64.2
P64-11
Distributed
Hydrau
-lie
63-,3
Kj-ii
CH-IO'
W3-92
CM-3
h©>
C63T12
Hydro-
dynamic
Multi-
Nonconservative Non- Pnaae
Sa
Lumpei
urated Zone Satu- s,,h- ho-
Distributed rated- surface moRe-
Hydrau
-lie
C6Z-1J
Hydro- Unsatu- & neous
dynamic rated Surface
U)
CJI
Objective function: P-physical; B-benefit; C-cost
EP-economic or physical
1-static; 2-statlc & dynamic; 3-stochastic; 4-accounting; 5-multicomponent surface treatment
Oper.-operation circled models are usable
Prod.-production
-------
TABLE A-24«. IDEHTIFICATHW MODELS - DIUCT CALIUATim (rootlnnd)
u>
Ol
System
(Model
calibrated)
Distributed
Transient
Hydraulic
with given
of water
level e, and
data
Distributed
Hodel
Spatial
Detail
2-Horl-
sontal
'•
„
(complex
domain)
2-Horl-
K
Scalar
T
Scalar
or
Tensor
Scalar
Tensor
Scalar
One per
side of
S
X
X
X
Sources
terns
X
Others
Objective
Function
weighted.
Including
I (AU)2,
Various
optiona on
(AU) and
(AU)2
E (AD)2
Error be-
glven K at
a polat on
• •traam-
tube
t (AH)2
Constraints
on
Output
X
Method of
Non-
iterative
Least
squares
Q.P.
R.L.P.
Nunarical
integration
of the Boue-
ainaaq aqua-
tube
Numerical
solution oE
the wall
function for
T and 8 by
LJ.P, with
tlve algorithm
Documentation
Avail-
ability
Complete Mo
Spanish
T ' T
T
Complete
Complete
Under
development
Yea
T
Tea
Ho
Application*
Field
Research
Field
(once)
Field
Field
Field
Special Features
and Comment*
Spllee Interpolation of head over time.
Polygonal mean. Large core storage.
Sensitive to minor Input arrera. Need*
further development before uae.
face from dlaerata data. Koneonvex pro-
Flexible output and display. Smell core
source terme. Heed (or conductivity
values along a reference line intersect-
ing the atreamlinee. Solution for data
at one time point.
Magnitude of problem reduced by decompo-
sition into homogeneous regions, with
impervious boundaries each enclosing a
single well. Solution by opt imitation at
two levels: direct search and Causa
Small amount of cora storage by
correcting the perameters of the celle
of convergence. Applicable to a large
storage device.
Id« tlflcation ^
Model
Mo.
70-1
7V2
method.
70-4
70-5
Country
rgentina
(U.S.)
•reel
U.S.
laraal
1 net! tut ion
Covt.
Govt.
Reporter
(year)
Mavarro
C»)
E7Z)
Sagar
(73).
Frledrlchs
(75)
1
University of
Caae Western
Covt ^
Halmee
(67)
Dax
-------
TABLE A-24*. IDENTIFICATION HOOELS - DIRECT CALIIRATICIII
System
(Model
calibrated)
Sat of well*
with given
past record*
sod drawdown
Blackbox
systea with
observed tlM
put and output
undergoing a
linear and
stationary
process
Spatial
Detail
given
distances
between
wells
Indices
of
welts
Luaped
K
T
S
Sources
snd a Ink
terms
Others
Coeffi-
cients
of a
power
series
sponse
Func-
tion
relat-
ing
down to
Dunpage
Lumped
para-
meters
relat-
ing
down to
Impulse
re-
sponse
tiona
Objective
Funct ion
I (fls)2
Constraints
Output
X
1 (As)2
Sum of
weighted
sq.ua.re* of
predicted
and observ-
ed output
X
X
lion-
It era El v*
Stepwlse
regression
Decon vol-
ution
Iterative
Decomposition
gradient
search
Documentation
Nonexistent
1
Avail-
ability
(to
•
Applications
Being
tested
ID the
field
Research
Special features
and Comments
Ho puMplni and drawdown record* should
be Biasing for site* where drawdown
1» to be predicted. Presently expanded
to Include missing data and ungauged
•ites
Superpoaitlon of drawdown in well*
Deconvolutlon (determination of the la-
Applicable to a coaplei system or to
and nonststlonary aystema. User
oriented. Proved convergence. Shape an
and saoothnes* of response function not
always satisfactory.
Model
Ho.
70-7
70- S
Ide tlflcatlon
Country
U.S.
U.S.
Institution
IKS.C.S.
Colorado
State
Reporter
(year)
M&doock
<76)
Labadle
US)
de Harally
(69)
-------
TABU A-Ub. IDEHTIPICATION HOOELS - tKDIMCT CALIUATIM (contlmnd)
SyiiU'tt
(Model
calibrated)
Silt con**rva-
tlVt Cloaed
groundHCtar
baa in in coa-
tac Mich
•ur ac« water
pee record*
rel ted Co
vat r and ealt
balancaa
Olatrlbuted
steady
hydraulic
groundwater
[low nod*l
DUtrlbutid
noMt*«dy
flew Model
TWO Inter-
connected
aquifer
colwn»
BpatUl
Detail
2-Horl*-
tontal
«
«
•
Luoped
K
Scalar
Scalar
Verti-
cal
T
Scalar
S
X
X
Source*
X
X
X
Ottwri
[nitUl
Inter-
face
eleva-
tion
Ofaj active
Function
Difference
»•!«•••
naawrad
ud calcu-
lated head*
conduct-
ivity
•nd salt
content
Coaatrainta
Oft
Output
Hffersnce '
Mtwen
coaqiutad
rater
leva la
E (4H)*
; (wi)2
Method ef
Trial
Afld
' Error
X
?
Search
Gradient
Gradient
(binary aaarch
technique)
Docuewntac ioa
Hot apecifUd
Lit tint ooly
Deacrlptlon
and
reference*
Ho
Avail-
ability
Vnknovn
No
Unknown
Ho
Applicative
Unknova
Field
Unknown
Field
(-any)
ipecUl Future*
Stvady acate approKtaiatlaa.
CO
-------
TABI.K A-24b. IDENTIFICATION MODELS - INDIRECT CAL1BWAT1ON
U>
Syst.-m
(Mode 1
r.-tl Ibrnti'i!)
nonateady
hydraulic
flow model
"
As above.
but Steady
SpaLinl
Ui-l.ill
2-Horl-
"
K
T
Scatar
as a
second
order
poly-
func-
of po-
sition
Scalar
S
X
terms
X
Other*
toe fi-
rle ta
of he
T p ly-
non al
tt s of
pn a-
he ds
Objective
I (Alt)2
Constraint*
Output
X
Difference x
between
I™' '-
wate
leve 6
flow c ir-
ections
Method of
Trial
Error
Iterative
Karguardt'a
nonlinear
estimation
Special
gradient
net hod
Accelvra ed
of quasi
Unc-arU -
tion, an
method
Documentation
Complete
preparation
Avail-
ability
Yes
Pant
Applications
Field
<5 altea)
Research
(with field
data)
Special Features
and Consents
simulation model. Convergence and rate
of convergence depend on Initial guess
Sensitivity analysis.
Large computer tine.
Under developnent. Transmlss IvLt y
Bomftlmes be adjusted for convorgi-nco.
Identification
Model
Ho.
70-15
Country
U.S.
Germany
Institution
Case
University
University
i
1
Reporter
(year)
Halves
(73)
Boehsi
-------
IDENTIFICATION MODELS
List of Symbols
K - Hydraulic conductivity
T - Transmissivity
S - Storativity
2 - Summation symbol
A( ) - Error in Quantity enclosed in the brackets
U - Volume
H - Head
S - Drawdown
L.P. - Linear Programming
Q.P. - Quadratic Programming
N.L.P. - Nonlinear Programming
140
-------
TABLE A-25. THE PRESENT STATUS OF IDENTIFICATION MODELS
Method
Direct
In-
Direct
Non-
Iterative
Iterative
Trial and
Iterative
Search
Constraints
Unconstrained
Constrained
Unconstrained
Constrained
Error
Unconstrained
Constrained
Single Phase
Homogeneous
Conservative
Lumped
70-13
Distributed
Hydraulic
70-1
7Q~2 70,7
70-3
7Q-A
fef-
70.^10.
7Q.-11
70-12
*tfM
lydro-
dynaraic
i
Saturated-
Un-
Saturated
Subsur-
face and
Surface
Non-
Conservativc
Non-
lomogeneous
Multi-
Phase
-------
NJ
TABLE A-26. DATA MANIPULATION MODELS
Purpose
Accounting of
exogenous Inflow
to a groundwater
basin
Account of deep
percolation as
Input to a ground
water flow model
Error detection
In ground water
levels .
Regionallzation of
point sample data
and assessment
of estimate
precision-
Data retrieval
and model input.
System
Groundwater basin,
surface waters,
water agencies,
water users.
Soils, crops,
irrigation units
surface water.
Time series of
observations in
wells
Point sample data
as realization of
a spatial sto-
chastic process.
Well data base.
Aquifer data.
Processes
Inflows,
outflows,
transfers.
Evapotran-
spiration
rainfall, re-
turn flow,
pumping , dee;
percolation
Data
retrieval.
Data input
from contou
maps.
Method
Water
balance
Volume
balance
Decompo-
sition of
time
series
into com-
ponents
& their
estimatlo
Optimal
interpo-
lation by
"Krlging"
Docu-
men-
tation
none
Complete
(report)
Descrip-
tion
(Hebrew)
18
Complete
Complete
Aval-
abil-
ity
no
Restric-
ted
Yes
Yes
After
publics*
tion
Past
Appli-
cations
Field
(many)
Field
Field
Field
(many)
Field
Special Features
Specialized to Kern County, California
Limited to areas with sufficient data
On water use. Prepares input for
flow models. User oriented.
Deviations from expected value as index
of acceptability. Each site treated
separately. Need for extension to
multlvarlate time series.
Unbiased estimator as a weighted ayerag
of the data. Standard deviation of the
error. Package of 90 subroutines.
Variety of output. Can be coupled to a
plotter. User oriented.
Special applications and manipulations
Preparation and check of model inputs.
Interactive graphics scope. Variety of
output. User oriented. Small core
storage. Mass storage.
Identification
todel
No.
80-1
80-2
80-3
80-4
80-5
oun-
try
.S.
rgen-
tina
Israel
ranee
U.S.
nsti-
ution
rlvate
UNDP
;ovt.
govt.
Battell
Reporter
Klelnecke
(76)
avarro
(69)
\vy /
Ben-Z vi
(76)
Delhorae
(75)
Frledrlchs
(77)
-------
APPENDIX B
LIST OF MDDELERS
This list includes the names and
addresses of all modelers who vrorked on
the models surveyed in this study. In each
case only the name of the reporter of the
model is listed on the associated Table.
143
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TAKE FROM
NUMBER APPENDIX A
ADAMS, B.R.
AGUADO
AHLSTROM, S.
ALDRICK, R.J.
ALLEY, W.M.
ASHKENAZI, S.
ASHLEY, R.P.
AVRON, M.
BACA, R.
BACHMAT, Y.
Institute of Geological Sciences
Exhibition Road
London SW7
United Kingdom
12-^20 A-2a
Stanford University
Palo Alto, California
94305
Battelle, Pacific Northwest
Laboratories
Water and Land Resources Department
P.O. Box 999
Richland, WA 99352
(509) 946-2121
Directorate of Resource Planning
Yorkshire Water Authority
21 Park Square South
Leeds LSI 2QG
United Kingdom
Stanford University
-Palo Alto, California
94305
TAHAL Consulting Engineers, Ltd.
54 IBN Gvirol Street
Tel-Aviv, Israel
Sir M. MacDonald & Partners
Demeter House
Station House
Cambridge, CBl 2RS
United Kingdom
TAHAL Consulting Engineers
54 IBN Gvirol Street
Tel-Aviv, Israel
Rockwell Hanf ord Operations
P.O. Box 250
Richland, WA 99352
Hydrological Service of Israel
P.O. Box 6381
Jerusalem, Israel
61- 2 A-19
A-23
23-11 A-ll
A-12
80- 5 A-26
70-11 A-24b
A-25
12-31 A-2a
61- 2 A-19
A-23
12-55 A-2a
12- 9 A-2a
23- 2 A-ll
A-12
50- 2 A-17
A-18
23-16 A-U
A-12
70- 6 A-24a
144
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABLE FROM
NUMBER APPENDIX A
BAKR, A.
BARADAT, Y.
BARENDS, F.
BARRIERE/ P.
BARTOLOME, J.C.
BASTIN, G.
BAZIER, G.
BEAR, J.
BECONEGRA, C.
New Mexico Institute of Mining
and Technology
Campus Station
Socorro, NM 87801
ARLAB
Eau et Environment
Sophia Antipolis - Boite Postale 15
06560 Valbonne - Alpes Maritimes
France
Laboratory of Soil Mechanics
Stieltjesweg, Delft
The Netherlands
SOGFEAH
74, avenue Marie Reynoard
38100 - Grenoble
France
Gabinete de Calculo
Ministerio de Obras Publicas
Nuevos Minister ios, Madrid
Spain
Laboratory of Automatics and
System Analysis
University of Louvain
1348 Louvain-la-Neuve
Belgium
Dept. of Agricultural Engineering
University of Louvain
1348 louvain-la-Neuve
Belgian
TECHNION
Dept. of Civil Engineering
Technion-Israel
Institute of Technology
Haifa
Israel
No Address
Contact Y.Y. Haimes
21- 5 A-9
A-12
12-19 A-2a
12-22 A-2a
12-62 A-2a
61- 4 A-19
A-23
18-8 A-7
16- 5 A-5
13-13u A-2b
12-32 A-2a
12-32 A-2a
12-14 A-2a
70- 2 A-24a
A-25
63-13 A-21b
A-23
145
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABLE FROM
NUMBER APPENDIX A
BEDINGER, M.S.
EEN-ZVI, M.
BEZES, C.
BIBBY, R.
BIESEL, F.
BLANC, G.
BLANK, D.
U.S. Geological Survey
Water Resources Division
Box 25046, Mail Stop-406
Denver Federal Center
Lakewood, CO 80225
Hydrological Service
P.O. Box 6381
Jerusalem
Israel
Laboratoire de Geologic
C.E.R.G.H. - U.S.T.L.
Place Eugene Bataillon
34060 Montpellier Cedex
France
Water Research Centre
P.O. Box 16, Henley Road
Medmenham Laboratories
Medmenham, Marlow
Buckinghamshire SL7 2HD
ttiited Kingdcm
GEOHYDRAULIQUE
10, rue Eugene Renault
94700 Maisons - Alfort
France
ARLAB
Eau et Environment
Sophia Antipolis - Boite Postale 15
06560 Valbonne - Alpes Maritimes
France
TABMi Consulting Engineers, Ltd.
54 IBN Gvirol Street
Tel-Aviv
Israel
16- 3u A-5
12-44u A-2a
80- 3 A-26
11- 2 A-l
12- 8 A-2a
13- 7
13- 8
14- 8
12-19
14-19
14-15
12-25
14- 8
14-16
14-17
12-22
61- 4
12-48
22- 2
A-2b
A-2b
A-3b
A-2a
A-3a
A-3b
A-2a
A-3a
A-3b
A-3b
A-2a
A-19
A-23
A-2a
A-lOa
A-12
146
-------
NAME
ADDRESS
MODEL ASSOCIATED
EEPOKT TABLE FROM
NUMBER APPENDIX A
BOEHM, B.
BONNIER, A.
BOSTOCK, C.A.
BREDEHOEFT, J.
BRESIER, E.
BRIECHLE, D.
BRISSAUD, F.
BRUTSAERT, W.
Institut fur Wasserwirtschaft
Hydrologie und Landw. Wasserbau
Technische Universitat Hannover
Callinstr. 15 c, 3000 Hannover
F.R. Germany
SCET - INTERNATIONAL
5-7, rue Bellini
92806 - Puteaux
France
Department of Hydrology
University of Arizona
Tucson, Arizona 85721
U.S. Geological Survey
Mail Stop 413
12201 Sunrise Valley Drive
Reston, VA 22092
(703) 860-6971
Dept. of Soil Physics
The Volcani Center A.R.O.
Bet Dagan
Israel
Institut fur Wasserwirtschaft
Hydrologie und landvrixtschaftlichen
Nasserbau
Technische Universitat Hannover
Callinstre. 15 c, 3000 Hannover 1
F.R. Germany
Service de Radi oagronomie
C.E.N. de Cadarache
13115 - St. Paul lex Durance
France
Dept. of Civil Engineering
458 Aubert Hall
University of Maine
Orono, Maine 04473
(207) 581-7693
70-15 A-24b
A-25
12- 2 A-2a
61- 3 A-19
A-23
22- 8
63- 9
61- 8
23- 7
A-lOa
A-12
A-21b
A-23
A-19
A-23
16- 7 A-5
12-26 A-2a
A-ll
A-12
12-38 A-2a
16-10 A-5
18-10 A-7
147
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABLE FROM
NUMBER APPENDIX A
BRYAN, C.A.
University of Montana
Missoula, MT 59801
BURKHOLDER, B.C. Battelle, Pacific Northwest
Laboratories
Water and Land Resources Department
P.O. Box 999
Richland, WA 99352
BURT, 0.
BURT, W.W.
CARRIERE, A.
CAZAL, A.
CEARLOCK, D.B.
CHAN, P.
CHEN, C.W.
Dept. of Economics
Montana State University
Bozeman, MT 59715
(406) 994-3701
Dept. of Civil Engineering
Colorado State University
Fort Collins, CO 80523
GERSAR
B.P. 4001
3001 - Nines
France
mstitut de Geodynamique
Universite de Bordeaux III
Avenue des Facultes
33405 - Talence
France
Battelle, Pacific Northwest
laboratories
Water and Land Resources Department
P.O. Box 999
Richland, WA 99352
Box 1751 G.P.O.
Adelaide 5001
South Australia
Tetra Tech, Inc.
Environmental Systems Engineering
3700 Mt. Diablo Boulevard
Lafayette, CA 94549
12-30u A-2a
23-12 A-ll
A-12
63- 3 A-21a
A-23
12-47 A-2a
13- 6 A-2b
30- 5 A-13
A-14
12-23 A-2a
70- 4 A-24a
A-25
12-41 A-2a
17- 3 A-6
148
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABLE FROM
NUMBER APPENDIX A
CHETBOUN, G.
CfflDLEY, T.
CHILES, J.P.
CHORLEY, D.W.
Hydrological Service 23-16 A-ll
P.O. Box 6381 A-12
Jerusalem
Israel
Dept. of Civil Engineering
University of Aston
Gosta Green
Birmingham
United Kingdom
Ecole Nationale Superieure
des Mines de Paris
Centre de Geostatistique
35, rue Saint - Honore
77305 - Fontainebleau
France
Dept. of Earth Sciences
University of Waterloo
Waterloo, Ontario
Canada
12-27 A-2a
80- 4 A-26
13-10 A-2b
CIABORN, B.J.
CLOUET D'ORVAL,
M.
COLE, C.R.
COLVILLE, J.S.
High Plains Underground Water 12-34 A-2a
Conservation District #1 70-12 A-24b
Lubbock, TX 79409 A-25
HJRGEAP 13- 3 A-2b
70, rue Mademoiselle 18- 6 A-7
75015 Paris 14-19 A-3b
France 14- 5 A-3a
14-10 A-3a
Battelle, Pacific Northwest 22- 5 A-lOa
Laboratories A-12
Water and Land Resources Department 13-19 A-2b
P.O. Box 999 12-30u A-2a
Richland, WA 99352 12-59 A-2a
CSIRO 12-35 A-2a
Division of Soils 12-36 A-2a
Private Bag No. 2
Glen Osmond, S.A. 5064
Australia
149
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABLE FROM
NUMBER APPENDIX A
COOLEY, R.
COUCHAT, P.
CtMMINGS, R.G.
DAGAN, G.
DAS, P.
DAVIDSON, J.M.
DAVIS, J.
DAX, A.
DE BACKER, L.
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver Federal Center
Lakewcod, CO 80225
Service de Radioagrononiie
C.E.N. Cadarache
13115-Saint Paul lez Durance
France
The University of Rhode Island
Warwick, Rhode Island 02886
Dept. of Engineering
University of Tel-Aviv
Israel
School of Civil Engineering
Purdue University
West Lafayette, IN 47907
Soil Science Department
University of Florida
Gainesville, FL 32611
Water Research Centre
P.O. Box 16, Henley Road
Medmenham laboratories
Medmenham Marlow
Buckinghamshire SL7 2HD
United Kingdom
Hydrological Service
P.O. Box 6381
Jerusalem, Israel
Dept. of Agricultural Engineering
University of Louvain
1348 Louvain-la-Neuve
Belgium
14- 2 A-3a
14- lu A-3a
16- 9 A-5
70-16 A-24b
A-25
23- 7
23- 8
62- 1
A-ll
A-12
A-ll
A-12
A-20
A-23
18- 1 A-7
70-14u A-24b
A-25
63-13 A-21b
A-23
23-17 A-ll
A-12
12-15 A-2a
70-6 A-24a
A-25
12^32 A-2a
150
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABIE FROM
NUMBER APPENDIX A
DEGALEJER, R.
DE LAAT, P.J.M.
DE LARMINAT, R.
DELFINER, P.
DELHCMME, J.P.
DE MARSILY, G.
DEMIER, W.V.
Bureau of Geological and
Mineral Research (BRGM)
Department of Hydrology
B.P. 6009
45018 - Orleans Cedex
France
International Institute for
Hydraulic & Environmental
Engineering
Delft
The Netherlands
SOGREAH
47, Avenue Marie Reynoard
38100 - Grenoble
France
Ecole Nationale Superieure
des Mines de Paris
35, rue Saint-Honore
77305 Fontainebleau
France
Ecole Nationale Superieure
des Mines de Paris
Centre de Geostatistique
Centre d'lnformatique Geologique
35, rue Saint-Honore
77305 - Fontainebleau
France
Ecole Nationale Superieure
des Mines de Paris
35, rue Saint-Honore
77305 Fontainebleau
France
Battelle, Pacific Northwest
Laboratories
Systems Department
Richland, WA 99352
17- 4 A-6
16- 2 A-5
13-14 A-2b
80- 4 A-26
80- 4 A-26
70- 9 A-24a
A-25
12-30u A-2a
151
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABLE FROM
NUMBER APPENDIX A
DRACUP, J.
DREIZIN, J.
DBEYFUS, A.
DUJARDIN, J.M.
ECKHARDT, J.E.
EWING, L.
FAUST, C.R.
FEDDES/ R.A.
FILLEKES, W.
Dept. of Civil Engineering
7620 B Boelter Hall
University of California
Los Angeles, CA 90024
(213) 825-1906
Metorof Water Conpany
Nine Lincoln Street
Tel-Aviv
Israel
Centre d'Informatique Geologique
Ecole des Mines de Paris
35, rue Saint-Honore
77305, Fontainebleau
France
SOGREAH
47, avenue Marie Reynoard
38100 - Grenoble
France
Dept. of Civil Engineering
Colorado State University
Fort Collins, CO 80721
General Electric - TEMPO
P.O. Drawer QQ
Santa Barbara, CA 93102
U.S. Geological Survey
Man Stop 413
12201 Sunrise Valley Drive
Reston, VA 22092
Institute of Soil and Water
Agriculture Research Organization
Bet Dagan
Israel
National Institute for Water Supply
P.O. Box 150
Leidschendam
The Netherlands
70- 5 A-24a
A-25
70-14u A-24b
A-25
63-13 A-21b
A-23
64- 2 A-22
A-23
13-14 A-2b
12-46 A-2a
70-13 A-24b
A-25
30- 9 A-13
A-14
16- 7 A-5
13- 5 A-2b
13-12 A-2b
152
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABLE FROM
NUMBER APPENDIX A
FLORES, W.
POOTE, H.P.
FREEZE, R.A.
New Mexico Institute of Mining
and Technology
Campus Station
Socorro, NM 87801
Battelle, Pacific Northwest
Laboratories
Water & Land Resources Department
P.O. Box 999
Richland, WA 99352
Dept. of Geological Sciences
University of British Columbia
2075 Westbrook Place
Vancouver, B.C. V6T 1W5
63- 2
FRIEDRICHS, D.R. Battelle, Pacific Northwest
Laboratories
Water and Land Resources Department
P.O. Box 999
Richland, WA 99352
FRIND, E.
FUJISAKI, K.
FURUNO, K.
GABLINGER, M.
Dept. of Earth Sciences
University of Waterloo
Waterloo, Ontario N2L 3G1
Canada
(519) 855-1211 x 3959
Kbkusai Aerial Surveys, Co., LTD
Asahigaoka 3, Hino
Tokyo 191
Japan
Chiba Prefectural Research Institute
for Environmental Pollution (CRIEP)
Inage-Kaigan 3-5, Chiba 281
Japan
TAHAL Consulting Engineers, Ltd.
54 IBN Gvirol Street
Tel-Aviv
Israel
23-11
A-21a
A-23
A-ll
A-12
17-lu A-6
80- 5 A-26
12-59 A-2a
70- 4 A-24a
A-25
12- 6 A-2a
13-10 A-2b
16-13u A-5
23- 3 A-ll
A-12
14-13 A-3a
40- 3
40- 4
63- 5
A-15
A-16
A-15
A-16
A-21a
A-23
153
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABLE FROM
NUMBER APPENDIX A
GAILLARD, P.
GARAY, H.L.
GARCIA, L.L.
GAUDET, J.P.
GELHAR, L.W.
GEVERS, M.
GIESEL, W.
SOGREAH
47, avenue Marie Reynoard
38100 - Grenoble
France
Dept. de Ingerieria de Sistemas
Faciltad de Ingenerha
Universidad de los Andes
Merida
Venezuela
INTECSA
Internacional de Ingenieria Y
Estudios Tecnicos, S.A.
Condesa de Venadito, 1
Madrid
Spain
Institut de Mecanique de Grenoble
B.P. 53 - Centre de Tri
38041 - Grenoble Cedex
France
New Mexico Institute of Mining
and Technology
Campus Station
Socorro, NM 87801
(505) 835-5307
Laboratory of Automatics and
Systems Analysis
University of Louvain
1348 Louvain-la-Neuve
Belgium
Bundesanstalt fur Geowissenschaften
und Rohstroffe
Hannover 51, P.O. 51 1 53
F.R. Germany
13-14 A-2b
16- 5 A-5
70-14u A-24b
A-25
63-13 A-21b
A-23
13-13u
23- 9 A-ll
A-12
40- 1
63- 2
21- 1
21- 5
A-15
A-16
A-21a
A-23
A-9
A-12
A-9
A-12
12-32 A-2a
13- 2 A-2b
154
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABIE FROM
NUMBER APPENDIX A
GOBLET, P.
GOODWILL, I.
GRANNEMANN, N.G.
GRANT, S.
GRIFFIN, J.D.
GRINGARTEN, A.C.
GROVE, D.
GUPTA, S.K.
GUVANASEN, V.
Centre d' Infontatique Geologique
Ecole des Mines de Paris
35, rue Saint-Honore
77305 Fontainebleau
France
Dept. of Civil Engineering
The University
Leeds LS2 9JT
United Kingdom
Geology Department
University of Missouri
Columbia, MO 65201
UCLA
405 Hilgard Avenue
Los Angeles, CA 90024
U.S. Geological Survey
Water Resources Division
Box 25046, Mail Stop 406
Denver Federal Center
Lakewood, CO 80225
Bureau de Recherches
Geologiques et Mineres
Service Geologique National
Dept. Geologie de I'Amenagement
B.P. 6009 - 45018 Orleans Cedex
France
U.S. Geological Survey
Box 25046, Mail Stop 413
Denver Federal Center
Lakewood, CO 80225
Water Resources Center
University of California
Room 475 APB-3
Davis, CA 95616
Post Office, James Cook University of
North Queensland
Queensland, 4811
Australia
22- 7
12-49
12-27
63- 7
30- 2
23-14
22- 4
A-lOa
A-12
A-2a
A-2a
12-40 A-2a
A-21a
A-23
12-44 A-2a
A-13
A-14
A-ll
A-12
A-lOa
A-12
12-43 A-2a
155
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABLE FROM
NUMBER APPENDIX A
HA3MES, Y.
HATKJEMA, H.M.
HALLIFAX, P.
HflMDMJ, A.
HNKN, G.
HANKS, R.J.
KARA, Y.
HARADA, K.
HARE, R.
Water Resources Systems
Engineering Program
Room 400, Wickenden Building
Cleveland, Ohio 44106
(216) 368-4076
University of Technology
Delft
Die Netherlands
Sir M. MacDonald & Partners
Demeter House, Station Road
Cambridge, CBl 2RS
United Kingdom
The University of Illinois
Charcpaign, Illinois 61820
Institut de Mecanique de Grenoble
B.P. 53 - Centre de Tri
38041 - Grenoble Gedex
France
Dept. of Soils and Meteorology
Utah State University
Logan, Utah 84321
Chiba Prefecture! Research Institute
for Environmental Pollution (CRIEP)
Inage-Kaigan 3-5, Chira 281
Japan
Kokusai Aerial Surveys, Co., LID.
Asahigaoka 3, Hino
Tokyo 191
Japan
General Electric - TEMPO
P.O. Drawer QQ
Santa Barbara, CA 93102
63- 6
30- 4
22- 3
40- 4
40- 2
40- 4
30- 3
70- 5 A-24a
A-25
70-14u A-24b
A-25
63-13 A-21b
A-23
61-10 A-19
A-23
63-12 A-21b
A-23
18- 4 A-7
12- 9 A-2a
A-21a
A-23
A-13
A-14
A-lOa
A-12
A-15
A-16
A-15
A-16
A-15
A-16
A-13
A-14
156
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABIE FROM
NUMBER APPENDIX A
HASSAN, A.
HAUSZ, W.
HAVERKAMP, R.
HEFEZ, E.
HELM, D.C.
HELWEG, O.J.
HENRY, J.L.
HERVE, J.
HIGUCHI, S.
California Dept. of Water Resources 21- 2 A-9
849 South Broadway A-12
Los Angeles, CA 90014
(213) 620-4107
General Electric - TEMPO
P.O. Drawer QQ
Santa Barbara, CA 93102
Institut de Mecanique de Grenoble
B.P. 53 - Centre de Tri
38041 - Grenoble Cedex
France
Dept. of Ccnputer Sciences
Haifa University
Haifa
Israel
U.S. Geological Survey
Subdistrict Office, WRD ,
Room W-2235, Federal Building
2800 Cottage Way
Sacramento, CA 95825
University of California 17- 3
Berkeley, CA 94720 64- 3
GEOHYDRAULIQUE 13- 7
10, rue Eugene Renault 13- 8
94700 Maisons - Alfort 14-18
France
30- 3 A-13
A-14
30- 4 A-13
A-14
23- 9 A-ll
A-12
12-14 A-2a
70- 2 A-24a
A-25
40- 5 A-15
A-16
A-6
A-22
A-23
A-2b
A-2b
A-3b
12-62 A-2a
ARLAB
Eau et Environment
Sophia Antipolis - Boite Postale 15
06560 Valbonne - Alpes Maritimes
France
Chiba Prefectural Research Institute 40- 4 A-15
for Environmental Pollution (CRIEP) A-16
Inage-Kaigan 3-5, Chiba 281
Japan
157
-------
NAME
ADDRESS
MDDEL ASSOCIATED
REPORT TABLE FROM
NUMBER APPENDIX A
HOSTETLER, D.D.
HSIEH
HUBER, R.
HUBERT, P.
HUNT, B.
HURR, R.T.
HUYAKDRN
IBM ISRAEL
SCIENTIFIC
CENTER
JANSEN, G.
BatteUe, Pacific Northwest
laboratories
Water and Land Resources' Department
P.O. Box 999
Richland, WA 99352
Dept. of Civil Engineering
Princeton University
Princeton, NJ 05840
SOGREAH
47, avenue Marie Reynoard
38100 - Grenoble
France
Centre de'Informatique Geologique
Ecole des Mines des Paris
35, rue Saint Honore
77305 - Fontainebleau
France
University of Canterbury
Christchurch
New Zealand
U.S. Geological Survey
Water Resources Division
Box 25046, Mail Stop 415
Denver Federal Center
Lakewood, CO 80225
Dept. of Civil Engineering
Princeton University
Princeton, NJ 08540
Technion City
Haifa
Israel
Battelle, Pacific Northwest
Laboratories
Water and Land Resources Department
P.O. Box 999
Richland, WA 99352
80- 5 A-26
22-16 A-lOb
A-12
13-14 A-2b
64- 1 A-22
A-23
64- 2 A-22
A-23
12-24 A-2a
12-42 A-2a
18- 9 A-7
22- 9 A-lOa
A-12
23-12 A-ll
A-12
158
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABLE FROM
NUMBER APPENDIX A
JARDIN, P.
JIERASAK, T.
JOSEPH, C.
JOUHET, P.
KAHAN, J.
KALLY, E.
KAMATA, A.
KAPULER, I.
SOGREAH
47, avenue Marie Reynoard
38100 - Grenoble
France
Post Office, James Cook University
of North Queensland
Queensland, 4811
Australia
Laboratorie de Geologie
C.E.R.G.H. — U.S.T.L.
Place Eugene Bataillon
34060 Montpellier Cedex
France
SOGREAH
47, avenue Marie Reynoard
38100 - Grenoble
France
TAHAL Consulting Engineers, LTD.
54 IBN Gvirol Street
Tel-Aviv
Israel
TAHAL Consulting Engineers, LTD.
54 IBN Gvirol Street
Tel-Aviv
Israel
Kbkusai Aerial Surveys, Co., LTD.
Asahigaoka 3, Hino
Tokyo 191
TAHAL Consulting Engineers, LTD.
54 IBN Gvirol Street
Tel-Aviv
Israel
13-14 A-2b
16- 5 A-5
12-43 A-2a
11- 2 A-l
13-14
16- 5
63-lu
63-lu
12- 4
40- 2
40- 4
40- 3
11- 1
22-13
18- 3
A-2b
A-5
A-21a
A-23
A-21a
A-23
A-2
A-15
A-16
A-15
A-16
A-15
A-16
A-l
A-lOa
A-12
A-7
159
-------
NAME
ADDRESS
MOCEL ASSOCIATED
REPCRT TABLE FROM
NUMBER APPENDIX A
KEATING, T.
KHANJI, J.
KEPP, K.L.
KTDCHING. R.
KLEDJECKE, D.C.
KLENKE, I.M.
KNOWLES, T.R.
Directorate of Resource Planning
Southern Water Authority
Eastleigh House
Two, Market Street
Eastleigh, Hampshire
United Kingdcm
Institut de Mecanigue de Grenoble
B.P. 53 - Center de Tri
38041 - Grenoble - Cedex
France
A.E.R.E.
19 West Drive
Harwell, Didcot
Oxfordshire OX 110 CP
United Kingdom
Institute of Geological Sciences
Exhibition Road
London SW7
United Kingdcm
2784 Glen Dessary Lane
Santa Barbara, CA 93105
12-33 A-2a
16-11 A-5
12-30u A-2a
70- 4 A-24a,
A-25
12-50
12-20
12- 1
13-16
14-11
Institut fur Wasserwirtschaft
Hydrologie und landwirtschaftlichen
wesserbau, Technische Universitat
Hannover, Callinstr. 15 c,
Hannover
F.R. Germany
Texas Water Development Board
Systems Engineering Divison
P.O. Box 13087
Austin, TX 78711
(512) 475-3606
A-2a
A-2a
A-2a
A-2b
A-3a
21-2
80- 1
13-20
13- 1
70-13
A-9
A-12
A-26
A-2b
A-2b
A-24b
A-25
12-21 A-2a
12-17 A-2a
12-34 A-2a
70-12 A-24b
A-25
160
-------
NAME
KQBUS, H.
KONIKQW, L.
KORGANOFF, A.
KUIPER, L.K.
KUMAI, H.
KUYPERS, J.P.
LABADIE, J.W.
LAMBERT, F.
LANDEL, P.
ADDRESS
Universitat Karlsruhe
Kaiserstrasse 12
Postfach 6380
75 - Karlsruhe 1
Germany
U.S. Geological Survey
Water Resources Division
Box 25046, Mail Stop 415
Denver Federal Center
lakewood, 00 80225
SCET-INTERNATICNAL
5-7, rue Bellini
92806, Puteaux
France
Iowa Geological Survey
Iowa City, IO 52242
Sinshu University
Asahi 3, Matsumoto
Nagano 390
Japan
Bydrological Service
University of Louvain
1348 Louvain-la-Neuve
Belgium
Colorado State University
Fort Collins, Colorado 80521
Service de Radioagronomie
C.E.N. de Cadarache
13115 - St. Paul lez Durance
France
Bureau de Recherches Geologiques
et Mineres, Service Geologique
National - Dept. Geologie de
I'Atnenagement
B.P. 6009 - 45018, Orleans Cedex
France
MODEL ASSOCIATED
REPORT TABLE FROM
NUMBER APPENDIX A
12-45 A-2a
22- 8 A-lOa
A-12
12- 2 A-2a
14-21 A-3b
11- 1 A-l
12-32 A-2a
64- 3 A-22
A-23
70- 8 A-24a
A-25
23- 7 A-ll
A-12
13-15 A-2b
30- 2 A-13
A-14
161
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABLE FROM
NUMBER APPENDIX A
LANTZ, R.
Interconp Resource Development Corp.
1201 Dairy-Ashford
Suite 200
Houston, TX 77079
(713) 497-8405
23-15 A-ll
A-12
18-11 A-7
50- 5 A-17
A-18
23- 4 A-ll
A-12
LARSON, S.P.
LE CARDINAL, G.
LE CLERCQ, P.
LEDOUX, E.
LESSI, J.
LEVASSOR, A.
LEVIN, O.
(deceased)
U.S. Geological Survey
Mail Stop 413
12201 Sunrise Valley Drive
Reston, VA 22092
Service de Radioagronanie
C.E.N. Cadarache
13115 - Saint Paul lez Durance
France
Hydrological Service
University of louvain
1348 Louvain-la-Neuve
Belgium
Centre d'Informatique Geologique
Ecole des Mines de Paris
35, rue St. Honore
77305 Fontainebleau
France
Centre d'Infontatigue Geologique
Ecole des Mines de Paris
35, rue St. Honore
77305 Fontainebleau
France
Centre dlmfornatique Geologique
Ecole des Mines de Paris
35, rue St. Honore
77305 Fontainebleau
France
Technion City
Haifa
Israel
14-20u A-3b
14- 3 A-3a
23- 8 A-ll
A-12
12-32 A-2a
23- 1 A-ll
A-12
22- 7 A-lOa
A-12
61-6u A-19
A-23
12-55 A-2a
162
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABLE FROM
NUMBER APPENDIX A
LIDDAMENT, M.W.
LIN, C.L.
W&ter Research Centre
P.O. Box 16, Henley Road
Medmenham Laboratories
Medmenhara Marlow
Buckinghamshire SL7 2HD
United Kingdom
Water Planning & Management
Nova Scotia Dept. of Environment
P.O. Box 2107
Halifax, Nova Scotia
13-14 A-2b
12-37 A-2a
12-39 A-2a
LIPPMAN, M.J.
LONGENBAUGH,
R.A.
LONNQUIST, C.G.
Dept. of Geological Engineering
University of California
Berkeley, CA 94720
Dept. of Civil Engineering
Colorado State University
Fort Collins, CO 80523
(303) 491-5861
Illinois State Water Survey
Urbana, Illinois 61801
LUCKEY, R.
LUTHIN, J.
U.S. Geological Survey
University of Kansas, Campus West
1950 Avenue A
Lawrence, Kansas 66044
Land, Air, and Water Resources
242 Veihtneyer Hall
University of California
Davis, CA 95616
(916) 752-0694
MAC MHIAN, J.R. New Mexico Institute of Mining
and Technology
Campus Station
Socorro, NM 87801
50- 4 A-17
12-29 A-2a
12-12
12- 3
40- 1
A-2a
A-2a
13-9u A-2b
22-17 A-lOb
,A-12
63- 8 A-23JD
A-23
22- 4 A-lOa
A-12
A-15
A-16
163
-------
NAME
ADDRESS
MCCEL ASSOCIATED
FEPORT TABLE FROM
NUMBER APPENDIX A
HADDOCK, in, T. U.S. Geological Survey
Mail Stop 413
12201 Sunrise Valley Drive
Reston, VA 22092
(703) 860-6904
MARTIN, H.
MASUHARA, N.
MCFARLAND, J.W.
MERLHQRN, H.
MERCADO, M.
J.W.
MEREDITH, D.D.
Laboratory of Geochemistry
University of Louvain
1348 louvain-la-Neuye
Belgium
KdJcusai Aerial Surveys Oo., Ltd.
Asahigaoka 3, Hino
Tokyo 191
Japan
The University of Rhode Island
Warwick, Rhode Island 02886
Institut fur Rydromechanik
Universitat Karlsruhe
D 75 Karlsruhe 1
F.R. Germany
TAHAL Consulting Engineers, LTD.
54 IBN Gvirol Street
Tel-Aviv
Israel
U.S. Geological Survey
Mail Stop 413
12201 Sunrise Valley Drive
Reston, VA 22092
Dept. of Civil Engineering
SUNY, Buffalo
New York 14214
12-53
70- 7
61- 9
61- 7
61-10
63-10
A-2a
A-24a
A-25
A-19
A-23
A-19
A-23
A-19
A-23
A-21b
A-23
12-32 A-2a
40- 2 A-15
A-16
62- 1 A-20
A-23
12-45 A-2a
21- 4 A-9
A-12
21- 3 A-9
A-12
30- 9 A-13
A-14
63- 6 A-21a
A-23
164
-------
NAME
ADDRESS
MCCEL ASSOCIATED
REPORT TABUS FRCM
NUMBER APPENDIX A
MEYER, C.
MEYER, H.
MIYAMOTO, N.
MOBUSHERI, F.
MOENCH, A.F.
MQLZ, F.J.
MOREL, E.H.
MOREL-SEYTOUX,
H.J.
MOOTONNET, P.
General Electric - TEMPO
P.O. Drawer QQ
Santa Barbara, CA 93102
Institut fur Wasserwirtschaf t
Hydrologie und landwirtschaftlichen
Wasserbau
Technische Universitat Hannover
Callinstr. 15 c, 3000 Hannover 1
F.R. Germany
Nippon Koei Co., Ltd.
Uhschisaiwai-cho 2-1-11
Chiyoda, Tokyo 100
Japan
UCLA
405 Hilgard Avenue
Los Angeles, California 90024
U.S. Geological Survey
Subdistrict Office
855 Oak Grove Avenue
Menlo Park, CA 94025
Civil Engineering Department
Auburn University
Auburn, AL 36830
Resources Division
Central Water Planning Unit
Reading Bridge House, RG1 8PS
United Kingdom
Dept. of Civil Engineering
Colorado State University
Fort Collins, CO 80523
(303) 491-1101
Service de Radioagronomie
C.E.N. Cadarache
13115 - Saint Paul lez Durance
France
70-13 A-24b
A-25
12-26 A-2a
40- 2 A-15
A-16
63- 7 A-21a
A-23
30- 8 A-13
A-14
16- 4 A-5
12-41 A-2a
12-54 A-2a
23- 8 A-ll
A-12
165
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABLE FRCM
NUMBER APPENDIX A
MURAKAMI, M.
Nippon Koei Oo., IflD.
Uchisaiwai-cho 2-1-11
Chiyoda, Tokyo 100
Japan
40- 2
McLIN, S. New Mexico Institute of Mining
and Technology
Campus Station
Sooorro, N4 87801
McCRACKEN & VOSS Dept. of Civil Engineering
Princeton University
Princeton, NJ 08540
McWHORTER, D.B. Dept. of Agricultural Engineering
Colorado State University
Fort Collins, CO 80523
NAFF, R.L.
New Mexico Institute of Mining
and Technology
Canpus Station
Sooorro, NM 87801
NARASIMHAN, T.N. Dept. of Geological Engineering
University of California
Berkeley, CA 94720
21- 5
NAVARRO, A.
Resources and Transportation Division
United Nations Station
New York, NY 10Q17
NELSON, R.W.
NEUMAN, S.P.
BCS Richland, Inc.
Federal Building, P.O. Box 300
Richland, WA 99352
Dept. of Hydrology & Water Resources
University of Arizona
Tucson, AZ 85717
(602) 884-4434
A-15
A-16
A-9
A-12
50- 1 A-17
12-47
22- 1
40- 1
16-12
40- 6
16- 6
50- 4
70- 1
13-18
12-64
12-51
80- 2
12-60
14- 6
16- 6
16- 7
14- 7
A-2a
A-lOa
A-12
A-15
A-16
A-5
A-15
A-16
A-5
A-17
A-24a
A-25
A-2b
A-2a
A-2a
A-26
A-2a
A-3a
A-5
A-5
A-3a
166
-------
NAME
ADDRESS
MCDEL ASSOCIATED
REPORT TABLE FROM
NUMBER APPENDIX A
NEWMAN, B.A.
NIREI, H.
NOFMAND, D.
OAKES, D.
OKA, H.
OLSTHOORN, T.
O'NEILL
PAGE, H.G.
PERRINE, R.L.
Dept. of Civil and Environmental 61- 5 A-19
Engineering A-23
Cornell University
Ithaca, New York 14850
Chiba Prefectural Research Institute 40-4 A-15
for Environmental Pollution (CRIEP) A-16
Inage-Kaigan 3-5, Chiba 281
Japan
16- 5 A-5
SOGREAH
47, avenue Marie Reynoard
38100 Grenoble
France
Water Research Center 17- 2 A-6
P.O. Box 16, Henley Road 22-14 A-lOa
Medmenham Laboratories A-12
Medmenham Marlow
Buckinghamshire SL7 2HD
United Kingdom
Kokusai Aerial Surveys Co. , Ltd. 40- 3 A-15
Asahigaoka 3, Hino A-16
Tokyo, 191
Japan
12-28 A-2a
KIWA N.V.
Sir Winston Churchill-laan 273
Rijswijk
The Netherlands
Dept. of Civil Engineering 30- 6 A-13
Princeton University A-14
Princeton, NJ 08540
18- 5 A-7
U.S. Geological Survey
Box 25046, Mail Stop 415
Denver Federal Center
LakewDod, CO 80202
University of California 70-5 A-24a
Los Angeles, CA 90024 A-25
167
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABLE FRCM
NUMBER APPENDIX A
PERSONS, E.
PETERS, J.
PICKENS, J.F.
PHKINGTON, G.
FINDER, G.F.
POITKENAL, D.
POIATSCHEK, M.
PONT1N, J.M.
Dept. of Agricultural Engineering
University of Louvain
1348 Louvain-la-Neuve
Belgian
Hydrologic Engineering Center
Corps of Engineers
609 Second Street
Davis, CA 95616
Faculty of Science
Dept. of Earth Science
University of Waterloo
Waterloo, Ontario N2L 3G1 Canada
(519) 885-1211
Engineering & Water Supply Dept.
Box 1751 G.P.O.
Adelaide 5001
Australia
Dept. of Civil Engineering
Princeton University
Princeton, NJ 08540
(609) 452-4602
12-32 A-2a
14-lu A-3a
23-5u A-ll
A-12
16- 8 A-5
12-41 A-2a
12- 6
22- 6
22- 5
50- 1
18- 9
18- 5
22-16
A-2a
A-lOa
A-12
A-lOa
A-12
A-17
A-7
A-7
A-lOb
A-12
ARLAB
Eau et Environment
Sophia Antipolis-Boite Postale 15
06560 Valbonne - Alpes Maritines
France
Technion City
Haifa
Israel
Hydraulics Research Station
Waningford
Berkshire
United Kingdom
70- 9
A-24a
A-25
12-55 A-2a
17- 2 A-6
168
-------
NAME
ADDRESS
MDEEL ASSOCIATED
REPORT TABLE FROM
APPENDIX A
PRAKASH, A.
PRICKETT, T.A.
, P.
REED, J.E.
REIN, M.
REISENAUER, A.
REMSON, I.
REMJIE, A.
ROBERTSON, J.B.
ROEFFS, T.G.
Chicago, Illinois
Illinois State Water Survey
Box 232
Urbana, Illinois 61801
(217) 333-1724
GEOHYDRAULIQUE
10, rue Eugene Renault
94700 Maisons-Alfort
France
U.S. Geological Survey
2301 Federal Office Building
Little Rock, AK 72201
Engineering & Water Supply Dept.
Box 1751 G.P.O.
Adelaide 5001
Australia
Battelle, Pacific Northwest
Laboratories
Water & Land Resources Division
P.O. Box 999
Richland, WA 99352
Stanford University
Palo Alto, California 94304
Post Office, James Cook University
of North Queensland
Queensland, 4811
Australia
U.S. Geological Survey
Subdistrict Office
855 Oak Grove Avenue
tfenlo Park, CA 94025
University of Arizona
Tucson, Arizona 85721
12-47 A-2a
12-12 A-2a
12- 3 A-2a
13- 9u A-2b
22-17 A-lOb
A-12
13- 7 A-2b
13- 8 A-2b
14-18 A-3b
16- 3u A-5
12-44u A-2a
12-41 A-2a
13-19 A-2b
12-30u A-2a
61- 2
A-19
A-23
12-43 A-2a
23-13 A-ll
A-12
23-10 A-ll
A-12
61- 3
A-19
A-23
169
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABLE FROM
NUMBER APPENDIX A
RQUSSELOT, D.
RUSHTON, K.R.
SAFAI
SAGAR, B.
SALEEM, S.
SARKAR, A.
SAUTY, J.P.
SCHALIER, J.
Bureau de Recherches
Geologiques et Minieres
Service Geologique National
Dept. Geologie de I'Amenagement
BP 6009 45018 Orleans Cedex
Francs
Dept. of Civil Engineering
University of Birmingham
P.O. Box 363
Birmingham B15 2TT
United Kingdom
Dept. of Civil Engineering
Princeton University
Princeton, NJ 08540
Hydrology Research Division
Inland Water Directory
Environment Canada
Ottawa, Ontario K1A OE7
Canada
Dept. of Geological Sciences
University of Illinois
Chicago, Illinois 60680
(312) 996-3154
(No address.
Contact: Y.Y. Haimes)
Bureau de Recherchas
Geologiques et Minieres
Service Geologique National
Dept. Geologie de I'Amenagement
BP 6009 45018 Orleans Cedex
France
Post Office, James Cook University
of North Queensland
Queensland, 4811
Australia
13-15 A-2b
12-18
12-10
14-12
40- 8
70- 3
13-11
63- 4
63-13
A-2a
A-2a
A-3a
A-15
A-16
A-24a
A-25
A-2b
A-21a
A-23
A-21b
A-23
13-15 A-2b
30- 2 A-13
A-14
12-43 A-2a
170
-------
Nfflffi
ADDRESS
MCDEL ASSOCIATED
REPORT TABLE FRCM
NUMBER APPENDIX A
SCFWIDT, G.
SCHWARTZ, F.W.
SCHWARZ, J.
SEGOL, G.
SEIDEL, G.
SELJM, H.M.
SERNE, R.J.
Bundesanstalt fur Geowissenscbaften
und Rohstoff e
(Federal Institute for Geosciences
and Natural Resources)
3000 Hannover 51
P.O. Box 51 1 53
Hannover
F.R. Germany
University of Alberta
Edmonton, Canada
TAHAL Consulting Engineers, LTD.
54 IBM Gvirol Street
Tel-Aviv
Israel
13- 2 A-2b
Bechtel
250 Bloor St., E.
Toronto, Ontario M4W 3K5
Canada
(416) 928-1600
Geology & Geophysics
Cns. Constitution
Av. Anzac Pde.
Canberra A.C.T. 2601
Australia
Soil Science Department
University of Florida
Gainesville, FL 32611
Battelle, Pacific Northwest
Laboratories
Water & Land Resources Division
Richland, WA 99352
23- 6
22- 2
61- 1
18- 2
21- 3
12-55
63-lu
63-11
23- 3
22-15
23-17
23-11
A-ll
A-12
A-lOa
A-12
A-19
A-23
A-7
A-9
A-12
A-2a
A-21a
A-23
A-21b
A-23
A-ll
A-12
A-lOb
A-12
13-17 A-2b
A-ll
A-12
A-ll
A-12
171
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABLE FROM
NUMBER APPENDIX A
SERVICE CE
MATHEMATIQUES
SHAH, C.R.
SHALEV, Z.
SHAMIR, U.
SHAPIRO, A.
SHARP, J.
SHCBASAKI, T.
SIMPSON, E .
laboratoire Central DesPonts &
Chaussees
58 Boulevard Lefebvre
75732 Paris Cedex 15
France
Central Designs Organisation
Secretariat Block No. 10
Gandhinagar 382010
India
TAHAL
54 IBN Gvirol Street
Tel-Aviv
Israel
Israel Institute of Technology
Haifa
Israel
Dept. of Civil Engineering
Princeton University
Princeton, NJ 08540
Geology Department
University of Missouri
Columbia, MO 65201
(314) 882-2121
Research Group for Water Balance
182 Fujigane
Tsurugashima, Saitama 350-02
Japan
50- 6u A-17
12-13 A-2a
63- 5
12-14
18- 1
70- 2
22-11
14- 4
12-40
50- 3
Department of Hydrology
University of Arizona
Tucson, AZ 85721
(602) 631-7137
12-52
61- 3
A-21a
A-23
A-2a
A-7
A-24a
A-25
A-lOa
A-12
A-3a
A-2a
A-17
12- 4
40- 2
40- 4
40- 3
11- 1
A-2
A-15
A-16
A-15
A-16
A-15
A-16
A-l
A-2a
A-19
A-23
172
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABLE FORM
NUMBER APPENDIX A
SOREY, M.L.
STARK, K.P.
STONER, R.F.
SUMMERS, K.
SUNADA, D.
SYLVESTRE, M.
TANJI, K.K.
TAYLOR, O.J.
U.S. Geological Survey
Subdistrict Office
855 Oak Grove Avenue
Menlo Park, CA 94025
Post Office, Janes Cook University
of North Queensland
Queensland, 4811, Australia
Sir M. MacDonaM & Partners
Daneter House
Station Road
Cambridge CBl 2RS
United Kingdom
Tetra Tech, Inc.
Environmental Systems
Engineering
3700 Mt. Diablo Boulevard
Lafayette, CA 94549
Dept. of Civil Engineering
Colorado State University
Fort Collins, CO 80523
(303) 491-6095 Main Campus
(303) 491-8666 Foothills Campus
Gouvernement du Quebec
Ministere des Richesses Naturelles
Hotel du Gouvernement
1640 Boulevard de I1 Entente
Quebec, Quebec G1S 4N6
Land, Air, and Water Resources
242 Veihmeyer Hall
University of California
Davis, CA 95616
U.S. Dept. of the Interior
Water Resources Division
1400 Independence Road, Stop 200
Rolla, MO 65401
30- 7 A-13
A-14
50- 4 A-17
12-43 A-2a
12- 9 A-2a
17- 3 A-6
12-47 A-2a
12-29 A-2a
12-46 A-2a
22- 4
63- 8
A-lOa
A-12
22- 1
14-13 A-3a
A-lOa
A-12
A-21b
A-23
173
-------
NAME
ADDRESS
MOCEL ASSOCIATED
REPORT TABLE FROM
NUMBER :.APPENDIX A
TERRY, J.E. U.S. Geological Survey
2301 Federal Office Building
Little Rock, AR 72201
THIEM, H. Institut fur WasserwLrtschaft
Hydrologie und landwirtschaftlichen
Wasserbau
Technische Universitat Hannover
Callinstr. 15 c, 3000 Hannover
F.R. Germany
THRAILKILL, J. Department of Geology
Water Resources Institute
University of Kentucky
Lexington, KY 40506
TILMAN, E.
TODD, O.K.
TOMEJNSON, L.M.
TRESCOTT, P.
1RIPPLER, K.
Dept. of Agricultural Engineering
University of Louvain
1348 iDuvain-la-Neuve
Belgium
Dept. of Civil Engineering
University of California
Berkeley, CA 94720
(415) 642-5525
Dept. of Civil Engineering
University of Birmingham
P.O. Box 363
Birmingham B15 2TT
United Kingdom
U.S. Geological Survey
Mail Stop 413
12201 Sunrise Valley Drive
Reston, VA 22092
Bundesanstalt fur Geowissenschaften
und Rohstoffe
(Federal Institute for Geosciences
and Natural Resources)
P.O. Box 51 1 53
3000 Hannover 51,
F.R. Germany
16- 3u A-5
22-lOu A-lOa
A-12
12-63 A-2a
12-32 A-2a
70-13 A-24b
A-25
30- 3 A-13
A-14
12-18 A-2a
12-10 A-2a
14-20u A-3b
14- 3 A-3a
13- 2 A-2b
174
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABLE FROM
NUMBER APPENDIX A
UPDEGRAEF, C.D.
VANCON, J.P.
VAN DEN AKKER,
C.
VANDENBERG, A.
New Mexico Institute of Mining 21- 5 A-9
and Technology A-12
Campus Station
Socorro, NM 87801
SGAL, 204, route de Schirmeck
67200 Strasbourg
France
Municipal Waterworks of Amsterdam
Oondensatorweg 54
Amsterdam-Sloterdijk
The Netherlands
12- 7 A-2a
12-57 A-2a
12-58 A-2a
16- 2 A-5
12-56 A-2a
Hydrology Research Division 12- 5 A-2a
Water Resources Branch 12-61 A-2a
Environment Canada
Place Vincent Massey
Ottawa, Ontario K1A OE7
VANDENBEUSCH, M. Bureau de Recherches Geologigues
et Mineres, Service Geologique
National - Dept. Geologie de
I'Amenagernent
B.P. 6009 - 45018, Orleans Cedex
France
VAN DER VEER, P. Rijkswaterstaat
Data Processing Division
Nijverheidsstraat 1
Rijswijk
The Netherlands
13-15 A-2b
VAN DER WEERT,
R.
VAN DOORNE, W.
National Institute for Water Supply
P.O. Box 150
Leidschendam
The Netherlands
Institute for Land and Water
Management Research (ICW)
Staringgebouw, Wageningen
The Netherlands
18- 7u A-7
15- 1
16- 1
A-4
A-5
15- 3 A-4
175
-------
NAME
ADDRESS
MDEEL ASSOCIATED
REPORT TABLE FROM
NUMBER APPENDIX A
VAN GENUCHTEN
VAUCUN, M.
VERGE, M.J.
VERRULJT, A.
VOLKER, R.E.
WALLICK, E.I.
WILLIS, R.
WILSDON, J.
Dept. of Civil Engineering
Princeton University
Princeton, NJ 08540
mstitut de Mecanique de Grenoble
B.P. 53 - Centre de Tri
38041 Grenoble, Cedex
France
Dept. of Earth Sciences
University of Waterloo
Waterloo, Ontario
Canada
Dept. of Hydraulic Engineering
Delft University of Technology
Delft
The Netherlands
(015) 13 32 22
Engineering Research Center
Foothills Carpus
Colorado State University
Fort Collins, CO 80521
Groundwater Division
Alberta Research Council
11315 - 87 Avenue
Edmonton, Alberta T6J 2W3
(403) 433-6421
Cornell University
Ithaca, New York 14850
State Rivers and Water Supply
Carmission, Victoria
590 Orrong Road
Azrodale, 3143
Victoria
22-12 A-lOa
A-12
16-11 A-5
30- 4 A-13
A-14
16-13u A-5
12-11 A-2a
40- 7 A-15
A-16
12-43 A-2a
70-10 A-24b
A-25
61- 5
62- 2
62- 3
A-19
A-23
A-20
A-23
A-20
A-23
14-14 A-3b
176
-------
NAME
ADDRESS
MODEL ASSOCIATED
REPORT TABLE FROM
NUMBER APPENDIX A
WILSON, J.
WIND, G.P.
WISHER, D.A.
WTTHERSPOCN, P.
WOLZACK, J.
YOUNG, R.A.
YU, W.
Parsons Laboratory for Water 21- 2 A-9
Resources and Hydrodynamics A-12
Dept. of Civil Engineering
Building 48-209
Massachusetts Institute of Technology
Cambridge, Massachusetts 02139
15- 3 A-4
Institute for Land and Water
Research (ICW)
Staringgebouw
Wageningen
The Netherlands
University of California 70-5 A-24a
Los Angeles, CA 90024 A-25
Dept. of Civil Engineering 14- 6 A-3a
University of California 14- 7 A-3a
Berkeley, CA 94720
(415) 642-5525
Div. Hydraulique Souterraine-Drainage 12-16 A-2a
DTGREF, Pard de Tourvoie 15- 2 A-4
92160 Antony
France
Resources for the Future 63- 9 A-21b
1755 Massachusetts Ave., N.W. A-23
Washington, DC 20036 61- 8 A-19
A-23
Dept. of Statistics & Operations 63-12 A-21b
Research A-23
Grad. School of Business
University of Texas
Austin, Texas
177
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO.
EPA-600/8-78-012
3. RECIPIENT'S ACCESSIOWNO.
4. TITLE AND SUBTITLE
UTILIZATION OF NUMERICAL GROUNDWATER MODELS
FOR WATER RESOURCE MANAGEMENT
5. REPORT DATE
June 1978
issuing date
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
8. PERFORMING ORGANIZATION REPORT NO,
Yehuda Bachmat, Barbara Andrews, David Holtz,
and Scott Sebastian
9. PERFORMING ORGANIZATION NAME AND ADDRESS
10. PROGRAM ELEMENT NO.
Scientific Committee on Problems of the
Environment (SCOPE)
Holcomb Research Institute, Butler University
Indianapolis, Indiana 46208
1NE625B
11. CONTRACT/GRANT NO.
Grant No. R-803713
12. SPONSORING AGENCY NAME AND ADDRESS
Robert S. Kerr Environmental Research Laboratory
Office of Research § Development
U.S. Environmental Protection Agency
Post Office Box 1198, Ada, OK 74820
13. TYPE OF REPORT AND PERIOD COVERED
Final C6/75 - 9/77*)
14. SPONSORING AGENCY CODE
EPA/600/15
15. SUPPLEMENTARY NOTES
16. ABSTRACT
The study assessed the present status of international numerical models as
a tool for ground-water related water resource management. Among the problem
areas considered are: the accessibility of models to users; communications
between managers and technical personnel; inadequacies of data; and inadequacies
in modeling.
The report, which is directed toward the nontechnical reader, describes 250
models. These are categorized as prediction, management, identification, and
data management models.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS
c. COSATI Field/Group
Ground Water, Hydrogeology, Water
Resources, Models
International
48G
18. DISTRIBUTION STATEMENT
Release to Public.
19. SECURITY CLASS (ThisReport)
Unclassified
21. NO. OF PAGES
20. SECURITY CLASS (TMspage)
Unclassified
22. PRICE
186
EPA Form 2220-1 (9-73)
178
U. S. 60VERMMMT PKIMTIMG OFFICE: 1978-757-:WO/1328 Region No, 5-H
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