|
Items in cart [1] |
Questions? Call 888-624-8373 |
PAPERBACK PDF BOOK Free Resources |
||||||||||||||||
|
||||||||||||||||
|
|
|||||||||||||||
| ||||||||||||||||||||||||||||||
|
||||||||||||||||||||||||||||||
| Copyright © 2009. National Academy of Sciences. All rights reserved. Terms of Use and Privacy Statement |
Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter.
Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.
OCR for page 249
7
Research Needs
INTRODUCTION
The committee has examined ground water modeling and the
use of these models in regulation and litigation. Specifically, the
committee was asked to answer two difficult questions: Alto what
extent can the current generation of ground water models accurately
predict complex hydrologic and chemical phenomena?" and "Given
the accuracy of these models, is it reasonable to assign liability for
specific ground water contamination incidents to individual parties
or make regulatory decisions based on long-term predictions?" This
chapter summarizes the committee's recommendations for the di-
rection and content of research programs necessary to improve the
current state of affairs.
Two comments are in order before the recommendations are pre-
sented. First, the focus of this study has been the status of ground
water models; and therefore associated areas of expertise (e.g., cli-
matic scenarios and exposure assessment models), while mentioned,
are not given the same consideration as ground water models. Hence,
the recommended research, while acknowledging related fields of
study, is biased toward ground water models and may not reflect
a complete and balanced research program. Second, the questions
presented above emphasize mode] accuracy; however, the committee
249
OCR for page 250
250
GROUND WATER MODELS
notes that the accuracy of models should not be equated with the
art of accurately applying models. Indeed, simulating the subsurface
environment is a mixture of art and science, and an assessment of
mode} accuracy is only one element in evaluating the confidence one
should have in simulation results.
Identifying key or cornerstone issues relevant to a host of policy
goals is essential so that limited resources can be devoted to the
development of technology necessary to achieve national goals on the
environment and economy. Certainly, as a nation we should maintain
a leadership role in hydrogeologic studies for a variety of reasons;
the application of ground water models in regulation and litigation
is only one. Other reasons for maintaining leadership involve the
estimation of natural resources and their availability, the evaluation
of the safety of disposal of high-level and transuranic wastes in deep
geologic deposits, and the understanding of potentially significant
changes to our ecosystems (e.g., acid rain and CO2 increases). In
general, it is difficult to prioritize specific research requirements for
each particular application, and this report does not attempt to
do so. If research is needed to improve an aspect of hydrogeologic
modeling for application to regulation or litigation, the committee
makes no attempt to place that need in the context of other areas of
study that will benefit from the research. Certainly, there are whole
areas of ground water research that will be omitted, e.g., regional
modeling of watersheds and river basins affected by global climate
changes.
Another consideration that influences the committee's recom-
mendations for future research is the present state of the science in
subsurface hydrology. It is evolving; indeed it is on the threshold of a
significant change in how the subsurface environment is interpreted.
Current transport theory developments based on statistical inter-
pretations of subsurface deposits may, in time, replace much of the
deterministic theory. At issue are the characterization and simula-
tion of dispersive phenomena. Central to this issue is the relationship
between measurable quantities and parameters for flow and trans-
port models. While these fundamental underpinnings to the models
of conservative contaminant transport are being revisited, research
continues to extend standard deterministic theory to better simu-
late a great variety of complex situations. Examples of extensions
to deterministically based theory are multiphase flow phenomena,
microbiological processes influencing water quality, and coupled geo-
chemistry and transport models. Thus extensions of current models
OCR for page 251
RESEARCH NEEDS
251
to more complex processes and greater spatial dimensionality are
being made at the same time that foundational aspects of basic
transport theory are being revisited.
The state of the practice does not reflect the state of the art,
because of the scope of ongoing research and because of the strength
with which opposing views are held and debated. The science has
not come to grips with the gap between practice and art. Concern
exists that until one can predict with confidence the migration of a
conservative solute within a heterogeneous medium, one will not be
able to convince a great many people of the veracity of reactive solute
migration predictions. However, scientists must come to realize that
modeling is used to avoid bad decisions as well as to make the
best decision. Indeed, the evaluation of good alternatives may be
uncertain to the degree that no clear best alternative exists. To the
extent that existing field-scale models provide qualitative assessments
of good versus bad, they are useful and appropriate. Such a rationale
justifies the use of screening models to prioritize sites for further
study and possible remediation. Research must be conducted to
encourage greater acceptance of screening models and to ensure the
proper expenditure of resources they influence. Resources also need
to be devoted both to continue fundamental research and to decrease
the gap between the state of the art and the state of the practice.
There is a recognized need to revise our current concept of mod-
eling and modelers. Modeling needs to be redefined as a cost-effective
way of interpreting all available data, to the extent that the interpre-
tation provided by that modeling effort enables one to be comfort-
able in making a decision. Viewed in this way, modeling involves a
spectrum of allied technologies that combine to provide the needed
interpretation of subsurface events. In such a setting the modeling
process would be viewed as a whole, and all subjective decisions af-
fecting the modeling process are seen to contribute to an assessment
of accuracy. Individuals responsible for mode} applications would
be more appropriately described as analysts, rather than modelers,
because of the spectrum of technologies to be applied and because of
the subjective interpretations required.
The preceding remarks guide the scope of the committee's recom-
mended research. The committee members, primarily ground water
modelers, recognize that evaluation of modeling accuracy is a broad
topic influenced heavily by subjective decisions made when climate
scenarios are developed, site characterization plans are made and
data are analyzed, and subsurface conceptual models are formalized.
OCR for page 252
252
GROUND WATER MODELS
The scope of research in the future must be broadened to formal-
ize methods of recording subjective inputs and quantifying accuracy
within the modeling process. The objective of mode} validation must
be to quantify the accuracy of a mode} prediction for a particular ap-
plication. In addition to a core effort to develop accuracy assessment
methods, research must improve the methods available to gather and
evaluate field data for site characterization, contaminant detection,
and contaminant plume monitoring. The focus of a coordinated
research program must be on the mode} process and its ability to
predict, over the time frame of interest, the behavior of field-scale
events.
USE OF MODELS
There is no doubt that increasingly greater scientific emphasis is
being placed on the use of predictive computer models in ground wa-
ter hydrology and geochemistry. Early applications of ground water
models emphasized qualitative or relative evaluation of several alter-
natives. Models were used to better understand the potential impacts
of alternative water use or disposal strategies. Water quantity rather
than quality was the focus of this modeling, and relative comparisons
appear to have been adequate to resolve litigation and regulation
questions. With the full allocation or overallocation of ground water
resources and the advent of ground water quality regulation, the at-
tention of hydrologists has turned to quantitative analysis of water
quantity and quality with emphasis placed on contaminant migra-
tion. The trend is toward analysis of the interrelationship between
quality and quantity of the subsurface water resource and optimiza-
tion of various pumping, storage, and remediation designs. The
emphasis of most modeling efforts today is on providing an absolute
rather than relative performance estimate.
Perhaps the most obvious example of this is in the area of storage
and disposal of high-level nuclear wastes in geologic repositories (see,
for example, Erdah} et al., 1985; Jacobs and Whatley, 1985~. The
Nuclear Waste Policy Act of 1982 (Public Law 97-425, 96 Stat. 2201,
42 USC 10101) specifies that the Department of Energy (DOE),
the U.S. Nuclear Regulatory Comrn~ssion (USNRC), and the U.S.
Environmental Protection Agency (EPA) are responsible for doing
the necessary preliminary work to permit the siting and construction
of a geologic repository for high-level nuclear wastes in the United
States. The only obvious method for predicting the rate of release,
OCR for page 253
RESEARCH NEEDS
253
geochemical behavior, and rate of transport over a period of 100,000
yr is through computer modeling. Other approaches are possible, but
they are at least as uncertain as computer modeling. For example,
experiments can be conducted at elevated temperatures to accelerate
reactions and thus to simulate longer periods of tune, but there is no
guarantee that acceleration resulting from higher temperatures will
really simulate long periods of time at low temperature. Another
approach is to examine geological sites and ancient archaeological
relics for clues as to the behavior of certain chemical elements, but
suitable situations are rare for implementing this strategy. All in all,
computer modeling probably has at least as good a chance of yielding
meaningful predictions as any of the other approaches.
A second example is the multitude of governmental agencies and
private firms that increasingly rely on computer modeling techniques
to investigate, predict, and guide the cleanup of natural waters con-
taminated by impurities that have escaped from landfi~Is or from
subsurface storage facilities. It appears that the two main objectives
in the use of predictive modeling in this area are (1) to optimize the
placement of test weld and monitoring wells and (2) to allow inves-
tigators to predict the future behavior of a plume of contarn~nation.
An obvious application would be to follow a plume of contamination
in an aquifer backward in time and space in an effort to determine
its original source. The general subject of contamination of ground
water is discussed in some detail in a report by the National Research
Council (1984) entitled Groundwater Contamination.
A third potential use of predictive modeling, which has not yet
been widely recognized, ~ to determine what the natural background
concentrations might have been in a region prior to any impact by
man. This latter application may be particularly useful in establish-
ing natural background concentrations of toxic metals in mineralized
regions prior to the initiation of mining and milling.
There ~ little doubt that the current use of predictive computer
models in interpreting and predicting the behavior of contaminants
in ground water will continue and, in all probability, will increase. At
the same time, as discumed in other chapters of this report, enough
has been learned about the weaknesses of such models to justify the
significant amount of skepticism that has also developed, both in
the scientific community and in the regulatory arena. It is hoped
that the proper mix of science and skepticism will be found and that
the combination will allow the identification and use of a variety of
predictive models that have been adequately tested and found to be
OCR for page 254
254
GROUND WATER MODELS
appropriate, within acceptable limits of error, for a variety of field
situations. This is truly a necessity for some situations, such as the
disposal of nuclear wastes, that cannot be addressed in any other
manner.
Emphasis on predictive rather than relative results has created
an interest in the uncertainty of predictions. Unfortunately, un-
certainty in estimates of ground water system behavior arises from
several sources, some of which cannot be quantified. Indeed, there is
no known truth to compare against when assessing uncertainty. This
is the state of affairs despite the fact that a single conceptual picture
of the subsurface environment does exist. Acknowledged sources of
uncertainty are (1) ignorance of the true operative and dominant
processes or reactions, (2) ignorance of true site characteristics lead-
ing to inaccurate boundary and initial conditions, (3) the inability
to sample and quantify natural spatial and temporal variability, and
(4) the extrapolative rather than interpolative character of predic-
tions. The ability to quantify sample variability is complicated by
the existence of measurement error, dissimilar data (e.g., sampling
method, instrument, and volume), and quasi-periodic or random
events. Clearly, sensitivity and uncertainty methods are unable to
represent several of the known sources of uncertainty.
Recent work has heightened the awareness of the potential un-
certainty in ground water mode! results and has led to some caution,
or at least warnings, regarding the use of modeling results in the
dec~ionmaking process. With regard to the use of deep geologic
deposits for the disposal of nuclear wastes, Niederer (1988) believes
that certainty is as important as safety. He suggests that the wise de-
cision is to place waste where one has confidence in the performance
of the geologic setting and not to place it where one merely hopes
the performance will be safer. Niederer (1988) also believes that un-
certainty in conceptual modem is more disquieting than uncertainty
in parameters, especially for flow models. Hm underlying concern
is the potential dominance of uncertainty components that are not
quantifiable. Confidence and credibility of ground water mode} ap-
plications depend on demonstrated applicability in every instance.
Research must be undertaken to establish the framework necessary
to demonstrate the applicability of models used in formulating or
responding to regulation. The objective of such a demonstration is
to ascertain the applicability of a given mode} through an assess-
ment of accuracy and uncertainty for each situation or problem set
of interest.
OCR for page 255
RESEARCH NEEDS
255
SCIENTIFIC TRENDS AND RESEARCH
Three basic objectives inform the recommendations for scien-
tific research presented here: (1) to better understand and mode!
individual processes and reactions, (2) to translate process-level un-
derstanding to sitewide simulation capability, and (3) to integrate the
interdisciplinary technology needed to solve ground water contami-
nation problems. While our understanding of subsurface processes
and reactions has grown significantly in recent decades, something
less than a predictive capability exists at this time. Indeed, where
process and reaction models exist, field-scale observations of flow and
transport have led to the realization that models based largely on
laboratory- or caisson-scale studies do not provide a predictive capa-
bility at the field scale. It is also apparent that the understanding of
models for some processes and reactions is not sufficient for predic-
tive purposes in the face of complex, heterogeneous, and anisotropic
environments. When process models become accepted, significant
efforts are needed to translate the research results into an accepted
field-scale technology. Assessments of mode} accuracy and validity at
the field scale are an important aspect of this translation from science
to application. Finally, interdisciplinary efforts that bring together
site geologists, hydrologists, geochemists, geostatisticians, and health
physicists are essential if ground water models and allied technolo-
gies are to be routinely applied to study and solve contamination
problems with confidence.
Basic Understanding and Process Models
Two paths have been taken toward improving our basic under-
standing and developing more predictive ground water models: (1)
the further development of mechanistic and deterministic models for
individual processes and (2) the development of probabilistic models
that recognize the inherent uncertainty in nature and in our ability
to characterize and mode} the subsurface environment. Ultimately,
both paths have a single objective: to understand basic processes
and reactions and their interrelationships. Such an understanding
will lead to predictive models of events at the field scale.
Physical processes that control or strongly influence contami-
nant migration in the subsurface remain an area of intense research.
While relatively better understood than geochem~cal and m~crobi-
ologica] processes, present conceptual and mathematical models of
convection and dispersion do not provide accurate results or inspire
OCR for page 256
256
GROUND WATER MODELS
confidence when applied to highly heterogeneous or otherwise com-
plex environments. The probabilistic approach is seen as a way to
account for the inherent uncertainty in both the subsurface structure
and the knowledge of flow and transport processes.
Process Models
While considerable progress has been evident in developing mass
transport as a practical tool, the hope of routinely using these models
in practice lies somewhere in the future. One reason for this state
of affairs is the limited ability of most models to account for the
important transport processes in a realistic and convincing way.
Nowhere is this problem as obvious as with the physical processes
accounting for organic compound migration and the chemical and
biological processes occurring for a variety of contarn~nants, where
considerable effort will be expended to solve a few key problems.
The following sections outline the trends of future research designed
to improve our understanding of the processes and demonstrate the
validity of coupled models.
Multiphase Fluid Flow and Transport Models
An obvious trend in research is to extend modeling capabilities
to new classes of problems. A case in point is the commonly encoun-
tered problem of multiphase fluid flow and transport accompanied by
dissolved component transport in water. Many of the most common
organic contaminants are moderately to strongly hydrophobic. Ex-
amples are the chlorinated solvents, various petroleum constituents,
pesticides, and PCBs. Modeling of the fate of hydrophobic com-
pounds can be complicated because they can form a continuous
nonaqueous phase, sorb to aquifer solids, and volatilize to a gas
phase. Modeling the transport of hydrophobic materials will require
that these complications be incorporated into a solute transport
model.
When the organic compound forms a nonaqueous-phase liquid
(NAPL), it creates three modeling difficulties. First, a significant
accumulation of NAPL gives rise to multiphase or immiscible flow,
a situation that is poorly understood mechanistically and difficult
to describe mathematically. Thus modeling the movement of the
NAPL, which is at least partly independent of the movement of
the water, creates an added computational burden, if it can be
OCR for page 257
RESEARCH NEEDS
257
described at all. A general lack of fluid retention characteristics and
relative permeabilities for organic compounds or mixtures of organic
compounds in the presence of water and air will greatly limit our
ability to simulate multiphase fluid migration. Because of interest in
the drainage and removal of hydrophobic contaminants, models of
hysteresis in soil-fluid properties are essential in correctly simulating
the wetting and drainage phenomena of both the organic compound
and the water.
Second, the presence of an NAPL provides a long-term source
for dissolution of contaminants to the aqueous phase. Description
of the rate of dissolution requires knowledge of the presence of the
NAPL and of the factors controlling its dissolution. Although it
is probable that the solubilization is driven by the difference be-
tween the aqueous-phase concentration and the maximum solubility,
the rate of dissolution is probably controlled by hydrodynamic as-
pects of mass transport and the presence of other contaminants.
Even when the controlling factors are known, their inclusion into
the mode! could increase the computational needs. Finally, model-
ing of NAP Es ultimately requires some field verification of NAPEs
in subsurface systems. This presents numerous difficulties with re-
gard to sampling and interpreting the field-scale environment. Bulk
spills or disposals of NAPEs dominated by a single fluid (e.g.,
fuel of! or trichIoroethene), do exist; however, many cases exist in
which the NAPL is a mixture whose behavior in the environment
can be quite complicated. Methods of sampling the subsurface
and of preserving samples to determine the extent of contamina-
tion must acknowledge the variety of contaminants potentially
present in soil and fluid samples. Due to the natural heterogene-
ity of subsurface environments, NAP Es often are not homogeneously
present but are difficult to locate, especially because they can spread
out into thin layers. Ultimately, the relationship between flow physics
and natural spatial variability will have an impact on the interpreta-
tion of field-scale observations through an understanding of viscous
fingering, i.e., the balance struck between continuum and channel
flow phenomena.
Hydrophobic organic compounds also sorb onto or into aquifer
and soil solids, especially soil organic matter and clays. Like NAPEs,
sorbed materials can be a source of long-term, chronic water con-
tamination as they are slowly Resorbed. Solute transport modeling
requires that the accumulation of sorbed material be accounted for
and that the rate of desorption be described. In addition, realistic
OCR for page 258
258
GROUND WATER MODELS
sorption relations are not necessarily linear (e.g., like partition coef-
ficients), which gives rise to much more difficult mathematical and
numerical solution requirements for nonlinear terms.
For NAPEs and sorbed contaminants, the coupling of their addi-
tion to the water with water-phase reactions, such as biodegradation,
can create significant complications. For example, microorganisms
degrading a dissolving solvent might be located a short distance away
from the interface of the water and the NAPL; thus the dissolving
compound is exposed to a biological reaction that consumes the con-
taminant, allows less contaminant to pass to the rest of the water,
and creates an increased driving force for more dissolution. Reac-
tions that can occur on a scale (e.g., micrometers to centimeters)
much smaller than the mode! grid are among the most significant
complications. The effect of including this microscale for a reaction
is to introduce another spatial scale to transport models, which in-
creases the computational intensity. Additionally, the phenomena
controlling reactions (especially biological) for dissolving or Resorb
ing contaminants are not easily described.
Third, some of the hydrophobic compounds (e.g., the chlorinated
solvents) also are volatile and will partition to a gas phase. Thus if
there are unconfined conditions and especially if there is gas produc-
tion (e.g., with in situ biorecIamation or in situ aeration), some of the
volatile contaminants can leave the aqueous and solid phases and go
into the gas phase. Modeling of solute transport in such a situation
must involve mass balances in the gas phase and description of the
transfer rates between the gas phase and other phases. Not only do
these requirements add to the computational demands, but they are
not easily described with our current knowledge.
In summary, modeling that realistically includes hydrophobic
components may become significantly more computationally inten-
sive because of the need to keep track of nondissolved species, to
describe transfer rates between phases, and to mode} on a small
scale. Computationally efficient solution techniques, such as quasi-
linearization, and the use of local analytical or pseudoanalytical
solutions may become a key aspect of successful modeling.
Linking Geochemical and Physical Transport Models
Considerable success has been achieved in modeling the geo-
chemistry of natural waters and in modeling the movement of ground
OCR for page 259
RESEARaH NEEDS
259
waters. It is logical to take the next step and link an equilibrium geo-
chemical mocle} with a ground water transport model. An optimist
would say that the product of the linkage should be a mode} that has
the capability of predicting chemical changes in the ground water
and reactions between the water and the aquifer at each point in
space along the flow path. A pessimist would probably visualize such
a linkage as being nothing more than the compounding of errors and
uncertainties inherent in each of the two separate and still immature
models. The truth, at this point in time, lies somewhere between the
extremes, but perhaps closer to the pessimist's point of view. The ba-
sis for this somewhat negative evaluation is the fact that researchers
in geochemistry have yet to demonstrate that any of the popular
geochemical models can be fully validated against field or laboratory
data. This is not the fault of the models, but instead points to a
surprising lack of field and laboratory studies that are designed or
are suitable for purposes of validating the theoretical models. Mod-
elers tend to go their own way, building impressive computer codes
to s~rnulate nature, while field and laboratory workers tend to gather
data that are highly relevant for many purposes, but perhaps not
for validating models. The lack of validation is far less severe and
pervasive in hydrology than it is in geochemistry, but it does exist.
The main obstacle in hydrology may be the disparity between the
simplifications that are required to write a usable computer code and
the great complexities that can exist in real field situations. The
most obvious example is the stratigraphic heterogeneity of many real
aquifers, in contrast to the perfect homogeneity or the vastly simpli-
fied heterogeneity required for modeling. A similar obstacle will face
geochemists when field-scale validation is undertaken.
Just as hydrologists use simplifying assumptions essential to the
creation of a viable conceptual model, geochemists also employ sim-
plifying assumptions. Foremost is the assumption of equilibrium
thermodynamics determining the aqueous-phase composition. This
single assumption influences the form of governing equations and
thermochemical databases. Time dependency through dynamic or
kinetic reactions is omitted, as are rate constants in the database.
When time dependency is observed to be significant in field settings,
both the reactions and the associated data will need to be incorpo-
rated into either established equilibrium-based codes or entirely new
codes. It is apparent that kinetic reactions are important to some
contamination events of interest, e.g., the leaching of fly ash and flue
gas desulfurization sludge (Warren and Dudas, 1986~.
OCR for page 274
274
GROUND WATER MODELS
1. The acIdition and extraction of water through wells or
trenches create local nonhomogeneities of head, flow, and solute
concentrations. Chemical and biological reactions are likely to be
most intense near the nonhomogeneities. Modeling around nonho-
mogeneities requires, at a minimum, a tight grid spacing.
2. Flow velocities are often significantly increased in a remedi-
ation site in order to flush water and reactants through the ground.
The high velocity can alter flow paths and may accentuate the effects
on heterogeneities (natural or induced). Therefore modeling that
includes heterogeneities is emphasized.
3. The biological and chemical reactions often will alter the
permeability of the soils or aquifer, especially near the introduced
nonhomogeneities. Thus models must include the interactions of flow
and reaction.
4. The mode] must keep track of at least two reacting species:
the contaminant and the added material that reacts with the contam-
inant. Their removals usually are linked stoichiometrically, but one or
both can control the overall reaction rate. Often, many species must
be followed, including products, and these species may be affected
in very different manners by other mechanisms, such as sorption or
volatilization.
Another area of interdisciplinary research involves the disposal
of liquid hazardous wastes by subsurface injection through wells into
deep aquifers. This technique began in the United States in the 1950s
and 1960s and was seen as a relatively inexpensive way to prevent
pollution of rivers and lakes. Depths of injection typically range from
0.25 to 1 mi below the surface (Gordon and Bloom, 1986~. The liquid
wastes most frequently injected into the subsurface are corrosive and
reactive liquids, organics, and dissolved metals.
In 1983, EPA identified 90 facilities in the United States where
195 wells were being used for disposal of hazardous wastes (Brasier,
1986~. Subsurface injection is the predominant form of hazardous
waste disposal in the United States, accounting for 60 percent, or ap-
proximately 10 billion gal. In contrast, only 35 percent of hazardous
wastes was disposed of in surface impoundments and 5 percent in
landfi~Is in 1981 (Gordon and Bloom, 1986~. The predominance of
subsurface injection as a method of disposal is largely due to the low
cost in relation to other technologies. Until recently, little, if any,
treatment of the wastes was required before injection. As with other
OCR for page 275
RESEARCH NEEDS
275
other methods of waste disposal, usable ground water has been con-
taminated by escaping toxic wastes from injection facilities (Gordon
and Bloom, 1986~.
A majority of the subsurface injection facilities are used by the
chemical and petrochemical industries located in Texas, Louisiana,
Ohio, Michigan, Indiana, and Illinois. All wells used for injection of
hazardous materials are subject to control by the Safe Drinking Water
Act (see discussion in Chapter 5) and the Resource Conservation and
Recovery Act (see Chapter 5~.
Prior to the initiation of injection, a vast array of chemical, phys-
ical, geological, and hydrological parameters should be considered.
Chemical and physical factors include density, reactivity, viscosity,
temperature, content of suspended solids, content of gases, pH, Eh,
stability, and volatility. Geological and hydrological factors that
should be considered include the permeability and effective porosity
of the injection horizon, thickness and integrity of the aquicludes that
separate the injection zone from adjacent usable aquifers, possible
zones of recharge and discharge, effective porosity, content of clay
and other reactivity minerals in the host formation, magnitude and
direction of pressure heads, preferred paths of flow, and salinity and
reactivity of indigenous water in the formation. The prospect of hav-
ing to properly consider such a list of parameters prior to injection
would probably cause any potential disposer to hesitate to initiate
such a program.
The extreme difficulty and cost involved in obtaining adequate
field and laboratory data prior to construction of deep-well injection
facilities contribute to the increasing use of predictive computer mod-
eling. Predictive modeling potentially offers a means to minimize,
or at least to optimize, the drilling of numerous test and monitoring
wells and possibly to fill existing gaps in knowledge. Prickett et al.
(1986) discuss the application of flow, mass transport, and chemical
reaction modeling to subsurface liquid injection. They point out that
modeling is necessary for estimation of pressure buildup rates at the
injection well and of distribution of pressure buildup in the reservoir.
With regard to transport of contaminants, it would be desirable to
include advection, dispersion, sorption, decay, and biochemical re-
action, but at present no mode] can deal with the full complexity
of the transport and chemical reactivity of a waste in a deep, high-
pressure, high-temperature, high-salinity, subsurface environment.
Prickett et al. (1986) suggest that, while it is not possible to truly
simulate the transport and reactivity of injected wastes, it should be
OCR for page 276
276
GROUND WATER MODELS
possible to mode} the worst-case scenario of conservative transport
of all dissolver! chemicals. Strycker and Collins (1987) state that ad-
ditional research is needed in virtually all areas of abiotic and biotic
waste interactions before definitive explanations can be given of their
long-term fate.
Clearly, the deep-well injection of hazardous wastes is an area
that could potentially benefit from improvements in our capabilities
for modeling transport in ground water. To reach this goal, much
research is needed in the coupling of transport and chemical models,
so that more realistic predictions of the movement and fate of injected
chemicals can be made.
POLICY TRENDS AND SUPPORT FOR RESEARCH
An EPA study found that existing ground water models do not
account for all processes affecting the fate and impact of contami-
nants. For example, the flow and transport of organic solvents are
influenced by the hysteresis in multiphase soil-fluid characteristics
and by biotic and abiotic fate processes; neither is accounted for in
existing and available codes. It is thought that existing models lack
accuracy when confronted with a high degree of heterogeneity, and,
in general, it is believed that data requirements to ensure high levels
of confidence in the accuracy of predicted results are prohibitively
expensive. It is disturbing to know that models lack accuracy; it is
worse not to know the accuracy of the model.
Models in support of policy and in response to regulation range
from generic to fully mechanistic. Generic models often require no
site-specific data, embody no attenuation mechanisms, and charac-
terize transport as a one-dimensional flow path. The need to prior-
itize or rank disposal sites for cleanup actions in the face of limited
resources has led to the application of models requiring little or no
site-specific data (Whelan et al., 1987; see vertical-horizontal spread
mode! case study in Chapter 5~. While applications of generic mod-
els will continue, it would be informative to better understand the
relationship between the results of such modeling and actual site per-
formance. For example, when generic models are used, are the worst
sites always identified as being worst, and are all sites ranked in a
hierarchy associated with a real risk ranking? At the other extreme,
the need to assess environmental impacts from wastes previously
disposed of in complex hydrogeologic systems makes it necessary to
improve our understanding of complex systems. Thus complexities of
OCR for page 277
RESEARCH NEEDS
277
process (e.g., organic compounds, dimensionality, and mathematical
formulation heterogeneity, anisotropy, spatial variability, fractured
media, and karst systems) must be addressed through continued re-
search if we are to be able to realistically portray the risk of future
events.
The siting regulation for new low-level waste (ELM) disposal
sites (10 CFR Part 61) states that "the disposal site shall be ca-
pable of being characterized, modeled, analyzed, and monitored"
(U.S. Nuclear Regulatory Commission, 1987~. Thus the responsi-
bility for being able to simulate site performance is a responsibility
of the licensee. Furthermore, it is implied that hydrogeologic sys-
tems that cannot be characterized, modeled, analyzed, or monitored
with confidence are to be eliminated from consideration. Thus the
need to regulate LLW sites does not directly justify research on com-
plex hydrogeologic systems. This regulation provides no guidance on
measures of confidence; however, all subsurface environments are un-
certain or unknown to some degree. A logical question is: What level
of confidence is necessary before one can claim an ability to mode}
or analyze a site? Methods that quantify confidence in ground water
modeling results must be developed for application to any disposal
site.
As models have begun to influence the assignment of liability and
the assessment of long-term hazard, modeling results have begun to
be viewed as quantitative rather than qualitative. Modeling results
are now frequently compared to regulatory limits, and the methods
used to make these comparisons are important to the proper por-
trayal of modeling results. Reasonable assurance is a concept that
has arisen from the study of the potential for deep geologic systems
to provide isolation of high-level radioactive wastes. This term refers
to the interval between a realistic assessment of poor performance
and a regulatory limit. It represents the interval of safety. If reason-
able assurance exists that an event is safe, then it is implied that a
comprehensive and defensible analysis supports the finding.
If a "bounding performance" estimate indicates good perfor-
mance (i.e., does not exceed the regulatory limit), then a realistic
analysis providing an estimate of mean and uncertainty ranges is
unnecessary. Only in the instance depicted in Figure 7.1, when
bounding performance exceeds regulatory limit, does one need to
perform a realistic analysis. A realistic analysis is essentially an ef-
fort to demonstrate regulatory compliance when realistic rather than
bounding models and mode} parameters are employed. Of course,
OCR for page 278
278
Good
Performance
Extreme
Realistic
Performance
Estimate
~\\ ~I
Uncertainty in Estimate |
GROUND WATER MODELS
Poor
Performance
Extreme
Regulatory
Limit
Bounding
Performance
Estimate
1. ~
Reasonable
Assurance
FIGURE 7.1 The relationship of reasonable assurance to bounding analysis,
regulatory limit, and realistic estimates.
when realism ~ introduced, so is uncertainty, and it must be quan-
tified to the extent practical. This same logic suggests that after
compliance is triggered by conservative modem (used in the prioriti-
zation of sites), more realism and certainty should be required if the
output of a mode! is used directly to trigger additional regulatory
action than if the mode} is used as an interpretative too! to better
understand how contaminants migrate.
Currently, EPA is adopting an approach for pesticide regulation
requiring differential management of pesticide use based on differ-
ences in the use, value, and vulnerability of ground water. This
implies a recognition of the value to society of using chemicals. It
may also signal movement toward acceptance of "de m~nimus"-based
regulations, in other words, regulations based on the detection of
chemicals at lower levels. Thus the ability to mode} complex envi-
ronments and complex contaminants may become more crucial in
the future.
Because mode} results are being viewed predorn~nantly as quan-
titative in regulatory and litigious settings, accuracy and uncertainty
are of interest. However, accuracy per se is difficult if not impossible
to assess because the subsurface is always to some degree unknown
and uncertain. Indeed, the dominant use of the term uncertainty
instead of certainty implies the degree to which the environment is
unknown and uncharacterizable. Current research seeks, in part,
methods to quantify certainty by relating uncertainty in knowledge
of the subsurface to uncertainty in predictions of future events. The
"truth" of the subsurface environment is not known; therefore re-
search toward methods of quantifying uncertainty must treat the
OCR for page 279
RESEARaH NEEDS
279
influence of both subjective and objective judgments on mode] pre-
dictions.
One should be aware that in the application of an overly so-
phisticated model, or any model, to a situation that does not merit
sophisticated modeling, the level of knowledge implied by such model
results can be misleading. When mean values and/or distributions of
parameters are purely assumed, assumptions may outweigh knowI-
edge, and mode} results may imply a level of knowledge or certainty
that does not exist. Methods of uncertainty analysis that include
the influence of subjective decisions on mode} results will help to
ensure the proper use of models by revealing cases where ignorance
outweighs knowledge.
A number of governmental agencies are active in subsurface en-
vironmental studies; however, it is not clear if this contributes to
the problem or to the solution of developing theoretically sound and
computationally correct ground water models. For example, hydro-
geologic studies are among the least funded research topics by the
National Science Foundation. This is the case despite the fact that
several federal agencies- including the Departments of Defense, the
Interior, and Energy, as well as EPA- support a variety of research
and application activities that depend on knowledge of the subsurface
environment.
Issue resolution, legal or regulatory, will not wait until the perfect
solution is found. The field of hydrogeology needs to have established
and accepted technology, even if flawed, for application to a host of
current problems while science advances. However, simply having
an accepted technology does not obviate the need for continued ad-
vancement. Within the federal bureaucracy, some division exists for
those who fund applications and those who perform research-oriented
studies. For example, within the USNRC, the bulk of funding to
support research is controlled by those responsible for licensing nu-
clear facilities. The foundational belief of any group having licensing
responsibility must logically be that sufficiently applicable and defen-
sible technology exists today to license needed facilities. Support for
research issues requiring {ong-term funding and high-risk approaches
may not be within their purview.
Management by crisis and/or strongly justified large initiatives
appears to be the current mode of operation within government. Ini-
tiatives such as acid rain, global climate change, the supercollider,
RCRA, and Superfund are examples. EPA is one of the few govern-
ment agencies that have as a minion the protection and especially
OCR for page 280
280
GROUND WATER MODELS
the improved understanding of our subsurface environment. Most
have the responsibility to quantify the impact of their mission on the
subsurface. Often they are charged with simply using existing tech-
nology to estimate the impacts of waste disposal, remediation, and so
on, on ground water aquifers. Frequently, new initiatives encompass
a spectrum of technologies, ground water environs being only one
component. Acid rain and global climate change are examples of
research investments that embrace ground water issues but may not
significantly improve our understanding of ground water flow and
contaminant transport. Rather, they will improve our understand-
ing of linked processes that, when integrated over significant spatial
and temporal scales, serve to estimate the overall response of the
environment. Such diversified studies do not significantly advance
our understanding of basic physical processes such as dispersion or
of ways to directly relate mode! parameters to measurable quantities.
It is true that ground water models that consider spatial and tem-
poral changes appear to be advanced technology when compared to
our understanding of geochemical and microbiological phenomena.
However, more advanced methods of ground water characterization
and modeling are needed in order to understand with confidence
where a contaminant ~ in the subsurface so that the effectiveness of
bioremediation methods for in situ treatment of contaminants can be
estimated. Government research programs studying interdisciplinary
problems need to appreciate the complexities of flow and transport
phenomena that are not well understood and, as a consequence, are
poorly simulated.
An interesting evolution seems to have taken place with regard
to predictive modeling from the point of view of regulatory agencies.
With the development of comprehensive hydrologic models in the
1960s and 1970s, regulatory agencies seemed to accept the predicted
results with a certain amount of awe. The potential power of the
approach was obvious to even the most nontechnical member of a
regulatory board or agency. The same is true of the introduction of
comprehensive geochemical models in the 1970s and 1980s. Again,
the sheer power of the methodology was obvious and a bit over-
whelming. Although regulatory bodies might not fully understand
either the input or the output from such models, they seemed to be
willing to accept the word of the experts regarding the usefulness
of the predictions. However, in the last five years or so, quite the
opposite attitude seems to be developing on the part of the regula-
tory agencies. An enormous amount of skepticism appears to have
OCR for page 281
RESEARCH NEEDS
281
developed, with a resulting attitude of "Prove it!" having replaced
the more passive and accepting faith of earlier years. At this time,
modelers are in the spotlight, and on the spot, to demonstrate that
their long-term predictions are worthwhile and meaningful. This
new attitude can only be healthy for the science and art of predictive
modeling; it will force the scientists to come to grips with the gaps
and unknowns that exist, both in the modem themselves and in the
field and laboratory data that are required to validate the models.
REFERENCES
Barstow, D. 1983. A perspective on automatic programming. Pp. 1170-1179
in Proceedings of the Eighth International Joint Conference on Artificial
Intelligence, Karlsruhe, West Germany.
Beck, M. B. 1987. Water quality modeling: A review of the analysis of
uncertainty. Water Resources Research 23~8), 1393-1442.
Betson, R. P., L. W. Gelhar, J. M. Boggs, and S. C. Young. 1985. Macrodis-
persion Experiment (MADE): Design of a Field Experiment to Investigate
Transport Processes in a Saturated Groundwater Zone. EPRI-EA-4082,
Electric Power Research Institute, Palo Alto, Calif.
Bonnet, A., and C. Dahan. 1983. Oil-well data interpretation using expert
system and pattern recognition technique. Pp. 185-189 in Proceedings
of the Eighth International Joint Conference on Artificial Intelligence,
Karlsrnhe, West Germany.
Cederburg, G. A., R. L. Street, and J. O. Leckie. 1985. A groundwater mass
transport and equilibrium chemistry model for multicomponent systems.
Water Resources Research 21~8), 1095-1104.
Domenico, P. A., and G. A. Robbins. 1985. A new method of contaminant
plume analysis. Ground Water 23~4), 476-485.
Duda, R. O., P. E. Hart, K. Konolige, and R. Reboh. 1979. A Computer-
Based Consultant for Mineral Exploration. Final Report, SRI Project
6415, Artificial Intelligence Center, SRI International, Menlo Park, Calif.
Erdahl, B. R., J. H. Heiken, and J. Howard. 1985. Workshop on Fundamental
Geochemistry Needs for Nuclear Waste Isolation, Los Alamos National
Laboratory, N. Mex. June 20-22, 1984. Department of Energy Report
CONF8406134, 208 pp.
Fenves, S. J. 1986. What is an expert system? Pp. 1-17 in Expert Systems in
Civil Engineering, C. N. Kostem and M. L. Maher, eds. American Society
of Civil Engineers, Seattle, Wash.
Freeze, R. A. 1975. A stochastic conceptual analysis of one-dimensional ground-
water flow in non-uniform homogeneous media. Water Resources Research
11~5), 725-741.
Freeze, R. A., and J. A. Cherry. 1979. Groundwater. Prentice-Hall, Englewood
Cliffs, N.J.
Freeze, R. A., G. De Marsily, L. Smith, and J. Massmann. 1989. Some Uncer-
tainties About Uncertainty. Pp. 231-260 in Proceedings of the Conference
on Geostatistical, Sensitivity, and Uncertainty Methods for Ground-Water
Flow and Radionuclide Transport Modeling Held in San Francisco, Cali-
fornia, September 15-17, 1987. Battelle Press, Columbus, Ohio.
OCR for page 282
282
GROUND WATER MODELS
Goodall, A. 1985. The Guide to Expert Systems. Learned Information (Europe)
Ltd., Abington, England, 220 pp.
Gordon, W., and J. Bloom. 1986. Deeper problems, limits to underground
injection as a hazardous waste disposal method. Pp. 3-50 in Proceedings
of the International Symposium on Subsurface Injection of Liquid Wastes,
March 3-5, New Orleans, La. Underground Injection Practices Council, As-
sociation of Ground Water Scientists and Engineers, Water Well Publishing
Company, Dublin, Ohio.
Gutjahr, A. L. 1988. Hydrology. In Techniques for Determining Probabilities of
Events and Processes Affecting the Performance of Geologic Repositories,
Chapter 5. SAND86-0196, Sandia National Laboratories, Albuquerque, N.
Mex.
Hardt, S. L. 1986. On the power of qualitative simulation for estimating diffusion
transit times. Pp. 46~463 in Proceedings of the 1986 Winter Simulation
Conference (held in Washington, D.C.), J. Wilson, J. Henriksen, and S.
Roberts, eds. Association for Computing Machinery, New York.
Hayes-Roth, F., D. A. Waterman, and D. B. Len at. 1983. An overview of
expert systems. Pp. 3-29 in Building Expert Systems, F. Hayes-Roth, D.
A. Waterman, and D. B. Lenat, eds. Addison-Wesley, London.
Hoekeema, R. J., and P. K. Kitanidis. 1985. Analysis of the spatial structure of
properties of selected aquifers. Water Resources Research 21~4), 563-572.
Hostetler, C. J., R. L. Erikson, J. S. Fruchter, and C. T. Kincaid. 1988. Overview
of the FASTCHEMTM Package: Application to Chemical Transport Prob-
lems. EPRI EA-5870-CCM, Vol. 1, Electric Power Research Institute, Palo
Alto, Calif.
Jacobs, G. K., and S. K. Whatley. 1985. Conference on the Application
of Geochemical Models to High-Level Nuclear Waste Repository Assess-
ment: Proceedings, Oak Ridge, Tenn., Oct. 2-5, 1984. NUREG/CP-0062,
ORNL/TM-9585, U.S. Nuclear Regulatory Commission, Washington, D.C.
126 pp.
Kirkner, D. J., A. A. Jennings, and T. L. Theis. 1985. Multisolute mass
transport with chemical interaction kinetics. Journal of Hydrology 76,
107-117.
Law, K. H., T. F. Zimmie, and D. R. Chapman. 1986. An expert system
for inactive hazardous waste site characterization. Pp. 159-168 in Expert
Systems in Civil Engineering, C. N. Kostem and M. L. Maher, eds.
American Society of Civil Engineers, Seattle, Wash.
Ludvigsen, P. J., R. C. Sim, and W. J. Grenneg. 1986. A demonstration expert
system to aid in assessing ground water contamination potential by organic
chemicals. Pp. 687-698 in Computers in Civil Engineering, Proceedings
of the Fourth Conference, W. T. Lenocker, ed. American Society of Civil
Engineers, Boston, Mass.
Mackay, D. M., D. L. Freyberg, P. V. Roberts, and J. A. Cherry. 1986.
A natural gradient experiment on solute transport in a sand aquifer, 1.
Approach and overview of plume movement. Water Resources Research
22~13), 2017-2029.
McClymont, G. L., and F. W. Schwartz. 1987. Development and application
of an expert system in contaminant hydrogeology. Unpublished report for
National Hydrology Research Institute, Environment Canada, 206 pp.
OCR for page 283
RESEARCH NEEDS
283
Meintjes, K., and A. P. Morgan. 1985. A Methodology for Solving Chemical
Equilibrium Systems. General Motors Research Laboratory Report GMR-
4971, Warren, Mich., 28 pp.
Morgan, A. P. 1987. Solving Polynomial Systems Using Continuation for
Engineering and Scientific Problems. Prentice-Hall, Englewood Cliffs, N.J.,
546 pp.
National Research Council. 1984. Groundwater Contamination. Studies in
Geophysics. National Academy Press, Washington, D.C., 179 pp.
Niederer, U. 1988. Perception of safety in waste disposal: The review of the
Swiss project GEWAHR 1985. Pp. 11-26 in Proceedings of the GEOVAL
1987 Symposium in Stockholm, April 7-9, 1987. The Swedish Nuclear
Power Inspectorate, Stockholm.
Prickett, T. A., D. L. Warner, and D. D. Runnells. 1986. Application of
flow, mass transport, and chemical reaction modeling to subsurface liquid
injection. Pp. 447-463 in Proceedings of the International Symposium
on Subsurface Injection of Liquid Wastes, March 3-5, New Orleans, La.
Underground Injection Practices Council, Association of Ground Water
Scientists and Engineers, Water Well Publishing Company, Dublin, Ohio.
Rehak, D. R., R. R. Christiano, and D. D. Norkin. 1985. SITECHAR: An expert
system component of a geotechnical site characterization work bench.
Pp. 117-133 in Applications of Knowledge-Based Systems to Engineering
Analysis and Design, C. L. Dym, ed. American Society of Mechanical
Engineers, Miami Beach, Fla.
Robinson, V. B., and A. U. Frank. 1987. Expert systems for geographic
information systems. Photogrammetric Engineering and Remote Sensing
53~10), 1435-1441.
Smith, R. G., and J. D. Baker. 1983. The dipmeter advisor system: A
case study in commercial expert system development. Pp. 122-129 in
Proceedings of the Eighth International Joint Conference on Artificial
Intelligence, Karlsrnhe, West Germany.
Strycker, A., and A. G. Collins. 1987. State-of-the-Art Report: Injection of
Hazardous Wastes into Deep Wells. Report NIPER-230, National Institute
of Petroleum and Energy Resources, Bartlesville, Okla., 55 pp.
Thurman, E. M., L. B. Barber, Jr., and D. LeBlanc. 1986. Movement and
fate of detergents in groundwater: A field study. Journal of Contaminant
Hydrology 1~1/2), 143-161.
U.S. Nuclear Regulatory Commission. 1987. Low-Level Waste Disposal Licens-
ing Program Standard Review Plans. NUREG-1200, Washington, D.C.
Warren, C. J., and M. J. Dudas. 1986. Mobilization and Attenuation of Trace
Elements in an Artificially Weathered Fly Ash. EPRI-EA-4747, Electric
Power Research Institute, Palo Alto, Calif.
Waterman, D. A. 1986. A Guide to Expert Systems. Addison-Wesley, Reading,
Mass., 419 pp.
Weis~, S. M., and C. A. Kulikow,~ci. 1984. A Practical Guide to Designing
Expert Systems. Rowman and Allanheld Publishers, Totowa, N.J., 174 pp.
Westall, J. C. 1979. MICROQL:1: A Chemical Equilibrium Program in BASIC,
EAWAG. Swis~ Federal Institute of Technology, Duebendorf, Switzerland.
Westall, J. C., J. T. Zachary, and F. M. M. Morel. 1976. MINEQI~A Com-
puter Program for the Calculations of Chemical Equilibrium Composition
of Aqueous Systems. Tech Note 18, R. M. Parsons Lab., Massachusetts
Institute of Technology, Cambridge, 91 pp.
OCR for page 284
284
~ ~ INS
Whelan' O., D. L. Strange, J. G. Droppo, Jr" B. L. Steeling, and J. W.
Buck. 1987. Ibe Remedl~1 Action Prlorhy System TIPSY: ~tbem~t-
~1 ~rmul~tlons. DOE/RL/87-Og, PAL 620O1 Department of Inert,
shlugton' D.C.
b, O. T~ and V. S. ~lp~thl. 1989. ^ crklcs1 ev~lustlon of recent deveL
opponents in ~drogeoche=~1 transport models of re~ctlve multlcbem~1
components. water Resources ~se~rcb 25~1~, g3-108.
Representative terms from entire chapter:
water models
