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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

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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

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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.

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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,

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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

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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.

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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

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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

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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

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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

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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~.

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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

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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

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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

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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,

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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

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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

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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

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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.

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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.

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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.

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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.