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Knowledge Gaps and Research Needs The statement of task for this study directed the committee to identify significant knowledge gaps relevant to subsurface contamination prob- lems at DOE sites and to provide recommendations for a long-term basic research program to fill those gaps (see Sidebar 1.1~. In this chapter, the committee identifies what it judges to be the significant knowledge gaps that emerged from its review of DOE's subsurface contamination problems in Chapter 2 and, for each identified gap, the committee provides a short discussion of basic research needs. This information will be used to formulate recommendations for a long-term research program in Chapter 6. For purposes of this discussion, the committee defines "knowledge gap" as a deficiency in scientific or engineering understanding that is now, or likely will be in the future, a significant impediment to DOE's efforts to complete its mission to clean up, stabilize, or contain subsur- face contamination. Perhaps the most direct manifestation of a DOE knowledge gap is a technology gap, that is, a deficiency in technical capabilities to identify and deal with contamination problems. The committee has not focused on technology gaps in this report; that is the topic of another recent N RC report (N RC, 1 999~. Rather, the committee has focused on the identification of the knowledge gaps that underpin those technology gaps. The committee has been selective in the identification of subsurface contamination knowledge gaps and research needs for the EM Science Program. The identification of knowledge gaps involves an appreciable element of judgment on the part of the committee, especially in inter- preting the significance of the subsurface contamination problems (see Chapter 2) and the scope and objective of other federal research pro- grams. The committee believes that the gaps it has identified are highly C h a p t e r 5 93

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significant and that they must be addressed through basic research if the DOE cleanup program is to succeed. Further, the committee believes that a focus on these knowledge gaps is likely to yield the greatest payoffs for DOE in terms of enhanced cleanup capabilities at reduced costs and risks at major DOE sites. This is especially true given the small size of the EM Science Program relative to the scope of the DOE cleanup mission. The annual budget for the EM Science Program budget is on the order of $30 mi l l ion to $50 mi l l ion and is used to support basic research related to all aspects of the cleanup mis- sion. This is less than 0.1 percent of the total EM annual budget of $5.8 hi l l ion. Without a sign if icant i ncrease i n its budget, the EM Science pro- gram is unlikely to have a significant impact on DOE cleanup effective- ness and costs. Organizing Scheme Used in This Analysis The committee identified significant knowledge gaps and research needs through discussions and analyses of the "snapshot" of DOE's sub- surface contamination problems presented in Chapter 2. To organize this analysis and ensure its completeness, the committee developed the organizing scheme shown in Figure 5.1. This organizing scheme is O O O O O . . , . , . . , , ,, ~ , , ~ , . based partly on the approach used by the Subsurface contaminants Focus Area to organize its technology development programs (see Figure 3.2), but it also includes the data collection and analysis steps that provide the supporting information needed to make appropriate corrective action decisions.2 The committee's organizing scheme, here- after referred to as the framework for site remediation, is described briefly in the following paragraphs. Was discussed in Chapter 2, the major sites represent DOE's largest future mort- gages and longest-term commitments. 2The committee uses the term "corrective action" in the following discussion to refer to actions taken by DOE to address its subsurface contamination problems. A corrective action can range from no action in cases where the subsurface contami- nation is thought to pose minimal hazards to humans or the environment, or where remediation is infeasible, to aggressive actions to treat, remove, or contain contamination that poses significant hazards. As noted in Chapter 1, the term is sometimes used interchangeably with terms like "cleanup" and "remedial action," but it really encompasses a broader range of possible options for dealing with con- tamination, because it includes the no action (i.e., no cleanup or no remedial action) option. S U B S U R F A C E S C ~ E N C E

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6. Corrective Action A. Take no L | remedial action | characterize model behavior 1. : ~-1 2. Assess risk Validate performance of remedial action The boxes in Figure 5.1 represent each of the major steps in the remediation process, and the arrows represent decision and assessment points. Boxes 1 through 5 represent the process that could be followed to develop information to make an appropriate corrective action deci- sion. The initial step is focused on locating and characterizing the conta- minants of concern (Box 1~. This step involves determining the spatial distributions, types, amounts, and physical and chemical states of subsur- face contaminants, as well as the subsurface properties that affect con- taminant fate and transport behavior. Locating and characterizing con- tamination in the subsurface may be done using direct (e.g., drilling and sampling) and indirect (e.g., surface and borehole geophysical) techniques. The location and characterization data obtained in the first step are then used to develop a conceptual model of the site (Box 2), that is, a description of the subsurface as estimated from knowledge of the known site geology and hydrology and the physical, chemical, and bio- logical processes that govern contaminant behavior. The conceptual model provides a descriptive framework for assessing how the subsur- face system will behave with passing time and in response to potential corrective actions. As noted later in this discussion, the conceptual model is improved over time as more information on subsurface condi- tions and processes becomes available. The conceptual model provides a basis for constructing more quan- titative dynamic models that can be used to predict behavior (Box 3) of C h a p t e r 5 it{ I B. Contain & | | stabilize r C. In situ treat or transform | D. Remove | hotspots E. Remove contamination r Monitor FIGURE 5. 1 Framework for site remediation. 95

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the subsurface system over a specified time period. These predictive models are developed from mathematical representations of the con- ceptual model. In current practice, most predictive models are discrete representations of the physically continuous subsurface system and are typically solved with such numerical techniques as finite elements and finite difference.3 The parameters in these models represent the physi- cal, chemical, and biological characteristics at each point in the subsur- face. Parameters of interest in predictive models quantify the relation- ship between the driving forces (e.g., hydraulic gradient and chemical concentration gradient) and the resulting behavior (e.g., flow and trans- port). In the case of discrete models, the parameter values are meant to represent volume-averaged properties around each modeled point. The predicted system behavior is then compared to the observed behavior as measured in the field through monitoring activities (Box 4~. A feedback loop (Arrow 1 ) updates the conceptual and predictive mod- els when the behaviors do not match according to some specified mea- surets) of comparison. The process of testing the predictive model to determine whether it appropriately represents the system behavior of interest is usually referred to as model validation.4 Because of uncer- tainties in the model and data any match between predicted and observed behaviors is only possible in a statistical sense. Consequently, validation is best thought of as a process of confidence building through increased understanding of fundamental mechanisms in the underlying system rather than as a process to confirm or prove the cor- rectness of a model. The predictive model can be used to understand the present behav- ior of the subsurface system and to estimate future contaminant migra- tion to assess risk to human and environmental health (Box 5~. A cor- rective action decision (Box 6A-E) that will reduce risk to acceptable levels is then made using the information developed in the risk assess- ment. The corrective action can range from no action (Box 6A) to remove contamination (Box BE). During and following the corrective action, monitoring activities (Box 7) are again employed to assess the efficacy of that action. Long- term monitoring is usually required to confirm the effectiveness of, or to gain regulatory approval for, approaches that involve no action or con- tainment and stabilization. Inconsistencies between the measured and 3Continuous representations are sometimes used in analytical models for screening-level assessments. 41n model development protocol, a step referred to as model verification involves evaluating whether the numerical model solves the mathematical equa- tions of the conceptual model with acceptable accuracy. In this discussion, model verification is included as a step in the validation process. S U B S U R F A C E S C ~ E N C E 96

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predicted performance of the corrective action may indicate that the conceptual model of the system is deficient or that the parameters of the model are not sufficiently resolved, and it may be extremely diffi- cult to know which is the case. In these cases, there is a feedback loop (Arrow 2) to the conceptual model (Box 2) through the predictive model, which must be updated so that the corrective action decision process can be revisited. Although the framework for site remed iation shown i n Figu re 5.1 is presented as a linear process, it is in reality an observational procedure that follows both parallel and iterative paths. The framework may be tra- versed many times as new information is acquired and incorporated into the conceptual and predictive models and as corrective action per- formance is assessed. There is some correspondence between the organizing scheme out- lined in Figure 5.1 and the technology development organizing scheme shown in Figure 3.2. For example, the identify function in Figure 3.2 is roughly equivalent to the locate and characterize function in Figure 5.1. Similarly, the validate function in Figure 3.2 is roughly equivalent to the validate performance of remedial action function (Arrow 2) in Figure 5.1. The remaining functions in Figure 3.2 have no directly equivalent functions in Figure 5.1, and there are many functions in Figure 5.1 that are not represented at all in Figure 3.2 (e.g., the develop conceptual model and predict system behavior functions). The organizing scheme shown in Figure 5.1 is more complete than that given in Figure 3.2. Knowledge Gaps The committee identified significant knowledge gaps in the follow- ing process steps in the framework for site remediation shown in Figure 5.1: location and characterization of subsurface contaminants and characterization of the subsurface (Box 1~; conceptual modeling (Box 2~; containment and stabilization (Box 6B); and · monitoring and validation (Boxes 4 and 7 and Arrows 1 and 2~. These knowledge gaps do not include those associated with active remediation of subsurface contamination (Boxes 6C-6E), with the exception of remediation monitoring. This may come as a surprise to some readers, given that the current EM Science Program portfolio is heavily focused on this area (see the closing section of Chapter 3~. The C h a p t e r 5

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committee did not highlight knowledge gaps on these process steps, because subsurface contamination is highly distributed at many DOE sites, making cost-effective remediation infeasible, and because EM Science Program resources are limited and there is much work on these topics in other federal research programs (see Chapter 4~. Location and Characterization of Subsurface Contaminants and Characterization of the Subsurface An important conclusion that emerges from the committee's analysis of subsurface contamination problems in Chapter 2 is that the capabili- ties to locate and characterize subsurface contaminants at many DOE sites are incomplete. This conclusion is perhaps best supported by the following three examples from Chapter 2: subsurface radionuclide contamination in the 200 Area at Hanford; mixed contam and contaminant plumes and hot spots in waste burial grounds at the Savannah River Site. inant plumes at Test Area North at the Idaho Site; Locating contamination in the subsurface at DOE sites has focused on three interrelated approaches: (1 ~ information derived from h istorical operations and records; (2) direct observations of contamination on the surface, in surface water, and in boreholes; and (3) indirect geochemi- cal and geophysical measurements from the surface and in boreholes. These three sources of information have been used at some sites to develop predictive models of contaminant movement in the subsurface and the predictive models have been tested by further direct observa- tions and measurements. Frequently, these models have not captured the essential behavior of the contaminant, either in direction or speed of movement. The challenges of locating subsurface contamination are magnified by the wide range of contaminant types (e.g., mixtures of organic sol- vents, metals, and radionuclides) in the subsurface at many DOE sites (see Chapter 2~; the wide variety of geological and hydrological condi- tions across the DOE complex (see Table 2.2~; and the wide range of spatial resolutions at which this contamination must be located and characterized, ranging from widely dispersed contamination in ground- water plumes to small isolated hot spots in waste burial grounds. Moreover, because contaminant migration involves dynamic transport processes, continuous temporal information on contaminant locations is required. In effect, location, characterization, and continuing moni- S U B S U R F A C E S C ~ E N C E 98

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taring efforts must be integrated to assure an adequate database for planning and implementing appropriate corrective actions. Fundamental advances in capabilities to locate and characterize subsurface contamination and important subsurface properties will help DOE better assess the potential hazards of its contamination problems and to design and implement appropriate corrective action strategies (e.g., see Sidebar 5.1~. Moreover, research on subsurface heterogeneity in geology, geochemistry, hydrology, and microbiology will provide a framework for assessing the fate and transport of contaminants. Examples of significant knowledge gaps include the following: · Locating contaminants in the subsurface. At many sites, the points of entry of contaminants into the subsurface (e.g., through a leaking waste burial ground or injection well) are at least approximately known. However, the determination of the spatial distributions of contaminants (that may or may not change with time) once they enter the subsurface remains a major knowledge gap. Currently available indirect measurement methods (e.g., geophysical methods) are inadequate for locating most types of contaminants in the subsurface, and direct methods such as drilling are both expensive and limited in effectiveness, because they only provide samples from specific points in the subsurface along the borehole. Moreover, boreholes provide potential con- taminant transport pathways through the subsurface. · Characterizing contaminants in the subsurface. Once contami- nants enter the subsurface, they can act as long-term sources of pollution to ground or surface water. Understanding how to characterize the concentrations, speciations, and release rates of contaminants in the subsurface is a significant knowledge gap across the DOE complex. In general, there are poor records of contaminant discharges to the subsurface, so contaminant quan- tities are highly uncertain. Moreover, once contaminants enter the subsurface they can move long distances, either diffusing through the fluid medium or migrating as a distinct plume, lead- ing to contaminant distributions that are variable in size, shape, and concentration. Currently available direct and indirect observing technologies5 have limited effectiveness for character- 5Direct observing technologies allow in situ measurements or samples to be obtained (e.g., by drilling). Indirect observing technologies allow measurements to be made remotely (e.g., through geophysical measurements of the subsurface). The terms "invasive" and "noninvasive" are sometimes used synonymously, but this usage is not strictly correct. Indirect measurements can be obtained through inva- C h a p t e r 5 99

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. . izing site conditions and defining the extent and concentrations of contaminant bodies. Characterizing physical, chemical, and biological properties of the subsurface, including improved approaches to understanding the properties of the geologic system and relating them to conta- minant fate and transport. The subsurface characteristics at a site place fundamental controls on contaminant fate and transport behavior. Subsurface characteristics also govern the selection of conceptual and predictive models as well as the application and effectiveness of appropriate corrective actions. The knowledge gaps include understanding which characteristics control fate and transport behavior in the subsurface and also understanding how those characteristics can be measured at the appropriate scales over large subsurface volumes, using both indirect and direct techniques. The integration of direct measurements of sub- surface geologic properties with indirect measurements (e.g., from geophysical methods) has been used very successfully in the petroleum industry to develop conceptual and quantitative models of subsurface transport. Such methods are potentially applicable to DOE sites. Characterizing highly heterogeneous systems. This knowledge gap is a special case of the previous knowledge gap and is a sig- nificant problem at many DOE sites, which are very large in spa- tial extent and exhibit intra- and inter-site variations in geologic and hydrologic conditions (see Chapter 2~. Heterogeneity arises from the spatial variability in geological, chemical, and biologi- cal properties of the subsurface. A fundamental understanding of these properties, and especially the geological framework, is a necessary prerequisite to understanding the fate and transport of contaminants. Heterogeneity may occur at several spatial scales in complex subsurface systems, but they may control contami- nant fate and transport processes only at one or a few scales. The primary knowledge gaps are in understanding the heterogeneity scales that govern these processes, how to characterize this het- erogeneity without having to perform an exhaustive characteriza- tion of the subsurface, and how to represent this heterogeneity in mathematical formulations. Research Needs In the committee's judgment, basic research can support the devel- opment of new and improved capabilities to locate and characterize sive means, as when borehole geophysical methods are employed to obtain sub- surface measurements. S U B S U R F A C E S C ~ E N C E 100

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contamination in the subsurface, and also to characterize subsurface properties at the scales that control contaminant fate and transport behavior. Development of the following capabilities is especially needed: Improved capabilities for characterizing the physical, chemical, and biological properties of the subsurface. These approaches should provide information on the following system properties and behaviors at the spatial and temporal scales that control contaminant fate and transport behavior: · contaminant locations and characteristics: · transport pathways; · subsurface properties and boundary conditions that control contaminant fate and transport behavior; and · physical, chemical, and biological interactions between con- taminants and earth materials. SIDEBAR 5.1 NEW APPROACHES FOR DIRECT OBSERVING The major limitations on direct observations by conventional drilling and sampling have been high costs and concerns that direct approaches may unwittingly exacerbate the spread of contaminants in the subsurface.The use of reduced diameter driliholes (using 4- to 6-inch diameter drills) as a cost-sav- ing method has been explored widely in the petroleum industry, but cost reductions have not been encouraging. However, recent developments in miniaturized drilling and sampling technologies (e.g., Albright and Dreesen, 2000) hold promise for significantly reducing drilling costs and reducing the potential for contaminant spread when these technologies are used at DOE sites. A new technology, microdrilling, represents the kinds of advanced capabilities made possible by basic scientific and engineering research.This technology uses coiled tubing, steerable miniature-diameter (1 3/8 inches to 2 inches [3.5 centimeters to 5.1 centimeters]) down-hole motors, and down-hole micro- instrumentation to obtain in situ measurements and samples of contaminated subsurface environ- ments. Additionally, smaller diameter holes reduce contaminant migration potential and promote more effective sealing. The depth capabilities thus far demonstrated are adequate for almost all of the major DOE sites (down to about 300 meters, or about 1,000 feet). Many aspects of this microborehole technology still require extensive research and development, including work on sampling techniques, down-hole instrumenta- tion for diverse measurements, and effective plugging; however, enough feasibility demonstrations have been completed to indicate great promise for use at DOE and other contaminated sites. Albright and Dreesen (2000) suggest that this technology may cut drilling costs by at least 70 percent compared to conventional technologies.They also suggest that much greater cost savings are possible as these techniques are refined. C h a p t e r 5 101

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Research on indirect observations could involve the develop- ment of new approaches for measuring contaminant and subsur- face properties (e.g., approaches utilizing "unconventional" geo- physical wave attributes such as polarized and nonlinear wave responses) or new ways of interpreting "conventional" observa- tional data to obtain information on the system properties of interest. For direct observations, the research must also address how the observing process changes the system being measured. Approaches for making direct and indirect observations in the unsaturated zone are especially needed. 2. Improved capabilities for characterizing physical, chemical, and biological heterogeneity, especially at the scales that control contaminant fate and transport behavior. Approaches that allow measurements or estimates of heterogeneity features to be obtained directly (i.e., without having to perform a detailed char- acterization of the subsurface) are especially needed. 3. Improved capabilities for measuring contaminant migration and the system properties that control contaminant movement. 4. Methods to integrate data collected at different spatial and tem- poral scales to better estimate contaminant and subsurface prop- erties and processes, and also methods to integrate such data into conceptual models. Conceptual Modeling As shown by several examples in Chapter 2, DOE is finding subsur- face contamination in unexpected places: . Technetium was discovered in groundwater beneath the SX Tank Farm in the 200 Area at the Hanford Site. · Plutonium was discovered in colloids in groundwater near the Benham Test at the Nevada Test Site. Plutonium was discovered in groundwater beneath the Radioactive Waste Management Complex at the Idaho Site. . These discoveries were "unexpected" because models of the subsur- tace at these sites did not predict them (e.g., see Sidebar 2.6~. Concep- tual and predictive models have been developed for subsurface conta- minant fate and transport for many DOE sites, but in many cases these models have proven ineffective for understanding and predicting conta- minant movement, especially at sites that have thick unsaturated zones or complex subsurface characteristics. The conceptual model "problem" has many possible causes. The models themselves may be deficient because they were developed S U B S U R F A C E S C ~ E N C E 102

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using insufficient data on subsurface characteristics, contaminant distri- butions, or transport processes, or the models may simply have an inap- propriate theoretical basis. Good conceptual models must be grounded in sound theory and underpinned with sound and sufficient data. In the committee's judgment, at least part of the problem is that conceptual model development is not viewed as an explicit part of remediation practice. Consequently, there are few standardized tools or accepted methodologies for developing such models, which has led to ad hoc and inconsistent approaches across DOE sites. Accurate conceptualizations are essential for understanding the long-term fate of contaminants in the subsurface and the selection and application of appropriate corrective actions. The significant knowledge gaps include the following: . · Contaminant fate and transport. Understanding the factors con- trolling the long-term fate of contaminants in the subsurface is important for assessing the potential for human and ecological exposure and for selecting appropriate corrective actions. Understanding the dominant contaminant transport processes and pathways through the subsurface remains a significant knowledge gap for building accurate and useful conceptual and predictive models. The simplest formu ration of contaminant transport uses porous media flow of a dissolved phase, but such transport may be the exception at many DOE sites, where trans- port can occur in several distinct manners (e.g., colloidal trans- port) through both porous media and fractures and may involve a variety of chemical and biological reactions. The myriad chem- ical, biological, and physical processes operating in the subsur- face operate at different time scales and are poorly understood, especial Iy for metals and radionucl ides. Coupling physical, chemical, and biological processes. The physi Cal, chemical, and biological properties and processes that gov- ern contaminant fate and transport do not act independently. Rather, they interact (i.e., they are coupled) in complex and often poorly understood ways. Many coupled processes operate over very small spatial scales that are defined by a distribution of prop- erties, making it difficult to incorporate representations of these processes into conceptual and mathematical models. For exam- ple, redox potential and pH (chemical properties related to bulk mineralogy, biological activity, and fluid composition) can affect either or both physisorption and chemisorption of contaminants onto solid phases. The heterogeneous distribution of permeability (a physical property related to the geological characteristics of the C h a p t e r 5 103

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subsurface) can result in highly variable rates of fluid flow (a physical process). These processes combine to effect transport (a coupled process) of certain metals and radionuclides over small spatial scales. Similarly, the coupling of biomass availability (a property with biological, physical, and chemical components) and substrate availability (controlled by processes such as sorp- tion, dissolution, and transport) with the distribution of electron acceptors (also possessing biological, physical, and chemical . . ~ . controls) can result in spatially variable rates of in situ contami- nant biodegradation (a coupled process). The coupling of process- es and their control by subsurface properties are only beginning to be understood. Moreover, little progress has been made on how to represent coupled processes in predictive models. Mode/ parameter development. Model parameters are well understood and definable for very simple homogeneous subsur- face systems. However, in highly complex subsurface systems, parameter definition may require unobtainable amounts of detailed characterization data. In these cases, it is important to understand which processes are actually dominating the behav- ior of the system and to define parameters appropriate to those processes. Determ i n i ng how to make the appropriate si mpl if ica- tions and approximations is the main thrust of conceptual mod- eling research that leads to the identification of appropriate model parameters. The definition and estimation of model parameters requires a good understanding of the subsurface system and transport processes being modeled, which is not often the case at DOE sites. For example, the tra- ditional approach for modeling porous media is to choose permeability as a model parameter. If the porous medium is highly heterogeneous (e.g., if it contains a few large and interconnected fractures) then the generalized concept of permeability is not well defined, and permeabil- ity may not be an appropriate characterization of the physical system. Flow and transport may be dominated by the fracture system, and the model parameters should represent the properties of these permeable and connected pathways. Similarly, for fate and transport models, the traditional approach is to assume equilibrium sorption and use the equilibrium partition coefficient as a model parameter. If the sorption reactions are not at equilibrium, however, then the equilibrium partition coefficient by itself is not an appropriate parameter, and additional parameters describing mass transfer kinetics must also be included. The challenge is to define the right conceptualization of the physical, chem- ical, or biological processes that dominate system behavior, which in S U B S U R F A C E S C ~ E N C E 104

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turn defines the appropriate model parameters to be used. The field observations used to develop parameter estimates are made at many different scales and times and provide information about differ- ent properties of the subsurface system. Samples from drillhole core, for example, can provide detailed information on the physical, chemical, and biological properties of the subsurface at small (centimeter) spatial scales. Borehole testing data (e.g., hydraulic pumping tests and tracer tests) and indirect observations (e.g., seismic surveys) provide indirect measurements of subsurface properties averaged over much larger (meters to tens of meters) spatial scales. Observations of a given sub- surface region using different measurement techniques can yield very different results, and measurements from a single technique can show significant variations over small spatial scales. One of the primary knowl- edge gaps for model conceptualizations is understanding how to inte- grate these field observations into the models and parameter estimates. The knowledge gaps include understanding the scale effects and devel- oping methods for data integration that take these effects into account. Research Needs Conceptual model development has not been an explicit topic for basic research in its own right. Indeed, conceptual model development is viewed as an inherently empirical and site-specific process using observational approaches that are not easily generalized or tested. The committee believes, however, that basic research that addresses the fun- damental approaches and assumptions underlying conceptual model development could produce a tool box of methodologies that are applicable to contaminated sites both inside and outside the DOE com- plex. This research should focus on the following topics: New observational and experimental approaches and tools for developing conceptual models that apply to complex subsurface environments, including such phenomena as colloidal transport and biologic activity. 2. New approaches for incorporating geological, hydrological, chemical, and biological subsurface heterogeneity into concep- tual model formulations at scales that dominate flow and trans- port behavior. 3. Development of coupled-process models through experimental studies at variable scales and complexities that account for the interacting physical, chemical, and biological processes that gov- ern contaminant fate and transport behavior. 4. Methods to integrate process knowledge from small-scale tests and observations into model formulations, including methods for C h a p t e r 5 105

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incorporating qualitative geological information from surface and near-surface observations into conceptual model formulations. 5. Methods to measure and predict the scale dependency of para- meter values. 6. Approaches for establishing bounds on the accuracy of parame- ters and conceptual model estimates from field and experimental data. The research needs outlined above call for more hypothesis-driven experimental approaches that address the fundamental methods and assumptions underlying the development of conceptual models. This research will require expertise from a wide range of disciplines and must be conducted at scales ranging from the laboratory bench top to contaminated field sites. Moreover, to have long-term relevance to the DOE cleanup mission, this research must be focused on the kinds of subsurface environments and contamination problems commonly encountered at major DOE sites. One way to ensure this focus is to give researchers the opportuni- ty to conduct research at contaminated DOE sites. The committee pro- vides additional comments on this issue in the next chapter.6 Containment antl Stabilization As noted by DOE in Paths to Closure (DOE, 1 998a) and as shown in Chapter 2 of this report, a great deal of subsurface contamination is likely to remain at DOE sites even after DOE's cleanup program is com- pleted. It will include contaminant plumes in groundwater, contaminat- ed soil, and waste burial grounds both the historical burial grounds discussed in Chapter 2 and new burial grounds developed by DOE to dispose of waste from its current and future cleanup operations. DOE is responsible for the long-term management of this contamination and must develop methods to contain and stabilize it until it no longer poses a hazard to humans or the environment or until new methods to remed late th is contami nation are developed. DOE's management commitment potentially extends for many thousands of years. DOE's containment and stabilization systems are likely to include surface caps, subsurface barriers, and other in situ stabilization systems. Once installed, these systems will have to be monitored to assure that they perform as expected, and if these systems fail, additional corrective actions may have to be taken to repair the barriers and remediate resid- ual contamination. There has been an increasing emphasis and accep- 6See the section titled "Field Sites" in Chapter 6. S U B S U R F A C E S C ~ E N C E 106

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tance of waste contai n ment and stabi I ization i n recent years, both i n DOE and by regulatory agencies. Decreasing cleanup budgets, evalua- tions that show that containment is a low-risk choice for some prob- lems, and recognition that some contamination cannot be remediated either with current technologies or conceivable new technologies are responsible for this change in phi losophy. This shift in emphasis is per- haps first fully acknowledged by DOE in Paths to Closure (DOE, 1 998a), which lays out DOE's cleanup objectives, and appears to be a developing trend across the DOE complex.7 A more recent DOE report (DOE, 1 999) discusses the long-term stewardship chal lenges. At some sites, containment and stabilization may be an interim measu re and has its own set of associated techn ical problems. These include particularly the availability of appropriate technologies to both contain and stabilize the residual contamination and to monitor and validate the long-term performance of containment and stabilization systems themselves. There is little understanding of the long-term per- formance of containment and stabilization systems, and there is a gen- eral absence of effective methods to validate that such systems are properly installed or that they can provide effective long-term perfor- mance. To address this knowledge gap, advances in basic knowledge to support the development of new and improved waste containment and stabilization systems will be needed, as noted below. The development of improved and novel containment and stabiliza- tion approaches will likely have the highest potential for cost savings and lowered risk of the four knowledge gaps identified by the commit- tee. The committee believes that the significant knowledge gaps include the following: · Development of robust physical, chemical, and biological con- tainment and stabilization systems. Trad itional contai n ment sys- tems comprised of surface caps, in situ walls, and bottom barri- ers employ low-permeability materials to reduce water infiltra- tion and provide a barrier to contaminant migration. When designed properly, these systems may provide effective contain- 7Another recent example of the shift in emphasis to containment strategies can be found in a recent report on disposal of DOE low-level waste (DOE, 1 998e). This report shows that DOE's estimates of the volume of its low-level waste requir- ing disposal between 1998 and 2070 has decreased from about 32 million cubic meters to about 8 million cubic meters, largely because DOE has decided to con- tain much of this low-level waste in place at its sites, rather than removing it for treatment or disposal elsewhere in the complex. Most of this waste exists in waste burial grounds at the major DOE sites (see Chapter 2). C h a p t e r 5 107

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ment for periods of up to a few decades,8 but current designs do not meet DOE's needs for containment of its long-lived radioac- tive and hazardous waste both for wastes contained in place and new waste sites developed from current and future cleanup operations. Natural low-permeability materials for minimizing infiltration (e.g., clays) work well in humid environments, but they may not be effective in arid regions, where dessication can lead to the development of preferred pathways. To the committee's knowledge, there has been little or no research or development work on longer-term systems for con- tainment of subsurface contamination of the sort encountered at DOE sites, either by DOE or by other organizations.9 The knowledge gaps include understanding how to design more effective and permanent barrier systems for long-term contain- ment, especially in arid environments characteristic of the west- ern DOE sites, including the development and application of more durable materials for barrier systems materials that are compatible with the surrounding environment and with the waste that is being contained. New containment approaches. Conventional barrier systems seek to m i n i m ize water i nfi Itration i nto the contai ned waste and to minimize the spread of waste from containment zones into the environment. Surface barrier systems (caps) have proven very . effective for retarding water infi Itration into containment zones, but they require ongoing maintenance to ensure their continued integrity, and they have short lives relative to the hazard of the contained waste. Moreover, subsurface infi Itration barriers (e.g., impermeable walls installed around or beneath waste burial grounds) are extremely difficult to install and maintain, especial- ly barriers emplaced beneath waste containment zones, and their performance is also extremely difficult to monitor. New approaches are needed to address DOE's needs for long-term in situ containment and treatment of subsurface conta- mination. The recent development of reactive barriers (i.e., barri- ers that degrade or immobilize contaminants through geochemi- cally and biochemically mediated reactions, such as ion To the committee's knowledge, this supposition has never been tested at a DOE site, so the actual longevity of such barrier systems is uncertain at best. 9There has been a great deal of research and development work in the United States and other countries on long-term containment systems for spent fuel and vitrified high-level waste, but this work does not appear to be directly applicable to the contamination problems at DOE sites. S U B S U R F A C E S C ~ E N C E 108

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exchange or redox processes) is an example of the kind of new approach that holds promise. The continued development of reactive barriers and the development of other hybrid systems (e.g., barrier systems that incorporate biological materials to reduce maintenance requirements and enhance long-term per- formance, or systems that use controlled water infiltration to en hance waste decomposition or transformation) cou Id i mp rove the technology for containment and in-situ stabilization of sub- surface contaminants across the DOE complex. Research Needs The construction of stabilization and containment systems is proper- ly within the province of applied technology development and will be the responsibility of other DOE programs (e.g., the Subsurface Contami- nants Focus Area). However, basic research focused on the following tonics will be needed to support this technology development effort: The mechanisms and kinetics of chemically and biologically mediated reactions that can be applied to new stabilization and containment approaches (e.g., reactions that can extend the use of reactive barriers to a greater range of contaminant types found at DOE sites) or that can be used to understand the long-term reversibi I ity of chemical and biological stabi I ization methods. 2. The physical, chemical, and biological reactions that occur among contaminants (metals, radionuclides, and organics), soils, and barri er components so that more compatible and durable materials for containment and stabilization systems can be developed. 3. The fluid transport behavior in conventional barrier systems, for example, understanding water infiltration into layered systems, including infiltration under partially saturated conditions and under the influences of capillary, chemical, electrical, and ther- mal gradients that can be used to support the design of more effective infiltration barrier systems. 4. The development of methods for assessing the long-term durabil- ity of containment and stabilization systems. Monitoring and Validation The abi I ity to man itor and val idate is essential to the successfu I application of any corrective action to a subsurface contamination problem, as is regulatory acceptance of that action. However, the knowledge and technology bases to support these activities are not fully developed and are receiving little attention in EM's science and tech- nology programs. The monitor process step does not appear on the C h a p t e r 5 109

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Subsurface Contaminants Focus Area's remedial action flow chart (see Figure 3.2), and its validate process step applies only to the confirma- tion of the performance of a remedial action. As noted in Chapter 3, very little research relevant to these activities is being supported cur- rently by the EM Science Program. As illustrated by Figure 5.1, monitoring and validation are important at both the front and back ends of the site remediation process. At the front end, monitoring and validation are used to support the develop- ment of conceptual and predictive models of subsurface and contami- nant behavior (Box 4 and Arrow 1~. At the back end, monitoring and validation are used to gain regulatory acceptance for corrective actions and to demonstrate the effectiveness of efforts to remove, treat, or espe- cially to contain contamination (Box 7 and Arrow 2~. Such monitoring and validation efforts can also improve the understanding of the conta- minant fate and transport processes and can be used to recalibrate and revise conceptual and predictive models important elements of the model bu i Id i ng process. Improvements in capabilities to monitor and validate could greatly improve the technical success of DOE's efforts to contain and stabilize contamination at its sites. The development of new containment and stabi I Cation approaches cou Id lower the cost, accelerate regu latory approvals for, and increase public confidence in efforts to address DOE contamination problems. In the committee's judgment, the significant knowledge gaps include the following: . . Design of efficient and effective monitoring systems. There is I it- tle experience with monitoring over the long (decadal to centen- nial) time scales that are required at DOE sites. Consequently, a great deal of basic knowledge is required to design efficient and effective monitoring systems. The knowledge gaps include under- standing what parameters need to be measured to assess system performance (e.g., the performance of a subsurface barrier); where, when, and how to obtain these measurements; and how to relate these measurements to system behavior. Unsaturated zone monitoring. Mon itori ng of the u nsatu rated zone is a special case of the previous knowledge gap and is a special need for DOE, because most of its containment and sta- bilization systems are being constructed above the water table, especially at the western U.S. sites. Unsaturated zone monitoring is an especially difficult problem; the physics and chemistry of unsaturated zone processes are more complicated than for the saturated zone, and these processes have received far less atten- tion from researchers. Contaminants may be present in both ~ . . . . . S U B S U R F A C E S C ~ E N C E

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liquid and gas phases in unsaturated zone environments and under both aerobic and anaerobic conditions. The exchange, degree of equilibration of these phases, and the transport of these phases may occur by different processes with very different rates. There is a great disparity between what can currently be measured and what needs to be measured to predict the behav- ior of contam i n ants i n many u nsatu rated setti ngs. · Mode/ validation. A conceptual model is an estimate of the real- world behavior and must be tested to ensure that it appropriately represents the behaviors of interest. This testing is usually carried out by comparing predictions made with the model against field and experimental observations. This testing also allows the model to be improved as new information on the subsurface sys- tem is collected. The science of model testing, or validation, has received relatively little attention until recently and is an area where significant work is needed. The knowledge gaps include understanding what measurements need to be collected to vali- date a model (it is frequently the case that what can be calculat- ed in a model cannot be measured in the field, and vice versa); how to evaluate the relationships between measured and pre- dicted behaviors; and understanding what diagnostic information these differences provide for assessing and improving the accura- cy of the models (e.g., see Sidebar 5.2~. · Performance validation. Performance validation is a necessary step to document the success, or lack thereof, with every step shown in Figure 5.1 . The issues here are simi lar to those for model validation, that is, how to assess whether the process is performing as designed. The knowledge gaps include under- standing what to measure, how to measure it, how to assess dis- crepancies between designed and measured behavior, and deter- mining what diagnostic information these differences provide for assessing and improving performance. For example, with regard to locating and characterizing con- taminants, one must determine when enough information for risk characterization and remedy selection has been gathered. Th is requires tools to validate the assessments of contaminant amounts, distributions, and mass release rates. Similar considera- tions arise for validation of predictive models in the face of vari- ability and uncertainty. The difficulty increases when probability models are introduced to try to deal with uncertainty. With regard to corrective action performance, validation is an essen- tial step that is lacking for many innovative technologies, and has prevented their selection for site remediation because of regula- C h a p t e r 5 111

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tory and stakeholder concerns. Knowledge gaps in performance validation include understanding how to develop monitoring sys- tems and sampling strategies, understanding the critical system variables that need to be used, strategies for data collection in highly heterogeneous systems, and the development of statistical methods to be used in performance evaluation. Research Needs Many of the research needs for monitoring and validation have been covered in previous sections; for example, research on locating conta- minants and characterizing contaminant and subsurface properties and research on data integration will provide new knowledge and capabili ties for monitoring and validation. In addition, the committee believes that basic research is needed on the following topics: . . . Development of methods for designing monitoring systems to detect both the current conditions and changes in system behav- iors. These methods may involve the application of conceptual, mathematical, and statistical models to determine the types and locations of observation systems and also will involve predicting the spatial and temporal resolutions at which observations need to be made. For example, such methods may help to determine what types of measurements (e.g., core samples from a borehole versus seismic images of the subsurface) can be used to validate the model and also suggest where such measurements should be made in both time and space. Development of validation processes. The research questions include (1 ) understanding what a representation of system behavior means and how to judge when a model provides an accurate representation of a system behavior the model may give the right answers for the wrong reasons and thus may not be a good predictive tool; and (2) how to validate the future perfor- mance of the model or system behavior based on present-day measurements. These questions might be addressed through research projects that focus on the development of validation methodologies using real-world examples at DOE sites. Data for model validation. Determining the key measurements that are required to validate models and system behaviors, the spatial and temporal resolutions at which such measurements must be obtained, and the extent to which surrogate data (e.g., data from lab-scale testing facilities) can be used in validation efforts. · Research to support the development of methods to monitor fluid and gaseous fluxes through the unsaturated zone, and for differ- S U B S U R F A C E S C ~ E N C E 112

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entiating diurnal and seasonal changes from longer-term secular changes. These methods may involve both direct (e.g., in situ sen- sors) and indirect (e.g., using plants and animals) measurements over long time periods, particularly for harsh chemical environ- ments characteristic of some DOE sites. This research should sup- port the development of both the physical instrumentation and measurement techniques. The latter includes measurement strate- gies and data analysis (including statistical) approaches. ·eeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeee SIDEBAR5.2 MANAGING UNCERTAINTY Management of uncertainty in model and performance validation is a theme that cuts across many of the knowledge gaps identified in this chapter. Uncertainties arise in multiple ways. In field data they can emerge in quality features: random measurement error, systematic errors from imperfectly cali- brated instruments, and recording and other transmission errors. In mathematical models, uncertain- ties stem from incorrect specifications and through propagation of errors in the data that are input to the computational models. In the integration (or combination) of models and data, uncertainties are affected by the need to link data and models that are on mismatched scales; some data may have to be aggregated, other data may need to be disaggregated. Quantifying the uncertainties in, for example, a site characterization problem can involve all the paths described above.There may be several data sets of varying quality; missing data (measurements on some contaminants may be found at some monitoring wells but missing at others); auxiliary data sets (e.g., river flow data) on time scales very different from the frequency of sampled monitoring data; his- torical records of differing content and quality; and transport models requiring uncertain input para- meters. How best to combine the variety of information and assess the accuracy of results and predic- tions is a great challenge. Similar issues are found in validation and performance assessment.These may be compounded by the need to perform detailed computer experiments to determine the impacts of uncertainties in data quality and input specifications. For perfomance assessment and validation, attention has to be given to design of future data collection: Where and when should collection be done to assure a desired level of accuracy? The daunting technical problem is how to respond to complex, though simple sounding, queries (e.g., Where is the contaminant plume now? Where will it be next year?) that demand intricate combinations of computer and statistical models fed by several data sources. Powerful methods such as Bayesian hierarchical modeling are emerging to break such complicated problems into components and, through intensive computation, capture the uncertainties; but implementation is limited by the com- plexity and scale of the problems typically encountered in subsurface contamination. C h a p t e r 5 113

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C ~scuss~on . As noted in the introduction to this chapter, the committee has been selective in the identification of subsurface contamination knowledge gaps and research needs for the EM Science Program. Indeed, the list of knowledge gaps presented in this chapter is not exhaustive and is per- haps notable for what it does not include, namely, the knowledge gaps associated with assessment of risk (Box 5 in Figure 5.1~° and many of the corrective actions associated with EM's cleanup program (Boxes 6C through BE in Figure 5.1~. The committee has been selective because (1 ) it believes that much of the subsurface at DOE sites cannot be reme- diated cost effectively; (2) the contamination is highly distributed in very large volumes of the subsurface; and (3) the EM Science Program does not have the management or financial capital to support a com- prehensive research program to address all of EM's cleanup problems. Further, the committee recognizes that there is much good research on these excluded topics being supported by other programs (see Chapter 4~. The committee has selected the four research areas highlighted in this chapter because, as illustrated by the examples in Chapter 2, these themes cut across all DOE cleanup efforts, and the committee believes that they are key to the long-term success of the DOE's cleanup pro- gram. Further, the committee believes that a focused, sustained, and adeauatelv funded research Program directed at the knowledge Baas ~~ ~ - ~ - r -o ~ - ----- lo-- - - -- --a- o~r- could result both in significant improvements to L9OE cleanup capabili- ties and the effectiveness of its cleanup actions. The committee discussed whether it should prioritize these four research areas, but decided against doing so. The selection of these four research foci from among a much broader range of potential research areas is in itself a significant prioritization. Further, the committee believes that all four research foci are equally important for DOE's need to be pursued aggressively if DOE is to improve its capabilities to address its subsurface contamination prob- lems. The new location, characterization, modeling, and monitoring capabi I ities that can resu It from th is research, when appl fed appropri- ately, will enable DOE to stay on a track that leads to success in its efforts to clean up or contain its widespread subsurface contamination. cleanup mission and wil I 4°Of course, the committee recognizes that the basic research needs outlined in this chapter will produce new knowledge on contaminant locations and behavior and thereby affect critical steps in the risk assessment. S U B S U R F A C E S C I E N C E