Ground Water Models Scientific and Regulatory Applications (1990) / Chapter Skim
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6 ISSUES IN THE DEVELOPMENT AND USE OF MODELS
6 ISSUES IN THE DEVELOPMENT AND USE OF MODELS
Pages 211-248
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From page 211... ...
and the Environmental Protection Agency (EPA) , are particularly concerned with ground water modeling to support many of their regulatory activities.
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From page 212... ...
and which code to use is often left to the discretion of the contractor who was hired by EPA or a potentially responsible party (International Ground Water Modeling Center, 1986~; ~ there is limited understanding among EPA staff concerning which models are available (International Ground Water Modeling Center, 1986~; , there is inadequate expertise within federal and state regulatory agencies to apply such models (Office of Technology Assessment, 1982~; the validity of some codes for the problem to which they are applied has not been established (Office of Technology Assessment, 1982~; ~ EPA enforcement offices strongly discourage the use of proprietary models (International Ground Water Modeling Center, 1986; Office of Technology Assessment, 1982~; ~ there is inadequate quality assurance, quality control, and peer review (Office of Technology Assessment, 1982~; and ~ there is a reluctance to use models if their use would be considered controversial (Office of Technology Assessment, 1982~. The committee's review confirmed most of these findings.
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From page 213... ...
Most states possess even more limited capabilities (Council of State Governments, 1985; Environmental Protection Agency, 1987; General Accounting Office, 1987; International Ground Water Modeling Center, 1986~. The substantial increase in the need for site-specific regulatory decisions in all the EPA programs concerned with regulating ground water can only exacerbate the breadth and depth of these shortages and critical neecis.
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From page 214... ...
Faced with the problem of an overall lack of qualified staff to use models and interpret results, regulatory agencies have a natural tendency toward simplification through the use of standard models and worst-case assumptions, as is done in the hazardous waste delisting program (Environmental Protection Agency, 1987; International Ground Water Modeling Center, 1986~. This decision is motivated by a concern about the lack of adequate resources and a preference for using overprotective assumptions.
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The use of overly simplistic models, such as the vertical-horizontal spread (VHS) model, at Superfund sites or other hazardous waste sites (1)
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prediction agrees with the behavior of this true system. Therefore the reference in discussing and/or assessing the accuracy of the modeling process is this real system, indicated by the top path of Figure 6.1.
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The following sections use this conceptual mode} to describe the major sources of uncertainty in the modeling process. The Sampling Process One can observe the real world only via a sampling process.
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Published field data have typically been taken at face value and have been freely extrapolated and generalized beyond their original purpose. This situation has begun to change, partly as a result of the demanding requirements of hazardous waste studies and partly because modelers are beginning to
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From page 219... ...
This basic fact needs to be recognized in any realistic assessment of the prediction capabilities of ground water models. Generally speaking, the field data used to estimate the inputs and check the predictions of ground water flow models are compiled from historical hydrogeologic surveys that were not planned with modeling in mind.
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From page 220... ...
The field data used in contaminant transport models typically have a very different history from those used in flow models. Most contaminant concentration measurements are collected at or near a contaminate site after an indication that some problem exists (e.g., observations of unusual taste or odor in well water)
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lack of knowledge about the processes that control contaminant transport and transformation at a particular site and (2) incomplete knowledge of the spatially and temporally variable environmental factors that influence these processes.
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Although intentional or afterthe-fact tracer analyses can be used to estimate macroscopic dispersivities, it is also possible to derive these macrodispersivities from theoretical analyses that recognize the variable nature of the smallscale flow field (Dagan, 1984; Gelhar and Axness, 1983; Neuman et al., 1987~. This is an important and somewhat controversial issue, which at least deserves consideration when designing a field sampling program.
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From page 223... ...
inputs. Input estimation and validation, the second phase of a modeloriented field sampling program, presume that the processes included in the mode} are, in fact, the ones that control contaminant behavior at the site of interest.
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of the mode! should reflect field sampling constraints, and the sampling program should be designed to serve the model.
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The process of selecting appropriate input values is termed "input estimation." Many of the coefficients and input variables included in ground water models must be estimated on a case-by-case basis, usually from a relatively limited number of field observations of related quantities. Input estimation is one of the most difficult, and often most frustrating, aspects of ground water modeling.
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Most ground water models include forcing terms, which account for sources and sinks of water or dissolved contaminants. Flow models typically include pumping and recharge terms, whereas transport moclels typically include terms that describe where and when contaminants are introduced into the subsurface environment.
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Similar remarks apply to initial conditions, which can be important in transient simulations. The traditional approach to ground water input estimation, developed largely in water resource investigations of large aquifers, focuses on constitutive parameters such as hydraulic conductivity and dispersivity.
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In the future, it is likely that automated inverse estimation algorithms will be included as part of the modeling packages distributed for general use by practicing hydrogeologists. The measurements used to estimate both constitutive parameters and auxiliary conditions are typically obtained at discrete times and locations (usually at monitoring welis)
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The results of a ground water input estimation depend greatly on which inputs are based on field data and which are assumed to be well known. If, for example, a velocity used in a transport mode!
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If the subsurface environment is very heterogeneous, measurements are very limited, or the mode} is improperly formulated, it is unlikely that the estimation process will be able, by itself, to ensure accurate predictions. The effort devoted to input estimation, and the sophistication of the estimation procedure, should be judged in a larger context that includes data collection and mode} formulation.
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Instead, mode! parameters are adjusted until a "reasonable" fit is oW tained and the result is presented as a "validated model." Modelers practically never declare their models to be "invalidated," primarily because ground water models nearly always have enough adjustable parameters to fit a limited set of field observations.
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. A Monte Cario analysis teased on Figure 4.1 essentially repeats the entire modeling process sanding, input estimation, and prediction- many times.
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sensitivity analysis includes field sampling and input estimation as well as the mode! proper.
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In ground water modeling, QA is crucial to both development and application of the mode} and should be an integral part of planning, applied to all phases of the modeling process. Adequate documentation and other forms of QA are becoming increasingly important as applications of models become part of regulatory submittals and are used to judge regulatory compliance.
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QA concepts will make a positive contribution to the way models are constructed and used; however, there is certainly a need to refine and extend existing approaches. QUALITY ASSURANCE PROCEDURES FOR CODE DEVELOPMENT The most important QA procedures in code development and maintenance applicable to ground water models are (van der Heij~e, 1987)
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From page 236... ...
Therefore, as part of the verification process, hypothetical problems might be used to test special computational features that are not represented in simple, analytical models, as in testing for irregular boundaries, varying boundary conditions, or certain heterogeneous and anisotropic aquifer properties. These hypothetical problems can be simulated by independent codes and the results compared.
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Several different groups in ground water modeling have in the past defined and used the terms validate and verify to mean different things. In fact, there is no consensus among ground water hydrologists, either on the definition of these two terms or on how to achieve validation and verification.
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Assess the quality of data in terms of accuracy (measurement errors) , precision, and completeness.
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Scientific and Ethnical Review Generally, the complete scientific and technical review process is qualitative in nature and comprises examination of mode! concepts, governing equations, and algorithms chosen, as well as evaluation of documentation and general ease of use, inspection of the structure of the program and the logic, handling of errors, and examination of the coding (Bryant and Wilburn, 1987; van der Beige et al., 1985b)
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will include realistic and appropriate boundary conditions, system properties, and discretization. It is too easy to calibrate (validate)
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Quality assurance in code application should cover all facets of the modeling process. It should address issues such as the following: project description and objectives; · correct and clear formulation of problems to be solved: type of modeling approach to the project; .
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peer review and oversight of the development and application of contaminant transport models have been performed, the quality of the modeling has been good (see the S-Area case study)
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Maximum likelihood method incorporating prior information. Water Resources Research 22~2)
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Unconditional moments. Water Resources Research 25~2)
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GWMI 84-13, International Ground Water Modeling Center, Holcomb Research Institute, Butler University, Indianapolis, Ind. Institute of Electrical and Electronic Engineers, Inc.
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1987. Comparison of three groundwater modeling studies.
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International Ground Water Modeling Center, Holcomb Research Institute, Butler University, Indianapolis, Ind. van der Heijde, P
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Water Resources Research 22~2)
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