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2007 International Symposium on Technology and Society, June 1-2 2007, Las Vegas, Nevada
Use of Numerical Groundwater Modeling to Evaluate Uncertainty in Conceptual Models of
Recharge and Hydrostratigraphy
Karl Pohlmann' (702-862-5485; Karl.Pohlmann@ dri.edu)
Ming Ye2 (MingYe@scs.fsu.edu)
Greg Pohll3 (Greg.Pohll@dri.edu)
Jenny Chapman' (Jenny.Chapman@ dri.edu)
'Desert Research Institute, Nevada System of Higher Education, 755 East Flamingo Road, Las
Vegas, NV 89119
2School of Computational Sciences and Department of Geological Sciences, Florida State
University, Tallahassee, FL 32306
3Desert Research Institute, Nevada System of Higher Education, 2215 Raggio Parkway, Reno,
NV 89512
Numerical groundwater models are based on conceptualizations of hydrogeologic systems that
are by necessity developed from limited information and therefore are simplifications of real
conditions. Each aspect (e.g. recharge, hydrostratigraphy, boundary conditions) of the
groundwater model is often based on a single conceptual model that is considered to be the best
representation given the available data. However, the very nature of their construction means that
each conceptual model is inherently uncertain and the available information may be insufficient
to refute plausible alternatives, thereby raising the possibility that the flow model is
underestimating overall uncertainty. In this study we use the Death Valley Regional Flow
System model developed by the U.S. Geological Survey as a framework to predict regional
groundwater flow southward into Yucca Flat on the Nevada Test Site. An important aspect of
our work is to evaluate the uncertainty associated with multiple conceptual models of
groundwater recharge and subsurface hydrostratigraphy and quantify the impacts of this
uncertainty on model predictions. In our study, conceptual model uncertainty arises from two
sources: (1) alternative interpretations of the hydrostratigraphy in the northern portion of Yucca
Flat where, owing to sparse data, the hydrogeologic system can be conceptualized in different
ways, and (2) uncertainty in groundwater recharge in the region as evidenced by the existence of
several independent approaches for estimating this aspect of the hydrologic system. The
composite prediction of groundwater flow is derived from the regional model that formally
incorporates the uncertainty in these alternative input models using the maximum likelihood
Bayesian model averaging method. An assessment of the joint predictive uncertainty of the input
conceptual models is also produced. During this process, predictions of the alternative models
are weighted by model probability, which is the degree of belief that a model is more plausible
given available prior information (expert opinion) and site measurements (hydraulic head and
groundwater flux). The results indicate that flow simulations in Yucca Flat are more sensitive to
hydrostratigraphic model than recharge model. Furthermore, posterior model uncertainty is
dominated by inter-model variance as opposed to intra-model variance, indicating that
conceptual model uncertainty has greater impact on the results than parametric uncertainty.
Without consideration of conceptual model uncertainty, uncertainty in the flow predictions
would be significantly underestimated. Incorporation of the uncertainty in multiple conceptual
models renders the groundwater flow model predictions more scientifically defensible.
KP: 2/6/2007
