Combined Estimation of Hydrogeologic Conceptual Model, Parameter, and Scenario Uncertainty with Application to Uranium Transport at the Hanford Site 300 Area (NUREG/CR-6940)

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Publication Information

Manuscript Completed: June 2007
Date Published: July 2007

Prepared by:
P.D. Meyer, M. Ye (DRI), M.L. Rockhold, S.P. Neuman (UA)
K.J. Cantrell

Pacific Northwest National Laboratory
P.O. Box 999
Richland, WA 99352

Desert Research Institute
Las Vegas, NV 89119
(Currently at Florida State University, Tallahassee, FL 32306)

University of Arizona
Tucson, AZ 85721

T.J. Nicholson, NRC Project Manager

Prepared for:
Division of Fuel, Engineering and Radiological Research
Office of Nuclear Regulatory Research
U.S. Nuclear Regulatory Commission
Washington, DC 20555-0001

NRC Job Code Y6465

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We describe the development and application of a methodology to systematically and quantitatively assess predictive uncertainty in groundwater flow and transport modeling. The methodology considers the combined impact of hydrogeologic uncertainties associated with the conceptual-mathematical basis of a model, model parameters, and the scenario to which the model is applied. The methodology is based on an extension of a Maximum Likelihood implementation of Bayesian Model Averaging. Model uncertainty is represented by postulating a discrete set of alternative conceptual models for a site with associated prior model probabilities. The prior model probabilities reflect a subjective belief about the relative plausibility of each model based on its apparent consistency with available knowledge and data. Posterior model probabilities are computed and parameter uncertainty is estimated by calibrating each model to observed system behavior. Posterior model probabilities are modifications of the subjective prior values based on an objective evaluation of each model’s consistency with available data. Prior parameter estimates are optionally included. Scenario uncertainty is represented as a discrete set of alternative future conditions affecting boundary conditions, source/sink terms, or other aspects of the models. The associated prior scenario probabilities reflect a subjective belief about the relative plausibility of the alternative scenarios. A joint assessment of uncertainty results from combining model predictions computed under each scenario using as weights the posterior model and prior scenario probabilities. The computed model predictions incorporate parameter uncertainties using, for example, Monte Carlo simulation. The uncertainty methodology was applied to modeling of groundwater flow and uranium transport at the Hanford Site 300 Area. Eight alternative models representing uncertainty in the hydrogeologic and geochemical properties as well as the temporal variability were considered. Two scenarios representing alternative future behavior of the Columbia River adjacent to the site were considered. The scenario alternatives were implemented in the models through the boundary conditions. Alternative models were calibrated using hydraulic head and uranium concentration observations over a seven-year period. Uranium concentrations under each scenario were predicted over a 20-year period. Results demonstrate the feasibility of applying a comprehensive uncertainty assessment to large-scale, detailed groundwater flow and transport modeling. Results also illustrate the ability of the methodology to provide better estimates of predictive uncertainty, quantitative results for use in assessing risk, and an improved understanding of the system behavior and the limitations of the models.

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