HR: 0800h
AN: H21F-0814    [Abstracts]
TI: An Example Multi-Model Analysis: Calibration and Ranking
AU: * Ahlmann, M
EM: mahlman@sandia.gov
AF: Sandia National Laboratories, Thermal/Fluid Science & Engineering, PO Box 969, Livermore, CA 94551-0969, United States
AU: James, S C
EM: scjames@sandia.gov
AF: Sandia National Laboratories, Thermal/Fluid Science & Engineering, PO Box 969, Livermore, CA 94551-0969, United States
AU: Lowry, T S
EM: tslowry@sandia.gov
AF: Sandia National Laboratories, Geohydrology, PO Box 5800, Albuquerque, NM 87185-0735, United States
AB: Modeling solute transport is a complex process governed by multiple site-specific parameters like porosity and hydraulic conductivity as well as many solute-dependent processes such as diffusion and reaction. Furthermore, it must be determined whether a steady or time-variant model is most appropriate. A problem arises because over-parameterized conceptual models may be easily calibrated to exactly reproduce measured data, even if these data contain measurement noise. During preliminary site investigation stages where available data may be scarce it is often advisable to develop multiple independent conceptual models, but the question immediately arises: which model is best? This work outlines a method for quickly calibrating and ranking multiple models using the parameter estimation code PEST in conjunction with the second-order-bias-corrected Akaike Information Criterion (AICc). The method is demonstrated using the twelve analytical solutions to the one- dimensional convective-dispersive-reactive solute transport equation as the multiple conceptual models (van~Genuchten M. Th. and W. J. Alves, 1982. {\sl Analytical solutions of the one-dimensional convective- dispersive solute transport equation}, USDA ARS Technical Bulletin Number 1661. U.S. Salinity Laboratory, 4500 Glenwood Drive, Riverside, CA 92501.). Each solution is calibrated to three data sets, each comprising an increasing number of calibration points that represent increased knowledge of the modeled site (calibration points are selected from one of the analytical solutions that provides the "correct" model). The AICc is calculated after each successive calibration to the three data sets yielding model weights that are functions of the sum of the squared, weighted residuals, the number of parameters, and the number of observations (calibration data points) and ultimately indicates which model has the highest likelihood of being correct. The results illustrate how the sparser data sets can be modeled accurately using several of the twelve analytical solutions, while more numerous calibration data lead to a clearly defined model ranking. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.
DE: 1805 Computational hydrology
DE: 1829 Groundwater hydrology
DE: 1846 Model calibration (3333)
DE: 1873 Uncertainty assessment (3275)
SC: Hydrology [H]
MN: 2007 Fall Meeting