Paper No. 8
Presentation Time: 10:00 AM

EVALUATING MODEL STRUCTURE ADEQUACY: THE CASE OF THE MAGGIA VALLEY, SOUTHERN SWITZERLAND, AND CONSEQUENCES FOR SIMULATING COUPLED HYDROLOGIC MODELS


FOGLIA, Laura, Technical University of Darmstadt, Karolinenplatz 5, Darmstadt, 64289, Germany, HILL, Mary C., U.S. Geological Survey, 3215 Marine Street, Boulder, CO 80303 and MEHL, Steffen, California State University, Chico, Department of Civil Engineering, 400 W 1st St Chico, CA, Chico, CA 95929, mchill@usgs.gov

Model adequacy is evaluated with alternative integrated groundwater/river models ranked using model selection criteria (AICc, BIC, and KIC) and three other statistics. Model selection criteria are tested with cross-validation experiments, and insights for using alternative models to evaluate model structural adequacy are provided. The study is conducted using the computer codes MODFLOW, UCODE_2005 and MMA (MultiModel Analysis). One recharge alternative is simulated using the TOPKAPI hydrological model. The predictions evaluated include eight heads and streamflow gains from groundwater along three reaches located where ecological consequences and model precision are of concern. Cross-validation is used to obtain measures of prediction accuracy. Sixty-four models were designed deterministically and differ in representation of river, recharge, bedrock topography, and hydraulic conductivity. Results include: (1) What may seem like inconsequential choices in model construction may affect predictions. Because of this, predictions from alternative models should be considered. An unexpectedly consequential decision in construction of this model was whether to use the recharge (RCH) or streamflow-routing (SFR) package to represent stream leakage in the MODFLOW simulation. (2) None of the model selection criteria consistently identified models with more accurate predictions. This is a disturbing result that suggests reconsideration of the utility of model selection criteria and/or the cross-validation measures used in this work to measure model accuracy. (3) KIC displayed poor performance for the present regression problems; theoretical considerations suggest that difficulties are associated with wide variations in the sensitivity term of KIC resulting from the models being nonlinear and the problems being ill-posed due to parameter correlations and insensitivity. The other criteria performed somewhat better, and similarly to each other. (4) Quantities with high leverage are more difficult to predict. The results are expected to have broad applicability.