A Hierarchical and Patch Dynamics Paradigm for Modeling Complex, 3D Groundwater Systems Across Multiple Scales

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0523107LiThis work would complement NSF Award 0430987 by adding a PEST-Based Module for Multi-Scale Inverse Modeling. The new "forward" hierarchical patch dynamic modeling capability developed through that award would by complemented by adding an important multi-scale inverse modeling component that would significantly enhance our ability to identify and characterize complex subsurface systems and fluxes at surface water interfaces so as to facilitate systematic use of expensive field information across multiple scales from disparate sources. The hierarchical inverse environment will be based on the popular inverse modeling engine - PEST - a general, model independent nonlinear parameter estimation program. The PEST program will be adapted and seamlessly embedded in the hierarchical modeling environment. It will communicate with the entire model hierarchy dynamically, obviating the need for offline processing, I/O, and file storage. The hierarchical inverse environment will allow integrated, simultaneous calibration of flow and/or transport processes within one or more patches across any combination of scales. To calibrate a complex system, a user will inform PEST interactively and graphically which parameters/input values at what scales will be adjusted and the patch and scale dependent calibration targets (e.g., heads, fluxes, concentration, etc.). PEST will then take control of the hierarchical modeling system, running it as many times as it needs to while adjusting parameter values until the discrepancies between model outputs and corresponding field or laboratory measurements are as small as possible in the weighted least squares sense. The program will provide a hierarchical environment to graphically display optimal parameter values, an estimate of the uncertainty associated with optimal parameter values, best-fit model outcomes, model-to-measurement residuals, and a suite of statistics related to the optimal parameter and residual sets.