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Optimal Linear/Nonlinear, Quantity/Quality Management Of Complex Multilayer Aquifers By Embedding, Ali Gharbi, Richard C. Peralta
Optimal Linear/Nonlinear, Quantity/Quality Management Of Complex Multilayer Aquifers By Embedding, Ali Gharbi, Richard C. Peralta
Civil and Environmental Engineering Faculty Publications
The embedding optimization modelling approach is adapted to aid long-term groundwater quality and quantity management of complex nonlinear multilayer aquifers. Implicit block-centered finite-difference approximations of the quasi-three-dimensional unsteady flow equation, and Galerkin finite-element approximations of the twodimensional advection-dispersion transport equation are embedded as constraints in the model. Other hydrological processes are also included as constraints. Cyclical linear differencing permits representation of nonlinear transport, even when contaminant is extracted by unsteady pumping (a decision variable). Also used are nonlinear (discontinuous derivative) constraints describing drainage, stream-aquifer interflow and evapotranspiration. The use of both linear and nonlinear formulations of the entire flow and …
Optimal Groundwater Quantity/Quality Planning For Salt Lake Valley, Ali Gharbi, Richard C. Peralta
Optimal Groundwater Quantity/Quality Planning For Salt Lake Valley, Ali Gharbi, Richard C. Peralta
Civil and Environmental Engineering Faculty Publications
Generally, the embedding technique for optimizing groundwater management has been limited to small scale or steady-state groundwater flow management cases. The embedding approach causes sparse, highly structured constraint matrices which have been sometimes difficult to solve. Embedding applications have been limited by lack of: optimization algorithms able to easily address such matrices for large scale problems, and efficient methods for addressing common nonlinearities and converging to a solution. Computer software, USUEM, addresses these issues by: creation of alternative linear, nonlinear, combined and partitioned formulations of the same problem, implemention of an efficient cycling procedure, and good selection of optimization algorithm …