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|Title:||Estimation of hydrogeological parameters in groundwater modeling by genetic algorithm|
|Citation:||GROUND WATER UPDATES,405-410|
|Abstract:||Efficient management of groundwater systems depends primarily on adequate knowledge of its hydrogeologic parameters. Estimation of these spatially distributed hydrogeologic parameters in large aquifer systems often involves considerable amount of time and financial resources. These parameters are required for the groundwater system simulation to predict head behavior in the flow domain. Inverse modeling of the system helps us in the adequate assessment of these parameters for getting a meaningful system simulation. A new approach for parameter estimation of groundwater systems based upon genetic algorithm (GA) global optimization technique coupled with Galerkin's finite element (FEM) flow simulation model is presented. The developed inverse GA model is applied for Mahi Right Bank Canal (MRBC) command area aquifer to estimate optimal aquifer parameters hydraulic conductivity and net recharge in the flow domain. The results show that the computed head distribution using the estimated parameters from inverse modeling is closer to the observed head contours. The estimated parameters are in acceptable agreement with the results obtained from another inverse model developed from conventional optimization technique of Gauss-Newton-Marquardt method. The study concludes that the developed algorithm is useful for successful estimation of aquifer parameters in the case of large aquifer systems.|
|Appears in Collections:||Proceedings papers|
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