Estimating net aquifer recharge and zonal hydraulic conductivity values for Mahi Right Bank Canal project area, India by genetic algorithm

The paper presents a recent approach for inverse modeling of groundwater systems based upon a generic algorithm (GA) global optimization technique which is coupled with a Galerkinʹs finite element (FEM) flow simulation model. Applicability, adequacy and robustness of the developed numerical model is tested by estimating the transmissivity parameter in various zones of a synthetic confined aquifer. The numerical model is applied to estimate hydraulic conductivity and recharge parameters of various zones in the Mahi Right Bank Canal (MRBC) project area. The solutions of synthetic and field aquifer problems are compared with another inverse model using the Gauss–Newton–Marquardt (GNM) method. Largely, the GA results are better compared to GNM parameter estimates, except, when no measurement errors in the observation head values are assumed. Head distribution computed using the estimated parameters for the MRBC aquifer is found closer to observed head distribution in the aquifer domain. From the adequacy of the estimated parameters the study concludes that the genetic algorithm approach can be successfully used for inverse modeling of regional aquifers where reliable parameter estimation is an important but difficult task for real system simulation.