Inverse modeling of variable-density groundwater flow in a semi-arid area in Iran using a genetic algorithm

Flow and mass transport parameter estimation was done by creating an inverse model of a seawater intrusion system using a genetic algorithm (GA) method as the optimization procedure. Firstly, the SEAWAT code was used for the forward solution part and then a program was written in MATLAB for coupling the forward and inverse processes. The auto-calibration objective function was defined with the root mean square errors (RMSE) between the observed and the simulated values. A simple GA was used to minimize the RMSE criterion. The methodology was applied to a coastal aquifer with heterogeneous formations in a semi-arid area near salty Tashk Lake (electrical conductivity 61,420 µS/cm), Fars province, Iran. In the last two decades, the overexploitation of groundwater has caused a major water level drawdown and, consequently, salt-water intrusion. Firstly, flow and transport parameters (hydraulic conductivity, porosity, specific storage coefficient and longitudinal dispersivity) were estimated simultaneously in steady-state and, secondly, in the developed code, these results were used as initial values of the parameters in transient-state. Results show a good match for observed and simulated data. It can be concluded that GA is a helpful tool for automatic calibration of variable density fluid systems such as seawater intrusion cases.