Coastal Groundwater Management by an Uncertainty-Based Parallel Decision Model

Abstract

Seawater intrusion is a common problem in coastal aquifers and can be intensified by various factors, such as unplanned groundwater extraction. Hence, making appropriate decisions for coastal groundwater management is essential to prevent excessive seawater intrusion, although the uncertainties of this procedure can undermine the reliability of obtained results and consequently affect proposed decisions. To address such challenges, this study presents an uncertainty-based decision model based on a combined simulation-optimization framework and parallel processing technique. In this model, the SUTRA numerical simulation model is combined with an evolutionary algorithm of continuous ant colony optimization, while Monte Carlo simulation is used to consider the uncertainties in the permeability of porous media. Two sets of probabilistic management problems are formulated for maximizing groundwater extraction and controlling the seawater intrusion in a real case coastal aquifer of Ajabshir, Iran. The results indicate that a 46% increase in groundwater extraction is possible for a low-exploitation-stress period of the year. Moreover, using a parallelization technique with 15 threads, the computational time of the decision model is cut in half.