Conjunctive Management of Surface and Ground Water Resources Using Conflict Resolution Approach

Abstract

Management of surface and ground water resources in drought-stricken regions with increasing water consumption poses a major challenge to water resource managers and decision makers. The situation is even graver in areas naturally classified as semiarid regions. Conjunctive management of ground and surface water is an appropriate strategy in such regions and in areas involving many stakeholders with various views and different water demands. It is, indeed, an effective approach that can enhance the reliability of water supplies. In the present study, the artificial neural networks (ANNs) and genetic algorithm (GA) are exploited to develop a simulation multiobjective optimization model. Conflict resolution models are also used to solve the problems and to seek a reliably stable solution for the study area, one of the subbasins of the Zayandehrood River Basin in central Iran, where recent water shortages and increased demands have led to conflicts between the Regional Water Company and the Agriculture Organization. To address the issue, the Pareto frontier or trade-off curve is generated and a unique solution is obtained by applying two conflict resolution methods. The conjunctive management model is then applied to establish stable and satisfactory conditions governing the relations between stakeholders that aim at supplying at least 65% of their demands and limiting groundwater level drawdown to 3 m per year.