Multi-objective optimization for allocation of surface water and groundwater resources

Abstract

Many developing countries face water deficit due to various reasons such as population growth, limited surface water resources, uneven spatial and temporal distributions of precipitation, industrialization, climate change, and lack of efficient management. This fact has led to a significant reduction in water resources, which has further caused water conflicts among the stakeholders. Hence, developing comprehensive water allocation policies to account for social standards, economic efficiency, and environmental sustainability is necessary. The objective of this study is to integrate the system dynamics simulation-optimization technique, and the Nash bargaining theory for optimal allocations of water resources. The proposed simulation, optimization, and conflict resolution modeling approach was applied for the joint allocation of surface water and groundwater among drinking, industrial, agricultural, and environmental sectors in the Najaf-Abad sub-basin in Iran. To obtain the Pareto front, the NSGA-II multi-objective optimization algorithm was used to maximize the water supply (i.e., minimize the water deficit) (objective function 1) and also minimize the groundwater extraction from the Najaf-Abad aquifer (objective function 2) over the entire operation period. The decision variables, the percentages of surface water and groundwater extractions, were determined for a set of optimal solutions. The optimum water supply (objective function 1) was 16.84 × 10 6 m 3 and the optimum reduction of the water table of the aquifer (objective function 2) was 0.63 m, representing an improvement of 30% over the existing condition. This study demonstrates the ability of the proposed simulation-optimization-conflict resolution modeling approach and its applicability for water resources allocation. • Allocation of surface water and groundwater resources with SD, simultaneously. • Considering water demands (drinking, industry, agriculture, and environment) simultaneously. • Minimization of aquifer loss and maximization of water supply, simultaneously. • Developing an automated coupled model using SD, NSGA-II and conflict resolution, simultaneously.