Multiobjective Optimization for Water Resource Management in Low-Flow Areas Based on a Coupled Surface Water–Groundwater Model

Abstract

Optimal operation of water resource systems requires understanding the interaction between the surface water and groundwater in the region of interest. Furthermore, model parameters as well as effective surface and underground factors should be estimated and calculated. This research focuses on linking the nondominated sorting genetic algorithm II with a coupled surface water–groundwater model in an area of southwestern Iran. The advantage of this structure is achieving and sustaining a balance between surface water and groundwater withdrawal by considering various constraints. The optimized withdrawal from surface water and groundwater in wet and dry areas is obtained by linking the optimization algorithm with the coupled model. Application of this method in the study area can first, to some extent, enhance the demand supply reliability and contribute to reducing the groundwater drawdown at the end of the operational period. In addition, in the proposed coupled model, all the components involved in the surface water and groundwater models are linked, with data and results flowing back and forth between the two models for each computational time step. Thus, the model structure can allow decision makers to simulate surface water–groundwater interaction in the region for computing simultaneous depletions in river flow and groundwater, particularly during dry years. This structure is suggested for sustainable water resources management, particularly in low-flow areas.