Optimization of Integrated Operation of Surface and Groundwater Resources using Multi-Objective Grey Wolf Optimizer (MOGWO) Algorithm

The knowledge of surface and groundwater interactions within the region, as well as the computation of surface and subsurface elements impacting them, are necessary for principled planning for the sustainable and optimal functioning of water resource systems. Investigating the effects of the surface–groundwater interaction by establishing a dynamic link between surface and groundwater models in the Lur plain, which is situated in Western Iran downstream of the Balarood River dam, is one of the main goals of this study. Every element of the surface and groundwater systems in the research area is connected to every other element of the model, allowing data to flow back and forth between the two systems at every time step. To calculate groundwater level values, the flow between aquifers, etc., and send the results back to the WEAP model so that this process continues until the simulation's conclusion, the withdrawal amount, infiltration, river level, runoff, etc. are imported to the WEAP model from the MODFLOW model in each time step. Optimizing the monthly volume of extraction from surface and groundwater resources to meet current consumptions during a 30-year planning horizon is another objective. The Multi-Objective Grey Wolf Optimizer (MOGWO) algorithm is connected to the integrated model body in order to carry out the system optimization. The primary and secondary goals of the optimization process are, respectively, to minimize the amount of groundwater withdrawal at the conclusion of the operating period and to maximize the percentage of meeting water needs. The proportion of monthly removal from surface and groundwater resources is one of the decision factors. Two managerial scenarios—the integrated operation based on the present condition (reference) and the integrated operation by carrying out the optimization process (optimal)—are established to examine the effects of the dam and aquifer operating together. The outcomes demonstrate that, in comparison to the reference scenario, the proportion of meeting farms' water demands during low water months is enhanced by 10% to 30% following the execution of the optimizer algorithm and the use of the integrated model body's optimal allocation parameters. The average drawdown in the Lur plain after the period, following system optimization, is equal to 7.6 m, which is 2.5 m better than the reference scenario. The outcomes of planners' decisions are quickly transformed into the whole system, and the subsequences are observable in both surface and groundwater sections. The results show that the MOGWO algorithm combined with the integrated operation model in the dynamic link mode is an effective solution for better management of the dam and aquifer.