Artificial recharge management of Shahriar plain aquifer with multi-objective simulation-optimization model

Population growth and the development of agriculture and industry have led to a significant reduction in groundwater resources. According to this issue, one of the useful and effective solutions for the optimal operation of aquifers is the implementation of artificial feeding systems. In this research, using mathematical model (HEC-HMS), flood routing in Karaj river and artificial feeding system reservoirs was performed. In this study, Considering to the mathematical model (HEC-HMS), flood routing was performed in Karaj river and artificial recharge system reservoirs. Then the storage volume in the artificial recharge system reservoirs was simulated by an artificial neural network and finally entered into a multi-objective genetic algorithm (NSGA-II). Multi-objective genetic algorithm (NSGA-II) was used for optimal utilization of the artificial recharge system , Considering to the optimal groundwater level changes. Based on the results, the total volume of optimal recharge in the desired time period by the artificial recharge system is equal to 97.94 million cubic meters and also optimal groundwater level changes have increased by 2.62 meters. Therefore, by allocating the optimal volume of the Bilqan diversion dam to the artificial recharge system, the optimal recharge volume and also optimal groundwater level changes in the desired time period have increased compared to the current conditions. considering that the optimal recharge volume and optimal groundwater level changes are proportional to each other, this performance will improve the aquifer conditions.