Abstract

In this paper, a new methodology is developed for the allocation of groundwater to agricultural lands considering the cultivated area of different crops, selling price and net benefit of products, and crops’ water requirements. The methodology includes an integrated model with daily time steps for simulating soil water balance, cultivar growth, and groundwater level fluctuations. The developed simulation model is linked with a particle swarm optimization model to find the optimal net benefit of beneficiaries. The non-dominated sorting genetic algorithm is also implemented to evaluate the fuzzy responses of the model against the existing uncertainty in the water supply. To evaluate the applicability and efficiency of the proposed methodology, it is applied to a real-world common pool groundwater allocation for agricultural uses in Iran. The results show that a centralized water allocation strategy can increase water productivity under water stress conditions by more than 0.2 kg/m3 for wheat, and barley. This policy can also provide the highest values for the benefit per cost ratio and the economic efficiency of land.

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