In this paper, a genetic algorithm model is developed to optimise the crop pattern of irrigation networks, considering water allocation priorities and surface and groundwater availability. The objective function of this model is to maximise the net benefits of agricultural products, considering allowable water table fluctuations, pumping costs, as well as the impacts of water supply deficit on crop production. The model is formulated in such a way that both crop pattern and water allocation from surface or groundwater resources are simultaneously optimized. Due to the large number of decision variables and the non-linearity of the problem, a genetic algorithm (GA) is used to find the optimal solution. One of the main advantages of the proposed model is consideration of the time series of monthly crop water demand, which allows incorporation of demand uncertainty in the development of optimal operation policies. A production function has also been used to estimate the production rate with respect to the amount of water allocation and water supply deficits. The results of the application of this model to agricultural lands in eight irrigation networks in Tehran province in Iran are also presented in the paper. The results include optimal crop pattern and operating policies for surface and groundwater allocation in a long-term planning horizon. The results of the model application to Tehran plain have shown a significant change in the area allocated to different crops to provide a higher total benefit.

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