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Optimum Design and Operation of a Reservoir and Irrigation Network Considering Uncertainty of Hydrologic, Agronomic and Economic Factors

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Abstract

In this research, a reliability-based method for optimum design of the capacity and operation policy for a water resource system including a reservoir and the downstream irrigation network is presented in which important stochastic hydrological, agronomic and economic factors are considered. The developed model is applied for the Marboreh reservoir and the irrigation network in west of Iran in the form of a stochastic mathematical program with the objective function of maximizing the net benefit gained from the crops’ production limited to the hydrologic constraints associated with the reservoir and soil moisture of the plants’ root zone and the agronomic constraints related to the crops. The decision variables are design parameters of the reservoir capacity, irrigation network area and the crops pattern and the operation parameters which include reservoir operation policy, water allocation to the crops and the irrigation strategy. The uncertain factors considered are the inflow to the reservoir, the water demands, the crops yield, the price of crops and the production costs. Genetic algorithm is used as the optimization routine and a Monte-Carlo routine takes into account the effect of the stochastic outcomes of the uncertain factors. Results state the optimal capacity of 161.8 MCM for the reservoir, area of 31,304 ha for the irrigation network and a volumetric reliability of 72.1% in the neutral to risk condition. In the risky state, the network area is increased and the reservoir capacity and the reliability index are decreased while in the risk-averse state the results are vice versa.

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Correspondence to Mojtaba Shourian.

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Sheibani, H., Alizadeh, H. & Shourian, M. Optimum Design and Operation of a Reservoir and Irrigation Network Considering Uncertainty of Hydrologic, Agronomic and Economic Factors. Water Resour Manage 33, 863–879 (2019). https://doi.org/10.1007/s11269-018-2148-5

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