As a common approach to reservoir operating policies, water levels at the end of each time interval should be kept at or above the rule curve. In this study, the policy is captured using rationing of the target yield to reduce the intensity of severe water shortages. For this purpose, a hybrid model is developed to optimize simultaneously both the conventional rule curve and the hedging rule. In the compound model, a simple genetic algorithm is coupled with a simulation program, including an inner linear programming algorithm. In this way, operational policies are imposed by priority concepts to achieve the optimal water allocation and the target storage levels for reservoirs. As a case study, a multipurpose, multireservoir system in southern Iran is selected. The results show that the model has good performance in extracting the optimum policy for reservoir operation under both normal and drought conditions.

A multiobjective programming model is proposed for optimal allocation of surface and groundwater resources under water deficits in arid and semiarid regions. This paper considers a biobjective problem in water allocation to agricultural areas by using a nondominated sorting genetic algorithm (NSGAII) as a multiobjective optimization method. Accordingly, there are two maximization objectives: (1) net benefit and (2) relative water use efficiency. Moreover, the optimized results of the aforementioned objectives have been determined to verify NSGAII solutions. Groundwater discharge, economic parameters, and evapotranspiration is formulated as three groups of constraints are linked together by the appropriate linear mathematical functions. The applicability of the irrigation scheduling is evaluated in the experimental field located at Baghmalek plain, Khuzestan province, Iran. The values of crop factors for different growth stages were estimated to obtain the production functions of wheat, barley, ric...