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, rice, maize, melon, tomato, onion, vegetable, and bean. The results showed that the model did not suggest deficit irrigation for melon and tomato during the middle stage. Overall, incorporating multiobjective optimization techniques using NSGAII can effectively improve precision in irrigation scheduling.