This work combines the Genetic Algorithm (GA) and Constrained Differential Dynamic Programming (CDDP) to solve the optimal pumping schedule and decreasing the environmental impact. The main structure of the hybrid algorithm is GA, in which each chromosome represents a possible network design and pumping wells expansion schedule. The fixed cost of each chromosome is computed easily by the GA. The CDDP then solves the optimal pumping scheme and, finally, evaluates the optimal operating costs associated with each chromosome. Simulation results indicate that under the same demand and annul interest rate, the capacity-expansion model has a lower total cost than the conventional design, which determines the system capacity initially. Furthermore, the land subsidence increases as total demand increases. The results further demonstrate that the proposed model is highly promising for use in facilitating a cost-efficiency design of well systems for regional groundwater supply and environmental preservation.