Multi-objective Planning for Conjunctive Use of Surface and Subsurface Water Using Genetic Algorithm and Dynamic Programming

The consideration of fixed cost and time–varying operating cost associated with the simultaneous conjunctive use of surface and subsurface water should be treated as a multi–objective problem due to the conflicting characteristics of these two objectives. In order to solve this multi–objective problem, a novel approach is developed herein by integrating the multi–objective genetic algorithm (MOGA), constrained differential dynamic programming (CDDP) and the groundwater simulation model ISOQUAD. A MOGA is used to generate the various fixed costs of reservoirs, generate a pattern of pumping/recharge, and estimate the non–inferior solutions set. A groundwater simulation model ISOQUAD is directly embedded to handle the complex dynamic relationship between the groundwater level and the generated pumping/recharge pattern. The CDDP optimization model is then adopted to distribute the optimal releases among reservoirs provided that reservoir capacities are known. Finally, the effectiveness of our proposed integrated model is verified by solving a water resources planning problem for the conjunctive use of surface and subsurface water in southern Taiwan.