Integration of Physiographic Drainage-Inundation Model and Nondominated Sorting Genetic Algorithm for Detention-Pond Optimization

Abstract

The study aims to propose a simulation-optimization model for deciding the optimal combination of detention ponds, which comprises a two-dimensional physiographic drainage-inundation model and a nondominated sorting genetic algorithm II (NSGA-II). Dian-Bao River Basin in southern Taiwan is chosen as the study area. Five detention-pond candidates with different sizes and locations are adopted for optimizing their combination. One-day design rainfalls for different return periods (i.e., 2, 5, 10, and 25 years) are used as the model input. During the optimization process, two conflicting objectives (i.e., the investment cost and the inundation-damage cost) are minimized to obtain the Pareto-optimal solutions by using the NSGA-II. Based on the posterior approach, the compromise solutions for different return periods are obtained. A cost-benefit analysis is further used to evaluate the compromise solutions for different return periods. The optimal combination of detention ponds for the return period (e.g., 25 years in the study case) with the highest value of direct benefit-cost ratio can be suggested for decision making.