Integration of Physiographic Drainage-Inundation Model and Nondominated Sorting Genetic Algorithm for Detention-Pond Optimization
Publication: Journal of Water Resources Planning and Management
Volume 141, Issue 11
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.
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Acknowledgments
The authors would like to thank the Ministry of Science and Technology of the Republic of China (Taiwan) for financially supporting this research under Contract No. NSC 101-2218-E-006-020-MY3.
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Published In
Journal of Water Resources Planning and Management
Volume 141 • Issue 11 • November 2015
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Jul 25, 2014
Accepted: Mar 31, 2015
Published online: Jun 2, 2015
Published in print: Nov 1, 2015
Discussion open until: Nov 2, 2015
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