Optimal Design of Check Dams in Mountainous Watersheds for Flood Mitigation

J. Yazdi (), M. Sabbaghian Moghaddam and B. Saghafian
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J. Yazdi: Shahid Beheshti University
M. Sabbaghian Moghaddam: Islamic Azad University, Science and Research Branch
B. Saghafian: Islamic Azad University, Science and Research Branch

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2018, vol. 32, issue 14, No 20, 4793-4811

Abstract: Abstract One of the measures for flood control is to construct a series of small barriers, known also as check dams, on tributaries of watershed stream network. Check dams are generally used in mountainous areas in order to control sediment transport and attenuate flood peak. In this paper, a simulation-based optimization model is developed to determine size, shape and the number of check dams for flood mitigation. HEC-HMS model is used to simulate watershed rainfall-runoff process considering various check dam designs. The model is coupled with a multi-objective evolutionary algorithm, called non-dominated sorting differential evolution (NSDE), to find the trade-off solutions considering three objective functions: 1) minimizing the investment cost, 2) minimizing the flood peak discharge and 3) maximizing the time to peak discharge. The proposed model is applied to a mountainous watershed in Iran and (near) optimal strategies, including the suitable number of check dams in each sub-watershed, and optimal dam size (e.g. optimal height, bottom width and side angles) in each sub-watershed are obtained. The results show that cost-effective designs can decrease peak discharge up to 53%, 54 and 54% corresponding to 2-yr, 5-yr and 10-yr flood return period scenarios, respectively. In addition, the check dams can also increase the time to peak for up to 88%, 81 and 77%, corresponding to 2-yr, 5-yr and 10-yr flood scenarios, respectively.

Keywords: Optimal design; Check dam; Optimization; Flood mitigation; Simulation (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s11269-018-2084-4

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