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Water 2015, 7(9), 5173-5202; doi:10.3390/w7095173

Optimal Spatial Design of Capacity and Quantity of Rainwater Harvesting Systems for Urban Flood Mitigation

1
Department of Civil Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan
2
Department of Marine Environmental Informatics, National Taiwan Ocean University, No. 2, Beining Road, Jhongjheng District, Keelung City 20224, Taiwan
*
Author to whom correspondence should be addressed.
Academic Editor: Ataur Rahman
Received: 8 July 2015 / Accepted: 15 September 2015 / Published: 23 September 2015
View Full-Text   |   Download PDF [2479 KB, uploaded 23 September 2015]   |  

Abstract

This study adopts rainwater harvesting systems (RWHS) into a stormwater runoff management model (SWMM) for the spatial design of capacities and quantities of rain barrel for urban flood mitigation. A simulation-optimization model is proposed for effectively identifying the optimal design. First of all, we particularly classified the characteristic zonal subregions for spatial design by using fuzzy C-means clustering with the investigated data of urban roof, land use and drainage system. In the simulation method, a series of regular spatial arrangements specification are designed by using statistical quartiles analysis for rooftop area and rainfall frequency analysis; accordingly, the corresponding reduced flooding circumstances can be simulated by SWMM. Moreover, the most effective solution for the simulation method is identified from the calculated net benefit, which is equivalent to the subtraction of the facility cost from the decreased inundation loss. It serves as the initially identified solution for the optimization model. In the optimization method, backpropagation neural network (BPNN) are first applied for developing a water level simulation model of urban drainage systems to substitute for SWMM to conform to newly considered interdisciplinary multi-objective optimization model, and a tabu search-based algorithm is used with the embedded BPNN-based SWMM to optimize the planning solution. The developed method is applied to the Zhong-He District, Taiwan. Results demonstrate that the application of tabu search and the BPNN-based simulation model into the optimization model can effectively, accurately and fast search optimal design considering economic net benefit. Furthermore, the optimized spatial rain barrel design could reduce 72% of inundation losses according to the simulated flood events. View Full-Text
Keywords: rainwater harvesting system; stormwater runoff management model; backpropagation neural network; tabu search; spatial design of capacity and quantity; optimization; urban flood mitigation rainwater harvesting system; stormwater runoff management model; backpropagation neural network; tabu search; spatial design of capacity and quantity; optimization; urban flood mitigation
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Huang, C.-L.; Hsu, N.-S.; Wei, C.-C.; Luo, W.-J. Optimal Spatial Design of Capacity and Quantity of Rainwater Harvesting Systems for Urban Flood Mitigation. Water 2015, 7, 5173-5202.

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