Spatial fuzzy clustering approach to characterize flood risk in urban storm water drainage systems

Li Liu (), Xing Li, Gaoyuan Xia, Juliang Jin and Guowei Chen
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Li Liu: Hefei University of Technology
Xing Li: Hefei University of Technology
Gaoyuan Xia: Hefei University of Technology
Juliang Jin: Hefei University of Technology
Guowei Chen: Hefei University of Technology

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2016, vol. 83, issue 3, No 6, 1469-1483

Abstract: Abstract Increasing environmental stress of drainage systems leads to frequent occurrence of urban flooding, which generates significant adverse economic, social, and environmental impacts. In this study, spatial fuzzy clustering approach (SFCA) is developed to estimate possible flood risks in storm water drainage systems and address complexity and uncertainties of flood risk assessment. The proposed approach is capable of gaining insights into system behavior by exploring spatial patterns of flood risk. The corresponding algorithm is utilized to divide a drainage system into various clusters to reflect flood risk levels along the network space. Application to a sample drainage system demonstrates that it provides an appropriate technique to determine spatial distribution of flood risks. Results reveal that areas with high, moderate, and low risk identified by SFCA correspond to a certain degree of environmental stress. The findings of this study can serve as a preliminary basis to guide managers in their evaluation of flood risks in various drainage management scenarios.

Keywords: Flood risks; Fuzzy clustering method; Spatial characterization; Spatial clustering analysis; Urban drainage system (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s11069-016-2371-4

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