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

Author

Listed:
  • 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)

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.

Suggested Citation

  • Li Liu & Xing Li & Gaoyuan Xia & Juliang Jin & Guowei Chen, 2016. "Spatial fuzzy clustering approach to characterize flood risk in urban storm water drainage systems," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(3), pages 1469-1483, September.
    • Handle: RePEc:spr:nathaz:v:83:y:2016:i:3:d:10.1007_s11069-016-2371-4
    DOI: 10.1007/s11069-016-2371-4
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    References listed on IDEAS

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    1. Liang, Gin-Shuh & Chou, Tsung-Yu & Han, Tzeu-Chen, 2005. "Cluster analysis based on fuzzy equivalence relation," European Journal of Operational Research, Elsevier, vol. 166(1), pages 160-171, October.
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