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Assessment of the Joint Impact of Rainfall Characteristics on Urban Flooding and Resilience Using the Copula Method

Author

Listed:
  • Kun Xie

    (Wuhan University)

  • Yanfeng He

    (Wuhan University
    PowerChina Chengdu Engineering Co. Ltd)

  • Jong-Suk Kim

    (Wuhan University)

  • Sun-Kwon Yoon

    (Seoul Institute of Technology)

  • Jie Liu

    (Wuhan University)

  • Hua Chen

    (Wuhan University)

  • Jung Hwan Lee

    (K-Water Research Institute)

  • Xiang Zhang

    (Wuhan University)

  • Chong-Yu Xu

    (University of Oslo)

Abstract

The performance of urban drainage system (UDS) and green infrastructures (GI) significantly depends on the accurate determination of the rainfall characteristics of an urban area, especially because these rainfall characteristic variables are closely related. A bivariate copula method is used to evaluate and compare the joint impact of rainfall depth and duration on the hydrological performance of UDS and GI by considering the dependent structure of flood drivers. The peak flow, peak flow occurrence time, outflow, runoff coefficient, overflow, and resilience serve as the performance indicators. The estimated joint probability based on the optimal copula is used to define the boundary conditions for the calibrated Storm Water Management Model to simulate the hydrological process and the magnitude of floods caused by various combination of rainfall depth and durations. Results demonstrate that considering the dependence structure of rainfall characteristics, especially for the peak flow, runoff coefficient, and overflow, is critical for the comprehensive evaluation of the performance of the UDS. Neglecting the interaction between flood drivers can lead to overestimating the performance of UDS and GI in mitigating urban flood risk. The GI can effectively reduce urban flood and improve resilience, which varies with rainfall characteristics. Our results suggest that the utilization of accurate data on rainfall characteristics enhances the performance of the GI in flood mitigation and resilience improvement.

Suggested Citation

  • Kun Xie & Yanfeng He & Jong-Suk Kim & Sun-Kwon Yoon & Jie Liu & Hua Chen & Jung Hwan Lee & Xiang Zhang & Chong-Yu Xu, 2023. "Assessment of the Joint Impact of Rainfall Characteristics on Urban Flooding and Resilience Using the Copula Method," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(4), pages 1765-1784, March.
    • Handle: RePEc:spr:waterr:v:37:y:2023:i:4:d:10.1007_s11269-023-03453-9
    DOI: 10.1007/s11269-023-03453-9
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    References listed on IDEAS

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    1. Kun Xie & Jong-Suk Kim & Linjuan Hu & Hua Chen & Chong-Yu Xu & Jung Hwan Lee & Jie Chen & Sun-Kwon Yoon & Di Zhu & Shaobo Zhang & Yang Liu, 2023. "Intelligent Scheduling of Urban Drainage Systems: Effective Local Adaptation Strategies for Increased Climate Variability," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(1), pages 91-111, January.
    2. Mao, Xuhui & Jia, Haifeng & Yu, Shaw L., 2017. "Assessing the ecological benefits of aggregate LID-BMPs through modelling," Ecological Modelling, Elsevier, vol. 353(C), pages 139-149.
    3. Frahm, Gabriel & Junker, Markus & Schmidt, Rafael, 2005. "Estimating the tail-dependence coefficient: Properties and pitfalls," Insurance: Mathematics and Economics, Elsevier, vol. 37(1), pages 80-100, August.
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