Urban flood risk assessment using storm characteristic parameters sensitive to catchment-specific drainage system Academic Article uri icon

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abstract

  • A recent increase in urban floods has necessitated more effective assessment of urban flood risks to quantify the failure probability of urban drainage systems. However, the random hyetographs of storm events influences the results of flood risk assessment using existing methods. In this study, an alternative and more effective method is developed. After extracting characteristic parameters from hyetographs, the correlation between storm events characteristic and urban flood is analyzed according to the hydraulic model simulation results. Based on it, the storm characteristic parameters sensitive to catchment-specific drainage system response and its threshold to urban flood can be determined. And then, the storm events probability can be described with joint probability distribution of the sensitive parameters through using the Frank Copula. Therefore, flood risks for specific urban catchment can then be assessed by calculating the frequency of occurrence of all the storm events for which sensitive parameter exceed the threshold. This methods was successfully applied for the Chengzhong drainage system in Jiaxing, China. For the catchment-specific system it was found that the most important storm event characteristics are the mean rainfall intensity (I) and the peak 30-min intensity (30-Rp). Thus, the bivariate joint probability distribution of I and 30-Rp was estimated and based on that the risks that the catchment may be flooded every year can be assessed by calculating the probabilities of occurrence of flood-causing storm events per year. The proposed method is applicable for urban areas with different catchment conditions and drainage facilities, and it can provide alternative efficient means for urban flood risk assessment.

authors

  • Zhou, Yongchao
  • Shen, Dali
  • Huang, Ning
  • Guo, Yiping
  • Zhang, Tuqiao
  • Zhang, Yiping

publication date

  • April 2019