Urban flooding resilience evaluation with coupled rainfall and flooding models: a small area in Kunming City, China as an example

Autor: Tong Xu, Zhiqiang Xie, Fengshan Jiang, Shouquan Yang, Zhanting Deng, Lei Zhao, Guang Wen, Qingyun Du
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Water Science and Technology, Vol 87, Iss 11, Pp 2820-2839 (2023)
Druh dokumentu: article
ISSN: 0273-1223
1996-9732
DOI: 10.2166/wst.2023.149
Popis: Climate change and increasing urbanization have contributed greatly to urban flooding, making it a global problem. The resilient city approach provides new ideas for urban flood prevention research, and currently, enhancing urban flood resilience is an effective means for alleviating urban flooding pressure. This study proposes a method to quantify the resilience value of urban flooding based on the `4R' theory of resilience, by coupling the urban rainfall and flooding model to simulate urban flooding, and the simulation results are used for calculating index weights and assessing the spatial distribution of urban flood resilience in the study area. The results indicate that (1) the high level of flood resilience in the study area is positively correlated with the points prone to waterlogging; the more an area is prone to waterlogging, the lower the flood resilience value. (2) The flood resilience index in most areas shows a significant local spatial clustering effect, the number of areas with nonsignificant local spatial clustering accounting for 46% of the total. The urban flood resilience assessment system constructed in this study provides a reference for assessing the urban flood resilience of other cities, thus facilitating the decision-making process of urban planning and disaster mitigation. HIGHLIGHTS Enhancing urban flood resilience is an effective means for alleviating urban flooding pressure.; A method to quantify the resilience value of urban flooding based on the ‘4R’ theory of resilience.; By coupling the urban rainfall and flooding model to simulate urban flooding and using the simulation results for calculating index weights.; Entropy weight method.;
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