Compound effects of rainfall and storm tides on coastal flooding risk
H Xu, K Xu, J Lian, C Ma - Stochastic Environmental Research and Risk …, 2019 - Springer
H Xu, K Xu, J Lian, C Ma
Stochastic Environmental Research and Risk Assessment, 2019•SpringerRainfall and storm tides are both flood drivers in coastal zones. The complex interplay
between them can lead to or exacerbate the impacts of flooding. While the dependence
between rainfall and storm tides has been extensively studied, the compound effects of them
on coastal flood risk have not been well researched. With Haikou city as the case study, this
study investigates the bivariate return period of compounding rainfall and storm tide events
based on copula functions and the failure probability is used to assess the variation of …
between them can lead to or exacerbate the impacts of flooding. While the dependence
between rainfall and storm tides has been extensively studied, the compound effects of them
on coastal flood risk have not been well researched. With Haikou city as the case study, this
study investigates the bivariate return period of compounding rainfall and storm tide events
based on copula functions and the failure probability is used to assess the variation of …
Abstract
Rainfall and storm tides are both flood drivers in coastal zones. The complex interplay between them can lead to or exacerbate the impacts of flooding. While the dependence between rainfall and storm tides has been extensively studied, the compound effects of them on coastal flood risk have not been well researched. With Haikou city as the case study, this study investigates the bivariate return period of compounding rainfall and storm tide events based on copula functions and the failure probability is used to assess the variation of bivariate flood risk during the entire project lifetime. The results show that (1) there is a significant correlation between rainfall and storm tides. Therefore, bivariate RP analysis can provide more adequate and comprehensive information about risks than univariate RP analysis. Kendall RP can describe the bivariate RP more accurately since the dangerous region of Kendall RP is divided by the joint probability value. (2) Neglecting the compounding impacts and the dependence of rainfall and storm tides causes significant underestimation of the joint RP and failure probability. (3) The bivariate hydrologic risk value will decrease quickly when the design rainfall is higher than 100 mm and it becomes small and decrease slowly when the design rainfall exceeds 450 mm. Furthermore, the bivariate hydrologic risk value would not decrease until the storm tide is higher than 2 m and the values would become quite small as the storm tide exceeds 4.5 m. Such bivariate hydrologic risk analysis can provide decision support for hydraulic facility design as well as actual flood control and mitigation.
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