Estimation of the non-exceedance probability of extreme storm surges in South Korea using tidal-gauge data

Abstract

Global warming, one of the most serious aspects of climate change, can be expected to cause rising sea levels. These have in turn been linked to unprecedentedly large typhoons that can cause flooding of low-lying land, coastal invasion, seawater flows into rivers and groundwater, rising river levels, and aberrant tides. To prevent typhoon-related loss of life and property damage, it is crucial to accurately estimate storm-surge risk. This study therefore develops a statistical model for estimating such surges' probability based on surge data pertaining to Typhoon Maemi, which struck South Korea in 2003. Specifically, estimation of non-exceedance probability models of the typhoon-related storm surge was achieved via clustered separated peaks-over-Threshold simulation, while various distribution models were fitted to the empirical data for investigating the risk of storm surges reaching particular heights. To explore the non-exceedance probability of extreme storm surges caused by typhoons, a threshold algorithm with clustering methodology was applied. To enhance the accuracy of such non-exceedance probability, the surge data were separated into three different components: predicted water level, observed water level, and surge. Sea-level data from when Typhoon Maemi struck were collected from a tidal-gauge station in the city of Busan, which is vulnerable to typhoon-related disasters due to its geographical characteristics. Fréchet, gamma, log-normal, generalized Pareto, and Weibull distributions were fitted to the empirical surge data, and the researchers compared each one's performance at explaining the non-exceedance probability. This established that Weibull distribution was better than any of the other distributions for modelling Typhoon Maemi's peak total water level. Although this research was limited to one city on the Korean Peninsula and one extreme weather event, its approach could be used to reliably estimate non-exceedance probabilities in other regions where tidal-gauge data are available. In practical terms, the findings of this study and future ones adopting its methodology will provide a useful reference for designers of coastal infrastructure. © 2021 The Author(s).