Articles | Volume 21, issue 8
https://doi.org/10.5194/nhess-21-2611-2021
https://doi.org/10.5194/nhess-21-2611-2021
Research article
 | 
26 Aug 2021
Research article |  | 26 Aug 2021

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

Sang-Guk Yum, Hsi-Hsien Wei, and Sung-Hwan Jang

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Cited articles

Bardsley, E.: The Weibull distribution as an extreme value model for transformed annual maxima, J. Hydrol., 58, 57–63, 2019. 
Bermúdez, M., Cea, L., and Sopelana, J.: Quantifying the role of individual flood drivers and their correlations in flooding of coastal river reaches, Stoch. Environ. Res. Risk A., 33, 1851–1861, 2019. 
Bommier, E.: Peaks-Over-Threshold Modelling of Environmental Data, Department of Mathematics, Uppsala University, Uppsala, 2014. 
Buchana, P. and McSharry, P. E.: Windstorm risk assessment for offshore wind farms in the North Sea, Wind Energy, 22, 1219–1229, 2019. 
Catalano, A. J., Broccoli, A. J., Kapnick, S. B., and Janoski, T. P.: High-Impact Extratropical Cyclones along the Northeast Coast of the United States in a Long Coupled Climate Model Simulation, J. Climate, 32, 2131–2143, 2019. 
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Developed statistical models to predict the non-exceedance probability of extreme storm surge-induced typhoons. Various probability distribution models were applied to find the best fitting to empirical storm-surge data.
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