Journal of Korea Water Resources Association (한국수자원학회논문집)

Korea Water Resources Association (한국수자원학회)
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Frequency analysis of storm surge using Poisson-Generalized Pareto distribution

Poisson-Generalized Pareto 분포를 이용한 폭풍해일 빈도해석

  • Kim, Tae-Jeong (Department of Civil Engineering, Chonbuk National University) ;
  • Kwon, Hyun-Han (Department of Civil and Environmental Engineering, Sejong University) ;
  • Shin, Young-Seok (Department of Information & Communication Engineering, Honam University)
  • 김태정 (전북대학교 토목공학과 방재연구센터) ;
  • 권현한 (세종대학교 건설환경공학과) ;
  • 신영석 (호남대학교 정보통신공학과)
  • Received : 2018.12.17
  • Accepted : 2019.01.15
  • Published : 2019.03.31
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Abstract

The Korean Peninsula is considered as one of the most typhoon related disaster prone areas. In particular, the potential risk of flooding in coastal areas would be greater when storm surge and heavy rainfall occurred at the same time. In this context, understanding the mechanism of the interactions between them and estimating the risk associated with the concurrent occurrence are of particular interests especially in low-lying coastal areas. In this study, we developed a Poisson-Generalized Pareto (Poisson-GP) distribution based storm surge frequency analysis model to combine the occurrence of the exceedance of a threshold, that is the peaks over threshold (POT), within a Bayesian framework. The storm surge frequency analysis technique developed through this study might contribute to the improvement of disaster prevention technology related to storm surge in the coastal area.

한반도는 지형학적 요건으로 인하여 태풍과 관련된 재난이 매년 발생하여 막대한 피해를 유발하고 있다. 태풍 내습시 폭풍해일과 집중호우가 동시에 발생한다면 해안지역의 침수피해는 더욱 증가할 것으로 사료된다. 이러한 관점에서 태풍과 폭풍해일의 상호의존성을 정량적으로 규명하는 것은 해안지역의 재해분석에 필수적이다. 본 연구에서는 Bayesian 기법을 기반으로 절점기준을 초과하는 임계값의 초과확률을 산정하기 위하여 Poisson 분포와 Generalized-Pareto 분포를 이용한 Poisson-GP 폭풍해일 빈도해석 기법을 개발하였다. 본 연구를 통하여 개발된 Poisson-GP 폭풍해일 빈도해석 기법은 설계해수면의 불확실성을 정량적으로 제시하였으며 해안지역의 폭풍해일 관련 방재기술 향상에 기여할 것으로 판단된다.

Keywords

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Fig. 1. Flow diagram of the storm surge frequency analysis

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Fig. 2. Locations of sea level stations by Korea hydrographic and oceanographic agency

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Fig. 3. The number of typhoons and its trend during the period of 1987∼2016

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Fig. 4. Time series of low pressure of typhoons during the period 1987∼2016

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Fig. 5. Design storm surge level and its uncertainty over all stations

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Fig. 5. Design storm surge level and its uncertainty over all stations (Continue)

Table 1. Sea Level observatory used in this study

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Table 2. The yearly number of typhoons, with number affecting the Korean peninsula in parentheses

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Table 4. Significance test results of storm surge data set

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Table 3. Sea level stations used in this study (unit: cm)

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Table 6. Estimated scale parameter (σ) of the GP distribution and its credible bounds

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Table 7. Estimated shape parameter (ξ) of the GP distribution and its credible bounds

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Table 5. Estimated parameter (λ) of the Poisson distribution and its uncertainty bounds

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