응용통계연구 (The Korean Journal of Applied Statistics)

  • 제27권6호
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  • Pages.947-958
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  • 2014
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  • 1225-066X(pISSN)
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  • 2383-5818(eISSN)
한국통계학회 (The Korean Statistical Society)
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한국지역 집중호우에 대한 반환주기의 베이지안 모형 분석

A Bayesian Analysis of Return Level for Extreme Precipitation in Korea

  • Lee, Jeong Jin (Department of Statistics, Kyungpook National University) ;
  • Kim, Nam Hee (Department of Statistics, Kyungpook National University) ;
  • Kwon, Hye Ji (Statistics Korea) ;
  • Kim, Yongku (Department of Statistics, Kyungpook National University)
  • 투고 : 2014.07.29
  • 심사 : 2014.08.29
  • 발행 : 2014.12.31
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초록

집중호우의 특성을 이해하는 것은 수문관리 및 재해방재 등에서 매우 중요하다. 특히 반환주기는 이러한 집중호우의 특성을 나타내는 측정치로 자주 사용된다. 본 논문에서는 베이지안 계층적 모형을 이용하여 강우의 반환주기에 대한 공간구조를 분석하였다. 먼저 국내 62개 지점에서 측정한 강우 강도을 기초로 하여 연간 일일 최대강우량과 특정한 수준을 초과하는 강우량에 대해서 generalized extreme value(GEV)와 generalized Pareto distribution(GPD)를 각각 가정하여 추정하였다. 집중호우 반환주기에 대한 공간구조는 이 GEV 분포와 GPD 분포의 모수에 공간구조를 가지는 다변량 정규분포를 이용하여 설명하였다. 제안된 모형을 국내 76개 지역에서 39년간 측정된 일별 강우량 관측자료에 적용하였다.

Understanding extreme precipitation events is very important for flood planning purposes. Especially, the r-year return level is a common measure of extreme events. In this paper, we present a spatial analysis of precipitation return level using hierarchical Bayesian modeling. For intensity, we model annual maximum daily precipitations and daily precipitation above a high threshold at 62 stations in Korea with generalized extreme value(GEV) and generalized Pareto distribution(GPD), respectively. The spatial dependence among return levels is incorporated to the model through a latent Gaussian process of the GEV and GPD model parameters. We apply the proposed model to precipitation data collected at 62 stations in Korea from 1973 to 2011.

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참고문헌

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