한국수자원학회논문집 (Journal of Korea Water Resources Association)

  • 제54권10호
  • /
  • Pages.747-757
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  • 2021
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  • 2799-8746(pISSN)
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  • 2799-8754(eISSN)
한국수자원학회 (Korea Water Resources Association)
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기후정보와 지리정보를 결합한 계층적 베이지안 모델링을 이용한 재현기간별 일 강우량의 공간 분포 및 불확실성

Spatial distribution and uncertainty of daily rainfall for return level using hierarchical Bayesian modeling combined with climate and geographical information

  • 이정훈 (부경대학교 환경공학과) ;
  • 이옥정 (K-water 유역물관리연구소 수자원연구팀) ;
  • 서지유 (부경대학교 지구환경시스템과학부 환경공학전공) ;
  • 김상단 (부경대학교 환경공학과)
  • Lee, Jeonghoon (Department of Environmental Engineering, Pukyong National University) ;
  • Lee, Okjeong (Water Resources Management Research Center, K-water Research Institute) ;
  • Seo, Jiyu (Division of Earth Environmental System Science (Major of Environmental Engineering), Pukyong National University) ;
  • Kim, Sangdan (Department of Environmental Engineering, Pukyong National University)
  • 투고 : 2021.05.11
  • 심사 : 2021.07.26
  • 발행 : 2021.10.31
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초록

극한 강우의 정량화는 홍수방어계획의 수립에 대단히 중요하며 극한 강우의 일반적인 척도는 T-년 재현기간으로 표현된다. 본 연구에서는 기후정보와 지리정보가 결합된 계층적 베이지안 모형을 이용하여 재현기간별 일 강우량의 공간 분포 및 불확실성을 추정하는 방법을 제시하고 이를 서울-인천-경기 지역에 적용하였다. 한국 기상청에서 운영 중인 서울-인천-경기 지역의 6개 종관기상관측소의 연 최대 일 강우량이 일반화된 극치 분포에 적합되었다. 지점 빈도해석과 지수 홍수법을 이용한 지역 빈도해석으로부터 도출된 재현기간별 일 강우량과의 비교를 통하여 제안된 방법의 적용성 및 신뢰도를 살펴보았다. 모든 지점과 모든 재현기간에서 지수홍수법에 의한 지역 빈도해석의 불확실성이 가장 큰 것으로 나타났으며, 계층적 베이지안 모형에 의한 지역 빈도해석의 신뢰도가 가장 높은 것을 확인하였다. 제안된 방법은 서울-인천-경기 지역 및 공간적인 크기가 유사한 다른 지역에서 다양한 지속기간에 대한 확률강우량 지도를 생성하는데 사용될 수 있을 것이다.

Quantification of extreme rainfall is very important in establishing a flood protection plan, and a general measure of extreme rainfall is expressed as an T-year return level. In this study, a method was proposed for quantifying spatial distribution and uncertainty of daily rainfall depths with various return periods using a hierarchical Bayesian model combined with climate and geographical information, and was applied to the Seoul-Incheon-Gyeonggi region. The annual maximum daily rainfall depth of six automated synoptic observing system weather stations of the Korea Meteorological Administration in the study area was fitted to the generalized extreme value distribution. The applicability and reliability of the proposed method were investigated by comparing daily rainfall quantiles for various return levels derived from the at-site frequency analysis and the regional frequency analysis based on the index flood method. The uncertainty of the regional frequency analysis based on the index flood method was found to be the greatest at all stations and all return levels, and it was confirmed that the reliability of the regional frequency analysis based on the hierarchical Bayesian model was the highest. The proposed method can be used to generate the rainfall quantile maps for various return levels in the Seoul-Incheon-Gyeonggi region and other regions with similar spatial sizes.

키워드

과제정보

본 연구는 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행되었음 (NRF-2019R1A2C1003114).

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