한국방재학회 논문집 (Journal of the Korean Society of Hazard Mitigation)

  • 제13권3호
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  • Pages.147-156
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  • 2013
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  • 1738-2424(pISSN)
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  • 2287-6723(eISSN)
한국방재학회 (Korean Society of Hazard Mitigation)
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비정상성 GEV 모형을 이용한 행정구역별 미래 확률강우량 산정

Estimation of Future Design Rainfalls in Administrative Districts Using Nonstationary GEV Model

  • 신지예 (한양대학교 대학원 건설환경공학과) ;
  • 박예준 (한양대학교 대학원 건설환경공학과) ;
  • 김태웅 (한양대학교 공학대학 건설환경플랜트공학과)
  • Shin, Ji Yae (Department of Civil and Environmental Engineering, Hanyang University) ;
  • Park, Yei Jun (Department of Civil and Environmental Engineering, Hanyang University) ;
  • Kim, Tae-Woong (Department of Civil and Environmental Engineering, Hanyang University)
  • 투고 : 2013.03.12
  • 심사 : 2013.05.21
  • 발행 : 2013.06.30
⟨ 이전 논문 다음 논문 ⟩

초록

국내에서는 설계강우량을 산정하기 위해서 정상성 강우빈도해석법이 일반적으로 적용되고 있다. 그러나, 기후변화 또는 기후 변동으로 인한 극치사상의 증가 등으로 최근의 강우패턴은 과거와는 다른 양상을 보여주고 있으며, 이러한 경향은 수문학적 설계를 위한 확률강우량 산정에 고려될 필요가 있다. 본 연구에서는 행정구역별 비정상성 강우빈도해석을 수행하였다. 이를 위하여 1973년부터 2012년까지 관측된 지점강우량을 이용하여 행정구역별 연최대강우량 자료를 구축하였다. 25년 이동평균방법으로 관측자료의 통계량과 GEV 분포함수의 모수 사이의 상관성을 검토한 후, 미래 특정 시점에 대한 분포함수의 모수를 추정할 수 있는 비선형 회귀식을 유도하였다. 본 연구에서 제시한 방법은 관측된 연최대강우량에 대하여 검증을 하였으며, 강우패턴의 변화를 정상성 강우빈도해석법에 비해 보다 적절히 반영하는 것으로 나타났다. 따라서, 본 연구에서 제시하는 행정구역별 비정상성 강우빈도해석법은 가까운 미래의 확률강우량 산정과 최근에 도입된 행정구역별 방재성능 목표강우량 산정에 유용할 것으로 판단된다.

In South Korea, stationary frequency analysis methods are generally used for estimating design rainfalls in practice. However, due to climate change and/or variability, recent rainfall observations have significantly different patterns from the past so that the recent trends need to be considered to estimate extreme rainfall quantiles for hydrologic design. This study focused on estimating extreme rainfall quantiles in administrative districts across South Korea, after building nonstationary GEV model using annual maximum rainfall (AMR) datasets for 228 administrative districts from point rainfall measures from 1973 to 2012. A moving average method with 25-year window was used for investigating time-dependent statistics of AMR, such as mean, variance and skewness, and parameters of GEV distribution. From the analyses of relationships between statistics and distribution parameters, this study derived nonlinear regression equations for distribution parameters, which provide the estimates of distribution parameters at any future time. The overall results achieved in this study illustrate that the nonlinear regression equations can be easily incorporated into the hydrologic frequency analysis and provide appropriate estimates of design rainfalls in the near future.

키워드

과제정보

연구 과제 주관 기관 : 한국연구재단

참고문헌

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피인용 문헌

  1. Flood Frequency Analysis Considering Probability Distribution and Return Period under Non-stationary Condition vol.48, pp.7, 2015, https://doi.org/10.3741/JKWRA.2015.48.7.567
  2. Estimation of Future Design Flood Under Non-Stationarity for Wonpyeongcheon Watershed vol.57, pp.5, 2015, https://doi.org/10.5389/KSAE.2015.57.5.139
  3. Nonstationary Probability Rainfall Estimation at Seoul Using Neural Networks and GCM Data vol.18, pp.2, 2018, https://doi.org/10.9798/KOSHAM.2018.18.2.63