Journal of Korea Water Resources Association (한국수자원학회논문집)

Korea Water Resources Association (한국수자원학회)
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A development of nonstationary rainfall frequency analysis model based on mixture distribution

혼합분포 기반 비정상성 강우 빈도해석 기법 개발

  • Choi, Hong-Geun (Department of Civil and Environmental Engineering, Sejong University) ;
  • Kwon, Hyun-Han (Department of Civil and Environmental Engineering, Sejong University) ;
  • Park, Moon-Hyung (Korea Institute of Construction Technology)
  • 최홍근 (세종대학교 건설환경공학과) ;
  • 권현한 (세종대학교 건설환경공학과) ;
  • 박문형 (한국건설기술연구원)
  • Received : 2019.08.07
  • Accepted : 2019.10.07
  • Published : 2019.11.30
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Abstract

It has been well recognized that extreme rainfall process often features a nonstationary behavior, which may not be effectively modeled within a stationary frequency modeling framework. Moreover, extreme rainfall events are often described by a two (or more)-component mixture distribution which can be attributed to the distinct rainfall patterns associated with summer monsoons and tropical cyclones. In this perspective, this study explores a Mixture Distribution based Nonstationary Frequency (MDNF) model in a changing rainfall patterns within a Bayesian framework. Subsequently, the MDNF model can effectively account for the time-varying moments (e.g. location parameter) of the Gumbel distribution in a two (or more)-component mixture distribution. The performance of the MDNF model was evaluated by various statistical measures, compared with frequency model based on both stationary and nonstationary mixture distributions. A comparison of the results highlighted that the MDNF model substantially improved the overall performance, confirming the assumption that the extreme rainfall patterns might have a distinct nonstationarity.

극치 강우 자료는 정상성 빈도모델에서 효과적으로 구현되지 않는 비정상성 거동을 종종 보인다. 또한, 극치 사상의 확률밀도함수는 여름 장마와 태풍 등의 서로 다른 강우 패턴에 의해 2개 이상의 첨두를 가지는 혼합분포형태이다. 이러한 강우 패턴의 변화에 대해 Bayesian 이론을 활용한 비정상성 혼합분포(mixture distribution based nonstationary frequency, MDNF)모델을 제안하였다. 2개의 Gumbel 분포형이 혼합된 MDNF 모델은 Gumbel 분포형 매개변수 중 하나인 위치매개변수의 시변성을 효과적으로 설명한다. 제안한 모델의 성능평가를 위해 정상성 혼합분포모델과의 다양한 통계치 결과를 비교하였다. 정상성 혼합분포모델보다 전반적으로 향상된 성능을 보여주는 MDNF 모델을 통해 극치 강우 패턴이 비정상성을 보인다는 가정을 확인할 수 있다.

Keywords

References

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