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Concept of Trend Analysis of Hydrologic Extreme Variables and Nonstationary Frequency Analysis

극치수문자료의 경향성 분석 개념 및 비정상성 빈도해석

  • Received : 2010.02.24
  • Accepted : 2010.07.01
  • Published : 2010.08.31

Abstract

This study introduced a Bayesian based frequency analysis in which the statistical trend analysis for hydrologic extreme series is incorporated. The proposed model employed Gumbel extreme distribution to characterize extreme events and a fully coupled bayesian frequency model was finally utilized to estimate design rainfalls in Seoul. Posterior distributions of the model parameters in both Gumbel distribution and trend analysis were updated through Markov Chain Monte Carlo Simulation mainly utilizing Gibbs sampler. This study proposed a way to make use of nonstationary frequency model for dynamic risk analysis, and showed an increase of hydrologic risk with time varying probability density functions. The proposed study showed advantage in assessing statistical significance of parameters associated with trend analysis through statistical inference utilizing derived posterior distributions.

본 논문에서는 극치수문자료의 경향성 분석 개념을 소개하고 이를 빈도해석과 연계시켜 해석하는 방법론을 제시하고자 Gumbel 극치분포를 기반으로, 시간변화에 의한 수문빈도 특성 변화를 모의할 수 있는 Bayesian 모형을 구성하였다. 사후분포의 매개변수는 깁스표본법에 의한 Markov Chain Monte Carlo Simulation을 통해 추정하였으며, 이를 통해 경향성을 고려한 확률강우량과 불확실성 구간을 추정하였다. 또한 경향성을 고려한 확률강우량이 현재 알려진 확률강우량을 초과할 확률을 통해 동적 위험도 해석과정을 소개하였으며, 현재의 경향성에 대해서 시간에 따라 연속으로 추정된 확률밀도함수를 비교하여 수문학적 위험도가 증가할 수 있음을 모의결과를 통해 확인하였다. 이와 더불어 단순히 경향성의 존재여부를 확인하는데 그치지 않고 사후분포를 통해서 통계적 추론을 수행함으로써 경향성에 대한 통계학적인 유의성을 정량적으로 평가할 수 있었다.

Keywords

References

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