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Regional Rainfall Frequency Analysis by Multivariate Techniques

다변량 분석 기법을 활용한 강우 지역빈도해석

  • 남우성 (연세대학교 대학원 토목공학과) ;
  • 김태순 (연세대학교 사회환경시스템공학부 BK21) ;
  • 신주영 (연세대학교 대학원 토목공학과) ;
  • 허준행 (연세대학교 사회환경시스템공학부)
  • Published : 2008.05.25

Abstract

Regional rainfall quantile depends on the identification of hydrologically homogeneous regions. Various variables relevant to precipitation can be used to form regions. Since the type and number of variables may lead to improve the efficiency of partitioning, it is important to select those precipitation related variables, which represent most of the information from all candidate variables. Multivariate analysis techniques can be used for this purpose. Procrustes analysis which can decrease the dimension of variables based on their correlations, are applied in this study. 42 rainfall related variables are decreased into 21 ones by Procrustes analysis. Factor analysis is applied to those selected variables and then 5 factors are extracted. Fuzzy-c means technique classifies 68 stations into 6 regions. As a result, the GEV distributions are fitted to 6 regions while the lognormal and generalized logistic distributions are fitted to 5 regions. For the comparison purpose with previous results, rainfall quantiles based on generalized logistic distribution are estimated by at-site frequency analysis, index flood method, and regional shape estimation method.

지역빈도해석을 통한 확률강우량 산정 결과는 수문학적으로 동질한 지역의 구분 결과에 따라 달라진다. 지역을 구분할 때에는 강우에 영향을 미치는 다양한 변수들이 사용될 수 있다. 변수의 유형과 개수가 지역 구분의 효율성을 좌우하기 때문에 활용 가능한 모든 변수들의 정보를 요약할 수 있는 변수들을 선택하는 것이 지역 구분의 효율성 면에서 유리하다고 할 수 있다. 이런 면에서 지역 구분의 효율성을 증대시킬 목적으로 다변량 분석 기법이 활용될 수 있다. 본 연구에서는 변수들 간의 상관관계를 바탕으로 모든 변수가 표현하는 정보를 대표할 수 있는 더 적은 수의 변수를 선정하는 기법으로 Procrustes analysis를 활용하였다. 이 기법을 활용하여 42개의 강우 관련 변수들을 21개로 줄일 수 있었다. 선정된 변수들을 바탕으로 요인분석을 수행하여 5개의 요인을 추출하였고, 이를 근거로 군집해석 기법인 fuzzy-c means 기법을 활용하여 지역을 구분하였다. 68개 강우 관측 지점을 대상으로 지역을 구분한 결과 6개의 지역으로 구분되었다. 6개의 지역에서 GEV 분포가 적합한 것으로 나타났고, 3변수 대수정규 분포와 generalized logistic 분포가 5개 지역에서 적합한 것으로 나타났다. 기존 연구 결과와의 비교를 위해 generalized logistic 분포를 바탕으로 지점빈도해석, 홍수지수법, 지역형상추정법을 적용하여 확률강우량을 산정하였다.

Keywords

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