한국수자원학회논문집 (Journal of Korea Water Resources Association)

  • 제52권12호
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  • Pages.985-999
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  • 2019
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  • 2799-8746(pISSN)
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  • 2799-8754(eISSN)
한국수자원학회 (Korea Water Resources Association)
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Copula 함수를 이용한 이변량 가뭄 지역빈도해석 모형 개발

A development of bivariate regional drought frequency analysis model using copula function

  • 김진국 (세종대학교 건설환경공학과) ;
  • 김진영 ((주)이산 수자원부) ;
  • 반우식 (K-water 한강권역부문 한강처 물관리센터) ;
  • 권현한 (세종대학교 건설환경공학과)
  • Kim, Jin-Guk (Department of Civil and Environmental Engineering, Sejong University) ;
  • Kim, Jin-Young (Water Management Division, ISAN Corporation) ;
  • Ban, Woo-Sik (Hangang Regional Head Office Regional Water Resources Management Department, K-water) ;
  • Kwon, Hyun-Han (Department of Civil and Environmental Engineering, Sejong University)
  • 투고 : 2019.10.06
  • 심사 : 2019.11.20
  • 발행 : 2019.12.31
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초록

전 세계적으로 극심한 가뭄현상이 반복적으로 발생하고 있으며, 이러한 가뭄을 분석하기 위한 연구가 다수 진행되고 있다. 최근 코플라 함수를 활용한 이변량 가뭄빈도해석에 대한 연구가 다수 진행된 바 있으나, 대부분 지점빈도해석에 국한되어 진행되었으며, 통계적으로 부족한 자료의 기간을 보완하기 위한 대안으로 지역빈도해석 개념을 도입한 연구는 미진한 실정이다. 이러한 점에서 본 연구에서는 기존의 베이지안 기법과 코플라 함수를 연계한 이변량 지역빈도해석 모형을 개발하였다. 최종적으로 이변량 코플라 가뭄 지역빈도해석 모형을 한강유역에 적용하여 2013-2015년에 발생한 가뭄 사상을 평가하였으며, 기존에 개발된 이변량 지점빈도해석 결과와 비교를 통해 모형의 해석결과에 대한 신뢰성을 확보하였다. 결과적으로 이변량 지점빈도해석에 비해 가뭄사상에 대한 결합재현기간의 불확실성 구간이 약 3배 가까이 감소하였으며, DIC 통계량 산정결과 약 15 이상 개선된 것을 확인하였다. 본 연구를 통해 제안된 베이지안 코플라 기반 이변량 가뭄 지역빈도해석 모형은 가뭄자료의 분포특성 및 자료간의 상관성을 효과적으로 재현하는데 유리할 뿐만 아니라, 지역적인 가뭄특성을 효과적으로 평가할 수 있는 장점을 확인할 수 있었다.

Over the last decade, droughts have become more severe and frequent in many regions, and several studies have been conducted to explore the recent drought. Copula-based bivariate drought frequency analysis has been widely used to evaluate drought risk in the context of point frequency analysis. However, the relatively significant uncertainties in the parameters are problematic when available data are limited. For this reason, the primary purpose of this study is to develop a regional drought frequency model based on the Copula function. All parameters, including marginal and copula functions in the regional frequency model, were estimated simultaneously. Here, we present a case study of recent drought 2013-2015 over the Han-River watershed where severe drought risk is consistently found to increase. The proposed model provided a reliable way to significantly reduce the uncertainty of parameters with a Bayesian modeling framework. The uncertainty of the joint return period in the regional frequency analysis is nearly three times lower than that of the point frequency analysis. Accordingly, DIC values in the regional frequency analysis model are significantly decreased by 15. The results confirm that the proposed model is not only reliably representing characteristics of historical droughts and dependencies between drought variables, but also providing the efficacy of understanding regional drought characteristics.

키워드

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