한국수자원학회논문집 (Journal of Korea Water Resources Association)

  • 제49권11호
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  • Pages.913-922
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  • 2016
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  • 2799-8746(pISSN)
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  • 2799-8754(eISSN)
한국수자원학회 (Korea Water Resources Association)
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Neyman-Scott Rectangular Pulse 모형 기반의 다지점 강수모의 기법 개발

A development of multisite hourly rainfall simulation technique based on neyman-scott rectangular pulse model

  • 문장원 (서울시립대학교 토목공학과) ;
  • 김장경 (전북대학교 토목공학과) ;
  • 문영일 (서울시립대학교 토목공학과) ;
  • 권현한 (전북대학교 토목공학과)
  • Moon, Jangwon (Department of Civil Engineering, University of Seoul) ;
  • Kim, Janggyeong (Department of Civil Engineering, Chonbuk National University) ;
  • Moon, Youngil (Department of Civil Engineering, University of Seoul) ;
  • Kwon, Hyunhan (Department of Civil Engineering, Chonbuk National University)
  • 투고 : 2016.09.04
  • 심사 : 2016.09.20
  • 발행 : 2016.11.30
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초록

유역의 신뢰성 있는 수자원계획을 수립하기 위해서는 장기간의 강수자료가 필수적으로 요구된다. 그러나 시간강수시계열의 경우 결측치가 상대적으로 많으며, 연속적인 시계열을 확보하는데 어려움이 있다. 이러한 점에서 본 연구에서는 대표적인 시간강수모의기법인 Neyman-Scott Rectangular Pulse Model (NSRPM) 기반의 강수모의기법을 활용하여, 모의기반의 장기강수자료를 생산할 수 있는 기법을 개발하고자 한다. 이와 더불어, 신뢰성 있는 면적강수량을 추정하기 위한 방안으로 유역 내 여러 지점의 강수량을 동시에 모의할 수 있는 다지점 시간강수모의기법을 개발하였다. 개발된 모형은 서울 우이천 유역 강수지점에 적용하여 모형의 적합성을 평가하였다. 모형 적용결과 다양한 지속시간에 대해서 강수량의 효과적인 모의(평균, 분산, 1차 자기상관계수)가 가능하였으며, 지점간의 공간성도 효과적으로 복원 가능하였다.

A long-term precipitation record is typically required for establishing the reliable water resources plan in the watershed. However, the observations in the hourly precipitation data are not always consistent and there are missing values within the time series. This study aims to develop a hourly rainfall simulator for extending rainfall data, based on the well-known Neyman-Scott Rectangular Pulse Model (NSRPM). Moreover, this study further suggests a multisite hourly rainfall simulator to better reproduce areal rainfalls for the watershed. The proposed model was validated with a network of five weather stations in the Uee-stream watershed in Seoul. The proposed model appeared a reasonable result in terms of reproducing most of the statistics (i.e. mean, variance and lag-1 autocovariance) of the rainfall time series at various aggregation levels and the spatial coherence over the weather stations.

키워드

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