Journal of Wetlands Research (한국습지학회지)

Korean Wetlands Society (한국습지학회)
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A Study on Application of Very Short-range-forecast Rainfall for the Early Warning of Mud-debris Flows

토사재해 예경보를 위한 초단기 예측강우의 활용에 대한 연구

  • Jun, Hwandon (Department of Civil Engineering, Seoul National University of Science and Technology) ;
  • Kim, Soojun (Department of Civil Engineering, Inha university)
  • 전환돈 (서울과학기술대학교 건설시스템공학과) ;
  • 김수전 (인하대학교 토목공학과)
  • Received : 2017.07.31
  • Accepted : 2017.08.23
  • Published : 2017.08.31
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Abstract

The objective of this study is to explore the applicability of very short-range-forecast rainfall for the early warning of mud-debris flows. An artificial neural network was applied to use the very short-range-forecast rainfall data. The neural network is learned by using the relationship between the radar and the AWS, and forecasted rainfall is estimated by replacing the radar rainfall with the MAPLE data as the very short-range-forecast rainfall data. The applicability of forecasted rainfall by the MAPLE was compared with the AWS rainfall at the test-bed using the rainfall criteria for cumulative rainfall of 6hr, 12hr, and 24hr respectively. As a result, it was confirmed that forecasted rainfall using the MAPLE can be issued prior to the AWS warning.

본 연구의 목적은 토사재해 예경보를 위하여 초단기 예측강우의 적용성을 검토하는 것이다. 초단기 예측자료를 활용하기 위한 방법으로 신경망 모형을 적용하였다. 여기에서 레이더와 AWS의 관계를 이용하여 신경망을 학습하고 레이더 강우를 초단기 예측강우(MAPLE)로 대체하여 대상지역에 대한 강우량을 예측하였다. 6hr, 12hr, 24hr의 누적강우에 대한 토사재해 예경보기준을 이용하여 MAPLE 예측강우의 적용성을 Test-bed 지점에 설치한 AWS 강우량과 비교 평가하였다. 평가결과 MAPLE 예측강우를 이용할 경우 AWS를 이용할 경우 보다 선행하여 토사재해 예경보를 발령할 수 있음을 확인하였다.

Keywords

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