대한토목학회논문집 (KSCE Journal of Civil and Environmental Engineering Research)

  • 제33권5호
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  • Pages.1809-1827
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  • 2013
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  • 1015-6348(pISSN)
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  • 2799-9629(eISSN)
대한토목학회 (Korean Society of Civil Engeneers)
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자료기반 실시간 홍수예측 모형의 비교·검토

Comparison of Data-based Real-Time Flood Forecasting Model

  • 최현구 (경북대학교 방재연구소) ;
  • 한건연 (경북대학교 건축.토목공학부) ;
  • 노홍식 (경북대학교 건축.토목공학부) ;
  • 박세진 (경북대학교 건축.토목공학부)
  • 투고 : 2013.02.15
  • 심사 : 2013.07.03
  • 발행 : 2013.09.30
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초록

기후변화로 인해 발생하는 이상홍수에 대비하기 위해서는 다양한 대책을 강구할 필요가 있다. 그 중 비구조적 대책으로 홍수예경보시스템을 구축하여 홍수에 대비할 수 있도록 하는 것이 중요하다. 본 연구의 목적은 실시간 홍수예측 시스템을 구축하기 위해 뉴로-퍼지 모형과 다중선형회귀 모형을 비교하여 우수한 실시간 홍수예측 모형을 개발하는데 있다. 이를 위해 같은 입력자료를 사용하여 뉴로-퍼지 모형과 다중선형회귀 모형을 구축하고 낙동강 유역의 다양한 홍수사상에 대해 적용하였다. 모의결과 뉴로-퍼지 모형이 다중선형회귀 모형보다 좀 더 나은 예측 결과를 나타내는 것을 확인할 수 있었다. 본 연구는 향후 낙동강 유역의 충분한 선행시간을 확보한 정확도 높은 홍수정보시스템의 구축에 활용할 수 있을 것으로 판단된다.

Recently we need to take various measures to prepare for extreme flood that occur due to climate change. It is important that establish flood forecasting system to prepare flood over non-structure measures. The objective of this study is to develop superior real-time flood forecasting model by comparing the Neuro-fuzzy model and the multiple linear regression model. The Neuro-fuzzy model and the multiple linear regression model are established using same input data and applied for various flood events in Nakdong basin. The results show that the Neuro-fuzzy model can carry out flood forecasting results more accurately than the multiple linear regression model. This study can contribute to the establishment of a high accuracy flood information system that secure lead time in Nakdong basin.

키워드

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