A Study on Multi-site Rainfall Prediction Model using Real-time Meteorological Data

실시간 기상자료를 이용한 다지점 강우 예측모형 연구

  • Jung, Jae-Sung (Dam Mangement Division, Korea Water Resources Corporation) ;
  • lee, Jang-Choon (Dept. of Civil Engineering, lri National College of Agriculture and Technolgy) ;
  • Park, Young-Ki (Dept. of Civil Engineering, lri National College of Agriculture and Technolgy)
  • 정재성 (한국수자원공사 댐관리처) ;
  • 이장춘 (이리농공전문대학 토목공학과) ;
  • 박영기 (이리농공전문대학 토목공학과)
  • Published : 1997.06.01

Abstract

For the prediction of multi-site rainfall with radar data and ground meteorological data, a rainfall prediction model was proposed, which uses the neural network theory, a kind of artifical Intelligence technique. The Input layer of the prediction model was constructed with current ground meteorological data, their variation, moving vectors of rain- fall field and digital terrain of the measuring site, and the output layer was constructed with the predicted rainfall up to 3 hours. In the application of the prediction model to the Pyungchang river basin, the learning results of neural network prediction model showed more Improved results than the parameter estimation results of an existing physically based model. And the proposed model comparisonally well predicted the time distribution of ralnfall.

Keywords

References

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