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Estimation of ESP Probability considering Weather Outlook

기상예보를 고려한 ESP 유출 확률 산정

  • Ahn, Jung Min (Korea Institute of Water and Environment, Korea Water Resources Corporation) ;
  • Lee, Sang Jin (Korea Institute of Water and Environment, Korea Water Resources Corporation) ;
  • Kim, Jeong Kon (Korea Institute of Water and Environment, Korea Water Resources Corporation) ;
  • Kim, Joo Cheol (Korea Institute of Water and Environment, Korea Water Resources Corporation) ;
  • Maeng, Seung Jin (Department of Agricultural and Rural Engineering, Chungbuk National University) ;
  • Woo, Dong Hyeon (Korea Institute of Water and Environment, Korea Water Resources Corporation)
  • 안정민 (한국수자원공사 K-water연구원) ;
  • 이상진 (한국수자원공사 K-water연구원) ;
  • 김정곤 (한국수자원공사 K-water연구원) ;
  • 김주철 (한국수자원공사 K-water연구원) ;
  • 맹승진 (충북대학교 지역건설공학과) ;
  • 우동현 (한국수자원공사 K-water연구원)
  • Received : 2011.01.12
  • Accepted : 2011.04.14
  • Published : 2011.05.30

Abstract

The objective of this study was to develop a model for predicting long-term runoff in a basin using the ensemble streamflow prediction (ESP) technique and review its reliability. To achieve the objective, this study improved not only the ESP technique based on the ensemble scenario analysis of historical rainfall data but also conventional ESP techniques used in conjunction with qualitative climate forecasting information, and analyzed and assessed their improvement effects. The model was applied to the Geum River basin. To undertake runoff forecasting, this study tried three cases (case 1: Climate Outlook + ESP, case 2: ESP probability through monthly measured discharge, case 3: Season ESP probability of case 2) according to techniques used to calculate ESP probabilities. As a result, the mean absolute error of runoff forecasts for case 1 proposed by this study was calculated as 295.8 MCM. This suggests that case 1 showed higher reliability in runoff forecasting than case 2 (324 MCM) and case 3 (473.1 MCM). In a discrepancy-ratio accuracy analysis, the Climate Outlook + ESP technique displayed 50.0%. This suggests that runoff forecasting using the Climate Outlook +ESP technique with the lowest absolute error was more reliable than other two cases.

Keywords

References

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