Journal of Korea Water Resources Association (한국수자원학회논문집)

Korea Water Resources Association (한국수자원학회)
권호 표지
DOI QR코드

DOI QR Code

Improvement of the Ensemble Streamflow Prediction System Using Optimal Linear Correction

최적선형보정을 이용한 앙상블 유량예측 시스템의 개선

  • Jeong, Dae-Il (School of Civil, Urban & Geosystem Engrg., Seoul National Univ.) ;
  • Lee, Jae-Kyoung (School of Civil, Urban & Geosystem Engrg., Seoul National Univ.) ;
  • Kim, Young-Oh (School of Civil, Urban & Geosystem Engrg., Seoul National Univ.)
  • 정대일 (서울대학교 지구환경시스템공학부) ;
  • 이재경 (서울대학교 지구환경시스템공학부) ;
  • 김영오 (서울대학교 지구환경시스템공학부)
  • Published : 2005.06.01
Download PDF
⟨ Previous Next ⟩

Abstract

A monthly Ensemble Streamflow Prediction (ESP) system was developed by applying a daily rainfall-runoff model known as the Streamflow Synthesis and Reservoir Regulation (SSARR) model to the Han, Nakdong, and Seomjin River basins in Korea. This study first assesses the accuracy of the averaged monthly runoffs simulated by SSARR for the 3 basins and proposes some improvements. The study found that the SSARR modeling of the Han and Nakdong River basins tended to significantly underestimate the actual runoff levels and the modeling of the Seomjin River basinshowed a large error variance. However, by implementing optimal linear correction (OLC), the accuracy of the SSARR model was considerably improved in predicting averaged monthly runoffs of the Han and Nakdong River basins. This improvement was not seen in the modeling of the Seomjin River basin. In addition, the ESP system was applied to forecast probabilistic runoff forecasts one month in advance for the 3 river basins from 1998 to 2003. Considerably improvement was also achieved with OLC in probabilistic forecasting accuracy for the Han and Nakdong River basins, but not in that of the Seomjin River basin.

일단위 강우-유출모형인 SSARR모형을 이용하여 한강, 낙동강, 섬진강유역에 월 앙상블 유량예측 시스템을 구축하였다. 우선 SSARR모형의 월 평균 유출량에 대한 모의정확성을 평가한 결과 한강과 낙동강유역에서는 과소추정하는 경향이 뚜렷하였으며, 섬진강유역에서는 모의오차의 분산이 커 정확성 개선이 필요하였다. 최적선형 보정기법을 적용하여 SSARR모형의 모의유량을 보정한 결과, 섬진강을 제외한 한강과 낙동강유역의 검증지점에서는 모의 정확성이 크게 개선되었다. 또한 1998년부터 2003년까지 월 앙상블 유량예측을 실시하여 예측 정확성을 평가하였다. 한강과 낙동강유역에서 최적선형 보정기법을 이용할 경우 앙상블 유량예측 정확성이 크게 개선되었으나, 섬진강유역은 개선효과가 미비하였다.

Keywords

References

  1. 강주환 (1986). '강우-유출모형에 의한 가지야마 공식의 한계성 검토.' 석사학위논문, 서울대학교
  2. 건설교통부 (1989). 낙동강수계 다목적댐 연계운영방안 연구 (1차) 보고서
  3. 건설교통부 (1996). 낙동강 수계 실시간 최적 저수관리 시스템 개발
  4. 건설교통부 (2001). 낙동강수계 댐군 최적연계운영 시스템개선 연구 보고서
  5. 건설교통부 (2002). 연속유출모형 실용화 및 GUI구축
  6. 건설교통부 (2004). 유역통합 물관리를 위한 하천유출량 예측방안 연구
  7. 과학기술부 (2004). 실시간 물관리 운영시스템 구축 기술개발
  8. 안상진, 이용수 (1989). 'SSARR 모형에 의한 유역유출 해석.' 한국수문학회지, 한국수문학회, 제 22권, 제 1호, pp. 109-116
  9. 정대일, 김영오 (2002), '앙상블 예측을 이용한 충주댐 월 유입량 예측.' 대한토목학회 논문집, 대한토목학회, 제 22권, 제 3-B호, pp. 321-331
  10. 정대일, 김영오, 고익환 (2003). '앙상블 유량에측의 정확도 향상을 위한 강우-유출모형에 대한 연구: 2.강우-유출모형의 결합.' 대한토목학회 논문집, 대한토목학회, 제 23권, 제 6-B호, pp. 531-540
  11. 한국수자원공사 (2004). 다목적댐 운영실무 편람
  12. Atger, F. (2003). 'Spatial and interannual variability of reliability of ensemble-based probabilistic forecasts; Consequences for calibration.' Monthly Weather Review, Vol. 131, pp. 1509-1523 https://doi.org/10.1175//1520-0493(2003)131<1509:SAIVOT>2.0.CO;2
  13. Croley II, T.E. (2000). 'Using meteorology probability forecasts in operational hydrology' , ASCE Press, VA, USA
  14. Day, G.N. (1985). 'Extended streamflow forecasting using NWSRFS.' Journal of Water Resources Planning and Management, Vol. 111(WR2), pp. 147-170 https://doi.org/10.1061/(ASCE)0733-9496(1985)111:2(157)
  15. Georgakakos, K.P., Seo, D.J., Gupta, H. Schaake, J., and Butts, M.B. (2004). 'Towards the characterization of streamflow simulation uncertainty through multimodel ensembles.' Journal of Hydrology, Vol. 298, pp. 222-241 https://doi.org/10.1016/j.jhydrol.2004.03.037
  16. Goodwin, P. (2000). 'Correct or combine? Mechanically integrating judgmental forecasts with statistical methods.' International Journal of Forecasting, Vol. 16, pp. 261-275 https://doi.org/10.1016/S0169-2070(00)00038-8
  17. Kim, Y.-O., Jeong, D.I., and Ko, I.H. (2004). 'Combining rainfall runoff model outputs for improving ensemble streamflow prediction.' Journal of Hydrologic Engineering, ASCE, (submitted) https://doi.org/10.1061/(ASCE)1084-0699(2006)11:6(578)
  18. Kim, Y.-O., Jeong, D.I., and Kim, H.S. (2001). 'Improving water supply outlooks in Korea with ensemble streamflow prediction.' Water International, Vol. 26, No. 4, pp. 563-568 https://doi.org/10.1080/02508060108686957
  19. Murphy, A.H. and Winkler, R.L. (1987). 'A general framework for forecast verification.' Monthly Weather Review, Vol. 115, pp. 1330-1338 https://doi.org/10.1175/1520-0493(1987)115<1330:AGFFFV>2.0.CO;2
  20. Stedinger, J.R. and Kim, Y.-O. (2002). 'Updating ensemble probailities based on climate forecasts.' Proceedings Conference on Water Resorces Planning and Management and Symposium on Managing the Extremes Floods and Droughts, EWRI, ASCE, Roanoke, VA. CD
  21. Theil, H. (1971). 'Applied economic forecasting.' North Holland Publishing Company, Amsterdam, Netherlands
  22. Wilks, D.S. (1995). 'Forecast verification: Statistical methods in the Atmospheric Sciences.' Academic Press, NY, USA
  23. Wood, A.W., Maurer, E.P., Kumar, A., and Lettenmaier, D.P. (2002). 'Long-range experimental hydrologic forecasting for eastern United States.' Journal of Geophysical Research, Vol. 107, No. D20, 4429 https://doi.org/10.1029/2001JD000659

Cited by

  1. Improvement of Mid/Long-Term ESP Scheme Using Probabilistic Weather Forecasting vol.44, pp.10, 2011, https://doi.org/10.3741/JKWRA.2011.44.10.843
  2. Verification of Bias Corrected Simulations of Climate Models Using Entropy vol.15, pp.5, 2015, https://doi.org/10.9798/KOSHAM.2015.15.5.25
  3. Development of water quality forecasting system with ensemble stream prediction method in the Geum River Basin, Korea vol.57, pp.2, 2016, https://doi.org/10.1080/19443994.2014.996010