한국수자원학회논문집 (Journal of Korea Water Resources Association)

  • 제48권7호
  • /
  • Pages.581-593
  • /
  • 2015
  • /
  • 2799-8746(pISSN)
  • /
  • 2799-8754(eISSN)
한국수자원학회 (Korea Water Resources Association)
권호 표지
DOI QR코드

DOI QR Code

ESP 기법을 이용한 수문학적 가뭄전망의 활용성 평가

Applicability Assessment of Hydrological Drought Outlook Using ESP Method

  • 손경환 (세종대학교 물자원연구소.건설환경공학과) ;
  • 배덕효 (세종대학교 물자원연구소.건설환경공학과)
  • 투고 : 2015.01.31
  • 심사 : 2015.06.02
  • 발행 : 2015.07.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

본 연구에서는 ESP (Ensemble Streamflow Prediction)기법을 활용한 가뭄전망 체계를 구축하고 가뭄예보에 있어 활용성을 평가하였다. 과거 관측 수문기상 및 지형정보를 이용하여 우리나라 전역에 지면모델(Land Surface Model, LSM)을 구축하고 유출량(Historical Runoff, HR)을 생산하였다. 또한, 모의기간 동안 과거 30개 기상자료와 초기 토양수분량을 이용하여 선행시간별(1, 2, 3개월) 전망된 유출량(Predicted Runoff, PR)을 생산하였다. 평가결과 여름 및 가을철 보다 봄철 및 겨울철에 정확도가 높았으며, 1개월 전망 이후로는 정확도가 낮게 나타났다. 가뭄지수는 국내 가뭄해석에 있어 검증된 표준유출지수(Standardized Runoff Index, SRI)를 활용하였으며, PR_SRI을 산정 및 평가하였다. 1, 2개월 전망에서는 과거 HR이 고려되어 ESP HR에 비해 정확도가 크게 개선됨을 알 수 있었다. 선행시간별 상관계수는 평균 0.71, 0.48, 0.00, 평균제곱근오차는 0.46, 0.76, 1.01로 나타났으며, 건조기에 정확도가 높게 나타나 1, 2개월 전망까지는 ESP를 활용한 국내 가뭄예보의 활용성이 높다고 판단된다.

This study constructs the drought outlook system using ESP(Ensemble Streamflow Prediction) method and evaluates its utilization for drought prediction. Historical Runoff(HR) was estimated by employing LSM(Land Surface Model) and the observed meteorological, hydrological and topographical data in South Korea. Also Predicted Runoff(PR) was produced for different lead times(i.e. 1-, 2-, 3-month) using 30-year past meteorological data and the initial soil moisture condition. The HR accuracy was higher during MAM, DJF than JJA, SON, and the prediction accuracy was highly decreased after 1 month outlook. SRI(Standardized Runoff Index) verified for the feasibility of domestic drought analysis was used for drought outlook, and PR_SRI was evaluated. The accuracy of PR_SRI with lead times of 1- and 2-month was highly increased as it considered the accumulated 1- and 2-month HR, respectively. The Correlation Coefficient(CC) was 0.71, 0.48, 0.00, and Root Mean Square Error(RMSE) was 0.46, 0.76, 1.01 for 1-, 2- and 3-month lead times, respectively, and the accuracy was higher in arid season. It is concluded that ESP method is applicable to domestic drought prediction up to 1- and 2-month lead times.

키워드

참고문헌

  1. Coelho, C.A.S., Uvo, C.B., and Ambrizzi, T. (2002). "Exploring the impacts of the tropical Pacific SST on the precipitation patterns over South America during ENSO periods." Theoretical and Applied Climatology, Vol. 71 pp.185-197. https://doi.org/10.1007/s007040200004
  2. Croley, T.E. (2000). Using meteorology probability forecasts in operational hydrology, ASCE press. pp. 206.
  3. Franz, K.J., Hartmann, H.C., Sorooshian, S., and Bales, R. (2003). "Verification of National Weather Service Ensemble Streamflow Predictions for Water Supply Forecasting in the Colorado River Basin." Journal of Hydrometeorology, Vol. 4, pp. 1105-1118. https://doi.org/10.1175/1525-7541(2003)004<1105:VONWSE>2.0.CO;2
  4. Hosking, J.R.M., and Wallis, J.R. (1993). "Some statistics useful in regional frequency analysis." Water Resources Research, Vol. 29, pp. 271-281. https://doi.org/10.1029/92WR01980
  5. Jung, D.I., and Kim, Y.O. (2002). "Forecasting Monthly Inflow to Chungju Dam using Ensemble Streamflow Prediction." Korean Society of Civil Engineers, Vol. 22, No. 3, pp. 321-331.
  6. Jung, I.W., and Chang, H.J. (2012). "Climate change inpacts on spatial patterns in drought risk in the willamette River Basin, Oregon, USA." Theoretical and Applied Climatology, DOI 10.1007/s00704-011-0531-8.
  7. Kim. J.H., and Bae, D.H. (2006). "Probabilistic Mediumand Long-Term Reservoir Inflow Forecasts(II) Use of GDAPS for Ensemble Reservoir Inflow Forecasts." Korea Water Resources Association, Vol. 39, No. 3, pp. 275-288. https://doi.org/10.3741/JKWRA.2006.39.3.275
  8. Korea Meteorological Administration (KMA) (2012). Development of Hydro-meteorological Early Warning System for Response to Climate Change.
  9. Landsea, C.W., and Knaff, J.A. (2000). "How much skill was there in forecasting the very strong 1997-98 El Nino?" Bulletin of the AmericanMeteorological Society, Vol. 81, pp. 2017-2119.
  10. Lee, S.J., Jeong, C.S., Kim. J.C., and Hwang, M.H. (2011). "Long-term Streamflow Prediction Using ESP and RDAPS Model." Korea Water Resources Association, Vol. 44, No. 12, pp. 967-974. https://doi.org/10.3741/JKWRA.2011.44.12.967
  11. Li, H., Luo, L., Wood, E.F., and Schaake, J. (2009). "The role of initial conditions and forcing uncertainties in seasonal hydrologic forecasting." Journal of Geophysical Research, Vol.114, D04114, doi:10.1029/2008JD010969.
  12. Liang, X., Jianzhong, G., and Ruby Leung, L. (2004). "Asesment of the efects of spatial resolutions on daily water flux simulations." Journal of Hydrology, Vol. 298, Isues. 1-4, pp. 287-310. https://doi.org/10.1016/j.jhydrol.2003.07.007
  13. Liang, X., Lettenmainer, D.P., Wood, E.F., and Burges, S.J. (1994). "A simple hydrologically based model of land surface water and energy fluxes for General Circulation Models." Journal of Geophysical Research, Vol. 99, pp. 14415-14428. https://doi.org/10.1029/94JD00483
  14. Liang, X., Wood, E.F., and Lettenmaier, D.P. (1996). "Surface soil moisture parameterization of the VIC-2L model: Evaluation and modifications." Global Planetary Change, Vol. 13, pp. 195-206. https://doi.org/10.1016/0921-8181(95)00046-1
  15. Luo, L., and Wood, E.F. (2008). "Use of Bayesian merging techniques in a multimodel seasonal hydrologic ensemble prediction system for the eastern United States." Journal of Hydrometeorology, Vol. 9, pp. 866-884. https://doi.org/10.1175/2008JHM980.1
  16. Maurer, E.P., Lettenmaier, D.P., and Mantua, N.J. (2004). "Variability and potential sources of predicability of North American runoff."Water Resources Research, Vol.40, W09306, doi:10.1029/2003WR002789.
  17. Mo, K.C. (2008). "Model-Based Drought Indices over the United States." Journal of Hydrometeorology, Vol. 9, pp. 1212-1229. https://doi.org/10.1175/2008JHM1002.1
  18. Mo, K.C., Shukla, S., Lettenmaier, D.P., and Chen L.C. (2012). "Do Climate Forecast System (CFSv2) forecasts improve seasonal soil moisture prediction?" Geophysical Research Letters, Vol. 39, L23703, doi:10.1029/2012GL053598, 2012R.
  19. National Emergency Management Agency (NEMA) (2013). Establishment of National Drought Disaster Information System.
  20. Ruy, J.H., Lee, D.H., Ahn, J.H., and Yoon, Y.N. (2002). "A Comparative Study on the Drought Indices for Drought Evaluation." Korea Water Resources Association, Vol. 35, No. 4, pp. 397-410. https://doi.org/10.3741/JKWRA.2002.35.4.397
  21. Shukla, S., and Lettenmaier, D.P. (2011). "Seasonal hydrologic prediction in the United States: understanding the role of initial hydrologic conditions and seasonal climate forecast skill." Hydrology and Earth System Sciences, Vol. 15, pp. 3529-3538. https://doi.org/10.5194/hess-15-3529-2011
  22. Shukla, S., and Wood, A.W. (2008). "Use of a standardized runoff index for characterizing hydrologic dought." Geophysical Research Letters, doi:10.1029/2007GL032487.
  23. Smith, J.A., Day, G.N., and Kane, M.D. (1992). "Nonparametric framework for long-range streamflow forecasting." Journal of Water Resources Planning and Management, Vol. 118, No. 1, pp. 82-92. https://doi.org/10.1061/(ASCE)0733-9496(1992)118:1(82)
  24. Son, K.H., Bae, D.H., and Jung, J.S. (2011). "Drought Analysis and Assessment by Using Land Surface Model on South Korea." Korea Water Resources Association, Vol. 44, No. 8, pp. 667-681. https://doi.org/10.3741/JKWRA.2011.44.8.667
  25. Son, K.H., Lee, J.D., and Bae, D.H. (2010). "The Application Assessment of Global Hydrologic Analysis Models on South Korea." Korea Water Resources Association, Vol. 43, No. 12, pp. 1063-1074. https://doi.org/10.3741/JKWRA.2010.43.12.1063
  26. Trambauer, P., Werner, M., Winsemius, H.C., Maskey, S., Dutra, E., and Uhlenbrook, S. (2014). "Hydrological drought forecasting and skill assessment for the Limpopo river basin, Southern Africa." Hydrology and Earth System Sciences, Vol. 11, pp. 9961-10000. https://doi.org/10.5194/hessd-11-9961-2014
  27. Wang, D., Hejazi, M., Cai, X., aqnd Vaocchi, A.J. (2011). "Climate change impact on meteorological, agricultural, and hydrological drought in central Illinois." Water Resources Research, Vol. 47, Issue 9, W09527. https://doi.org/10.1029/2010WR009845
  28. Werner, K., Brandon, D., Clark, M., and Gangopadhyay, S. (2005). "Incorporating Medium- Range Numerical Weather Model Output into the Ensemble Streamflow Prediction System of the National Weather Service." Journal of Hydrometeorology, Vol. 6, pp. 101-114. https://doi.org/10.1175/JHM411.1
  29. Wood, A.W., and Lettenmaier, D.P. (2007). "A test bed for new seasonal hydrologic forecasting approaches in the Western United States." Bulletin of the American Meteorological Society, Vol. 87, pp. 1699-1712.
  30. Wood, A.W., and Lettenmaier, D.P. (2008) "An ensemble approach for attribution of hydrologic prediction uncertainty." Journal of Geophysical Research, Vol. 35, No. 14, L14401, doi:1029/2008GL034648. https://doi.org/10.1029/2008GL034648
  31. Wood, A.W., Maurer, E.P., Kumar, A., and Lettenmaier, D.P. (2002). "Long-range experimental hydrologic forecasting for the Eastern United States." Journal of Geophysical Research, Vol. 107, 4439, doi:10.1029/2001JD000659.
  32. Yuan, X., Wood, E.F., Luo, L., and Pan, M. (2011) "A first look at Climate Forecast System version 2 (CFSv2) for hydrological seasonal prediction." Journal of Geophysical Research, Vol. 38, L13402, doi:10.1029/2011GL047792.

피인용 문헌

  1. Uncertainty Assessment of Future High and Low Flow Projections According to Climate Downscaling and Hydrological Models vol.154, 2016, https://doi.org/10.1016/j.proeng.2016.07.560
  2. The probabilistic drought forecast based on ensemble using improvement of the modified surface water supply index vol.49, pp.10, 2016, https://doi.org/10.3741/JKWRA.2016.49.10.835
  3. The probabilistic drought prediction using the improved surface water supply index in the Korean peninsula vol.50, pp.1, 2018, https://doi.org/10.2166/nh.2018.045