All Issue

2016 Vol.49, Issue 5
One-month lead dam inflow forecast using climate indices based on tele-connection

원격상관 기후지수를 활용한 1개월 선행 댐유입량 예측

Jaepil Choa
,
Il Won Jungb*
,
Chul Gyium Kimb
,
Tae Guk Kimc
조 재필a
,
정 일원b*
,
김 철겸b
,
김 태국c
aClimate Research Department, APEC Climate Center
bWater Resources Research Division, Korea Institute of Civil Engineering and Building Technology
cWater Management Center, Korea Water Resources Corporation
a전북대학교 토목공학과
b한국건설기술연구원 수자원연구실
cK-water 물관리센터
*교신저자. *Corresponding Author. 
31 May 2016. pp. 361-372
PDF XML Citation
Abstract

Reliable long-term dam inflow prediction is necessary for efficient multi-purpose dam operation in changing climate. Since 2000s the teleconnection between global climate indices (e.g., ENSO) and local hydroclimate regimes have been widely recognized throughout the world. To date many hydrologists focus on predicting future hydrologic conditions using lag teleconnection between streamflow and climate indices. This study investigated the utility of teleconneciton for predicting dam inflow with 1-month lead time at Andong dam basin. To this end 40 global climate indices from NOAA were employed to identify potential predictors of dam inflow, areal averaged precipitation, temperature of Andong dam basin. This study compared three different approaches; 1) dam inflow prediction using SWAT model based on teleconneciton-based precipitation and temperature forecast (SWAT-Forecasted), 2) dam inflow prediction using teleconneciton between dam inflow and climate indices (CIR-Forecasted), and 3) dam inflow prediction based on the rank of current observation in the historical dam inflow (Rank-Observed). Our results demonstrated that CIR-Forecasted showed better predictability than the other approaches, except in December. This is because uncertainties attributed to temporal downscaling from monthly to daily for precipitation and temperature forecasts and hydrologic modeling using SWAT can be ignored from dam inflow forecast through CIR-Forecasted approach. This study indicates that 1-month lead dam inflow forecast based on teleconneciton could provide useful information on Andong dam operation.

Keywords
Dam inflow forecast
Climate indices
Teleconnection
SWAT
Andong dam

신뢰성 있는 댐유입량의 장기예측은 효율적인 댐운영에 필수적이다. 2000년대 이후 엘리뇨-남방진동(ENSO) 등의 전구기후지수와 지역수문기후와의 원격상관성이 규명되면서, 이를 활용한 미래의 수문조건을 예측하기 위한 연구가 활발히 시도되고 있다. 본 연구에서는 안동댐유역을 대상으로 미국 NOAA에서 제공하는 40개 전구기후지수의 원격상관을 분석하고, 이를 기반으로 1개월 선행 댐유입량의 예측성능 및 활용성을 평가하였다. 본 연구에서는 1) 원격상관을 통해 강수와 기온을 예측하고 SWAT 모델을 이용하여 예측 댐유입량을 산정하는 방법(SWAT-Forecasted), 직접 댐유입량을 예측하는 기법(CIR-Forecasted), 예측시점의 관측값이 과거자료에서 해당하는 순위(rank)에 근거한 방법(Rank-Observed)을 비교하였다. 결과적으로 통계적 방법으로 댐유입량을 직접 예측하는 접근 방식(CIR-Forecasted)이 12월을 제외하고는 다른 방법에 비해 우수한 예측성을 보였다. 이것은 강수량 및 기온 예측정보를 일단위로 상세화하는 가정과 유출모델링과정에서 발생하는 불확실성이 예측결과에 포함되지 않기 때문인 것으로 판단된다. 본 연구결과는 원격상관기반의 1개월 선행 댐유입량 예측이 안동댐 운영에 유용한 정보를 제공할 수 있는 것을 시사하였다.

키워드
댐유입량
기후지수
원격상관
SWAT
안동댐
References
1
Arnold, J.G., R. Srinivasan, R.S. Muttiah, and J.R. Williams (1998). “Large‐area hydrologic modeling and assessment: Part I. Model development.” J. American Water Resour. Assoc., Vol. 34, No. 1, pp. 73-89.
2
Bae, D.H., Jung, I.W., Lettenmaier, D.P. (2011). “Hydrologic uncertainties in climate change from IPCC AR4 GCM simulations of the Chungju Basin, Korea.” Journal of Hydrology, Vol. 401, pp. 90-105.
3
Barnston, A.G., Kumar, A., Goddard, L. and Hoerling, M.P. (2005). “Improving seasonal prediction practices through attribution of climate variability.” Bulletin of the American Meteorological Society, Vol. 86, pp. 59-72.
4
Bierkens, M.F.P. and van Beek, L.P.H. (2009). “Seasonal Predictability of European Discharge: NAO and Hydrological Response Time.” Journal of Hydrometeorology, Vol. 10, pp. 953-968.
5
Block, P.J., Souza, F.A., Sun, L.Q. and Kwon, H.H. (2009). “A Streamflow Forecasting Framework using Multiple Climate and Hydrological Models.” Journal of the American Water Resources Association, Vol. 45, pp. 828-843.
6
Burt, T.P. and Howden, N.J.K. (2013). “North Atlantic Oscillation amplifies orographic precipitation and river flow in upland Britain.” Water Resour. Res., Vol. 49, pp. 3504–3515.
7
Chandimala, J. and Zubair, L. (2007). “Predictability of stream flow and rainfall based on ENSO for water resources management in Sri Lanka.” Journal of Hydrology, Vol. 335, pp. 303-312.
8
Chiew, F.H.S., Piechota, T.C., Dracup, J.A., and McHahon, T.A. (1998). “El-Nino/Southern Oscillation and Australian rainfall, streamflow and drought: Links and potential for forecasting.” Journal of Hydrology, Vol. 204, No. 1-4, pp. 138-149.
9
Enfield, D.B., Mestas-Nunez, A.M., and Trimble, P.J. (2001). “The Atlantic multidecadal oscillation and its relation to rainfall and river flows in the continental U.S.” Geophysical Research Letters, Vol. 28, No. 10, pp. 2077-2080.
10
Fleming, S.W. and Dahlke, H.E. (2014). “Parabolic northern-hemisphere river flow teleconnections to El Nino-Southern Oscillation and the Arctic Oscillation.” Environmental Research Letters, Vol. 9, No. 104007, doi:10.1088/1748-9326/9/10/104007.
11
Gobena, A., and Gan, T.Y. (2010). “Incorporating of seasonal climate forecasts in the ensemble streamflow prediction system.” Journal of Hydrology, Vol. 385, pp. 336-352.
12
Gong, D.Y., and Ho, C.H. (2003). “Siberian high and climate change over middle to high latitude Asia.” Theoretical Applied Climatology, Vol. 72, pp. 1-9.
13
Hamlet, A.F., and D.P. Lettenmaier (2000). “Long-range climate forecasting and its use for water management in the Pacific Northwest region of North America.” J. Hydroinformatics, Vol. 2, pp. 163–182.
14
Hurrell, J.W. (1995). “Decadal trends in the North Atlantic Oscillation: regional temperatures and precipitation.” Science, Vol. 269, No. 5224, pp. 676-679.
15
Jung, C.M., Shin, M.J., and Kim, Y.O. (2015). “A comparison study of runoff projections for Yongdam Dam watershed using SWAT.” Journal of Korean Water Resources Association, Vol. 48, No. 6, pp. 439-449.
16
Kalra, A., Ahmad, S. and A. Nayak. (2013). “Increasing streamflow forecast lead time for snowmelt-driven catchment based on large-scale climate patterns.” Advances in Water Resources, Vol. 53, pp. 150-162.
17
Kim, M.K., Kim, Y.H., and Lee, W.S. (2007). “Seasonal prediction of Korean regional climate from preceding large-scale climate indices.” International Journal of Climatology, Vol. 27, pp. 825-934.
18
Kim, N.W., Lee, B.J., and Lee, J.E. (2006). “An evaluation of snowmelt effects using SWAT in Chungju Dam Basin.” Journal of Korean Water Resources Association, Vol. 39, No. 10, pp. 833-844.
19
Kim, Y.H., Kim, M.K., and Lee, W.S. (2008). “An investigation of large-scale climate indices with the influence on temperature and precipitation variation in Korea.” Atmosphere, Vol. 18, No. 2, pp. 83-95.
20
Kuo C.C., Gan, T.Y. and Yu, P.S. (2010). “Wavelet analysis on the variability, teleconnectivity, and predictability of the seasonal rainfall of Taiwan.” Monthly Weather Review, Vol. 138, No. 1, pp. 162-175.
21
Lee, J., Kim, N.W., and Lee, J.E. (2014). “Estimation of actual evapotranspiration and storage change for the Bokahcheon Upper-middle watershed.” Journal of Korean Water Resources Association, Vol. 47, No. 7, pp. 615-628.
22
Luo LF and Wood EF. (2008). “Use of Bayesian Merging Techniques in a Multimodel Seasonal Hydrologic Ensemble Prediction System for the Eastern United States.” Journal of Hydrometeorology No. 9, pp. 866-884.
23
Mahalanobis, P.C. (1936). “On the generalised distance in statistics.” Proceedings of the National Institute of Sciences of India, Vol. 2, No. 1, pp. 49–55.
24
McCabe, G.J., Palecki, M.A., and Betancourt, J.L. (2004). “Pacific and Atlantic Ocean influences on multidecadal drought frequency in the United States.” Proceedings of the National Academy of Sciences, Vol. 101, No. 12, pp. 4136-4141.
25
Neitsch, S.L., J.G. Arnold, J.R. Kiniry, J.R. Williams, et al. (2002). Soil and Water Assessment Tool Theoretical Documentation. Ver. 2000. Temple, Tex.: USDA‐ARS Grassland Soil and Water Research Laboratory and Texas A&M University, Blackland Research and Extension Center.
26
Rasmusson, E. M. and Carpenter, T.H. (1982). “Variations in tropical sea surface temperature and surface wind fields associated with southern oscillation/El nino.” Monthly Weather Review, Vol. 110, pp. 354-384.
27
Ruiz, J.E., Cordery, I. and Sharma, A. (2007). “Forecasting streamflows in Australia using the tropical Indo-Pacific thermocline as predictor.” Journal of Hydrology Vol. 341, pp. 156-164.
28
Svensson, C. and Prudhomme, C. (2005). “Prediction of British summer river flows using winter predictors.” Theoretical and Applied Climatology Vol. 82, pp. 1-15.
29
Wang, Q.J., Robertson, D.E. and Chiew, F.H.S. (2009). “A Bayesian joint probability modelling approach for seasonal forecasting of streamflows at multiple sites.” Water Resour. Res., Vol. 45, No. W05407, doi:10.1029/2008WR007355.
30
Werner, K., D. Brandon, M. Clark, and S. Gangopadhyay, (2005). “Incorporating medium-range numerical weather model output into the ensemble streamflow prediction system of the National Weather Service.” J. Hydrometeor., Vol. 6,  pp. 101–114.
31
Wilby RL. (2001). “Seasonal forecasting of river flows in the British Isles using North Atlantic pressure patterns.” Journal of the Chartered Institution of Water and Environmental Management, Vol. 15, pp. 56-63.
32
Wilby, R, L,, O’Hare, G. and Barnsley, N. (1997). “The North Atlantic Oscillation and British Isles climate variability, 1865–1996.” Weather, Vol. 52, pp. 266–276.
33
Wood, A.W. A. Kumar, and D.P. Lettenmaier, (2005). “A retro-spective assessment of climate model-based ensemble hydrologic forecasting in the western U.S.” J. Geophys. Res., Vol. 110, No. D04105, doi:10.1029/2004JD004508.
34
Wood, A.W., and Lettenmaier, D.P. (2006). “A test bed for new seasonal hydrologic forecasting approaches in the western united states.” Bull. Amer. Meteor. Soc., Vol. 87, pp. 1699–1712.
Information
  • Publisher :KOREA WATER RESOURECES ASSOCIATION
  • Publisher(Ko) :한국수자원학회
  • Journal Title :Journal of Korea Water Resources Association
  • Journal Title(Ko) :한국수자원학회 논문집
  • Volume : 49
  • No :5
  • Pages :361-372
  • Received Date : 2015-12-01
  • Revised Date : 2016-02-23
  • Accepted Date : 2016-03-07
  • DOI :https://doi.org/10.3741/JKWRA.2016.49.5.361
Journal Informaiton Journal of Korea Water Resources Association Journal of Korea Water Resources Association
Online Submission
Archives
  • scopus
  • NRF
  • KOFST
  • KISTI Current Status
  • KISTI Cited-by
  • crosscheck
  • orcid
  • open access
  • ccl
Journal Informaiton Journal Informaiton - close