Evaluation of Future Turbidity Water and Eutrophication in Chungju Lake by Climate Change Using CE-QUAL-W2

CE-QUAL-W2를 이용한 충주호의 기후변화에 따른 탁수 및 부영양화 영향평가

  • Ahn, So Ra (Dept. of Civil and Environmental System Engineering, Konkuk University) ;
  • Ha, Rim (Dept. of Civil and Environmental System Engineering, Konkuk University) ;
  • Yoon, Sung Wan (Dept. of Environmental Engineering, Chungbuk National University) ;
  • Kim, Seong Joon (Dept. of Civil and Environmental System Engineering, Konkuk University)
  • 안소라 (건국대학교 사회환경시스템공학과) ;
  • 하림 (건국대학교 사회환경시스템공학과) ;
  • 윤성완 (충북대학교 환경공학과) ;
  • 김성준 (건국대학교 사회환경시스템공학과)
  • Received : 2013.12.03
  • Accepted : 2014.01.06
  • Published : 2014.02.28


This study is to evaluate the future climate change impact on turbidity water and eutrophication for Chungju Lake by using CE-QUAL-W2 reservoir water quality model coupled with SWAT watershed model. The SWAT was calibrated and validated using 11 years (2000~2010) daily streamflow data at three locations and monthly stream water quality data at two locations. The CE-QUAL-W2 was calibrated and validated for 2 years (2008 and 2010) water temperature, suspended solid, total nitrogen, total phosphorus, and Chl-a. For the future assessment, the SWAT results were used as boundary conditions for CE-QUAL-W2 model run. To evaluate the future water quality variation in reservoir, the climate data predicted by MM5 RCM(Regional Climate Model) of Special Report on Emissions Scenarios (SRES) A1B for three periods (2013~2040, 2041~2070 and 2071~2100) were downscaled by Artificial Neural Networks method to consider Typhoon effect. The RCM temperature and precipitation outputs and historical records were used to generate pollutants loading from the watershed. By the future temperature increase, the lake water temperature showed $0.5^{\circ}C$ increase in shallow depth while $-0.9^{\circ}C$ in deep depth. The future annual maximum sediment concentration into the lake from the watershed showed 17% increase in wet years. The future lake residence time above 10 mg/L suspended solids (SS) showed increases of 6 and 17 days in wet and dry years respectively comparing with normal year. The SS occupying rate of the lake also showed increases of 24% and 26% in both wet and dry year respectively. In summary, the future lake turbidity showed longer lasting with high concentration comparing with present behavior. Under the future lake environment by the watershed and within lake, the future maximum Chl-a concentration showed increases of 19 % in wet year and 3% in dry year respectively.

본 연구에서는 충주댐을 대상으로 유역모델인 SWAT과 저수지모델인 CE-QUAL-W2를 연계 적용하여 기후변화에 따라 저수지로 유입되는 하천의 유량 및 탁수발생량을 모의하고, 저수지내의 탁수변화 및 부영양화 영향평가를 통한 저수지 수환경 변화를 전망하였다. 먼저 SWAT을 적용하여 강우시 저수지 유입하천의 유량 및 수질을 모의하여 모델의 재현성을 검토하였으며, 모형의 보정(2000~2005)과 검증(2006~2010) 결과 모델 예측값과 실측값이 적절하게 일치하는 것으로 나타났다. SWAT의 결과를 CE-QUAL-W2의 하천유량 및 유입수 수질경계조건 입력자료로 활용하고, 보정(2010년)과 검증(2008년)을 통하여 저수지 내 시간에 따른 물수지, 수온 변화, 부유물질(SS), T-N, T-P 및 부영양화(Chl-a) 양상 등을 분석하고 모델의 재현성을 검토하였다. 이후 기후변화 시나리오 적용에 따른 저수지 내수환경변화를 모의하기 위한 기후변화자료로 IPCC AR4 GCM(ECHO-G)을 고해상도지역 기후 시나리오로 개선시킨 RCM(MM5)의 A1B 시나리오를 다시 태풍사상을 고려한 인공신경망 기법에 의해 상세화하여 이용하였다. 기후변화 시나리오에 따른 기온증가의 영향으로 미래로 갈수록 상층수온은 증가하는 반면 심층수온은 감소하는 경향을 보였다. SS 최고유입농도는 평수년에 비해 풍수년에 17%, 갈수년에 0.2% 가량 증가하는 것으로 나타났다. 호소내 SS 10mg/L 이상 점유일수는 평수년에 비해 풍수년이 6일, 갈수년이 17일 증가하였고, 점유율 역시 풍수년에 24%, 갈수년에 26%가량 증가하는 것으로 분석되었다. 미래로 갈수록 기후변화가 충주댐 탁수장기화에 영향을 미치는 것으로 분석되었다. Chl-a의 최고농도는 평수년에 비해 풍수년에 19%, 갈수년에 3% 가량 조류의 농도가 증가되는 것으로 나타나 조류의 영향이 커지는 것을 알 수 있었다.


  1. Ahn, S.R., Kim, S.H., Yoon, S.W., and Kim, S.J. (2013). "Evaluation of suspended solids and eutrophication in Chungju Lake Using CE-QUAL-W2." Journal of the Korea Water Resources Association, Vol. 46, No. 11, pp. 1115-1128.
  2. Arnold, J.G., and Allen, P.M. (1996). "Estimating hydrologic budgets for three illinois watersheds." Journal of Hydrology, Vol. 176, No. 1, pp. 57-77.
  3. Brown, L.C., and Barnell, T.O. Jr. (1987). The enhanced water quality models QUAL2E and QUAL2E-UNCAS documentation and user manual. EPA document EPA/600/3-87/007, USEPA, Athens, GA.
  4. Choi, K.S., Kim, B.C., Kim, H.B., and Sa, S.H. (2000). "Relationships between organic carbon and codmn in a deep reservoir, Lake Soyang, Korea." Korean Journal of Limnology, Vol. 33, No. 4, pp. 328-335.
  5. Chung, S.W. (2004). "Density flow regime of turbidity current into a stratified reservoir and vertical twodimensional modeling." Journal of Korean Society of Environmental Engineers, Vol. 26, No. 9, pp. 970-978.
  6. Chung, S.W., Oh, J.K., and Ko, I.H. (2005). "Simulations of temporal and spatial distributions of rainfall-induced turbidity flow in a reservoir using CE-QUALW2." Journal of the Korea Water Resources Association, Vol. 38, No. 8, pp. 655-664.
  7. Chung, S.W., Park, J.H., Kim, Y.K., and Yoon, S.W. (2007). "Application of CE-QUAL-W2 to daecheong reservoir for eutrophication simulation." Journal of Korean Society ofWater Quality, Vol. 23, No. 1, pp. 52-63.
  8. Cole, T.M., and Tillman, D.H. (1999). Water Quality Modeling of Lake Monroe Using CE-QUAL-W2, Miscellaneous Paper EL-99-1.
  9. Cole, T.M., and Tillman, D.H. (2001). Water Quality Modeling of Allatoona and Wast Point Reservoir Using CE-QUAL-W2, U.S. Army Corps of Engineers.
  10. Debele, B., Srinivasan, R., and Parlange, J.Y. (2006). "Coupling upland watershed and downstream waterbody hydrodynamic and water quality models (SWAT and CE-QUAL-W2) for better water resources management in complex river basins." Environmental Modeling & Assessment, Vol. 13, pp. 135-153.
  11. Deus, R., Brito, D., Mateus, M., Kenov, I., Fornaro, A., Neves, R., and Alves, C.N. (2013). "Impact evaluation of a pisciculture in the Tucurui reservoir (Para, Brazil) using a two-dimensional water quality model." Journal of Hydrology, Vol. 487, pp. 1-12.
  12. Jung, Y.R., Chung S.W., Ryu, I.G., and Choi, J.K. (2008). "Two-dimensional hydrodynamic and water quality simulations for a coinjunctive system of Daecheong Reservoir and its downstream." Journal of Korean Society ofWater Quality, Vol. 24, No. 5, pp. 581-591.
  13. Kim, B.C., Choi, K,S., Kim, C.G., Lee, Y.H., Kim, D.S., and Park, J.C. (1998). "The distribution of dissolved and particulate organic carbon in Lake Soyang." Korean Journal of Limnology, Vol. 31, No. 1, pp. 17-24.
  14. Kim, Y.H., Kim, B.C., Choi, K,S., and Seo, D.I. (2001). "Modeling of thermal stratification and transport of density flow in Soyang Reservoir using the 2-d hydrodynamic water quality model, CE-QUAL-W2." Journal of the Korean Society ofWater and Wastewater, Vol. 15, No. 1, pp. 40-49.
  15. Kim, Y.K., and Chung, S.W. (2011). "Research paper : laterally-averaged two-dimensional hydrodynamic and turbidity modeling for the downstream of Yongdam Dam." Journal of Korean Society of Water Quality, Vol. 27, No. 5, pp. 710-718.
  16. Kuo, J.T., Lung, W.S., Yang, C.P., Liu, W.C., Yang, M.D., and Tang, T.S. (2006). "Eutrophication modelling of reservoirs in Taiwan." Environmental Modeling & Software, Vol. 21, pp. 829-844.
  17. Martin, N., McEachern, P., Yu, T., and Zhu, D.Z. (2013). "Model development for prediction and mitigation of dissolved oxygen sags in the Athabasca River, Canada." Science of The Total Environment, Vol. 443, pp. 403-412.
  18. Neitsch, S.L., Arnold, J.G. Kiniry, J.R., and Williams, J.R. (2001). "Soil and water assessment tool; the theoretical documentation." U.S Agricultural Research Service, pp. 340-367.
  19. Norton, G.E., and Bradford, A. (2009). "Comparison of two stream temperature models and evaluation of potential management alternatives for the Speed River, Southern Ontario." Journal of Environmental Management, Vol. 90, pp. 866-678.
  20. Ostfeld, A., and Salomons, S. (2005). "A hybrid genetic-instance based learning algorithm for CE-QUAL-W2 calibration." Journal of Hydrology, Vol. 310, pp. 122-142.
  21. Park, J.Y., Park, G.A., and Kim, S.J. (2013). "Assessment of future climate change impact on water quality of Chungju Lake, South Korea, using WASP Coupled with SWAT." Journal of the AmericanWater Resources Association, DOI: 10.1111/jawr.12085 (Published online).
  22. Williams, J.R. (1975). Sediment-yield Prediction with Universal Equation Using Runoff Energy Factor. In present and prospective technology for predicting sediment yield and sources, ARS-S-40, USDA-ARS.
  23. Wischmeier, W.H., and Smith, D.D. (1965). Predicting rainfall-erosion losses from cropland east of the Roky Mountains. Agriculture Handbook 282, USDA-ARS.
  24. Wischmeier, W.H., and Smith, D.D. (1978). Predicting rainfall erosion losses: a guide to conservation planning. Agriculture Handbook 282, USDA-ARS.
  25. Yi, H.S., Jeong, S.A., Park, S.Y., and Lee, Y.S. (2008). "Modeling study of turbid water in the stratified reservoir using linkage of HSPF and CE-QUAL-W2." Journal ofKorean Society of Environmental Engineers, Vol. 30, No. 1, pp. 69-78.
  26. Yi, Y.K., Kim, Y.D., Park, K.Y., and Kim, W.G. (2005). "Two dimensional numerical modeling of turbidity variation in Imha Reservoir." Journal of the Korean Society of Civil Engineers, Vol. 25, No. 4B, pp. 257-266.
  27. Yoo, S.J., Kim C.S., Ha, S.Y., Hwang, J.Y., and Chae, M.H. (2005). "Analysis of natural organic matter (NOM) characteristics in the Geum River." Journal of Korean Society of Water Quality, Vol. 21, No. 2, pp. 125-131.

Cited by

  1. A counterfactual assessment for interagency collaboration on water quality: the case of the Geum River basin, South Korea vol.40, pp.4, 2015,
  2. Establishment of Resilient Infrastructures for the Mitigation of an Urban Water Problem: 1. Robustness Assessment of Structural Alternatives for the Problem of Urban Floods vol.3, pp.2, 2016,
  3. Water Quality Analysis of Hongcheon River Basin Under Climate Change vol.17, pp.4, 2015,
  4. Impact of climate change on the persistent turbidity issue of a large dam reservoir in the temperate monsoon region pp.1573-1480, 2018,