한국수자원학회논문집 (Journal of Korea Water Resources Association)

  • 제57권10호
  • /
  • Pages.741-755
  • /
  • 2024
  • /
  • 2799-8746(pISSN)
  • /
  • 2799-8754(eISSN)
한국수자원학회 (Korea Water Resources Association)
권호 표지
DOI QR코드

DOI QR Code

SWAT을 이용한 AR6 기후변화 시나리오에 의한 영산강 및 주요 지천 수질 변화 분석

Analysis of water quality changes in the mainstream and major tributaries of the Youngsan River by AR6 climate change scenario with SWAT

  • 이승문 (충남대학교 환경IT융합공학과) ;
  • 이어진 (충남대학교 환경IT융합공학과) ;
  • 이지형 (충남대학교 환경IT융합공학과) ;
  • 서동일 (충남대학교 환경IT융합공학과)
  • Lee, Seungmoon (Department of Environmental and IT Convergence, Chungnam National University) ;
  • Lee, Eojin (Department of Environmental and IT Convergence, Chungnam National University) ;
  • Lee, Jihyung (Department of Environmental and IT Convergence, Chungnam National University) ;
  • Seo, Dongil (Department of Environmental and IT Convergence, Chungnam National University)
  • 투고 : 2024.09.02
  • 심사 : 2024.10.04
  • 발행 : 2024.10.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

본 연구는 영산강 유역의 본류와 주요 지천을 대상으로, SWAT (Soil and Water Assessment Tool) 모델을 이용하여 기후변화에 따른 수질 변화를 예측하고 분석하는 것을 목적으로 수행되었다. 모델의 신뢰성을 높이기 위해 2007년부터 2021년까지 정부가 제공하는 기상 및 유량 자료를 이용해 입력자료를 구축하고 모델 보정을 실시하였다. 제6차 IPCC 보고서에 대해 WRF 기후변화 모델을 이용하여 산정된 중간 배출 시나리오(SSP2-4.5)와 극한 배출 시나리오(SSP5-8.5)를 SWAT에 적용하여 유량, TN 및 TP 부하량을 예측하였다. 미래 기후변화 시나리오에 따른 수질 변화는 단기(2021~2040년), 중기(2041~2060년), 장기(2081~2100년)로 구분하여 분석하였으며, 수질 평가는 환경부의 하천 및 호소 생활환경기준(Living Environmental Standards)과 실시간수질지수(RTWQI)를 기준으로 수행하였다. 결과적으로, 영산강 유역 대부분의 지역에서 TN 농도는 "나쁨" 이상으로 나타났으며, 특히 본류 및 하류 지역에서 "매우 나쁨" 등급이 우세하였다. TP 농도는 시나리오에 따라 다소 차이를 보였으나, 장기적으로는 수질이 개선되는 경향을 보였다. RTWQI 평가에서는 생활환경기준에 따른 평가보다 전반적으로 더 높은 수질 등급이 나타났으며, 시간이 지남에 따라 수질이 개선되는 경향을 보였다. 이는 영산강 유역의 수질 관리에 있어 농업 지역이 주를 이루어 TN 농도가 주요 문제점으로 작용할 수 있음을 시사하는 것을 알 수 있다. 따라서, 미래 기후변화에 따른 수질의 개선을 위해 비료관리, 보존 농업 등과 같은 농업 비점오염원 저감 관리와 함께 도심지역을 중점으로 저영향개발, 침투 도랑, 지붕 녹화 및 하수처리장 개선 등 점·비점오염원 저감이 더욱 필요할 것으로 보인다.

This study was conducted to predict and analyze water quality changes due to climate change using the SWAT (Soil and Water Assessment Tool) model for the main stream and major tributaries of the Yeongsan River Basin. To enhance the reliability of the model, input data was constructed using weather and flow data provided by the government from 2007 to 2021, and the model was calibrated. The mid-emission scenario (SSP2-4.5) and extreme emission scenario (SSP5-8.5), derived using the WRF climate change model from the 6th IPCC report, were applied to SWAT to predict flow and nutrient loads. The water quality changes under future climate change scenarios were analyzed by categorizing them into short-term (2021-2040), mid-term (2041-2060), and long-term (2081-2100) periods. Water quality assessments were conducted based on the Living Environment Standards and the Real-Time Water Quality Index (RTWQI). As a result, in most areas of the Yeongsan River Basin, the concentration of TN was found to be at or above the "Poor" level, with the "Very Poor" level being predominant, especially in the main stream and downstream areas. While the concentration of TP showed some variation depending on the scenario, it exhibited a trend of improvement over the long term. The RTWQI assessment generally showed higher water quality levels compared to the evaluation based on living environment standards, with a trend of water quality improvement over time. This suggests that the concentration of TN can act as a major problem as agricultural regions are the main areas in water quality management in the Yeongsan River basin. Therefore, in order to improve water quality according to future climate change, it is expected that it is necessary to further reduce point and non-point sources such as agricultural non-point source reduction management such as fertilizer management and conservation agriculture, and improvement of roof greening and sewage treatment plants in urban areas.

키워드

과제정보

본 연구는 환경부의 재원을 지원받아 한국환경산업기술원 "신기후체제 대응 환경기술개발사업"의 연구개발을 통해 창출되었습니다. (2022003570007)

참고문헌

  1. Abbaspour, K.C. (2007). User manual for SWAT-CUP, SWAT calibration and uncertainty analysis programs. Swiss Federal Institute of Aquatic Science and Technology, Eawag, Deubendorf, Switzerland, pp. 1-33.
  2. Arnold, J.G., Srinivasan, R., Muttiah, R.S., and Williams, J.R. (1998). "Large area hydrologic modeling and assessment part I: Model development." JAWRA Journal of the American Water Resources Association, Vol. 34, pp. 73-89.
  3. Cho, H.L., Jeong, E., and Koo, B.K. (2015). "Development of a hybrid watershed model STREAM: Model structures and theories." Journal of Korean Society on Water Environment, Vol. 31, No. 5, pp. 491-506. https://doi.org/10.15681/KSWE.2015.31.5.491
  4. Choi, D.G., Kim, M.S., Kim, N.W., and Kim, S.D. (2009). "An analysis of the effect of climate change on Byeongseong stream's hydrologic and water quality responses using CGCM's future climate information." Journal of Korea Water Resources Association, Vol. 42, No. 11, pp. 921-931. https://doi.org/10.3741/JKWRA.2009.42.11.921
  5. IPCC (2021). "Contribution of working group I, II and III to the sixth assessment report of intergovernmental panel on climate change." Climate Change 2021: Synthesis Report. Edited by Core Writing Team, Aldunce, P., and Blanco, G., Geneva, Switzerland, pp. 33-35.
  6. Han, J.H., Lee, D.J., Kang, B.S., Jang, W.S., Lim, K.J., and Lim, J.G. (2017). "Potential impacts of future extreme storm events on streamflow and sediment in Soyang-dam watershed." Journal of Korean Society on Water Environment, Vol. 33, No. 2, pp. 160-169. https://doi.org/10.15681/KSWE.2017.33.2.160
  7. Jang, J.H., and Ahn, J.H. (2012). "Assessing future climate change impact on hydrologic and water quality components in Nakdong River basin." Journal of Korea Water Resources Association, Vol. 45, No. 11, pp. 1121-1130. https://doi.org/10.3741/JKWRA.2012.45.11.1121
  8. Jang, S.S., and Kim, S.J. (2017). "Assessment of climate change impact on highland agricultural watershed hydrologic cycle and water quality under RCP scenarios using SWAT." Journal of the Korean Society of Agricultural Engineers, Vol. 59, No. 3, pp. 41-50. https://doi.org/10.5389/KSAE.2017.59.3.041
  9. Jang, Y.J., Park, J.T., and Seo, D.I. (2018). "Estimations of flow rate and pollutant loading changes of the Yo-Cheon basin under AR5 climate change scenarios using SWAT." Journal of the Korean Society of Water and Wastewater, Vol. 32, No. 3, pp. 221-233. https://doi.org/10.11001/jksww.2018.32.3.221
  10. Kim, D.H., and Kim, S.M. (2017). "Estimation of inflow into Namgang dam according to climate change using SWAT model." Journal of the Korean Society of Agricultural Engineers, Vol. 59, No. 6, pp. 9-18. https://doi.org/10.5389/KSAE.2017.59.6.009
  11. Kim, D.H., Hwang, S.W., Jang, T.E., and So, H.C. (2018). "Assessing climate change impacts on hydrology and water quality using SWAT model in the Mankyung watershed." Journal of the Korean Society of Agricultural Engineers, Vol. 60, No. 6, pp. 83-96. https://doi.org/10.5389/KSAE.2018.60.6.083
  12. Kim, D.H., Kim, J.U., Byun, Y.H., Kim, T.J., Kim, J.W., Kim, Y.H., Ahn, J.B., Cha, D.H., Min, S.K., and Chang, E.C. (2021). "Future projection of extreme climate over the Korean peninsula using multi-RCM in CORDEX-EA Phase 2 Project." Atmosphere, Vol. 31, No. 5, pp. 607-623. https://doi.org/10.14191/ATMOS.2021.31.5.607
  13. Kim, J.U., Kim, T.J., Kim, D.H., Kim, J.W., Cha, D.H., Min, S.K., and Kim, Y.H. (2020). "Evaluation of performance and uncertainty for multi-RCM over CORDEX-East Asia phase 2 region." Atmosphere, Vol. 30, No. 4, pp. 361-376. https://doi.org/10.14191/ATMOS.2020.30.4.361
  14. Kim, J.U., Sang, J., Kim, M.K., Byun, Y.H., Kim, D.H., and Kim, T.J. (2022). "Future climate projection in South Korea using the high-resolution SSP scenarios based on statistical downscaling." Atmosphere, Vol. 17, No. 2, pp. 89-106.
  15. Krause, P., Boyle, D.P., and Base, F. (2005). "Comparison of different efficiency criteria for hydrological model assessment." Advances in Geosciences, Vol. 5, pp. 89-97. https://doi.org/10.5194/adgeo-5-89-2005
  16. K-water (2006). Basic status survey report: Investigation of the Seomjin River and Yeongsan River Basins, Vol. II-3. National Assembly Library, MONO1200707748, pp. 172-214.
  17. Lee, J.W., Eom, J.S., Kim, B.C., Jang, W.S., Ryu, J.C., Kang, H.W., Kim, K.S., and Lim, K.J. (2011). "Water quality prediction at Mandae watershed using SWAT and water quality improvement with vegetated filter strip." Journal of the Korean Society of Agricultural Engineers, Vol. 53, No. 1, pp. 37-45. https://doi.org/10.5389/KSAE.2011.53.1.037
  18. Lee, Y.W., Yang, W.M., and Yoon, K.S. (2019). "A study on the enhancement method of Yeongsan River maintenance flow." Journal of the Korean Society of Urban Environment, Vol 19, No. 1, pp. 13-20. https://doi.org/10.33768/ksue.2019.19.1.013
  19. Legates, D.R., and McCabe, G.J. (1999). "Evaluating the use of "goodness-of-fit" Measures in hydrologic and hydroclimatic model validation." Water Resources Research, Vol. 35, No. 1, pp. 233-241. https://doi.org/10.1029/1998WR900018
  20. Li, X., Jia, H., Chen, Y., and Wen, J. (2022). "Runoff simulation and projection in the source area of the Yellow River using the SWAT model and SSPs scenarios." Frontiers in Environmental Science, Vol. 10, 1012838.
  21. Ministry of Environment (ME) (2017). 2017 White paper of environment. p. 630.
  22. Ministry of Environment (ME) (2021). A study on the development of integrated water management strategies for youngsan and sumjin river basins., Ministry of Environment, 11-1480000-001774-01.
  23. Moriasi, D. N., Gitau, M. W., Pai, N., and Daggupati, P. (2015). "Hydrologic and water quality models: performance measures and evaluation criteria. transactions of the Asabae.", Vol 58, No.6, pp. 1763-1785. https://doi.org/10.13031/trans.58.10715
  24. National Institute of Environmental Research (NIER) (2013). Real time water quality data system construction and database enhancement(I).
  25. Nazari-Sharabian, M., Taheriyoun, M., Ahmad, S., Karakouzian, M., and Ahmadi, A. (2019). "Water quality modeling of Mahabad dam watershed - reservoir system under climate change conditions, using SWAT and system dynamics." Water, Vol. 11, No. 2, 394.
  26. Neitsch, S.L., Arnold, J.G., Kiniry, J.R., and Williams, J.R. (2001). Soil and water assessment tool; The theoretical documentation (version 2000, US Agricultural Research Service). Texas Water Resources Institute, College Station, TX, US, pp. 340-367.
  27. Park, Y.K., Lee, J.K., Kin, J.S., and Kim, S.D. (2018). "Multi-objective optimization of BMPs for controlling water quality in upper basin of Namgang dam." Journal of Korean Society on Water Environment, Vol. 34, No. 6, pp. 591-601. https://doi.org/10.15681/KSWE.2018.34.6.591
  28. Rabezanahary Tanteliniaina, M.F., Rahaman, M.H., and Zhai, J. (2021). "Assessment of the future impact of climate change on the hydrology of the Mangoky river, Madagascar using ANN and SWAT." Water Vol. 13, No. 9, 1239.
  29. Ryu, J., Kang, H.W., Choi, J.W., Kong, D.S., Kum, D.H., Jang, C.H., and Lim, K.J. (2012). "Application of SWATCUP for streamflow auto-calibration at Soyang-gang Dam watershed." Journal of Korean Society on Water Environment, Vol. 28, No. 3, pp. 347-358.
  30. Shin, Y.H., and Jung, H.C. (2015). "Assessing uncertainty in future climate change in Northeast Asia using multiple CMIP5 GCMs with four RCP scenarios." Journal of Korea Environmental Impact Assessment, Vol. 24, No. 3, pp. 205-216.
  31. Sun, J., Yan, H., Bao, Z., and Wang, G. (2022). "Investigating impacts of climate change on runoff from the Qinhuai river by using the SWAT model and CMIP6 scenarios." Water Vol. 14, No. 11, 1778.
  32. Ullrich, A., and Volk, M. (2009). "Application of the Soil and Water Assessment Tool (SWAT) to predict the impact of alternative management practices on water quality and quantity." Agricultural Water Management, Vol. 96, No. 8, pp. 1207-1217. https://doi.org/10.1016/j.agwat.2009.03.010
  33. Williams, J.R. (1975). Present and prospective technology for predicting sediment yield and sources. USDA Sedimentation Laboratory, Oxford, MS, U.S., pp. 244-245.
  34. Yasin, H.Q., and Clemente, R.S. (2014). "Application of SWAT model for hydrologic and water quality modeling in Thachin River basin, Thailand." Arabian Journal for Science and Engineering, Vol. 39, No. 3, pp. 1671-1684. https://doi.org/10.1007/s13369-013-0770-3
  35. Zhang, X., Arnold, J.G., Williams, J.R., and Srinivasan, R. (2022). SWAT-carbon user manual. Agricultural Research Service, United States Department of Agriculture. Beltsville, MD, U.S.