Journal of Korea Water Resources Association (한국수자원학회논문집)

Korea Water Resources Association (한국수자원학회)
권호 표지
DOI QR코드

DOI QR Code

Assessment of future climate and land use changes impact on hydrologic behavior in Anseong-cheon Gongdo urban-growing watershed

미래 기후변화와 토지이용변화가 안성천 공도 도시성장 유역의 수문에 미치는 영향 평가

  • Kim, Da Rae (Department of Civil, Environmental and Plant Engineering, Konkuk University) ;
  • Lee, Yong Gwan (Department of Civil, Environmental and Plant Engineering, Konkuk University) ;
  • Lee, Ji Wan (Department of Civil, Environmental and Plant Engineering, Konkuk University) ;
  • Kim, Seong Joon (Department of Civil, Environmental and Plant Engineering, Konkuk University)
  • 김다래 (건국대학교 사회환경플랜트공학과) ;
  • 이용관 (건국대학교 사회환경플랜트공학과) ;
  • 이지완 (건국대학교 사회환경플랜트공학과) ;
  • 김성준 (건국대학교 사회환경플랜트공학과)
  • Received : 2017.10.25
  • Accepted : 2017.11.28
  • Published : 2018.02.28
Download PDF
⟨ Previous Next ⟩

Abstract

The purpose of this study is to evaluate the future hydrologic behavior affected by the potential climate and land use changes in upstream of Anseong-cheon watershed ($366.5km^2$) using SWAT. The HadGEM3-RA RCP 4.5 and 8.5 scenarios were used for 2030s (2020-2039) and 2050s (2040-2059) periods as the future climate change scenario. It was shown that maximum changes of precipitation ranged from -5.7% in 2030s to +18.5% in 2050s for RCP 4.5 scenarios and the temperature increased up to $1.8^{\circ}C$ and $2.6^{\circ}C$ in 2030s RCP 4.5 and 2050s 8.5 scenarios respectively based on baseline (1976-2005) period. The future land uses were predicted using the CLUE-s model by establishing logistic regression equation. The 2050 urban area were predicted to increase of 58.6% (29.0 to $46.0km^2$). The SWAT was calibrated and verified using 14 years (2002-2015) of daily streamflow with 0.86 and 0.76 Nash-Sutcliffe model efficiency (NSE) for stream flow (Q) and low flow 1/Q respectively focusing on 2 drought years (2014-2015) calibration. For future climate change only, the stream discharge showed maximum decrease of 24.2% in 2030s RCP 4.5 and turned to maximum increase of 10.9% in 2050s RCP 4.5 scenario compared with the baseline period stream discharge of 601.0 mm by the precipitation variation and gradual temperature increase. While considering both future climate and land use change, the stream discharge showed maximum decrease of 14.9% in 2030s RCP 4.5 and maximum increase of 19.5% in 2050s RCP 4.5 scenario by the urban growth and the related land use changes. The results supported that the future land use factor might be considered especially for having high potential urban growth within a watershed in the future climate change assessment.

본 연구의 목적은 안성천 상류 공도유역($366.5km^2$)을 대상으로 SWAT 모형을 이용하여 미래 기후변화 평가에 있어, 미래의 토지이용변화를 동시에 고려하면 수문학적 거동에 얼마나 영향을 주는지를 분석하고자 하였다. 미래기후변화 시나리오는 HadGEM3-RA의 RCP 4.5와 8.5 시나리오를 이용하여 2030s (2020-2039)과 2050s (2040-2059) 기간으로 나누어 적용하였으며, 토지이용변화는 도시성장 시나리오에 따른 회귀모형 기반의 CLUE-s 모델을 이용하였다. 기준년(1976-2005) 대비 미래 강수량은 RCP 4.5에서 2030s에 최대 5.7%의 감소, 2050s에는 최대 18.5% 증가하였고, 미래 기온은 2030s RCP 4.5에서 최대 $1.8^{\circ}C$, 2050s RCP 8.5에서 최대 $2.6^{\circ}C$ 증가하였다. 미래 토지이용은 2050년 도시지역이 58.6% ($29.0km^2$에서 $46.0km^2$) 증가하는 것으로 예측되었다. SWAT 수문 검보정은 14년(2002-2015) 동안의 공도관측소 일유량 자료를 이용하였으며, 저유량 모델효율의 향상을 위하여 2014-2015년 연속 가뭄년을 대상으로 보정을 실시한 결과, 하천유량(Q)과 1/Q을 대상으로 Nash-Sutcliffe 모델효율은 각각 0.86과 0.76이었다. 미래 기후변화 시나리오만을 적용한 결과, 하천유출량이 2030s RCP 4.5에서 최대 24.2% 감소하다가 2050s RCP 4.5에서 최대 10.9% 증가하는 변화를 보여주었다. 한편, 기후변화와 더불어 미래의 토지이용변화를 함께 고려한 경우는 하천유출량이 2030s RCP 4.5에서 최대 14.9% 감소, 2050s RCP 4.5에서 최대 19.5% 증가하는 변화를 보여주어, 미래 기후변화에 따른 유역의 수문평가 시, 도시성장이 기대되는 유역 등 미래의 토지이용변화가 클 가능성이 있는 유역에 대해서는 토지이용변화 요소를 고려할 필요가 있다고 생각된다.

Keywords

References

  1. Ahn, S. R., Jang, C. H., Lee, J. W., and Kim, S. J. (2015). "Assessment of climate and land use change impacts on watershed hydrology for an urbanizing watershed." Journal of the Korean Society of Civil Engineers, Vol. 35, No. 3, pp. 567-577. https://doi.org/10.12652/Ksce.2015.35.3.0567
  2. Arnold, J. G., Williams, J. R., Srinivasan, R., and King, K. W. (1996). SWAT Manual. USDA, Agricultural Research Service and Blackland Research Center, Texas.
  3. Cho, M. R. (2003). "Trend and prospect of urbanization in Korea: reflections on Korean cities." Economy and Society, Vol. 60, pp. 10-39.
  4. Han, W. S., Jeong, S. J., and Kim, B. S. (2015) "The analysis method of future flooding discharge considering climate and land-use change using Dyna-CLUE." Journal of the Korean Society of Hazard Mitigation, Vol. 15, No. 6, pp. 361-371. https://doi.org/10.9798/KOSHAM.2015.15.6.361
  5. Kim, D. R., and Kim, S. J. (2017). "A Study on parameter estimation for SWAT calibration considering streamflow of long-term drought periods." Journal of the Korean Society of Agricultural Engineers, Vol. 59, No. 2, pp. 19-27. https://doi.org/10.5389/KSAE.2017.59.2.019
  6. Kim, J. H., Kim, S. D., Park, M. J., and Joo, J. G. (2016) "A comparison of drought prospection by future climate models." Journal of Korea Society of Hazard Mitigation, Vol. 16, No. 2, pp. 463-472. https://doi.org/10.9798/KOSHAM.2016.16.2.463
  7. Kim, J. H., Park, M. J., and Joo, J. G. (2015) "Comparison of characteristics and spatial distribution tendency of daily precipitation based on the regional climate models for the Korean peninsula." Journal of Korea Society of Hazard Mitigation, Vol. 15, No. 4, pp. 59-70. https://doi.org/10.9798/KOSHAM.2015.15.4.59
  8. Kim, M. H., Han, S. H., Joh, J. S., and Kim, T. W. (2013). KREI outlook of the agricultural economy. Korean Rural Economic Institute, p. 31.
  9. Kim, W. S., Yun, K. H., Heo, J., and Jayakumar, S. (2008). "The expectation of the land use and land cover using CLUE-s model and Landsat images." The Korean Society for Geospatial Information System, Vol. 16, No. 1, pp. 33-41.
  10. Lee, Y. G., Cho, Y. H., and Kim, S. J. (2016). "Prediction of landuse change based on urban growth scenario in South Korea using CLUE-s model." Journal of the Korean Association of Geographic Information Studies, Vol. 19, No. 3, pp. 75-88. https://doi.org/10.11108/kagis.2016.19.3.075
  11. Legesse, D., Vallet-Coulomb, C., and Gasse, F. (2003). "Hydrological response of a catchment to climate and land use change in Tropical Africa: case study South Central Ethiopia." Journal of Hydrology, Vol. 275, No. 1-2, pp. 67-85. https://doi.org/10.1016/S0022-1694(03)00019-2
  12. Li, Z., Liu, W. Z., Zhang, X. C., and Zheng, F. L. (2009). "Impacts of land use change and climate variability on hydrology in an agricultural catchment on the Loess Plateau of China." Journal of Hydrology, Vol. 377, No. 1-2, pp. 35-42. https://doi.org/10.1016/j.jhydrol.2009.08.007
  13. Neitsch, S. L., Arnold, J. G., Kiniry, J. R., and Williams, J. R. (2001). Soil and Water Assessment Tool: Theoretical documentation. Texas Water Resources Institute.
  14. NIMR (2011). Climate change scenario report 2011 to respond to the IPCC 5th Assessment Report. National Institute of Meteorological Research, Korea.
  15. Park, J. Y., Park, M. J., Ahn, S. R., and Kim, S. J. (2009). "Watershed modeling for assessing climate change impact on stream water quality of Chungju dam watershed." Journal of Korea Water Resources Association, Vol. 42, No. 10, pp. 877-889. https://doi.org/10.3741/JKWRA.2009.42.10.877
  16. Park, J. Y., Park, M. J., Joh, H. K., Shin, H. J., Kwon, H. J., Srinivasn, R., and Kim, S. J. (2011). "Assessment of MIROC3.2 HiRes climate and CLUE-s land use change impacts on watershed hydrology using SWAT." Transactions of the ASABE, Vol. 54, No. 5, pp. 1713-1724. https://doi.org/10.13031/2013.39842
  17. Ryu, J. C., Ahn, K. H., Han, M. D., Hwang, H. S., Choi, J. W., Kim, Y. S., and Lim, K. J. (2014). "Evaluation and application of CLUE-s model for spatio-temporal analysis of future land use change in total water pollution load management system." Journal of Korea Society on Water Environment, Vol. 30, No. 4, pp. 418-428. https://doi.org/10.15681/KSWE.2014.30.4.418
  18. USDA-SCS (1972). National Engineering Handbook, Section 4: Hydrology. USDA Soil Conservation Service, Washington, D.C.
  19. Zhang, P., Liu, Y., Pan, Y., and Yu, Z. (2013). "Land use pattern optimization based on CLUE-S and SWAT models for agricultural non-point source pollution control." Mathematical and Computer Modeling, Vol. 58, No. 3-4, pp. 588-595. https://doi.org/10.1016/j.mcm.2011.10.061