DOI QR코드

DOI QR Code

SWAT 모형을 이용한 기후와 식생 활력도 변화가 수자원에 미치는 영향 평가

Assessment of Climate and Vegetation Canopy Change Impacts on Water Resources using SWAT Model

  • 박민지 (건국대학교 사회환경시스템공학과) ;
  • 신형진 (건국대학교 사회환경시스템공학과) ;
  • 박종윤 (건국대학교 사회환경시스템공학과) ;
  • 강부식 (단국대학교 토목환경공학과) ;
  • 김성준 (건국대학교 사회환경시스템공학과)
  • 발행 : 2009.09.30

초록

The objective of this study is to evaluate the future potential climate and vegetation canopy change impact on a dam watershed hydrology. A $6,661.5\;km^2$ dam watershed, the part of Han-river basin which has the watershed outlet at Chungju dam was selected. The SWAT model was calibrated and verified using 9 year and another 7 year daily dam inflow data. The Nash-Sutcliffe model efficiency ranged from 0.43 to 0.91. The Canadian Centre for Climate Modelling and Analysis (CCCma) Coupled Global Climate Model3 (CGCM3) data based on Intergovernmental Panel on Climate Change (IPCC) SRES (Special Report Emission Scenarios) B1 scenario was adopted for future climate condition and the data were downscaled by artificial neural network method. The future vegetation canopy condition was predicted by using nonlinear regression between monthly LAI (Leaf Area Index) of each land cover from MODIS satellite image and monthly mean temperature was accomplished. The future watershed mean temperatures of 2100 increased by $2.0^{\circ}C$, and the precipitation increased by 20.4 % based on 2001 data. The vegetation canopy prediction results showed that the 2100 year LAI of deciduous, evergreen and mixed on April increased 57.1 %, 15.5 %, and 62.5% respectively. The 2100 evapotranspiration, dam inflow, soil moisture content and groundwater recharge increased 10.2 %, 38.1 %, 16.6 %, and 118.9 % respectively. The consideration of future vegetation canopy affected up to 3.0%, 1.3%, 4.2%, and 3.6% respectively for each component.

키워드

참고문헌

  1. Ahn, S. R., M. J. Park, G. A. Park, and S. J. Kim, 2008. Assessing future climate change impact on hydrologic components of Gyeongancheon watershed. Journal of Korea Water Resources Association 42(1):33-50 (in Korean) https://doi.org/10.3741/JKWRA.2009.42.1.33
  2. B$\ddot{a}$rland, I., T. Kirkkala, O. Malve, and J. K$\ddot{a}$m$\ddot{a}$ri, 2007. Assessing SWAT model performance in the evaluation of management actions for the implementation of the Water Framework Directive in a Finnish catchment. Environmental Modelling & Software 22:719-724 https://doi.org/10.1016/j.envsoft.2005.12.030
  3. Ha, R., H. J. Shin and S. J. Kim, 2007. Proposal of prediction technique for future vegetation information by climate change using satellite image. Journal of the Korean Association of Geographic information studies 10(3): 58-69 (in Korean)
  4. Heuvelmans, G., B. Muys, and J. Feyen, 2006. Regionalisation of the parameters of a hydrological model: Comparison of linear regression models with artificial neural nets. Journal of Hydrology 319:245-265 https://doi.org/10.1016/j.jhydrol.2005.07.030
  5. IPCC, 2007. Climate change 2007: The Physical Science Basis, IPCC contribution of working group I to the Third Assessment Report of the Intergovermental Panel on climate change, Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K. b. Averyt, M. Tigor and H. L. Miller (Eds.). Cambridge Univ. Press, Cambridge, UK. and NY., USA
  6. Kendall, M. G., 1975. Rank Correlation Methods. Griffin, London
  7. Kim, G. S. and T. K. Yim, 2005. Assessment of Characteristics of Regional Climate Change : Urban Effect or Environmental Change, Proceedings of the Korea Water Resources Association Conference, 912-915 (in Korean)
  8. Kim, N. W., B. J. Lee and J. E. Lee, 2006. An evaluation of snowmelt effects using SWAT in Chungju dam basin. Journal of Korea Water Resources Association 39(10): 833-844 (in Korean) https://doi.org/10.3741/JKWRA.2006.39.10.833
  9. Kwon, H. J., S. C. Shin and S. J. Kim, 2005. Climatic Water Balance Analysis Using NOAA/AVHRR Satellite Images. Journal of the Korean Society of Agricultural Engineers 47(1): 3-9 (in Korean)
  10. Lee, S. H., H. K. Jo, J. H. Im, J. H. Chun, M. S. Won, and G. S. Lee, 2007. Development of applied technique and forest information analysis of hyperspectal image. Dongdaemun-gu, Seoul: Korea Forest Research institute, ISBN: 978-89-8176-375-6 (in Korean)
  11. Mann, H. B., 1945. Nonparametric tests against trend. Econometrica 13: 245-259 https://doi.org/10.2307/1907187
  12. Muleta, M. K. and J. W. Nicklow, 2005. Sensitivity and uncertainty analysis coupled with automatic calibration for a distributed watershed model. Journal of Hydrology 306, 127-145 https://doi.org/10.1016/j.jhydrol.2004.09.005
  13. Myneni R. B. and D. L. Williams, 1994. On the relationship between FAPAR and NDVI. Remote Sensing of Environment 49(3): 200-211 https://doi.org/10.1016/0034-4257(94)90016-7
  14. Nash, J. E., and J. V. Sutcliffe, 1970. River flow foresting through conceptual models; Part 1-A discussion of principles. Journal Hydrology 10(3): 282-290 https://doi.org/10.1016/0022-1694(70)90255-6
  15. Park, M. J., H. J. Shin, M. S. Lee, G. A. Park, N. W. Kim, K. J. Lim, and S. J. Kim, 2009. Assessment of Future Climate and Vegetation Canopy Changes and Their Impacts on Hydrological Behavior of Dam Watershed Using the SWAT Model. Stochastic Environmental Research and Risk Assessment (Submitted)
  16. Park, J. H., 2005. Analysis of vegetation net primary production algorithm based on MODIS satellite data, Master's Thesis in Inha University (in Korean)
  17. Shin, S. C., S. Jeong, K. T. Kim, J. H. Kim and J. S. Park, 2006. Drought detection and estimation of water deficit using NDVI. Journal of Geographic information system Association of Korea 9(2): 102-114 (in Korean)
  18. Sung, H. H. and O. J. Park, 2000. A Study on distribution and change of NDVI with Land-Cover change in City of Sungnam. Journal of Geographic information system Association of Korea 8(2): 275-288 (in Korean)
  19. Yingxin Gu, Stėphane Bėlair, Jean-Francois Mahfouf and Godelieve Deblonde. 2006. Optimal interpolation analysis of leaf area index using MODIS data. Remote Sensing of Environment 104(3): 283-296 https://doi.org/10.1016/j.rse.2006.04.021
  20. Zhang, G. H., 2007. Predicting hydrologic response to climate change in the Luohe River Basin Using the SWAT model. Trans. of ASAE 50(3): 901-910