Journal of Korea Water Resources Association (한국수자원학회논문집)

Korea Water Resources Association (한국수자원학회)
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Estimating Climate Change Impact on Drought Occurrence Based on the Soil Moisture PDF

토양수분 확률밀도함수로 살펴본 가뭄발생에 대한 기후변화의 영향

  • Received : 2010.02.24
  • Accepted : 2010.08.02
  • Published : 2010.08.31
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Abstract

This paper describes the modeling of climate change impact on drought using a conceptual soil moisture model and presents the results of the modeling approach. The future climate series is obtained by scaling the historical series, informed by CCCma CGCM3-T63 with A2 green house emission scenario, using a daily scaling method that considers changes in the future monthly precipitation and potential evapotranspiration as well as in the daily precipitation distribution. The majority of the modeling results indicate that there will be more frequent drought in Korea in the future.

본 연구에서는 개념적인 토양수분 모형을 이용하여 가뭄에 대한 기후변화의 영향을 모형화하고, 모형으로부터의 결과를 분석하고 있다. 미래 기후자료로서 A2 온실가스 배출 시나리오에 따라 CCCma CGCM3-T63에 의해 도출된 자료가 이용되며, 일별 강수분포 및 월별 강수량 및 잠재증발산량의 변화를 고려하기 위하여 일별 스케일링 기법이 적용된다. 모형으로부터 도출된 주요결과로부터 미래에는 우리나라에 보다 잦은 가뭄이 있을 수 있음을 살펴볼 수 있다.

Keywords

References

  1. 변희룡 (1996). “한반도에 가뭄을 초래하는 대기 순환.” 한국기상학회지, 한국기상학회, 제32권, pp. 455-469.
  2. 변희룡, 한영호 (1994). “한반도에서 계절별로 발생하는 가뭄에 관한 연구.” 한국기상학회지, 한국기상학회, 제30권, pp. 457-467.
  3. 유철상, 김대하, 김상단 (2006). “EOF 해석 및 다변량시계열 모형을 이용한 농업가뭄 대비능력의 평가.” 한국수자원학회논문집, 한국수자원학회, 제39권, pp. 617-626.
  4. 유철상, 류소라 (2003). “서울지점 가뭄의 재현 및 지속특성 분석.” 한국수자원학회논문집, 한국수자원학회, 제36권, pp. 561-573.
  5. 장연규, 김상단, 최계운 (2006). “SPI 가뭄지수의 EOF 분석을 이용한 가뭄의 시공간적인 특성 연구.”, 한국수자원학회논문집, 한국수자원학회, 제39권, pp. 691-702.
  6. 한국수자원공사 (2002). 가뭄관리 종합대책 수립연구. 한국수자원공사, 대전, p. 554
  7. 한수희, 안재현, 김상단 (2009). “토양수분의 추계학적 거동과 기후변화가 미치는 영향.” 한국수자원학회논문집, 한국수자원학회, 제42권, pp. 433-443. https://doi.org/10.3741/JKWRA.2009.42.6.433
  8. California Department of Water Resources (2009). Using Future Climate Projections to Support Water Resources Decision Making in California. California Climate Change Center, CEC-500-2009-052-D.
  9. Chang, J.S., and Cooper, G. (1970). A practical difference scheme for Fokker-Plank equations. Journal of Computational Physics, 6, pp. 1-16. https://doi.org/10.1016/0021-9991(70)90001-X
  10. Charles, S.P., Bates, B.C., Smith, I.N., and Hughes, J.P. (2004). Statistical downscaling of daily precipitation from observed and modelled atmospheric fields. Hydrological Processes, Vol. 18, pp. 1373-1394. https://doi.org/10.1002/hyp.1418
  11. Dai, A., Trenberth, K.E., and Qian, T. (2004). A Global Dataset of Palmer Drought Severity Index for 1870-2002: Relationship with Soil Moisture and Effects of Surface Warming. American Meteorological Society, Vol. 5, pp. 1117-1130.
  12. Daly, E., and Porporato, A. (2006). Impact of hydroclimatic flucturations on the soil water balance.Water Resources Research, Vol. 42, W06401, doi:10.1029/2005WR004606.
  13. Diaz-Nieto, J., and Wilby, R.L. (2005). A comparison of statistical downscaling and climate change factor methods: Impacts on low flows in the river thames, united Kingdom. Climate Change, Vol. 69, pp. 245-268. https://doi.org/10.1007/s10584-005-1157-6
  14. Entekhabi, D., and Rodriguez-Iturbe, I. (1994). Analytical framework for the characterization of the spacetime variability of soil moisture. Advances in Water Resources, Vol. 17, pp. 35-45. https://doi.org/10.1016/0309-1708(94)90022-1
  15. Fowler, H.J., Blenkinsop, S., and Tebaldi, C. (2007). Linking climate change modelling to impact studies: Recent advances in downscaling techniques for hydrological modelling. International Journal of Climatolgy, Vol. 27, pp. 1547-1578. https://doi.org/10.1002/joc.1556
  16. Gordon, H.B., and O'Farrell, S.P. (1997). Transient climate change in the CSIRO coupled model with dynamic sea ice. American Meteorological Society, Vol. 125, pp. 875-907.
  17. Jackson, T.J., Le, Vine, D.M., Swift, C.T., “Schmugge, T.J., and Schiebe, F.R. (1995). Large area mapping of soil moisture using the ESTAR passive microwave radiometer in Washita '92. Remote Sensing of Environment, Vol. 53, pp. 27-37.
  18. Kavvas, M.L. (2003). Nonlinear hydrologic processes: Conservation equation for determining their means and probability distribution. Journal of Hydrologic Engineering, Vol. 8, No. 2, pp. 44-53. https://doi.org/10.1061/(ASCE)1084-0699(2003)8:2(44)
  19. Kim, S., Han, S., and Kavvas, M.L. (2007). Analytical derivation of steady-state soil water probability density function coupled with simple stochastic point rainfall model. Journal of Hydrologic Engineering ASCE, Vol. 13, No. 11, pp. 1069-1077. https://doi.org/10.1061/(ASCE)1084-0699(2008)13:11(1069)
  20. Mckee, T.B., Doesken, N.J., and Kleist, J. (1993) The relationship of drought frequency and duration to time scale. Eighth Conference on Applied Climatology, 17-22 January 1993, Anaheim, California.
  21. Nunez, M., and McGregor, J.L. (2007). Modelling future water environments of Tasmania, Australia. Climate Research, Vol. 34, No. 1, pp. 25-37. https://doi.org/10.3354/cr034025
  22. Porporato, A., Daly, E., and Rodriguez-Iturbe, I (2004). Soil water balance and ecosystem response to climate change. American Naturalist, Vol. 164, No. 5, pp. 625-632. https://doi.org/10.1086/424970
  23. Porporato, A., Laio, F., Ridolfi, L., and Rodriguez-Iturbe, I. (2001). Plants in water-controlled ecosystems: Active role in hydrologic processes and response to water stress. III. Vegetation water stress. Advances inWater Resources, Vol. 24, pp. 725-744. https://doi.org/10.1016/S0309-1708(01)00006-9
  24. Rodriguez-Iturbe, I., Porporato, A., Ridolfi, L., Isham, V., and Cox, D.R. (1999). Probabilistic modeling of water balance at a point: The role of climate, soil and vegetation. Proceedings The Royal Society A, Vol. 455, pp. 3789-3805. https://doi.org/10.1098/rspa.1999.0477
  25. Rodriguez-Iturbe, I., Vogel, G.K., Rigon, R., Entekhabi, D., Castelli, F., and Rinaldo, A. (1996). On the spatial organization of soil moisture fields. Geophysical Research Letters, Vol. 22, pp. 2757-2760.
  26. Sheffield, J., Goteti, G., Wen, F., and Wood, E.F. (2004). A simulated soil moisture based drought analysis for the United States. Journal of Geophysical Research Atmospheres, Vol. 109, D24108, doi:10.1029/2004JD005182
  27. Silverman, B.W. (1986). Density estimator for statistics and data analysis. Chapman and Hall, New York.
  28. Yoo, C., Kim, S., and Kim, T.W. (2006). Assessment of drought vulnerability based on the soil moisture PDF. Stochastic Environmental Research and Risk Assessment, Vol. 21, No. 2 pp. 131-141. https://doi.org/10.1007/s00477-006-0050-9

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