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준 분포형 수문모형 SLURP에서 융설매개변수 적용 및 영향 평가

Application of Snowmelt Parameters and the Impact Assessment in the SLURP Semi-Distributed Hydrological Model

  • 신형진 (건국대학교 대학원 사회환경시스템공학과) ;
  • 김성준 (건국대학교 생명환경과학대학 사회환경시스템공학과)
  • 발행 : 2007.08.31

초록

본 연구는 충주댐 유역을 대상으로 SLURP 모형에서 RS, GIS를 이용한 융설매개변수 적용 및 영향을 평가하고자 한다. 모형의 음설 관련 매개변수 준비를 위해 3 set (1998-1999, 2000-2001, 2001-2002)의 NOAA AVHRR 위성영상을 분석하였다. 적설분포면적은 채널 1번, 3번, 4번을 이용하여 추출하였고, 적설심은 지상기상관측소의 적설심 자료를 이용하여 공간적으로 내삽하여 추출하였다. 융설 매개변수와 DEM, 토지피복도, NDVI, 수문기상자료를 이용하여 3개년도(1998, 2000, 2001)의 일별유출량을 모의하여 보정하였다 그리고 보정된 매개변수를 이용하여 1개년도(1999)를 검증하였다. 4년(1998-2001)동안의 유량 비교 결과, 평균 Nash-Sutcliffe의 모형 효율은 0.76이고 적설 및 융설 기간(1월$\sim$5월)동안의 평균 모형 효율은 0.57이다. 융설매개변수 미고려시 평균 Nash-Sutcliffe의 모형 효율은 0.73이고 적설 및 융설 기간(1월$\sim$5월)동안의 평균 모형 효율은 0.19이다. 융설매개변수를 포함한 유출량이 융설매개변수를 포함하지 않은 경우보다 관측유량의 수문시계열적 특성을 잘 표현하는 결과를 보였다.

The purpose of this paper is to prepare snowmelt parameters using RS and GIS and to assess the snowmelt impact in SLURP (Semi-distributed Land Use-based Runoff Process) model for Chungju-Dam watershed $(6,661.5km^2)$. Three sets of NOAA AVHRR images (1998-1999, 2000-2001, 2001-2002) were analyzed to prepare snow-related data of the model during winter period. Snow cover areas were extracted using 1, 3 and 4 channels, and the snow depth was spatially interpolated using snowfall data of ground meteorological stations. With the snowmelt parameters, DEM (Digital Elevation Model), land cover, NDVI (Normalized Difference Vegetation Index) and weather data, the model was calibrated for 3 years (1998, 2000, 2001), and verified for 1 year (1999) using the calibrated parameters. The average Nash-Sutcliffe efficiencies for 4 years (1998-2001) discharge comparison with and without snowmelt parameters were 0.76 and 0.73 for the full period, and 0.57 and 0.19 for the period of January to May. The results showed that the spatially prepared snow-related data reduced the calibration effort and enhanced the model results.

키워드

참고문헌

  1. 배덕효, 오재호 (1998). '장기 유출해석에서의 유설영향에 관한 기초 연구.' 한국수자원학회논문집, 한국수자원학회, 제31권, 제6호, pp. 833-844
  2. 이상호, 안태진, 윤병만, 심명필 (2003). '적설 및 융설모의를 포함한 탱크모형의 소양강댐 및 충주댐에 대한 적용.' 한국수자원학회논문집, 한국수자원학회, 제36권, 제5호 pp. 851-861
  3. 임혁진, 권형중, 장철희, 김성준 (2004). 'SLURP 모형을 이용한 유출수문분석 : 소양강댐 유역을 대상으로.' 한국수자원학회논문집, 한국수자원학회, 제37권, 제8호, pp. 631-641
  4. Baglio, J.V., and Holroyd, E.W. (1989). 'Methods for Operational Snow Cover Area Mapping Using the Advanced Very High Resolution Radiometer San Juan Mountain Test Study,' Research Technical Report, USGS EROS Data Center, Sioux Falls, South Dakota, March 1989 : 820
  5. Baumgartner, M.F., Seidel, K., and Martinec, J. (1987). 'Toward Snowmelt Runoff Forecasting Based on Multisensor Remote Sensing Information.' IEEE Transactions on Geoscience and Remote Sensing, Vol. GE-25, NO.6 https://doi.org/10.1109/TGRS.1987.289744
  6. Brubaker, K., Range, A. and Kustas, W. (1996). ' Incorporating radiation inputs into the Snowmelt Runoff Model.' Hydrological Processes, 464
  7. Kazama, S. (1995). Study on Water Cyde in Middle Scale Region, Dept. Civil Engrg, Tohoku University, Japan
  8. Kite, G.W. (1998). 'Land surface parameterizations of GCMs and macroscale hydrological models.' Journal American Water Resources Association, Vol. 34, No.6, pp. 1247-1254 https://doi.org/10.1111/j.1752-1688.1998.tb05428.x
  9. Kustas, W.P., Range, A., and Uijlenhoet, R. (1994). 'A simple energy budget algorithm for the snowmelt runoff model.' Water Resources Research, Vol. 30, No.5, pp. 1515-1527 https://doi.org/10.1029/94WR00152
  10. Martinec, J., Range, A., and Major, E. (1983). The Snoumelt-Runoff Model (SRM) : User's Manual (NASA Reference Publication No. 1100), Scientific and Technical Information Branch, NASA, Washington, DC
  11. Nash, J.E., and Sutcliffe, J.V. (1970). 'River flow forecasting through conceptual models; Part 1 - A discussion of principles.' J. Hydrology, Vol. 10, No.3, pp. 282-290 https://doi.org/10.1016/0022-1694(70)90255-6
  12. Range, A., and Itten, K.I. (1976). 'Satellite Potentials in Snowcover Monitoring and Runoff Prediction.' Nordic Hydrology, Vol. 7, pp. 209-230 https://doi.org/10.2166/nh.1976.014
  13. Range, A. and Martinec, J. (1995). 'Revisiting the degree-day method for snowmelt conditions.' Wat. Res. Bull., 31, 4, 657-669 https://doi.org/10.1111/j.1752-1688.1995.tb03392.x
  14. Ranzi, R., Grossi, G., and Bacchi, B. (1999). 'Ten Years of Monitoring Areal Snowpack in the Southern Alps Using NOAA - AVHRR Imagery, Ground Measurements and Hydrological Data.' Hydrological Process, Vol. 13, pp. 2079-2095 https://doi.org/10.1002/(SICI)1099-1085(199909)13:12/13<2079::AID-HYP875>3.0.CO;2-U
  15. Sandra, L., and Woo, M.K. (2003). 'Application of hydrological model with increasing complexity to subarctic catchments.' Journal of Hydrology, Vol. 270, pp. 145-157 https://doi.org/10.1016/S0022-1694(02)00291-3
  16. Seidel, K., and Martinec, J. (2002). 'NOAA/ AVHRR Monitoring of Snow Cover for Modelling Climate-Affected Runoff in Ganges and Brahmaputra Rivers.' Proceeding of EARSeL eProceedings, NO.2, pp. 188-200
  17. Simic, A., Fernandes, R., Brown, R., Romanov, P., and Park, W. (2004). 'Validation of VEGETATION, MODIS, and GOES+SSM/I Snow-Cover Products over Canada Based on Suoface Snow Depth Observations.' Hydrological Process, Vol. 18, pp. 1089-1104 https://doi.org/10.1002/hyp.5509
  18. Tarboten, D.G., Al-Adhami, M.J. and Bowles, D.S. (1991). 'A preliminary comparison of snowmelt models for erosion prediction.' Proceedings of the 59th Annual Western Snow Conference, 12-15 April, 1991, Juneau, Alaska, 79-90
  19. Tekeli A.E., Akyurek, Z., Sorman, A.A., Sensoy, A., and Sonnan, A.U. (2005). 'Using MODIS Snow Cover Maps in Modeling Snowmelt Runoff Process in the Eastern Part of Turkey.' Remote Sensing of Environment, Vol. 97, pp. 216-230 https://doi.org/10.1016/j.rse.2005.03.013

피인용 문헌

  1. Assessment of Snowmelt Impact on Chungju Dam Watershed Inflow Using Terra MODIS Data and SWAT Model vol.34, pp.2, 2014, https://doi.org/10.12652/Ksce.2014.34.2.0457