Korean Journal of Agricultural and Forest Meteorology (한국농림기상학회지)

Korean Society of Agricultural and Forest Meteorology (한국농림기상학회)
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Evaluation of MODIS-derived Evapotranspiration at the Flux Tower Sites in East Asia

동아시아 지역의 플럭스 타워 관측지에 대한 MODIS 위성영상 기반의 증발산 평가

  • Jeong, Seung-Taek (Department of Environmental Science, Kangwon National University) ;
  • Jang, Keun-Chang (Department of Environmental Science, Kangwon National University) ;
  • Kang, Sin-Kyu (Department of Environmental Science, Kangwon National University) ;
  • Kim, Joon (Department of Atmospheric Sciences/Global Environment Lab, Yonsei University) ;
  • Kondo, Hiroaki (National Institute of Advanced Industrial Science and Technology (AIST)) ;
  • Gamo, Minoru (National Institute of Advanced Industrial Science and Technology (AIST)) ;
  • Asanuma, Jun (Terrestrial Environment Research Center University of Tsukuba) ;
  • Saigusa, Nobuko (Center for Global Environmental Research (CGER), National Institute for Environmental Studies (NIES)) ;
  • Wang, Shaoqiang (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences) ;
  • Han, Shijie (Institute of Applied Ecology, Chinese Academy of Science)
  • 정승택 (강원대학교 환경과학과) ;
  • 장근창 (강원대학교 환경과학과) ;
  • 강신규 (강원대학교 환경과학과) ;
  • 김준 (연세대학교 대기과학과/지구환경 연구소) ;
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  • ;
  • ;
  • Published : 2009.12.30
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Abstract

Evapotranspiration (ET) is one of the major hydrologic processes in terrestrial ecosystems. A reliable estimation of spatially representavtive ET is necessary for deriving regional water budget, primary productivity of vegetation, and feedbacks of land surface to regional climate. Moderate resolution imaging spectroradiometer (MODIS) provides an opportunity to monitor ET for wide area at daily time scale. In this study, we applied a MODIS-based ET algorithm and tested its reliability for nine flux tower sites in East Asia. This is a stand-alone MODIS algorithm based on the Penman-Monteith equation and uses input data derived from MODIS. Instantaneous ET was estimated and scaled up to daily ET. For six flux sites, the MODIS-derived instantaneous ET showed a good agreement with the measured data ($r^2=0.38$ to 0.73, ME = -44 to $+31W\;m^{-2}$, RMSE =48 to $111W\;m^{-2}$). However, for the other three sites, a poor agreement was observed. The predictability of MODIS ET was improved when the up-scaled daily ET was used ($r^2\;=\;0.48$ to 0.89, ME = -0.7 to $-0.6\;mm\;day^{-1}$, $RMSE=\;0.5{\sim}1.1\;mm\;day^{-1}$). Errors in the canopy conductance were identified as a primary factor of uncertainty in MODIS-derived ET and hence, a more reliable estimation of canopy conductance is necessary to increase the accuracy of MODIS ET.

지표 증발산은 육상 생태계의 수문순환의 주요 성분으로서, 지표-대기간의 에너지 교환, 미기후, 지역의 수자원 함량, 식생의 일차생산성 등에 중요한 영향을 미친다. 증발산을 추정하기 위한 방법들 중에서 MODIS를 이용한 방법은 위성 자료만을 사용하여 넓은 지역에 대한 지속적인 증발산 모니터링이 가능하다는 장점을 갖고 있다. 본 연구에서는 MODIS 기반의 증발산 추정 알고리즘을 동아시아 지역에 적용하고, 그 신뢰도를 평가하였으며, 주요 오차요인을 분석하였다. 증발산 평가 결과 여섯 연구지역(GDK, HFK, TKY, TMK, CBS, SKT)에서는 $r^2$가 0.38~0.73, ME 와 RMSE가 각각 $-44{\sim}+31W\;m^{-2}$, $48{\sim}111W\;m^{-2}$로 신뢰할 만한 결과를 나타냈다. 하지만 다른 세 연구지역(HBG, QYZ, MKL)에서는 관측 값과 비교해서 차이를 나타내었고, 과소평가하는 경향을 보였다. HBG, MKL 지역은 MODIS 기상 자료 및 복사요소의 오차가 주요 원인으로 나타났다. 그러나 QYZ지역은 기상 자료와 복사요소가 모두 좋은 일치도를 보였기 때문에, 모형의 모수와 관련된 오차가 주요 원인의 하나로 판단된다. 임관 전도도의 오차가 증발산 오차에 미치는 영향을 분석한 결과, HBG지역을 제외한 다른 연구지 역에서 r값이 0.59~0.82로 관측값과의 상관성이 높은 것을 확인하였다. 또한 MODIS로부터 산출된 순간 증발산을 일 단위로 확장시킨 결과, 순간 증발산의 일치도가 떨어졌던 3개 연구지역을 제외하고 6개 지역에서 $r^2$가 0.44~0.89, ME와 RMSE는 각각 $-0.7{\sim}+0.6mm\;day^{-1}$, $0.5{\sim}1.1mm\;day^{-1}$의 범위로 신뢰도 있는 결과를 나타냈다.

Keywords

References

  1. Allen, R.G., M. E. Jensen, J. L. Wright, and R.D. Burman, 1989: Operational estimates of reference evapotranspiration, Agronomy Journal 81, 650-662 https://doi.org/10.2134/agronj1989.00021962008100040019x
  2. Annear, R. L., and S. A. Wells, 2007: A comparison of five models for estimating clear-sky solar radiation, Water Researches Research 43, W10415
  3. Bird, R. E. and R. L. Hulstrom, 1981: A simplified clear sky model for direct and diffuse insolation on horizontal surfaces, SERI Report TR642-761: Golden, USA
  4. Bisht, G., V. Venturini, S. Islam, and L. Jiang, 2005: Estimation of the net radiation using MODIS (Moderate Resolution Imaging Spectroradiometer) data for clear sky days, Remote Sensing of Environment 97, 52-67 https://doi.org/10.1016/j.rse.2005.03.014
  5. Boegh, E., H. Soegaard, and A. Thomsen, 2002: Evaluating evapotranspiration rates and surface conditions using Landsat TM to estimate atmospheric resistance and surface resistance, Remote Sensing of Environment 79,329-343 https://doi.org/10.1016/S0034-4257(01)00283-8
  6. Carlson, T. (1991) Modeling stomatal resistance: an overview of the 1989 workshop at the Pennsylvania State University, Agricultural and Forest Meteorology 54, 103-106 https://doi.org/10.1016/0168-1923(91)90001-7
  7. Chen, R., E. Kang, X. Ji, J. Yang, and J. Wang, 2007: An hourly solar radiation model under actual weather and terrain conditions: A case study in Heihe river basin,Energy 32, 1148-1157 https://doi.org/10.1016/j.energy.2006.07.006
  8. Cleugh, H. A., R. Leuning, Q. Mu, and S. W. Running, 2007: Regional evaporation estimates from flux tower and MODIS satellite data, Remote Sensing of Environment 106, 285-304 https://doi.org/10.1016/j.rse.2006.07.007
  9. Crago, R. D., 1996: Comparison of the evaporative fraction and the Priestley-Taylor α for parameterizing daytime evaporation, Water Resource Research 32, 1403-1409 https://doi.org/10.1029/96WR00269
  10. Dingman, S. L., 1994: Physical hydrology (2nd ed.), New Jersey: Prentice Hall., 272-324
  11. Federer, C. A., C. Vorosmarty, and B. Fekete, 1996: Intercomparison of methods for calculating potential evaporation in regional and global water balance models, Water Resource Research 32, 2315-2321 https://doi.org/10.1029/96WR00801
  12. Fisher, J. B., Tu, K. P., and Baldocchi, D. D. 2008: Global estimation of the land-atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites, Remote Sensing of Environment 112,901-919 https://doi.org/10.1016/j.rse.2007.06.025
  13. Heinsch, F. A., M. Reeves, P. Votava, S. Kang, C. Milesi, M. Zhao, 2003: User’s guide GPP and NPP (MOD17A2/ A3) products, NASA MODIS Land Algorithm 1-57
  14. Heinsch, F. A., M. Zhao, S. W. Running, J. Kimball, R. Nemain, and K. Davis, 2006: Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations, IEEE Transactions on Geoscience and Remote Sensing 44, 1908-1925 https://doi.org/10.1109/TGRS.2005.853936
  15. Hong, J. K., T. J. Choi, and J. Kim, 1997: Evapotranspiration from Plants into the Atmosphere: Micrometeorological Perspectives, Asia-Pacific Journal of Atmospheric Sciences 33, 569-579
  16. Jang, K. C., S. K. Kang, H. W. Kim, and H. J. Kwon, 2009: Evaluation of Shortwave Irradiance and Evapotranspiration Derived from Moderate Resolution Imaging Spectroradiometer (MODIS), Asia-Pacific Journal of Atmospheric Sciences 45, 233-246
  17. Jiang, L., S. Islam, 2001: Estimation of surface evaporation map ocer shuthern Great Plains using remote sensing data, Water Resources Research 37, 329-340 https://doi.org/10.1029/2000WR900255
  18. Kelliher, F.M.,R. Leuning, M.R. Raupach, E.-D. Schulze, 1995: Maximum conductances for evaporation from global vegetation types, Agricultural and Forest Meteorology 73,1-16 https://doi.org/10.1016/0168-1923(94)02178-M
  19. Matsumoto, K., T. Ohta, and T. Tanaka, 2005: Dependence of stomatal conductance on leaf chlorophyll concentration and meteorological variables, Agricultural and Forest Meteorology 132, 44-57 https://doi.org/10.1016/j.agrformet.2005.07.001
  20. Mu, Q., F. A. Heinsch, M. Zhao, and S. W. Running, 2007: Development of a global evapotranspiration algorithm based on MODIS and global meteorology data, Remote Sensing of Environment 111, 519-536 https://doi.org/10.1016/j.rse.2007.04.015
  21. Nishida, K., R. R. Nemani, S. W. Running, and J. M. Glassy, 2003a: An operational remote sensing algorithm of land surface evaporation, Journal of Geophysical Research108, D9, 4270
  22. Nishida, K., R. R. Nemani, J. M. Glassy, and S. W. Running, 2003b: Development of an evapotranspiration Index Aqua/MODIS for Monitoring Surface Moisture Status, IEEE Transaction on Geoscience and Remote Sensing 41, 493-501 https://doi.org/10.1109/TGRS.2003.811744
  23. Penman, H.L. 1948: Natural evaporation from open water, bare soil, and grass, proceedings of the Royal Society series A 193, 108-120
  24. Prata, A. J.,1996: A new long-wave formula for estimating downward clear-sky radiation at the surface, Quarterly Journal of the Royal Meteorological Society 122, 1127-1151 https://doi.org/10.1002/qj.49712253306
  25. Ryu, Y., S. Kang, S. Moon, and J. Kim, 2008: Evaluation of Moderate Resolution Imaging Spectroradiometer (MODIS) derived land surface radiation balance over complex terrain and heterogeneous landscape for clear sky days, Agricultural and Forest Meteorology 148, 1538-1552 https://doi.org/10.1016/j.agrformet.2008.05.008
  26. Shin, S. C., and T. Y. An, 2007: Development of Estimating Method for Areal Evapotranspiration using Satellite Data, Korean Journal of Geography Information 10, 70- 80 (in Korean with English abstract)
  27. Shuttleworth, W. J., R. J. Gurney, A. Y. Hsu, and J. P. Ormsby, 1989: FIFE: The variation in energy partition at surface flux sites, Proceedings International Association of Hydrological Sciences, Assembly, Baltimore, 67-74
  28. Sugita, M., and W. Brutsaert, 1991: Daily evaporation over a region from lover boundary-layer profiles measured with radiosondes, Water Resources Research 27, 747-752 https://doi.org/10.1029/90WR02706
  29. Venturini, V., S. Islam, and L. Rodriguez, 2008: Estimation of evaporative fraction and evapotranspiration from MODIS products using a complementary based model, Remote Sensing of Environment 112, 132-141 https://doi.org/10.1016/j.rse.2007.04.014
  30. Zhang, L., and R. Lemeur, 1995: Evaluation of daily evapotranspiration estimates from instantaneous measurements, Agricultural and Forest Meteorology 74, 139-154 https://doi.org/10.1016/0168-1923(94)02181-I

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