Hydrology and Earth System Sciences www.hydrol-earth-syst-sci.net 1027-5606 1607-7938 13 10 2009 10.5194/hess-13-1775-2009 http://www.hydrol-earth-syst-sci.net/13/1775/2009/ http://www.hydrol-earth-syst-sci.net/13/1775/2009/hess-13-1775-2009.html http://www.hydrol-earth-syst-sci.net/13/1775/2009/hess-13-1775-2009.pdf 1775 1787 2009-10-05 Regional estimation of daily to annual regional evapotranspiration with MODIS data in the Yellow River Delta wetland L. Jia li.jia@wur.nl G. Xi S. Liu C. Huang Y. Yan G. Liu Alterra, Wageningen University and Research Centre, The Netherlands State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, China National Marine Data & Information Service, Tianjin, China State key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing, China Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China China National Climate Centre, Beijing, China Evapotranspiration (ET) from the wetland of the Yellow River Delta (YRD) is one of the important components in the water cycle, which represents the water consumption by the plants and evaporation from the water and the non-vegetated surfaces. Reliable estimates of the total evapotranspiration from the wetland is useful information both for understanding the hydrological process and for water management to protect this natural environment. Due to the heterogeneity of the vegetation types and canopy density and of soil water content over the wetland (specifically over the natural reserve areas), it is difficult to estimate the regional evapotranspiration extrapolating measurements or calculations usually done locally for a specific land cover type. Remote sensing can provide observations of land surface conditions with high spatial and temporal resolution and coverage. In this study, a model based on the Energy Balance method was used to calculate daily evapotranspiration (ET) using instantaneous observations of land surface reflectance and temperature from MODIS when the data were available on clouds-free days. A time series analysis algorithm was then applied to generate a time series of daily ET over a year period by filling the gaps in the observation series due to clouds. A detailed vegetation classification map was used to help identifying areas of various wetland vegetation types in the YRD wetland. 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