Applying Multi-source Remote Sensing Data on Estimating Ecological Water Requirement of Grassland in Ungauged Region

Abstract The ecological water requirement of grassland in the year 2009 in Ili river basin in growing season is calculated according to multi-source remote sensing data, including MODIS products (Land Surface Temperature, Leaf Area Index, and emissivity), Global Land Data Assimilation System (GLDAS)-wind speed, monthly mean air temperature, GLDAS-daily maximum and minimum air temperature, STRM-DEM and MERIS land cover product. Radiation estimation method in SEBS model, the FAO- recommended Penman-Monteith formula and single crop coefficient method are adopted to calculate net solar radiation, reference evapotranspiration and crop coefficient, respectively. The results show that ecological water requirement of grassland in April is the lowest, about 2.90 mm/day, while that in July reached its peak value, about 4.66 mm/day. Except the result in May, the ecological water requirement at east side is higher than other sides of the river basin. The analysis on obtained results reveals that multi-source remote sensing data can be effectively used instead of observed data to estimate ecological water requirement in arid and semi-arid region where meteorological and hydrological data are nearly ungauged.