Land surface evapotranspiration estimation combining soil texture information and global reanalysis datasets in Google Earth Engine

ABSTRACT

Global accurate evapotranspiration (ET) maps are crucial to monitor the water balance on the Earth’s surface. For this purpose, Walker et al. (2019) developed a methodology to estimate ET (ET_WV), considering that the soil properties and moisture (SM) are important limiting factors. In this work ET_WV was assessed in different land covers, land uses and soil properties using FLUXNET data and climate reanalysis datasets available in Google Earth Engine (GEE). GEE application programming interface (API), a powerful programming tool for non-experienced user, was used here to derived global ET_WV maps. ET_WV, computed with in situ FLUXNET data resulted in an overall ubRMSE of about 1.58 mm d^?1. The ET_WV estimates with GEE datasets yielded RMSE at least 56% smaller than those published by the available weather datasets. So, ET_WV methodology showed to be suitable for deriving global ET maps from different sources of data.