Improving remotely sensed actual evapotranspiration estimation with raster meteorological data

Evapotranspiration is a process driven by weather, vegetation, and soil conditions. The complex interrelations among these parameters have been modelled by numerous remote-sensing energy balance algorithms. When estimating evapotranspiration on a regional scale, the spatial variability of the weather parameters is important and thus closer attention to the meteorological input data is required. The aim of this work is to improve the accuracy of estimating actual evapotranspiration by integrating outputs from a meteorological model into a remotely sensed energy balance model. In order to achieve this, a time series of Terra Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images were processed to retrieve daily evapotranspiration values using raster meteorological data. The ITA-MyWater tool implementing the ReSET-Raster algorithm was used in the Tamega trans-boundary watershed shared by Portugal and Spain. The results were compared to the global MODIS evapotranspiration products for validation, achieving a coefficient of correlation of 0.61 and a root mean square error of 0.92 mm day(-1). Compared with an actual evapotranspiration map that was generated using weather station data, there were improvements in the spatial distribution, especially in dry areas where differences between evapotranspiration estimations of up to 1.88 mm day(-1) were noticed. The proposed methodology contributes to the improved estimation of water use, an important parameter of water cycles, using satellite remote-sensing data.