Improving remotely sensed actual evapotranspiration estimation with raster meteorological data

Evapotranspiration is a process driven by weather, vegetation, and soil conditions. Thecomplex interrelations among these parameters have been modelled by numerousremote-sensing energy balance algorithms. When estimating evapotranspiration on aregional scale, the spatial variability of the weather parameters is important and thuscloser attention to the meteorological input data is required. The aim of this work is toimprove the accuracy of estimating actual evapotranspiration by integrating outputsfrom a meteorological model into a remotely sensed energy balance model. In order toachieve this, a time series of Terra Moderate Resolution Imaging Spectroradiometer(MODIS) satellite images were processed to retrieve daily evapotranspiration valuesusing raster meteorological data. The ITA-MyWater tool implementing the ReSET-Raster algorithm was used in the Tâmega trans-boundary watershed shared by Portugaland Spain. The results were compared to the global MODIS evapotranspirationproducts for validation, achieving a coefficient of correlation of 0.61 and a rootmean square error of 0.92 mm day–1. Compared with an actual evapotranspirationmap that was generated using weather station data, there were improvements in thespatial distribution, especially in dry areas where differences between evapotranspira-tion estimations of up to 1.88 mm day–1were noticed. The proposed methodologycontributes to the improved estimation of water use, an important parameter of watercycles, using satellite remote-sensing data.