Abstract

Two methods are used for estimating evapotranspiration (ET) rate: scintillometry and meteorological measurements with the FAO-PM56 model based on the reference Evapotranspiration for the crop (ETO) with the specific crop coefficient (Kc) for corn at its stage development. Additionally, both methods for different environmental parameters are compared and which one of them can have more influence on the final result of ET. A model to forecast ET based on an artificial neural network (ANN) is developed, in order to anticipate the necessary action for water management. Finally, it is selected the best ET method of calculation giving a good prediction, and besides, the optimal numbers for both training days and predicted days to obtain a reliable forecast are found.