Abstract:Evapotranspiration (ET) plays an important role in agricultural irrigation and water resources management. ET can be accurately estimated by the FAO-Penman-Monteith method (ETFPM). The ETFPM method is the standard reference method for ET estimation. This method needs to provide more detailed meteorological data. For the estimation of ET, it is necessary to find an alternative method that uses less input data without affecting the accuracy of the prediction. This study used 5 radiation-based models, including Makkink (ETMAK), Priestley and Taylor (ETPT), Abtew (ETABT), Jensen-Haise (ETJH), McGuinness and Bordne (ETMB), and 3 temperature-based models, including Hargreaves and Samani (ETHS), Hamon (ETHAM) and Linacre (ETLIN), and a model Penman (ETPEN) based on aerodynamics. Using the long-term data from 6 meteorological and hydrological stations in the Hancang River Basin, the selected model were evaluated by comparing them with ETFPM on a monthly and growing season scale. The statistical analysis revealed that ETJH and ETHAM are the best forecasting methods for monthly ET in 67% and 33% of the study area respectively. In the study area, the radiation-based methods were better than temperature-based methods. The cumulative values of ET during the vegetation growth periods showed that the Jensen-Haise method and Hamon method perform best in the warm season and autumn and winter growing seasons, while the best prediction method for the spring growing season only included the Jensen-Haise method. However, divergence between estimations of the best alternative methods and the reference method showed that the best ET alternative methods might be unreliable in some regions. Accordingly, the spatiotemporal variability in predictability performance of ET models should be taken into account prior to use.