Resumen
Accurate and reliable estimations of reference evapotranspiration (ET0) are imperative in irrigation scheduling and water resource planning. This study aims to analyze the spatiotemporal trends of the monthly ET0 calculated by the Penman?Monteith FAO-56 (PMF-56) model in the Huai River Basin (HRB), eastern China. However, the use of the PMF-56 model is limited by the insufficiency of climatic input parameters in various sites, and the alternative is to employ simple empirical models. In this study, the performances of 13 empirical models were evaluated against the PMF-56 model by using three common statistical approaches: relative root-mean-square error (RRMSE), mean absolute error (MAE), and the Nash?Sutcliffe coefficient (NS). Additionally, a linear regression model was adopted to calibrate and validate the performances of the empirical models during the 1961?2000 and 2001?2014 time periods, respectively. The results showed that the ETPMF increased initially and then decreased on a monthly timescale. On a daily timescale, the Valiantzas3 (VA3) was the best alternative model for estimating the ET0, while the Penman (PEN), WMO, Trabert (TRA), and Jensen-Haise (JH) models showed poor results with large errors. Before calibration, the determination coefficients of the temperature-based, radiation-based, and combined models showed the opposite changing trends compared to the mass transfer-based models. After calibration, the performance of each empirical model in each month improved greatly except for the PEN model. If the comprehensive climatic datasets were available, the VA3 would be the recommended model because it had a simple computation procedure and was also very well correlated linearly to the PMF-56 model. Given the data availability, the temperature-based, radiation-based, Valiantzas1 (VA1) and Valiantzas2 (VA2) models were recommended during April?October in the HRB and other similar regions, and also, the mass transfer-based models were applicable in other months.