摘要
The FAO-56 Penman-Monteith (PMF56) model is accepted as the standard method for estimating reference crop (grass) evapotranspiration. However, poor data availability limits the use of this method in many regions. This study aimed to overcome this limitation (1) by evaluating the goodness-of-fit of selected simple evapotranspiration methods in relation to the PMF56 model and (2) by adjusting four of these models and developing a multiple regression equation for conditions in Poland using the PMF56 model as a reference. Using daily meteorological data, four simple models were calibrated by the generalised reduced gradient (GRG) method; moreover, a multiple regression equation was developed on the basis of Cochrane-Orcutt estimation because the error term of the ordinary least squares model was autocorrelated. When radiation data were lacking and sunshine duration data were available, the PMF56 method with a calibrated ?ngstr?m-based estimation of solar radiation was the most accurate method (relative error, RE--.096, for Sulejów). When neither radiation nor sunshine duration data were included in the dataset, the calibrated Penman method performed best (RE--.254). Moreover, when only temperature or pan evaporation data were available, the calibrated Hargreaves method provided the most accurate results (RE--.275). Much poorer results were obtained using the calibrated pan coefficient method (RE--.435). Ultimately, we developed a multiple regression method in this study that exhibited good performance (RE--.170). Taking into account the data limitations, the methods calibrated in this study are recommended for estimating evapotranspiration in Central Europe. This approach would substantially decrease the errors produced by the recommended non-calibrated equations.