基于温度资料的参考作物蒸发蒸腾量计算方法研究

FAO56 Penman-Monteith equation (FAO56-PM) is the standard method for estimating reference evapotranspiration (ET0). However, the climatic variables that FAO56-PM required for estimating ET0 would not always available in a given station. In this paper, temperature-based approaches and BP artificial neural network model based on temperature data were analyzed and established. Based on the results of FAO56-PM, performance of four temperature-based approaches (Hargreaves, adjusted Thornthwaite, reduced set FAO56-PM and Mc cloud) under humid climate of China was compared and analyzed. Then, methods were calibrated and a BP artificial neural network model only based on temperature data was established. Results show that: Hargreaves, adjusted Thornthwaite, reduced set FAO56-PM predicted greater ET0 than FAO56-PM when daily ET0 was relatively low and predicting less ET0 when ET0 was relatively high. Adjusted Thornthwaite was proved to be the best method for estimation of ET0 under this location and Mc cloud was the worst one compared to FAO56-PM. Except for Mc cloud, calibrated temperature-based methods were suitable to the climate condition with low error. Precision of BP model was higher than some temperature-based methods and could be used for the prediction of ET0 when only temperature was available.