摘要：In this study, the class A pan coefficient (K p ) values were simulated via the M5 tree model, by using daily meteorological data of four stations in East Azerbaijan province, which has arid and cold climate in the northwest of Iran. Firstly, FAO-24 and FAO-56 methods, which are commonly used to calculate K p values, were taken into consideration in the study. The K p values calculated in the second stage were assumed to be observed values and were taken as the outputs of the M5 model. Four different training datasets consisting of 66, 70, 75 and 80% of the original data were tested. The best results were obtained when 70% of the data were used for training and 30% for testing. Results indicated that K p value was easily simulated with simple linear equations having high accuracy rate (R 2 = 0.99) in all the stations. Furthermore, the K p value was easily simulated using only two meteorological variables (relative humidity and wind speed) without the need for complex tables and equations. The most important finding of this study was the easy estimation of the K p with a number of linear functions obtained from the M5 model. As a result of this study, the simulated K p can help us calculate evapotranspiration accurately for more effective irrigation planning. The proposed method offers advantages as it is simpler and easier than the existing approaches in the literature.
关键词：Class A Pan; Data mining; Decision tree; Evapotranspiration; Pan coefficient
