Use of average data of 181 synoptic stations for estimation of reference crop evapotranspiration by temperature-based methods

Evapotranspiration has a highlighted role in agricultural and forest meteorology researches, hydrological cycle, irrigation scheduling, and water resources management. There are many models to estimate the evapotranspiration including mass transfer, radiation, temperature, and pan evaporation-based models. This study aims to compare temperature-based models to detect the best model under different weather conditions. For this purpose, weather data were gathered from 181 synoptic stations in 31 provinces of Iran. The evapotranspiration was estimated using 11 temperature-based models and was compared with the FAO Penman-Monteith model. The results showed that the Modified Hargreaves-Samani models estimate the evapotranspiration better than other models in the most provinces of Iran (25 provinces). However, the values of R2 were less than 0.98 for 15 provinces of Iran. Therefore, the models were calibrated and preciseness of estimation was increased. However, the estimation was improved only in 14 provinces. The new temperature-based models estimated the evapotranspiration in the eastern (RK, NK, SB, and KE) provinces of Iran (with a various temperature range 14–20 °C) better than other provinces. The best precise methods were the Modified Hargreaves-Samani 1 method for AL (before calibration) and the Modified Hargreaves-Samani 3 method for KE (after calibration). Finally, a list of the best performance of each model has been presented to use other regions and next researches according to values of mean, maximum, and minimum temperature, elevation, minimum and mean relative humidity, sunshine, precipitation, and wind speed. The results are also useful for selecting the best model when we must apply temperature-based models because of type of available data.