عنوان مقاله [English]
Evaporation process is considered to be one of the main components in hydrological cycle. Therefore, its accurate estimation plays a vital role in studies of irrigation management and river flow forecasting. In order to estimate evaporation from pan, ? metrological parameters such as temperature, relative humidity, wind speed, vapor pressure deficit, and extraterrestrial radiation were daily collected during ????-???? at Shiraz Synoptic Station. In the first step, from ?? different combinations of input parameters, the best subset including relative humidity, vapor pressure deficit, and extraterrestrial radiation were detected by using the Gamma test (GT). Then, by applying M test, ???? patterns were selected for an established training model and the rest of ???? patterns were used for verification of the model. Afterward, based on the GT results, the evaporation model was established by applying adaptive neuro-fuzzy inference system (ANFIS). In addition, the results of this method compared with Marciano empirical equation, and calibrated Stephens–Stewart (S-S) equation. The results come from the evaluation of these models in the test period showed that the ANFIS model and S–S equation with determination coefficients of ?.???? and ?.???? on the line of (?:?) and RMSE with ?.??? and ?.??? mm day-?, respectively are more accuracy than other models.