عنوان مقاله [English]
نویسندگان [English]چکیده [English]
Evaporation is one of the climatic variables that predict significant role in the planning of water. Due to the relatively high rainfall in areas of West Iran, awareness of the evaporation rate of water in these areas is essential for proper management.The factors influencing rate of evaporation, which are climatic signals according to their role in predicting enables evaporation. Evaporation prediction was performed using artificial neural network model based on climatic signals. the data of evaporation at three synoptic stations and the most important climate signals whit at least 20 years of monthly analysis using NeuroSolution software. The results show that the most Important signals affecting the evaporation areas include; Nina3, Nina1, Sw monsoon, Mei and Nina4.Comparison of observed data with a high correlation between the ANN output data shows. So that the correlation of the Kermanshah station is 71%, Hamedan 82% and Sanandaj 80%.The output data of the neural network and climatic signals, can accurately predict the top 97% of the areas evaporation.