Evaluation of time series models in forecasting pan evaporation in different climates of Hormozgan province

Evaporation is one of the most important and effective factors in water resources planning and management in arid and semi-arid areas and examining it's changes in time scales and different years as one of the most important climatic parameters, has an important role in planning and water resource management in agriculture section and determining cultivation pattern and proper water resource management. One of the methods to assess and forecast changes in evaporation is time series models by the generic name of ARIMA models. Therefore, in order to determine the best model to predict pan evaporation, after considering the climate using improved Domarton climatic classification method, in each climatic sample, one evaporation station was selected and standardized ​​pan evaporation index (SPEI) was calculated for each of the stochastic model for estimation the amount of future monthly time series SPEI in the period of 1954-1955 to 2009-2010 over the next 12 months. Results showed that the Auto Regressive Moving Average model (ARMA) and Auto Regressive (AR) had the best performance, in Hormozgan province, so that, in the hot and dry, hyper hot arid and hyper hot hyper arid climates, in the next month, had the highest standard coefficient of determination (R) of 0.83, 0.71, 0.7 and the lowest value RMSE of 0.59, 0.8, 0.88, respectively and the AR model was able to predict the next 11 months, well. The results showed that AR model has better performance compared to ARMA model in estimating monthly pan evaporation in hot and dry climates in coastal wilderness areas.