Forecasting Of Monthly Precipitation Using M5 Model Tree And Classic Statistical Methods (Case Study: Synoptic Oroumieh Station)

This study carried out to estimate monthly rainfall data of Oroumieh that are assumed to be lost from 2006 to 2007 , by classic statistical methods and M5 model tree using the software Weka using Mahabad, Khoy, Salmas, Makoo and Tekab stations . Among the studied stations, Mahabad station (R = 0.90) had the highest correlation with Oroumieh station. 26 scenarios of nearby stations have been introduced to Weka software in estimating monthly precipitation of Oroumieh station that among scenarios, the scenario which was defined as the simplest and most accurate scenario, included three Mahabad, Makoo and Tekab stations with values of (MAE = 7.19, R = 0.90, RMSE = 9.64) because of the lower input parameters to the model. Among the classical methods, the single best estimator (SIB) method has been selected as the best method with the highest correlation coefficient and the lowest error (R = 0.90 , RMSE = 10.51 ,MAE = 7.07). M5 model tree had the best performance in estimating quantities of data (R = 0.91 ,RMSE = 9.94 , MAE = 7.29) and is considered as an alternative and applied method in the calculation of monthly precipitation data due to simple linear and understandable relationships .