Comparison of the efficiency of intelligent and statistical methods in the reconstruction of sunshine hours data (Case study: East of Urmia Lake basin)

One of the climate variables with relatively large gaps in observation and significant importance in estimation of evapotranspiration is sunshine hours. In the present study, in order to reconstruction the sunshine hour data of several selected stations in Tabriz province, Iran namely,Tabriz, Sarab, Sahand and Maragheh during the period of 1990 to 2019, skill of intelligent approaches of SVR, ANN and RF was compared with statistical methods of normal ratio, geographical coordinates and weight correlation coefficient. Statistical indices of R, RMSE, MAD and Taylor diagrams were used for evaluation of comparisons. The obtained results showed that ANN and geographical coordinate methods have the highest accuracy in reconstruction sunshine hours among the selected intelligent and statistical methods, respectively. In Tabriz and Sahand stations, the geographical coordinate method with RMSE of 1.04 and 1.13 hours, respectively, in the Sarab station SVR with RMSE of 1.58 hours and in Maragheh station the normal ratio method with RMSE of 1.45 hours showed the highest accuracy in generating sunshine hours. Besides, RF method had the lowest accuracy in reconstruction of sunshine hours data. It can be concluded that in Tabriz, Sarab and Sahand stations, both types of intelligent and statistical methods have almost same accuracy, but in Maragheh station, statistical methods provided slightly better estimations.