Determining the potential evaporation and transpiration (ET) in an efficient way which has attracted a lot of attention due to its importance in water balance studies, water supply of plants, management planning in agriculture.Therefore, in this research, it has been tried with spatial coordinates and meteorological data of Ramsar, Kermanshah, Hamedan, Semnan, Mashhad, Shiraz, Ardabil, Urmia, Zanjan, Yazd and Rasht stations, the methods of Hargreaves-Samani, Belani-Cridel, Ivanov and Torrent White are modified on an annual and seasonal scale. The used method as a basis for the correction of equations was considered the FAO-Penman-Monteith method. The basis of the correction methods was based on regression and support vector regression, relative and parallel hybrid framework. The type of spatial and meteorological information played an important role in increasing the accuracy of corrective equations, as an example, the increase in the variance of errors in Ivanov's method from the corrected regression equation with all the data to the equation with the removal of the wind component was 38.18%. The regression correction method had better performance against the ratio method, so that the average increase of the Willmott index for all input states from the ratio method to the regression in the Torrent-White, Blaney-Cridle, Ivanov and Hargreaves-Samani methods is equal to 42.67, 5.45, 25 and 3%, respectively. The structure of parallel hybrid framework in all methods reduced the error in determining potential evaporation and transpiration, and the final approach including the parallel framework of optimal modes of support vector regression and simple regression had significant accuracy. The final approach showed that Torrent White, Blaney-Cridel and Ivanov methods have underestimation and Hargreaves-Samani has overestimation.The structure of the corrective method has the significant importance in increasing the efficiency of potential ET and finally water demand planning based on the available information.