Estimation of Real Evapotranspiration of Wheat and Rapeseed Using SEBAL Algorithm (Case Study: Esmaeil Abad Agricultural Research Station in Qazvin Province)

Evapotranspiration is a complex phenomenon that depends on many factors and data, so determining it is very difficult and costly. In most methods mainly aimed at estimating evapotranspiration, point measurements have been used to estimate this variable. Therefore, it is only suitable on a local scale and cannot be extended to large basins due to the dynamics and regional changes of evapotranspiration (ET). One of the remote sensing algorithms for estimating real evapotranspiration is the Surface Energy Balance Algorithms for Land (SEBAL). In this algorithm, by estimating all energy components on the land surface such as pure radiation flux, soil heat flux, and tangible heat flux, using the energy balance equation, evapotranspiration is used. The aim of this study is to compare the estimation of real evapotranspiration using SEBAL algorithm in wheat and rapeseed crops with the results of estimating evapotranspiration by Penman-Monteith-FAO method in the field of Esmaeil Abad Agricultural Research Station in 2019-2020. Single-sample T-test of ground surface temperature reflection index showed that the spectral reflection of wheat and rapeseed crops during phenological growth period had a significant difference. The results showed that the computational values of the two models are relatively good and the mean value of square root of error (RMSE) in estimating real evapotranspiration for wheat and rapeseed plants was 3.04 and 2.09 mm/day, respectively, and the coefficient of explanation (R2) was 0.78 and 0.81, respectively. The results showed that SEBAL algorithm model in comparison with Penman-Monteith-FAO model (based on up-to-date meteorological data) The amount of evapotranspiration for wheat and rapeseed plants is lower.