The influence of land surface temperature (LST) on estimated actual evapo transpiration

The remote sensing technique is a suitable method for estimating actual evapotranspiration (ETa) at the large-scale due to spatial and temporal resolution. The present study aims to assess the ETa using the SEBAL and different algorithms to survey the effect of the LST and their impact assessment on the ETa fluctuation. Field measurement, including canopy temperature and the volume of inflow and outflow of water consumption was done based on lysimeters during 2018-2019. After the necessary pre-processing on the satellite images, the Land Surface Temperature (LST) was estimated using Planck's and split window algorithms. The result showed that the performance of Split window was better than to the Planck algorithm. Also, ETa was estimated by the SEBAL algorithm based on two temperature scenarios including the Planck and split window. The results showed, the cold pixel of SEBAL algorithm had compliance with the Lysimetric measurement. Moreover, the cold pixel of the split window algorithm with RMSE=0.56, NRMSE=0.084 and NS=0.992 (mm/day) had the highest consistency with the lysimeter data. Also, the rMBE index of the split window algorithm was associated with underestimation in the range of -4.07 to -3.22%, while the Planck function algorithm fluctuated with overestimation in the range of 4.76 to 12.65%. This research has been verified to the cold pixel of satellite for crop with no stress conditions and for better investigation at crop stress condition, precise instruments are needed.