Estimation of actual evapotranspiration using SEBAL Surface Energy Balance Algorithm and Fusion of Landsat8 and Sentinel2 satellite images (Case Study: Mirza Kouchak khan Agroindustrial Company)

Evapotranspiration is one of the most important factors in the hydrology cycle and is one of the determinants of energy equations at ground level and water balance. Most of the ground-based methods use point measurements to estimate evapotranspiration. Remote sensing has the ability to estimate the amount of evapotranspiration and examine its spatial distribution. In this study, Landsat8 and Sentinel2 satellite images combined to estimate the actual daily evapotranspiration of sugarcane in the Mirza Kouchak khan Agro industrial Company, Khuzestan province, using the SEBAL model at six dates.Validation of SEBAL model performance was performed in two modes: using integrated images and using Landsat 8 images with lysimeter data. The results indicated that the SEBAL model with Landsat 8 satellite images with (R2=0.88), and the SEBAL model with Landsat 8 and Sentinel2 satellite images with (R2=0.90), Overall, it was well correlated with the lysimeter method and estimated similar and appropriate results.