Evapotranspiration estimation using a satellite-based surface energy balance: a case study of Upper Bari Doab, Pakistan.

Surface Energy Balance Algorithm for Land (SEBAL) is a remote sensing-based spatial evapotranspiration (ET) model known for its minimum reliance on ground-based weather data. The SEBAL model has been validated in many countries using information from different satellite sensors and validation techniques. In this study, the Visible, Near Infrared (NIR), Shortwave Infrared (SWIR), and Thermal Infrared (TIR) bands from Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) have been used to validate SEBAL model using ET from non-weighing (drainage) lysimeter. The study was carried out on semiarid Upper Bari Doab region located in central Punjab, Pakistan. The SEBAL model is sensitive to the presence of cloud cover which necessitates the use of cloud free satellite images. Hence, eight Landsat 8 OLI/TIRS images from July 2019 to April 2021 were processed and the results for daily actual ET (ETa) were compared with the observed ET from Lysimeter. The comparison of the daily estimated SEBAL ET and lysimeter ET showed a Root Mean Square Error (RMSE = 1.26 mmd⁻¹), Coefficient of Determination (R² = 0.9), Mean Absolute Error (MAE = 0.52 mmd⁻¹), and Nash–Sutcliffe Efficiency (NSE = 0.92). The findings of this study suggest that the SEBAL model can be reliably used to determine consumptive water use, schedule irrigation in canal command areas, and ensure equitable water distribution in arid/semiarid regions of Pakistan where agricultural productivity heavily relies on irrigation water supply. [ABSTRACT FROM AUTHOR]