Evapotranspiration Estimation Using a Satellite-Based Surface Energy Balance – A Case Study of Upper Bari Doab, Pakistan

Abstract

Satellite Surface Energy Balance Algorithm for Land (SEBAL) is a remotely sensed spatial evapotranspiration (ET) model known for its minimum reliance on ground- based weather data. This quality makes it efficient over other spatial evapotranspiration models. The SEBAL model has been validated in many countries using different satellite sensors and validation techniques. In this study, the Landsat 8 OLI/TIRS satellite sensor has been used to validate SEBAL model using observed ET from drainage lysimeter. The research was carried out on Upper Bari Doab (a semi- arid region of central Punjab, Pakistan) for two hydrological years (2019-21). The sensitivity of SEBAL model requires cloud free satellite images, therefore, only eight such images could be acquired. Daily actual evapotranspiration (ETa) was estimated for each satellite image using routine meteorological data. The comparison of estimated ET with lysimeter ET showed RMSE of 1.26 mmd-1 and coefficient of correlation (R2=0.89). The model both under estimated and over estimated ET. Advection in arid/semi-arid regions is significant, however, the SEBAL model assumes a constant EF throughout a day. Therefore, the errors due to advection are unavoidable. Other spatial ET models such as METRIC incorporate effects due to advection, however, such models are more dependent on ground-based weather data such as hourly reference ET. In areas where ground-based data is minimal, SEBAL is the preferred choice of water managers.