Estimation of Evapotranspiration Using Surface Energy Balance Algorithm for Land and Satellite Data: A Case Study of Lower Bari Doab Punjab, Pakistan

Abstract

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. 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 generate ET maps for Lower Bari Doab Canal Command Area (LBDC) and compare the estimated ET with reference ET generated from CROPWAT model. The SEBAL model was applied on nine cloud-free satellite images acquired in the year 2020. Daily actual evapotranspiration (ETa) was estimated for each satellite image using routine meteorological data. The spatio-temporal distribution of ET across LBDC was analyzed and the efficiency of the SEBAL model was studied with regards to its validation. The study area is ideal for the application of SEBAL because it is semi-arid and effects of advection on surface energy balance terms are significant. The efficiency of SEBAL model has thus been studied in this regard. Furthermore, spatio-temporal distribution of various model parameters including daily actual ET have been discussed vis-à-vis different land classes.