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.
