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.
