Lysimetric evaluation of SEBAL using high resolution airborne imagery from BEAREX08

• SEBAL evaluated against large precision weighing lysimeter.
• SEBAL-instantaneous ET estimated with overall root mean square error 0.16 mm h−1 (29.6%).
• Uncertainty in hot and wet pixel selection could lead to 20% variability in ET estimates.
• Adoption of excess resistance to heat transfer (kB−1) model into SEBAL.
• SEBAL performance improved with the introduction of kB−1 parameterization.

In this study, Surface Energy Balance Algorithm for Land (SEBAL) was evaluated for its ability to derive aerodynamic components and surface energy fluxes from very high resolution airborne remote sensing data acquired during the Bushland Evapotranspiration and Agricultural Remote Sensing Experiment 2008 (BEAREX08) in Texas, USA. Issues related to hot and cold pixel selection and the underlying assumptions of difference between air and surface temperature (dT) being linearly related to the surface temperature were also addressed. Estimated instantaneous evapotranspiration (ET) and other components of the surface energy balance were compared with measured data from four large precision weighing lysimeter fields, two each managed under irrigation and dryland conditions. Instantaneous ET was estimated with overall mean bias error and root mean square error (RMSE) of 0.13 and 0.15 mm h−1 (23.8 and 28.2%) respectively, where relatively large RMSE was contributed by dryland field. Sensitivity analysis of the hot and cold pixel selection indicated that up to 20% of the variability in ET estimates could be attributed to differences in the surface energy balance and roughness properties of the anchor pixels. Adoption of an excess resistance to heat transfer parameter model into SEBAL significantly improved the instantaneous ET estimates.