U.S. Validation Tests on the SEBAL Model for Evapotranspiration via Satellite

SEBAL (Surface Energy Balance Algorithm for Land) is a widely applied remote-sensing evapotranspiration (ET) estimation model. This paper presents the results of two validation studies of SEBAL applications in the western United States, with some results of sensitivity and repeatability analyses. The validation studies show that the ET estimated by SEBAL corresponded well with lysimeter measured ET for agricultural crops in the semi-arid climate. Sensitivity analyses on impacts of atmospheric correction for surface temperature and albedo showed that the internal calibration procedures of SEBAL compensated well for errors in temperature and albedo when atmospheric correction was not made. Therefore, users can avoid applying complex and time-consuming atmospheric correction procedures with SEBAL. A repeatability test by two totally independent applications using different images, operators and weather datasets, shows that seasonal estimation by SEBAL has a high repeatability (i.e. stable for the differences of satellite image timings, operators preferences and input weather datasets). We also demonstrate that SEBAL results can be used as a means to confirm traditionally applied crop coefficient curves.

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