Modifying SEBAL Model Based on the Trapezoidal Relationship between Land Surface Temperature and Vegetation Index for Actual Evapotranspiration Estimation

Abstract

The Surface Energy Balance Algorithm for Land (SEBAL) is widely used to estimate actual evapotranspiration (ETa). One major limitation of the SEBAL model is the subjectiveness in selecting extreme cold/hot pixels. In the present study, the SEBAL model is modified by determining the extreme cold/hot status, based on the theoretical trapezoidal relationship between land surface temperature (Ts) and Enhanced Vegetation Index (EVI), which is established for each pixel. In this way, the dependence of SEBAL model on the existence of extreme cold/hot status and the subjectiveness in selecting cold/hot pixels with SEBAL model are eliminated. The performance of the classical SEBAL model and the modified version, T-SEBAL, are compared for estimating ETa for a semi-arid catchment, and the result showed that the accuracy of ETa estimation is improved by the T-SEBAL model compared with the classical SEBAL model.