Knowledge of evapotranspiration (ET) is essential for enhancing our understanding of
the hydrological cycle, as well as for managing water resources, particularly in semi-arid regions.
Remote sensing offers a comprehensive means of monitoring this phenomenon at different spatial
and temporal intervals. Currently, several satellite methods exist and are used to assess ET at various
spatial and temporal resolutions with various degrees of accuracy and precision. This research
investigated the performance of three satellite-based ET algorithms and two global products, namely
land surface temperature/vegetation index (TsVI), Penman–Monteith (PM), and the Meteosat Second
Generation ET (MET) and the Global Land-surface Evaporation: the Amsterdam Methodology
(GLEAM) global products, in two eco-regions of South Africa. Daily ET derived from the eddy
covariance system from Skukuza, a sub-tropical, savanna biome, and large aperture boundary layer
scintillometer system in Elandsberg, a Mediterranean, fynbos biome, during the dry and wet seasons,
were used to evaluate the models. Low coefficients of determination (R2) of between 0 and 0.45 were
recorded on both sites, during both seasons. Although PM performed best during periods of high ET
at both sites, results show it was outperformed by other models during low ET times. TsVI and MET
were similarly accurate in the dry season in Skukuza, as GLEAM was the most accurate in Elandsberg
during the wet season. The conclusion is that none of the models performed well, as shown by low
R2 and high errors in all the models. In essence, our results conclude that further investigation of the
PM model is possible to improve its estimation of low ET measurements.
This manuscript is part of the PhD research work done under the Council for Scientific
and Industrial Research in collaboration with the University of Twente.