Assessment of an evapotranspiration algorithm accounting for land cover types and photosynthetic perspectives using remote sensing images

In this study, Eco-hydrometeorological Remote Sensing-based Penman-Monteith algorithm (Eh-RSPM) was developed by implementing the gross primary productivity into the revised Remote Sensing based Penman-Monteith algorithm (RS-PM). Evaluation of Eh-RSPM was conducted through comparison with in-situ measurements as well as model-based products (e.g. MODerate resolution Imaging Spectroradiometer (MODIS) 16 global ET products (MOD16 ET) and Surface Energy Balance System (SEBS)) during two years (2004 and 2012) in Northeast Asia. Comparison of ET from Eh-RSPM algorithm with five flux tower measurement agreed well with the flux tower datasets at the entire validation sites. Especially, Eh-RSPM showed advantages in improving the accuracy of ET at stations with relatively short canopy height (e.g. QHB and KBU site) as well as the forest site (e.g. SMK). Focusing on the forest site, Eh-RSPM exhibited slightly better statistical performance compared to MOD16. Specifically, the temporal mean bias and RMSD showed a slight improvement, decreasing from -15.40 W m-2 to -12.58 W m-2 and from 28.41 W m-2 to 25.26 W m-2, respectively. This is a key finding of this study, demonstrating the applicability of the improved ET algorithm to regions with significant forest cover. Similarly, spatial distribution of Eh-RSPM showed similar patterns with MOD16 and SEBS. Eh-RSPM strongly showed advantages over the land cover types with relatively shorter canopy height (e.g. grassland and alpine meadow) as well as the heterogeneous forest showed significant improvement in Eh-RSPM through considering the actual physiological behavior variation and influence of photosynthesis into ET calculation.