Improving the evapotranspiration estimation by coupling soil moisture and atmospheric variables in the relative evapotranspiration parameterization

Abstract

Accurate monthly evapotranspiration (ET) estimation is essential for many forest, climate, and hydrological applications, as well as for some agricultural uses. In this study, the relationship between ET and relative evapotranspiration (F) using land surface, and atmospheric variables was assessed with 17 FLUXNET sites data in savanna, cropland, and forest land covers, distributed all over the world. A sigmoid (Fs) and a logarithmic (Fl) F expression were included in Walker et al.’s (2019a,b) equations to evaluate their impact on the accuracy of ET estimations. The new parameterizations of ET outperformed the original expression, showing root mean square errors lower than 24% of the mean observed ET. The results presented here suggest that atmospheric parameters, coupled with land explanatory variables included in F estimates, produce more precise ET estimations. In addition, Soil Moisture Active Passive (SMAP) products were used to obtain global maps of ET and compared with Global Landsurface Evaporation Amsterdam Methodology (GLEAM) and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) MOD16 products, displaying the flexibility of these new parametrizations with different sources of data.