Terrestrial evapotranspiration (ET) is a key hydrological component in the land surface system and its accurate estimation is crucial in understanding the global water and energy budgets. The current large-scale ET estimation models depend on the remotely sensed data products of meteorological variations and vegetation phenology but high uncertainty remains due to the difficulty to well represent ecological factors. In recent years, solar-induced fluorescence (SIF), a proxy for photosynthesis, has been extensively used in different perspectives of ecological research and is conceived to be of great potential for ET estimation when combined with other meteorological variables, in order to constrain the transpiration flux, which is the larger component of ET. So far, most SIF-based ET estimation methods are achieved via empirical methods, which are either computationally expensive or lack a solid physical foundation. In this research, we developed a method to estimate ET by combining Fick’s law, SIF, an optimal stomatal behavior model, and meteorological variables, and validated the model across different eddy-covariance flux stations with large vegetation cover around the globe. The model showed varied performance in different ecosystems but the performance is mostly convincing. The results are also compared with other remote sensing-based ET models like Priestley Taylor-JPL(PT-JPL) model, the Moderate Resolution Imaging Spectroradiometer (MODIS)-ET products, and the simple empirical linear SIF-ET model, the RMSE of estimated ET of the model we proposed in this work demonstrates better performance. The model we proposed here has the potential to be extended for a reliable ET estimation at a global scale.
 

Evapotranspiration,solar-induced fluorescence (SIF),vapor pressure deficit,water-carbon coupling