Land evaporation (E), which has the same meaning as land evapotranspiration in this study as advocated by Miralles et al. (2020), is the water transferred from the land surface into the unsaturated atmosphere (Han & Tian, 2018a;Wang & Dickinson, 2012). E is the most important water consumption in the water budget and a keystone climate variable that connects the energy, water, and carbon cycles of terrestrial ecosystems (Fisher et al., 2017;Jung et al., 2010). More than 60% of the global land precipitation is returned to the atmosphere by land E (Oki & Kanae, 2006), even exceeding 90% in arid areas. In the form of latent heat flux, E consumes about 50% of the solar radiation absorbed by the Earth's surface (Trenberth et al., 2009). Moreover, characterized by complex processes and strong spatial and temporal heterogeneity, E plays a key role in soil-vegetation-atmospheric system interactions and is found to be critical in driving weather patterns, affecting convection, cloud formation, and turbulence (Fisher et al., 2017;Vergopolan & Fisher, 2016). Thus, improving understanding and quantification of E is essential for hydroclimatic processes, water balance computations, optimal allocation of regional water resources, and agricultural management (Jung et al., 2010;Xu & Singh, 2005).Although eddy covariance, weighing lysimeters, energy balance, Bowen ratio, and scintillometer methods can be used to measure or estimate E, large-scale long-term E estimates remain difficult due to the lack of in situ observations and their limitations . Therefore, remote sensing, hydrological modeling, land surface modeling, and machine-learning algorithms have been used to directly or indirectly estimate E