Accurate estimation of terrestrial evapotranspiration (E) is critical to understand the world's energy and water cycles. MOD16 is the core algorithm of the widely used global E data set (the Moderate Resolution Imaging Spectroradiometer [MODIS] E product). However, it exhibits considerable uncertainties in some regions. Based on the data from 175 flux towers, we identified the key parameters of the MOD16 algorithm using the Sobol’ sensitivity analysis method across biomes. The output of the MOD16 algorithm was sensitive to eight parameters. Among them, β, which is treated as a constant (0.2 kPa) across biomes in the original MOD16 algorithm, was identified as the parameter to which the algorithm was most sensitive. We used the differential‐evolution Markov chain method to obtain the proper posterior distributions for each key parameter across a range of biomes. The values of the key parameters for the different biomes were accurately estimated by differential‐evolution Markov chain in comparison with data from the flux towers. We then evaluated the performances of the original MOD16 and the optimized MOD16 and compared them at multiple spatial scales (i.e., site, catchment, and global). We obtained relatively consistent and more reliable E simulations using the optimized MOD16 at all three scales. In the future, more attention should be paid to uncertainties in the algorithm's structure and its parameterizations of soil moisture constraint, canopy resistance, and energy partitioning.

Commonly used soil hydraulic models that account for capillary forces often do not perform well when water flow occurs in thin liquid films in unsaturated porous media. A new theoretical soil water retention curve model was formulated based on the film thickness function that accounts for matric potential. Coupling this new model with a modified Tokunaga model that considers hydraulic conductivity yields a theoretical and mathematically simple soil hydraulic model that accounts for film flow in unsaturated porous media. Inverse modeling of an evaporation experiment showed that the new model provides a good description of water flow at low water contents. The combination of van Genuchten model with the modified Tokunaga model performed best in inverse modeling; however, the fitted parameters did not describe water flow under drier conditions because of the higher hydraulic conductivity and sharper water potential gradient when the water content approached the residual water content, which caused severe overestimation of water loss. Simulation of the water dynamic in a 2 m profile using the modified Tokunaga model combined with the new theoretical soil water retention curve model provided reliable results for water changes under field conditions, including very dry conditions.