| Summary: | Although soil moisture (<i>SM</i>) is an important constraint factor of evapotranspiration (<i>ET</i>), the majority of the satellite-driven <i>ET</i> models do not include <i>SM</i> observations, especially the <i>SM</i> at different depths, since its spatial and temporal distribution is difficult to obtain. Based on monthly three-layer <i>SM</i> data at a 0.25° spatial resolution determined from multi-sources, we updated the original Priestley Taylor–Jet Propulsion Laboratory (PT-JPL) algorithm to the Priestley Taylor–Soil Moisture Evapotranspiration (PT-SM <i>ET</i>) algorithm by incorporating <i>SM</i> control into soil evaporation (<i>E</i><sub>s</sub>) and canopy transpiration (<i>T</i>). Both algorithms were evaluated using 17 eddy covariance towers across different biomes of China. The PT-SM <i>ET</i> model shows increased <i>R</i><sup>2</sup>, <i>NSE</i> and reduced <i>RMSE</i>, Bias, with more improvements occurring in water-limited regions. <i>SM</i> incorporation into <i>T</i> enhanced <i>ET</i> estimates by increasing <i>R</i><sup>2</sup> and <i>NSE</i> by 4% and 18%, respectively, and <i>RMSE</i> and Bias were respectively reduced by 34% and 7 mm. Moreover, we applied the two <i>ET</i> algorithms to the whole of China and found larger increases in <i>T</i> and <i>E</i><sub>s</sub> in the central, northeastern, and southern regions of China when using the PT-SM algorithm compared with the original algorithm. Additionally, the estimated mean annual <i>ET</i> increased from the northwest to the southeast. The <i>SM</i> constraint resulted in higher transpiration estimate and lower evaporation estimate. <i>E</i><sub>s</sub> was greatest in the northwest arid region, interception was a large fraction in some rainforests, and <i>T</i> was dominant in most other regions. Further improvements in the estimation of <i>ET</i> components at high spatial and temporal resolution are likely to lead to a better understanding of the water movement through the soil–plant–atmosphere continuum.
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