Demonstrates a two-step strategy enhancing evapotranspiration partitioning in water resource management, indicating better accuracy and performance compared to conventional methods.
Accurately partitioning evapotranspiration (ET) into soil evaporation (E) and plant transpiration (T) is fundamental for improving water resource management, yet robust ET partitioning remains challenging. This study proposes a two-step ET partitioning strategy that first extracts pure E and T samples from long-term ET observations and then uses these samples to independently constrain E and T sub-models. The strategy was implemented in three classical two-source ET models: Shuttleworth–Wallace (SW), Priestley–Taylor Jet Propulsion Laboratory (PT-JPL), and FAO-56 dual crop coefficient (FAO56-DK), and was compared against the conventional one-step calibration approach. Results show that the two-step strategy consistently improves the estimation of ET components and the transpiration fraction (T/ET). For the PT-JPL model, RMSEs of E, T, and ET decreased from 0.04, 0.06, and 0.078 to 0.03, 0.03, and 0.04 mm/30 min, respectively. In FAO56-DK, R2 values increased from 0.08, 0.55, and 0.65 to 0.10, 0.65, and 0.75. The RMSE of T/ET declined from 0.21 to 0.18 in SW and from 0.47 to 0.34 in FAO56-DK. The effectiveness of pure samples depends on model structure, with E samples most beneficial for SW, T samples for FAO56-DK, and both for PT-JPL. Overall, these results demonstrate that pure-sample constraints substantially enhance ET partitioning accuracy.
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Hu et al. (2026) studied this question.
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