Abstract
Accurate high-resolution evapotranspiration (ET) estimates are essential for effective local-scale water resource management. This task is often challenging due to the complexities involved in parameterizing surface conditions, which is crucial for driving various ET models. To address this challenge, we presented a novel approach to acquire long-term surface parameters by synthesizing observations from multiple Landsat satellites, and furthermore integrate the Penman-Monteith-Leuning model, leading to the PML_30 model designed for ET estimations at an impressive 30 m resolution. At the site scale, comparison with observations from 42 FLUXNet sites across diverse arid and semi-arid regions globally showed the reliable performance of the PML_30 model, boasting average coefficient of determination (R2) of 0.79, root mean square error (RMSE) of 0.52 mm/day, and bias of 0.39 mm/day. At the regional scale, the PML_30 model was applied to estimate monthly ET from 2000 to 2020 over a typical arid region in Northwest China. The mean annual ET estimated by the PML_30 model closely aligned with the reference based on regional water balance. Additionally, the model accurately described the spatial distribution of ET, which showed a notable improvement over existing products. In summary, our proposed PML_30 model emerges as a reliable tool for ET estimations at a specific high spatial resolution, particularly beneficial for arid and semi-arid regions.
Published Version
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