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Evapotranspiration (ET) is a fundamental process linking the energy, water, and carbon cycles in terrestrial ecosystems. In dryland regions like Northwest China, where water availability strongly constrains ecosystem functioning, understanding the spatiotemporal dynamics of actual evapotranspiration ( ET a ) and its controlling mechanisms is critical for ecohydrological assessments under climate change. However, these regions face persistent challenges due to sparse vegetation, heterogeneous soils, and limited observations, which impede accurate regional-scale ET a quantification and attribution analysis. This study investigates the spatiotemporal patterns and controlling factors of ET a in Northwest China from 2001 to 2024 using the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model optimized with remote sensing and flux observations. The model was optimized using 16 flux towers, achieving an R 2 of 0.74 and enabling reliable regional ET a estimation under data-scarce conditions. The optimized model produced multi-year average ET a of 292.2 mm and an increasing trend of 0.43 mm yr −1 . ET a exhibited a clear spatial gradient, higher in the east, lower in the west, corresponding to vegetation and water availability. Importantly, standardized ridge regression revealed that environmental factors explained 83.4 % of ET a variability, with relative humidity alone contributing the largest share (33.6 %). Vegetation dynamics accounted for 16.6 %, primarily associated with farmland expansion and afforestation. This findings offer a robust framework for disentangling ET a drivers in data-scarce drylands and underscore the dominant role of both atmospheric humidity and land cover change in shaping regional evapotranspiration patterns. This study delivers valuable insights for sustainable water and land resource management under climate change. • The PT-JPL model accurately simulated actual evapotranspiration after calibration. • Climatic factors dominated actual evapotranspiration variations in Northwest China. • Evapotranspiration dynamics is mainly influenced by moisture rather than temperature. • Vegetation and humidity explained 16.6 % and 33.6 % of evapotranspiration variability.
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Liu et al. (2025) studied this question.
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