Spatiotemporal variations and driver-specific response characteristics of evapotranspiration across different vegetation types in the Qilian Mountains

Study region The Qilian Mountains, northwestern China Study focus Using the PML-V2.8 evapotranspiration (ET) dataset together with hydroclimatic, vegetation, and topographic variables, this study examined the spatiotemporal variations of ET across forests, shrublands, and grasslands in the Qilian Mountains during 2000–2022. Ensemble machine-learning models combined with SHapley Additive exPlanations (SHAP) were further used to identify dominant controls, monthly shifts in driving factors, and response patterns among different vegetation types. New hydrological insights for the region From 2000–2022, ET increased significantly in the Qilian Mountains, mainly in spring and summer. Forest ET increased fastest, whereas grassland ET showed the strongest interannual variability. The dominant controls differed among vegetation types: forest and shrubland ET were mainly regulated by hydroclimatic factors, particularly solar radiation, whereas grassland ET was jointly constrained by energy conditions and elevation-related topographic gradients represented by DEM. Monthly SHAP analysis revealed clear seasonal shifts in dominant controls, with LAI dominating forest and shrubland ET during June-August and DEM dominating grassland ET in most months. Response curves indicated no strong nonlinear responses or clear threshold effects, highlighting the combined roles of vegetation type, seasonal driver shifts, and topographic constraints in regulating ET across mountainous ecosystems.