Soil salinization severely constrains agricultural sustainability and ecological security in arid inland river This study establishes an integrated "inversion-evolution-zoning" framework to elucidate the spatiotemporal dynamics and risk structure of soil salinization in the Weigan River Basin from 2000 to 2024. Using temporal Landsat imagery and field-measured salinity data (275 sites, 0-30 cm depth), three machine learning models-Decision Tree, Gradient Boosting Decision Tree, and Random Forest-were compared. Random Forest achieved the highest accuracy (R2 = 0.81, RMSE = 9.08 g/kg), with NDVI, ENDSI, and the predominant contributors. Results reveal pronounced spatial heterogeneity: low salinity predominates upper alluvial fan, whereas high salinity concentrates in the lower fan and along the Tarim River, corridor-like belts and island-like patches. Although the proportion of non-saline land increased from 30% and saline land decreased from 61% to 47%, the evolutionary process was highly dynamic, characterized bidirectional transitions among moderate, severe and saline classes, particularly during 2010-2020-a driven by irrigation expansion and groundwater dynamics. Geo-informatic Tupu analysis identified 17 evolution trajectories, among which persistently stable (41.6%) and risk-reduction (32.5%) patterns dominate. Unstable areas are predominantly located in low-lying zones and desert-oasis ecotones. Integrating baseline evolutionary pathways, and transition frequency, the basin was delineated into four zones: stable (40.0%), improvement (27.4%), warning (22.6%), and high-risk (10.0%). This framework provides spatially guidance for precision irrigation and groundwater control, and is transferable to other arid and semi-arid river basins.