Flash floods, typically triggered by natural events such as heavy rainfall, snowmelt, and dam failures, are characterized by abrupt onset, destructive power, unpredictability, and challenges in mitigation. This study investigates the spatial distribution patterns and driving mechanisms of rainstorm-induced flash flood disasters in the Yarlung Tsangpo River Basin (YTRB) by integrating topography, hydrometeorology, human activity data, and historical disaster records. Through a multi-method spatial analysis framework—including kernel density estimation, standard deviation ellipse, spatial autocorrelation (Moran’s I and Getis–Ord Gi*), and the optimal parameter geographic detector (OPGD) model (integrating univariate analysis and interaction detection)—we reveal multiscale disaster dynamics across county, township, and small catchment levels. Key findings indicate that finer spatial resolution (e.g., small catchment scale) enhances precision when identifying high-risk zones. Temporally, the number of rainstorm-induced flash floods increased significantly and disaster-affected areas expanded significantly from the 1980s to the 2010s, with a peak spatial dispersion observed during 2010–2019, reflecting a westward shift in disaster distribution. Spatial aggregation of flash floods persisted throughout the study period, concentrated in the central basin. Village density (TD) was identified as the predominant human activity factor, exhibiting nonlinear amplification through interactions with short-duration heavy rainfall (particularly 3 h [P3] and 6 h [P6] maximum precipitations) and GDP. These precipitation durations demonstrated compounding risk effects, where sustained rainfall intensity progressively heightened disaster potential. Topographic and ecological interactions, particularly between elevation (DEM) and vegetation type (VT), further modulate disaster intensity. These findings provide critical insights for risk zonation and targeted prevention strategies in high-altitude river basins.

The implementation of vegetation restoration projects in the Three-North Sandstorm Region has provided a critical opportunity for ecological rehabilitation. A thorough exploration of the mutual feedback mechanisms between land use and vegetation dynamics holds significant guiding value for ecological restoration practices. This study innovatively integrates the Hurst index, trend analysis, and significance testing to systematically analyze the characteristics of vegetation dynamics and their responses to land-use changes from 1990 to 2020. By constructing a multidimensional evaluation system, including the comprehensive land-use index (L) and land-use change rate (R), this research is the first to quantitatively reveal the relationship between land-use characteristics and the Normalized Difference Vegetation Index (NDVI) across different desertification regions. Key findings include: (1) Vegetation in the study area exhibited a significant improvement trend, with 92.12% of regions showing a Hurst index > 0.5, indicating strong persistence in vegetation recovery. (2) Land-use transitions revealed a consistent increase in construction land across all sandy regions, accompanied by the conversion of unused land to grassland. (3) The fluctuation of R gradually narrowed from 1990 to 2020, while the L demonstrated a significant upward trend. (4) The R generally exerted a negative influence on NDVI, whereas the L exhibited a threshold effect. Specifically, NDVI increased with rising L when L < 215 (e.g., MWSD, KBQD regions), but declined when L exceeded 215 (e.g., SNS region). This suggests that frequent land-use changes hinder vegetation growth, while moderate increases in land-use intensity initially promote biomass accumulation—until a critical threshold is surpassed, beyond which further intensification exerts adverse effects. One-way ANOVA and significance testing further demonstrated that climate predominantly drove NDVI increases in cropland, forest, shrubland, and grassland, whereas human activities played a decisive role in vegetation growth within unused or sparsely vegetated areas. This study not only quantitatively identifies critical thresholds for land-use impacts on vegetation but also provides a scientific foundation for targeted ecological restoration strategies, offering practical insights for reconciling ecological conservation with land-use demands.