Climate and land use exert profound influences on runoff-sediment dynamics, but the interaction influence of factors such as rainfall and vegetation restoration on the multi-scale spatiotemporal distribution of connectivity levels has not been yet fully understood, especially in arid and semi-arid regions. In this study, the connectivity index, Pearson's correlation analysis and Geographical Detector Model (GDM) are combined to assess the connectivity level at different spatial and temporal scales, and to elucidate the explanation level of connectivity by each factor and its interaction. The results reveal a consistent decline in multi-year average connectivity, with high connectivity values predominantly concentrated near riverbanks and lower values typically found in the forested regions to the east and west of the basin. Moreover, the GDM reveals that in 2035, the interactive explanatory power of rainfall erosivity (R) and the aggregated weighting factor (AWC) is superior (0.343) than the interaction between rainfall erosivity (R) and AWC in 2020 (0.339). The spatial distribution pattern of the connectivity is significantly correlated with static topographic elements (especially slope factors) and is co-regulated by climate change and dynamic succession of vegetation cover. Monthly scale analysis further validates this finding: when the normalised R-value (R-n) > 0.18, high rainfall erosivity factor in July and August significantly increase the connectivity of the basin by breaking through the vegetation constraints. Spatial and temporal integration of climate, land use, and connectivity can contribute valuable insights into the dynamic interplay between surface processes and soil-water resource management.