Spatial Patterns of Water-Induced Soil Erosion and Their Associations with Vegetation Condition, Drought and Topography in East Kazakhstan: Implications for Sustainable Land Management Using RUSLE and Geographically Weighted Regression

Soil erosion in semi-arid mountain–steppe regions is closely associated with climatic variability, vegetation condition and terrain, but their joint spatial patterns remain insufficiently quantified in Kazakhstan. We assessed RUSLE-estimated water-driven soil loss and meteorological drought and vegetation condition in East Kazakhstan during 2001–2024 by integrating RUSLE modelling with SPI-12, VCI and geographically weighted regression (GWR). FAO-classified RUSLE estimates showed that very low erosion (<5 t ha−1 yr−1) generally increases over time, whereas high (20–50 t ha−1 yr−1) and very high (50–100 t ha−1 yr−1) classes remain almost constant at about one third of the area and severe-to-extreme erosion occasionally reaches double-digit shares, indicating modest improvement in regional averages but persistent hotspots on foothills and mountain slopes. SPI-12 and VCI revealed alternating multi-year periods of dry and wet conditions and corresponding changes in vegetation condition. GWR results indicate that slope is the most stable and coherent predictor of soil loss, while local VCI coefficients, although weaker and more variable, tend to be negatively associated with erosion where vegetation cover deteriorates. The integrated RUSLE–SPI–VCI–GWR framework provides a reproducible basis for identifying areas where high modelled erosion susceptibility coincides with topographic vulnerability and adverse hydroclimatic or vegetation conditions, supporting targeted soil-conservation planning, climate-resilient land management, and the long-term protection of soil and water resources in semi-arid mountain–steppe landscapes.