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Soil erosion poses a major threat to forest ecosystems in the fragile north-western Himalayas, where steep terrain, variable rainfall, and sensitive soils accelerate erosion, resulting in topsoil loss and decreased forest productivity. This study evaluated soil loss across various forest types within a 2,800-hectare watershed in the north-western Himalaya (elevation 1,100–2,400 m). The Universal Soil Loss Equation (USLE), combined with GIS and remote sensing, was used to estimate the spatial pattern of soil erosion. Key parameters, including rainfall erosivity (R), soil erodibility (K), topographic factor (LS), cover management factor (C), and support practice factor (P), were obtained from rainfall data, field observations, satellite images, digital elevation models (DEMs), and relevant literature to estimate annual soil loss. The soil loss in the study area was categorized into six classes: slight (< 5 t ha⁻¹ yr⁻¹), moderate (5–10 t ha⁻¹ yr⁻¹), high (10–20 t ha⁻¹ yr⁻¹), very high (20–40 t ha⁻¹ yr⁻¹), severe (40–80 t ha⁻¹ yr⁻¹), and very severe (> 80 t ha⁻¹ yr⁻¹). The average soil loss during the three-year study was 12.36, 12.88, and 13.65 t ha⁻¹ yr⁻¹ in 2021, 2022, and 2023, respectively. Among forest types, the moist deodar forest showed the highest soil loss, followed by the ban oak forest and the Himalayan chirpine forest consistently over all three years. The results emphasise the importance of implementing targeted soil conservation strategies in the Shamli watershed. The combined USLE–GIS approach highlights the critical influence of vegetation cover and topography in controlling soil erosion and offers a valuable framework for identifying priority areas for restoration and sustainable watershed management. Assessed soil loss using USLE integrated with GIS and remote sensing in a Himalayan watershed. Quantified spatial variation in erosion across chir pine, oak, and moist deodar forest types. Identified degraded forest patches as erosion hotspots with the highest soil loss rates. Demonstrated the significance of geospatial analysis for erosion risk mapping and conservation planning. Provides baseline data for future research on forest soil erosion in Himalayan watersheds.