Quantifying the Influence of Soil Condition, Topography and Land Use on Soil Loss in a Watershed in Phuleng-e-Nyane, Lesotho

Soil erosion significantly threatens agricultural sustainability in Lesotho, driven by its mountainous topography, erosive rainfall, and traditional farming practices. This study therefore quantified annual soil loss and evaluated the influence of soil condition (K), topography (LS), and land use (C) on erosion risk within the Phuleng-e-Nyane watershed at Ha ‘Mantšebo Local Community Council area of the Maseru District, Lesotho during the 2024/2025 growing season. Both field and climatic data were collected to quantified soil erosion indices. The various land use and topo-sequence positions were delineated using Geographic Information Systems (GIS) while soil loss was quantified using the Universal Soil Loss Equation (USLE). The soil loss was modeled using the erosion indices and soil properties while the effect of land use and topo-sequence position on the measured variables was evaluated using 2-way analysis of variance. The 40-year average rainfall erosivity (R) was 1256.89 MJ mm ha−1 h−1 yr−1. Soil erodibility (K) ranged from 0.027 to 0.038 Mg h MJ−1 mm−1, peaking at the toe-slope due to low saturated hydraulic conductivity. The topographic factor (LS) varied from 0.09 to 0.31, with the highest values on the steep back-slope. Overall, long-term fallow land showed significantly (p < 0.05) lower mean soil loss (0.08 Mg ha−1 yr−1) compared to active cropland (1.49 Mg ha−1 yr−1). The highest erosion rate (1.98 Mg ha−1 yr−1) was recorded on the cropland back-slope. The results highlight land use (C-factor) as the dominant determinant, accounting for over 90% of the difference in soil loss between land-use types. However, topo-sequence (LS-factor) dictates localized severity, with the back-slope being the highest risk. Prioritizing vegetation cover management and targeted interventions on steep back-slopes to ensure agricultural sustainability are strongly recommended as effective conservation strategies. Future studies should incorporate inter-seasonal field and weather data collection and quantification of vegetation indices to improve the calculation of the land use factor.