• Assessment of soil erosion Indices using Landsat series of data. • Derivation of conservation practice factor and slope erodibility factor. • Assessment of soil yields scenario for soil erosion modelling. • Determining the soil loss using RUSSLE and USLE models. Soil erosion poses a substantial threat to environmental and human sustainability, intensified by anthropogenic interference, climate fluctuations, and socio-economic modifications. This study presents a meticulous and systematic analysis of soil erosion within the Basantar and Devak watersheds of the north-western Himalaya, employing geospatial technologies integrated with the USLE (Universal Soil Loss Equation) and RUSLE (Revised Universal Soil Loss Equation) modeling techniques. To derive the USLE and RUSLE based soil loss, various equation-based parameters such as rainfall (R), length slope factor (LS), cover management (C), conservation practice factor (P), and slope erodibility factor (K) were derived to assess the spatial soil loss in the study area. Based on both model outputs spatial maps have been derived in the Geographic Information System (GIS) platform to determine the soil loss in the study area. The results have been classified into five categories: very high, high, medium, low, and very low areas of soil erosion. Further, the analytical approach also involved the derivation of various satellite data-based soil indices to juxtapose remotely sensed soil loss results, enabling a more detailed understanding of soil loss dynamics in the watersheds. The comprehensive analysis demonstrated the practicality of the employed models in formulating geospatial soil erosion databases, aiding future research, planning, conservation strategies, and climate impact assessment, therefore, laying a foundation for informed environmental decision-making and sustainable land-use practices. The multifaceted exploration of soil erosion in the Basantar and Devak watersheds through intricate modeling and geospatial technologies accentuates the study's significance in advancing soil conservation research, and the potential applications of these models in varied environmental contexts.
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Taloor et al. (2025) studied this question.