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@article{200231,
        author = {G. Vijayakumar and P. P. V. Neelendra and M. Srujana Grace and V.Glory and L. Chandra Kiran},
        title = {Geospatial assessment of soil erosion risk using the RUSLE model in lower Krishna Lanka areas of Andhrapradesh, India},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {721-727},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=200231},
        abstract = {Soil erosion is a major environmental challenge that threatens land productivity and long-term sustainability, particularly in dynamic floodplain environments. The Lower Krishna Lanka region, situated downstream of the Krishna River in Andhra Pradesh, India, is especially prone to erosion due to intense rainfall, fluctuating river regimes, diverse land use practices, and subtle topographic variations. This study evaluates the spatial distribution of soil erosion risk in the region using the Revised Universal Soil Loss Equation (RUSLE) integrated with geospatial techniques. The RUSLE model was implemented within a Geographic Information System (GIS) framework to estimate annual soil loss across the study area. Five key parameters—rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), cover management (C), and conservation practice (P) were generated using rainfall records, soil datasets, satellite imagery, and digital elevation models processed in ArcGIS. The computed soil loss values were classified into five erosion risk categories: very low (0–5 t/ha/year), low (5–10 t/ha/year), moderate (10–25 t/ha/year), high (25–50 t/ha/year), and very high (>50 t/ha/year). The results reveal that annual soil loss in the study area ranges from negligible values to as high as 11,631.79 t/ha/year, with an average soil loss of 23.57 t/ha/year. For the total area of 1032.61 hectares, the estimated annual soil loss is approximately 24,340 tons. Spatial analysis indicates that a significant portion of the region falls under moderate erosion risk, while high and very high erosion zones are primarily associated with steeper slopes, exposed soils, and sparse vegetation cover. The study demonstrates that integrating RUSLE with GIS provides a reliable and effective approach for identifying erosion-prone areas. The findings offer valuable insights for planning targeted soil conservation strategies and support sustainable land management practices in the Lower Krishna Lanka region.},
        keywords = {GIS, Remote Sensing, Soil Erosion, RUSLE, Krishna River Delta, ArcGIS, Andhra Pradesh},
        month = {May},
        }