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Assessment of water erosion risk in the Fergoug watershed in Algeria using a GIS-based RUSLE approach Oualid, Ahmed Tewfik; Hamimed, Abderrahmane; Benamina, Benyekhlef; Miloudi, Kaddour; Benslimane , Mohammed
Journal of Degraded and Mining Lands Management Vol. 13 No. 1 (2026)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2026.131.9531

Abstract

This work evaluated the spatial distribution and severity of water-driven soil erosion in the Fergoug watershed in northwestern Algeria by using the RUSLE model integrated within a Geographic Information System (GIS) framework. The watershed, characterized by steep slopes, erodible marly formations, and semi-arid Mediterranean climatic conditions, is highly vulnerable to land degradation. Five thematic layers corresponding to the RUSLE factors (rainfall erosivity, soil erodibility, slope length and steepness, cover management, and support practices) were produced using long-term rainfall records, a 30 m resolution Digital Elevation Model (DEM), Landsat-8 OLI imagery, and lithological maps. The spatial analysis revealed that rainfall erosivity ranges from 120 to 301 MJ mm ha-1 h-1 yr-1, while soil erodibility ranges from 0.015 to 0.065 t ha h ha-1 MJ-1 mm-1. High LS values are concentrated in the rugged southern and western sectors, whereas low C and P values are associated with forested zones with adequate soil protection. The integration of these parameters indicates an average annual soil loss of approximately 38.5 t ha-1 yr-1, with the most critical erosion zones exceeding 150 t ha-1 yr-1, mainly in steep and poorly vegetated areas. These findings demonstrate the effectiveness of coupling RUSLE with GIS and remote sensing for mapping erosion risk in data-scarce environments. The generated erosion risk map serves as a key tool to support decision-making, promote sustainable land management, and implement targeted soil and water conservation strategies in fragile semi-arid Mediterranean ecosystems.