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<p>This study aims to quantify soil erosion and identify vulnerable areas in the Ifni Massif and Lakhsas limestone plateau, located in Morocco, by integrating the five factors of the Revised Universal Soil Loss Equation (RUSLE): Rainfall-Runoff Erosivity (R), Soil Erodibility (K), slope Length &amp; Steepness (LS), vegetation cover (C), and supporting practices (P) performed using the Google Earth Engine (GEE) platform. Results show significant spatial variability in soil loss: with the highest values occurring in hydrographic networks, and the lowest in areas with flat topography. The model estimates an average annual soil loss of 18.3 t/ha/yr, with 59% of the study area experiencing rates exceeding 10 t/ha/yr. These GEE spatial modeling results have demonstrated the high fragility of soils and the importance of targeted conservation measures to mitigate the impacts of erosion in these vulnerable environments, and provide valuable information to decision-makers for land-use planning and the implementation of sustainable soil conservation strategies, particularly in the context of quarry siting. This could also have a positive impact on future projects in areas exposed to soil degradation risk.</p>

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GEE-assisted RUSLE modeling of water erosion: case of the Ifni Massif and Lakhssas plateau (Western Anti-Atlas, Morocco)

  • 期刊论文

  • 发表日期：

    2026年2月12日

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  • Mohamed Mahmoud Sebbab,
  • Hamza Taghlaoui,
  • Abdelhadi El Ouahidi,
  • Khadija Sebbab,
  • Hassan Bita,
  • Badreddine Ennassiri,
  • Hanane Bekri,
  • abderrahmane Jadouane

摘要

This study aims to quantify soil erosion and identify vulnerable areas in the Ifni Massif and Lakhsas limestone plateau, located in Morocco, by integrating the five factors of the Revised Universal Soil Loss Equation (RUSLE): Rainfall-Runoff Erosivity (R), Soil Erodibility (K), slope Length & Steepness (LS), vegetation cover (C), and supporting practices (P) performed using the Google Earth Engine (GEE) platform. Results show significant spatial variability in soil loss: with the highest values occurring in hydrographic networks, and the lowest in areas with flat topography. The model estimates an average annual soil loss of 18.3 t/ha/yr, with 59% of the study area experiencing rates exceeding 10 t/ha/yr. These GEE spatial modeling results have demonstrated the high fragility of soils and the importance of targeted conservation measures to mitigate the impacts of erosion in these vulnerable environments, and provide valuable information to decision-makers for land-use planning and the implementation of sustainable soil conservation strategies, particularly in the context of quarry siting. This could also have a positive impact on future projects in areas exposed to soil degradation risk.