Geospatial Assessment of Soil Erosion Using Revised Universal Soil Loss Equation in Hirshabelle State of Somalia
2024
Abdiaziz Hassan Nur, Md. Faruq Hasan, Susmita Sarmin, Atia Shahin, Abdinasir Abdullahi Mohamed and Ali Hussein Ahmed
The objective of this study is to provide a thorough assessment of soil erosion in the Hirshabelle state from 2020 to 2023, utilizing the Revised Universal Soil Loss Equation (RUSLE) and advanced geospatial technologies, particularly Google Earth Engine, to guide sustainable land management strategies. The study integrates multiple datasets, including CHIRPS for rainfall measurement, MODIS for land use analysis, and a digital elevation model for slope calculation, to offer a comprehensive understanding of the factors contributing to soil erosion. The rainfall erosivity (R) factor is calculated using CHIRPS data, while the soil erodibility (K-factor) is derived from the soil dataset. The topographic condition (LS-factor) is computed using the digital elevation model, and the cover-management (C) and support practice (P) factors are determined from the NDVI and land use data, respectively. The findings reveal considerable spatial variation in soil erosion across the Hirshabelle state. The results are categorized into five levels based on the severity of soil loss: very low (<5), low (5-10), moderate (10-20), high (20-40), and very high (≥40). While areas classified under “very low” soil loss are dominant, indicating relatively stable soils, regions under “very high” soil loss signal potential land degradation and the need for immediate intervention. Furthermore, the study revealed the intricate interplay of slope, vegetation, and land use in influencing soil erosion. Areas with steeper slopes and less vegetation were more susceptible to soil loss, emphasizing the need for targeted soil conservation measures in these regions. The land use factor played a crucial role, with certain land uses contributing more to soil erosion than others.
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