From Data to Action: Rainfall Factor-Based Soil Erosion Assessment in Arid Regions Through Integrated Geospatial Modeling

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Abstract
Soil erosion poses a significant threat to natural resources and agricultural productivity in arid regions. This study applied the Revised Universal Soil Loss Equation (RUSLE) model to simulate rainfall erosivity and soil erosion risk in the Wadi Allith basin, Saudi Arabia, using rainfall data from 2016 to 2018. The results demonstrated that the basin experienced a predominant slight level of erosion risk, with around 5 tons/ha annually. This study revealed that a very slight erosion risk was predominant in 2016 (97% of the basin area), 2017 (96%), and 2018 (95%), while less than 1% of the study area was exposed to severe erosion risks across all three years. An increasing trend in erosion severity was observed between 2016 and 2018, correlating with rising average annual rainfall amounts of 120 mm, 145 mm, and 155 mm. This underscores the importance of understanding how climatic factors influence soil stability, particularly in arid regions where water scarcity is typically a limiting factor. The successful application of Geographic Information Systems (GISs) and remote sensing tools integrating the various components of the RUSLE model showcases the effectiveness of these technologies in environmental monitoring and risk assessment. These tools facilitate a comprehensive analysis of the factors contributing to soil erosion, enabling researchers and policymakers to visualize erosion risk across the basin and prioritize areas for intervention. This study highlights the importance of ongoing soil erosion monitoring in arid environments such as the Wadi Allith basin, Saudi Arabia.
Funding Information
  • The Chinese Academy of Sciences (CAS), President’s International Fellowship Initiative (PIFI) (2021VEA0007)

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