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Machine learning-based variable importance analysis of soil factors influencing wind erodibility and threshold wind velocity in Central Iran
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DOI：10.1016/j.aeolia.2025.101026.png)
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Abstract
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• Wind erosion risk assessed using wind tunnel tests and soil analysis. • Gypsum, sodium absorption ratio, electrical conductivity and men weight of diameter strongly influenced sediment yield. • Clay, CaCO3, and shear strength governed threshold wind velocity. • Random Forest model accurately predicted threshold wind velocity (R2 = 0.83). • Machine learning enhances understanding of soil–wind interactions in arid zones.
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