Optimizing interpolation and quantitative morphometry analysis suitability to soil erodibility modeling for soil erosion risk mapping in a complex topography

This study prioritizes soil erosion risk using geoinformatics, addressing the novel experimental validation gap of morphometric parameters (MPs) with soil erodibility quotient (K). Hence, we analyzed 178 soil samples, deduced 31 key MPs from 84 quaternary watersheds within South Africa, and analyzed...

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Bibliographic Details
Main Authors: Solomon Temidayo Owolabi, Johanes A. Belle
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:Geocarto International
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Online Access:https://www.tandfonline.com/doi/10.1080/10106049.2025.2509878
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Summary:This study prioritizes soil erosion risk using geoinformatics, addressing the novel experimental validation gap of morphometric parameters (MPs) with soil erodibility quotient (K). Hence, we analyzed 178 soil samples, deduced 31 key MPs from 84 quaternary watersheds within South Africa, and analyzed for the most suitable interpolation method to identify erosion-prone areas. Results indicate a mean soil erodibility of 0.062 ton•yr•MJ−1•mm−1, with a high bifurcation ratio (12.72) reflecting significant drainage complexity. Average form factor (0.44), elongation ratio (0.74), and wandering ratio (3.60) suggest moderate runoff and efficient drainage. Natural neighbor interpolation emerged as the most effective method (R2 = 0.997). Correlation analysis indicates that only 19 principal MPs’ suitability relates to soil erodibility (p-value < 0.05), while texture ratio and drainage texture achieved the strongest correlations (p-value < 0.000). The findings highlight the importance of site-specific morphometric parameter (MP) modeling in accounting for landscape heterogeneity and human impacts.
ISSN:1010-6049
1752-0762