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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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-12-01
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| Series: | Geocarto International |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/10106049.2025.2509878 |
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| author | Solomon Temidayo Owolabi Johanes A. Belle |
| author_facet | Solomon Temidayo Owolabi Johanes A. Belle |
| author_sort | Solomon Temidayo Owolabi |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-4d84cb0c18bb41e682014c72bb62d5db |
| institution | Kabale University |
| issn | 1010-6049 1752-0762 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geocarto International |
| spelling | doaj-art-4d84cb0c18bb41e682014c72bb62d5db2025-08-20T03:25:30ZengTaylor & Francis GroupGeocarto International1010-60491752-07622025-12-0140110.1080/10106049.2025.2509878Optimizing interpolation and quantitative morphometry analysis suitability to soil erodibility modeling for soil erosion risk mapping in a complex topographySolomon Temidayo Owolabi0Johanes A. Belle1Disaster Management Training and Education Centre for Africa, Faculty of Natural and Agricultural Science, University of the Free State, Bloemfontein, Free State, South AfricaDisaster Management Training and Education Centre for Africa, Faculty of Natural and Agricultural Science, University of the Free State, Bloemfontein, Free State, South AfricaThis 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.https://www.tandfonline.com/doi/10.1080/10106049.2025.2509878Watershed managementsoil conservationquantitative morphometric analysisSouth Africa |
| spellingShingle | Solomon Temidayo Owolabi Johanes A. Belle Optimizing interpolation and quantitative morphometry analysis suitability to soil erodibility modeling for soil erosion risk mapping in a complex topography Geocarto International Watershed management soil conservation quantitative morphometric analysis South Africa |
| title | Optimizing interpolation and quantitative morphometry analysis suitability to soil erodibility modeling for soil erosion risk mapping in a complex topography |
| title_full | Optimizing interpolation and quantitative morphometry analysis suitability to soil erodibility modeling for soil erosion risk mapping in a complex topography |
| title_fullStr | Optimizing interpolation and quantitative morphometry analysis suitability to soil erodibility modeling for soil erosion risk mapping in a complex topography |
| title_full_unstemmed | Optimizing interpolation and quantitative morphometry analysis suitability to soil erodibility modeling for soil erosion risk mapping in a complex topography |
| title_short | Optimizing interpolation and quantitative morphometry analysis suitability to soil erodibility modeling for soil erosion risk mapping in a complex topography |
| title_sort | optimizing interpolation and quantitative morphometry analysis suitability to soil erodibility modeling for soil erosion risk mapping in a complex topography |
| topic | Watershed management soil conservation quantitative morphometric analysis South Africa |
| url | https://www.tandfonline.com/doi/10.1080/10106049.2025.2509878 |
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