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Predicting sediment yield on different landuse surfaces in Calabar River Catchment, Nigeria
This study predicts sediment yield on various landuse surfaces within the Calabar River Catchment, Nigeria. Five experimental plots of 31 by 23 cm (representing urban, farm, grass, bare, and forest surfaces) were established on a convex slope series with a 20% gradient, oriented along the slope stri...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10448462/ https://www.ncbi.nlm.nih.gov/pubmed/37636378 http://dx.doi.org/10.1016/j.heliyon.2023.e19071 |
Sumario: | This study predicts sediment yield on various landuse surfaces within the Calabar River Catchment, Nigeria. Five experimental plots of 31 by 23 cm (representing urban, farm, grass, bare, and forest surfaces) were established on a convex slope series with a 20% gradient, oriented along the slope strike. Rainfall, morphological, and hydraulic stations were derived for each plot. Multiple regressions and Factor analysis were employed to analyse the collected data. The research identifies critical factors influencing sediment yield, such as rainfall amount, rainfall intensity, slope gradient, slope length, sand, silt, clay, vegetation cover, and infiltration capacity. The results (p < 0.05) indicate that slope length, sand, silt, clay, infiltration capacity, and vegetation cover significantly influence sediment yield for urban, farmland, grassland, and bare surfaces, respectively. Factor analysis revealed strong correlations between sediment yield, silt, rainfall amount, rainfall intensity, and slope gradient. Case-wise diagnostics predictions indicate sediment yields for urban, bare, farm, grass, and vegetation-covered surfaces as 14.95 kg, 33.91 kg, 28.78 kg, 33.50 kg, and 5.66 kg, respectively. The regression model, with case-wise diagnostic residual statistics and standard prediction coefficients, provides valuable insights. For example, the forest surface exhibited a minimum sediment yield of −1.413 kg/m(2) with each unit decrease in forest area, emphasising the significance of vegetation cover in sediment retention. Conversely, bare surfaces showed a maximum sediment yield of 0.843 kg/m(2) with each unit increase in bare surface area, highlighting their heightened vulnerability to sediment erosion. Considering the implications of these findings, the development of urban master plans that incorporate well-designed landscaping and drainage systems is crucial, particularly in high rainfall catchments like the study area. Such measures can effectively mitigate sediment yield and address the adverse effects of land use changes on different surfaces. |
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