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...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-08-01
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| Series: | Heliyon |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023062795 |
| _version_ | 1797732845370736640 |
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| author | M.A. Abua E.I. Igelle V.B. Eneyo T.P. Abali N.A. Akpan E.P. Archibong Kamal Abdelrahman Mohammed S. Fnais Peter Andráš Ahmed M. Eldosouky |
| author_facet | M.A. Abua E.I. Igelle V.B. Eneyo T.P. Abali N.A. Akpan E.P. Archibong Kamal Abdelrahman Mohammed S. Fnais Peter Andráš Ahmed M. Eldosouky |
| author_sort | M.A. Abua |
| collection | DOAJ |
| description | 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/m2 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/m2 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. |
| first_indexed | 2024-03-12T12:20:25Z |
| format | Article |
| id | doaj.art-33297e51848f49d29e0662317b16685e |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-03-12T12:20:25Z |
| publishDate | 2023-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-33297e51848f49d29e0662317b16685e2023-08-30T05:53:38ZengElsevierHeliyon2405-84402023-08-0198e19071Predicting sediment yield on different landuse surfaces in Calabar River Catchment, NigeriaM.A. Abua0E.I. Igelle1V.B. Eneyo2T.P. Abali3N.A. Akpan4E.P. Archibong5Kamal Abdelrahman6Mohammed S. Fnais7Peter Andráš8Ahmed M. Eldosouky9Department of Geography and Environmental Science, University of Calabar, NigeriaDepartment of Environmental Resource Management, University of Calabar, NigeriaDepartment of Tourism Studies, University of Calabar, NigeriaDepartment of Geography and Environmental Management, Rivers State University, Nkpolu, Port Harcourt, NigeriaDepartment of Environmental Education, University of Calabar, NigeriaDepartment of Social Work, University of Calabar, NigeriaDepartment of Geology and Geophysics, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi ArabiaDepartment of Geology and Geophysics, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi ArabiaFaculty of Natural Sciences, Matej Bel University in BanskaBystrica, Tajovského 40, 974 01, BanskaBystrica, SlovakiaGeology Department, Faculty of Science, Suez University, Suez, 43518, Egypt; Academy of Scientific Research & Technology, Cairo, Egypt; Corresponding author. Geology Department, Faculty of Science, Suez University, Suez, 43518, Egypt.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/m2 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/m2 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.http://www.sciencedirect.com/science/article/pii/S2405844023062795Sediment yieldLanduse surfacesCalabar river catchmentPredictionHydrogeomorphologyCross river state |
| spellingShingle | M.A. Abua E.I. Igelle V.B. Eneyo T.P. Abali N.A. Akpan E.P. Archibong Kamal Abdelrahman Mohammed S. Fnais Peter Andráš Ahmed M. Eldosouky Predicting sediment yield on different landuse surfaces in Calabar River Catchment, Nigeria Heliyon Sediment yield Landuse surfaces Calabar river catchment Prediction Hydrogeomorphology Cross river state |
| title | Predicting sediment yield on different landuse surfaces in Calabar River Catchment, Nigeria |
| title_full | Predicting sediment yield on different landuse surfaces in Calabar River Catchment, Nigeria |
| title_fullStr | Predicting sediment yield on different landuse surfaces in Calabar River Catchment, Nigeria |
| title_full_unstemmed | Predicting sediment yield on different landuse surfaces in Calabar River Catchment, Nigeria |
| title_short | Predicting sediment yield on different landuse surfaces in Calabar River Catchment, Nigeria |
| title_sort | predicting sediment yield on different landuse surfaces in calabar river catchment nigeria |
| topic | Sediment yield Landuse surfaces Calabar river catchment Prediction Hydrogeomorphology Cross river state |
| url | http://www.sciencedirect.com/science/article/pii/S2405844023062795 |
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