Estimation of soil water erosion using RUSLE, GIS, and remote sensing in Obibia River watershed, Anambra, Nigeria
The urban watershed of Obibia River is rapidly being degraded owing to pressures from increasing population and associated land-use changes. Erosion, an aspect of land degradation, has often been assumed to be costly and catastrophic due to the inability to accurately detect its occurrence at the ea...
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| Format: | Article |
| Language: | English |
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E-NAMTILA
2023-01-01
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| Series: | Dysona. Applied Science |
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| Online Access: | http://applied.dysona.org/article_155281_1e72db79ddafad23ec8a2d006a6b437b.pdf |
| _version_ | 1797973803550113792 |
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| author | Frank Okenmuo Temitayo Ewemoje |
| author_facet | Frank Okenmuo Temitayo Ewemoje |
| author_sort | Frank Okenmuo |
| collection | DOAJ |
| description | The urban watershed of Obibia River is rapidly being degraded owing to pressures from increasing population and associated land-use changes. Erosion, an aspect of land degradation, has often been assumed to be costly and catastrophic due to the inability to accurately detect its occurrence at the early stages to initiate conservation measures. This study aims to apply revised universal soil loss equation (RUSLE), remote sensing, and geographic information system (GIS) to accurately detect incipient soil erosion hazards in Obibia River watershed. The multi-source data for RUSLE was based on erosion factors of rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), and the vegetation (C) combined within a GIS environment. The erosion hazard map indicated erosion categories were: very low (55.1% <20 t ha-1 yr-1), low (31.3% 21-82 t ha-1 yr-1), medium (9.4% 82-243 t ha-1 yr-1), high (3% 234-543 t ha-1 yr-1); and extreme (1.2% >543 t ha-1 yr-1). Most extreme forms of erosion occurred in undulating landscapes near river bodies. The entire erosion categories require urgent management considerations except for the low categorization. The data can be relied upon for hydro-soil erosion identification, management, and control. |
| first_indexed | 2024-04-11T04:10:02Z |
| format | Article |
| id | doaj.art-c558a408f41b4bfda3cbf8dad40c7333 |
| institution | Directory Open Access Journal |
| issn | 2708-6283 |
| language | English |
| last_indexed | 2024-04-11T04:10:02Z |
| publishDate | 2023-01-01 |
| publisher | E-NAMTILA |
| record_format | Article |
| series | Dysona. Applied Science |
| spelling | doaj.art-c558a408f41b4bfda3cbf8dad40c73332023-01-01T09:59:22ZengE-NAMTILADysona. Applied Science2708-62832023-01-014161410.30493/das.2022.349144155281Estimation of soil water erosion using RUSLE, GIS, and remote sensing in Obibia River watershed, Anambra, NigeriaFrank Okenmuo0Temitayo Ewemoje1Department of Environmental Management, Pan African University of Life and Earth Sciences Institute, University of Ibadan, Ibadan, NigeriaDepartment of Agricultural and Environmental Engineering, Faculty of Technology, University of Ibadan, Ibadan, NigeriaThe urban watershed of Obibia River is rapidly being degraded owing to pressures from increasing population and associated land-use changes. Erosion, an aspect of land degradation, has often been assumed to be costly and catastrophic due to the inability to accurately detect its occurrence at the early stages to initiate conservation measures. This study aims to apply revised universal soil loss equation (RUSLE), remote sensing, and geographic information system (GIS) to accurately detect incipient soil erosion hazards in Obibia River watershed. The multi-source data for RUSLE was based on erosion factors of rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), and the vegetation (C) combined within a GIS environment. The erosion hazard map indicated erosion categories were: very low (55.1% <20 t ha-1 yr-1), low (31.3% 21-82 t ha-1 yr-1), medium (9.4% 82-243 t ha-1 yr-1), high (3% 234-543 t ha-1 yr-1); and extreme (1.2% >543 t ha-1 yr-1). Most extreme forms of erosion occurred in undulating landscapes near river bodies. The entire erosion categories require urgent management considerations except for the low categorization. The data can be relied upon for hydro-soil erosion identification, management, and control.http://applied.dysona.org/article_155281_1e72db79ddafad23ec8a2d006a6b437b.pdfsoil erosionremote sensingenvironmental managementgeographic information system |
| spellingShingle | Frank Okenmuo Temitayo Ewemoje Estimation of soil water erosion using RUSLE, GIS, and remote sensing in Obibia River watershed, Anambra, Nigeria Dysona. Applied Science soil erosion remote sensing environmental management geographic information system |
| title | Estimation of soil water erosion using RUSLE, GIS, and remote sensing in Obibia River watershed, Anambra, Nigeria |
| title_full | Estimation of soil water erosion using RUSLE, GIS, and remote sensing in Obibia River watershed, Anambra, Nigeria |
| title_fullStr | Estimation of soil water erosion using RUSLE, GIS, and remote sensing in Obibia River watershed, Anambra, Nigeria |
| title_full_unstemmed | Estimation of soil water erosion using RUSLE, GIS, and remote sensing in Obibia River watershed, Anambra, Nigeria |
| title_short | Estimation of soil water erosion using RUSLE, GIS, and remote sensing in Obibia River watershed, Anambra, Nigeria |
| title_sort | estimation of soil water erosion using rusle gis and remote sensing in obibia river watershed anambra nigeria |
| topic | soil erosion remote sensing environmental management geographic information system |
| url | http://applied.dysona.org/article_155281_1e72db79ddafad23ec8a2d006a6b437b.pdf |
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