Prediction Models for Water Erosion Risk Management: A Review
| dc.contributor.author | Ahamefule, Henry Emeka | |
| dc.contributor.author | Fatola, F.O. | |
| dc.contributor.author | Olaniyan, J.O. | |
| dc.contributor.author | Amana, Sani Mathew | |
| dc.contributor.author | Eifediyi, E.K. | |
| dc.contributor.author | Ihem, E. | |
| dc.contributor.author | Nwokocha, C.C. | |
| dc.contributor.author | Adepoju, A.S. | |
| dc.contributor.author | Adepoju, I.O. | |
| dc.contributor.author | Babalola, M.J. | |
| dc.date.accessioned | 2023-12-11T14:06:44Z | |
| dc.date.available | 2023-12-11T14:06:44Z | |
| dc.date.issued | 2018-05-21 | |
| dc.description.abstract | In order to estimate the potential soil erosion hazard of an area, erosion prediction models are needed. Various models have been used by researchers, which ranges from mathematical and conceptual simple approaches to complex models that try to include the complexities of the real world. Six (6) models are reviewed in relation to their suitability for use. The KINEROS, CORINE and EUROSEM were best suited for water erosion risk prediction in cultivated soils. On the other hand, the KINEROS, PESERA, CORINE and EUROSEM were found to be applicable in all sectors (Agronomy, water resources management and road construction) highlighted. The GLASOD had the least applicability with respect to this study. | en_US |
| dc.identifier.citation | Amana, S.M. et al. (2018) Prediction Models for Water Erosion Risk Management: A Review | en_US |
| dc.identifier.uri | https://keffi.nsuk.edu.ng/handle/20.500.14448/3086 | |
| dc.language.iso | en | en_US |
| dc.publisher | Department of Agronomy, Nasarawa State University, Keffi. | en_US |
| dc.title | Prediction Models for Water Erosion Risk Management: A Review | en_US |
| dc.type | Article | en_US |