Please use this identifier to cite or link to this item: https://repository.seku.ac.ke/handle/123456789/4333
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dc.contributor.authorNjiru, Gabriel N.-
dc.contributor.authorKariuki, Patrick C.-
dc.contributor.authorMwetu, Kennedy-
dc.date.accessioned2019-01-29T07:10:27Z-
dc.date.available2019-01-29T07:10:27Z-
dc.date.issued2018-11-
dc.identifier.citationOpen Journal of Soil Science, 8, 277-302en_US
dc.identifier.issn2162-5379-
dc.identifier.issn2162-5360-
dc.identifier.urihttps://file.scirp.org/pdf/OJSS_2018111215001430.pdf-
dc.identifier.urihttp://repository.seku.ac.ke/handle/123456789/4333-
dc.descriptionDOI: https://doi.org/10.4236/ojss.2018.811021en_US
dc.description.abstractThis study modeled soil erosion between January 2016 and September 2018 for land management in Golole catchment. The Revised Universal Soil Loss Equation (RUSLE) constituting the main agents of soil erosion was modeled in a Geographical Information System (GIS) environment. The objective of this study was to model soil erosion for land management in the ungauged Golole catchment. The Golole catchment soil erosion map reveals that within the catchment the soil loss was not homogeneous and erosion risk was not the same. The catchment experiences an annual mean score soil loss rate of 279 t/ha that is above the recommended maximum allowable annual soil loss rate of 4 t/ha. The catchment’s soil loss rate is described as high and severe representing 70% and 30% of landmass respectively. This study found the need to decelerate the above soil loss rates to moderate and low levels by adopting soil erosion mitigation measures such as stone contour ridges, manure, strip cropping, and terracing in the cultivated areas and controlled grazing in the lowland rangeland. The study strongly felt the need to protect the forest reserve from tree cutting and further human encroachment. This study concludes that there is the need for further research 1) in the forest reserve areas that showed the greatest rates of soil erosion menace to determine the underlying causes, and 2) to assess the temporal trends of the soil erosion hazard using high-resolution data.en_US
dc.language.isoenen_US
dc.publisherScientific Research Publishingen_US
dc.subjectCatchmenten_US
dc.subjectSoil Lossen_US
dc.subjectErosivityen_US
dc.subjectErodibilityen_US
dc.subjectErosion Modelingen_US
dc.subjectArcGISen_US
dc.subjectRUSLEen_US
dc.titleModelling soil erosion for land management in ungauged golole catchment in Marsabit County, Kenyaen_US
dc.typeArticleen_US
Appears in Collections:School of Agriculture, Environment, Water and Natural Resources Management (JA)



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