Modelling soil erosion for land management in ungauged golole catchment in Marsabit County, Kenya

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dc.contributor.author Njiru, Gabriel N.
dc.contributor.author Kariuki, Patrick C.
dc.contributor.author Mwetu, Kennedy
dc.date.accessioned 2019-01-29T07:10:27Z
dc.date.available 2019-01-29T07:10:27Z
dc.date.issued 2018-11
dc.identifier.citation Open Journal of Soil Science, 8, 277-302 en_US
dc.identifier.issn 2162-5379
dc.identifier.issn 2162-5360
dc.identifier.uri https://file.scirp.org/pdf/OJSS_2018111215001430.pdf
dc.identifier.uri http://repository.seku.ac.ke/handle/123456789/4333
dc.description DOI: https://doi.org/10.4236/ojss.2018.811021 en_US
dc.description.abstract This 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.iso en en_US
dc.publisher Scientific Research Publishing en_US
dc.subject Catchment en_US
dc.subject Soil Loss en_US
dc.subject Erosivity en_US
dc.subject Erodibility en_US
dc.subject Erosion Modeling en_US
dc.subject ArcGIS en_US
dc.subject RUSLE en_US
dc.title Modelling soil erosion for land management in ungauged golole catchment in Marsabit County, Kenya en_US
dc.type Article en_US


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