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dc.contributorLe, Quang Baoen_US
dc.creatorTamene, Lulsegeden_US
dc.date2015-01-22en_US
dc.date.accessioned2022-03-28T21:47:37Z
dc.date.available2022-03-28T21:47:37Z
dc.identifierhttps://mel.cgiar.org/dspace/limiteden_US
dc.identifier.citationLulseged Tamene, Quang Bao Le. (22/1/2015). Estimating soil erosion in sub-Saharan Africa based on landscape similarity mapping and using the revised universal soil loss equation (RUSLE). Nutrient Cycling in Agroecosystems, 102 (1), pp. 17-31.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/67279
dc.description.abstractSoil erosion is one of the major forms of land degradation in sub-Saharan Africa (SSA) with serious impact on agricultural productivity. Due to the absence of reliable data at appropriate resolution and differences in the methods used, there are discrepancies in soil erosion estimates at both continental and basin levels. This study attempts to contribute to the existing regional soil erosion estimates based on a two-stage approach. First, we partitioned SSA into environmental units, so-called similar environmental constraint envelops (SECEs), using broad scale data as proxies of erosion drivers. The SECEs are intended to provide spatial frame for scaling out modeled erosion results. Second, soil erosion estimate is made at two selected basins of the White Volta and the Nile using spatially distributed revised universal soil loss (RUSLE) model. The delineation of SECEs across SSA provided spatially differentiated clusters governed by the existence of similar environmental conditions and soil erosion risk levels. The RUSLE-based estimates show that soil erosion ranges between 0 to 120 t ha(-1) yr(-1) (overall mean of 35 t ha(-1) yr(-1)) in the White Volta basin, and 0-650 t ha(-1) yr(-1) (overall mean of 75 t ha(-1) yr(-1)) in the Nile basin. The soil loss estimates show an overall agreement with other studies conducted in the two basins. Our approach provides guidance on where empirically estimated soil erosion for a given SECE can be extrapolated to similar SECE's with acceptable confidence and where finer SECE's sub-units should be defined to further collapse the spatial variability of drivers of erosion.en_US
dc.languageenen_US
dc.publisherSpringeren_US
dc.rightsCopyrighted; all rights reserveden_US
dc.sourceNutrient Cycling in Agroecosystems;102,(2015) Pagination 17,31en_US
dc.subjecterosion modelingen_US
dc.subjectlandscape similarityen_US
dc.subjectrusleen_US
dc.subjectwhite volta basinen_US
dc.subjectnile basinen_US
dc.titleEstimating soil erosion in sub-Saharan Africa based on landscape similarity mapping and using the revised universal soil loss equation (RUSLE)en_US
dc.typeJournal Articleen_US
cg.creator.idTamene, Lulseged: 0000-0002-3806-8890en_US
cg.creator.idLe, Quang Bao: 0000-0001-8514-1088en_US
cg.creator.ID-typeORCIDen_US
cg.creator.ID-typeORCIDen_US
cg.subject.agrovocsoil erosionen_US
cg.subject.agrovocsub-saharan africaen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerInternational Center for Tropical Agriculture - CIATen_US
cg.contributor.centerSwiss Federal Institute of Technology Zurich - ETH Zurichen_US
cg.contributor.crpCGIAR Research Program on Dryland Systems - DSen_US
cg.contributor.funderInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.projectCommunication and Documentation Information Services (CODIS)en_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.date.embargo-end-dateTimelessen_US
cg.coverage.regionGlobalen_US
cg.contactLT.Desta@CGIAR.ORGen_US
cg.identifier.doihttps://dx.doi.org/10.1007/s10705-015-9674-9en_US
dc.identifier.statusTimeless limited accessen_US
mel.impact-factor3.270en_US


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