An evaluation of soil erosion hazard: A case study in Southern Africa using geomatics technologies

Persistent Link:
http://hdl.handle.net/10150/289928
Title:
An evaluation of soil erosion hazard: A case study in Southern Africa using geomatics technologies
Author:
Eiswerth, Barbara A.
Issue Date:
2003
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
Accelerated soil erosion in Malawi, Southern Africa, increasingly threatens agricultural productivity, given current and projected population growth trends. Previous attempts to document soil erosion potential have had limited success, lacking appropriate information and diagnostic tools. This study utilized geomatics technologies and the latest available information from topography, soils, climate, vegetation, and land use of a watershed in southern Malawi. The Soil Loss Estimation Model for Southern Africa (SLEMSA), developed for conditions in Zimbabwe, was evaluated and used to create a soil erosion hazard map for the watershed under Malawi conditions. The SLEMSA sub-models of cover, soil loss, and topography were computed from energy interception, rainfall energy, and soil erodibility, and slope length and steepness, respectively. Geomatics technologies including remote sensing and Geographic Information Systems (GIS) provided the tools with which land cover/land use, a digital elevation model, and slope length and steepness were extracted and integrated with rainfall and soils spatial information. Geomatics technologies enable rapid update of the model as new and better data sets become available. Sensitivity analyses of the SLEMSA model revealed that rainfall energy and slope steepness have the greatest influence on soil erosion hazard estimates in this watershed. Energy interception was intermediate in sensitivity level, whereas slope length and soil erodibility ranked lowest. Energy interception and soil erodibility were shown by parameter behavior analysis to behave in a linear fashion with respect to soil erosion hazard, whereas rainfall energy, slope steepness, and slope length exhibit non-linear behavior. When SLEMSA input parameters and results were compared to alternative methods of soil erosion assessment, such as drainage density and drainage texture, the model provided more spatially explicit information using 30 meter grid cells. Results of this study indicate that more accurate soil erosion estimates can be made when: (1) higher resolution digital elevation models are used; (2) data from improved precipitation station network are available, and; (3) greater investment in rainfall energy research.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Physical Geography.; Agriculture, Soil Science.; Environmental Sciences.; Remote Sensing.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Graduate College; Arid Lands Resources Sciences
Degree Grantor:
University of Arizona
Advisor:
Marsh, Stuart E.

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleAn evaluation of soil erosion hazard: A case study in Southern Africa using geomatics technologiesen_US
dc.creatorEiswerth, Barbara A.en_US
dc.contributor.authorEiswerth, Barbara A.en_US
dc.date.issued2003en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractAccelerated soil erosion in Malawi, Southern Africa, increasingly threatens agricultural productivity, given current and projected population growth trends. Previous attempts to document soil erosion potential have had limited success, lacking appropriate information and diagnostic tools. This study utilized geomatics technologies and the latest available information from topography, soils, climate, vegetation, and land use of a watershed in southern Malawi. The Soil Loss Estimation Model for Southern Africa (SLEMSA), developed for conditions in Zimbabwe, was evaluated and used to create a soil erosion hazard map for the watershed under Malawi conditions. The SLEMSA sub-models of cover, soil loss, and topography were computed from energy interception, rainfall energy, and soil erodibility, and slope length and steepness, respectively. Geomatics technologies including remote sensing and Geographic Information Systems (GIS) provided the tools with which land cover/land use, a digital elevation model, and slope length and steepness were extracted and integrated with rainfall and soils spatial information. Geomatics technologies enable rapid update of the model as new and better data sets become available. Sensitivity analyses of the SLEMSA model revealed that rainfall energy and slope steepness have the greatest influence on soil erosion hazard estimates in this watershed. Energy interception was intermediate in sensitivity level, whereas slope length and soil erodibility ranked lowest. Energy interception and soil erodibility were shown by parameter behavior analysis to behave in a linear fashion with respect to soil erosion hazard, whereas rainfall energy, slope steepness, and slope length exhibit non-linear behavior. When SLEMSA input parameters and results were compared to alternative methods of soil erosion assessment, such as drainage density and drainage texture, the model provided more spatially explicit information using 30 meter grid cells. Results of this study indicate that more accurate soil erosion estimates can be made when: (1) higher resolution digital elevation models are used; (2) data from improved precipitation station network are available, and; (3) greater investment in rainfall energy research.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectPhysical Geography.en_US
dc.subjectAgriculture, Soil Science.en_US
dc.subjectEnvironmental Sciences.en_US
dc.subjectRemote Sensing.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineArid Lands Resources Sciencesen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorMarsh, Stuart E.en_US
dc.identifier.proquest3106981en_US
dc.identifier.bibrecord.b44649320en_US
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