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Geomorphic provinces of South Africa, Lesotho and Swaziland: A physiographic subdivision for earth and environmental scientists

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dc.contributor.author Partridge, TC
dc.contributor.author Dollar, ESJ
dc.contributor.author Moolman, J
dc.contributor.author Dollar, LH
dc.date.accessioned 2010-09-30T07:37:15Z
dc.date.available 2010-09-30T07:37:15Z
dc.date.issued 2010-02
dc.identifier.citation Partridge, TC, Dollar, ESJ, Moolman, J and Dollar, LH. 2010. Geomorphic provinces of South Africa, Lesotho and Swaziland: A physiographic subdivision for earth and environmental scientists, Transactions of the Royal Society of South Africa, Vol. 65(1), pp 1-47 en
dc.identifier.issn 0035-919X
dc.identifier.uri http://www.informaworld.com/smpp/content~content=a920181189&db=all
dc.identifier.uri http://hdl.handle.net/10204/4421
dc.description Copyright: 2010 Royal Society of South Africa en
dc.description.abstract This work has drawn upon previous attempts to define geomorphic provinces, but also on more recent work on the geological and geomorphological evolution of southern African fluvial systems. It has also used Digital Terrain Model (DTM)-derived data and statistical techniques to determine 34 geomorphic provinces and 12 sub-provinces within South Africa, Lesotho and Swaziland. Ninety-nine main stem river longitudinal profiles and valley cross-sectional profiles were generated from the DTM-derived data, and a statistical technique, the Worsley likelihood ratio test (WLRT), was applied to define statistically significant changes in slope and valley cross-sectional width along the river continuum. This isolated 471 macro-reaches for the 99 main stem rivers. Each macro-reach was then analysed using a variety of descriptors including shape, best fit curve, slope, sediment storage potential and valley width. Principal component analysis was applied to the data set to determine whether significant groupings existed, indicating significant similarities in the data by way of area, and conversely, whether distinct differences between groups of data were evident. The scores for the whole data set showed a large grouping around the origin with some scatter along the PC1 axis. Distinct groups were, however, evident for macro-reaches within each province. These reflect the extent of uniformity in the slopes, valley widths, altitudes and shape descriptors of each province. A description of each of the 34 provinces and 12 sub-provinces is presented. en
dc.language.iso en en
dc.publisher Royal Society of South Africa en
dc.subject Geomorphic provinces en
dc.subject Conservation planning en
dc.subject Southern African fluvial systems en
dc.subject Digital Terrain Model en
dc.title Geomorphic provinces of South Africa, Lesotho and Swaziland: A physiographic subdivision for earth and environmental scientists en
dc.type Article en
dc.identifier.apacitation Partridge, T., Dollar, E., Moolman, J., & Dollar, L. (2010). Geomorphic provinces of South Africa, Lesotho and Swaziland: A physiographic subdivision for earth and environmental scientists. http://hdl.handle.net/10204/4421 en_ZA
dc.identifier.chicagocitation Partridge, TC, ESJ Dollar, J Moolman, and LH Dollar "Geomorphic provinces of South Africa, Lesotho and Swaziland: A physiographic subdivision for earth and environmental scientists." (2010) http://hdl.handle.net/10204/4421 en_ZA
dc.identifier.vancouvercitation Partridge T, Dollar E, Moolman J, Dollar L. Geomorphic provinces of South Africa, Lesotho and Swaziland: A physiographic subdivision for earth and environmental scientists. 2010; http://hdl.handle.net/10204/4421. en_ZA
dc.identifier.ris TY - Article AU - Partridge, TC AU - Dollar, ESJ AU - Moolman, J AU - Dollar, LH AB - This work has drawn upon previous attempts to define geomorphic provinces, but also on more recent work on the geological and geomorphological evolution of southern African fluvial systems. It has also used Digital Terrain Model (DTM)-derived data and statistical techniques to determine 34 geomorphic provinces and 12 sub-provinces within South Africa, Lesotho and Swaziland. Ninety-nine main stem river longitudinal profiles and valley cross-sectional profiles were generated from the DTM-derived data, and a statistical technique, the Worsley likelihood ratio test (WLRT), was applied to define statistically significant changes in slope and valley cross-sectional width along the river continuum. This isolated 471 macro-reaches for the 99 main stem rivers. Each macro-reach was then analysed using a variety of descriptors including shape, best fit curve, slope, sediment storage potential and valley width. Principal component analysis was applied to the data set to determine whether significant groupings existed, indicating significant similarities in the data by way of area, and conversely, whether distinct differences between groups of data were evident. The scores for the whole data set showed a large grouping around the origin with some scatter along the PC1 axis. Distinct groups were, however, evident for macro-reaches within each province. These reflect the extent of uniformity in the slopes, valley widths, altitudes and shape descriptors of each province. A description of each of the 34 provinces and 12 sub-provinces is presented. DA - 2010-02 DB - ResearchSpace DP - CSIR KW - Geomorphic provinces KW - Conservation planning KW - Southern African fluvial systems KW - Digital Terrain Model LK - https://researchspace.csir.co.za PY - 2010 SM - 0035-919X T1 - Geomorphic provinces of South Africa, Lesotho and Swaziland: A physiographic subdivision for earth and environmental scientists TI - Geomorphic provinces of South Africa, Lesotho and Swaziland: A physiographic subdivision for earth and environmental scientists UR - http://hdl.handle.net/10204/4421 ER - en_ZA


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