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dc.contributor.advisorFerre, Ty P. A.en_US
dc.contributor.authorRice, Amy Katherine
dc.creatorRice, Amy Katherineen_US
dc.date.accessioned2011-12-05T14:18:13Z
dc.date.available2011-12-05T14:18:13Z
dc.date.issued2009en_US
dc.identifier.urihttp://hdl.handle.net/10150/193437
dc.description.abstractTraditional soil classification methods invoke physical differences based on particle size to group soils into textural classes. Resulting groupings are used to make predictions about soil attributes and processes of interest including hydrologic response. My hypothesis is that more useful classification schemes will be created by starting with response and applying an inverse approach to generate soil groupings. I propose an alternative classification scheme based on these hypotheses, using techniques of cluster analysis. The resulting system has high predictive capacity with simplicity comparable to the U.S. Dept. of Agriculture soil textural triangle or other similar classification diagrams. I conclude that: classification is most appropriate when carried out on process and objective specific bases; there is a physical meaning to cluster-based groupings, which allows for more appropriate segregation of response as compared to textural groupings; using clusters, a small number of samples can be used to characterize the range of response.
dc.language.isoENen_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.subjectclustersen_US
dc.subjectHYDRUSen_US
dc.subjectkmeansen_US
dc.subjectROSETTAen_US
dc.subjectsoil classificationen_US
dc.subjectUSDA soil textural triangleen_US
dc.titlePREDICTING HYDRAULIC RESPONSE: COMPARISON OF TEXTURAL AND RESPONSE CLUSTERING APPROACHES TO SOIL CLASSIFICATIONen_US
dc.typetexten_US
dc.typeElectronic Thesisen_US
dc.contributor.chairFerre, Ty P. A.en_US
dc.identifier.oclc659753612en_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.levelmastersen_US
dc.contributor.committeememberSchaap, Marcelen_US
dc.contributor.committeememberTuller, Markusen_US
dc.contributor.committeememberZreda, Mareken_US
dc.identifier.proquest10770en_US
thesis.degree.disciplineHydrologyen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.nameM.S.en_US
refterms.dateFOA2018-06-16T23:27:37Z
html.description.abstractTraditional soil classification methods invoke physical differences based on particle size to group soils into textural classes. Resulting groupings are used to make predictions about soil attributes and processes of interest including hydrologic response. My hypothesis is that more useful classification schemes will be created by starting with response and applying an inverse approach to generate soil groupings. I propose an alternative classification scheme based on these hypotheses, using techniques of cluster analysis. The resulting system has high predictive capacity with simplicity comparable to the U.S. Dept. of Agriculture soil textural triangle or other similar classification diagrams. I conclude that: classification is most appropriate when carried out on process and objective specific bases; there is a physical meaning to cluster-based groupings, which allows for more appropriate segregation of response as compared to textural groupings; using clusters, a small number of samples can be used to characterize the range of response.


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