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dc.contributor.authorShirley, Aubrey Christian
dc.date.accessioned2014-03-04T20:00:48Z
dc.date.available2014-03-04T20:00:48Z
dc.date.issued2011-05
dc.identifier.othershirley_aubrey_c_201105_ms
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/shirley_aubrey_c_201105_ms
dc.identifier.urihttp://hdl.handle.net/10724/27300
dc.description.abstractPedotransfer functions (PTFs) are used to predict saturated hydraulic conductivity (Ks) from more easily measured soil properties. Our objective was to determine if soil morphology was an important factor in predicting Ks using PTFs. We used soil profile descriptions for nine soils from the S-124 regional project dataset describing soils of the southeastern United States. Our best decision-tree model predicted log10 Ks (cm day-1) with an average log10 root mean square residual (RMSR) of 0.8017. The best models used bulk density and texture but not soil morphological descriptors. Sand textural class predicted the highest Ks. For the finer textured soils, the splits were based on bulk density. The NRCS method predicted Ks with a RMSR of 0.9562. Morphological descriptors of soil structure may not have been important because bulk density acted as a surrogate for structure.
dc.languageeng
dc.publisheruga
dc.rightspublic
dc.subjectRegression tees
dc.subjectsaturated hydraulic conductivity
dc.subjectsoil structure
dc.titleEstimating saturated hydraulic conductivity for southeastern soils using decision tree analysis
dc.typeThesis
dc.description.degreeMS
dc.description.departmentCrop and Soil Sciences
dc.description.majorCrop and Soil Sciences
dc.description.advisorDavid E. Radcliffe
dc.description.committeeDavid E. Radcliffe
dc.description.committeeTodd C. Rasmussen
dc.description.committeeMiguel L. Cabrera


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