期刊
SOIL SCIENCE SOCIETY OF AMERICA JOURNAL
卷 65, 期 3, 页码 811-819出版社
WILEY
DOI: 10.2136/sssaj2001.653811x
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A 937-horizon data set composed of site characteristics, morphology, and laboratory characterization data for soils of Ohio was used to develop soil bulk density (D-b) prediction models. We tested the hypothesis that using a combination of continuous variables (laboratory data) and nominal variables (site/state factor and morphological class descriptors) would enable the development of improved Pedo-Transfer Functions (PTFs) for D-b Three primary models were developed. The Lab Model, composed entirely of continuous variables, accounted for 56% of the variability in D-b Using only state factors and morphology as nominal variables, the Field Model explained 69%, A combined Field + Lab Model accounted for 72%, Restricting the data set to samples derived from loess and glacial till generated a Field + Lab Model that explained nearly 80% of the variability in D-b For a subset of 402 horizons.
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