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Ricardo Simão Diniz Dalmolin ; Pablo Miguel ;Revista Brasileira de Ciência do Solo 2013, 37 2

Author: Alessandro Samuel-Rosa

Source: http://www.redalyc.org/


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Revista Brasileira de Ciência do Solo ISSN: 0100-0683 revista@sbcs.org.br Sociedade Brasileira de Ciência do Solo Brasil Samuel-Rosa, Alessandro; Diniz Dalmolin, Ricardo Simão; Miguel, Pablo BUILDING PREDICTIVE MODELS OF SOIL PARTICLE-SIZE DISTRIBUTION Revista Brasileira de Ciência do Solo, vol.
37, núm.
2, 2013, pp.
422-430 Sociedade Brasileira de Ciência do Solo Viçosa, Brasil Available in: http:--www.redalyc.org-articulo.oa?id=180226346013 How to cite Complete issue More information about this article Journals homepage in redalyc.org Scientific Information System Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal Non-profit academic project, developed under the open access initiative 422 Alessandro Samuel-Rosa et al. BUILDING PREDICTIVE MODELS OF SOIL PARTICLE-SIZE DISTRIBUTION (1) Alessandro Samuel-Rosa(2), Ricardo Simão Diniz Dalmolin(3) & Pablo Miguel(4) SUMMARY Is it possible to build predictive models (PMs) of soil particle-size distribution (psd) in a region with complex geology and a young and unstable land-surface? The main objective of this study was to answer this question.
A set of 339 soil samples from a small slope catchment in Southern Brazil was used to build PMs of psd in the surface soil layer.
Multiple linear regression models were constructed using terrain attributes (elevation, slope, catchment area, convergence index, and topographic wetness index).
The PMs explained more than half of the data variance. This performance is similar to (or even better than) that of the conventional soil mapping approach.
For some size fractions, the PM performance can reach 70 %. Largest uncertainties were observed in geologically more complex areas.
Therefore, significant improvements in the predictions can only be achieved if accurate geological data is made available.
Meanwhile, PMs built on terrain attributes are efficient in predicting the particle-size distribution (psd) of soils in regions of complex ge...





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