Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1139947
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dc.contributor.authorSANTOS, P. A.
dc.contributor.authorPINHEIRO, H. S. K.
dc.contributor.authorCARVALHO JUNIOR, W. de
dc.contributor.authorPEREIRA, N. R.
dc.contributor.authorBHERING, S. B.
dc.contributor.authorSILVA, I. L.
dc.date.accessioned2022-02-11T17:00:24Z-
dc.date.available2022-02-11T17:00:24Z-
dc.date.created2022-02-11
dc.date.issued2022
dc.identifier.citationIn: PEDOMETRICS BRAZIL, 2., 2021, Rio de Janeiro. Annals [...]. Rio de Janeiro: Embrapa Solos, 2022. Não paginado. Evento online.
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1139947-
dc.descriptionThe research goal is to analyze soil?s properties and associate them with the behavior and vertical variability of soil basic infiltration speed (bir) and saturated hydraulic conductivity (ksat) in soils from Guapi-Macacu watershed using the Algorithm for Quantitative Pedology (AQP) package, in order to support predictive vertical modeling of soil attributes. To achieve the goals, 36 soil profiles were subjected to statistical analysis and then applied the AQP depth functions: standardization, slicing and aggregation methods. Thus, having the harmonized data set, the results were quantitatively and qualitatively evaluated, which pointed to high soil granulometric and physicochemical properties variability, maintaining a moderate to strong correlation with the physical-hydric attributes. It is concluded that the high soil properties variability can affect the vertical modeling in terms of prediction, as it tends to reduce the assertive degree in the training/validation of the models.
dc.language.isoeng
dc.rightsopenAccess
dc.subjectAQP
dc.subjectGeoprocessing
dc.subjectHydropedology
dc.subjectDigital Soil Mapping
dc.subjectPredictive Modeling
dc.titleModeling soils physical-hydric attributes through algorithms for quantitative pedology in Guapi-Macacu watershed, RJ.
dc.typeArtigo em anais e proceedings
riaa.ainfo.id1139947
riaa.ainfo.lastupdate2022-02-11
dc.contributor.institutionPRISCILLA A. SANTOS, UFRRJ; HELENA S. K. PINHEIRO, UFRRJ; WALDIR DE CARVALHO JUNIOR, CNPS; NILSON RENDEIRO PEREIRA, CNPS; SILVIO BARGE BHERING, CNPS; IGOR L. SILVA, UFRRJ.
Aparece nas coleções:Artigo em anais de congresso (CNPS)

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