Data/hora: 31/05/2024 11:57:46

Biblioteca(s): | Embrapa Solos.
Data corrente: | 11/02/2022
Data da última atualização: | 11/03/2022
Autoria: | SANTOS, P. A.; PINHEIRO, H. S. K.; CARVALHO JUNIOR, W. de; PEREIRA, N. R.; BHERING, S. B.; SILVA, I. L.
Afiliação: | PRISCILLA 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.
Título: | Modeling soils physical-hydric attributes through algorithms for quantitative pedology in Guapi-Macacu watershed, RJ.
Ano de publicação: | 2022
Fonte/Imprenta: | In: PEDOMETRICS BRAZIL, 2., 2021, Rio de Janeiro. Annals [...]. Rio de Janeiro: Embrapa Solos, 2022. Não paginado. Evento online.
Idioma: | Inglês
Conteúdo: | The 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.
Palavras-Chave: | AQP; Digital Soil Mapping; Geoprocessing; Hydropedology; Predictive Modeling.
Categoria do assunto: | P Recursos Naturais, Ciências Ambientais e da Terra
URL: | http://ainfo.cnptia.embrapa.br/digital/bitstream/item/231211/1/Modeling-soils-physical-hydric-attributes-through-algorithms-2022.pdf
Registro original: | Embrapa Solos (CNPS)
Exemplares: | CNPS - (20987-1) - UPC - AA - DD -  -  -  - DIS