Use este identificador para citar ou linkar para este item:
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1139947
Título: | Modeling soils physical-hydric attributes through algorithms for quantitative pedology in Guapi-Macacu watershed, RJ. |
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. |
Ano de publicação: | 2022 |
Referência: | In: PEDOMETRICS BRAZIL, 2., 2021, Rio de Janeiro. Annals [...]. Rio de Janeiro: Embrapa Solos, 2022. Não paginado. Evento online. |
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 Geoprocessing Hydropedology Digital Soil Mapping Predictive Modeling |
Tipo do material: | Artigo em anais e proceedings |
Acesso: | openAccess |
Aparece nas coleções: | Artigo em anais de congresso (CNPS)![]() ![]() |
Arquivos associados a este item:
Arquivo | Descrição | Tamanho | Formato | |
---|---|---|---|---|
Modeling-soils-physical-hydric-attributes-through-algorithms-2022.pdf | 284,79 kB | Adobe PDF | ![]() Visualizar/Abrir |