01794nam a2200229 a 450000100080000000500110000800800410001910000180006024501450007826001410022352010020036465300080136665300250137465300180139965300180141765300240143570000230145970000270148270000190150970000190152870000170154721399472022-03-11       2022    bl uuuu     u00u1 u    #d1 aSANTOS, P. A.  aModeling soils physical-hydric attributes through algorithms for quantitative pedology in Guapi-Macacu watershed, RJ.h[electronic resource]  aIn: PEDOMETRICS BRAZIL, 2., 2021, Rio de Janeiro. Annals [...]. Rio de Janeiro: Embrapa Solos, 2022. Não paginado. Evento online.c2022  aThe 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.  aAQP  aDigital Soil Mapping  aGeoprocessing  aHydropedology  aPredictive Modeling1 aPINHEIRO, H. S. K.1 aCARVALHO JUNIOR, W. de1 aPEREIRA, N. R.1 aBHERING, S. B.1 aSILVA, I. L.