Busca avançada
Ano de início
Entree
(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Evaluation of models for fitting soil particle-size distribution using UNSODA and a Brazilian dataset

Texto completo
Autor(es):
Vaz, Carlos Manoel Pedro [1] ; Ferreira, Ednaldo Jose [1] ; Posadas, Aldolfo Durand [2]
Número total de Autores: 3
Afiliação do(s) autor(es):
[1] Embrapa Instrumentat, Rua XV Novembro 1452, POB 741, BR-13561206 Sao Carlos, SP - Brazil
[2] AgriEntech Ltda, Rua Oseas Rocha Ramalho 110, BR-13563753 Sao Carlos, SP - Brazil
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: GEODERMA REGIONAL; v. 21, JUN 2020.
Citações Web of Science: 0
Resumo

The mineral soil Particle Size Distribution (PSD) is a fundamental and very useful soil characteristic widely used to support soil classification, soil management and soil processes modeling. An important limitation of PSD is the lack of standardization for granulometric fractions obtained from different soil classification systems, making difficult to compare and combine data. To overcome this drawback several attempts have been made to mathematically fit PSD data in order to allow soil texture data conversion among soil databases. Parametric equations have been proposed and/or evaluated for particular systems, but none of them has been studied, compared and proved being effective for soils of different types, regions and textural classes. Thus, the purpose of this work was evaluating and comparing performances of several PSD equations on a more comprehensive soil database as well as providing a method capable of fitting a general model for any soil texture. Cumulative PSD data of 221 soil samples, carefully selected from UNSODA and Brazilian/Embrapa datasets to include 12 soil textural classes mapped in the texture triangle, were used in this study to evaluate the fitting performance of commonly applied PSD equations with three and four parameters for unimodal data (SKAG-3p, ANDE-4p, BEST-3p, FRED-4p) and a seven-parameters equation (FRED-7p) used for gap-graded bimodal shaped data. The FRED-7p equation showed outstanding fittings accuracies with average RMSE (100{*}g g(-1)) of 0.53 for all soils, about twice as low as the second best fitted equation (ANDE-4p). FRED-7p fitting accuracy was slightly influenced by soil texture, showing a small increase as sand content increases and a decrease as silt content increases. The FRED-7p equation, originally proposed to fit cumulative gap-graded bimodal PSD, performed properly and accurately for all textural classes, including both unimodal and bimodal shaped PSDs. As a result of that, it is strongly recommended as a general model for any kind of soil PSD. (C) 2020 Elsevier B.V. All rights reserved. (AU)

Processo FAPESP: 18/16226-1 - Caracterização multifractal de imagens microtomográficas e sua correlação com a retenção e o transporte de água no solo
Beneficiário:Carlos Manoel Pedro Vaz
Linha de fomento: Auxílio à Pesquisa - Pesquisador Visitante - Internacional