Use este identificador para citar ou linkar para este item: http://repositorio.ufla.br/jspui/handle/1/43131
Título: Utilizing Splintex 2.0 for estimating the soil hydraulic conductivity curve measured with instantaneous profile method
Palavras-chave: Pedotransfer function
Soil hydraulic permeability
Saturated conductivity
Condutividade hidráulica do solo
Função de Pedotransferência
Condutividade hidráulica saturada
Solos - Permeabilidade
Data do documento: Out-2020
Editor: Elsevier
Citação: SILVA, A. C. da; ARMINDO, R. A.; PREVEDELLO, C. L. Utilizing Splintex 2.0 for estimating the soil hydraulic conductivity curve measured with instantaneous profile method. Soil and Tillage Research, [S.I.], v. 204, Oct. 2020. DOI: https://doi.org/10.1016/j.still.2020.104722.
Resumo: Soil hydraulic conductivity curve (SHCC) is a key-physical-function in hydrological and environmental studies. Measuring SHCC is a difficult and onerous task and often unfeasible in large-scale monitoring. Therefore, pedotransfer functions (PTFs) have been an alternative way for estimating SHCC. In this study, the novel version of Splintex model (Splintex 2.0) is analyzed to estimate the unsaturated soil hydraulic conductivity (K) as a function of water content (θ). Splintex 2.0 estimates the function K(θ) assuming that soil pores can be represented by equivalent capillary tubes and that the water flow rate is a function of pore size distribution. Then, the estimates of K(θ) data are fitted to the SHCC described by the van Genuchten (1980); Mualem (1976) (VGM) equation. In this study, the goodness-of-fit of K(θ) estimation was evaluated with selected 198 measured SHCCs by the instantenous profile method. Each data set contains measured information of textural composition, solid and bulk densities, total porosity, and K(θ) data. Estimated and measured SHCCs were compared dividing the analyzed soil data in four textures and computing Pearson correlation coefficient (r), mean error (ME), and root mean square error (RMSE) measures. The estimation using Splintex 2.0 revealed a mean RMSE of log10[K(θ)] of 1.17, ranging from 0.77 to 1.22, pointing for an acceptable performance for PTFs purposes.
URI: https://doi.org/10.1016/j.still.2020.104722
http://repositorio.ufla.br/jspui/handle/1/43131
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