Probabilistic Analysis of Soil-Water Characteristic Curve of Bentonite: Multivariate Copula Approach
Publication: International Journal of Geomechanics
Volume 20, Issue 2
Abstract
Measurement of the soil-water characteristic curve (SWCC) is time-consuming for soils such as bentonites. It is desirable to develop a first-hand estimate of SWCC from a statistical generalization of the available data. A database for SWCCs of bentonite was compiled from the literature. The proposed approach entails the parameterization of SWCCs and constructing a multivariate probability distribution for the SWCC parameters. The choice of parameter constraints has a significant impact on SWCC quantification, which has not been studied for bentonites. Therefore, a database from this study was used to investigate the effect of van Genuchten (vG) model constraints on SWCC parameter statistics of bentonite. The three-parameter vG model with parameters , and provided the best choice. Subsequently, trivariate probability distributions of parameters , and were constructed using Gaussian and copulas. The proposed trivariate copula is suitable for modeling the asymmetric dependence structure of vG parameters. It was demonstrated that the proposed approach can be used to construct the confidence intervals for SWCCs of bentonites. In the absence of measured data, the trivariate distribution provides a first-hand estimate of the SWCC. It also can be used as an informative prior for updating site-specific limited data using a Bayesian approach.
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International Journal of Geomechanics
Volume 20 • Issue 2 • February 2020
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©2019 American Society of Civil Engineers.
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Received: Jun 15, 2018
Accepted: Jun 12, 2019
Published online: Nov 21, 2019
Published in print: Feb 1, 2020
Discussion open until: Apr 21, 2020
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