Probabilistic Analysis of Soil-Water Characteristic Curves
Publication: Journal of Geotechnical and Geoenvironmental Engineering
Volume 136, Issue 3
Abstract
Direct measurement of the soil-water characteristic curve (SWCC) is costly and time consuming. A first-order estimate from statistical generalization of experimental data belonging to soils with similar textural and structural properties is useful. A simple approach is to fit the data with a nonlinear function and to construct an appropriate probability model of the curve-fitting parameters. This approach is illustrated using sandy clay loam, loam, loamy sand, clay, and silty clay data in Unsaturated Soil Database. This paper demonstrates that a lognormal random vector is suitable to model the curve-fitting parameters of the SWCC. Other probability models using normal, gamma, Johnson, and other distributions do not provide better fit than the proposed lognormal model. The engineering impact of adopting a probabilistic SWCC is briefly discussed by studying the uncertainty of unsaturated shear strength due to the uncertainty of SWCC.
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Information
Published In
Journal of Geotechnical and Geoenvironmental Engineering
Volume 136 • Issue 3 • March 2010
Pages: 445 - 455
Copyright
© 2010 ASCE.
History
Received: Feb 3, 2008
Accepted: Aug 18, 2009
Published online: Feb 12, 2010
Published in print: Mar 2010
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