Please use this identifier to cite or link to this item: https://doi.org/10.1061/(ASCE)GT.1943-5606.0000222
Title: Probabilistic analysis of soil-water characteristic curves
Authors: Phoon, K.-K. 
Santoso, A. 
Quek, S.-T. 
Keywords: Correlation
Curve fitting
Lognormal
Probability
Random vector
Soil-water characteristic curve
Translation
Unsaturated soils
Issue Date: Mar-2010
Source: Phoon, K.-K., Santoso, A., Quek, S.-T. (2010-03). Probabilistic analysis of soil-water characteristic curves. Journal of Geotechnical and Geoenvironmental Engineering 136 (3) : 445-455. ScholarBank@NUS Repository. https://doi.org/10.1061/(ASCE)GT.1943-5606.0000222
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. © 2010 ASCE.
Source Title: Journal of Geotechnical and Geoenvironmental Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/66025
ISSN: 10900241
DOI: 10.1061/(ASCE)GT.1943-5606.0000222
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