A database of saturated hydraulic conductivity of fine-grained soils: probability density functions

ABSTRACT

Saturated hydraulic conductivity is a key soil mechanics parameter which has widespread use in many geotechnical applications. In order to set up stochastic analyses, geotechnical modellers require databases to calibrate the parameter ranges and distributions employed. This letter uses a recently compiled database of saturated hydraulic conductivity measurements called FG/KSAT-1358 and reports on the fitting of various probability density functions to the data of void ratio, liquid limit, water content ratio and the negative natural logarithm of k_sat. It is shown that the best fit distribution is the lognormal for void ratio, while the loglogistic distribution is most favoured for liquid limit and water content ratio, and the best fit distribution for -ln[k_sat(m/s)] is the logistic function. The data of -ln[k_sat(m/s)] is then subdivided according to liquid limit level, silt or clay classification, type of hydraulic conductivity test used and sample preparation/condition. When some subdivisions of the database are analysed, the best fit distribution is more variable with GEV and logistic being the most favoured for most of the studied subsets.

KEYWORDS:

• Saturated hydraulic conductivity
• probability density functions
• Akaike information criterion
• corrected Akaike information criterion

Acknowledgments

The authors thank Dr Flavia De Luca for her helpful comments and suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

This research has not generated new experimental data.

ORCID

Shuyin Feng http://orcid.org/0000-0002-3837-6762

Paul J. Vardanega http://orcid.org/0000-0001-7177-7851

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Additional information

Funding

The first author acknowledges the support from the China Scholarship Council (CSC) under the [grant number CSC No. 201708060067].