A database of saturated hydraulic conductivity of fine-grained soils: probability density functions. Issue 4 (2nd October 2019)

• Record Type: Journal Article
• Authors: Feng, Shuyin; Vardanega, Paul J.
• Is Part Of: Georisk. Volume 13:Issue 4(2019)
• Page Start: 255
• Page End: 261
• Publication Date: 2019-10-02
• Subjects: Saturated hydraulic conductivity -- probability density functions -- Akaike information criterion -- corrected Akaike information criterion; Environmental risk assessment -- Periodicals; Hazardous geographic environments -- Risk assessment -- Periodicals; Reliability (Engineering) -- Periodicals; Risk management -- Periodicals; 624.151
• DOI: 10.1080/17499518.2019.1652919
• Languages: English
• ISSNs: 1749-9518

Abstract

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 ksat . 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[ ksat (m/s)] is the logistic function. The data of -ln[ ksat (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.