Abstract
The particle-size distribution (PSD) is the key information required by several models for prediction of the soil-water characteristic curve (SWCC). The performance of these models has been extensively investigated in the literature; however, limited studies have been undertaken with respect to the uncertainty associated with the SWCC predictions resulting from the variability in the PSD. This study aims to investigate the influence of the variability of the PSD in the prediction of SWCCs using five different models applied to three different glass beads (GBs). The PSD curves were determined by sieve analysis, laser diffraction, and image analysis. The various testing procedures were statistically evaluated to understand the influence of variability of the PSD in terms of the coefficient of uniformity (CU) and de size of particles corresponding to 10% in the PSD (D10). For each prediction model, a combination of PSD curves and their coefficient of variation were used to estimate the SWCCs. Both theCUandD10proved to have a strong relationship with the predicted SWCCs. TheCUappears to influence more the residual suction prediction while theD10seems to have a major role for the transition and residual stages.
Highlights
There are many models available in the literature to predict or estimate the soil-water characteristic curve (SWCC) such as the Arya & Paris (1981) [1]; Haverkamp & Parlange (1986) [2]; Fredlund & Xing (1994) [3]; Fredlund et al (2002) [4]; Aubertin el al. (2003) [5]; Tuller & Or (2005) [6]; Jaafar & Likos (2011) [7]; Wang et al (2017) [8] and Alves et al (2020) [9]. Several of these models attempt to establish a correlation between their input variables and geotechnical parameters, which include the particle-size distribution (PSD), void ratio, organic matter content, dry density, specific gravity, coefficient of uniformity, liquid limit, and specific surface area
To avoid bias in the manner how the PSDs are used, compared, and combined, only two parameters of the PSD curve were analyzed, namely: D10 and coefficient of uniformity (CU). These two attributes were selected for the following reasons: i) CU (D60/D10) is used as an input variable for the models of Aubertin et al (2003) [5] and Wang et al (2017) [8]; ii) the importance of finer particles represented by D10 for the matric suction is wellrecognized (Lane & Washburn 1946 [35], Peck et al 1974 [36], Aubertin et al 2003 [5], Torres 2011 [37], Wang et al 2017 [8])
The difference between the results are higher for glass beads (GBs) #3
Summary
There are many models available in the literature to predict or estimate the soil-water characteristic curve (SWCC) such as the Arya & Paris (1981) [1]; Haverkamp & Parlange (1986) [2]; Fredlund & Xing (1994) [3]; Fredlund et al (2002) [4]; Aubertin el al. (2003) [5]; Tuller & Or (2005) [6]; Jaafar & Likos (2011) [7]; Wang et al (2017) [8] and Alves et al (2020) [9]. The presence of organic matter influences the interaction forces mainly for the fine fractions (Gupta & Larson 1979 [15], Jong et al 1983 [16], Liu et al 2014 [17]). Considering that these aspects act simultaneously to determine the soil suction, it is clear the difficulty involved in predicting the SWCC
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