In this paper, a simple and efficient fractal-based approach is presented for capturing the effects of initial void ratio on the soil-water characteristic curve (SWCC) in a deformable unsaturated soil. In terms of testing results, the SWCCs (expressed by gravimetric water content) of the unsaturated soils at different initial void ratios were found to be mainly controlled by the air-entry value (Ψ_a), while the fractal dimension (D) could be assumed to be constant. As a result, in contrast to the complexity of existing models, a simple and efficient model with only two parameters (i.e., D and Ψ_a) was established for predicting the SWCC considering the effects of initial void ratio. The procedure for determining the model parameters with clear physical meaning were then elaborated. The applicability and accuracy of the proposed model were well demonstrated by comparing its predictions with four sets of independent experimental data from the tests conducted in current work, as well as the literature on a wide range of soils, including Wuhan Clay, Hefei and Guangxi expansive soil, Saskatchewan silt, and loess. Good agreements were obtained between the experimental data and the model predictions in all of the cases considered.

Accurate determination of soil-water characteristic curve (SWCC) is of immense importance for understanding the mechanical behavior of unsaturated soils. Due to the difficulty and long duration of experimental procedures, it is of great significance to estimate the SWCC by indirect methods. To address this issue, in this article an effective fractal method is proposed for predicting the SWCC based on mercury intrusion porosimeter (MIP) data. Only two characteristic parameters, namely the fractal dimension and air-entry value, are needed in the presented approach. Detailed procedures for determining the parameters are clearly elaborated. Due to the influence of sample size difference on the equivalent connected pore size, a sample scale effect coefficient is proposed to predict air-entry values. The concept of “critical pore size” is introduced to obtain the optimal fractal dimension, which can accurately reflect the fractal behaviour of SWCC samples. By comparisons between predicted and experimental SWCCs, the validation of the proposed method is verified. The comparisons reveal the good agreement between the proposed approach and laboratory experiments.

The fitting analysis of soil‐water characteristic curve (SWCC) is the foundation of engineering properties of unsaturated soils. The purpose of this paper is to explore the differences of fitting effects between different fractal and empirical models as well as the effect of residual water content θ_r on the model fitting. The experimental SWCCs of Hunan clay at different initial dry densities are measured by pressure plate instrument, and then they are fitted by fractal and empirical models. The effect of the limit of θ_r on the fitting results is analyzed by comparing the results of indoor evaporation test. The results show that within the measured data point range, fractal model II‐2 and van Genuchten model (VG model) have the best fitting effect, fractal models I and II‐1 take the second place, and the fitting effect of Gardner model is the worst. When the matrix suction is more than the measured data, the fitting accuracy of the model is poor. For the model with θ_r, reasonable limit range of θ_r can only improve the fitting accuracy of the model to a certain extent. For the fractal model, the fitting accuracy of the model can be improved effectively when θ_r is considered. Furthermore, the difference of fractal dimension and air‐entry value in various fractal models are also discussed in this paper.

Soil water characteristic curve (SWCC) has been an important role in hydraulic engineering, civil engineer and petroleum engineering, etc. Most of SWCC models neglected the film flow in the dry state, so that they cannot accurately describe the SWCC over entire range of water content. In this work, an alternative fractal model is proposed to predict the SWCC over entire range of water content by combining Campbell and Shiozawa model and Tao model. The proposed model can well predict twelve sets of experimental data, and its parameters, including the fractal dimension, the saturated volumetric water content, the matric suction at oven-dry condition, and the air-entry value, accord with theoretical value. The results show that there is a strong linear relationship between volumetric water content and matrix suction in log-log scale for different fractal pore-size distribution of soils. In addition, good agreement is obtained between the experimental data and the model predictions in all of the cases.