Prediction of hysteretic soil and water characteristic curve of loess based on multifractal theory and improved physical statistics

Abstract

Soil and water characteristic curve (SWCC) is an important soil parameter which is used to estimate various parameters to describe unsaturated soil hydrodynamic properties. Due to the large span of soil matric suction, this procedure is time-consuming and difficult to measure it in the laboratory. However it is of great significance to find a scientifically efficient and economically viable method to predict SWCC of loess soil. Based on the measurement of soil–water characteristic curves in the laboratory, this study predicted the drying curve (DC) based on the soil particle size distribution (PSD) fractal theory. It also used the domain model to predict the wetting curve (WC) based on the pore distribution, and finally obtained the complete soil–water characteristic curve of loess. These procedures improved the research status which using the drying curve to instead of the wetting curve, and this replace usually leads to a large calculation error and underestimates the safety of the slope. The method proposed in this study can quickly obtain the hysteretic soil–water characteristic curve of loess based on only the soil particle size distribution, improve the correlative calculation accuracy of unsaturated loess, and play an important role in predicting the hydraulic parameters of loess soil.