The distribution of Van Genuchten model parameters on soil-water characteristic curves in Chinese Loess Plateau and new predicting method on unsaturated permeability coefficient of loess.

Abstract

The unsaturated permeability coefficients are often used to solve geotechnical problems associated with unsaturated soils. But it is very difficult to measure. However, the unsaturated permeability coefficients can be predicted by the Soil-water Characteristic Curves (SWCCs). The Van Genuchten Model (VG model) is very rife as it's smooth and good fitting, thus, it has the most research data. Therefore, the research data on VG model parameters (α, n, θs and θr) of Malan loess in Chinese Loess Plateau are collected in the past two decades to obtain the spatial distribution characteristics of parameters. The trend surface analysis method is employed to clarify the regional scale distribution and the variation regular pattern on ArcGIS. Then the linear regression method is utilized to fit the relationship between suction and water content in three different regions of Chinese Loess Plateau, which is divided according to the properties and particle gradation. By using this relationship and the trend surface analysis contour map, the unsaturated permeability coefficient of the sample can be predicted after measuring the saturated permeability coefficient. The example verification shows that the difference between the prediction results and the experimental results is very small when the sample has the lower saturation, and the deviation is slightly larger if it has the higher saturation, but they are all within the acceptable range. This method not only saves the test cost, but also considers the physical properties of the loess in the three different regions of the Loess Plateau. With the improvement of data and the gradual improvement of sampling density, the prediction accuracy will gradually improve. It can provide convenience for solving the engineering problems of loess and water and other engineering applications.