A Soil–Water Retention Model Incorporating Pore-Fluid Osmotic Potential

Abstract

The water retention characteristics of geomaterials directly influence the hydrological processes for the subsurface flow regime and surface runoff. Despite its utmost importance, most of the soil–water retention models were simply developed based on the retention data of pure water. However, natural processes, such as acidic rainfall or dissolved ions in the pore fluid and the undeniable role of industrialized pollution, result in a certain impurity in the pore water, which is reflected as an osmotic suction component. Therefore, the main goal of this study is to introduce a novel soil–water retention model that considers the role of osmotic potential. The proposed model is developed from a previous model by embedding two new parameters that have clear physical meanings. The parameters are the pore fluid salinity index (PSI) and the modified effective stress that account for the influence of the osmotic potential on the desorption rate and air entry suction, respectively. The model is benchmarked and validated against four experimental data sets that have been rigorously measured and reported by various research groups. The results reveal the robustness of the model when capturing the retention behavior of soils that are exposed to different salt concentrations and species for the matric and total suctions. The soil water retention curve (SWRC) is one of the main hydraulic features of unsaturated soils, which has been extensively used when simulating the transient multiphase flow, soil deformation, and shear strength characteristics. Due to its essence and application when solving a wide range of geoenvironmental problems, numerous models have been developed to date. However, the majority of the existing models rely on the simplifying assumption that pure water is the pore fluid, which is contradictory to the nature of several natural and human-induced phenomena, such as acidic rainfall and contamination. Therefore, the main goal of this study was to introduce a new solute-dependent fluid retention model. Then, the modeling framework was validated against comprehensive fluid retention data sets from several research groups. The new framework proved robust when predicting fluid retention as a function of the solute concentration in a simplified yet precise manner. The proposed model, which is an extended form of a previous model, is easy to implement and requires two additional parameters. In conclusion, the new model has the potential to be implemented in numerical codes, constitutive models, and analytical solutions to analyze and design certain geoenvironmental problems in the presence of contamination.