Qualifying the Saturated Hydraulic Conductivity and Corresponding Infiltration Processes

Abstract

Many engineering systems such as the hydraulic barriers and infiltration practices are designed based on the understanding of water infiltration through the subsurface. Among the soil hydraulic properties, the saturated hydraulic conductivity Ks is the most important parameter that controls the water seepage processes through the soil profile. Clay-sand mixtures that have low Ks values are often used to construct hydraulic barriers. Several empirical models are available in the literature that can be used to predict reductions in Ks value of coarse sand due to the presence of clay and other fine minerals. However, all these models require measurements of multiple physical properties of the porous media. The resulting empirical expressions have several parameters that need to be individually evaluated using multiple soil characterization tests. In this study, a single parameter model was proposed and used to capture the variations in Ks value of different types of porous media mixtures using a scalable modeling framework. Several laboratory tests were conducted to measure Ks values of a variety of coarse and fine mixtures using synthetic porous media, natural clay-sand mixtures, and also using multiple literature-derived datasets to test the validity of the proposed model. Infiltration practices are designed to have a high Ks value to enhance water infiltration into the underlying soil. During the construction and operational period, the hydraulic properties of the system have to be carefully measured at multiple locations and at multiple suction conditions. A technique that is inexpensive, easy to use, and requires a minimal amount of water to estimate the in situ Κs and the Green–Ampt suction head Ψ at the wetting front is the Modified Philip–Dunne Infiltrometer (MPDI). In this study, a novel forward modeling algorithm was developed and used to investigate the performance of the MPDI. The forward model was used to simulate water level changes inside the infiltrometer with time when the soil hydraulic properties Κs and Ψ are known. The model was used to generate 30,000 water level datasets using randomly generated values of Κs and Ψ values. These data were then compared against field-measured drawdown data collected for three types of soil. The Nash–Sutcliffe efficiency (NSE) was used to assess the quality of the fit. Results show that multiple sets of the model parameters Κs and Ψ can yield drawdown curves that can fit the field-measured data equally well. Interestingly, all the successful sets of parameters (delineated by NSE ≥ the threshold value) give Κs values that converged to a valid range that is fully consistent with the tested soil texture class. However, the Ψ values varied significantly and did not converge to a valid range. Based on these results, we conclude that the MPDI is a useful field method to estimate Κs values, but it is not a robust method to estimate Ψ values. The effect of the initial soil moisture content θin on the drawdown data measured using the MPDI and consequently on the estimated Κs and Ψ values were also investigated. Several laboratory tests were conducted using three types of porous media. Results show that the drawdown curve is different for each soil under varying θin. The estimated Κs values of every soil varied with θin, and the variation in Κs, however, could be minimized using a correction factor that is related to θin The estimated Ψ values in all the experiments did not correctly reflect the changes in soil texture classes and soil moisture content.