Probability models for SWCC and hydraulic conductivity

Abstract

Direct measurement of the soil-water characteristic curve (SWCC) and hydraulic conductivity is costly and time consuming. A first-order estimate from statistical generalization of experimental data for soils with similar texture is useful. A simple approach is to fit the soil water content data with available SWCC equation and to develop an appropriate probability model of the curve-fitting parameters. This paper demonstrates that a lognormal random vector is suitable to model the variability of SWCC parameters. When experimental data of hydraulic conductivity is not available, the probability model of hydraulic conductivity can be consistently derived from the probability model of SWCC. The derivation is based on the relation between saturated hydraulic conductivity and the saturated water content. The proposed probability models can be readily used to perform probabilistic analysis of problems involving unsaturated seepage.