2023 journal article
An Unsaturated Hydraulic Conductivity Model Based on the Capillary Bundle Model, the Brooks-Corey Model and Waxman-Smits Model
WATER RESOURCES RESEARCH, 59(6).
AbstractSoil unsaturated hydraulic conductivity (K), which depends on water content (θ) and matric potential (ψ), exhibits a high degree of variability at the field scale. Here we first develop a theoretical hydraulic‐electrical conductivity (σ) relationship under low and high salinity cases based on the capillary bundle model and Waxman and Smits model which can account for the non‐linear behavior of σ at low salinities. Then the K‐σ relationship is converted into a K(θ, ψ) model using the Brooks‐Corey model. The model includes two parameters c and γ. Parameter c accounts for the variation of the term (λ + 2)/(λ + 4) where λ is the pore size distribution parameter in the Brooks‐Corey model, and the term m‐n where m and n are Archie's saturation and cementation exponents, respectively. Parameter γ is the sum of the tortuosity factor accounting for the differences between hydraulic and electrical tortuosity and Archie's saturation exponent. Based on a calibration data set of 150 soils selected from the UNSODA database, the best fitting log(c) and γ values were determined as −2.53 and 1.92, −4.39 and −0.14, −5.01 and −1.34, and −5.79 and −2.27 for four textural groups. The estimated log10(K) values with the new K(θ, ψ) model compared well to the measured values from an independent data set of 49 soils selected from the UNSODA database, with mean error (ME), relative error (RE), root mean square error (RMSE) and coefficient of determination (R2) values of 0.02, 8.8%, 0.80 and 0.73, respectively. A second test of the new K(θ, ψ) model using a data set representing 23 soils reported in the literature also showed good agreement between estimated and measured log10(K) values with ME of −0.01, RE of 9.5%, RMSE of 0.77 and R2 of 0.85. The new K(θ, ψ) model outperformed the Mualem‐van Genuchten model and two recently published pedo‐transfer functions. The new K(θ, ψ) model can be applied for estimating K under field conditions and for hydrologic modeling without need for soil water retention curve data fitting to derive a K function.