A simple model to predict hydraulic conductivity in medium to dry soil from the water retention curve
- TU Braunschweig, Institute of Geoecology, Soil Physics, Braunschweig, Germany (a.peters@tu-braunschweig.de)
The mathematical representation of the soil hydraulic properties is of central importance for modeling water, solute and energy transport in the vadose zone. The established models of the soil water retention and hydraulic conductivity curves account for capillary water retention and capillary conductivity, but neglect water adsorption and water flow in films and in pore corners. They are therefore suited for modeling flow and transport processes in the medium to wet moisture range, but are susceptible to failure in dry soil. The model system developed by Peters (2013, 2014) and Iden and Durner (2014) (PDI in the following) is a simple parametric framework that overcomes these structural shortcomings. However, it requires an additional parameter to scale the hydraulic conductivity curve in the medium to dry moisture range where non-capillary flow is dominant. Measured conductivity data are required to estimate this scaling parameter and to compute the hydraulic conductivity over the complete moisture range. In this contribution, we first analyze the original model formulation and show that it is in close agreement with a comprehensive physically-based model for film conductivity in porous media. We then suggest a physically based method to predict the film conductivity from the water retention curve. This reduces the number of free parameters by one and gives a complete prediction of the hydraulic conductivity curve if only water retention data and the saturated conductivity are known. Application to literature data covering a broad range of textures shows a very good agreement between measured data and predictions.
How to cite: Peters, A., Hohenbrink, T. L., Iden, S. C., and Durner, W.: A simple model to predict hydraulic conductivity in medium to dry soil from the water retention curve, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8717, https://doi.org/10.5194/egusphere-egu21-8717, 2021.