Saturated hydraulic conductivity model computed from bimodal water retention curves for a range of New Zealand soils

• Main Authors: J. A. P. Pollacco, T. Webb, S. McNeill, W. Hu, S. Carrick, A. Hewitt, L. Lilburne
• Format: Article
• Language: English
• Published: Copernicus Publications 2017-06-01
• Series: Hydrology and Earth System Sciences
• Online Access: http://www.hydrol-earth-syst-sci.net/21/2725/2017/hess-21-2725-2017.pdf
• ISSN: 1027-5606; 1607-7938

Descriptions of soil hydraulic properties, such as the soil moisture retention curve, <i>θ</i>(<i>h</i>), and saturated hydraulic conductivities, <i>K</i>_s, are a prerequisite for hydrological models. Since the measurement of <i>K</i>_s is expensive, it is frequently derived from statistical pedotransfer functions (PTFs). Because it is usually more difficult to describe <i>K</i>_s than <i>θ</i>(<i>h</i>) from pedotransfer functions, Pollacco et al. (2013) developed a physical unimodal model to compute <i>K</i>_s solely from hydraulic parameters derived from the Kosugi <i>θ</i>(<i>h</i>). This unimodal <i>K</i>_s model, which is based on a unimodal Kosugi soil pore-size distribution, was developed by combining the approach of Hagen&ndash;Poiseuille with Darcy's law and by introducing three tortuosity parameters. We report here on (1) the suitability of the Pollacco unimodal <i>K</i>_s model to predict <i>K</i>_s for a range of New Zealand soils from the New Zealand soil database (S-map) and (2) further adaptations to this model to adapt it to dual-porosity structured soils by computing the soil water flux through a continuous function of an improved bimodal pore-size distribution. The improved bimodal <i>K</i>_s model was tested with a New Zealand data set derived from historical measurements of <i>K</i>_s and <i>θ</i>(<i>h</i>) for a range of soils derived from sandstone and siltstone. The <i>K</i>_s data were collected using a small core size of 10 cm diameter, causing large uncertainty in replicate measurements. Predictions of <i>K</i>_s were further improved by distinguishing topsoils from subsoil. Nevertheless, as expected, stratifying the data with soil texture only slightly improved the predictions of the physical <i>K</i>_s models because the <i>K</i>_s model is based on pore-size distribution and the calibrated parameters were obtained within the physically feasible range. The improvements made to the unimodal <i>K</i>_s model by using the new bimodal <i>K</i>_s model are modest when compared to the unimodal model, which is explained by the poor accuracy of measured total porosity. Nevertheless, the new bimodal model provides an acceptable fit to the observed data. The study highlights the importance of improving <i>K</i>_s measurements with larger cores.