Physical pedotransfer functions to compute saturated hydraulic conductivity from bimodal characteristic curves for a range of New Zealand soils

Abstract. Descriptions of soil hydraulic properties, such as soil moisture release curve, θ(h), and saturated hydraulic conductivities, Ks, are a prerequisite for hydrological models. Since the measurement of Ks is expensive, it is frequently derived from pedotransfer functions. Because it is usually more difficult to describe Ks than θ(h) from pedotransfer functions, Pollacco et al. (2013) developed a physical unimodal model to compute Ks solely from hydraulic parameters derived from the Kosugi θ(h). This unimodal Ks model, which is based on a unimodal Kosugi soil pore-size distribution, was developed by combining the approach of Hagen-Poiseuille with Darcy’s law and by introducing three tortuosity parameters. We report here on (1) the suitability of the Pollacco unimodal Ks model to predict Ks for a range of New Zealand soils, and (2) further adaptations to this model to adapt it to dual-porosity structural soils by computing the soil water flux through a continuous function of an improved bimodal pore-size distribution. The improved bimodal Ks model was tested with a New Zealand data set derived from historical measurements of Ks and θ(h) for a range of soils derived from sandstone and siltstone. The Ks data were collected using a small core size of 100 mm, causing large uncertainty in replicate measurements. Predictions of Ks 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 Ks models because the Ks model is based on pore-size distribution and the calibrated parameters were obtained within the physically feasible range. The improvements made to the unimodal Ks model by using the new bimodal Ks 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 Ks measurements with larger cores.