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Modelling water and solute transport through soil requires the characterisation of the soil hydraulic functions; however, determining these functions based on measurements is time-consuming and costly. Pedotransfer functions (PTFs), which make use of easily measurable soil properties to predict the hydraulic functions, have been proposed as an alternative to measurements. The better known and more widely used PTFs were developed in the USA or Europe, where large datasets exist. No specific PTFs have been published for New Zealand soils. To address this gap, we evaluated a range of published PTFs against an available dataset comprising a range of different soils from New Zealand and selected the best PTFs to construct an ensemble PTF (ePTF). Assessment (and adjustment when required) of published PTFs was done by comparing measurements and estimates of soil water content and the hydraulic conductivity at selected matric suction values. For each point, the best two or three PTFs were chosen to compose the ePTF, with correcting constants if needed. The outputs of the ePTF are the hydraulic properties at selected matric suctions, akin to obtaining measurements, thus allowing the fit of different equations as well as combining any available measurements. Testing of the ePTF showed promising performance, with reasonably accurate estimates of the water retention of an independent dataset. Root mean square error values averaged 0.06 [m.sup.3] [m.sup.-3] for various New Zealand soils, which is within the accuracy level of published PTF studies. The largest errors were found for soils with high clay content, for which the ePTF should be used with care. The performance of the ePTF for estimating soil hydraulic conductivity was not as reliable as for water content, exhibiting large scatter. Predictions of saturated hydraulic conductivity were of the same magnitude as the measurements, whereas the unsaturated values were generally under- predicted. The conductivity data available for this study were limited and highly variable. The estimates for hydraulic conductivity should therefore be used with much care, and future research should address measurements and analysis to improve the predictions. The cPTF was also used to parameterise the SWIM soil module for use in Agricultural Production Systems Simulator (APSIM) simulations. Comparisons of drainage predicted by APSIM against results from lysimeter experiments suggest that the use of the derived ePTF is suited for the estimation of soil parameters for use in modelling. The ePTF is not envisaged as a substitute for measurements but is a useful tool to complement datasets with limited amounts of measured data. Additional keywords: APSIM, drainage, hydraulic conductivity, simulation modelling, soil water content, volcanic soils., Introduction Soil hydraulic characteristics are among the most important properties for characterising physical behaviour of a soil type. Quantitative descriptions of either the characteristic points (water content values at saturation, [...]

********** Landcare in Australia is a community participatory process for encouraging land managers to collaborate in tackling existing and potential problems of land degradation. The operation of landcare is based [...]

Descriptions of soil hydraulic properties, such as the soil moisture retention 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 statistical pedotransfer functions (PTFs). 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 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 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 10 cm diameter, 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. [ABSTRACT FROM AUTHOR]