Evaluation and development of hydraulic conductivity pedotransfer functions for Australian soil Budiman Minasny A and Alex. B. McBratney A Department of Agricultural Chemistry and Soil Science, Ross St Building A03, The University of Sydney, NSW 2006, Australia. B Corresponding author; e-mail: budiman@acss.usyd.edu.au Abstract Pedotransfer functions (PTFs) for predicting saturated hydraulic conductivity (K s ) were evaluated using published Australian soil data sets. Eight published PTFs were evaluated. Generally, published PTFs provide a satisfactory estimation of K s depending on the spatial scale and accuracy of prediction. Several PTFs were developed in this study, including the power function of effective porosity, multiple linear regression, fractal model, and artificial neural networks. Different methods for estimating the fractal dimension of particle-size distributions showed no significant differences in predicting K s . The simplest model for estimating fractal dimension from the log–log plot of particle-size distribution is therefore recommended. The data set was also stratified into 3 broad classes of texture: sandy, loamy, and clayey. Stratification of PTFs based on textural class showed small improvements in estimation. The published PTF of Dane and Puckett (1994) Proc. Int. Workshop (Univ. of California: Riverside, CA) gives the best prediction for sandy soil; the PTF of Cosby et al. (1984) Water Resources Research 20, 682–90 gives the best production for loamy soil; and the PTF of Schaap et al. (1998) Soil Science Society of America Journal 62, 847–55 gives the best prediction for clayey soil. The data set used comprised different field and laboratory measurements over large areas, and limited predictive variables were available. The PTFs developed here may predict adequately in large areas (residuals = 10–20 mm/h), but for site-specific applications, local calibration is needed. Additional keywords: permeability, fractal dimensions, saturated zone, neural networks. Introduction Saturated hydraulic conductivity (K s ) is an important physical factor determining water and solute transport in soil. Knowledge of K s is useful in managing irrigation and drainage problems and in environmental planning. Measurement of K s can be done in the field or laboratory. In the field, the disc permeameter has been used extensively for measuring saturated and near-saturated hydraulic conductivity (K). However, K s is rarely measured in routine soil survey because it is time consuming and can be expensive. The databases containing measured K s values from Australian soil are also very limited. Only a few published databases include this measurement; for example, Forrest et al. (1985) measured K s in the laboratory from undisturbed core samples; Geeves et al. (1995) measured near-saturated K in the field using the disc permeameter and predicted K s from the Mualem–van Genuchten model (van Genuchten 1980). Furthermore, only a few published Australian papers have reported measurements of unsaturated hydraulic conductivity (Rose et al. 1965; Olsson and Rose 1978). Because of the widespread need for K s values to evaluate agricultural and environmental processes, the use of indirect methods to predict them has been proposed Aust. J. Soil Res., 2000, 38, 905–26 10.1071/SR99110 0004-9573/00/040905 © CSIRO 2000