Abstract
Effective hydraulic conductivity (K~e~) can be estimated with statistical models derived from datasets of field measured conductivities. Pedotransfer functions (PTFs) estimate constant K~e~ values, but suffer from large prediction errors because the functions usually do not account for soil structural heterogeneities. Rainfall‐runoff data have shown that the effective hydraulic conductivity, defined as final infiltration rate at steady state given ponding, is dependent on rainfall intensity. In this study a statistical approach to establish functions for rainfall intensity‐dependent K~e~ values is presented, including some specific functions for Western European loamy agricultural soils. Steady‐state rainfall experiments have been conducted with a drip‐type rainfall simulator at multiple intensities on small plots, installed on fields covered by four typical crops of the central part of the Belgian loess belt. A mixed linear model has been applied to temperature standardized and ln‐transformed values of apparent steady‐state infiltration rate and rainfall intensity data for the determination of significant explanatory variables and their parameters. Crop type was a necessary classification effect that accounts for much of the variation that could not be explained by continuous variables of soil and surface properties. However, soil surface bulk density, silt and sand content, tortuosity in surface microtopography, plant and residue cover (RC) were predictors that improved predictions combined with crop effect. Model efficiency (ME) values were between 0·81 and 0·97 for calibration and between 0·75 and 0·95 for validation. The application of the functions is limited to sloping, loamy agricultural soils in a Western European climate, during the spring and early summer growing phase, with not fully developed canopy cover and an RC of less than 20%. These limitations bound field conditions that are vulnerable to severe erosion events. A dynamic K~e~ could be applied in infiltration models, changing runoff and erosion response in hillslope models. Copyright © 2010 John Wiley & Sons, Ltd.