Building and testing conceptual and empirical models for predicting soil bulk density

The development of pedotransfer functions offers a potential means of alleviating cost and labour burdens associated with bulk-density determinations. As a means of incorporating a priori knowledge into the model-building process, we propose a conceptual model for predicting soil bulk density from other more regularly measured properties. The model considers soil bulk density to be a function of soil mineral packing structures (rho(m)) and soil structure (Delta rho). Bulk-density maxima were found for soils with approximately 80% sand. Bulk densities were also observed to increase with depth, suggesting the influence of over-burden pressure. Residuals from the rho(m) model, hereby known as Delta rho, correlated with organic carbon. All models were trained using Australian soil data, with limits set at bulk densities between 0.7 and 1.8 g cm(-3) and containing organic carbon levels below 12%. Performance of the conceptual model (r(2) = 0.49) was found to be comparable with a multiple linear regression model (r(2) = 0.49) and outperformed models developed using an artificial neural network (r(2) = 0.47) and a regression tree (r(2) = 0.43). Further development of the conceptual model should allow the inclusion of soil morphological data to improve bulk-density predictions.