LAUSR

ABSTRACT Apparent diffusion constants in soil are generally estimated by dividing molecular diffusion coefficient for a solute with soil tortuosity (&tgr;) values. Several models have been proposed to estimate &tgr; from soil porosity (ϕ) alone, but most of these models fail when the variability in observed &tgr;-ϕ pairs increases. Pedotransfer functions can be used to predict &tgr; from easy-to-measure soil properties such soil texture, organic carbon contents, and ϕ, but such an approach requires more measurements to be performed than just measuring ϕ. Here, we show that &tgr; may be estimated from ϕ alone using the ensemble averaging approach. We examined seven different analytical expressions for &tgr;-ϕ and seven different ensemble-modeling approaches to estimate &tgr; for 100 pairs of &tgr;-ϕ collected from a wide geographical area. Modeling results showed that the Bayesian model averaging method was the best ensemble-modeling approach for estimating &tgr; from ϕ. Of 119 different combinations of &tgr; (ϕ) models, three models derived considering (1) packing of square-shaped particles, (2) fractal geometry with particles of different sizes, and (3) percolation theory were identified as the best individual models for ensemble modeling. The coefficient of determination (0.67), root-mean-squared error (0.23), and the Akaike information criterion (94.37) values for this ensemble model were better than those when a single model was used for prediction. Inclusion of these three models that are based on both fractal and regular geometrical shapes for particles of different sizes may be a reason for improved performance of the ensemble approach. These results suggest that &tgr; may be estimated from ϕ using the ensemble approach without the need for additional soil data, as is done in a pedotransfer function approach.