Evaluation of models for description of wet aggregate size distribution from soils of different land uses

Abstract

A proper description of aggregate size distribution (ASD) with an optimum mathematical model would be useful in modeling and monitoring land use effect. The objective of this study was to evaluate the suitability of six cumulative distribution models, namely, Jaky, normal, log-normal, Rosin-Rammler, Fredlund and a mass-based fractal model with wet aggregate size distribution (WASD) data sets from a given range of soil structural properties. The models were tested on wet sieving data of samples that had been collected from a number of different land use types (dry farmland, rangeland and forestland). Three statistical criteria, namely, coefficient of determination (R2), Mallows statistics (Cp), and Akaike’s information criterion (AIC), were used for evaluating model performance, based on the least sum of square error and number of fitting parameters. Analysis of R2 showed that the Fredlund three-parameter model showed the best performance in all of the soils apart from the number of parameters. The log-normal model gave a good fit on WASD from rangeland and forestland; it was the best especially in dry farmland. The normal model provided a good description of WASD from the rangeland and forest. However, it failed in dry farmland. According to Cp and AIC as the evaluation criteria, the fractal model was the optimum to describe WASD for all of the land uses. The Fredlund, log-normal, Jaky and Rosin-Rammler models ranked next in the given order.