ESTIMATING SOIL PARTICLE-SIZE DISTRIBUTION FOR SICILIAN SOILS
AbstractThe soil particle-size distribution (PSD) is commonly used for soil classification and for estimating soil behavior. An accurate mathematical representation of the PSD is required to estimate soil hydraulic properties and to compare texture measurements from different classification systems. The objective of this study was to evaluate the ability of the Haverkamp and Parlange (HP) and Fredlund et al. (F) PSD models to fit 243 measured PSDs from a wide range of 38 005_Bagarello(547)_33 18-11-2009 11:55 Pagina 38 soil textures in Sicily and to test the effect of the number of measured particle diameters on the fitting of the theoretical PSD. For each soil textural class, the best fitting performance, established using three statistical indices (MXE, ME, RMSE), was obtained for the F model with three fitting parameters. In particular, this model performed better in the fine-textured soils than the coarse-textured ones but a good performance (i.e., RMSE < 0.03) was detected for the majority of the investigated soil textural classes, i.e. clay, silty-clay, silty-clay-loam, silt-loam, clay-loam, loamy-sand, and loam classes. Decreasing the number of measured data pairs from 14 to eight determined a worse fitting of the theoretical distribution to the measured one. It was concluded that the F model with three fitting parameters has a wide applicability for Sicilian soils and that the comparison of different PSD investigations can be affected by the number of measured data pairs.
PlumX Metrics provide insights into the ways people interact with individual pieces of research output (articles, conference proceedings, book chapters, and many more) in the online environment. Examples include, when research is mentioned in the news or is tweeted about. Collectively known as PlumX Metrics, these metrics are divided into five categories to help make sense of the huge amounts of data involved and to enable analysis by comparing like with like.
Copyright (c) 2009 Vincenzo Bagarello, Vito Ferro, Giuseppe Giordano
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.