Particle size distribution models for soils of the humid tropics

• Published in: Journal of soils and sediments 2013-04, Vol.13 (4), p.686-698
• Main Authors: Botula, Yves-Dady, Cornelis, Wim M., Baert, Geert, Mafuka, Paul, Van Ranst, Eric
• Format: Article
• Language: English
• Subjects: Earth and Environmental Science; Environ Risk Assess; Environment; Environmental Physics; Mathematical models; Particle size; Sec 2 • Global Change; Soil Science & Conservation; Soil sciences; Soil texture; Soils; Sustainable Land Use • Research Article; Tropical environments
• ISSN: 1439-0108; 1614-7480
• DOI: 10.1007/s11368-012-0635-5

Purpose Standardisation of particle size distribution (PSD) is a prerequisite to achieve compatibility of soil data among various countries with different texture classification systems. Therefore, several mathematical models have been proposed to accurately represent PSD. Previous studies evaluated the performance of such models to describe PSD of soils from temperate regions. This study aims at evaluating the performance of models for describing PSD of soils from the humid tropics based on a large dataset. Materials and methods A dataset of 1,412 soils from Central Africa representing 11 different FAO Soil Groups was used. Ten PSD models with two to four fitting parameters were selected: simple log-normal (LN_2p), van Genuchten-type1 (VG_2p), van Genuchten-type2 (vG_3p), Fredlund-type1 (F_3p), Fredlund-type2 (F_4p), Weibull (W_3p), Skaggs (Sk_3p), Gompertz-type1 (G_2p), Gompertz-type2 (G_4p) and Andersson (A_4p). The fitting performance of the PSD models was evaluated by three statistical indices: the adjusted coefficient of determination, the Akaike information criterion and the relative error. Clustered columns and box plots were also used to get more insights. The predictive ability of the best PSD models was tested using a leave-one-out method and 1:1 plots. Results and discussion A table of initial values for the fitting parameters of each PSD model was provided for future applications. Some models like VG_2p, VG_3p, Sk_3p and G_4p were not suitable to describe PSD of soils in the humid tropics. On the other hand, F_3p, F_4p, W_3p and A_4p models showed outstanding fitting performance. The fitting performance of PSD models was also dependent of the textural class, the broad textural group and the bimodal character of the soil. For the most frequent textural classes in the dataset, the F_3p and A_4p models were the best closely followed by the W_3p model. While the F_3p model performed better than the A_4p model for coarse-textured soils, the opposite was observed for fine-textured soils. The W_3p model showed acceptable fitting performance for fine, medium and coarse-textured soils. The performance of the PSD models was found to be better for bimodal soils, which are common in the humid tropics, than for unimodal soils. Conclusions Great differences in fitting and prediction performance were found between the PSD models. Soil texture as well as the bimodal character of the soil significantly affect their respective performance. Some models like VG_2