ABSTRACT Bulk density (BD) is a soil physical property used as a soil quality indicator and variations in this measurement influence soil water content and carbon stock estimates. This study aims to compile a database of samples of bulk density, textural fractions, and organic carbon values, as well as evaluate the accuracy of published pedotransfer functions (PTF) that predict bulk density, and propose a hierarchical PTF to predict the bulk density of Brazilian Soils. The performance of eleven PTFs and the newly proposed PTFs were evaluated and compared using the root mean square error (RMSE) and coefficient of determination (R2) based on a testing soil database collected from the literature. We noticed a slight improvement in accuracy when organic carbon and coarse and fine sand fractions were included as predictors alongside silt and clay. The best results with existing PTFs were obtained by PTF-A in Tomasella and Hodnett (1998) (RMSE = 0.20 g cm–3) and PTF-F in Benites et al. (2007) (RMSE = 0.17 g cm–3). Our proposed PTFs use textural fractions and organic carbon as predictors in a hierarchical form. The proposed PTF-4, which uses fine sand, coarse sand, clay, and organic carbon, presented the lowest value for RMSE (0.14 g cm–3) for BD prediction.

ABSTRACT The soil water retention curve (SWRC) is essential for vadose zone hydrological modeling and related applications. In 2004, Groenevelt and Grant (GRT) presented a mathematical model for describing the SWRC and reported its mathematical versatility and good fit to soils from a Dutch database. In order to evaluate the application of GRT to SWRCs of Brazilian soils, we aimed to analyze the performance of GRT for 72 soils from Brazil. Besides that, the obtained results with GRT for these soils were compared to the fitting performance of the most frequently used models: Brooks and Corey (BC) and van Genuchten-Mualem (VGM). The three models were fitted to available soil water retention data by minimizing the sum of square errors. The Pearson correlation coefficient (r) and the Root Mean Square Error (RMSE) were used to assess the goodness-of-fit. Results showed high correlation coefficients (r≥0.95) and small values of RMSE (RMSE ≤0.03 cm3 cm-3) for all fits. The goodness-of-fit was of similar performance for the three models with a positively correlation between them. The major difference in shape among GRT, BC, and VGM occurred in the near saturated range, while they were almost identical for low matric potentials. The exponent of GRT showed to be highly correlated with exponents of BC and VGM, but the correlation between the other shape parameters is not well defined, making a direct conversion still difficult.