Abstract
The particle size distribution of solid particles (PSD) is critical in determining the potential for compaction, the availability and the redistribution of water in the soil, especially in the areas of building material and soil mechanics, among others. However, many banks of soil data does not contain detailed PSD data, but only some fractions. A mathematical accurate representation of the PSD is required to estimate soil hydraulic properties and texture comparing measurements of different classification systems. The objective of this study was to compare the performance of 12 models, with 2 and 3 tuning parameters proposed in the literature to represent the PSD, and, predict the water retention curve in the soil, from a wide range of Brazilian soils textures. The statistical parameters (NDEs, RD, MS CRM) showed three models tuning parameters proposed by Lima & Silva, Weibull and Fredlund got the best performance, with lower NDE, RD, MS very close to one and CRM values very low. The models Lima & Silva, Weibul, Fredlund and Skaggs, with three tuning parameters, and the models Skaggs end Lima & Silva, with two parameters, proved to be suitable for estimate the water retention curve in the soil, for soils with coarse and fine texture. Keywords: Granulometry; Soil texture; Curve Adjustments.
Highlights
In the literature we find several models that stand out in this order (JAKY, 1944; SHIRAZI and BOERSMA, 1984; CAMPBELL, 1985; HAVERKAMP and PARLANGE, 1986; SHIOZAWA and CAMPBELL, 1991; BUCHAN et al, 1993; NEMES et al, 1999, FREDLUND et al, 2000; among others)
The results indicated that the Fredlund models, with three four tuning parameters, achieved the best performance for most soils
For models with two tuning parameters we can classify the performance of the models into three groups
Summary
The grading distribution of soil particles (PSD) is a very important attribute for understanding the physical properties of the soil, mainly due to its strong influence on other properties related to erosion, runoff, infiltration and deep drainage.Recent studies have used the PSD to estimate various properties, such as the hydraulic conductivity and the water retention curve in the soil (SILTECHO et al, 2015), for estimating the thermal diffusivity (LIER and DURIGON, 2012) and even to compare and convert measurements texture in different classification systems (SHANGGUAN et al, 2013; SHANGGUAN et al, 2014).Conventional lifting grading analysis of the data is to determine only a limited number of soil fractions. Recent studies have used the PSD to estimate various properties, such as the hydraulic conductivity and the water retention curve in the soil (SILTECHO et al, 2015), for estimating the thermal diffusivity (LIER and DURIGON, 2012) and even to compare and convert measurements texture in different classification systems (SHANGGUAN et al, 2013; SHANGGUAN et al, 2014). To be able to use these discrete experimental data in the estimation of other soil properties, it is necessary to assume a theoretical model of the PSD, enabling a more complete description of the soil (WEIPENG et al, 2015). Even knowing that the selected model can have a significant impact on the estimates of the percentage of soil particles (NEMES et al, 1999), few comparative studies of PSD models were conducted to evaluate the adherence of the model to the data measured in loco, especially in Brazil
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