Estimating particle-size distribution from limited soil texture data: Introducing two new methods. (April 2022)

• Record Type: Journal Article
• Authors: Mozaffari, Hasan; Moosavi, Ali Akbar; Dematte, Jose A.M.
• Is Part Of: Biosystems engineering. Volume 216(2022)
• Page Start: 198
• Page End: 217
• Publication Date: 2022-04
• Subjects: Clay -- Sand -- Silt -- Soil texture class -- Soil texture triangle -- Very coarse sand; Bioengineering -- Periodicals; Agricultural engineering -- Periodicals; Biological systems -- Periodicals; Génie rural -- Périodiques; Systèmes biologiques -- Périodiques; 631
• DOI: 10.1016/j.biosystemseng.2022.02.007
• Languages: English
• ISSNs: 1537-5110

Abstract

Abstract : Most soil databases present the mass fractions of sand, silt, and clay particles without detailed primary particle-size distribution (PSD). In the present paper two simple methods are introduced to estimate the PSD using the fractions of sand, silt, clay, and very coarse sand. A total of 504 soil samples with different texture classes from different regions, i.e., southern Iran (245), south-eastern Brazil (116), and UNSODA database (143) were used. PSD of the Iranian and Brazilian soil samples were determined using a combination of wet-sieving and sedimentation (hydrometer for Iranian and pipette for Brazilian soils) approaches and that of the others extracted from UNSODA database. We developed two new methods including very coarse sand-dependent (VCS-D) and very coarse sand-independent (VCS–I) to predict PSD of the soils. PSD were also predicted using the revised Skaggs method (R-Skaggs) and compared with the measured ones. Both VCS-D and VCS-I approaches with very simple equations accurately estimated full range of PSD in a wide range of the fine to medium textured soils)clay, clay loam, loam, silty clay, silty clay loam, silt loam, and silt texture classes). Accuracy of predictions was slightly lower in coarse textured soils (sandy clay, sandy clay loam, sandy loam, loamy sand, and sand textures) than that of the other texture classes. For these coarse textured soils, it is strongly recommended that the fraction of particles between 0.05 and 2 mm diameters be estimated using the VCS-D or VCS-I methods and the fraction of particles between 0.002 and 0.05 mm diameters be estimated using the R-Skaggs method. The R-Skaggs method could only predict the PSD in the soils with nearly 25–60% sand content, accurately. Whereas, the new proposed methods could predict full range of PSD with high accuracy (NRMSE <10%) in soils with sand content less than 53%. Overall, the proposed methods could accurately predict full range of PSD curve by using only the content of primary soil particles in nearly 73% of soil classes in texture triangle. Highlights: New methods (VCS-D and VCS-I) proposed to estimate particle-size distribution (PSD). The methods are very simple and accurate to estimate PSD from limited texture data. The methods are very accurate to estimate PSD in 73% of soil texture triangle. The methods excellently estimate PSD in fine and medium textured soils. The methods were more accurate than R-Skaggs in fine and medium textured soils.