Scaling the Dependency of Soil Penetration Resistance on Water Content and Bulk Density of Different Soils

• Published in: Soil Science Society of America journal Vol. 77; no. 5; pp. 1488 - 1495
• Main Authors: Vaz, Carlos M. P., Manieri, Juliana M., Maria, Isabella C., Th. van Genuchten, Martinus
• Format: Journal Article
• Language: English
• Published: Madison The Soil Science Society of America, Inc 01.09.2013; American Society of Agronomy
• Subjects: Bulk density; Crop management; Experiments; Mathematical analysis; Mineralogy; Moisture content; Organic matter; Parametrization; Penetration; Penetrometers; Rainy season; Sand & gravel; Soil (material); Soil compaction; Soil profiles; Soil properties; Soil texture; Soil types; Soil water; Soils; Surface layer; Texture; Water content
• ISSN: 0361-5995; 1435-0661
• DOI: 10.2136/sssaj2013.01.0016

Although soil cone penetrometers have been used for decades to assess soil mechanical strength and evaluate soil compaction, the strong dependency of the penetration resistance (PR) on soil water content and soil type makes it difficult to compare field data that vary in space and time because of soil spatial variability, variable weather conditions, and implementation of varying soil and crop management practices. In this study we introduce and evaluate a procedure to normalize and scale PR data measured with a dynamic soil cone penetrometer in six Brazilian soil profiles having different soil textures. Data covered a wide range of water contents taken during both dry and wet seasons. Correlations between PR and measured volumetric water content (θv) and bulk density (ρb) data often display exponential type relationships that are known to depend on such soil properties as texture, mineralogy, and organic matter (OM) content. However, expressing θv and ρb as a function of scaled water contents and bulk densities significant reduced the influence of soil type and allowed a parameterization independent of soil texture. The obtained regression equation produced much lower root mean square deviation (RMSD) values for our dataset as compared to previously published equations for PR using pedotransfer function approaches. The proposed scaling approach seems very promising and should be tested and expanded to other classes of soils and databases.