Predicting the pressure–sinkage characteristics of two forest sites in Ireland using in situ soil mechanical properties

• Published in: Biosystems engineering Vol. 97; no. 2; pp. 267 - 281
• Main Authors: Zeleke, G., Owende, P.M.O., Kanali, C.L., Ward, S.M.
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01-06-2007; Elsevier
• Subjects: Agricultural machinery and engineering; Agronomy. Soil science and plant productions; Biological and medical sciences; equations; forest soils; Fundamental and applied biological sciences. Psychology; Generalities. Biometrics, experimentation. Remote sensing; mathematical models; mechanical properties; modulus of elasticity; peat soils; soil compaction; soil physical properties; Ireland; Europe; Western Europe; Site; Bioengineering; Forests; In situ; Prediction; Property of soil; Mechanical properties; Physical properties; Temperate zone; Pressure; Engineering; Characteristics; Agriculture
• ISSN: 1537-5110; 1537-5129
• DOI: 10.1016/j.biosystemseng.2007.03.007

The mechanical properties of two forest soils in Ireland were determined in order to model the pressure−sinkage characteristics of the forest floor. The stiffness values of the surface mat and the underlying weak peat substrata, and Young's modulus were determined from
in situ load–sinkage experimental data obtained from the sites. The measured mean values of stiffness of surface mat (underlying peat soil) were found to vary between 368 and 1634 (1028 and 4320
kN/m
3). The measured mean value of Young's modulus of the forest floor was found to vary between 427 and 718
kN/m
2. A non–linear model that predicted the pressure–sinkage characteristics of the forest floor, with less than 19% error, was developed. Application of the non-linear model for prediction of potential site damage by timber harvesting and extraction machinery traffic was exemplified. Such application of the model has an advantage in that it only requires Young's modulus of the soil and harvesting machine configuration to be known.