open access publication

Article, 2023

An empirical model for prediction of topsoil deformation in field traffic

In: Soil and Tillage Research, ISSN 1879-3444, 0167-1987, Volume 227, Page 105589, 10.1016/j.still.2022.105589

Contributors (1)

Schjønning, Per (0000-0002-9362-1003) [1]

Affiliations

  1. [1] Aarhus University
  2. [NORA names: AU Aarhus University; University; Denmark; Europe, EU; Nordic; OECD]

Abstract

Agricultural topsoils are characterized by a heterogeneous mixture of structural units with a considerable difference in soil mechanical properties. Mechanistic modeling of compaction for this layer is challenging because of the need to parameterize model input parameters. This study quantified soil deformation during loading in semi-confined conditions and searched for drivers decisive for observed strains with no a priori assumptions of material properties. Undisturbed soil samples were collected in the plough layer of eleven sandy and loamy soils in Denmark. The samples were adjusted to either of the following matric potentials: − 30, − 50, − 75, − 100, − 160 and − 300 hPa (pF from ∼1.5 to ∼2.5). Cores at each water condition were loaded with an annulus covering one third of the soil surface at either of the following normal loads: 30, 60, 90, 120, 150, 180 kPa. Multiple regression was performed to estimate the best model describing the variation in soil compressibility. Measured strain, ε, decreased with increase in soil organic matter, bulk density and pF, but the effect of pF was affected by soil clay content. The model explained ∼84 % of the variation in data and predicted well measured strain for two independent data sets. The regression model is suggested for prediction of soil deformation of arable topsoils in field traffic. A procedure is described for the prediction, including calculation of the relevant stress based on loading characteristics.

Keywords

Denmark, PF, agricultural topsoils, annulus, arable topsoil, assumption, best model, bulk density, calculations, characteristics, clay content, compaction, compressibility, conditions, considerable differences, content, core, data, data sets, deformation, density, differences, drivers, effect, empirical model, field traffic, heterogeneous mixture, increase, independent data sets, input parameters, layer, load, loading, material properties, matric potential, matter, mechanical properties, mechanistic modeling, mixture, model, model input parameters, modeling, multiple regression, need, normal load, observed strain, organic matter, parameters, plow layer, potential, prediction, procedure, properties, regression, regression models, relevant stresses, samples, semi-confined conditions, set, soil clay content, soil compressibility, soil deformation, soil mechanical properties, soil organic matter, soil samples, soil surface, strains, stress, structural units, study, surface, third, topsoil, traffic, undisturbed soil samples, units, variation, water conditions

Funders

  • European Commission