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https://doi.org/10.4296/cwrj2011-909

has been cited by the following article:

• TITLE: Relating Cone Penetration and Rutting Resistance to Variations in Forest Soil Properties and Daily Moisture Fluctuations

  AUTHORS: Marie-France Jones, Paul A. Arp

  KEYWORDS: Soil Resistance to Penetration, Cone Index, Soil Moisture, Texture, Coarse Fragments, Organic Matter, Weather Records, Hydrological Modelling, Soil Trafficability, Rutting Depth, Recreational Vehicles

  JOURNAL NAME: Open Journal of Soil Science, Vol.7 No.7, July 17, 2017

  ABSTRACT: Soil resistance to penetration and rutting depends on variations in soil texture, density and weather-affected changes in moisture content. It is therefore difficult to know when and where off-road traffic could lead to rutting-induced soil disturbances. To establish some of the empirical means needed to enable the “when” and “where” determinations, an effort was made to model the soil resistance to penetration over time for three contrasting forest locations in Fredericton, New Brunswick: a loam and a clay loam on ablation/ basal till, and a sandy loam on alluvium. Measurements were taken manually with a soil moisture probe and a cone penetrometer from spring to fall at weekly intervals. Soil moisture was measured at 7.5 cm soil depth, and modelled at 15, 30, 45 and 60 cm depth using the Forest Hydrology Model (ForHyM). Cone penetration in the form of the cone index (CI) was determined at the same depths. These determinations were not only correlated with measured soil moisture but were also affected by soil density (or pore space), texture, and coarse fragment and organic matter content (R2 = 0.54; all locations and soil depths). The resulting regression-derived CI model was used to emulate how CI would generally change at each of the three locations based on daily weather records for rain, snow, and air temperature. This was done through location-initialized and calibrated hydrological and geospatial modelling. For practical interpretation purposes, the resulting CI projections were transformed into rut-depth estimates regarding multi-pass off-road all-terrain vehicle traffic.