Soil Trafficability Forecasting

Abstract

This article introduces and evaluates a Soil Trafficability Model (STRAM) designed to estimate and forecast potential rutting depth on forest soils due to heavy machine traffic. This approach was developed within the wood-forwarding context of four harvest blocks in Northern and Central New Brunswick. Field measurements used for model calibration involved determining soil rut depths, volumetric moisture content, bulk density, soil resistance to cone penetration (referred to as cone index, or CI), and the dimensionless nominal soil cone index (NCI) defined by the ratio of CI over wheel foot print pressure. With STRAM, rut depth is inferred from: 1) machine dimensions pertaining to estimating foot print area and pressure; 2) pore-filled soil moisture content and related CI projections guided by year-round daily weather records using the Forest Hydrology Model (ForHyM); 3) accounting for within-block soil property variations using multiple and Random Forest regression techniques. Subsequent evaluations of projected soil moisture, CI and rut-depth values accounted for about 40 (multiple regression) and 80 (Random Forest) percent of the corresponding field measured values.

Comparison of Selected Terramechanical Test Procedures and Cartographic Indices to Predict Rutting Caused by Machine Traffic during a Cut-to-Length Thinning Operation

“…When the flow accumulation of a cell reaches a certain value, the very cell is defined as the starting point of a flow line, which continues the flow downhill until leaving the mapped area. The required area to start a flow line is defined as "Flow Initiation Area" and herein was set to 4 ha, as suggested by Jones and Arp [29] for likewise conditions. Subsequently, a least-cost function calculates the least slope path from each cell within the grid towards the nearest flow line [36,37].…”

“…This might have also caused the contradictory response between DTW index and observed rut H , which occurred completely independent of DTW (Figure 9A). The analyzed DTW maps, which were calculated with a flow initiation area of 4 ha [36,37], would represent a low overall moisture [29]. The created index is usually converted to a dummy variable, with a threshold of 1 m [51], where values below this threshold are assumed to predict wet and sensitive areas.…”

“…For example, Sirén et al [18,28] reported a correlation between rut depth after harvest and Cone Index (CI). The same index has been frequently used for validations of accessibility maps, where CI was used instead of assessing actual machine traffic (e.g., [29]). Less commonly used, but already reported by Heubaum et al [30], a vane meter can be used to assess soil trafficability through the determination of shear strength.…”

Impact on Soil Physical Properties Related to a High Mechanization Level in the Row Thinning of a Korean Pine Stand

“…Displacement is defined as the shift of topsoil from one location to another laterally by machine traffic, which increases the soil erosion potential [12,14]. Rutting and puddling are induced by both soil compaction and displacement [23]. Thus, excessive traffic from forest machines (e.g., harvesters, forwarders, and skidders) may induce soil disturbance in the forest stand.…”

Depth-to-Water Maps to Identify Soil Areas That Are Potentially Sensitive to Logging Disturbance: Initial Evaluations in the Mediterranean Forest Context

“…One of the most recent and interesting applications of GIS to tackle the issue of reducing soil disturbances caused by logging consists of the development of trafficability maps [16][17][18]. These maps are generally developed starting from a digital terrain model (DTM) and indicate areas that are expected to be particularly sensitive to soil compaction and therefore should be avoided by the operator who is driving the machine [19,20].…”