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

Marian Schönauer,Joachim Maack,Dirk Jaeger,Stephan Hoffmann,Martin Jansen

doi:10.3390/f12020113

Abstract

Timber harvesting operations using heavy forest machinery frequently results in severe soil compaction and displacement, threatening sustainable forest management. An accurate prediction of trafficability, considering actual operating conditions, minimizes these impacts and can be facilitated by various predictive tools. Within this study, we validated the accuracy of four terramechanical parameters, including Cone Index (MPa, Penetrologger), penetration depth (cm, Penetrologger), cone penetration (cm blow−1, dual-mass dynamic cone penetrometer) and shear strength (kPa, vane meter), and additionally two cartographic indices (topographic wetness index and depth-to-water). Measurements applying the four terramechanical approaches were performed at 47 transects along newly assigned machine operating trails in two broadleaved dominated mixed stands. After the CTL thinning operation was completed, measurement results and cartographic indices were correlated against rut depth. Under the rather dry soil conditions (29 ± 9 vol%), total rut depth ranged between 2.2 and 11.6 cm, and was clearly predicted by rut depth after a single pass of the harvester, which was used for further validations. The results indicated the easy-to-measure penetration depth as the most accurate approach to predict rut depth, considering coefficients of correlation (rP = 0.44). Moreover, cone penetration (rP = 0.34) provided reliable results. Surprisingly, no response between rut depth and Cone Index was observed, although it is commonly used to assess trafficability. The relatively low moisture conditions probably inhibited a correlation between rutting and moisture content. Consistently, cartographic indices could not be used to predict rutting. Rut depth after the harvester pass was a reliable predictor for total rut depth after 2–5 passes (rP = 0.50). Rarely used parameters, such as cone penetration or shear strength, outcompeted the highly reputed Cone Index, emphasizing further investigations of applied tools.

Highlights

IntroductionThe forest in Germany and other countries suffer from several climate change-induced stressors like drought, fires and other extreme weather conditions [1,2]
The results give clear evidence that rut depth caused by the first machine pass of the harvester remains a reliable indicator of further rut formation through up to four consecutive machine passes in current site conditions, and should be cautiously monitored during the felling
The auspicious remote sensing-based cartographic indices DTW and topographic wetness index (TWI) seem promising towards an operational usage, presuming a high accuracy of rut prediction

Summary

Introduction

The forest in Germany and other countries suffer from several climate change-induced stressors like drought, fires and other extreme weather conditions [1,2]. One consequence of these weather phenomena is an ongoing large scale bark beetle infestation [3]. The required machine-operating trails for off-road traffic still have to be established to ensure the necessary year-round access to the affected stands. Negative impacts like compaction (e.g., [13]) and soil displacement (e.g., [14]) are the consequence of heavy machine traffic on forest soils.

Methods

Results

Conclusion