Trafficability Prediction Using Depth-to-Water Maps: the Status of Application in Northern and Central European Forestry

Abstract

Purpose of Review Mechanized logging operations with ground-based equipment commonly represent European production forestry but are well-known to potentially cause soil impacts through various forms of soil disturbances, especially on wet soils with low bearing capacity. In times of changing climate, with shorter periods of frozen soils, heavy rain fall events in spring and autumn and frequent needs for salvage logging, forestry stakeholders face increasingly unfavourable conditions to conduct low-impact operations. Thus, more than ever, planning tools such as trafficability maps are required to ensure efficient forest operations at reduced environmental impact. This paper aims to describe the status quo of existence and implementation of such tools applied in forest operations across Europe. In addition, focus is given to the availability and accessibility of data relevant for such predictions. Recent Findings A commonly identified method to support the planning and execution of machine-based operations is given by the prediction of areas with low bearing capacity due to wet soil conditions. Both the topographic wetness index (TWI) and the depth-to-water algorithm (DTW) are used to identify wet areas and to produce trafficability maps, based on spatial information. Summary The required input data is commonly available among governmental institutions and in some countries already further processed to have topography-derived trafficability maps and respective enabling technologies at hand. Particularly the Nordic countries are ahead within this process and currently pave the way to further transfer static trafficability maps into dynamic ones, including additional site-specific information received from detailed forest inventories. Yet, it is hoped that a broader adoption of these information by forest managers throughout Europe will take place to enhance sustainable forest operations.

Variations of Soil Physico-Chemical and Biological Features after Logging Using Two Different Ground-Based Extraction Methods in a Beech High Forest—A Case Study

“…On the other hand, the obtained findings are not consistent with the common assertion that an advanced mechanization level leads to decreased impact on the soil. Therefore, it can be speculated that the lower impact reported in current literature for machinery specifically dedicated to forestry [14] could be related more to the correct application of specific tools to decrease soil damage that is caused by the tires of the forwarders, for instance bogie tracks [12,26]. Without such specific adjustments, the higher number of passages per volume unit needed to extract timber with the CTL system in comparison to the TLS system seems to lead to higher soil disturbance.…”

“…One of the main issues when putting SFOs into practice is limiting the impact on forest soil caused by logging [14]. Soil compaction because of forest operations that can lead to hydrological issues of increased runoff and sediment yield [15,16], including the improper development of natural regeneration with decreased seedling biomass and root length [17].…”

Use of Hydrological Models to Predict Risk for Rutting in Logging Operations

“…This strength could be applied to improve DTW maps by adjusting threshold values concerning flow initiation areas (FIA), required for mapping flow channels, or to decide proper DTW limit to distinguish wet/dry areas. A 1 ha FIA threshold value and a DTW limit of ≤ 1 m to separate wet/dry areas are currently used in DTW maps available at the Swedish Forest Agency [19]. Higher values of relative soil moisture (Rel_srfd) or relative ground water level (Rel_gwat), compared to averaged conditions over longer periods, can indicate wetter soil moisture conditions.…”

“…Various technical and planning measures are used in Swedish forestry to reduce the risk for rutting. Important planning measures include scheduling of logging to avoid sensitive sites in wet conditions and trafficability prediction models to decide where to drive and where strip trails need to be reinforced with slash [18,19]. Sites with low bearing capacity can be scheduled for harvesting in dry periods when soil moisture content and, consequently, wet areas are at minimum, or in frozen periods.…”

“…In the past decade, topography-based soil moisture models, such as depth-to-water (DTW) maps, have been used as trafficability prediction models by most Swedish forest companies [19]. The DTW maps provided by the Swedish Forest Agency are available as spatial data layers covering the entire country.…”