Abstract
Root systems of trees reinforce the underlying soil in hillslope environments and therefore potentially increase slope stability. So far, the influence of root systems is disregarded in Geographic Information System (GIS) models that calculate slope stability along distinct failure plane. In this study, we analyse the impact of different root system compositions and densities on slope stability conditions computed by a GIS-based slip surface model. We apply the 2.5D slip surface model r.slope.stability to 23 root system scenarios imposed on pyramidoid-shaped elements of a generic landscape. Shallow, taproot and mixed root systems are approximated by paraboloids and different stand and patch densities are considered. The slope failure probability (Pf) is derived for each raster cell of the generic landscape, considering the reinforcement through root cohesion. Average and standard deviation of Pf are analysed for each scenario. As expected, the r.slope.stability yields the highest values of Pf for the scenario without roots. In contrast, homogeneous stands with taproot or mixed root systems yield the lowest values of Pf. Pf generally decreases with increasing stand density, whereby stand density appears to exert a more pronounced influence on Pf than patch density. For patchy stands, Pf increases with a decreasing size of the tested slip surfaces. The patterns yielded by the computational experiments are largely in line with the results of previous studies. This approach provides an innovative and simple strategy to approximate the additional cohesion supplied by root systems and thereby considers various compositions of forest stands in 2.5D slip surface models. Our findings will be useful for developing strategies towards appropriately parameterising root reinforcement in real-world slope stability modelling campaigns.
Highlights
As a slope-forming process, landslides depict a natural part of landscape evolution that can be triggered by various agents, mainly rainfall and earthquakes (Glade et al 2005)
An increase in the slip surface size generally results (i) in blurred patterns (Fig. 5) and (ii) in lower values of Pf. (i) is explained by the increasing area covered by each individual—and the most critical—slip surface. (ii) is related to the fact that smaller slip surfaces are more likely to squeeze in the spaces between the individual root systems, and escape the influence of root cohesion
To explore the potential of root system morphology implementation in a 2.5D slip surface model and its impact on the model performance, we used a set of idealised root systems as input for the computational tool r.slope.stability
Summary
As a slope-forming process, landslides depict a natural part of landscape evolution that can be triggered by various agents, mainly rainfall and earthquakes (Glade et al 2005). The size, shape, intensity and predisposition of the triggered landslides, are mainly determined by (un)certain environmental factors, such as slope geometry, composition of the soil or regolith and the vegetation cover (Guzzetti et al 1999; Glade et al 2005; Reichenbach et al 2014). The susceptibility of a landscape to be affected by landslides is highly associated to the spatio-temporal change of the forest cover (Papathoma-Köhle et al 2013; Promper et al 2014). A dimensionless Factor of Safety (FoS) is calculated that measures the relation between the resisting forces (R) and the driving forces (T) that stabilise or destabilise the soil package on a slope: FoS 1⁄4 R : ð1Þ
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
