Including root reinforcement variability in a probabilistic 3D stability model.

Cislaghi A., Chiaradia E. A., Bischetti G. B.

Forests play a significant role in protecting people, settlements in mountainous terrains from hydrogeomorphic hazards, including shallow landslides. Although several studies have investigated the interactions between forests and slope instabilities, a full understanding of them has not yet been obtained. Additionally, models that incorporate forest stand properties into slope failure probability analyses have not been developed. In principle, physical‐based models, which are powerful tools for landslide hazard analyses, represent an appropriate approach to linking stand properties and slope stability. However, the reliability of these models depends on numerous parameters that describe highly complex geotechnical and hydrological processes (e.g. potential failure depth, saturation ratio, root reinforcement, etc.) that are difficult to measure and model. In particular, the spatial heterogeneity of root reinforcement remains a problem, and the use of physically based models from a forest management perspective has been limited.

This paper presents a procedure for assessing slope stability in terms of the Factor of Safety that accounts for forest stand characteristics such as tree density, average diameter at breast height and minimum distance between trees. The procedure combines a three‐dimensional (3D) slope stability model with an evaluation of the variability of root reinforcement in terms of a probability distribution, according to forest characteristics. Monte Carlo simulation is used to account for the residual uncertainties in both stand characteristics and 3D stability model parameters.

The proposed method was applied in a subalpine catchment in the Italian Alps, mainly covered by coniferous forest and characterized by steep slopes and high landslide risk. The results suggest that the procedure is highly reliable, according to landslide inventory maps [area under the ROC curve (AUC) is 0.82 and modified success rate (MSR) is 0.70]. Thus, it represents a promising tool for studying the role of root reinforcement in landslide hazard mapping and guiding forest management from a slope stability perspective. Copyright © 2017 John Wiley & Sons, Ltd.