NH23A-3856:
Integrating the effects of forest cover on slope stability in a deterministic landslide susceptibility model (TRIGRS 2.0)
NH23A-3856:
Integrating the effects of forest cover on slope stability in a deterministic landslide susceptibility model (TRIGRS 2.0)
Tuesday, 16 December 2014
Abstract:
The potentially stabilizing effects of forest cover in respect of slope stability have been the subject of many studies in the recent past. Hence, the effects of trees are also considered in many deterministic landslide susceptibility models. TRIGRS 2.0 (Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability; USGS) is a dynamic, physically-based model designed to estimate shallow landslide susceptibility in space and time. In the original version the effects of forest cover are not considered. As for further studies in Vorarlberg (Austria) TRIGRS 2.0 is intended to be applied in selected catchments that are densely forested, the effects of trees on slope stability were implemented in the model. Besides hydrological impacts such as interception or transpiration by tree canopies and stems, root cohesion directly influences the stability of slopes especially in case of shallow landslides while the additional weight superimposed by trees is of minor relevance. Detailed data on tree positions and further attributes such as tree height and diameter at breast height were derived throughout the study area (52 km²) from high-resolution airborne laser scanning data. Different scenarios were computed for spruce (Picea abies) in the study area. Root cohesion was estimated area-wide based on published correlations between root reinforcement and distance to tree stems depending on the stem diameter at breast height. In order to account for decreasing root cohesion with depth an exponential distribution was assumed and implemented in the model. Preliminary modelling results show that forest cover can have positive effects on slope stability yet strongly depending on tree age and stand structure.This work has been conducted within C3S-ISLS, which is funded by the Austrian Climate and Energy Fund, 5th ACRP Program.