The influence of Biomass and its change on landSLIDE activity (BioSLIDE)


2015-05-01 – 2018-04-30

Landslides occur in many hilly and mountainous regions all over the world. These potentially
damaging phenomena are caused by multiple interacting natural and anthropogenic factors. Human
induced land cover changes (e.g. deforestation) are known to have a large influence on landslide
activity.
In contrast to climatic, geological and topographical factors, forest stands can be managed directly
by humans. Therefore we suggest that in order to draw up appropriate avoidance strategies, it is
crucial to investigate the interdependent processes that define stability under forested and nonforested
conditions.
Newly developed physically based modelling methods exist to simulate such effects. However, the
reliability of the modelling results is usually hampered by the availability of reliable input data.
This project strives to counter this much discussed weakness of physically based modelling
approaches. The main objective of this research is to simulate and quantify the effects of forest
related biomass and biomass changes on slope stability at regional scale (~15km²).
The innovative approach will be developed and tested for a study area located in the federal state
of Vorarlberg, where landsliding represents a prevalent geomorphic phenomenon and high resolution
multi temporal ALS (airborne laser scanning) data exist.
Based on 3D ALS point cloud data from the years 2004, 2011 and 2015 multiple biomass
parameters (e.g. biomass, vertical layer structure, crown volume) will be derived. An in-situ
assessment of vegetation related information (e.g. root distribution) will be conducted in order to
enable an empirical linking between the ALS derived information and additional relevant parameters
(e.g. tree allometry). The effect of biomass- and climatic changes on slope stability will be simulated
using a sophisticated physically based hydro-mechanical model, which enables to implement
geomechanical (e.g. root cohesion, bulk unit weight) and hydrological (e.g. interception,
evapotranspiration) effects to simulate slope stability in time.
The proposed innovative combination of vegetational parameters derived from ALS data with a
physically based slope stability model is expected to allow a better understanding of geomorphic
interdependencies at this scale. Furthermore, this interdisciplinary approach is expected to generate
synergies between scientific fields, which will lead to an improved spatio-temporal prediction of the
effects of human activity and environmental changes on landslide activity.

Project manager

Project members

Partners

  • Utrecht University
  • TU Delft
  • University of Vienna