EGU2020-21264
https://doi.org/10.5194/egusphere-egu2020-21264
EGU General Assembly 2020
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Factor of safety analysis with and without vegetation using the SOSlope model

Massimiliano Schwarz1, Ilenia Murgia2, Filippo Giadrossich3, Massimiliano Bordoni4, Claudia Meisina4, Gian Battista Bischetti5, Gian Franco Capra2, and Denis Cohen6
Massimiliano Schwarz et al.
  • 1Bern University of Applied Sciences, Mountain Forests and Natural Hazards, Forestry, Zollikofen, Switzerland (massimiliano.schwarz@bfh.ch)
  • 2. Department of Architecture, Design and Urban Planning, University of Sassari, Bionaturalistic Pole, Via Piandanna n° 4, 07100 Sassari, Italy
  • 3. Department of Agriculture, University of Sassari, viale Italia 39, 07100 Sassari, Italy
  • 4. Department of Earth and Environmental Sciences, University of Pavia, Via Ferrata 1, 27100 Pavia, Italy
  • 5. Institute of Agricultural Hydraulics, University of Milano, Celoria n. 2, Italy
  • 6. Department of Earth and Environmental Science, New Mexico Tech New Mexico, USA

Until now, slope stability models include the effects of the vegetation by adding a fixed value of apparent root cohesion as an estimate of root strength. However, some studies have demonstrated that root reinforcement depends on poorly constrained factors such as the heterogeneous distribution of roots in the soil and their tensional and compressional strength behavior.

SOSlope (Self-Organized Slope) is a hydro-mechanical model that computes the factor of safety on a hillslope discretized into a two-dimensional array of blocks connected by bonds to simulate the interactions of root-soil systems (Cohen and Schwarz, 2017). SOSlope estimates slope stability considering the presence of vegetation as a function of parameters such as species, tree density and diameter at breast height. In particular, bonds between adjacent blocks represent mechanical forces acting across the blocks due to roots and soil, in tension or compression, depending on the relative position of blocks. It is a strain-step discrete element model that reproduces the self-organized redistribution of forces on a slope during a rainfall-triggered shallow landslide. The innovative aspect of this model is a complete evaluation of the effects of roots on slope stability calculated using the Root Bundle Model with Weibull survival function  (RBMw, Schwarz et al, 2013).

In this case study, SOSlope was used to reconstruct a critical shallow landslide triggering and to observe how the factor of safety changes depending on the presence, or not, of vegetation. The study area is located in the north-eastern part of the Oltrepò Pavese (Pavia, Italy), and is characterized by a high density of past landslides as reported in the database of Italian landslide inventories (IFFI). In the past, the common land use was vineyards, abandoned in the 1980s. Presently, the vegetation consists of grasses and shrubs moving to a thinned forest of young Robinia pseudoacacia L.    

On 27 and 28 April 2009 a shallow landslide triggered after an intense and prolonged rainfall event (160 mm accumulated in 62 h with a maximum intensity of 22.6 mm/h). A large number of shallow landslides occurred in the surrounding area with about 29 landslides per km2 (1600 landslides in 240 km2). Five years later, on 28 February - 2 March 2014, 15 meters from a monitoring station and close to the previously affected area, another superficial landslide was triggered after 30 days of rain with a total precipitation of 105.5 mm (68.9 mm in 42 h recorded by the rain gauge of the monitoring station). In addition to the significance of this large landslide, this case study was scientifically important because it wasthe first documented case of a natural shallow landslide induced by rainfall since the 1950s (Bordoni et al, 2015).

The results of SOSlope simulations show good agreement with the real event of 28 February - 2 March 2014, and emphasize the important role of tree roots in the variation of the factor of safety. In this specific case, adding trees results in a reduction of about 39% of the dimensions of the unstable area.

How to cite: Schwarz, M., Murgia, I., Giadrossich, F., Bordoni, M., Meisina, C., Bischetti, G. B., Capra, G. F., and Cohen, D.: Factor of safety analysis with and without vegetation using the SOSlope model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21264, https://doi.org/10.5194/egusphere-egu2020-21264, 2020.