EGU21-14454
https://doi.org/10.5194/egusphere-egu21-14454
EGU General Assembly 2021
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Using SlideforMAP and SOSlope to identify susceptible areas to shallow landslides in the Foreste Casentinesi National Park (Tuscany, Italy)

Ilenia Murgia1,2, Filippo Giadrossich3,4,5, Marco Niccolini2, Federico Preti3,6, Yamuna Giambastiani3,7,8, Gian Franco Capra1,5, and Denis Cohen9
Ilenia Murgia et al.
  • 1Department of Architecture, Design and Urban Planning, University of Sassari, Via Piandanna, 4, 07100 Sassari, Italy.
  • 2D.R.E.Am. Italia Soc. Coop. Agr., Via Garibaldi, 3, 52015 Pratovecchio Stia (AR)
  • 3AIPIN (Italian Soil and Water Bioengineering Association), Via San Bonaventura 13, 50145 Firenze
  • 4Nuoro Forestry School, Department of Agricultural, University of Sassari, Viale Italia, 39, 07100 Sassari, Italy
  • 5Desertification Research Centre, University of Sassari, Viale Italia, 39, 07100 Sassari, Italy.
  • 6Department of Agricultural, Food, Environmental and Forestry Sciences and Technologies, University of Florence, 50144 Firenze, Italy
  • 7CNR-IBE National Research Council Institute of BioEconomy, 50019 Sesto F.no, Firenze, Italy
  • 8Bluebiloba Startup Innovativa SRL, Firenze, Italy
  • 9Department of Earth and Environmental Science, New Mexico Tech, New Mexico, Socorro, USA

SlideforMAP and SOSlope are part of a suite of software available through ecorisQ (www.ecorisq.org), an international, non-profit association promoting solutions for risk reduction of natural hazards. SlideforMap is a probabilistic model that quantifies the stabilizing effect of vegetation at the regional scale and localizes potential areas where forest protection could be improved. SOSlope is a hydro-mechanical model that computes the factor of safety at the slope scale, using a strain-step discrete element method, which includes the effects of vegetation root structure and composition. The research aims at investigating the landslide susceptibility at two different spatial scales, using both models. 

The study area is located on a vegetated slope near an interregional connecting road (Tuscany, Emilia-Romagna, central Italy), which crosses the Foreste Casentinesi National Park (Tuscany) an important natural area for both touristic and recreational activities. 

A shallow landslide susceptibility analysis was performed at two different spatial scales, combining the use of the two previously mentioned models. In particular, SlideforMap was applied to identify the main susceptible areas to landslides at regional scale. Next, the identified unstable areas were investigated at detailed scale using SOSlope which simulated an intense rainfall event. Specifically, both distributions of root and soil forces along the slope were analyzed; for the sake of comparison, beech (Fagus sylvatica L.) and spruce (Picea abies L.) parameters were used. Finally, a back-analysis was performed on real landslides. 

The results showed the activation of root reinforcement spatially distributed in the studied slope. The basal root reinforcement map highlights significant differences, with beech showing higher reinforcement values compared to spruce. According to the factor of safety map, landslides may occur along the investigated unstable area. 

SlideforMap and SOSlope may be useful tools to support land and forestry planning, allowing the localization and quantification of the protective effects of forests, root reinforcement included. Results demonstrated that the factor of safety can be used as benchmarks for silvicultural interventions, thus improving the whole planning activities in both forest and surrounding natural and man-made systems.

How to cite: Murgia, I., Giadrossich, F., Niccolini, M., Preti, F., Giambastiani, Y., Capra, G. F., and Cohen, D.: Using SlideforMAP and SOSlope to identify susceptible areas to shallow landslides in the Foreste Casentinesi National Park (Tuscany, Italy), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14454, https://doi.org/10.5194/egusphere-egu21-14454, 2021.