EGU2020-11291
https://doi.org/10.5194/egusphere-egu2020-11291
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Forecasting landslide at slope-scale: past achievements, present challenges and future perspectives

Emanuele Intrieri, Tommaso Carlà, Giovanni Gigli, and Nicola Casagli
Emanuele Intrieri et al.
  • Università di Firenze, Earth Science, Firenze, Italy (emanuele.intrieri@unifi.it)

In general, the most reliable parameters to forecast the occurrence of a landslide are kinematics parameters, such as displacement, velocity and acceleration, since they represent the direct indicator of the stability conditions of a slope. Despite recent advancement in satellite interferometry, the highest temporal resolution, necessary to set up an effective early warning system, are still achievable from ground-based instrumentation.

Within this framework a few methods to forecast the time of failure of landslides at slope-scale have been developed in the last decades and, in many instances, they have been successfully used to prevent casualties and economic losses.

Common applications include public safety situations and open-pit mines, for which accurate warnings are crucial to protect workers and at the same time avoid unnecessary interruptions of the extraction activities.

In this work, a review of the most relevant kinematics-based forecasting methods is presented. Some examples are shown to illustrate the respective advantages, limitations and range of applicability of each method. Future challenges, trends and opportunities provided by technological innovations and scientific advances, also in related fields such as Material Science and Applied Mathematics, are also presented.

How to cite: Intrieri, E., Carlà, T., Gigli, G., and Casagli, N.: Forecasting landslide at slope-scale: past achievements, present challenges and future perspectives, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11291, https://doi.org/10.5194/egusphere-egu2020-11291, 2020

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