Orals

Among the many mitigation measures available for reducing the risk to life related to landslides, early warning systems certainly constitute a significant option available to the authorities in charge of risk management and governance. Landslide early warning systems (LEWS) are non-structural risk mitigation measures applicable at different scales of analysis: slope and regional. Systems addressing single landslides at slope scale can be named local LEWS (Lo-LEWS), systems operating over wide areas at regional scale are referred to as territorial systems (Te-LEWSs). An initial key difference between Lo-LEWSs and Te-LEWSs is the knowledge “a priori” of the areas affected by future landsliding. When the location of future landslides is unknown and the area of interest extends beyond a single slope, only Te-LEWS can be employed. Conversely, Lo-LEWSs are typically adopted to cope with the risk related to one or more known well-identified landslides.

Independently by the scale of analysis, the structure of LEWS can be schematized as an interrelation of four main modules: setting, modelling, warning, response. However, the definition of the elements of these modules and the aims of the warnings/alerts issued considerably vary as a function of the scale at which the system is employed.

The session focuses on landslide early warning systems (LEWSs) at both regional and local scales. The session wishes to highlight operational approaches, original achievements and developments useful to operate reliable (efficient and effective) local and territorial LEWS. Moreover, the different schemes describing the structure of a LEWS available in literature clearly highlight the importance of both social and technical aspects in the design and management of such systems.

For the above-mentioned reasons, contributions addressing the following topics are welcome:
• rainfall thresholds definition;
• monitoring systems for early warning purposes;
• warning models for warning levels issuing;
• performance analysis of landslide warning models;
• communication strategies;
• emergency phase management;
• landslide risk perception.