Application of an Integrated Method for Landslide Hazard Assessment in the Area of Corvara in Badia (Dolomites, Italy).

The area of Corvara in Badia (Dolomites, Italy) has undergone detailed geomorphological investigation aiming at the identification, characterisation and management of mass movements within the framework of the NEWTECH Project (New technologies for landslide hazard assessment and management in Europe) funded by the European Union. From the Lateglacial, the area of Corvara in Badia has been thoroughly modelled by slope processes which resulted on a variety of landslides, some of which are still active today. In particular, some active mass movements affect tourist infrastructures and roads on the slope of Col Alto - Pralongià, located immediately to the SE of the village of Corvara in Badia. This paper presents the four main phases that make up the method adopted for integrated landslide hazard assessment in the area of Corvara in Badia. The first phase consisted in a geomorphological survey of the valley which led to the elaboration of a geomorphological map at a 1:10,000 scale. In particular, this phase enabled landslides location and type to be characterised. The second phase of the research was focused on the Col Alto - Pralongià slope and consisted of a detailed analysis of slope instability conditions. This enabled the type and state of activity of the geomorphological effects of slope instability to be defined and mapped at a 1:5000 scale. At the same time, this phase permitted the main determining causes of slope instability, such as geotechnical and geomechanical properties, slope morphometry etc., to be analysed and mapped at the same scale. The third phase of the research included databases implementation and GIS-based data analysis which eventually led to the elaboration and publication of a landslide susceptibility map at a 1:5000 scale. The fourth and the last phase of the research, which led to an integrated assessment of landslide hazard in the Col Alto - Pralongià slope, consisted in the integration of susceptibility information with hydrological, geotechnical, monitoring and recurrence data, thus producing a qualitative assessment of the triggering mechanisms and of their possible return times.