Data collection and GIS-based procedure for debris-flow characterization at the regional scale in northeastern Italy

Cavalli M., Crema S., Marchi L., 2019, Data collection and GIS-based procedure for debris-flow characterization at the regional scale in northeastern Italy, GIT 2019, 14° Convegno Nazionale "GIT- Geosciences and Information Technologies", Melfi (PZ), 17-19/06/19,
URL: http://www.cnr.it/prodotto/i/403748

Debris flows are among the most dangerous phenomena in mountain catchments and they are particularly destructive when they intersect transport routes or urban areas. Debris flows are expected to increase in the frequency and magnitude as a result of the current climate change. In order to test this hypothesis by analyzing the variations of debris-flow frequency and magnitude with time, it is of utmost importance the availability of a long time series of primary data on debris-flows occurrence and volume. Furthermore, to cope with these dangerous phenomena at the regional scale, the development of new tools for the assessment of areas affected by debris flows and their spatial characterization is needed. The aim of this work is twofold_ to extend primary data collection on debris flows in northeastern Italy and to provide a simple GIS-based procedure that can be easily applied to identify debris-flow channels and alluvial fans in the same geographical context. The results of the analysis of date of occurrence and volume of the large collected dataset of debris-flows show the occurrence, in the last forty years, of some high-magnitude debris flows characterized by the largest unit volumes of the dataset. This seems to suggest a role played by climate changes on debris-flow magnitude that should be further investigated. In addition, a simple and fast semi-automated GIS based procedure is presented. It consists of a low data-demanding method for a preliminary mapping of potentially debris-flow affected areas to enable priority ranking of channels and alluvial fans at risk by debris flows. This approach has been validated by means of field checks and through its extensive application in the eastern Italian Alps.

Data from https://intranet.cnr.it/people/