In Val di Fassa (Dolomites, Eastern Italian Alps) rockfalls constitute the most significant gravity-induced natural disaster that threatens both the inhabitants of the valley, who are few, and the thousands of tourists who populate the area in summer and winter. To assess rockfall susceptibility, we developed an integrated statistical and physically-based approach that aimed to predict both the susceptibility to onset and the probability that rockfalls will attain specific reaches. Through field checks and multi-temporal aerial photo-interpretation, we prepared a detailed inventory of both rockfall source areas and associated scree-slope deposits. Using an innovative technique based on GIS tools and a 3D rockfall simulation code, grid cells pertaining to the rockfall source-area polygons were classified as active or inactive, based on the state of activity of the associated scree-slope deposits. The simulation code allows one to link each source grid cell with scree deposit polygons by calculating the trajectory of each simulated launch of blocks. By means of discriminant analysis, we then identified the mix of environmental variables that best identifies grid cells with low or high susceptibility to rockfalls. Among these variables, structural setting, land use, and morphology were the most important factors that led to the initiation of rockfalls. We developed 3D simulation models of the runout distance, intensity and frequency of rockfalls, whose source grid cells corresponded either to the geomorphologically-defined source polygons (geomorphological scenario) or to study area grid cells with slope angle greater than an empirically-defined value of 37° (empirical scenario). For each scenario, we assigned to the source grid cells an either fixed or variable onset susceptibility; the latter was derived from the discriminant model group (active/inactive) membership probabilities. Comparison of these four models indicates that the geomorphological scenario with variable onset susceptibility appears to be the most realistic model. Nevertheless, political and legal issues seem to guide local administrators, who tend to select the more conservative empirically-based scenario as a land-planning tool.
Frattini, P., Crosta, G., Carrara, A., & Agliardi, F. (2008). Assessment of rockfall susceptibility by integrating statistical and physically-based approaches. GEOMORPHOLOGY, 94(3-4), 419-437.
|Citazione:||Frattini, P., Crosta, G., Carrara, A., & Agliardi, F. (2008). Assessment of rockfall susceptibility by integrating statistical and physically-based approaches. GEOMORPHOLOGY, 94(3-4), 419-437.|
|Tipo:||Articolo in rivista - Articolo scientifico|
|Carattere della pubblicazione:||Scientifica|
|Titolo:||Assessment of rockfall susceptibility by integrating statistical and physically-based approaches|
|Autori:||Frattini, P; Crosta, G; Carrara, A; Agliardi, F|
|Data di pubblicazione:||15-feb-2008|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1016/j.geomorph.2006.10.037|
|Appare nelle tipologie:||01 - Articolo su rivista|