Mapping snow avalanches hazard in poorly monitored areas. The case of Rigopiano avalanche, Apennines of Italy

Abstract

Abstract. Hazard mapping is carried out in Italy according to the AINEVA guidelines, which require (i) data driven avalanche dynamic modelling to assess end mark and pressure, and (ii) assessment of maximum yearly three-day snow depth increase h72 for 30 to 300 years return period. When no historical avalanche data are present, model tuning and data based assessment of avalanche return periods are hardly feasible. Also when (very) short series of h72 are available, station based quantile estimation for such high return periods is very uncertain, and regionally based approaches can be used. We apply an index value approach for the case study avalanche of Rigopiano, where a 105 m3 snow mass hit the Rigopiano Hotel killing 29 persons on January 18th 2017. This area is poorly monitored avalanche wise, and displays short series (max 14 years) of snow depth measurements, no historical avalanche maps are available on the avalanche track, and no hazard maps have been developed hitherto. First, we tune the recently developed Poly-Aval dynamic avalanche model (1D/q2D) against the 18th January event data (release zone, release depth, end mark) from different sources. We then use snow data from 7 snow stations in Abruzzo (75 equivalent years of data) to tune a regionally valid distribution of h72. We then calculate the 30-years, 100-years, and 300-years runout zone and flow pressures, including confidence limits. We demonstrate that (i) properly tuned 1D/quasi2D models can be used for avalanche modeling even within poorly monitored area as here, and (ii) the use of regional analysis allows hazard mapping for large return periods, reducing greatly the uncertainty against canonical, single site analysis. Our approach is usable in poorly monitored regions like Abruzzo here, and we suggest that (i) avalanche hazard mapping needs to be pursued with regional approaches for h72, and (ii) confidence limits need to be provided for the proposed zoning.

Seismically Induced Snow Avalanches: The Central Italy Case

“…Previous studies on these events mostly focused on the geology of the earthquakes and seismically induced surface deformation and landslides. Specific investigations particularly concerning avalanche features, field analyses, numerical simulations (Bocchiola et al, 2018;Frigo et al, 2018), and forensic applications (Chiambretti et al, 2018), as well as analysis of the triggering conditions (Puzrin et al, 2019), also focused on the NE slope of Mt. Siella, where well-documented avalanches occurred on January 18, 2017 after four main seismic events (e.g., the catastrophic Rigopiano event, which affected a tourist facility).…”

“…In this work, the software features were exploited for modeling the deformation occurring within a thick snow cover on a steep slope both under static and dynamic conditions to investigate the detachment area and the role of the seismic shaking in the avalanche trigger. The nivological data (Bocchiola et al, 2018; NGI, 2018) do not provide an accurate definition of the snow cover and profile in the detachment area. For this reason, a plausible overall cover of 3.0 m was assumed over the entire slope.…”

Reconstructing the Snow Avalanche of Coll de Pal 2018 (SE Pyrenees)

“…According to the Emergency Events Database, EM-DAT [2], snowfall and snow avalanches are considered natural hazard belonging to hydrometeorological events. Snow avalanches have caused, and cause, important damages, especially in mountain areas; thus, hazard assessment and prevention to reduce the associated risk become mandatory [3][4][5][6][7][8][9][10][11][12][13][14].…”