Automated snow avalanche release area delineation in data sparse, remote, and forested regions

Potential avalanche release area (PRA) modelling is critical for generating automated avalanche terrain maps which provide low-cost large scale spatial representations of snow avalanche hazard for both infrastructure planning and recreational applications. Current methods are not applicable in mountainous terrain where high-resolution elevation models are unavailable and do not include an efficient method to account for avalanche release in forested terrain. This research focuses on expanding an existing PRA model to better incorporate forested terrain using satellite imagery and presents a novel approach for validating the model using local expertise, thereby broadening its application to numerous mountain ranges worldwide. The study area of this research is a remote portion of the Columbia Mountains in southeastern British Columbia, Canada which has no pre-existing high-resolution spatial data sets. Our research documents an open source workflow to generate high-resolution DEM and forest land cover data sets using optical satellite data processing. We validate the PRA model by collecting a polygon dataset of observed potential release areas from local guides, using a method which accounts for the uncertainty of human recollection and variability of avalanche release. The validation dataset allows us to perform a quantitative analysis of the PRA model accuracy and optimize the PRA model input parameters to the snowpack and terrain characteristics of our study area. Compared to the original PRA model our implementation of forested terrain and local optimization improved the percentage of validation polygons accurately modelled by 11.7 percentage points and reduced the number of validation polygons that were underestimated by 14.8 percentage points. Our methods demonstrate substantial improvement in the performance of the PRA model in forested terrain and provide means to generate the requisite input datasets and validation data to apply and evaluate the PRA model in vastly more mountainous regions worldwide than was previously possible.

Snow Avalanche Assessment in Mass Movement-Prone Areas: Results from Climate Extremization in Relationship with Environmental Risk Reduction in the Prati di Tivo Area (Gran Sasso Massif, Central Italy)

Mass movements processes (i.e., landslides and snow avalanches) play an important role in landscape evolution and largely affect high mountain environments worldwide and in Italy. The increase in temperatures, the irregularity of intense weather events, and several heavy snowfall events increased mass movements’ occurrence, especially in mountain regions with a high impact on settlements, infrastructures, and well-developed tourist facilities. In detail, the Prati di Tivo area, located on the northern slope of the Gran Sasso Massif (Central Italy), has been widely affected by mass movement phenomena. Following some recent damaging snow avalanches, a risk mitigation protocol has been activated to develop mitigation activities and land use policies. The main goal was to perform a multidisciplinary analysis of detailed climatic and geomorphological analysis, integrated with Geographic Information System (GIS) processing, to advance snow avalanche hazard assessment methodologies in mass movement-prone areas. Furthermore, this work could represent an operative tool for any geomorphological hazard studies in high mountainous environments, readily available to interested stakeholders. It could also provide a scientific basis for implementing sustainable territorial planning, emergency management, and loss-reduction measures.

Upslope migration of snow avalanches in a warming climate

Snow is highly sensitive to atmospheric warming. However, because of the lack of sufficiently long snow avalanche time series and statistical techniques capable of accounting for the numerous biases inherent to sparse and incomplete avalanche records, the evolution of process activity in a warming climate remains little known. Filling this gap requires innovative approaches that put avalanche activity into a long-term context. Here, we combine extensive historical records and Bayesian techniques to construct a 240-y chronicle of snow avalanching in the Vosges Mountains (France). We show evidence that the transition from the late Little Ice Age to the early twentieth century (i.e., 1850 to 1920 CE) was not only characterized by local winter warming in the order of +1.35 °C but that this warming also resulted in a more than sevenfold reduction in yearly avalanche numbers, a severe shrinkage of avalanche size, and shorter avalanche seasons as well as in a reduction of the extent of avalanche-prone terrain. Using a substantial corpus of snow and climate proxy sources, we explain this abrupt shift with increasingly scarcer snow conditions with the low-to-medium elevations of the Vosges Mountains (600 to 1,200 m above sea level [a.s.l.]). As a result, avalanches migrated upslope, with only a relict activity persisting at the highest elevations (release areas >1,200 m a.s.l.). This abrupt, unambiguous response of snow avalanche activity to warming provides valuable information to anticipate likely changes in avalanche behavior in higher mountain environments under ongoing and future warming.

Brief communication: Weak control of snow avalanche deposit volumes by avalanche path morphology

Snow avalanches are a major component of the mountain cryosphere, but little is known about the factors controlling the variability of their deposit volumes. This study investigates the influence of avalanche path morphology on ca. 1500 deposit volumes recorded between 2003 and 2018 in 77 snow avalanche paths of the French Alps. Different statistical techniques show a slight but significant link between deposit volumes and path mean elevation and orientation, with contrasted patterns between winter and spring seasons. The limited and partially non-linear nature of this control may result from the combined influence on the genesis of deposit volumes of mean path activity, climate conditions, and mechanical thresholds determining avalanche release.