294 Geologic Mapping (Posters)
Showcase your latest geologic mapping methods, techniques, and map products! This poster session highlights new detailed geologic maps addressing critical minerals, land management, groundwater, coastal resources, geologic hazards, and other derivative maps. NCGMP map submissions are encouraged.
Wednesday, 22 October 2025
8:00 AM - 5:30 PM
HBGCC, Hall 1
Digital Mapping Methods to Identify Areas Prone to “Impactful” Avalanches Events
Paper number: 294-1
Program: Technical Sessions
Time: 8:00 AM – 8:00 AM
Authors
Abstract
Avalanches have killed over 600 people over the past 25 years and caused millions of dollars in property damage. While an avalanche can be any body of snow and/or ice sliding down a slope, an “impactful” avalanche is one that is large enough to damage property and injure and/or kill people. Producing a nationwide map of areas at risk to impactful avalanches, though, can be a tricky task. The primary factors for avalanche risk are slopes between 30 and 50 degrees and snow depth of 1 meter or more. Other factors, such as aspect, land cover, and primary wind direction, all play a role in avalanche potential, however the primary goal is first to identify any areas that are prone to avalanches. Digital elevation models (DEMs), at ~10m resolution are available from the National Map nationwide and can be converted to slope using GIS tools. Finding areas where, historically, there have been 1m or more of snow depth is less straightforward. Within the continental US, historical snow depth data is available from the Snow Data Assimilation System (SNODAS), from which any area that had snow depths reaching 1m or more were identified. For Alaska, lacking SNODAS data, a combination of weather station snow depth records and machine learning were needed to provide maximum snow depth estimates. Once the identification of areas at risk to any avalanches have been determined, other factors can be included to determine areas at risk to impactful avalanches. By downscaling the DEM to a 100m resolution, identification of areas at risk to avalanches is reduced to larger, impactful avalanches, limiting smaller areas such as steep river valleys and small road cuts. Combining this data with historical impactful avalanche events, it is then possible to filter out regions that are unlikely to have impactful avalanches, despite their satisfaction of the two main criteria. From here, the other impactful factors can be used to distinguish between areas more or less at risk to impactful avalanches events. Beyond this, it is also possible to identify areas downslope, within the avalanche runout zone, which are areas not directly identified using the primary two factors.
Geological Society of America Abstracts with Programs. Vol. 57, No. 6
doi: 10.1130/abs/2025AM-413494
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