Item: AN AUTOMATED METHOD FOR REGIONAL AVALANCHE ALPHA-ANGLE CHARACTERIZATION BASED IN WESTERN CANADA
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Title: AN AUTOMATED METHOD FOR REGIONAL AVALANCHE ALPHA-ANGLE CHARACTERIZATION BASED IN WESTERN CANADA
Proceedings: Proceedings, International Snow Science Workshop, Whistler, BC, Canada, 2026
Authors:
- Declan Knies [ Simon Fraser University Avalanche Research Program, Burnaby, BC, Canada ]
- John Sykes [ Simon Fraser University Avalanche Research Program, Burnaby, BC, Canada ]
- Pascal Haegeli [ Simon Fraser University Avalanche Research Program, Burnaby, BC, Canada ] [ WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland ]
Date: 2026-09-28
Abstract: The Avalanche Terrain Exposure Scale (ATES) is used to communicate spatial susceptibility to avalanche terrain (Statham and Campbell 2025). Historically, ATES maps were produced manually for small, high-use areas, however, advances in GIS, remote sensing, and automated terrain modelling now enable large-scale mapping (Jamieson and Campbell 2018; Huber et al. 2023). A new SAR-NIF project aims to produce ATES maps across Western Canada using the automated ATES (autoATES) protocol. A key component in autoATES is runout extent, calculated by the statistical runout model FlowPy. FlowPy primarily uses maximum alpha-angle, the angle between the avalanche crown and toe along the path of travel, to compute avalanche runout (D'Amboise et al. 2022; Huber et al. 2024). AutoATES v2.0 used a conservative 18° alpha-angle parameter to capture extreme runouts for all regions. However, a Coast Mountains study reported a minimum alpha-angle of 20.4°, indicating a need for regional calibration (Nixon and McClung 1993). We propose a method for estimating regional avalanche alpha-angle parameters from operational avalanche occurrence records in western Canada. In this workflow, we use FlowPy to model an avalanche thalweg (flow path), statistically estimate a crown location, and locate a toe mass location using operational data to calculate regional alpha-angle distributions. Quality control removes unsuitable avalanche paths from statistics, reducing 153 initial paths to 40 retained. Across retained paths, alpha-angles ranged 21° to 56° for Bear Pass and 24° to 50° for Duffey Lake. Mean alpha-angles were 32° in both regions. The Bear Pass minimum closely matched the 20.4° Coast Mountains minimum, but other results differed (Nixon and McClung 1993). The absence of start-zone data, the operational nature of the dataset, and the limited number of retained paths introduce substantial uncertainty. However, the program can easily accommodate new datasets, improved thalweg routing, or the implementation of alpha-beta or runout-ratio regression models.
Object ID: ISSW2026_P4.45.pdf
DOI: https://doi.org/10.15788/1790099370
Language of Article: English
Presenter(s): Declan Knies
Keywords: Automated Avalanche Terrain Mapping; FlowPy; Runout Simulation; Model Validation; Alpha-Angle
Page Number(s): 2030 - 2037
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