Abstract
Abstract. Snow avalanches affect transportation corridors and settlements worldwide. In many mountainous regions, robust records of avalanche frequency and magnitude are sparse or non-existent. However, dendrochronological methods can be used to fill this gap and infer historical avalanche patterns. In this study, we developed a tree-ring-based avalanche chronology for large magnitude avalanche events (size ≥∼D3) using dendrochronological techniques for a portion of the US northern Rocky Mountains. We used a strategic sampling design to examine avalanche activity through time and across nested spatial scales (i.e., from individual paths, four distinct subregions, and the region). We analyzed 673 samples in total from 647 suitable trees collected from 12 avalanche paths from which 2134 growth disturbances were identified over the years 1636 to 2017 CE. Using existing indexing approaches, we developed a regional avalanche activity index to discriminate avalanche events from noise in the tree-ring record. Large magnitude avalanches, common across the region, occurred in 30 individual years and exhibited a median return interval of approximately 3 years (mean = 5.21 years). The median large magnitude avalanche return interval (3–8 years) and the total number of avalanche years (12–18) varies throughout the four subregions, suggesting the important influence of local terrain and weather factors. We tested subsampling routines for regional representation, finding that sampling 8 random paths out of a total of 12 avalanche paths in the region captures up to 83 % of the regional chronology, whereas four paths capture only 43 % to 73 %. The greatest value probability of detection for any given path in our dataset is 40 %, suggesting that sampling a single path would capture no more than 40 % of the regional avalanche activity. Results emphasize the importance of sample size, scale, and spatial extent when attempting to derive a regional large magnitude avalanche event chronology from tree-ring records.
Highlights
1.1 BackgroundSnow avalanches are hazardous to human safety and infrastructure (Mock et al, 2016; Schweizer, 2003), as well as an important landscape disturbance affecting mountain ecosystems (Bebi et al, 2009)
Scars were the dominant input type of growth disturbances (GDs) classified as C1, and reaction wood comprised the majority of GDs classified as C2, C3, and C4 (Table A3)
By analyzing 673 samples from 12 avalanche paths, we identified 30 years with large magnitude events across the region and a median return interval of ∼ 3 years
Summary
1.1 BackgroundSnow avalanches are hazardous to human safety and infrastructure (Mock et al, 2016; Schweizer, 2003), as well as an important landscape disturbance affecting mountain ecosystems (Bebi et al, 2009). Avalanches, especially large magnitude events, affect transportation corridors and settlements throughout the world. Avalanches impact numerous roadways and railroad corridors in the western United States (Armstrong, 1981; Hendrikx et al, 2014; Reardon et al, 2008). Understanding general avalanche processes and associated large magnitude avalanche return intervals (RIs) is critical for local and regional avalanche forecasters, transportation agencies, and land use planners. Long-term, reliable, and consistent avalanche observation records are necessary for calculating avalanche return intervals which can be used in infrastructure planning and avalanche forecasting operations. Such records are often sparse or non-existent in many mountainous regions, including areas with existing transportation corridors.
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