Spatio-temporal analysis of large magnitude avalanches using dendrochronology
Peitzsch, Erich Hans
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Snow avalanches are a natural hazard to humans and infrastructure as well as an important landscape disturbance affecting mountain ecosystems. In many mountainous regions, records of avalanche frequency and magnitude are sparse or non-existent. Inferring historic avalanche patterns to improve forecasting and understanding requires the use of dendrochronological methods. In this dissertation, we examine a regional tree-ring derived large magnitude avalanche dataset from northwest Montana in the northern Rocky Mountains, USA, to produce avalanche chronologies at three distinct scales (path, sub-region, and region), assess seasonal climate drivers of years with large magnitude avalanche occurrence on a regional scale, and characterize vegetation in select avalanche paths. By implementing a strategic spatial sampling design and collecting a large dataset of tree-ring samples, we: (1) assessed scaling in the context of a regional avalanche chronology, reconstructed avalanche chronologies for 12 avalanche paths in four subregions, and examined the effects of two methods of sampling indexing on the resultant avalanche chronology; (2) identified specific climate drivers of large magnitude avalanche years across a region and identified trends in avalanche year probability through time; and (3) tested the feasibility of using remote sensing products to quantify vegetation types in avalanche paths and characterized the vegetation composition based on return periods within specific avalanche paths. This dissertation is organized into 3 key chapters/manuscripts (Chapters 2, 3, and 4) and two supporting chapters (Chapters 1 and 5) that address the problem of assessing large magnitude avalanche frequency at various spatio-temporal scales using a tree-ring dataset. The results contribute toward a better understanding of reconstructing regional avalanche chronologies, a more accurate assessment of avalanche-climate relationships, and improved methods to characterize vegetation characteristics within avalanche path return periods. This work has applications for regions with sparse avalanche records.