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dc.contributor.authorPeitzsch, Erich
dc.contributor.authorHendrikx, Jordy
dc.contributor.authorStahle, Daniel
dc.contributor.authorPederson, Gregory
dc.contributor.authorBirkeland, Karl
dc.contributor.authorFagre, Daniel
dc.date.accessioned2022-06-17T18:58:13Z
dc.date.available2022-06-17T18:58:13Z
dc.date.issued2021-02
dc.identifier.citationPeitzsch, E., Hendrikx, J., Stahle, D., Pederson, G., Birkeland, K., & Fagre, D. (2021). A regional spatiotemporal analysis of large magnitude snow avalanches using tree rings. Natural Hazards and Earth System Sciences, 21(2), 533-557.en_US
dc.identifier.issn1684-9981
dc.identifier.urihttps://scholarworks.montana.edu/xmlui/handle/1/16831
dc.description.abstractSnow 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.en_US
dc.language.isoen_USen_US
dc.publisherCopernicus GmbHen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.titleA regional spatiotemporal analysis of large magnitude snow avalanches using tree ringsen_US
dc.typeArticleen_US
mus.citation.extentfirstpage533en_US
mus.citation.extentlastpage557en_US
mus.citation.issue2en_US
mus.citation.journaltitleNatural Hazards and Earth System Sciencesen_US
mus.citation.volume21en_US
mus.identifier.doi10.5194/nhess-21-533-2021en_US
mus.relation.collegeCollege of Letters & Scienceen_US
mus.relation.departmentEarth Sciences.en_US
mus.relation.universityMontana State University - Bozemanen_US
mus.data.thumbpage8en_US


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