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dc.contributor.authorKronholm, Kalle
dc.contributor.authorBirkeland, Karl W.
dc.date.accessioned2023-11-01T14:27:18Z
dc.date.available2023-11-01T14:27:18Z
dc.date.issued2005
dc.identifier.urihttps://hdl.handle.net/11250/3100066
dc.description.abstractSnow avalanches are a major mountain hazard that kills hundreds of people and causes millions of dollars in damage worldwide annually. Yet, the relationship between the well-documented spatial variability of the snowpack and the avalanche release process is not well understood. We utilize a cellular automata model to show that the spatial structure of shear strength may be critically important for avalanche fracture propagation. Fractures through weak layers with large-scale spatial structure are much more likely to propagate over large areas than fractures through weak layers with smaller-scale spatial structure. Our technique of integrating spatial structure into the model can improve many cellular automata models that aim to explain and predict other natural hazards, such as forest fires, landslides and earthquakes.en_US
dc.language.isoengen_US
dc.publisherAmerican Geophysical Unionen_US
dc.subjectAvalanche-RnDen_US
dc.subjectSnøskred-FoUen_US
dc.titleIntegrating spatial patterns into a snow avalanche cellular automata modelen_US
dc.typeJournal articleen_US
dc.rights.holderAmerican Geophysical Unionen_US
dc.source.pagenumber4en_US
dc.source.volume32en_US
dc.source.journalGeophysical Research Lettersen_US
dc.source.issue19en_US
dc.identifier.doihttp://dx.doi.org/10.1029/2005GL024373
dc.source.articlenumberL19504en_US


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