Snow avalanches are a widespread natural hazard to humans and infrastructure as well as an important landscape disturbance affecting mountain ecosystems. Forecasting avalanche frequency is challenging on various spatial and temporal scales, and this project aims to fill a gap in snow science by focusing on reconstructing avalanche history on the continental mountain range scale - throughout the Rocky Mountains and into southeast Alaska. This should provide an opportunity to more thoroughly assess current and future trends in avalanche activity and, ultimately, improve public safety and protect resources. The project aims to advance our understanding of avalanche frequency, magnitude, and character changes and to improve estimates of future changes in these types of avalanche parameters in the context of changing climate drivers. In other words, how does avalanche frequency and character vary across space and time, and what are the primary drivers of this variability?
Statement of Problem: In the western United States, avalanches are the most frequently occurring lethal form of slope movement and, on an annual basis, cause more fatalities than earthquakes and all other forms of slope failure combined. Avalanches affect a substantial portion of society, including human safety and commerce, and also serve as a major driver of ecological disturbance by modifying habitat for flora and fauna. Economic impacts due to avalanches in the western United States are substantial. For instance, the economic loss when Interstate-70 through Colorado closes due to avalanche impacts is approximately $1 million per hour ($3330/ lane mile hour). In addition, avalanches impact the spring opening operations of the Going-to-the-Sun Road, a major attraction in Glacier National Park, where visitors contribute $344 million to surrounding communities.
- Determine avalanche frequency across multiple spatial scales by incorporating tree ring records, historical observations, and remote sensing (UAS) tools.
- Determine the weather, climate, and snowpack drivers of large magnitude avalanche events and assess variability across multiple spatio-temporal scales and avalanche climates.
- Examine climate and weather drivers to assess a historical and ongoing shift in avalanche character across different spatial extents and avalanche climates.
Methods:
Reconstructing past avalanche frequency using tree-rings - Trees are susceptible to damage from geomorphic processes such as avalanches, and individual trees record the effects of the disturbance in several ways. An avalanche may cause wounds on the tree trunk or branches. It can also locally destroy the cambium (plant cells responsible for plant diameter increasing), causing disruption of new cell formation. As a result, the tree then produces tissue and the cells overgrow the injury forming a “scar” on the tree-ring. Other markers of mechanical disturbance from avalanches in tree ring records include reaction wood (created in response to gravity to push a tree back to a vertical position) and traumatic resin ducts (created after injury to deliver more resin, an antiseptic, to injured part of tree).
We collect cross-sectional wood samples from dead (both downed and standing dead) trees and trunk core samples from live trees. We process, date, and measure tree ring widths using standard procedures, and then process the samples for signs of traumatic impact events likely caused by snow avalanches. Using the resulting avalanche event chronologies, the return periods for each path, sub-region, and entire study site are estimated. Chronologies from the northern Rockies (intermountain avalanche climate) and southeast Alaska (maritime avalanche climate) were previously collected and will be used in this study to examine potential geographic differences in avalanche frequency within the Rocky Mountain cordillera and variability within and between avalanche climates. Finally, we use historical avalanche occurrence records from throughout the study area to assess the tree-ring derived chronology in more recent times.
Atmospheric and climate drivers of large magnitude avalanches - Understanding the spatio-temporal behavior of avalanches and the contributing climate factors is important for understanding climate variability, interpreting historical avalanche variability, and improving avalanche forecasting. We use the reconstructed avalanche chronologies and existing historical datasets as well as climate databases to examine relationships between years of large magnitude avalanche events and climate variables. We will begin by investigating trends in wet snow avalanche frequency throughout the study site using historical observational datasets.
Using remote sensing to examine avalanche and snowpack characteristics - Snow depth varies both among sites and within a season. The amount of weater stored as snow has direct impacts on water availability and flooding that could affect downstream communities. The seasonal evolution of the spatial distribution of snow depth reflects water storage information that is valuable to resource managers and downstream communities concerned about water availability and flooding. Snow distribution data on shorter time scales are necessary for avalanche risk assessment. New methods have been developed to estimate snowpack variability and the amount of water stored in snowpack, using Unmanned Aerial Systems (UASs) and Structure-from-Motion (SfM) photogrammetry. Aerial images of complex alpine terrain were collected in the winter using UAS and high-resolution GPS measurements. These images are then processed using photogrammetry software and programming language platforms to build geo-referenced digital elevation products. A variety of statistical techniques are then employed to assess variability of snow depth change and avalanche frequency across the sites and through time.
We also are exploring use of satellite imagery to detect landscape change due to avalanche disturbance. We are also working on pattern recognition techniques to identify changes in properties of multi-band spectral imagery after the March 2019 historic avalanche cycle in Colorado. In addition, preliminary exploratory analysis shows strong potential for use of historical imagery time series to examine changes in vegetation within and around avalanche paths to provide another measure of avalanche frequency.
The Western Mountain Initiative (WMI)
Snow avalanches are a widespread natural hazard to humans and infrastructure as well as an important landscape disturbance affecting mountain ecosystems. Forecasting avalanche frequency is challenging on various spatial and temporal scales, and this project aims to fill a gap in snow science by focusing on reconstructing avalanche history on the continental mountain range scale - throughout the Rocky Mountains and into southeast Alaska. This should provide an opportunity to more thoroughly assess current and future trends in avalanche activity and, ultimately, improve public safety and protect resources. The project aims to advance our understanding of avalanche frequency, magnitude, and character changes and to improve estimates of future changes in these types of avalanche parameters in the context of changing climate drivers. In other words, how does avalanche frequency and character vary across space and time, and what are the primary drivers of this variability?
Statement of Problem: In the western United States, avalanches are the most frequently occurring lethal form of slope movement and, on an annual basis, cause more fatalities than earthquakes and all other forms of slope failure combined. Avalanches affect a substantial portion of society, including human safety and commerce, and also serve as a major driver of ecological disturbance by modifying habitat for flora and fauna. Economic impacts due to avalanches in the western United States are substantial. For instance, the economic loss when Interstate-70 through Colorado closes due to avalanche impacts is approximately $1 million per hour ($3330/ lane mile hour). In addition, avalanches impact the spring opening operations of the Going-to-the-Sun Road, a major attraction in Glacier National Park, where visitors contribute $344 million to surrounding communities.
- Determine avalanche frequency across multiple spatial scales by incorporating tree ring records, historical observations, and remote sensing (UAS) tools.
- Determine the weather, climate, and snowpack drivers of large magnitude avalanche events and assess variability across multiple spatio-temporal scales and avalanche climates.
- Examine climate and weather drivers to assess a historical and ongoing shift in avalanche character across different spatial extents and avalanche climates.
Methods:
Reconstructing past avalanche frequency using tree-rings - Trees are susceptible to damage from geomorphic processes such as avalanches, and individual trees record the effects of the disturbance in several ways. An avalanche may cause wounds on the tree trunk or branches. It can also locally destroy the cambium (plant cells responsible for plant diameter increasing), causing disruption of new cell formation. As a result, the tree then produces tissue and the cells overgrow the injury forming a “scar” on the tree-ring. Other markers of mechanical disturbance from avalanches in tree ring records include reaction wood (created in response to gravity to push a tree back to a vertical position) and traumatic resin ducts (created after injury to deliver more resin, an antiseptic, to injured part of tree).
We collect cross-sectional wood samples from dead (both downed and standing dead) trees and trunk core samples from live trees. We process, date, and measure tree ring widths using standard procedures, and then process the samples for signs of traumatic impact events likely caused by snow avalanches. Using the resulting avalanche event chronologies, the return periods for each path, sub-region, and entire study site are estimated. Chronologies from the northern Rockies (intermountain avalanche climate) and southeast Alaska (maritime avalanche climate) were previously collected and will be used in this study to examine potential geographic differences in avalanche frequency within the Rocky Mountain cordillera and variability within and between avalanche climates. Finally, we use historical avalanche occurrence records from throughout the study area to assess the tree-ring derived chronology in more recent times.
Atmospheric and climate drivers of large magnitude avalanches - Understanding the spatio-temporal behavior of avalanches and the contributing climate factors is important for understanding climate variability, interpreting historical avalanche variability, and improving avalanche forecasting. We use the reconstructed avalanche chronologies and existing historical datasets as well as climate databases to examine relationships between years of large magnitude avalanche events and climate variables. We will begin by investigating trends in wet snow avalanche frequency throughout the study site using historical observational datasets.
Using remote sensing to examine avalanche and snowpack characteristics - Snow depth varies both among sites and within a season. The amount of weater stored as snow has direct impacts on water availability and flooding that could affect downstream communities. The seasonal evolution of the spatial distribution of snow depth reflects water storage information that is valuable to resource managers and downstream communities concerned about water availability and flooding. Snow distribution data on shorter time scales are necessary for avalanche risk assessment. New methods have been developed to estimate snowpack variability and the amount of water stored in snowpack, using Unmanned Aerial Systems (UASs) and Structure-from-Motion (SfM) photogrammetry. Aerial images of complex alpine terrain were collected in the winter using UAS and high-resolution GPS measurements. These images are then processed using photogrammetry software and programming language platforms to build geo-referenced digital elevation products. A variety of statistical techniques are then employed to assess variability of snow depth change and avalanche frequency across the sites and through time.
We also are exploring use of satellite imagery to detect landscape change due to avalanche disturbance. We are also working on pattern recognition techniques to identify changes in properties of multi-band spectral imagery after the March 2019 historic avalanche cycle in Colorado. In addition, preliminary exploratory analysis shows strong potential for use of historical imagery time series to examine changes in vegetation within and around avalanche paths to provide another measure of avalanche frequency.