Jordy Hendrikx

On optimal stability test spacing for assessing snow avalanche conditions

Assessing snow stability requires a holistic approach, relying on avalanche, snowpack and weather observations. Part of this assessment utilizes stability tests, but these tests can be unreliable due in part to the spatial variability of test results. Conducting more than one test can help to mitigate this uncertainty, though it is unclear how far apart to space tests to optimize our assessments. To address this issue we analyze the probability of sampling two relatively strong test results over 25 spatial datasets collected using a variety of stability tests. Our results show that the optimal distance for spacing stability tests varies by dataset, even when taking the sampling scheme and stability-test type into account. This suggests that no clear rule currently exists for spacing stability tests. Our work further emphasizes the spatial complexity of snow stability measurements, and the need for holistic stability assessments where stability tests are only one part of a multifaceted puzzle.

Developing Climate Change Maps for Tourism Essential Information or Awareness Raising

Climate change adaptation is a pressing need. However, local level stakeholders often find themselves overwhelmed with climate change information presented at both small temporal and spatial scales. To address this gap, and using a case study from New Zealand’s Southern Lakes region, this research links tourism operators’ information requirements with climate change projections. Interviews with 42 stakeholders provided exemplary storylines and insights into the climate parameters that would be useful for their planning (mean precipitation, extreme wind conditions, mean temperature, and frost days). These findings were then used to generate sector-relevant maps. Climate change maps were produced based on global and regional models to generate detailed climate projection information for the A2 emission scenario in the form of regional scale, color-coded maps. A final stakeholder workshop confirmed the usefulness of the maps as a planning tool but also highlighted a number of future challenges for climate change communication.

ASSESSING THE IMPORTANCE OF TERRAIN PARAMETERS ON GLIDE AVALANCHE RELEASE

Glide snow avalanches are dangerous and difficult to predict. Despite recent research there is still a lack of understanding regarding the controls of glide avalanche release. Glide avalanches often occur in similar terrain or the same locations annually and observations suggest that specific topog- raphy may be critical. Thus, to gain an understanding of the terrain component of these types of ava- lanches we examined terrain parameters associated with glide avalanche release and compared to avalanche starting zones where no glide avalanches were observed (i.e. non-glide avalanche terrain). Glide avalanche occurrences visible from the Going-to-the-Sun Road corridor in Glacier National Park, Montana from 2003-2013 are investigated using an avalanche database derived of daily observations each year from April 1 to June 15. This yielded 192 glide avalanches in 53 distinct avalanche paths. Each avalanche was digitized in a GIS using satellite, oblique, and aerial imagery as reference. A smaller set of 31 non-glide avalanche starting zones were also selected in this manner. Topographical parameters such as area, slope, aspect, incoming solar radiation, distance from ridge, and elevation were then derived for the entire dataset utilizing tools with a GIS and a 10 m DEM. Surface roughness and a glide factor were calculated using a four level classification index and a land surface type layer in a GIS. For this study area, glide avalanches released at elevations ranging from 1300 to 2700 m with a mean aspect of 98 degrees (east) and a mean slope angle of 38 degrees. A total of 26 terrain variables were examined using a univariate analysis between areas where glide avalanches occurred and areas where glide avalanches were never observed, despite crack formation. Only three variables were not significant- ly different. The significantly different variables were then used to train a classification tree to distinguish between glide and non-glide avalanche terrain. The 10-fold cross validated tree resulted in two branches. The nodes split on maximum slopes and glide factor. This tree was then completed without cross- validation for exploratory purposes and results show maximum slope, mean aspect, and daily solar radia- tion to be important variables for distinguishing between glide avalanche and non-glide avalanche terrain. Finally, the results of the cross-validated tree will be used in a GIS to examine other areas of potential glide avalanche release within Glacier National Park. Using this understanding of the role of topographic parameters on glide avalanche activity, a spatial terrain based model will be developed to identify other areas with high glide avalanche potential outside of our immediate observation area.