1  Avalanche  release  zone  information  such  as  location,  extent  and 
release  height  are  essential  for  avalanche  mitigation measure planning.
2 However, the identification of release areas is a very difficult task as the
release mechanism of snow avalanches depends on many different terrain,
meteorological, snowpack and triggering parameters and their interactions.
3 Furthermore, nearly no information on avalanche release areas exists in
many alpine regions, such as the Indian Himalaya, mainly due to the very
rough and poorly accessible terrain, the vast size of the region and the lack
of avalanche records.  4  Thus, avalanche release information is urgently
required for numerical simulation of avalanche events to plan mitigation
measures, for hazard mapping and to secure important roads, such as the
Rohtang tunnel access road near Manali, India. 5 By far the most reliable
way to identify avalanche release areas is using historic avalanche records
and field investigations accomplished by avalanche experts in the formation
zones. 6 However, neither of these methods is feasible for this area due to
the rough terrain, its vast extent and lack of time. 7 Therefore, we have
developed an operational, easy-to-use automated potential release area
(PRA) detection tool in Python/ArcGIS. 8 This tool uses high spatial
resolution digital elevation models (DEMs) and forest cover information
derived from airborne remote sensing instruments as input. 9 Such
instruments can acquire spatially continuous data even over inaccessible
terrain and cover large areas. 10 The tool was validated using a database
of historic avalanches acquired over 56 years in Davos, Switzerland, and
apply this method for the avalanche tracks along the Rohtang tunnel
access road. 11 This tool, used by avalanche experts, delivers valuable input
to identify focus areas for more detailed investigations on avalanche release
areas in remote regions, such as the Indian Himalaya. In addition, it is a
precondition for large-scale avalanche hazard mapping.

Last modified: Wednesday, 8 March 2023, 8:47 AM