How Sask. researchers cracked the code of predicting Rocky Mountain snowpack
Researchers dig down into the snow to compare data taken using drones at the Fortress Basin research site. (Phillip Harder)
SASKATOON -- University of Saskatchewan scientists have developed a way to predict the depth and movement of snowpacks in the Canadian Rocky Mountains, the school announced on Monday.
This will provide valuable information on spring runoff, risk of flooding, avalanche danger and the effects of climate change, according to a news release.
“Snow in the Canadian Rockies accounts for 60 per cent of the flow of the South Saskatchewan River and three-quarters of the province relies on it for drinking water, for irrigation, for potash mining and other industries,” said John Pomeroy, Canada Research Chair in Water Resources and Climate Change and professor in the U of S Department of Geography and Planning.
“The rivers in Saskatchewan really are the lifeblood of the province.”
Run on supercomputers, the Canadian Hydrological Model (CHM) crunches detailed data on snow distribution by wind and avalanches, shading by mountains, wind flow over ridges, and vegetation, along with weather forecasts, to generate an estimate of where and how much snow has accumulated in a given area.
The researchers used their model to predict the amount of snowpack in a 1,000-square kilometre area of the southern Kananaskis Valley, in the Canadian Rockies. Their results, published in mid-February in the journal The Cryosphere, were a close match with snow depth data collected by a team of scientists at the University of British Columbia using laser measurements taken by airplane.
High-resolution snow cover data captured by satellite and processed by a lab at University of Toulouse in France confirmed the results.
The team has created a demonstration website called Snowcast which uses their model to generate nearly real-time estimates of snowpack for a section of the Bow Valley starting just west of Calgary and running up to Lake Louise and Field.