5.6 Improving Snow Pack Analysis for Flood Forecasting and Early Warnings—Lessons Learned from the June 2013 Southern Alberta Flood

Tuesday, 8 January 2019: 11:45 AM
North 126BC (Phoenix Convention Center - West and North Buildings)
Anthony Liu, Environment and Climate Change Canada, Edmonton, AB, Canada; and C. Mooney, K. Szeto, J. M. Thériault, B. Kochtubajda, R. E. Stewart, S. Boodoo, R. Goodson, Y. Li, and J. W. Pomeroy

Snowmelt is an important source of water supply, and under certain weather conditions, can play a significant role in triggering severe downstream flooding. The 2013 southern Alberta flood event which occurred downstream of the Canadian Rockies is the second costliest natural disaster in Canadian history, and snowmelt from the Canadian Rockies was a significant contributor. In this study, we investigate snowmelt contributions by examining changes in snow pack during the flooding period using various sources, including surface and satellite observations and model reanalysis datasets. We also analyzed the synoptic-scale weather conditions that led to the intense precipitation and snowmelt associated with this event. The analysis from all data sources show that significant snow packs existed before the flood, and snowmelt contributed to the runoff. High freezing levels supported rain falling on snow over mountainous areas, which likely led to additional runoff. Observations from neighbouring mountain stations within the Marmot Creek research basin were significantly different preceding and during the event, which illustrates the complexity of snowmelt processes in complex terrain. Due to the mutual interaction of multiple factors, including precipitation phase and amounts, temperature, wind and variations in solar radiation, data from the current snow pack observation network is inadequate to quantify enhanced snowmelt at the basin scale for flood risk assessment. The results from this study indicate that an enhanced snow pack analysis for the Canadian Rockies is necessary to improve future flood forecasting and early warnings.
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