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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Discussion papers
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 23 Apr 2019

Research article | 23 Apr 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Hydrology and Earth System Sciences (HESS).

High-resolution hydrometeorological modelling of the June 2013 flood in southern Alberta, Canada

Vincent Vionnet1, Vincent Fortin2, Etienne Gaborit3, Guy Roy2, Maria Abrahamowicz2, Nicolas Gasset3, and John W. Pomeroy1 Vincent Vionnet et al.
  • 1Centre for Hydrology, University of Saskatchewan, Saskatoon, SK, Canada
  • 2Environmental Numerical Research Prediction, Environment and Climate Change Canada, Dorval, QC, Canada
  • 3Environmental Numerical Prediction Development, Meteorological Service of Canada, Environment and Climate Change Canada, Dorval, QC, Canada

Abstract. From June 19 to June 22, 2013, intense rainfall and concurrent snowmelt led to devastating floods in the Canadian Rockies, foothills and downstream areas of southern Alberta and southeastern British Columbia. The complexity of the topography in the mountain headwaters, presence of snow at high elevations and other factors challenged hydrological forecasting of this extreme event. In this study, the ability of the Global Environmental Multi-scale hydrological modelling platform (GEM-Hydro), running at a 1-km grid spacing, to simulate hydrometeorological conditions in several Alberta rivers during this event is assessed. Four quantitative precipitation estimation (QPE) products were generated using the Canadian Precipitation Analysis (CaPA) system by varying (i) station density and (ii) horizontal resolutions (10, 2.5 and 1 km) of the GEM precipitation background. CaPA at 2.5 and 1 km including all available stations in the headwaters provided the most accurate estimation of intensity and total amount of precipitation during the flooding event. Using these products to drive GEM-Hydro, it is shown that QPE accuracy dominates the ability to predict flood volumes. Initial snow conditions also represent a large additional source of uncertainty. Default GEM-Hydro simulations starting with almost no snowpack at high-elevations led to a systematic underestimation of flood volume and peak flow. Gridded estimates of snow water equivalent from the Snow Data Assimilation System (SNODAS) were also considered. They led to contrasting abilities to simulate flood discharge volumes and a consistent overestimation in the headwater catchments, illustrating the strong need for a reference snow product in the mountains of Western Canada. Finally, GEM-Hydro did not predict peak flow timing and hydrograph shape well. Model sensitivity tests show that it could be improved by adjusting the Manning coefficients, suggesting the need to revisit the routing parameters. There may be a need to include water management effects on flood hydrographs as well. These results will guide the development of GEM-Hydro as a hydrological forecasting system in Western Canada.

Vincent Vionnet et al.
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Status: open (extended)
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Vincent Vionnet et al.
Data sets

A multi-scale meteorological dataset of the June 2013 flood in Southern Alberta, Canada V. Vionnet, V. Fortin, E. Gaborit, G. Roy, M. Abrahamowicz, N. Gasset, and J. W. Pomeroy

Vincent Vionnet et al.
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Short summary
This study investigates the ability of the GEM-Hydro modelling platform to simulate hydrometeorological conditions during the 2013 Alberta Flood in Canada. New precipitation datasets at kilometre scale provided the best estimate of cumulative and extreme values of precipitation in the mountain headwaters, translating into improved hydrological simulations. Results also show the importance of accurate initial snow conditions for accurate spring and early summer flood simulation in this region.
This study investigates the ability of the GEM-Hydro modelling platform to simulate...