Assessing the factors governing the ability to predict late-spring flooding in cold-region mountain basins
2020
Abstract. From 19 to 22 June 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, Canada. Such an event is typical of late-spring floods in cold-region mountain headwater, combining intense precipitation with rapid
melting of late-lying snowpack, and represents a challenge for hydrological
forecasting systems. This study investigated the factors governing the
ability to predict such an event. Three sources of uncertainty, other than
the hydrological model processes and parameters, were considered: (i) the
resolution of the atmospheric forcings, (ii) the snow and soil moisture initial conditions (ICs) and (iii) the representation of the soil texture.
The Global Environmental Multiscale hydrological modeling platform
(GEM-Hydro), running at a 1 km grid spacing, was used to simulate
hydrometeorological conditions in the main headwater basins of southern
Alberta during this event. The GEM atmospheric model and the Canadian
Precipitation Analysis (CaPA) system were combined to generate atmospheric
forcing at 10, 2.5 and 1 km over southern Alberta. Gridded estimates of snow
water equivalent (SWE) from the Snow Data Assimilation System (SNODAS) were used
to replace the model SWE at peak snow accumulation and generate alternative
snow and soil moisture ICs before the event. Two global soil texture
datasets were also used. Overall 12 simulations of the flooding event
were carried out. Results show that the resolution of the atmospheric
forcing affected primarily the flood volume and peak flow in all river
basins due to a more accurate estimation of intensity and total amount of
precipitation during the flooding event provided by CaPA analysis at
convection-permitting scales (2.5 and 1 km). Basin-averaged snowmelt also
changed with the resolution due to changes in near-surface wind and
resulting turbulent fluxes contributing to snowmelt. Snow ICs were the main
sources of uncertainty for half of the headwater basins. Finally, the soil
texture had less impact and only affected peak flow magnitude and timing for
some stations. These results highlight the need to combine atmospheric
forcing at convection-permitting scales with high-quality snow ICs to provide
accurate streamflow predictions during late-spring floods in cold-region mountain river basins. The predictive improvement by inclusion of high-elevation weather stations in the precipitation analysis and the need for
accurate mountain snow information suggest the necessity of integrated
observation and prediction systems for forecasting extreme events in
mountain river basins.
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