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The potential impacts of floods are of significant concern to our modern society raising the need to identify and quantify all the uncertainties that can impact their simulations. Climate simulations at finer spatial resolutions are expected to bring more confidence in these hydrological simulations. However, the impact of the increasing spatial resolutions of climate simulations on floods simulations has to be evaluated. To address this issue, this paper assesses the sensitivity of summer–fall flood simulations to the Canadian Regional Climate Model (CRCM) grid resolution. Three climate simulations issued from the fifth version of the CRCM (CRCM5) driven by the ERA-Interim reanalysis at 0.44°, 0.22° and 0.11° resolutions are analysed at a daily time step for the 1981–2010 period. Raw CRCM5 precipitation and temperature outputs are used as inputs in the simple lumped conceptual hydrological model MOHYSE to simulate streamflows over 50 Quebec (Canada) basins. Summer–fall flooding is analysed by estimating four flood indicators: the 2-year, 5-year, 10-year and 20-year return periods from the CRCM5-driven streamflows. The results show systematic impacts of spatial resolution on CRCM5 outputs and seasonal flood simulations. Floods simulated with coarser climate datasets present smaller peak discharges than those simulated with the finer climate outputs. Smaller catchments show larger sensitivity to spatial resolution as more detail can be obtained from the finer grids. Overall, this work contributes to understanding the sensitivity of streamflow modelling to the climate model’s resolution, highlighting yet another uncertainty source to consider in hydrological climate change impact studies.
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AbstractA snow model forced by temperature and precipitation is used to simulate the spatial distribution of snow water equivalent (SWE) over a 600,000 km2 portion of the province of Quebec, Canada. We propose to improve model simulations by assimilating SWE data from sporadic manual snow surveys with a particle filter. A temporally and spatially correlated perturbation of the meteorological forcing is used to generate the set of particles. The magnitude of the perturbations is fixed objectively. First, the particle filter and direct insertion were both applied on 88 sites for which measured SWE consist of more or less five values per year over a period of 17 years. The temporal correlation of perturbations enables to improve the accuracy and the ensemble dispersion of the particle filter, while the spatial correlation lead to a spatial coherence in the particle weights. The spatial estimates of SWE obtained with the particle filter are compared with those obtained through optimal interpolation of the sno...