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Atmospheric reanalysis data provides a numerical description of global and regional water cycles by combining models and observations. These datasets are increasingly valuable as a substitute for observations in regions where these are scarce. They could significantly contribute to reducing losses by feeding flood early warning systems that can inform the population and guide civil security action. We assessed the suitability of two different precipitation and temperature reanalysis products readily available for predicting historic flooding of the La Chaudière River in Quebec: 1) Environment and Climate Change Canada's Regional Deterministic Reanalysis System (RDRS-v2) and 2) ERA5 from the Copernicus Climate Change Service. We exploited a multi-model hydrological ensemble prediction system that considers three sources of uncertainty: initial conditions, model structure, and weather forcing to produce streamflow forecasts up to 5 days into the future with a time step of 3 hours. These results are compared to a provincial reference product based on gauge measurements of the Ministère de l'Environnement et de la Lutte contre les Changements Climatiques. Then, five conceptual hydrological models were calibrated with three different meteorological datasets (RDRS-v2, ERA5, and observational gridded) and fed with two ensemble weather forecast products: 1) the Regional Ensemble Prediction System (REPS) from the Environment and Climate Change Canada and 2) the ensemble forecast issued by the European Centre for Medium-Range Weather Forecasts (ECMWF). Results reveal that the calibration of the model with reanalysis data as input delivered a higher accuracy in the streamflow simulation providing a useful resource for flood modeling where no other data is available. However, although the selection of the reanalysis is a determinant of capturing the flood volumes, selecting weather forecasts is more critical in anticipating discharge threshold exceedances.
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A flood frequency analysis is conducted using instantaneous peak flow data over a hydrologic sub-region of southern Québec following three distinct methodological frameworks. First, the analysis is conducted locally using available instantaneous peak flow data. Second, the analysis is conducted locally using daily peak flow data processed to consider the peak flow effect. Third, a regional frequency analysis is conducted pooling all available instantaneous peak flow data over the study area. Results reveal a notable diversity in the resulting recurrence peak flow estimates and related uncertainties from one analysis to another. Expert judgement appears essential to arbitrate which alternative should be operated considering a specific context of application for flood plain delineation. Pros and cons for each approach are discussed. We finally encourage the use of a diversity of approaches to provide a robust assessment of uncertainty affecting peak flow estimates.