Evaluation of a short-term ensemble water level forecasting system: case of the Chaudière River
- 1Université Laval, Department of Civil and Water Engineering, Canada
- 2Environment and Climate Change Canada (ECCC), Canada
The quality of water level predictions is highly dependent on the success of the flow forecasts that inform the hydraulic model. Ensemble predictions, by considering several sources of uncertainty, provide more accurate and reliable forecasts. In this project, we aim to evaluate a water level ensemble prediction system coupling a hydraulic model to an ensemble streamflow prediction system accounting for 3 sources of uncertainty: meteorological data, hydrological processing (multimodel) and data assimilation to update the initial conditions. The hydraulic model is previously calibrated and validated and the roughness coefficients are adapted as a function of flow according to predefined relationships developed for several river segments. The forecasts reliability and accuracy are then assessed at each layer of the forecasting system and the outcomes are illustrated comparing the ensembles skills and reliability for the considered events. Overall, the results show that accounting of the hydrometeorological uncertainty improves the performances of the water level forecasts for different lead times.
How to cite: Bessar, M. A., Anctil, F., and Matte, P.: Evaluation of a short-term ensemble water level forecasting system: case of the Chaudière River, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8000, https://doi.org/10.5194/egusphere-egu21-8000, 2021.