Project 2-2
Theme 2

Comparison of ensemble forecast methods for operational streamflow forecasting based on multiple models

Leader:

Dr. François Anctil (Université Laval)
Email:  francois.anctil@gci.ulaval.ca

Co-investigators:

Dr. Bryan Tolson (University of Waterloo)
Email:  btolson@uwaterloo.ca

Dr. Amaury Tilmant (Université Laval)
Email:  amaury.tilmant@gci.ulaval.ca

Objective: Compare the performance and reliability of many probabilistic implementations of operational ensemble streamflow forecasting based on multiple hydrological models.

Significance:  Because models are abstractions of real systems, it cannot be anticipated which specific model offers the greatest accuracy and predictive capability for specific catchments and hydrologic conditions. Multimodel prediction aims to extract as much information as possible from existing models. A multimodel approach emerged as a top priority for a large group of recently interviewed professional flood forecasters (Wetterhall et al., 2013).

Outcomes:  Project 2-2 will identify the advantages and disadvantages of ensemble prediction systems of various complexities.  This outcome will guide Canadian agencies responsible for flood warning in identifying an ensemble prediction system suitable for their needs. It will also guide FloodNet in developing the Canadian Adaptive Flood Forecasting and Early Warning System (Project 3-4).