Project 2-4

Evaluation of flood warning based on a hydraulic model with assimilation and hydrological ensemble forecasts

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. Aaron Berg (University of Guelph)
Email:  aberg@uoguelph.ca

Dr. Paulin Coulibaly (McMaster University)
Email:  couliba@mcmaster.ca

Objective: Explore flood warning based on a hydraulic model with assimilation and hydrological ensemble forecasts, extending the hydrological ensemble prediction system tested in Project 2-2, with an additional vertical component.

Significance:  Flood warning relies on threshold-based decision rules that prescribe actions when streamflow exceeds a predefined value. In a deterministic world, the decision to act on forecast information is often guided by experience, especially when water levels are close to a threshold. It is then strictly up to decision makers to interpret the situation based on a qualitative appreciation of the uncertainty (experience). In a probabilistic world, access to a predictive distribution allows a better appreciation of the risks since the probability of exceeding a threshold may be estimated to be, for example, 20% or 70%.

Outcomes:  Project 2-4 will extend hydrological ensemble forecasts by issuing a distribution of water level forecasts at each time step.