Project 2-1

Comparison of ensemble forecast methods for operational streamflow forecasting based on a single model

Leader:

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

Co-investigators:

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

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

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

Objective: Compare the performance and reliability of many probabilistic implementations of operational ensemble streamflow forecasting based on a single hydrological model.

Significance: Many Canadian agencies interested in flood forecasting have devoted substantial resources into developing one reasonably accurate, often distributed, hydrologic simulation model of their system that they want to utilize in a formal hydrological ensemble prediction system.  In these cases, agencies are often hesitant to consider multi-model ensemble prediction systems (see Project 2-2 below) and as such this project aims to identify the most robust single model based forecast method.  In particular, the work will focus on calibrating the model to multiple realizations of input forcing data (precipitation and temperature) to identify multiple parameter sets (rather than multiple models) to use in the ensemble forecast.    

Outcomes: Project 2-1 will compare multiple approaches for making ensemble forecasts with a single model.  In addition, we will develop a forecast system evaluation framework customized for how each partner organization will make decisions using an ensemble forecast. This project will also inform the development of CAFFEWS (Project 3-4) on the role of input uncertainty.