Canada-wide Modelling – Analysis of Model Accuracy to Drive Appropriate Use and Risk Reduction Program Development

In many countries, continental and global scale flood hazard modelling methodologies are employed to provide an understanding of flood hazard over large geographical areas and at multiple return periods, flood generating mechanisms, and future climate change scenarios.  These models are commonly used for estimating flood hazard in areas where high resolution flood mapping is unavailable, and for estimating portfolio risk for insurers and the financial sector. However, these products are generally lower accuracy and precision than local (e.g. regulatory, engineering-level) maps, and therefore the limitations and appropriate use cases of continental and global scale mapping should be understood when using these products to understand flood hazard and flood risk.  

Public Safety Canada (PS) has the mandate to keep Canadians safe from a range of risks and is working towards several soon-to-be launched flood resilience policy programs that depend upon a consistent, Canada-wide characterization of flood risk, and has accordingly procured multiple flood hazard models. PS bridges policy work to data science and engineering practices by conducting quantitative risk analysis, using Canada-wide flood hazard models, robust exposure data, and damage estimation methodologies. 

PS has done extensive testing of Canada-wide flood hazard models, including quality control and evaluation, to better understand their limitations and uses, and to support quantitative risk analysis for PS and other federal departments and agencies. This presentation will describe the results of PS’s evaluation and use of global models, including performance assessment against a set of comparable regulatory-quality flood maps across Canada and recommendations for appropriate use cases. These findings will contribute to a future partnership between PS and an academic research consortium to develop a made-in-Canada, open source, Canada-wide flood hazard model that will leverage data and expertise developed across government and other sectors.