Multivariate Analysis of Compound Flood Hazard Across Canada's Atlantic, Pacific and Great Lakes Coastal Areas

• Published in: Earth's future 2022-08, Vol.10 (8), p.n/a
• Main Authors: Jalili Pirani, Farshad, Najafi, Mohammad Reza
• Format: Article
• Language: English
• Subjects: Bayes Theorem; Bayesian analysis; Canada; CHR index; Coastal flooding; Coastal management; Coastal storms; Coastal structures; Coastal zone; Coasts; compound flooding; Environmental risk; Extreme weather; failure probability; Flood control; Flood hazards; Flood management; Flood risk; Flooding; Floods; Hazard assessment; Hurricanes; Insured losses; join return period; Lakes; Multivariate analysis; Precipitation; Rain; Sea level; Storm damage; Storm tides; Stream flow; Tidal waves; trivariate extreme analysis; vine copula; Weather
• ISSN: 2328-4277; 2328-4277
• DOI: 10.1029/2022EF002655

Compound flooding, caused by the simultaneous or successive occurrence of two or more flood mechanisms, is mainly associated with extreme precipitation, river overflows, and storm tides across coastal areas. The interdependencies between these components can increase the risks of flood impacts, threatening coastal communities and infrastructure systems. This study quantifies the corresponding multivariate hazard over Canada's coastal areas by characterizing the dependencies between multiple drivers of flooding based on the C‐vine copula statistical approach. The joint return periods of compound flooding considering the AND, OR, and Kendall scenarios are estimated and the corresponding failure probabilities are assessed. Further, the compound hazard ratio (CHR) index is applied to quantify possible under‐ or overestimations of the flood hazards when individual drivers are assessed independently. Analyses are performed at 41 locations across the Atlantic, Pacific, and the Great Lakes coasts, and the uncertainties are quantified based on the Bayes theorem. Results show that at approximately 50% of locations (mostly at the Great Lakes), the flood hazard associated with the AND scenario increases considerably when the dependencies are characterized compared to the (unrealistic) independence scenario, indicating the potential for compound flooding in these regions. Besides, at more than half of the studied locations, the CHR index exceeds one highlighting the interrelationships between drivers of flooding. The results of this study provide a deeper understanding of the flood mechanisms and their interdependencies across Canada's coasts, which support the development of resilient structures and improved coastal flood management. Plain Language Summary Approximately half of the global population lives within 200 km of coastlines. The communities and infrastructure systems in the coastal environments are at risk of flooding caused by one or multiple mechanisms. Understanding the compounding effects of the drivers of flooding and quantifying the corresponding uncertainties are critical for flood risk analysis and the development of effective resilience strategies. To address this objective, we investigate compound flood events considering terrestrial (both precipitation, and streamflow which reflects the effects of snow/ice melt in addition to rainfall) and coastal mechanisms across Canada's Atlantic, Pacific and Great Lakes' coasts, with distinct hydroclimate chara