Recent Trends in Individual and Multivariate Compound Flood Drivers in Canada's Coasts

Intl Journal of Climatology

Souza

et al. 2023

Self Cite

The concurrent occurrence of extreme events can significantly impact societies and infrastructure systems, especially when the instructions provided to the exposed communities demand conflicting responses. In this study, a probabilistic assessment of concurrent tornado and storm-related flash flood (TORFF) events is performed across southern Canada. We quantify the interdependencies between tornadoes and flash floods (extreme precipitation as proxy) using ground-based and reanalysis datasets. Windspeed values corresponding to tornado events, categorized based on the recorded Fujita rating, are derived through a resampling approach. The TORFF events are clustered and the corresponding bivariate probability distributions of the resampled windspeed and associated precipitation are characterized based on Copula framework. The individual and joint return periods of concurrent tornadoes and flash floods are then assessed under the AND (when both variables exceed predefined thresholds), OR (when either one of the two variables exceeds predefined thresholds), and conditional hazard scenarios across Canada. Results show positive strong dependencies between resampled windspeed and associated precipitation in Saskatchewan, and weaker dependencies followed by Alberta, Manitoba, Ontario, and Quebec. The Saskatchewan region shows the highest risk underestimation considering the independence scenario compared to the other regions. Higher precipitation is also expected during extreme windspeed, as observed in the conditional assessment of precipitation given windspeed. This study provides insights for more robust recurrence interval estimation for tornadoes and flash floods to aid in emergency planning of evacuation decision-making process.

Section: Methodsmentioning

confidence: 99%

Probabilistic assessment of concurrent tornado and storm‐related flash flood events

Ngui

Intl Journal of Climatology

Souza

et al. 2023

Self Cite

“…The names of these locations are provided in Table S3 in Supporting Information S1. Further information is provided in Jalili Pirani and Najafi (2020).…”

Section: Study Area and Datamentioning

confidence: 99%

“…Examples of such events include Hurricane Katrina (2005) affecting south Florida (Johnson, 2006), Hurricane Harvey (2017) in southeast Texas (Frame et al., 2020), both with at least $125 billion in damage, and recent hurricanes of Elsa, and Henri (Eckstein et al., 2021) with $1.2 billion and $550 million in damage respectively. Previous studies have analyzed compound flood events at global (Eilander et al., 2020; Ward et al., 2018), continental (Ganguli & Merz, 2019; Paprotny et al., 2020), national (Ghanbari et al., 2021; Jalili Pirani & Najafi, 2020), and regional scales (Valle‐Levinson et al., 2020; van Berchum et al., 2020) using statistical and process‐based approaches (Hao et al., 2018). These analyses include characterizing the statistical interrelationships between drivers of flooding based on Bayesian networks (Couasnon et al., 2018; Sebastian et al., 2017), copula theory (Bevacqua et al., 2017; Gori et al., 2020; Moftakhari et al., 2017; Paprotny et al., 2018; Xu et al., 2014), bivariate extreme value distributions (Zheng et al., 2014), correlation and linear regression (Robins et al., 2021), bivariate logistic threshold‐excess model (Zheng et al., 2013) among others.…”

Section: Introductionmentioning

confidence: 99%

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

Pirani

2022

Earth's Future

Self Cite

Flooding, as the most common natural hazard in the world (Kundzewicz et al., 2014), has affected more than two billion people and caused approximately USD 656 billion of damage between 1998 and 2017 (AghaKouchak et al., 2020;Wallemacq, 2018). From 1980 to 2019, flood events have accounted for 41% of all the 17,300 weather-related events, 28% of 890,000 lives lost, 27% of USD 4,000 billion economic losses, and 10% of USD 1,300 billion insured losses worldwide (Golnaraghi et al., 2020). The frequency of flood events has been increasing from 1960 to 2013, globally (Tanoue et al., 2016). Similarly, the magnitude of flooding shows increases in some regions around the world (Do et al., 2020). Around 0.8-1.1 million people experience flooding and its devastating socioeconomic consequences each year (Muis et al., 2016), especially the coastal communities. The population of the low-lying coastal areas was approximately 625 million in 2000, which is anticipated to reach 949 million by the 2030s and 1.4 billion by 2060s (Neumann et al., 2015), indicating larger exposure to different Abstract 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 SummaryApproximately 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 multipl...

“…The resultant risk is often significantly underestimated with severe consequences (Bevacqua et al, 2017; Chen et al, 2010; Kumbier et al, 2018). Until present, only a few studies have characterized compound flood hazards using process‐based (Couasnon et al, 2018; Joyce et al, 2018; Kumbier et al, 2018; Serafin et al, 2019; Tang et al, 2013) and statistical methods (Bevacqua et al, 2017; Jalili Pirani & Najafi, 2020; Klerk et al, 2015; Sadegh et al, 2018; van den Hurk et al, 2015; Wahl et al, 2015; Ward et al, 2018), and applied frameworks that combine them together (Lian et al, 2013; Moftakhari et al, 2019; Santiago‐Collazo et al, 2019; Thompson & Frazier, 2014). Thompson and Frazier (2014) studied joint impacts of storm surges, inland precipitation and sea level rise (SLR) over Sarasota County, Florida.…”

Section: Introductionmentioning

confidence: 99%

“…Understanding of compound flooding requires analysis of the effects of heavy rainfall events as well as flooding caused by high coastal water levels and the interactions between river flows and sea levels (Jalili Pirani & Najafi, 2020). Despite successful applications of 2‐D hydrodynamic models in the analysis of individual flood hazards, very few studies have performed a thorough analysis of compound flooding caused by the simultaneous occurrence of multiple flood hazards (i.e., pluvial, riverine, and coastal flooding) and the associated uncertainties and contributions (Bilskie & Hagen, 2018).…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Numerical Modeling of Compound Flooding Caused by Tropical Storm Matthew Over a Data‐Scarce Coastal Environment

Zhang

Water Resources Research

2020

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The passage of a tropical storm, as the main driver of storm surge and high waves in many coastal regions, can also generate heavy rainfall and cause river overflow. The resulting combination of riverine, pluvial, and coastal flood hazard can result in catastrophic losses particularly in densely populated coastal environments. In this study, we characterize compound flooding caused by Tropical Storm Matthew and assess the significance and associated uncertainties of multiple contributing factors over a data-scarce coastal region. A hydrological model combined with a simplified two-dimensional hydrodynamic model are set up and validated to investigate the compounding effects of storm tide, wave runup, rainfall, and river overflow at the southern coast of Saint Lucia in the Caribbean Sea. Pléiades-1 and Sentinel-1 satellite imageries are used to determine the flood-impacted areas. The analyses are performed based on deterministic and probabilistic approaches and the effects of uncertain boundary conditions and model parameters are investigated. Results show that the individual analysis of flood hazards, in isolation, can lead to substantial underestimation of flood risks. Heavy rainfall and wave runup are the most significant contributors to compound flooding in Saint Lucia. In addition, the interactions between seawater and streamflow can exacerbate riverine flood hazards particularly upstream of the river mouth. Communities in western Vieux Fort, and the Hewanorra International Airport, have high exposure to compound flooding, which is projected to intensify under climate change.