Rapid flood risk screening model for compound flood events in Beira, Mozambique

Berchum, Erik C. van; Ledden, Mathijs van; Timmermans, Jos; Kwakkel, Jan H.; Jonkman, Sebastiaan N.

doi:10.5194/nhess-2020-56

Cited by 3 publications

(3 citation statements)

References 13 publications

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“…The riskframework presented ("Setting the scene: Risk-based evaluation of strategies" section) can be applied to any region where multiple coastal risk reduction measures are possible. For example, it has been explored in collaboration with the World Bank to inform the development of a coastal adaptation strategy for Beira, Mozambique (Van Berchum, van Ledden, Timmermans, Kwakkel, & Jonkman, 2020). Since many urbanized areas around the world are developing coastal adaptation strategies, the plans and projects for and from Texas can also inform and inspire other regions.…”

Section: Closing Discussionmentioning

confidence: 99%

Flood risk reduction for Galveston Bay: Preliminary design of a coastal barrier system

Jonkman¹,

Berchum²

2022

Coastal Flood Risk Reduction

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Section: Closing Discussionmentioning

confidence: 99%

Flood risk reduction for Galveston Bay: Preliminary design of a coastal barrier system

Jonkman¹,

Berchum²

2022

Coastal Flood Risk Reduction

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“…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

Najafi

2022

Earth's Future

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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...

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“…Box 1.1: Tropical cyclone Idai -an example of a compound flood event Tropical cyclone (TC) Idai is considered by many scientists as a compound flood event (Emerton et al, 2020;van Berchum et al, 2020) since many flood drivers interacted and exacerbated flood impacts. The event is described here to highlight the elements of a compound flood event.…”

Section: Definitions Of Compound Floodingmentioning

confidence: 99%

The role of (in)dependence in flood risk assessments

Couasnon¹

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Flooding remains the most frequent natural hazard, affecting more people than any other weather-related disasters. The increase in frequency, duration and severity of floods in many parts of the world is projected to rise due to changes in climate, population and land use. Compound flooding, which occurs when multiple flood drivers interact to cause or exacerbate flooding, is a significant challenge in estuarine environments. However, the influence of flood drivers on compound flooding in estuaries remains poorly understood. To address this issue, the goal of this thesis is to improve flood risk assessments in estuarine environments by advancing our understanding and modelling of compound flood hazard. The thesis first identifies potential hotspots of compound flooding at the global scale by analyzing discharge and storm surge time series from state-of-the-art global models. The study is performed at 3,434 river mouths, encompassing all catchments along the coast with an upstream area larger than 1,000 km2. About 6% of the locations are classified as having the highest compound flooding potential. The results show that the dependence between river discharge and storm surge is significant in many areas, including the coasts of Madagascar, northern Morocco, northern Australia, Vietnam, and Taiwan. Furthermore, the study highlights the complex temporal dynamics between discharge and storm surge that cannot be captured by one indicator alone. Next, the thesis develops different probabilistic assessment methods to account for the dependence of flood drivers in flood risk assessment through two case studies. The first case study assesses the impact of the spatial dependence between river discharges and storm surge on the flood hazard quantification for a small catchment in Galveston Bay, Texas. The second case study expands the probabilistic assessment method into a computationally efficient probabilistic framework for calculating flood risk using Ho Chi Minh City as a case study. The framework allows for multiple dependence structures and is applied at a monthly time scale to account for seasonality. Lastly, the thesis moves beyond traditional expected annual damage (EAD) as the indicator of flood risk and discusses the many implications of spatial and temporal dynamics on disaster risk management. The development of plausible storylines and their impact on risk management decisions are explored within a serious game called Breaking the Silos. Breaking the Silos is a collaborative role-playing game designed to explore the impacts of these complexities on risk management decisions. Overall, the thesis provides important insights into the challenges of compound flooding in estuarine environments and proposes new methods to account for these challenges in flood risk assessments. The study highlights the need to include compound flooding in flood hazard assessments in locations where fluvial, pluvial, and coastal interactions are important. The thesis also emphasizes the need for disaster management measures to consider the spatial and temporal dynamics between hazards and their impact on residual risk.

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Rapid flood risk screening model for compound flood events in Beira, Mozambique

Cited by 3 publications

References 13 publications

Flood risk reduction for Galveston Bay: Preliminary design of a coastal barrier system

Flood risk reduction for Galveston Bay: Preliminary design of a coastal barrier system

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

The role of (in)dependence in flood risk assessments

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