Application and validation of mortality functions to assess the consequences of flooding to people

Mauro, M. Di; Bruijn, K de

doi:10.1111/j.1753-318x.2011.01131.x

Cited by 17 publications

(13 citation statements)

References 19 publications

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“…Jonkman et al (2008) provides a thorough and comprehensive review of these methods as well as describing a new approach. This approach has been further verified by Di Mauro and de Bruijn (2012). Relatively recently, Agent, or Individual, based models have been increasingly developed and applied to support emergency planning and evacuation modelling in relation to floods, BC Hydro (2004), Dawson et al (2011) and, for example.…”

Section: Life Lossmentioning

confidence: 84%

A flood system risk analysis model with dynamic sub-element 2D inundation model, dynamic breach growth and life-loss

Gouldby

Lhomme

McGahey³

et al. 2012

Comprehensive Flood Risk Management

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Risk analysis models of fluvial and coastal flood systems have been in use for over a decade. They have been applied to support a wide range of flood risk management decisions, including long term strategic planning and shorter term asset management. Models that are currently applied in practice make a number of simplifying assumptions. The development of a new model that offers a major improvement over these methods is described. The new model incorporates: a unique dynamic 2D inundation model that captures sub-mesh element topography (RFSM EDA); a new computationally efficient model of embankment breach growth (AREBA) and extends the range of consequences considered to include the loss of life. The model has been applied on a pilot site to demonstrate its capabilities. A flood system risk analysis model with dynamic sub-element 2D inundation model, dynamic breach growth and life-loss

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Section: Life Lossmentioning

confidence: 84%

A flood system risk analysis model with dynamic sub-element 2D inundation model, dynamic breach growth and life-loss

Gouldby

Lhomme

McGahey³

et al. 2012

Comprehensive Flood Risk Management

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“…Three factors refer to flood characteristics. Di Mauro and De Brujn [36] stated that results are largely influenced by the extent of the flooded area, which then raises questions about the simulation of flood hazards. The introduction of a new parameter based on vulnerability may considerably enhance fatality estimation.…”

Section: Limits Of Fatality Assessmentsmentioning

confidence: 99%

Method to Identify the Likelihood of Death in Residential Buildings during Coastal Flooding

Créach¹,

Bastidas‐Arteaga

Pardo

et al. 2022

Buildings

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Tools exist to predict fatalities related to floods, but current models do not focus on fatalities in buildings. For example, Storm Xynthia in France in 2010 resulted in 41 drowning deaths inside buildings. Therefore, there has been increasing recognition of the risk of people becoming trapped in buildings during floods. To identify buildings which could expose their occupants to a risk of death in the case of flooding, we propose the use of the extreme vulnerability index (VIE index), which identifies which buildings are at greatest risk of trapping people during floods. In addition, the “mortality function method” is used to further estimate the expected number of fatalities based on (1) groups of vulnerable people (e.g., aged or disabled), (2) the location of buildings in relation to major watercourses, and (3) the configuration of buildings (e.g., single or multiple entries and single or multiple stories). The overall framework is derived from case studies from Storm Xynthia which give a deterministic approach for deaths inside buildings for coastal floods, which is suited for low-lying areas protected by walls or sandy barriers. This methodology provides a tool which could help make decisions for adaptation strategy implementation to preserve human life.

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“…There is a need to have systematic techniques that can predict flood based on those causes which can avoid from any catastrophic disaster to human population [5][6]. Recent research had shown that data mining techniques had gained its popularity and had been used in predicting flood [7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

A comparative analysis of classification techniques on predicting flood risk

Nawi

Makhtar

Salikon

et al. 2020

IJEECS

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Flood is a temporary overflow of a dry area due to overflow of excess water, runoff surface waters or undermining of shoreline. In Malaysia itself in 2014, the country grieved with the catastrophic flood event in Kuala Krai, Kelantan, which caused of human lives, public assets and money lost. Due to uncertainties in flooding event, it is vital for Malaysia to have pre-warning system that assist related agencies in to categorize land areas that face high risk of flood so preventive actions can be planned in place. This paper conducts a comparative analysis of three classifications in classifying the risk of flood, whether high or low. The classification experiment conducts using three variants of Bayesian approaches, which are Bayesian Networks (BN), Naive Bayes (NB), and Tree Augmented Naive Bayes (TAN). The outcome of this research shows that Tree Augmented Naive Bayes (TAN) has the best algorithms as compared to others algorithms in classifying the risk of flood.

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Application and validation of mortality functions to assess the consequences of flooding to people

Cited by 17 publications

References 19 publications

A flood system risk analysis model with dynamic sub-element 2D inundation model, dynamic breach growth and life-loss

A flood system risk analysis model with dynamic sub-element 2D inundation model, dynamic breach growth and life-loss

Method to Identify the Likelihood of Death in Residential Buildings during Coastal Flooding

A comparative analysis of classification techniques on predicting flood risk

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