A general approach for the estimation of loss of life due to natural and technological disasters

Jonkman, Sebastiaan N.; Lentz, A; Vrijling, J.K.

doi:10.1016/j.ress.2010.06.019

Cited by 29 publications

(18 citation statements)

References 21 publications

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“…While the data presented in BSample data set^section can serve as a basis for identification of risk factors, it is of utmost importance that the amount of data is sufficient relative to the number of parameters in a model (Jonkman et al 2010). The amount of available data determines the detail level in the model used for estimation.…”

Section: Methodsmentioning

confidence: 99%

“…Methods for quantifying fatalities (C f ) General methods for estimating consequences such as loss of life have not been standardized to the same extent as estimations of hazard probabilities (Jonkman et al 2010). Jonkman et al (2010) presented a general approach for estimating loss of life for Blow probability-large consequence^accidents and disasters.…”

Section: Factors Affecting Susceptibility (S F )mentioning

confidence: 99%

“…Jonkman et al (2010) presented a general approach for estimating loss of life for Blow probability-large consequence^accidents and disasters. This general approach includes an assessment of physical effects associated with an event, determination of the number of exposed persons, and determination of the mortality among the exposed population.…”

Section: Factors Affecting Susceptibility (S F )mentioning

confidence: 99%

“…Within the field of risk assessment, methods for estimating hazard probabilities are relatively wellestablished, but when determining risks related to natural hazards, many studies neglect investigating the damage potential or are limited to the assessment of immobile objects such as buildings (Jonkman et al 2010). Landslide risk (R) is usually described as a function of probability and the consequences of a landslide (e.g., Andersson-Sköld et al 2014)…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Assessment of data availability for the development of landslide fatality curves

Grahn

Jaldell

2016

Landslides

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Quick clay landslides are a special feature of Norwegian and Swedish geologies. Vibrations or small initial landslides can cause a quick clay layer to collapse and liquefy, resulting in rapid landslides with little or no time for evacuation, making them a real threat to human life. Research concentrating on damages due to landslides is scarce, and analyses of loss of human lives caused by quick clay landslides in the scientific literature are, to our knowledge, nonexisting. Fatality quantification can complement landslide risk assessments and serves as guidance for policy choices when evaluating efficient risk-reducing measures. The objectives of this study were to assess and analyze available damage information in an existing data set of 66 historical landslide events that occurred in Norway and Sweden between 1848 and 2009, and access its applicability for quantifying loss of human life caused by quick clay landslides. Fatality curves were estimated as functions of the number of exposed persons per landslide. Monte Carlo simulations were used to account for the uncertainties in the number of people actually exposed. The results of the study imply that the quick clay fatality curves are nonlinear, indicating that the probability of losing lives increases exponentially when the number of exposed persons increases. Potential factors affecting human susceptibility to landslides (e.g., landslide-, area-, or individual-specific characteristics) could not be satisfyingly quantified based on available historical records. Future research should concentrate on quantifying susceptibility factors that can further explain human vulnerability to quick clay landslides.

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Section: Methodsmentioning

confidence: 99%

Section: Factors Affecting Susceptibility (S F )mentioning

confidence: 99%

Section: Factors Affecting Susceptibility (S F )mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Assessment of data availability for the development of landslide fatality curves

Grahn

Jaldell

2016

Landslides

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“…This quantitative estimate is usually expressed as a combination of probabilities and consequences derived from a range of possible accident scenarios, which can be used as a basis for cost-benefit analysis. For risk evaluation and decision-making, potential loss of life plays an important role (Jonkman et al 2003(Jonkman et al , 2010. Different damage and loss estimation techniques are used to quantify the potential social and economic losses from an earthquake.…”

Section: Introductionmentioning

confidence: 99%

Impact of Temporal Population Distribution on Earthquake Loss Estimation: A Case Study on Sylhet, Bangladesh

Ara

2014

Int J Disaster Risk Sci

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To estimate human loss in an earthquake-prone area, it is necessary to analyze the role played by the spatiotemporal distribution of the area's resident population. In order to evaluate earthquake impact, this article focuses on the spatiotemporal distribution of population and five scenario earthquakes that form the basis for loss estimation in the city of Sylhet, Bangladesh. Four temporal contexts (weekday, weekly holiday, the 30 days of Ramadan, and strike days) expand the more typical daytime and nighttime settings in which to examine hazard risk. The population distribution for every 2 hour interval in a day is developed for each type of day. A relationship between the occupancy classes and average space (persons per 100 m 2 ) is used to distribute people in each building regardless of building locations. A total daytime and nighttime population is obtained for each building and the estimated nighttime population is used to model the population for four temporal scenarios in a year based on different factors and weights. The resulting data are employed to estimate population loss for each of the temporal and earthquake scenarios. This study used building-specific human vulnerability curves developed by the Central American Probabilistic Risk Assessment (CAPRA) to obtain possible loss of life estimates. The results reveal that there is a high positive correlation between the spatiotemporal distribution of population and the potential number of casualties.

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Cumulative hazard: The case of nuisance flooding

et al. 2017

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The cumulative cost of frequent events (e.g., nuisance floods) over time may exceed the costs of the extreme but infrequent events for which societies typically prepare. Here we analyze the likelihood of exceedances above mean higher high water and the corresponding property value exposure for minor, major, and extreme coastal floods. Our results suggest that, in response to sea level rise, nuisance flooding (NF) could generate property value exposure comparable to, or larger than, extreme events. Determining whether (and when) low cost, nuisance incidents aggregate into high cost impacts and deciding when to invest in preventive measures are among the most difficult decisions for policymakers. It would be unfortunate if efforts to protect societies from extreme events (e.g., 0.01 annual probability) left them exposed to a cumulative hazard with enormous costs. We propose a Cumulative Hazard Index (CHI) as a tool for framing the future cumulative impact of low cost incidents relative to infrequent extreme events. CHI suggests that in New York, NY, Washington, DC, Miami, FL, San Francisco, CA, and Seattle, WA, a careful consideration of socioeconomic impacts of NF for prioritization is crucial for sustainable coastal flood risk management.

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A general approach for the estimation of loss of life due to natural and technological disasters

Cited by 29 publications

References 21 publications

Assessment of data availability for the development of landslide fatality curves

Assessment of data availability for the development of landslide fatality curves

Impact of Temporal Population Distribution on Earthquake Loss Estimation: A Case Study on Sylhet, Bangladesh

Cumulative hazard: The case of nuisance flooding

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