Large variance and fat tail of damage by natural disaster

Hang Hyun Jo, Yu Li Ko

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

In order to account for large variance and fat tail of damage by natural disaster, we study a simple model by combining distributions of disaster and population/property with their spatial correlation. We assume fat-tailed or power-law distributions for disaster and population/property exposed to the disaster, and a constant vulnerability for exposed population/property. Our model suggests that the fat tail property of damage can be determined either by that of disaster or by those of population/property depending on which tail is fatter. It is also found that the spatial correlations of population/property can enhance or reduce the variance of damage depending on how fat the tails of population/property are. In case of tornadoes in the United States, we show that the damage does have fat tail property. Our results support that the standard cost-benefit analysis would not be reliable for social investment in vulnerability reduction and disaster prevention.

Original languageEnglish
Title of host publicationVulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014
EditorsMichael Beer, Siu-Kui Au, Jim W. Hall
PublisherAMERICAN SOCIETY OF CIVIL ENGINEERS
Pages2744-2753
Number of pages10
ISBN (Electronic)9780784413609
DOIs
Publication statusPublished - 2014
MoE publication typeA4 Article in a conference publication
Event2nd International Conference on Vulnerability and Risk Analysis and Management, (ICVRAM) and the 6th International Symposium on Uncertainty Modeling and Analysis (ISUMA) - Liverpool, United Kingdom
Duration: 13 Jul 201416 Jul 2014

Conference

Conference2nd International Conference on Vulnerability and Risk Analysis and Management, (ICVRAM) and the 6th International Symposium on Uncertainty Modeling and Analysis (ISUMA)
Country/TerritoryUnited Kingdom
CityLiverpool
Period13/07/201416/07/2014

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