Risk assessment of natural hazards: Data availability and applicability for loss quantification
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]
Quantitative risk assessments are a fundamental part of economic analysis and natural hazard risk management models. It increases the objectivity and the transparency of risk assessments and guides policymakers in making efficient decisions when spending public resources on risk reduction. Managing hazard risks calls for an understanding of the relationships between hazard exposure and vulnerability of humans and assets.
The purpose of this thesis is to identify and estimate causal relationships between hazards, exposure and vulnerability, and to evaluate the applicability of systematically collected data sets to produce reliable and generalizable quantitative information for decision support.
Several causal relationships have been established. For example, the extent of lake flood damage to residential buildings depends on the duration of floods, distance to waterfront, the age of the house and in some cases the water level. Results also show that homeowners private initiative to reduce risk, prior to or during a flood, reduced their probability of suffering building damage with as much as 40 percent. Further, a causal relationship has been established between the number of people exposed to quick clay landslides and landslide fatalities.
Even though several relationships were identified between flood exposure and vulnerability, the effects can only explain small parts of the total variation in damages, especially at object level. The availability of damage data in Sweden is generally low. The most comprehensive damage data sets in Sweden are held by private insurance companies and are not publicly available. Data scarcity is a barrier to quantitative natural hazard risk assessment in Sweden. More efforts should therefore be made to collect data systematically for modelling and validating standardized approaches to quantitative damage estimation.
Abstract [en]
Natural hazard damages have increased worldwide. Impacts caused by hydrological and meteorological hazards have increased the most. An analysis of insurance payments in Sweden showed that flood damages have been increasing in Sweden as well. With climate change and increasing populations we can expect this trend to continue unless efforts are made to reduce risk and adapt communities to the threats. Economic analysis and quantitative risk assessments of natural hazards are fundamental parts of a risk management process that can support policymakers' decisions on efficient risk reduction. However, in order to develop reliable damage estimation models knowledge is needed of the relationships between hazard exposure and the vulnerability of exposed objects and persons. This thesis has established causal relationships between residential exposure and flood damage on the basis of insurance data. I also found that private damage-reducing actions decreased the probability of damage to buildings with almost 40 percent. Further, a causal relationship has been established between the number of people exposed to quick clay landslides and fatalities. Even though several relationships have been identified between flood exposure and vulnerability, the effects can explain only small parts of the total variation in damages, especially at object level, and more effort is needed to develop quantitative models for risk assessment purposes.
Place, publisher, year, edition, pages
Karlstad: Karlstads universitet, 2017. , p. 79
Series
Karlstad University Studies, ISSN 1403-8099 ; 16
Keywords [en]
flood, landslide, damage, damage function, cost-benefit, decision support, causal relationship
National Category
Other Social Sciences
Research subject
Risk and Environmental Studies
Identifiers
URN: urn:nbn:se:kau:diva-48324ISBN: 978-91-7063-773-5 (print)ISBN: 978-91-7063-774-2 (electronic)OAI: oai:DiVA.org:kau-48324DiVA, id: diva2:1089652
Public defence
2017-06-02, 1B364, Frödingsalen, Karlstad, 10:00 (English)
Opponent
Supervisors
2017-05-122017-04-202022-11-23Bibliographically approved
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