Vulnerability of Russian regions to natural risk: experience of quantitative assessment

One of the important tracks leading to natural risk prevention, disaster mitigation or the reduction of losses due to natural hazards is the vulnerability assessment of an 'at-risk' region. The majority of researchers propose to assess vulnerability according to an expert evaluation of sev...

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Main Author: E. Petrova
Format: Article
Language:English
Published: Copernicus Publications 2006-01-01
Series:Natural Hazards and Earth System Sciences
Online Access:http://www.nat-hazards-earth-syst-sci.net/6/49/2006/nhess-6-49-2006.pdf
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spelling doaj-6251aa1774cc4053af370ea17d7d6b012020-11-24T23:38:56ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812006-01-01614954Vulnerability of Russian regions to natural risk: experience of quantitative assessmentE. PetrovaOne of the important tracks leading to natural risk prevention, disaster mitigation or the reduction of losses due to natural hazards is the vulnerability assessment of an 'at-risk' region. The majority of researchers propose to assess vulnerability according to an expert evaluation of several qualitative characteristics, scoring each of them usually using three ratings: low, average, and high. Unlike these investigations, we attempted a quantitative vulnerability assessment using multidimensional statistical methods. Cluster analysis for all 89 Russian regions revealed five different types of region, which are characterized with a single (rarely two) prevailing factor causing increase of vulnerability. These factors are: the sensitivity of the technosphere to unfavorable influences; a 'human factor'; a high volume of stored toxic waste that increases possibility of NDs with serious consequences; the low per capita GRP, which determine reduced prevention and protection costs; the heightened liability of regions to natural disasters that can be complicated due to unfavorable social processes. The proposed methods permitted us to find differences in prevailing risk factor (vulnerability factor) for the region types that helps to show in which direction risk management should focus on.http://www.nat-hazards-earth-syst-sci.net/6/49/2006/nhess-6-49-2006.pdf
collection DOAJ
language English
format Article
sources DOAJ
author E. Petrova
spellingShingle E. Petrova
Vulnerability of Russian regions to natural risk: experience of quantitative assessment
Natural Hazards and Earth System Sciences
author_facet E. Petrova
author_sort E. Petrova
title Vulnerability of Russian regions to natural risk: experience of quantitative assessment
title_short Vulnerability of Russian regions to natural risk: experience of quantitative assessment
title_full Vulnerability of Russian regions to natural risk: experience of quantitative assessment
title_fullStr Vulnerability of Russian regions to natural risk: experience of quantitative assessment
title_full_unstemmed Vulnerability of Russian regions to natural risk: experience of quantitative assessment
title_sort vulnerability of russian regions to natural risk: experience of quantitative assessment
publisher Copernicus Publications
series Natural Hazards and Earth System Sciences
issn 1561-8633
1684-9981
publishDate 2006-01-01
description One of the important tracks leading to natural risk prevention, disaster mitigation or the reduction of losses due to natural hazards is the vulnerability assessment of an 'at-risk' region. The majority of researchers propose to assess vulnerability according to an expert evaluation of several qualitative characteristics, scoring each of them usually using three ratings: low, average, and high. Unlike these investigations, we attempted a quantitative vulnerability assessment using multidimensional statistical methods. Cluster analysis for all 89 Russian regions revealed five different types of region, which are characterized with a single (rarely two) prevailing factor causing increase of vulnerability. These factors are: the sensitivity of the technosphere to unfavorable influences; a 'human factor'; a high volume of stored toxic waste that increases possibility of NDs with serious consequences; the low per capita GRP, which determine reduced prevention and protection costs; the heightened liability of regions to natural disasters that can be complicated due to unfavorable social processes. The proposed methods permitted us to find differences in prevailing risk factor (vulnerability factor) for the region types that helps to show in which direction risk management should focus on.
url http://www.nat-hazards-earth-syst-sci.net/6/49/2006/nhess-6-49-2006.pdf
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