Social and economic factors of the natural risk increasing: estimation of the Russian regions

This study is an attempt to assess quantitatively social and economic factors that determine vulnerability of Russian regions to natural risk, to trace the space differences of the considered factors, and to group the regions by their similarity. In order to indicate the regional differences in social and economic development, equipment condition, dangerous substances accumulation, and social trouble four the most suitable parameters were estimated, including the per capita production of Gross Regional Product (GRP), capital consumption, volume of total toxic waste, and crime rate. Increase of the first parameter causes vulnerability reducing, the increase of the last three causes its increasing. Using multidimensional cluster analysis five types of regions were found for Russia according to similarity of the considered parameters. These types are characterized with higher value of a single (rarely two) chosen parameter, which seems to be sufficient enough to affect natural risks increasing in these regions in near future. Only few regions belonging to the fifth type proved to have rather high value of GRP and relatively low values of the other parameters. The negative correlation was found between a number of natural disasters (ND) and the per capita GRP in case when some parameters reached anomalously high value. The distinctions between regions by prevailing different parameters, which result in natural risk increasing, help risk management to find directions where to focus on

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

International audienceOne 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