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| Titel |
Local scale multiple quantitative risk assessment and uncertainty evaluation in a densely urbanised area (Brescia, Italy) |
| VerfasserIn |
S. Lari, P. Frattini, G. B. Crosta |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Science ; 12, no. 11 ; Nr. 12, no. 11 (2012-11-20), S.3387-3406 |
| Datensatznummer |
250011197
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| Publikation (Nr.) |
 copernicus.org/nhess-12-3387-2012.pdf |
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| Zusammenfassung |
The study of the interactions between natural and anthropogenic risks is
necessary for quantitative risk assessment in areas affected by active
natural processes, high population density and strong economic activities.
We present a multiple quantitative risk assessment on a 420 km2 high
risk area (Brescia and surroundings, Lombardy, Northern Italy), for flood,
seismic and industrial accident scenarios. Expected economic annual losses
are quantified for each scenario and annual exceedance probability-loss
curves are calculated. Uncertainty on the input variables is propagated by
means of three different methodologies: Monte-Carlo-Simulation, First Order
Second Moment, and point estimate.
Expected losses calculated by means of the three approaches show similar
values for the whole study area, about 64 000 000 € for earthquakes, about
10 000 000 € for floods, and about 3000 € for industrial accidents.
Locally, expected losses assume quite different values if calculated with
the three different approaches, with differences up to 19%.
The uncertainties on the expected losses and their propagation, performed
with the three methods, are compared and discussed in the paper. In some
cases, uncertainty reaches significant values (up to almost 50% of the
expected loss). This underlines the necessity of including uncertainty in
quantitative risk assessment, especially when it is used as a support for
territorial planning and decision making. The method is developed thinking
at a possible application at a regional-national scale, on the basis of data
available in Italy over the national territory. |
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