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Identifying spatial clusters of flood exposure to support decision making in risk management
- Source :
- Röthlisberger, V, Zischg, A P & Keiler, M 2017, ' Identifying spatial clusters of flood exposure to support decision making in risk management ', Science of The Total Environment, vol. 598, pp. 593-603 . https://doi.org/10.1016/j.scitotenv.2017.03.216, Röthlisberger, Veronika; Zischg, Andreas Paul; Keiler, Margreth (2017). Identifying spatial clusters of flood exposure to support decision making in risk management. Science of the total environment, 598, pp. 593-603. Elsevier 10.1016/j.scitotenv.2017.03.216
- Publication Year :
- 2017
-
Abstract
- A sound understanding of flood risk drivers (hazard, exposure and vulnerability) is essential for the effective and efficient implementation of risk-reduction strategies. In this paper, we focus on ‘exposure’ and study the influence of different methods and parameters of flood exposure analyses in Switzerland. We consider two types of exposure indicators and two different spatial aggregation schemes: the density of exposed assets (exposed numbers per km2) and the ratios of exposed assets (share of exposed assets compared to total amount of assets in a specific region) per municipality and per grid cells of similar size as the municipalities. While identifying high densities of exposed assets highlights priority areas for cost-efficient strategies, high exposure ratios can suggest areas of interest for strategies focused on the most vulnerable regions, i.e. regions with a low capacity to cope with a disaster. In Switzerland, the spatial distribution of high exposure densities and exposure ratios tend to be complementary. With regards to the methods, we find that the spatial cluster analysis provides more information for the prioritization of flood protection measures than ‘simple’ maps of spatially aggregated data represented in quantiles. In addition, our study shows that the data aggregation scheme influences the results. It suggests that the aggregation based on grid cells supports the comparability of different regions better than aggregation based on municipalities and is, thus, more appropriate for nationwide analyses.
- Subjects :
- Environmental Engineering
010504 meteorology & atmospheric sciences
Flood risk management
0211 other engineering and technologies
Vulnerability
02 engineering and technology
910 Geography & travel
01 natural sciences
Flood exposure
Prioritization strategies
Spatial cluster analysis
MAUP
550 Earth sciences & geology
Environmental Chemistry
Waste Management and Disposal
Risk management
0105 earth and related environmental sciences
021110 strategic, defence & security studies
Flood myth
business.industry
Comparability
Environmental resource management
Pollution
Hazard
Data aggregator
Modifiable areal unit problem
Environmental science
business
Switzerland
Quantile
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Röthlisberger, V, Zischg, A P & Keiler, M 2017, ' Identifying spatial clusters of flood exposure to support decision making in risk management ', Science of The Total Environment, vol. 598, pp. 593-603 . https://doi.org/10.1016/j.scitotenv.2017.03.216, Röthlisberger, Veronika; Zischg, Andreas Paul; Keiler, Margreth (2017). Identifying spatial clusters of flood exposure to support decision making in risk management. Science of the total environment, 598, pp. 593-603. Elsevier 10.1016/j.scitotenv.2017.03.216 <http://dx.doi.org/10.1016/j.scitotenv.2017.03.216>
- Accession number :
- edsair.doi.dedup.....319bd79c8a9a490f1806a4f2450feb69