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| Titel |
Potential of semi-structural and non-structural adaptation strategies to reduce future flood risk: case study for the Meuse |
| VerfasserIn |
J. K. Poussin, P. Bubeck, J. C. J. H. Aerts, P. J. Ward |
| 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 (2012-11-21), S.3455-3471 |
| Datensatznummer |
250011202
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| Publikation (Nr.) |
 copernicus.org/nhess-12-3455-2012.pdf |
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| Zusammenfassung |
| Flood risk throughout Europe has increased in the last few decades, and is
projected to increase further owing to continued development in flood-prone
areas and climate change. In recent years, studies have shown that adequate
undertaking of semi-structural and non-structural measures can considerably
decrease the costs of floods for households. However, there is little
insight into how such measures can decrease the risk beyond the local level,
now and in the future. To gain such insights, a modelling framework using
the Damagescanner model with land-use and inundation maps for 2000 and 2030
was developed and applied to the Meuse river basin, in the region of
Limburg, in the southeast of the Netherlands. The research suggests that
annual flood risk may increase by up to 185% by 2030 compared with 2000,
as a result of combined land-use and climate changes. The independent
contributions of climate change and land-use change to the simulated
increase are 108% and 37%, respectively. The risk-reduction capacity
of the implementation of spatial zoning measures, which are meant to limit
and regulate developments in flood-prone areas, is between 25% and
45%. Mitigation factors applied to assess the potential impact of three
mitigation strategies (dry-proofing, wet-proofing, and the combination of
dry- and wet-proofing) in residential areas show that these strategies have
a risk-reduction capacity of between 21% and 40%, depending on their
rate of implementation. Combining spatial zoning and mitigation measures
could reduce the total increase in risk by up to 60%. Policy implications
of these results are discussed. They focus on the undertaking of effective
mitigation measures, and possible ways to increase their implementation by
households. |
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