 |
| Titel |
How are flood risk estimates affected by the choice of return-periods? |
| VerfasserIn |
P. J. Ward, H. Moel, J. C. J. H. Aerts |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1561-8633
|
| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Science ; 11, no. 12 ; Nr. 11, no. 12 (2011-12-07), S.3181-3195 |
| Datensatznummer |
250009825
|
| Publikation (Nr.) |
 copernicus.org/nhess-11-3181-2011.pdf |
|
|
|
|
|
| Zusammenfassung |
| Flood management is more and more adopting a risk based approach, whereby
flood risk is the product of the probability and consequences of flooding.
One of the most common approaches in flood risk assessment is to estimate the
damage that would occur for floods of several exceedance probabilities (or
return periods), to plot these on an exceedance probability-loss curve (risk
curve) and to estimate risk as the area under the curve. However, there is
little insight into how the selection of the return-periods (which ones and
how many) used to calculate risk actually affects the final risk calculation.
To gain such insights, we developed and validated an inundation model capable
of rapidly simulating inundation extent and depth, and dynamically coupled
this to an existing damage model. The method was applied to a section of the
River Meuse in the southeast of the Netherlands. Firstly, we estimated risk
based on a risk curve using yearly return periods from 2 to 10 000 yr
(€ 34 million p.a.). We found that the overall risk is greatly
affected by the number of return periods used to construct the risk curve,
with over-estimations of annual risk between 33% and 100% when only
three return periods are used. In addition, binary assumptions on dike
failure can have a large effect (a factor two difference) on risk estimates.
Also, the minimum and maximum return period considered in the curve affects
the risk estimate considerably. The results suggest that more research is
needed to develop relatively simple inundation models that can be used to
produce large numbers of inundation maps, complementary to more complex
2-D–3-D hydrodynamic models. It also suggests that research into flood risk
could benefit by paying more attention to the damage caused by relatively
high probability floods. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|