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| Titel |
Distribution of uncertainties at the municipality level for flood risk modelling along the river Meuse: implications for policy-making |
| VerfasserIn |
Michel Pirotton, Frédéric Stilmant, Sébastien Erpicum, Benjamin Dewals, Pierre Archambeau |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250135935
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| Publikation (Nr.) |
 EGU/EGU2016-16860.pdf |
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| Zusammenfassung |
| Flood risk modelling has been conducted for the whole course of the river Meuse in Belgium.
Major cities, such as Liege (200,000 inh.) and Namur (110,000 inh.), are located in the
floodplains of river Meuse. Particular attention has been paid to uncertainty analysis and its
implications for decision-making.
The modelling chain contains flood frequency analysis, detailed 2D hydraulic
computations, damage modelling and risk calculation. The relative importance of each source
of uncertainty to the overall results uncertainty has been estimated by considering several
alternate options for each step of the analysis: different distributions were considered in the
flood frequency analysis; the influence of modelling assumptions and boundary conditions
(e.g., steady vs. unsteady) were taken into account for the hydraulic computation; two
different landuse classifications and two sets of damage functions were used; the number of
exceedance probabilities involved in the risk calculation (by integration of the risk-curves)
was varied. In addition, the sensitivity of the results with respect to increases in flood
discharges was assessed. The considered increases are consistent with a “wet” climate
change scenario for the time horizons 2021-2050 and 2071-2100 (Detrembleur et al.,
2015).
The results of hazard computation differ significantly between the upper and lower parts
of the course of river Meuse in Belgium. In the former, inundation extents grow gradually as
the considered flood discharge is increased (i.e. the exceedance probability is reduced), while
in the downstream part, protection structures (mainly concrete walls) prevent inundation for
flood discharges corresponding to exceedance probabilities of 0.01 and above (in the
present climate). For higher discharges, large inundation extents are obtained in the
floodplains.
The highest values of risk (mean annual damage) are obtained in the municipalities which
undergo relatively frequent flooding (upper part of the river), as well as in those of the
downstream part of the Meuse in which flow depths in the urbanized floodplains are
particularly high when inundation occurs. This is the case of the city of Liege, as a result of a
subsidence process following former mining activities. For a given climate scenario, the
uncertainty ranges affecting flood risk estimates are significant; but not so much that the
results for the different municipalities would overlap substantially. Therefore, these
uncertainties do not hamper prioritization in terms of allocation of risk reduction measures at
the municipality level.
In the present climate, the uncertainties arising from flood frequency analysis have a
negligible influence in the upper part of the river, while they have a considerable impact
on risk modelling in the lower part, where a threshold effect was observed due to
the flood protection structures (sudden transition from no inundation to massive
flooding when a threshold discharge is exceeded). Varying the number of exceedance
probabilities in the integration of the risk curve has different effects for different
municipalities; but it does not change the ranking of the municipalities in terms of flood
risk. For the other scenarios, damage estimation contributes most to the overall
uncertainties.
As shown by this study, the magnitude of the uncertainty and its main origin vary in space
and in time. This emphasizes the paramount importance of conducting distributed uncertainty
analyses. In the considered study area, prioritization of risk reduction means can be reliably
performed despite the modelling uncertainties.
Reference
Detrembleur, S., Stilmant, F., Dewals, B., Erpicum, S., Archambeau, P., & Pirotton, M.
(2015). Impacts of climate change on future flood damage on the river Meuse, with a
distributed uncertainty analysis. Natural Hazards, 77(3), 1533-1549.
Acknowledgement
Part of this research was funded through the ARC grant for Concerted Research Actions,
financed by the Wallonia-Brussels Federation. It was also supported by the NWE Interreg
IVB Program. |
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