© Author(s) 2012. This work is distributed
under the Creative Commons Attribution 3.0 License.
Potential of semi-structural and non-structural adaptation strategies to reduce future flood risk: case study for the Meuse
1Institute for Environmental Studies (IVM), VU University Amsterdam, Amsterdam, The Netherlands
2Amsterdam Global Change Institute (AGCI), VU University Amsterdam, Amsterdam, The Netherlands
3Helmholtz Centre Potsdam, German Research Centre for Geosciences (GFZ), Section Hydrology, Germany
Abstract. 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.