Simulating low‐probability peak discharges for the Rhine basin using resampled climate modeling data

Linde, A.H. te; Aerts, J.C.J.H.; Bakker, A.; Kwadijk, Jaap

doi:10.1029/2009wr007707

Cited by 104 publications

(94 citation statements)

References 56 publications

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“…MOS removes much of the model error in the precipitation, making it more useful in impact studies, which is considered by many to allow confidence in the examination of future changes in flow regimes in catchments from Europe and the wider world (e.g. Bell et al, 2007, Fowler et al, 2007bLeander and Buishand, 2007;Akhtar et al, 2009;Linde et al, 2010;Marke et al, 2011;Rojas et al, 2011;Turco et al, 2011). However, MOS can potentially also remove much of the spread in the driving variables, which could disrupt signals of climate change.…”

Section: Introductionmentioning

confidence: 99%

Modelling climate impact on floods with ensemble climate projections

Cloke

Wetterhall

et al. 2012

Quart J Royal Meteoro Soc

109

104

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The evidence provided by modelled assessments of future climate impact on flooding is fundamental to water resources and flood risk decision making. Impact models usually rely on climate projections from global and regional climate models (GCM/RCMs). However, challenges in representing precipitation events at catchment-scale resolution mean that decisions must be made on how to appropriately pre-process the meteorological variables from GCM/RCMs. Here the impacts on projected high flows of differing ensemble approaches and application of Model Output Statistics to RCM precipitation are evaluated while assessing climate change impact on flood hazard in the Upper Severn catchment in the UK. Various ensemble projections are used together with the HBV hydrological model with direct forcing and also compared to a response surface technique. We consider an ensemble of single-model RCM projections from the current UK Climate Projections (UKCP09); multi-model ensemble RCM projections from the European Union's FP6 'ENSEMBLES' project; and a joint probability distribution of precipitation and temperature from a GCM-based perturbed physics ensemble.The ensemble distribution of results show that flood hazard in the Upper Severn is likely to increase compared to present conditions, but the study highlights the differences between the results from different ensemble methods and the strong assumptions made in using Model Output Statistics to produce the estimates of future river discharge. The results underline the challenges in using the current generation of RCMs for local climate impact studies on flooding.

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Section: Introductionmentioning

confidence: 99%

Modelling climate impact on floods with ensemble climate projections

Cloke

Wetterhall

et al. 2012

Quart J Royal Meteoro Soc

109

104

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“…In a warmer climate, however, an acceleration of the hydrologic cycle could affect the occurrence of extreme flood events (Voss et al, 2002;Allen and Ingram, 2002;Milly et al, 2002Milly et al, , 2005Christensen and Christensen, 2003). Several modelling studies suggest that central Europe would experience an increase in flood risk under human-induced climate warming (Kwadijk and Rotmans, 1995;Middelkoop et al, 2001;Allamano et al, 2009;Feyen, 2008, 2009;Hurkmans et al, 2010;te Linde et al, 2010). Milly et al (2008) recently challenged the validity of the stationarity assumption, declaring it 'dead' and pushing forward the need to find solutions that would allow us to live in a 'nonstationary' world.…”

Section: Introductionmentioning

confidence: 99%

Analyses of extreme flooding in Austria over the period 1951–2006

Villarini

Smith

Serinaldi

et al. 2011

Intl Journal of Climatology

102

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ABSTRACT:Analyses of extreme flooding in Austria is performed using daily discharge time series from 27 stations over the period . The main research questions revolve around: (1) temporal non-stationarities in the flood record, (2) upper tail and scaling properties of the flood peak records, and (3) relation between magnitude and frequency of flooding and the North Atlantic Oscillation (NAO). Two datasets are derived from the daily discharge time series: annual maximum daily discharge and peaks-over-threshold (POT) data. The validity of the stationarity assumption in the annual maximum discharge record is assessed by investigating the presence of abrupt and slowly varying changes using nonparametric tests. The time series are tested for abrupt changes both in the mean and variance of the flood peak distributions by means of the Pettitt test. The presence of monotonic trends is investigated by means of the Mann-Kendall and Spearman tests. Violations of the stationarity assumption are associated with abrupt rather than gradual changes. These step changes generally involve river regulation through construction of dams or other major engineering works. It is not possible to make conclusive statements about the presence of an anthropogenic climate change signal in the flood peak record. Similar conclusions are obtained when focussing on the frequency of POT floods. The Generalised Extreme Value distribution is used to study the upper tail and scaling properties of annual maximum daily discharge records. The location and scale parameters exhibit power-law behaviour as a function of drainage area. The shape parameters indicate that the flood peak distributions for Austria have a heavy tail. Non-stationary modelling of the annual maximum daily discharge and POT time series is used to explore the relation between flood magnitude and frequency and NAO. The results indicate that NAO is a significant covariate in explaining the magnitude and frequency of occurrence of flooding over a large part of Austria.

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“…Flood damage is projected to increase further as a result of continued urban development combined with climate-change effects on river discharges and flood probabilities Bouwer et al, 2006;IPCC, 2007;te Linde et al, 2010;. In the light of these developments, more and more studies are assessing changes in flood risk, where flood risk is defined as the probability of flooding multiplied by the potential consequences, such as economic damage or loss of lives (Maaskant et al, 2009;Merz et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

Potential of semi-structural and non-structural adaptation strategies to reduce future flood risk: case study for the Meuse

Poussin

Bubeck

Aerts

et al. 2012

Nat. Hazards Earth Syst. Sci.

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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.

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Simulating low‐probability peak discharges for the Rhine basin using resampled climate modeling data

Cited by 104 publications

References 56 publications

Modelling climate impact on floods with ensemble climate projections

Modelling climate impact on floods with ensemble climate projections

Analyses of extreme flooding in Austria over the period 1951–2006

Potential of semi-structural and non-structural adaptation strategies to reduce future flood risk: case study for the Meuse

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