Abstract. The summer flood of 2013 set a new record for large-scale floods in Germany for at least the last 60 years. In this paper we analyse the key hydro-meteorological factors using extreme value statistics as well as aggregated severity indices. For the long-term classification of the recent flood we draw comparisons to a set of past large-scale flood events in Germany, notably the high-impact summer floods from August 2002 and July 1954. Our analysis shows that the combination of extreme initial wetness at the national scale -caused by a pronounced precipitation anomaly in the month of May 2013 -and strong, but not extraordinary event precipitation were the key drivers for this exceptional flood event. This provides additional insights into the importance of catchment wetness for high return period floods on a large scale. The database compiled and the methodological developments provide a consistent framework for the rapid evaluation of future floods.
Abstract. For the purpose of flood risk analysis, reliable loss models are an indispensable need. The most common models use stage-damage functions relating damage to water depth. They are often derived from empirical flood loss data (i.e. loss data collected after a flood event). However, object specific loss data (e.g. losses of single residential buildings) from recent flood events in Germany showed higher average losses in less probable events, regardless of actual water level. Hence, models that were derived from such data tend to overestimate losses caused by more probable events. Therefore, it is the aim of the study to analyse the relation between flood damage and recurrence interval and to propose a method for considering recurrence interval in flood loss modelling. The survey was based on residential building loss data (n = 2158) of recent flood events in 2002, 2005 and 2006 in Germany and on-site recurrence interval of the respective events. We discovered a highly significant positive correlation between loss extent and recurrence interval for classified water levels as well as increasing average losses for longer recurrence intervals within each class. The application of principal component analysis revealed the interrelation between factors that influence the damage extent directly or indirectly, and recurrence interval. No single factor or component could be identified that explained the influence of recurrence interval, which led to the conclusion that recurrence interval cannot substitute, but complement other damage influencing factors in flood loss modelling approaches. Finally, a method was developed to include recurrence interval in typical flood loss models and make them applicable to a wider range of flood events. Validation including statistical error analysis showed that the modified models improve loss estimates in comparison to traditional approaches. The proposed multi-parameter model FLEMOps+r performs particularly well.
Abstract.The need for an efficient use of limited resources fosters the application of risk-oriented design in flood mitigation. Flood defence measures reduce future damage. Traditionally, this benefit is quantified via the expected annual damage. We analyse the contribution of "high probability/low damage" floods versus the contribution of "low probability/high damage" events to the expected annual damage. For three case studies, i.e. actual flood situations in floodprone communities in Germany, it is shown that the expected annual damage is dominated by "high probability/low damage" events. Extreme events play a minor role, even though they cause high damage. Using typical values for flood frequency behaviour, flood plain morphology, distribution of assets and vulnerability, it is shown that this also holds for the general case of river floods in Germany. This result is compared to the significance of extreme events in the public perception. "Low probability/high damage" events are more important in the societal view than it is expressed by the expected annual damage. We conclude that the expected annual damage should be used with care since it is not in agreement with societal priorities. Further, risk aversion functions that penalise events with disastrous consequences are introduced in the appraisal of risk mitigation options. It is shown that risk aversion may have substantial implications for decisionmaking. Different flood mitigation decisions are probable, when risk aversion is taken into account.
aBStract. -the June 2013 flood was the most severe large-scale flood in Germany, at least for the last 6 decades for which a hydrological flood severity has been calculated. Many gauges along the elbe and Danube rivers showed record water levels. the flood severity index, a measure which combines magnitude and spatial extension, is almost twice as large as the index of the august 2002 flood which has been the most expensive natural disaster for Germany to date. the enormous hydrological severity was caused by widespread and intense rainfall in combination with wet catchments due to exceptionally high rainfall in the month preceding the event. Preliminary damage estimates are in the order of 8.7 to 12 billion €. Hence, the losses seem to be lower compared to the 2002 flood (11.8 billion € for Germany). although detailed analyses have not been performed to date, it can be assumed that the investments and improvements in flood risk management since 2002 have reduced the flood risk and prevented higher damage.
Abstract. The observed increase of direct flood damage over the last decades may be caused by changes in the meteorological drivers of floods, or by changing land-use patterns and socio-economic developments. It is still widely unknown to which extent these factors will contribute to future flood risk changes.We survey the change of flood risk in terms of expected annual damage for residential buildings in the lower part of the Mulde River basin (Vereinigte Mulde) between 1990 and 2020 in 10-yr time steps based on measurements and model projections. For this purpose we consider the complete risk chain from climate impact via hydrological and hydraulic modelling to damage and risk estimation. We analyse what drives the changes in flood risk and quantify the contributions of these drivers: flood hazard change due to climate change, land-use change and changes in building values.
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