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Abstract. The paper analyses the prevailing breach mechanisms of fluvial dikes. Piping in the dike foundation and slope failure as a consequence of seepage flow through a dike core (micro-instability) were identified as two of the dominant breach mechanisms for historically-grown dikes along with overtopping and slope macro-instability. For the former two mechanisms the physically-based and empirical process descriptions were reviewed and led to the formulation of the reliability functions. Evaluation of these functions in the Monte Carlo framework for the time dependent load led to the development of fragility functions. These functions indicate the probability of failure of a dike section upon loading and can be computed for each spatially discretised dike section. The probability of breaching is conditioned by the uncertainty in geometrical and geotechnical dike parameters. This uncertainty is explicitly taken into account during computation of the fragility functions in a Monte Carlo simulation. Sensitivity analysis was carried out in order to identify the sensitive geotechnical parameters influencing the distribution of failure probability. The identification of sensitive parameters indicates the priorities in geotechnical measurement campaigns aimed at the assessment of dike stability. The newly developed fragility functions can be applied in flood hazard and risk assessment studies for modelling of dike failures in a probabilistic framework.

Abstract. Flood hazard projections under climate change are typically derived by applying model chains consisting of the following elements: "emission scenario – global climate model – downscaling, possibly including bias correction – hydrological model – flood frequency analysis". To date, this approach yields very uncertain results, due to the difficulties of global and regional climate models to represent precipitation. The implementation of such model chains requires major efforts, and their complexity is high. We propose for the Mekong River an alternative approach which is based on a shortened model chain: "emission scenario – global climate model – non-stationary flood frequency model". The underlying idea is to use a link between the Western Pacific monsoon and local flood characteristics: the variance of the monsoon drives a non-stationary flood frequency model, yielding a direct estimate of flood probabilities. This approach bypasses the uncertain precipitation, since the monsoon variance is derived from large-scale wind fields which are better represented by climate models. The simplicity of the monsoon–flood link allows deriving large ensembles of flood projections under climate change. We conclude that this is a worthwhile, complementary approach to the typical model chains in catchments where a substantial link between climate and floods is found.

Abstract. Flood disaster mitigation strategies should be based on a comprehensive assessment of the flood risk combined with a thorough investigation of the uncertainties associated with the risk assessment procedure. Within the "German Research Network of Natural Disasters" (DFNK) the working group "Flood Risk Analysis" investigated the flood process chain from precipitation, runoff generation and concentration in the catchment, flood routing in the river network, possible failure of flood protection measures, inundation to economic damage. The working group represented each of these processes by deterministic, spatially distributed models at different scales. While these models provide the necessary understanding of the flood process chain, they are not suitable for risk and uncertainty analyses due to their complex nature and high CPU-time demand. We have therefore developed a stochastic flood risk model consisting of simplified model components associated with the components of the process chain. We parameterised these model components based on the results of the complex deterministic models and used them for the risk and uncertainty analysis in a Monte Carlo framework. The Monte Carlo framework is hierarchically structured in two layers representing two different sources of uncertainty, aleatory uncertainty (due to natural and anthropogenic variability) and epistemic uncertainty (due to incomplete knowledge of the system). The model allows us to calculate probabilities of occurrence for events of different magnitudes along with the expected economic damage in a target area in the first layer of the Monte Carlo framework, i.e. to assess the economic risks, and to derive uncertainty bounds associated with these risks in the second layer. It is also possible to identify the contributions of individual sources of uncertainty to the overall uncertainty. It could be shown that the uncertainty caused by epistemic sources significantly alters the results obtained with aleatory uncertainty alone. The model was applied to reaches of the river Rhine downstream of Cologne.

Abstract. There is a wide variety of flood damage models in use internationally, differing substantially in their approaches and economic estimates. Since these models are being used more and more as a basis for investment and planning decisions on an increasingly large scale, there is a need to reduce the uncertainties involved and develop a harmonised European approach, in particular with respect to the EU Flood Risks Directive. In this paper we present a qualitative and quantitative assessment of seven flood damage models, using two case studies of past flood events in Germany and the United Kingdom. The qualitative analysis shows that modelling approaches vary strongly, and that current methodologies for estimating infrastructural damage are not as well developed as methodologies for the estimation of damage to buildings. The quantitative results show that the model outcomes are very sensitive to uncertainty in both vulnerability (i.e. depth–damage functions) and exposure (i.e. asset values), whereby the first has a larger effect than the latter. We conclude that care needs to be taken when using aggregated land use data for flood risk assessment, and that it is essential to adjust asset values to the regional economic situation and property characteristics. We call for the development of a flexible but consistent European framework that applies best practice from existing models while providing room for including necessary regional adjustments.

Flood risk is dynamic and influenced by many processes related to hazard, exposure and vulnerability. Flood damage increased significantly over the past decades, however, resulting overall economic loss per event is an aggregated indicator and it is difficult to attribute causes to this increasing trend. Much has been learned about damaging processes during floods at the micro-scale, e.g. building level. However, little is known about the main factors determining the amount of flood damage on event level. Thus, we analyse and compare paired flood events, i.e. consecutive, similar damaging floods that occurred in the same area. In analogy to 'Paired catchment studies' - a well-established method in hydrology to understand how changes in land use affect streamflow – we will investigate how and why resulting flood damage in a region differed between the first and second consecutive flood events. One example are the 2002 and 2013 floods in the Elbe and Danube catchments in Germany. The 2002 flood caused the highest economic damage (EUR 11600 million) due to a natural hazard event in Germany. Damage was so high due to extreme flood hazard triggered by extreme precipitation and a high number of resulting dyke breaches. Additionally, exposure hotspots like the city of Dresden at the Elbe river as well as some smaller municipalities at the river Mulde (e.g. Grimma, Eilenburg, Bitterfeld, Dessau) were severely impacted. However, affected parties and authorities learned from the extreme flood in 2002, and many governmental flood risk programs and initiatives were launched. Considerable improvements since 2002 occurred on many levels that deal with flood risk reduction and disaster response, in particular in 1) increased flood prevention by improved spatial planning, 2) an increased number of property-level mitigation measures, 3) more effective early warning and improved coordination of disaster response and 4) a more targeted maintenance of flood defence systems and their deliberate relocation. Thus, despite higher hydrological severity damage due to the 2013 flood was significantly lower than in 2002. In our international comparative paired event study we investigate under which circumstances similar or contrasting processes occurred and hope to identify common key processes which determine flood damage on event level.