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.

Applied flood risk analyses, especially in urban areas, very often pose the question how detailed the analysis needs to be in order to give a realistic figure of the expected risk. The methods used in research and practical applications range from very basic approaches with numerous simplifying assumptions up to very sophisticated, data and calculation time demanding applications both on the hazard and vulnerability part of the risk. In order to shed some light on the question of required model complexity in flood risk analyses and outputs sufficiently fulfilling the task at hand, a number of combinations of models of different complexity both on the hazard and vulnerability side were tested in a case study. The different models can be organized in a model matrix of different complexity levels: On the hazard side the approaches/models selected were A) linear interpolation of gauge water levels and intersection with a digital elevation model (DEM), B) a mixed 1D/2D hydraulic model with simplifying assumptions (LISFLOOD-FP) and C) a SaintVenant 2D zero-inertia hyperbolic hydraulic model considering the built environment and infrastructure. On the vulnerability side the models used for the estimation of direct damage to residential buildings are in order of increasing complexity: I) meso-scale stage-damage functions applied to CORINE land cover data, II) the rule-based meso-scale model FLEMOps+ using census data on the municipal building stock and CORINE land cover data and III) a rule-based microscale model applied to a detailed building inventory. Besides the inundation depths, the latter two models consider different building types and qualities as well as the level of private precaution and contamination of the floodwater. The models were applied in a municipality in southeast Germany, Eilenburg. It suffered extraordinary damage during the flood of August 2002, which was well documented as were the inundation extent and depths. These data provide an almost unique data set for the validation of flood risk analyses. The analysis shows that the combination of the 2 1D/2D-model and the meso-scale damage model FLEMOps+ performed best and provide the best compromise between data requirements, simulation effort, and an acceptable accuracy of the results. The more detailed approaches suffered from complex model setup, high data requirements, and long computation times.

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.

In order to be economically viable, flood disaster mitigation should be based on a comprehensive assessment of the flood risk. This requires the estimation of the flood hazard (i.e. runoff and associated probability) and the consequences of flooding (i.e. property damage, damage to persons, etc.). Within the ''German Research Network Natural Disasters'' project, the working group on ''Flood Risk Analysis'' investigated the complete flood disaster chain from the triggering event down to its various consequences. The working group developed complex, spatially distributed models representing the relevant meteorological, hydrological, hydraulic, geo-technical, and socio-economic processes. In order to assess flood risk these complex deterministic models were complemented by a simple probabilistic model. The latter model consists of modules each representing one process of the flood disaster chain. Each module is a simple parameterisation of the corresponding more complex model. This ensures that the two approaches (simple probabilistic and complex deterministic) are compatible at all steps of the flood disaster chain. The simple stochastic approach allows a large number of simulation runs in a Monte Carlo framework thus providing the basis for a probabilistic risk assessment. Using the proposed model, the flood risk including an estimation of the flood damage was quantified for an example area at the river Rhine. Additionally, the important influence of upstream levee breaches on the flood risk at the lower reaches was assessed. The proposed model concept is useful for the integrated assessment of flood risks in flood prone areas, for cost-benefit assessment and risk-based design of flood protection measures and as a decision support tool for flood management.Key words: flood risk, probabilistic model, flood damage estimation, levee failure ABBREVIATIONS: a.s.l. -above sea level; AMS -annual maximum series; BL -levee breach location; CDF -cumulated probability density function; CPU -central processor unit; LC -levee crest; LF -levee foot; MC -Monte Carlo; QD -direct discharge; QD max -maximum direct discharge; QD norm -normalised direct discharge; Q LC -discharge at levee crest; t norm -normalised time; t Qdmax -time of maximum direct discharge; V pol -volume of polder

By a common definition, flood risk assessments are comprised of two parts: a hazard and vulnerability assessment. The hazard assessment investigates the extent and magnitude of usually large flood events, which are associated to a certain exceedance probability, whereas the vulnerability part assesses the impact of the flooding on specified targets, e.g., building, people or infrastructure. Being inherently speculative flood risk assessments should always be accompanied by an uncertainty assessment in order to assist consequent decision properly. In this paper a dynamic-probabilistic method is proposed, which enables a cumulated flood risk assessment of a complete river reach considering dike failures at all dike locations. The model uses simple but computational efficient modules to simulate the complete process chain of flooding. These modules are embedded into a Monte Carlo framework thus enabling a risk assessment which is physically based thus mapping the real flooding process, and which is also probabilistic and not based on scenarios. The model also provides uncertainty estimates by quantifying various epistemic uncertainty sources of the hazard as well as the vulnerability part in a second layer of Monte Carlo simulations. These uncertainty estimates are associated to defined return intervals of the model outputs, i.e., the derived flood frequencies at the end of the reach and the risk curves for the complete reach, thus providing valuable information for the interpretation of the results. By separating single uncertainty sources a comparison of the contribution of different uncertainty sources to the overall predictive uncertainty in terms of derived flood frequencies and monetary risks could be performed. This revealed that the major uncertainties are extreme value statistics, resp. the length of the data series used and the discharge-stage relation used for the transformation of discharge into water levels in the river.

[1] This study focuses on development and application of a new modeling approach for a comprehensive flood hazard assessment along protected river reaches considering dike failures. The proposed Inundation Hazard Assessment Model (IHAM) represents a hybrid probabilistic-deterministic model. It comprises three models that are coupled in a dynamic way: (1) 1D unsteady hydrodynamic model for river channel and floodplain between dikes; (2) probabilistic dike breach model which determines possible dike breach locations, breach widths and breach outflow discharges; and (3) 2D raster-based inundation model for the dike-protected floodplain areas. Due to the unsteady nature of the 1D and 2D models and runtime coupling, the interdependence between the hydraulic loads on dikes at various locations along the reach is explicitly considered. This ensures a more realistic representation of the fluvial system dynamics under extreme conditions compared to the steady approaches. The probabilistic dike breach model describes dike failures due to three failure mechanisms: overtopping, piping and slope instability caused by seepage flow through the dike core (micro-instability). The 2D storage cell model computes various flood intensity indicators such as water depth, flow velocity, and inundation duration. IHAM is embedded in a Monte Carlo simulation in order to account for the natural variability of the input hydrograph form and the randomness of dike failures. Besides binary (wet/dry) inundation patterns, IHAM generates new probabilistic flood hazard maps for each intensity indicator and the associated uncertainty bounds. Furthermore, the novel probabilistic dike hazard maps indicate the failure probability of dikes for each considered breach mechanism.Citation: Vorogushyn, S., B. Merz, K.-E. Lindenschmidt, and H. Apel (2010), A new methodology for flood hazard assessment considering dike breaches, Water Resour. Res., 46, W08541,

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As flood impacts are increasing in large parts of the world, understanding the primary drivers of changes in risk is essential for effective adaptation. To gain more knowledge on the basis of empirical case studies, we analyze eight paired floods, that is, consecutive flood events that occurred in the same region, with the second flood causing significantly lower damage. These success stories of risk reduction were selected across different socioeconomic and hydro‐climatic contexts. The potential of societies to adapt is uncovered by describing triggered societal changes, as well as formal measures and spontaneous processes that reduced flood risk. This novel approach has the potential to build the basis for an international data collection and analysis effort to better understand and attribute changes in risk due to hydrological extremes in the framework of the IAHSs Panta Rhei initiative. Across all case studies, we find that lower damage caused by the second event was mainly due to significant reductions in vulnerability, for example, via raised risk awareness, preparedness, and improvements of organizational emergency management. Thus, vulnerability reduction plays an essential role for successful adaptation. Our work shows that there is a high potential to adapt, but there remains the challenge to stimulate measures that reduce vulnerability and risk in periods in which extreme events do not occur.