Abstract. Damage assessments of natural hazards supply crucial information to decision support and policy development in the fields of natural hazard management and adaptation planning to climate change. Specifically, the estimation of economic flood damage is gaining greater importance as flood risk management is becoming the dominant approach of flood control policies throughout Europe. This paper reviews the state-of-the-art and identifies research directions of economic flood damage assessment. Despite the fact that considerable research effort has been spent and progress has been made on damage data collection, data analysis and model development in recent years, there still seems to be a mismatch between the relevance of damage assessments and the quality of the available models and datasets. Often, simple approaches are used, mainly due to limitations in available data and knowledge on damage mechanisms. The results of damage assessments depend on many assumptions, e.g. the selection of spatial and temporal boundaries, and there are many pitfalls in economic evaluation, e.g. the choice between replacement costs or depreciated values. Much larger efforts are required for empirical and synthetic data collection and for providing consistent, reliable data to scientists and practitioners. A major shortcoming of damage modelling is that model validation is scarcely performed. Uncertainty analyses and thorough scrutiny of model inputs and assumptions should be mandatory for each damage model development and application, respectively. In our view, flood risk assessments are often not well balanced. Much more attention is given to the hazard assessment part, whereas damage assessment is treated as some kind of appendix within the risk analysis. Advances in floodCorrespondence to: B. Merz (bmerz@gfz-potsdam.de) damage assessment could trigger subsequent methodological improvements in other natural hazard areas with comparable time-space properties.

[1] In the aftermath of a severe flood event in August 2002 in Germany, 1697 computeraided telephone interviews were undertaken in flood-affected private households. Besides the damage to buildings and contents a variety of factors that might influence flood damage were queried. It is analyzed here how variables describing flood impact, precaution, and preparedness as well as characteristics of the affected buildings and households vary between the lower and upper damage quartiles of all affected households. The analysis is supplemented by principal component analyses. The investigation reveals that flood impact variables, particularly water level, flood duration, and contamination are the most influential factors for building and for content damage. This group of variables is followed by items quantifying the size and the value of the affected building/flat. In comparison to these factors, temporal and permanent resistance influences damage only to a small fraction, although in individual cases, precaution can significantly reduce flood damage.

Abstract. The usual approach for flood damage assessment consists of stage-damage functions which relate the relative or absolute damage for a certain class of objects to the inundation depth. Other characteristics of the flooding situation and of the flooded object are rarely taken into account, although flood damage is influenced by a variety of factors. We apply a group of data-mining techniques, known as tree-structured models, to flood damage assessment. A very comprehensive data set of more than 1000 records of direct building damage of private households in Germany is used. Each record contains details about a large variety of potential damage-influencing characteristics, such as hydrological and hydraulic aspects of the flooding situation, early warning and emergency measures undertaken, state of precaution of the household, building characteristics and socio-economic status of the household. Regression trees and bagging decision trees are used to select the more important damageinfluencing variables and to derive multi-variate flood damage models. It is shown that these models outperform existing models, and that tree-structured models are a promising alternative to traditional damage models.

In August 2002, a severe flood event occurred in Central Europe. In the following year, a poll was performed in Germany in which 1697 private households were randomly selected from three regions: (a) the River Elbe area, (b) the Elbe tributaries in Saxony and Saxony-Anhalt, and (c) the Bavarian Danube catchment. Residents were interviewed about flood characteristics, early warning, damage, recovery, preparedness and previously experienced floods. Preparedness, response, financial losses and recovery differed in the three regions under study. This could be attributed mainly to differences in flood experience and flood impact. Knowledge about self-protection, residents' homeownership and household size influenced the extent and type of private precautions taken, as well as the residents' ability to perform mitigation measures. To further improve preparedness and response during future flood events, flood warnings should include more information about possible protection measures. In addition, different information leaflets with flood mitigation options for specific groups of people, e.g. tenants, homeowners, elderly people or young families, should be developed.

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21During the last decades several destructive floods in Germany led to the impression that 22 the frequency and/or magnitude of flooding has been increasing. In this study, flood 23 time series are derived and analyzed for trends for 145 discharge gauges in Germany. A 24 common time period of 52 years ) is used. In order to obtain a country-wide 25 picture, the gauges are rather homogeneously distributed across Germany. Eight flood 26 indicators are studied, which are drawn from annual maximum series and peak over 27 threshold series. Our analysis detects significant flood trends (at the 10% significance 28 level) for a considerable fraction of basins. In most cases, these trends are upward; 29 decreasing flood trends are rarely found and are not field-significant.

The estimation of flood losses is an essential component for risk-oriented flood design, risk mapping or financial appraisals in the reinsurance sector. However, only simple models, e.g. stage-damage curves, have been used frequently. Further, the reliability of flood loss and risk estimates is fairly unknown, since flood loss models are scarcely validated.In the aftermath of flooding in August 2002 large data sets of flood losses were collected at affected properties in Germany. These data were used to derive multi-factorial loss models. This paper presents FLEMOps -the Flood Loss Estimation Model for the private sector, which estimates direct monetary flood losses of residential buildings and household contents considering water level, building type and building quality. In an additional model stage (FLEMOps+), the effects of private precautionary measures as well as of the contamination of the floodwater can be quantified. Together with census data and land use information the model is adapted for applications on the meso-scale.Further, different data sets of repair costs for single buildings and in whole municipalities were used to validate loss estimates on the micro-as well as on the meso-scale. First results show that the model FLEMOps+ outperforms simple stage-damage-functions.