Abstract. Flow velocity is generally presumed to influence flood damage. However, this influence is hardly quantified and virtually no damage models take it into account. Therefore, the influences of flow velocity, water depth and combinations of these two impact parameters on various types of flood damage were investigated in five communities affected by the Elbe catchment flood in Germany in 2002. 2-D hydraulic models with high to medium spatial resolutions were used to calculate the impact parameters at the sites in which damage occurred. A significant influence of flow velocity on structural damage, particularly on roads, could be shown in contrast to a minor influence on monetary losses and business interruption. Forecasts of structural damage to road infrastructure should be based on flow velocity alone. The energy head is suggested as a suitable flood impact parameter for reliable forecasting of structural damage to residential buildings above a critical impact level of 2 m of energy head or water depth. However, general consideration of flow velocity in flood damage modelling, particularly for estimating monetary loss, cannot be recommended.

The estimation of flood damage is an important component for risk-oriented flood design, risk mapping, financial appraisals and comparative risk analyses. However, research on flood-loss modelling, especially in the commercial sector, has not gained much attention so far. Therefore, extensive data about flood losses were collected for affected companies via telephone surveys after the floods of 2002, 2005 and 2006 in Germany. Potential loss determining factors were analysed. The new Flood Loss Estimation MOdel for the commercial sector (FLEMOcs) was developed on the basis of 642 loss cases. Losses are estimated depending on water depth, sector and company size as well as precaution and contamination. The model can be applied to the micro-scale, i.e. to single production sites as well as to the meso-scale, i.e. land-use units, thus enabling its countrywide application.

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The estimation of flood loss is difficult, especially in the commercial sector, because of its great inhomogeneity. However, the reliability of loss modelling is fairly unknown, since flood-loss models are scarcely validated. The newly developed Flood Loss Estimation MOdel for the commercial sector (FLEMOcs) was validated on the micro-scale using a leave-one-out cross-validation procedure. Additionally, different meso-scale loss functions were compared. Meso-scale model application was undertaken in 19 municipalities which were affected during the 2002 flood in Germany. Model results were compared with the results of three other loss models, as well as with official loss records. The micro-scale validation shows very good results, with no bias and mean absolute errors between 23 and 31%. The meso-scale validation indicates that FLEMOcs provides good results, especially in large areas with many affected companies where high losses are expected.Key words flood-loss model; stage-damage curves; model comparison; validation; Germany Application et validation des FLEMOcs -un modèle d'estimation des dommages dus aux inondations dans le secteur commercial Résumé L'estimation des dommages dus aux inondations est difficile, en particulier dans le secteur commercial en raison de sa grande homogénéité. Toutefois, la fiabilité de la modélisation des dommages est plutôt inconnue, puisque les modèles de dommages dus aux inondations ne sont peu validés. Le nouveau modèle d'estimation des dommages dus aux inondations dans le secteur commercial (FLEMOcs) a été validé à la micro-échelle en utilisant une procédure de validation croisée "leave-one-out". En outre, différentes fonctions de dommages à méso-échelle ont été comparées. La mise en oeuvre du modèle à méso-échelle a été menée dans 19 municipalités touchées lors de la crue de 2002 en Allemagne. Les résultats du modèle ont été comparés avec les résultats de trois autres modèles de dommages, ainsi qu'avec les dossiers de dommages officiels. La validation à micro-échelle montre de très bons résultats, sans biais et avec des erreurs moyennes absolues comprises entre 23% et 31%. La validation à méso-échelle indique que FLEMOcs donne de bons résultats, en particulier dans les grandes zones qui comprennent de nombreuses entreprises touchées et où des dommages élevés sont prévus.

Abstract. In risk analysis there is a spatial mismatch of hazard data that are commonly modelled on an explicit raster level and exposure data that are often only available for aggregated units, e.g. communities. Dasymetric mapping techniques that use ancillary information to disaggregate data within a spatial unit help to bridge this gap. This paper presents dasymetric maps showing the population density and a unit value of residential assets for whole Germany. A dasymetric mapping approach, which uses land cover data (CORINE Land Cover) as ancillary variable, was adapted and applied to regionalize aggregated census data that are provided for all communities in Germany. The results were validated by two approaches. First, it was ascertained whether population data disaggregated at the community level can be used to estimate population in postcodes. Secondly, disaggregated population and asset data were used for a loss evaluation of two flood events that occurred in 1999 and 2002, respectively. It must be concluded that the algorithm tends to underestimate the population in urban areas and to overestimate population in other land cover classes. Nevertheless, flood loss evaluations demonstrate that the approach is capable of providing realistic estimates of the number of exposed people and assets. Thus, the maps are sufficient for applications in large-scale risk assessments such as the estimation of population and assets exposed to natural and man-made hazards.