Annegret H. Thieken

Insurability and Mitigation of Flood Losses in Private Households in Germany

In Germany, flood insurance is provided by private insurers as a supplement to building or contents insurance. This article presents the results of a survey of insurance companies with regard to eligibility conditions for flood insurance changes after August 2002, when a severe flood caused 1.8 billion euro of insured losses in the Elbe and the Danube catchment areas, and the general role of insurance in flood risk management in Germany. Besides insurance coverage, governmental funding and public donations played an important role in loss compensation after the August 2002 flood. Therefore, this article also analyzes flood loss compensation, risk awareness, and mitigation in insured and uninsured private households. Insured households received loss compensation earlier. They also showed slightly better risk awareness and mitigation strategies. Appropriate incentives should be combined with flood insurance in order to strengthen future private flood loss mitigation. However, there is some evidence that the surveyed insurance companies do little to encourage precautionary measures. To overcome this problem, flood hazards and mitigation strategies should be better communicated to both insurance companies and property owners.

Flood Risk Mapping At The Local Scale: Concepts and Challenges

Maps give a more direct and stronger impression of the spatial distribution of the flood risk than other forms of presentation (verbal description, diagrams). Thus, maps are valuable for presenting and assessing the local flood situation, and they provide information for many applications in flood defence and disaster management. In Europe, there are no standardised nomenclature or agreed practices for flood mapping. The paper reviews the concepts of flood risk mapping at the local scale, discusses the challenges and proposes a systematic presentation of flood hazards, vulnerabilities and flood risks, spanning from flood danger maps to damage risk maps

Development of FLEMOcs - a new model for the estimation of flood losses in the commercial sector

Abstract 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. Citation Kreibich, H., Seifert, I., Merz, B. & Thieken, A. H. (2010) Development of FLEMOcs – a new model for the estimation of flood losses in the commercial sector. Hydrol. Sci. J. 55(8), 1302–1314.

Quantification of uncertainties in flood risk assessments

Abstract 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.

Development and evaluation of FLEMOps - a new Flood Loss Estimation MOdel for the private sector

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.

Seasonality of floods in Germany

Abstract The seasonal distribution of annual maximum floods at 481 gauging stations throughout Germany was analysed and classified by cluster analysis. As a result, a new map with three regions that represent homogeneous flood regimes is presented: Cluster A in the western and central part of Germany with distinct winter floods; Cluster B with its centre in north and east Germany, in which the percentage of spring and summer floods is higher than in Cluster A; and a small Cluster C in southern Germany, which is dominated by summer floods. The occurrence of maximum observed flood events in three clusters corresponds well with the general seasonality of flooding. Finally, the stability of the flood regimes in different time periods was analysed, and a slight spatial extension of Cluster A towards the southeast was detected. This may hint at changes in westerly circulation patterns, but needs further investigation.

Influence of dike breaches on flood frequency estimation

Many river floodplains and their assets are protected by dikes. In case of extreme flood events, dikes may breach and floodwater may spill over into the dike hinterland. Depending on the specific situation, e.g. time and location of breach, and the capacity of the hinterland to contain the floodwater, dike breaches may lead to significant reductions of flood peaks downstream of breach locations. However, the influence of dike breaches on flood frequency distributions along rivers has not been systematically analysed. In order to quantify this influence, a dynamic-probabilistic model is developed. This model combines simplified flood process modules in a Monte Carlo framework. The simplifications allow for the simulation of a large number of different scenarios, taking into account the main physical processes. By using a Monte Carlo approach, frequency distributions can be derived from the simulations. In this way, process understanding and the characteristics of the river-dike-floodplain system are included in the derivation of flood frequency statements. The dynamic-probabilistic model is applied to the Lower Rhine in Germany and compared to the usually used flood frequency analysis. For extreme floods, the model simulates significant retention effects due to dike breaches, which lead to significant modifications of the flood frequency curve downstream of breach locations. The resulting probabilistic statements are much more realistic than those of the flood frequency approach, since the dynamic-probabilistic model incorporates an important flood process, i.e. dike breaching, that only occurs when a certain threshold is reached. Beyond this point, the behaviour of the flood frequency curve is dominated by this process.

Application and validation of FLEMOcs - a flood-loss estimation model for the commercial sector

Abstract 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. Citation Seifert, I., Kreibich, H., Merz, B. & Thieken, A. H. (2010) Application and validation of FLEMOcs – a flood-loss estimation model for the commercial sector. Hydrol. Sci. J. 55(8), 1315–1324.

A delphi method expert survey to derive standards for flood damage data collection.

For the purpose of flood damage analyses reliable, comparable, comprehensive, consistent, and up-to-date data are an indispensable need. Like in many other countries a database with this kind of datasets does not exist in Germany. To establish it, standards have to be set for flood damage data collection. We approached this problem by questioning experts about their information needs for flood damage analysis. This survey is done by applying a Delphi survey approach. The aptitude of the Delphi approach to assess, structure, and standardize expert knowledge is evaluated in this article. In the survey a panel of 55 experts working in the field of flood damage analysis for insurances, engineering companies/consultancy, public water management, and universities and other scientific institutions helped to identify common information needs. The multi-step Delphi method proved to reduce the deviation of answers thereby enabling consensual results and also enhanced the quality by modifying group answers in the direction of experience based answers. There was also a high level of congruence in information needs between experts from different fields of employment that allowed the derivation of common standards.

The Role of Disaggregation of Asset Values in Flood Loss Estimation: A Comparison of Different Modeling Approaches at the Mulde River, Germany

In loss estimation there is a spatial mismatch of hazard data that are commonly modeled on an explicit raster level and exposure data that are often available only for aggregated administrative units. Usually disaggregation methods that use ancillary information to distribute lumped exposure data in a finer spatial resolution help to bridge this gap. However, the actual influence of different mapping techniques and ancillary data on the final loss estimation has not been analyzed yet. In this paper three methods are applied to disaggregate residential building assets using two kinds of land use/land cover (LULC) data. The resulting disaggregated assets are validated and compared using census data of the residential building number on the community and constituency level. In addition, the disaggregated assets are taken to estimate residential building losses due to the flood in August 2002 in 21 municipalities on the River Mulde in Saxony, Germany. Losses are calculated with the help of four loss models. In general, disaggregation helps to decrease the error variance within the loss estimation. It must, however, be stated that the application of sophisticated disaggregation methods does not lead to significant improvements compared to the straightforward binary method. Therefore more effort should instead be put into the provision of high-resolution LULC data. Finally, the remaining uncertainties in loss estimation are high and demand further improvements in all modeling aspects.