@article{SchroeterKreibichVogeletal.2014, author = {Schroeter, Kai and Kreibich, Heidi and Vogel, Kristin and Riggelsen, Carsten and Scherbaum, Frank and Merz, Bruno}, title = {How useful are complex flood damage models?}, series = {Water resources research}, volume = {50}, journal = {Water resources research}, number = {4}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0043-1397}, doi = {10.1002/2013WR014396}, pages = {3378 -- 3395}, year = {2014}, abstract = {We investigate the usefulness of complex flood damage models for predicting relative damage to residential buildings in a spatial and temporal transfer context. We apply eight different flood damage models to predict relative building damage for five historic flood events in two different regions of Germany. Model complexity is measured in terms of the number of explanatory variables which varies from 1 variable up to 10 variables which are singled out from 28 candidate variables. Model validation is based on empirical damage data, whereas observation uncertainty is taken into consideration. The comparison of model predictive performance shows that additional explanatory variables besides the water depth improve the predictive capability in a spatial and temporal transfer context, i.e., when the models are transferred to different regions and different flood events. Concerning the trade-off between predictive capability and reliability the model structure seem more important than the number of explanatory variables. Among the models considered, the reliability of Bayesian network-based predictions in space-time transfer is larger than for the remaining models, and the uncertainties associated with damage predictions are reflected more completely.}, language = {en} } @misc{ThiekenKienzlerKreibichetal.2016, author = {Thieken, Annegret and Kienzler, Sarah and Kreibich, Heidi and Kuhlicke, Christian and Kunz, Michael and Muehr, Bernhard and Mueller, Meike and Otto, Antje and Petrow, Theresia and Pisi, Sebastian and Schroeter, Kai}, title = {Review of the flood risk management system in Germany after the major flood in 2013}, series = {Ecology and society : a journal of integrative science for resilience and sustainability}, volume = {21}, journal = {Ecology and society : a journal of integrative science for resilience and sustainability}, publisher = {Resilience Alliance}, address = {Wolfville}, issn = {1708-3087}, doi = {10.5751/ES-08547-210251}, pages = {8612 -- 8614}, year = {2016}, abstract = {Widespread flooding in June 2013 caused damage costs of (sic)6 to 8 billion in Germany, and awoke many memories of the floods in August 2002, which resulted in total damage of (sic)11.6 billion and hence was the most expensive natural hazard event in Germany up to now. The event of 2002 does, however, also mark a reorientation toward an integrated flood risk management system in Germany. Therefore, the flood of 2013 offered the opportunity to review how the measures that politics, administration, and civil society have implemented since 2002 helped to cope with the flood and what still needs to be done to achieve effective and more integrated flood risk management. The review highlights considerable improvements on many levels, in particular (1) an increased consideration of flood hazards in spatial planning and urban development, (2) comprehensive property-level mitigation and preparedness measures, (3) more effective flood warnings and improved coordination of disaster response, and (4) a more targeted maintenance of flood defense systems. In 2013, this led to more effective flood management and to a reduction of damage. Nevertheless, important aspects remain unclear and need to be clarified. This particularly holds for balanced and coordinated strategies for reducing and overcoming the impacts of flooding in large catchments, cross-border and interdisciplinary cooperation, the role of the general public in the different phases of flood risk management, as well as a transparent risk transfer system. Recurring flood events reveal that flood risk management is a continuous task. Hence, risk drivers, such as climate change, land-use changes, economic developments, or demographic change and the resultant risks must be investigated at regular intervals, and risk reduction strategies and processes must be reassessed as well as adapted and implemented in a dialogue with all stakeholders.}, language = {en} } @article{ThiekenBesselKienzleretal.2016, author = {Thieken, Annegret and Bessel, Tina and Kienzler, Sarah and Kreibich, Heidi and Mueller, Meike and Pisi, Sebastian and Schroeter, Kai}, title = {The flood of June 2013 in Germany: how much do we know about its impacts?}, series = {Natural hazards and earth system sciences}, volume = {16}, journal = {Natural hazards and earth system sciences}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1561-8633}, doi = {10.5194/nhess-16-1519-2016}, pages = {1519 -- 1540}, year = {2016}, abstract = {In June 2013, widespread flooding and consequent damage and losses occurred in Central Europe, especially in Germany. This paper explores what data are available to investigate the adverse impacts of the event, what kind of information can be retrieved from these data and how well data and information fulfil requirements that were recently proposed for disaster reporting on the European and international levels. In accordance with the European Floods Directive (2007/60/EC), impacts on human health, economic activities (and assets), cultural heritage and the environment are described on the national and sub-national scale. Information from governmental reports is complemented by communications on traffic disruptions and surveys of flood-affected residents and companies. Overall, the impacts of the flood event in 2013 were manifold. The study reveals that flood-affected residents suffered from a large range of impacts, among which mental health and supply problems were perceived more seriously than financial losses. The most frequent damage type among affected companies was business interruption. This demonstrates that the current scientific focus on direct (financial) damage is insufficient to describe the overall impacts and severity of flood events. The case further demonstrates that procedures and standards for impact data collection in Germany are widely missing. Present impact data in Germany are fragmentary, heterogeneous, incomplete and difficult to access. In order to fulfil, for example, the monitoring and reporting requirements of the Sendai Framework for Disaster Risk Reduction 2015-2030 that was adopted in March 2015 in Sendai, Japan, more efforts on impact data collection are needed.}, language = {en} } @article{SairamSchroeterRoezeretal.2019, author = {Sairam, Nivedita and Schroeter, Kai and R{\"o}zer, Viktor and Merz, Bruno and Kreibich, Heidi}, title = {Hierarchical Bayesian Approach for Modeling Spatiotemporal Variability in Flood Damage Processes}, series = {Water resources research}, volume = {55}, journal = {Water resources research}, number = {10}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0043-1397}, doi = {10.1029/2019WR025068}, pages = {8223 -- 8237}, year = {2019}, abstract = {Flood damage processes are complex and vary between events and regions. State-of-the-art flood loss models are often developed on the basis of empirical damage data from specific case studies and do not perform well when spatially and temporally transferred. This is due to the fact that such localized models often cover only a small set of possible damage processes from one event and a region. On the other hand, a single generalized model covering multiple events and different regions ignores the variability in damage processes across regions and events due to variables that are not explicitly accounted for individual households. We implement a hierarchical Bayesian approach to parameterize widely used depth-damage functions resulting in a hierarchical (multilevel) Bayesian model (HBM) for flood loss estimation that accounts for spatiotemporal heterogeneity in damage processes. We test and prove the hypothesis that, in transfer scenarios, HBMs are superior compared to generalized and localized regression models. In order to improve loss predictions for regions and events for which no empirical damage data are available, we use variables pertaining to specific region- and event-characteristics representing commonly available expert knowledge as group-level predictors within the HBM.}, language = {en} }