TY - JOUR A1 - Paprotny, Dominik A1 - Kreibich, Heidi A1 - Morales-Napoles, Oswaldo A1 - Wagenaar, Dennis A1 - Castellarin, Attilio A1 - Carisi, Francesca A1 - Bertin, Xavier A1 - Merz, Bruno A1 - Schröter, Kai T1 - A probabilistic approach to estimating residential losses from different flood types JF - Natural hazards : journal of the International Society for the Prevention and Mitigation of Natural Hazards N2 - Residential assets, comprising buildings and household contents, are a major source of direct flood losses. Existing damage models are mostly deterministic and limited to particular countries or flood types. Here, we compile building-level losses from Germany, Italy and the Netherlands covering a wide range of fluvial and pluvial flood events. Utilizing a Bayesian network (BN) for continuous variables, we find that relative losses (i.e. loss relative to exposure) to building structure and its contents could be estimated with five variables: water depth, flow velocity, event return period, building usable floor space area and regional disposable income per capita. The model's ability to predict flood losses is validated for the 11 flood events contained in the sample. Predictions for the German and Italian fluvial floods were better than for pluvial floods or the 1993 Meuse river flood. Further, a case study of a 2010 coastal flood in France is used to test the BN model's performance for a type of flood not included in the survey dataset. Overall, the BN model achieved better results than any of 10 alternative damage models for reproducing average losses for the 2010 flood. An additional case study of a 2013 fluvial flood has also shown good performance of the model. The study shows that data from many flood events can be combined to derive most important factors driving flood losses across regions and time, and that resulting damage models could be applied in an open data framework. KW - fluvial floods KW - coastal floods KW - pluvial floods KW - Bayesian networks KW - flood KW - damage surveys Y1 - 2020 U6 - https://doi.org/10.1007/s11069-020-04413-x SN - 0921-030X SN - 1573-0840 VL - 105 IS - 3 SP - 2569 EP - 2601 PB - Springer CY - New York ER - TY - JOUR A1 - Kreibich, Heidi A1 - Di Baldassarre, Giuliano A1 - Vorogushyn, Sergiy A1 - Aerts, Jeroen C. J. H. A1 - Apel, Heiko A1 - Aronica, Giuseppe T. A1 - Arnbjerg-Nielsen, Karsten A1 - Bouwer, Laurens M. A1 - Bubeck, Philip A1 - Caloiero, Tommaso A1 - Chinh, Do T. A1 - Cortes, Maria A1 - Gain, Animesh K. A1 - Giampa, Vincenzo A1 - Kuhlicke, Christian A1 - Kundzewicz, Zbigniew W. A1 - Llasat, Maria Carmen A1 - Mard, Johanna A1 - Matczak, Piotr A1 - Mazzoleni, Maurizio A1 - Molinari, Daniela A1 - Dung, Nguyen V. A1 - Petrucci, Olga A1 - Schröter, Kai A1 - Slager, Kymo A1 - Thieken, Annegret A1 - Ward, Philip J. A1 - Merz, Bruno T1 - Adaptation to flood risk BT - Results of international paired flood event studies JF - Earth's Future N2 - 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. KW - flooding KW - vulnerability KW - global environmental change KW - adaptation Y1 - 2017 U6 - https://doi.org/10.1002/2017EF000606 SN - 2328-4277 VL - 5 SP - 953 EP - 965 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Tarasova, Larisa A1 - Merz, Ralf A1 - Kiss, Andrea A1 - Basso, Stefano A1 - Blöchl, Günter A1 - Merz, Bruno A1 - Viglione, Alberto A1 - Plötner, Stefan A1 - Guse, Björn A1 - Schumann, Andreas A1 - Fischer, Svenja A1 - Ahrens, Bodo A1 - Anwar, Faizan A1 - Bárdossy, András A1 - Bühler, Philipp A1 - Haberlandt, Uwe A1 - Kreibich, Heidi A1 - Krug, Amelie A1 - Lun, David A1 - Müller-Thomy, Hannes A1 - Pidoto, Ross A1 - Primo, Cristina A1 - Seidel, Jochen A1 - Vorogushyn, Sergiy A1 - Wietzke, Luzie T1 - Causative classification of river flood events JF - Wiley Interdisciplinary Reviews : Water N2 - A wide variety of processes controls the time of occurrence, duration, extent, and severity of river floods. Classifying flood events by their causative processes may assist in enhancing the accuracy of local and regional flood frequency estimates and support the detection and interpretation of any changes in flood occurrence and magnitudes. This paper provides a critical review of existing causative classifications of instrumental and preinstrumental series of flood events, discusses their validity and applications, and identifies opportunities for moving toward more comprehensive approaches. So far no unified definition of causative mechanisms of flood events exists. Existing frameworks for classification of instrumental and preinstrumental series of flood events adopt different perspectives: hydroclimatic (large-scale circulation patterns and atmospheric state at the time of the event), hydrological (catchment scale precipitation patterns and antecedent catchment state), and hydrograph-based (indirectly considering generating mechanisms through their effects on hydrograph characteristics). All of these approaches intend to capture the flood generating mechanisms and are useful for characterizing the flood processes at various spatial and temporal scales. However, uncertainty analyses with respect to indicators, classification methods, and data to assess the robustness of the classification are rarely performed which limits the transferability across different geographic regions. It is argued that more rigorous testing is needed. There are opportunities for extending classification methods to include indicators of space-time dynamics of rainfall, antecedent wetness, and routing effects, which will make the classification schemes even more useful for understanding and estimating floods. This article is categorized under: Science of Water > Water Extremes Science of Water > Hydrological Processes Science of Water > Methods KW - flood genesis KW - flood mechanisms KW - flood typology KW - historical floods KW - hydroclimatology of floods Y1 - 2019 U6 - https://doi.org/10.1002/wat2.1353 SN - 2049-1948 VL - 6 IS - 4 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Wietzke, Luzie M. A1 - Merz, Bruno A1 - Gerlitz, Lars A1 - Kreibich, Heidi A1 - Guse, Björn A1 - Castellarin, Attilio A1 - Vorogushyn, Sergiy T1 - Comparative analysis of scalar upper tail indicators JF - Hydrological sciences journal = Journal des sciences hydrologiques N2 - Different upper tail indicators exist to characterize heavy tail phenomena, but no comparative study has been carried out so far. We evaluate the shape parameter (GEV), obesity index, Gini index and upper tail ratio (UTR) against a novel benchmark of tail heaviness - the surprise factor. Sensitivity analyses to sample size and changes in scale-to-location ratio are carried out in bootstrap experiments. The UTR replicates the surprise factor best but is most uncertain and only comparable between records of similar length. For samples with symmetric Lorenz curves, shape parameter, obesity and Gini indices provide consistent indications. For asymmetric Lorenz curves, however, the first two tend to overestimate, whereas Gini index tends to underestimate tail heaviness. We suggest the use of a combination of shape parameter, obesity and Gini index to characterize tail heaviness. These indicators should be supported with calculation of the Lorenz asymmetry coefficients and interpreted with caution. KW - upper tail behaviour KW - heavy-tailed distributions KW - extremes KW - diagnostics KW - surprise Y1 - 2020 U6 - https://doi.org/10.1080/02626667.2020.1769104 SN - 0262-6667 SN - 2150-3435 VL - 65 IS - 10 SP - 1625 EP - 1639 PB - Routledge, Taylor & Francis Group CY - Abingdon ER - TY - JOUR A1 - Merz, Bruno A1 - Apel, Heiko A1 - Dung Nguyen, Viet-Dung A1 - Falter, Daniela A1 - Guse, Björn A1 - Hundecha, Yeshewatesfa A1 - Kreibich, Heidi A1 - Schröter, Kai A1 - Vorogushyn, Sergiy T1 - From precipitation to damage BT - a coupled model chain for spatially coherent, large-scale flood risk assessment JF - Global flood hazard : applications in modeling, mapping and forecasting N2 - Flood risk assessments for large river basins often involve piecing together smaller-scale assessments leading to erroneous risk statements. We describe a coupled model chain for quantifying flood risk at the scale of 100,000 km(2). It consists of a catchment model, a 1D-2D river network model, and a loss model. We introduce the model chain and present two applications. The first application for the Elbe River basin with an area of 66,000 km(2) demonstrates that it is feasible to simulate the complete risk chain for large river basins in a continuous simulation mode with high temporal and spatial resolution. In the second application, RFM is coupled to a multisite weather generator and applied to the Mulde catchment with an area of 6,000 km(2). This approach is able to provide a very long time series of spatially heterogeneous patterns of precipitation, discharge, inundation, and damage. These patterns respect the spatial correlation of the different processes and are suitable to derive large-scale risk estimates. We discuss how the RFM approach can be transferred to the continental scale. Y1 - 2018 SN - 978-1-119-21788-6 SN - 978-1-119-21786-2 U6 - https://doi.org/10.1002/9781119217886.ch10 SN - 0065-8448 VL - 233 SP - 169 EP - 183 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Sairam, Nivedita A1 - Schroeter, Kai A1 - Rözer, Viktor A1 - Merz, Bruno A1 - Kreibich, Heidi T1 - Hierarchical Bayesian Approach for Modeling Spatiotemporal Variability in Flood Damage Processes JF - Water resources research N2 - 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. KW - flood risk KW - flood loss model transfer KW - multilevel probabilistic flood loss model Y1 - 2019 U6 - https://doi.org/10.1029/2019WR025068 SN - 0043-1397 SN - 1944-7973 VL - 55 IS - 10 SP - 8223 EP - 8237 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Metin, Ayse Duha A1 - Nguyen Viet Dung, A1 - Schröter, Kai A1 - Guse, Björn A1 - Apel, Heiko A1 - Kreibich, Heidi A1 - Vorogushyn, Sergiy A1 - Merz, Bruno T1 - How do changes along the risk chain affect flood risk? JF - Natural hazards and earth system sciences N2 - Flood risk is impacted by a range of physical and socio-economic processes. Hence, the quantification of flood risk ideally considers the complete flood risk chain, from atmospheric processes through catchment and river system processes to damage mechanisms in the affected areas. Although it is generally accepted that a multitude of changes along the risk chain can occur and impact flood risk, there is a lack of knowledge of how and to what extent changes in influencing factors propagate through the chain and finally affect flood risk. To fill this gap, we present a comprehensive sensitivity analysis which considers changes in all risk components, i.e. changes in climate, catchment, river system, land use, assets, and vulnerability. The application of this framework to the mesoscale Mulde catchment in Germany shows that flood risk can vary dramatically as a consequence of plausible change scenarios. It further reveals that components that have not received much attention, such as changes in dike systems or in vulnerability, may outweigh changes in often investigated components, such as climate. Although the specific results are conditional on the case study area and the selected assumptions, they emphasize the need for a broader consideration of potential drivers of change in a comprehensive way. Hence, our approach contributes to a better understanding of how the different risk components influence the overall flood risk. Y1 - 2018 U6 - https://doi.org/10.5194/nhess-18-3089-2018 SN - 1561-8633 SN - 1684-9981 VL - 18 IS - 11 SP - 3089 EP - 3108 PB - Copernicus CY - Göttingen ER - TY - GEN A1 - Metin, Ayse Duha A1 - Dung, Nguyen Viet A1 - Schröter, Kai A1 - Guse, Björn A1 - Apel, Heiko A1 - Kreibich, Heidi A1 - Vorogushyn, Sergiy A1 - Merz, Bruno T1 - How do changes along the risk chain affect flood risk? T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Flood risk is impacted by a range of physical and socio-economic processes. Hence, the quantification of flood risk ideally considers the complete flood risk chain, from atmospheric processes through catchment and river system processes to damage mechanisms in the affected areas. Although it is generally accepted that a multitude of changes along the risk chain can occur and impact flood risk, there is a lack of knowledge of how and to what extent changes in influencing factors propagate through the chain and finally affect flood risk. To fill this gap, we present a comprehensive sensitivity analysis which considers changes in all risk components, i.e. changes in climate, catchment, river system, land use, assets, and vulnerability. The application of this framework to the mesoscale Mulde catchment in Germany shows that flood risk can vary dramatically as a consequence of plausible change scenarios. It further reveals that components that have not received much attention, such as changes in dike systems or in vulnerability, may outweigh changes in often investigated components, such as climate. Although the specific results are conditional on the case study area and the selected assumptions, they emphasize the need for a broader consideration of potential drivers of change in a comprehensive way. Hence, our approach contributes to a better understanding of how the different risk components influence the overall flood risk. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1067 KW - global sensitivity analysis KW - climate change KW - river floods KW - frequency KW - Europe KW - model KW - vulnerability KW - adaptation KW - strategies KW - catchment Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-468790 SN - 1866-8372 IS - 1067 ER - TY - JOUR A1 - Schroeter, Kai A1 - Kreibich, Heidi A1 - Vogel, Kristin A1 - Riggelsen, Carsten A1 - Scherbaum, Frank A1 - Merz, Bruno T1 - How useful are complex flood damage models? JF - Water resources research N2 - 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. KW - floods KW - damage KW - model validation KW - Bayesian networks KW - regression tree Y1 - 2014 U6 - https://doi.org/10.1002/2013WR014396 SN - 0043-1397 SN - 1944-7973 VL - 50 IS - 4 SP - 3378 EP - 3395 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Merz, Bruno A1 - Kuhlicke, Christian A1 - Kunz, Michael A1 - Pittore, Massimiliano A1 - Babeyko, Andrey A1 - Bresch, David N. A1 - Domeisen, Daniela I. A1 - Feser, Frauke A1 - Koszalka, Inga A1 - Kreibich, Heidi A1 - Pantillon, Florian A1 - Parolai, Stefano A1 - Pinto, Joaquim G. A1 - Punge, Heinz Jürgen A1 - Rivalta, Eleonora A1 - Schröter, Kai A1 - Strehlow, Karen A1 - Weisse, Ralf A1 - Wurpts, Andreas T1 - Impact forecasting to support emergency management of natural hazards JF - Reviews of geophysics N2 - Forecasting and early warning systems are important investments to protect lives, properties, and livelihood. While early warning systems are frequently used to predict the magnitude, location, and timing of potentially damaging events, these systems rarely provide impact estimates, such as the expected amount and distribution of physical damage, human consequences, disruption of services, or financial loss. Complementing early warning systems with impact forecasts has a twofold advantage: It would provide decision makers with richer information to take informed decisions about emergency measures and focus the attention of different disciplines on a common target. This would allow capitalizing on synergies between different disciplines and boosting the development of multihazard early warning systems. This review discusses the state of the art in impact forecasting for a wide range of natural hazards. We outline the added value of impact-based warnings compared to hazard forecasting for the emergency phase, indicate challenges and pitfalls, and synthesize the review results across hazard types most relevant for Europe. KW - impact forecasting KW - natural hazards KW - early warning Y1 - 2020 U6 - https://doi.org/10.1029/2020RG000704 SN - 8755-1209 SN - 1944-9208 VL - 58 IS - 4 PB - American Geophysical Union CY - Washington ER - TY - GEN A1 - Sieg, Tobias A1 - Shinko, Thomas A1 - Vogel, Kristin A1 - Mechler, Reinhard A1 - Merz, Bruno A1 - Kreibich, Heidi T1 - Integrated assessment of short-term direct and indirect economic flood impacts including uncertainty quantification T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Understanding and quantifying total economic impacts of flood events is essential for flood risk management and adaptation planning. Yet, detailed estimations of joint direct and indirect flood-induced economic impacts are rare. In this study an innovative modeling procedure for the joint assessment of short-term direct and indirect economic flood impacts is introduced. The procedure is applied to 19 economic sectors in eight federal states of Germany after the flood events in 2013. The assessment of the direct economic impacts is object-based and considers uncertainties associated with the hazard, the exposed objects and their vulnerability. The direct economic impacts are then coupled to a supply-side Input-Output-Model to estimate the indirect economic impacts. The procedure provides distributions of direct and indirect economic impacts which capture the associated uncertainties. The distributions of the direct economic impacts in the federal states are plausible when compared to reported values. The ratio between indirect and direct economic impacts shows that the sectors Manufacturing, Financial and Insurance activities suffered the most from indirect economic impacts. These ratios also indicate that indirect economic impacts can be almost as high as direct economic impacts. They differ strongly between the economic sectors indicating that the application of a single factor as a proxy for the indirect impacts of all economic sectors is not appropriate. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 708 KW - June 2013 KW - Damage KW - Model KW - Inoperability KW - Disasters KW - Hazards KW - Germany KW - Losses KW - Event KW - Costs Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-429119 IS - 708 ER - TY - JOUR A1 - Sieg, Tobias A1 - Schinko, Thomas A1 - Vogel, Kristin A1 - Mechler, Reinhard A1 - Merz, Bruno A1 - Kreibich, Heidi T1 - Integrated assessment of short-term direct and indirect economic flood impacts including uncertainty quantification JF - PLoS ONE N2 - Understanding and quantifying total economic impacts of flood events is essential for flood risk management and adaptation planning. Yet, detailed estimations of joint direct and indirect flood-induced economic impacts are rare. In this study an innovative modeling procedure for the joint assessment of short-term direct and indirect economic flood impacts is introduced. The procedure is applied to 19 economic sectors in eight federal states of Germany after the flood events in 2013. The assessment of the direct economic impacts is object-based and considers uncertainties associated with the hazard, the exposed objects and their vulnerability. The direct economic impacts are then coupled to a supply-side Input-Output-Model to estimate the indirect economic impacts. The procedure provides distributions of direct and indirect economic impacts which capture the associated uncertainties. The distributions of the direct economic impacts in the federal states are plausible when compared to reported values. The ratio between indirect and direct economic impacts shows that the sectors Manufacturing, Financial and Insurance activities suffered the most from indirect economic impacts. These ratios also indicate that indirect economic impacts can be almost as high as direct economic impacts. They differ strongly between the economic sectors indicating that the application of a single factor as a proxy for the indirect impacts of all economic sectors is not appropriate. KW - June 2013 KW - Damage KW - Model KW - Inoperability KW - Disasters KW - Hazards KW - Germany KW - Losses KW - Event KW - Costs Y1 - 2019 U6 - https://doi.org/10.1371/journal.pone.0212932 SN - 1932-6203 VL - 14 IS - 4 PB - Public Library of Science CY - San Francisco ER - TY - JOUR A1 - Speckhann, Gustavo Andrei A1 - Kreibich, Heidi A1 - Merz, Bruno T1 - Inventory of dams in Germany JF - Earth system science data : the data publishing journal N2 - Dams are an important element of water resources management. Data about dams are crucial for practitioners, scientists, and policymakers for various purposes, such as seasonal forecasting of water availability or flood mitigation. However, detailed information on dams on the national level for Germany is so far not freely available. We present the most comprehensive open-access dam inventory for Germany (DIG) to date. We have collected and combined information on dams using books, state agency reports, engineering reports, and internet pages. We have applied a priority rule that ensures the highest level of reliability for the dam information. Our dam inventory comprises 530 dams in Germany with information on name, location, river, start year of construction and operation, crest length, dam height, lake area, lake volume, purpose, dam structure, and building characteristics. We have used a global, satellite-based water surface raster to evaluate the location of the dams. A significant proportion (63 %) of dams were built between 1950-2013. Our inventory shows that dams in Germany are mostly single-purpose (52 %), 53% can be used for flood control, and 25% are involved in energy production. The inventory is freely available through GFZ (GeoForschungsZentrum) Data Services (https://doi.org/10.5880/GFZ.4.4.2020.005) Y1 - 2021 U6 - https://doi.org/10.5194/essd-13-731-2021 SN - 1866-3508 SN - 1866-3516 VL - 13 IS - 2 SP - 731 EP - 740 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Kreibich, Heidi A1 - Hudson, Paul A1 - Merz, Bruno T1 - Knowing what to do substantially improves the effectiveness of flood early warning JF - Bulletin of the American Meteorological Society N2 - Flood warning systems are longstanding success stories with respect to protecting human life, but monetary losses continue to grow. Knowledge on the effectiveness of flood early warning in reducing monetary losses is scarce, especially at the individual level. To gain more knowledge in this area, we analyze a dataset that is unique with respect to detailed information on warning reception and monetary losses at the property level and with respect to amount of data available. The dataset contains 4,468 loss cases from six flood events in Germany. These floods occurred between 2002 and 2013. The data from each event were collected by computer-aided telephone interviews in four surveys following a repeated cross-sectional design. We quantitatively reveal that flood early warning is only effective in reducing monetary losses when people know what to do when they receive the warning. We also show that particularly long-term preparedness is associated with people knowing what to do when they receive a warning. Thus, risk communication, training, and (financial) support for private preparedness are effective in mitigating flood losses in two ways: precautionary measures and more effective emergency responses. KW - adaptation KW - damage assessment KW - emergency preparedness KW - emergency KW - response KW - flood events Y1 - 2021 U6 - https://doi.org/10.1175/BAMS-D-20-0262.1 SN - 0003-0007 SN - 1520-0477 VL - 102 IS - 7 SP - E1450 EP - E1463 PB - American Meteorological Soc. CY - Boston ER - TY - JOUR A1 - Farrag, Mostafa A1 - Brill, Fabio Alexander A1 - Nguyen, Viet Dung A1 - Sairam, Nivedita A1 - Schröter, Kai A1 - Kreibich, Heidi A1 - Merz, Bruno A1 - de Bruijn, Karin M. A1 - Vorogushyn, Sergiy T1 - On the role of floodplain storage and hydrodynamic interactions in flood risk estimation JF - Hydrological sciences journal = Journal des sciences hydrologiques N2 - Hydrodynamic interactions, i.e. the floodplain storage effects caused by inundations upstream on flood wave propagation, inundation areas, and flood damage downstream, are important but often ignored in large-scale flood risk assessments. Although new methods considering these effects sometimes emerge, they are often limited to a small or meso scale. In this study, we investigate the role of hydrodynamic interactions and floodplain storage on flood hazard and risk in the German part of the Rhine basin. To do so, we compare a new continuous 1D routing scheme within a flood risk model chain to the piece-wise routing scheme, which largely neglects floodplain storage. The results show that floodplain storage is significant, lowers water levels and discharges, and reduces risks by over 50%. Therefore, for accurate risk assessments, a system approach must be adopted, and floodplain storage and hydrodynamic interactions must carefully be considered. KW - hydrodynamic interactions KW - derived flood risk analysis KW - flood modelling; KW - Rhine basin Y1 - 2022 U6 - https://doi.org/10.1080/02626667.2022.2030058 SN - 0262-6667 SN - 2150-3435 VL - 67 IS - 4 SP - 508 EP - 534 PB - Routledge, Taylor & Francis Group CY - Abingdon ER - TY - JOUR A1 - Rözer, Viktor A1 - Kreibich, Heidi A1 - Schröter, Kai A1 - Müller, Meike A1 - Sairam, Nivedita A1 - Doss-Gollin, James A1 - Lall, Upmanu A1 - Merz, Bruno T1 - Probabilistic Models Significantly Reduce Uncertainty in Hurricane Harvey Pluvial Flood Loss Estimates JF - Earths future N2 - Pluvial flood risk is mostly excluded in urban flood risk assessment. However, the risk of pluvial flooding is a growing challenge with a projected increase of extreme rainstorms compounding with an ongoing global urbanization. Considered as a flood type with minimal impacts when rainfall rates exceed the capacity of urban drainage systems, the aftermath of rainfall-triggered flooding during Hurricane Harvey and other events show the urgent need to assess the risk of pluvial flooding. Due to the local extent and small-scale variations, the quantification of pluvial flood risk requires risk assessments on high spatial resolutions. While flood hazard and exposure information is becoming increasingly accurate, the estimation of losses is still a poorly understood component of pluvial flood risk quantification. We use a new probabilistic multivariable modeling approach to estimate pluvial flood losses of individual buildings, explicitly accounting for the associated uncertainties. Except for the water depth as the common most important predictor, we identified the drivers for having loss or not and for the degree of loss to be different. Applying this approach to estimate and validate building structure losses during Hurricane Harvey using a property level data set, we find that the reliability and dispersion of predictive loss distributions vary widely depending on the model and aggregation level of property level loss estimates. Our results show that the use of multivariable zero-inflated beta models reduce the 90% prediction intervalsfor Hurricane Harvey building structure loss estimates on average by 78% (totalling U.S.$3.8 billion) compared to commonly used models. KW - pluvial flooding KW - loss modeling KW - urban flooding KW - probabilistic KW - Hurricane Harvey KW - climate change adaptation Y1 - 2019 U6 - https://doi.org/10.1029/2018EF001074 SN - 2328-4277 VL - 7 IS - 4 SP - 384 EP - 394 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Kreibich, Heidi A1 - Botto, Anna A1 - Merz, Bruno A1 - Schröter, Kai T1 - Probabilistic, Multivariable Flood Loss Modeling on the Mesoscale with BT-FLEMO JF - Risk analysis N2 - Flood loss modeling is an important component for risk analyses and decision support in flood risk management. Commonly, flood loss models describe complex damaging processes by simple, deterministic approaches like depth-damage functions and are associated with large uncertainty. To improve flood loss estimation and to provide quantitative information about the uncertainty associated with loss modeling, a probabilistic, multivariable Bagging decision Tree Flood Loss Estimation MOdel (BT-FLEMO) for residential buildings was developed. The application of BT-FLEMO provides a probability distribution of estimated losses to residential buildings per municipality. BT-FLEMO was applied and validated at the mesoscale in 19 municipalities that were affected during the 2002 flood by the River Mulde in Saxony, Germany. Validation was undertaken on the one hand via a comparison with six deterministic loss models, including both depth-damage functions and multivariable models. On the other hand, the results were compared with official loss data. BT-FLEMO outperforms deterministic, univariable, and multivariable models with regard to model accuracy, although the prediction uncertainty remains high. An important advantage of BT-FLEMO is the quantification of prediction uncertainty. The probability distribution of loss estimates by BT-FLEMO well represents the variation range of loss estimates of the other models in the case study. KW - Damage modeling KW - multiparameter KW - probabilistic KW - uncertainty KW - validation Y1 - 2016 U6 - https://doi.org/10.1111/risa.12650 SN - 0272-4332 SN - 1539-6924 VL - 37 IS - 4 SP - 774 EP - 787 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Sairam, Nivedita A1 - Brill, Fabio Alexander A1 - Sieg, Tobias A1 - Farrag, Mostafa A1 - Kellermann, Patric A1 - Viet Dung Nguyen, A1 - Lüdtke, Stefan A1 - Merz, Bruno A1 - Schröter, Kai A1 - Vorogushyn, Sergiy A1 - Kreibich, Heidi T1 - Process-based flood risk assessment for Germany JF - Earth's future / American Geophysical Union N2 - Large-scale flood risk assessments are crucial for decision making, especially with respect to new flood defense schemes, adaptation planning and estimating insurance premiums. We apply the process-based Regional Flood Model (RFM) to simulate a 5000-year flood event catalog for all major catchments in Germany and derive risk curves based on the losses per economic sector. The RFM uses a continuous process simulation including a multisite, multivariate weather generator, a hydrological model considering heterogeneous catchment processes, a coupled 1D-2D hydrodynamic model considering dike overtopping and hinterland storage, spatially explicit sector-wise exposure data and empirical multi-variable loss models calibrated for Germany. For all components, uncertainties in the data and models are estimated. We estimate the median Expected Annual Damage (EAD) and Value at Risk at 99.5% confidence for Germany to be euro0.529 bn and euro8.865 bn, respectively. The commercial sector dominates by making about 60% of the total risk, followed by the residential sector. The agriculture sector gets affected by small return period floods and only contributes to less than 3% to the total risk. The overall EAD is comparable to other large-scale estimates. However, the estimation of losses for specific return periods is substantially improved. The spatial consistency of the risk estimates avoids the large overestimation of losses for rare events that is common in other large-scale assessments with homogeneous return periods. Thus, the process-based, spatially consistent flood risk assessment by RFM is an important step forward and will serve as a benchmark for future German-wide flood risk assessments. KW - risk model chain KW - continuous simulation KW - expected annual damage KW - risk KW - curves KW - multi-sector risk Y1 - 2021 U6 - https://doi.org/10.1029/2021EF002259 SN - 2328-4277 VL - 9 IS - 10 PB - Wiley-Blackwell CY - Hoboken, NJ ER - TY - JOUR A1 - Sairam, Nivedita A1 - Schröter, Kai A1 - Lüdtke, Stefan A1 - Merz, Bruno A1 - Kreibich, Heidi T1 - Quantifying Flood Vulnerability Reduction via Private Precaution JF - Earth future N2 - Private precaution is an important component in contemporary flood risk management and climate adaptation. However, quantitative knowledge about vulnerability reduction via private precautionary measures is scarce and their effects are hardly considered in loss modeling and risk assessments. However, this is a prerequisite to enable temporally dynamic flood damage and risk modeling, and thus the evaluation of risk management and adaptation strategies. To quantify the average reduction in vulnerability of residential buildings via private precaution empirical vulnerability data (n = 948) is used. Households with and without precautionary measures undertaken before the flood event are classified into treatment and nontreatment groups and matched. Postmatching regression is used to quantify the treatment effect. Additionally, we test state-of-the-art flood loss models regarding their capability to capture this difference in vulnerability. The estimated average treatment effect of implementing private precaution is between 11 and 15 thousand EUR per household, confirming the significant effectiveness of private precautionary measures in reducing flood vulnerability. From all tested flood loss models, the expert Bayesian network-based model BN-FLEMOps and the rule-based loss model FLEMOps perform best in capturing the difference in vulnerability due to private precaution. Thus, the use of such loss models is suggested for flood risk assessments to effectively support evaluations and decision making for adaptable flood risk management. KW - flood loss KW - average treatment effect KW - matching methods KW - loss models KW - risk analysis KW - adaptation Y1 - 2019 U6 - https://doi.org/10.1029/2018EF000994 SN - 2328-4277 VL - 7 IS - 3 SP - 235 EP - 249 PB - American Geophysical Union CY - Washington ER - TY - GEN A1 - Sieg, Tobias A1 - Vogel, Kristin A1 - Merz, Bruno A1 - Kreibich, Heidi T1 - Seamless Estimation of Hydrometeorological Risk Across Spatial Scales T2 - Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe N2 - Hydrometeorological hazards caused losses of approximately 110 billion U.S. Dollars in 2016 worldwide. Current damage estimations do not consider the uncertainties in a comprehensive way, and they are not consistent between spatial scales. Aggregated land use data are used at larger spatial scales, although detailed exposure data at the object level, such as openstreetmap.org, is becoming increasingly available across the globe.We present a probabilistic approach for object-based damage estimation which represents uncertainties and is fully scalable in space. The approach is applied and validated to company damage from the flood of 2013 in Germany. Damage estimates are more accurate compared to damage models using land use data, and the estimation works reliably at all spatial scales. Therefore, it can as well be used for pre-event analysis and risk assessments. This method takes hydrometeorological damage estimation and risk assessments to the next level, making damage estimates and their uncertainties fully scalable in space, from object to country level, and enabling the exploitation of new exposure data. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 743 KW - spatial scales KW - risk assessment KW - hydro-meterological hazards KW - object-based damage modeling KW - uncertainty KW - probabilistic approaches Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-435341 SN - 1866-8372 IS - 743 SP - 574 EP - 581 ER - TY - JOUR A1 - Sieg, Tobias A1 - Vogel, Kristin A1 - Merz, Bruno A1 - Kreibich, Heidi T1 - Seamless Estimation of Hydrometeorological Risk Across Spatial Scales JF - Earth's Future N2 - Hydrometeorological hazards caused losses of approximately 110 billion U.S. Dollars in 2016 worldwide. Current damage estimations do not consider the uncertainties in a comprehensive way, and they are not consistent between spatial scales. Aggregated land use data are used at larger spatial scales, although detailed exposure data at the object level, such as openstreetmap.org, is becoming increasingly available across the globe.We present a probabilistic approach for object-based damage estimation which represents uncertainties and is fully scalable in space. The approach is applied and validated to company damage from the flood of 2013 in Germany. Damage estimates are more accurate compared to damage models using land use data, and the estimation works reliably at all spatial scales. Therefore, it can as well be used for pre-event analysis and risk assessments. This method takes hydrometeorological damage estimation and risk assessments to the next level, making damage estimates and their uncertainties fully scalable in space, from object to country level, and enabling the exploitation of new exposure data. KW - spatial scales KW - risk assessment KW - hydro-meterological hazards KW - object-based damage modeling KW - uncertainty KW - probabilistic approaches Y1 - 2019 U6 - https://doi.org/10.1029/2018EF001122 SN - 2328-4277 VL - 7 IS - 5 SP - 574 EP - 581 PB - Wiley-Blackwell CY - Hoboken, NJ ER - TY - JOUR A1 - Metin, Ayse Duha A1 - Dung, Nguyen Viet A1 - Schröter, Kai A1 - Vorogushyn, Sergiy A1 - Guse, Björn A1 - Kreibich, Heidi A1 - Merz, Bruno T1 - The role of spatial dependence for large-scale flood risk estimation JF - Natural hazards and earth system sciences N2 - Flood risk assessments are typically based on scenarios which assume homogeneous return periods of flood peaks throughout the catchment. This assumption is unrealistic for real flood events and may bias risk estimates for specific return periods. We investigate how three assumptions about the spatial dependence affect risk estimates: (i) spatially homogeneous scenarios (complete dependence), (ii) spatially heterogeneous scenarios (modelled dependence) and (iii) spatially heterogeneous but uncorrelated scenarios (complete independence). To this end, the model chain RFM (regional flood model) is applied to the Elbe catchment in Germany, accounting for the spatio-temporal dynamics of all flood generation processes, from the rainfall through catchment and river system processes to damage mechanisms. Different assumptions about the spatial dependence do not influence the expected annual damage (EAD); however, they bias the risk curve, i.e. the cumulative distribution function of damage. The widespread assumption of complete dependence strongly overestimates flood damage of the order of 100% for return periods larger than approximately 200 years. On the other hand, for small and medium floods with return periods smaller than approximately 50 years, damage is underestimated. The overestimation aggravates when risk is estimated for larger areas. This study demonstrates the importance of representing the spatial dependence of flood peaks and damage for risk assessments. Y1 - 2020 U6 - https://doi.org/10.5194/nhess-20-967-2020 SN - 1561-8633 SN - 1684-9981 VL - 20 IS - 4 SP - 967 EP - 979 PB - European Geosciences Union (EGU) ; Copernicus CY - Göttingen ER - TY - JOUR A1 - Barendrecht, Marlies H. A1 - Viglione, Alberto A1 - Kreibich, Heidi A1 - Merz, Bruno A1 - Vorogushyn, Sergiy A1 - Blöschl, G. T1 - The Value of Empirical Data for Estimating the Parameters of a Sociohydrological Flood Risk Model JF - Water resources research N2 - In this paper, empirical data are used to estimate the parameters of a sociohydrological flood risk model. The proposed model, which describes the interactions between floods, settlement density, awareness, preparedness, and flood loss, is based on the literature. Data for the case study of Dresden, Germany, over a period of 200years, are used to estimate the model parameters through Bayesian inference. The credibility bounds of their estimates are small, even though the data are rather uncertain. A sensitivity analysis is performed to examine the value of the different data sources in estimating the model parameters. In general, the estimated parameters are less biased when using data at the end of the modeled period. Data about flood awareness are the most important to correctly estimate the parameters of this model and to correctly model the system dynamics. Using more data for other variables cannot compensate for the absence of awareness data. More generally, the absence of data mostly affects the estimation of the parameters that are directly related to the variable for which data are missing. This paper demonstrates that combining sociohydrological modeling and empirical data gives additional insights into the sociohydrological system, such as quantifying the forgetfulness of the society, which would otherwise not be easily achieved by sociohydrological models without data or by standard statistical analysis of empirical data. Y1 - 2019 U6 - https://doi.org/10.1029/2018WR024128 SN - 0043-1397 SN - 1944-7973 VL - 55 IS - 2 SP - 1312 EP - 1336 PB - American Geophysical Union CY - Washington ER - TY - JOUR A1 - Sieg, Tobias A1 - Vogel, Kristin A1 - Merz, Bruno A1 - Kreibich, Heidi T1 - Tree-based flood damage modeling of companies: Damage processes and model performance JF - Water resources research N2 - Reliable flood risk analyses, including the estimation of damage, are an important prerequisite for efficient risk management. However, not much is known about flood damage processes affecting companies. Thus, we conduct a flood damage assessment of companies in Germany with regard to two aspects. First, we identify relevant damage-influencing variables. Second, we assess the prediction performance of the developed damage models with respect to the gain by using an increasing amount of training data and a sector-specific evaluation of the data. Random forests are trained with data from two postevent surveys after flood events occurring in the years 2002 and 2013. For a sector-specific consideration, the data set is split into four subsets corresponding to the manufacturing, commercial, financial, and service sectors. Further, separate models are derived for three different company assets: buildings, equipment, and goods and stock. Calculated variable importance values reveal different variable sets relevant for the damage estimation, indicating significant differences in the damage process for various company sectors and assets. With an increasing number of data used to build the models, prediction errors decrease. Yet the effect is rather small and seems to saturate for a data set size of several hundred observations. In contrast, the prediction improvement achieved by a sector-specific consideration is more distinct, especially for damage to equipment and goods and stock. Consequently, sector-specific data acquisition and a consideration of sector-specific company characteristics in future flood damage assessments is expected to improve the model performance more than a mere increase in data. Y1 - 2017 U6 - https://doi.org/10.1002/2017WR020784 SN - 0043-1397 SN - 1944-7973 VL - 53 SP - 6050 EP - 6068 PB - American Geophysical Union CY - Washington ER -