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  - GEN
A1  - Rözer, Viktor
A1  - Müller, Meike
A1  - Bubeck, Philip
A1  - Kienzler, Sarah
A1  - Thieken, Annegret
A1  - Pech, Ina
A1  - Schröter, Kai
A1  - Buchholz, Oliver
A1  - Kreibich, Heidi
T1  - Coping with pluvial floods by private households
N2  - Pluvial floods have caused severe damage to urban areas in recent years. With a projected increase in extreme precipitation as well as an ongoing urbanization, pluvial flood damage is expected to increase in the future. Therefore, further insights, especially on the adverse consequences of pluvial floods and their mitigation, are needed. To gain more knowledge, empirical damage data from three different pluvial flood events in Germany were collected through computer-aided telephone interviews. Pluvial flood awareness as well as flood experience were found to be low before the respective flood events. The level of private precaution increased considerably after all events, but is mainly focused on measures that are easy to implement. Lower inundation depths, smaller potential losses as compared with fluvial floods, as well as the fact that pluvial flooding may occur everywhere, are expected to cause a shift in damage mitigation from precaution to emergency response. However, an effective implementation of emergency measures was constrained by a low dissemination of early warnings in the study areas. Further improvements of early warning systems including dissemination as well as a rise in pluvial flood preparedness are important to reduce future pluvial flood damage.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 355 
KW  - pluvial floods
KW  - surface water flooding
KW  - emergency response
KW  - early warning
KW  - preparedness
KW  - damage
KW  - mitigation
Y1  - 2017
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-400465
ER  - 
TY  - JOUR
A1  - Rözer, Viktor
A1  - Müller, Meike
A1  - Bubeck, Philip
A1  - Kienzler, Sarah
A1  - Thieken, Annegret
A1  - Pech, Ina
A1  - Schröter, Kai
A1  - Buchholz, Oliver
A1  - Kreibich, Heidi
T1  - Coping with Pluvial Floods by Private Households
JF  - Water
N2  - Pluvial floods have caused severe damage to urban areas in recent years. With a projected increase in extreme precipitation as well as an ongoing urbanization, pluvial flood damage is expected to increase in the future. Therefore, further insights, especially on the adverse consequences of pluvial floods and their mitigation, are needed. To gain more knowledge, empirical damage data from three different pluvial flood events in Germany were collected through computer-aided telephone interviews. Pluvial flood awareness as well as flood experience were found to be low before the respective flood events. The level of private precaution increased considerably after all events, but is mainly focused on measures that are easy to implement. Lower inundation depths, smaller potential losses as compared with fluvial floods, as well as the fact that pluvial flooding may occur everywhere, are expected to cause a shift in damage mitigation from precaution to emergency response. However, an effective implementation of emergency measures was constrained by a low dissemination of early warnings in the study areas. Further improvements of early warning systems including dissemination as well as a rise in pluvial flood preparedness are important to reduce future pluvial flood damage.
KW  - pluvial floods
KW  - surface water flooding
KW  - emergency response
KW  - early warning
KW  - preparedness
KW  - damage
KW  - mitigation
Y1  - 2016
U6  - https://doi.org/10.3390/w8070304
SN  - 2073-4441
VL  - 8
PB  - MDPI
CY  - Basel
ER  - 
TY  - BOOK
A1  - Thieken, Annegret
A1  - Bessel, Tina
A1  - Callsen, Ines
A1  - Falter, Daniela
A1  - Hasan, Issa
A1  - Kienzler, Sarah
A1  - Kox, Thomas
A1  - Kreibich, Heidi
A1  - Kuhlicke, Christian
A1  - Kunz, Michael
A1  - Matthias, Max
A1  - Meyer, Volker
A1  - Mühr, Bernhard
A1  - Müller, Meike
A1  - Otto, Antje
A1  - Pech, Ina
A1  - Petrow, Theresia
A1  - Pisi, Sebastian
A1  - Rother, Karl-Heinz
A1  - Schröter, Kai
T1  - Das Hochwasser im Juni 2013
BT  - Bewährungsprobe für das Hochwasserrisikomanagement in Deutschland
T3  - Schriftenreihe des DKKV ; 53
Y1  - 2015
SN  - 978-3-933181-62-6
PB  - Deutsches Komitee Katastrophenvorsorge
CY  - Bonn
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  - 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  - 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  - JOUR
A1  - Vogel, Kristin
A1  - Weise, Laura
A1  - Schröter, Kai
A1  - Thieken, Annegret
T1  - Identifying Driving Factors in Flood-Damaging Processes Using Graphical Models
JF  - Water resources research
N2  - Flood damage estimation is a core task in flood risk assessments and requires reliable flood loss models. Identifying the driving factors of flood loss at residential buildings and gaining insight into their relations is important to improve our understanding of flood damage processes. For that purpose, we learn probabilistic graphical models, which capture and illustrate (in-)dependencies between the considered variables. The models are learned based on postevent surveys with flood-affected residents after six flood events, which occurred in Germany between 2002 and 2013. Besides the sustained building damage, the survey data contain information about flooding parameters, early warning and emergency measures, property-level mitigation measures and preparedness, socioeconomic characteristics of the household, and building characteristics. The analysis considers the entire data set with a total of 4,468 cases as well as subsets of the data set partitioned into single flood events and flood types: river floods, levee breaches, surface water flooding, and groundwater floods, to reveal differences in the damaging processes. The learned networks suggest that the flood loss ratio of residential buildings is directly influenced by hydrological and hydraulic aspects as well as by building characteristics and property-level mitigation measures. The study demonstrates also that for different flood events and process types the building damage is influenced by varying factors. This suggests that flood damage models need to be capable of reproducing these differences for spatial and temporal model transfers.
KW  - flood loss
KW  - Bayesian Network
KW  - Markov Blanket
KW  - vulnerability
KW  - Germany
Y1  - 2018
U6  - https://doi.org/10.1029/2018WR022858
SN  - 0043-1397
SN  - 1944-7973
VL  - 54
IS  - 11
SP  - 8864
EP  - 8889
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  - THES
A1  - Schröter, Kai
T1  - Improved flood risk assessment
BT  - new data sources and methods for flood risk modelling
N2  - Rivers have always flooded their floodplains. Over 2.5 billion people worldwide have been affected by flooding in recent decades. The economic damage is also considerable, averaging 100 billion US dollars per year. There is no doubt that damage and other negative effects of floods can be avoided. However, this has a price: financially and politically. Costs and benefits can be estimated through risk assessments. Questions about the location and frequency of floods, about the objects that could be affected and their vulnerability are of importance for flood risk managers, insurance companies and politicians. Thus, both variables and factors from the fields of hydrology and sociol-economics play a role with multi-layered connections. One example are dikes along a river, which on the one hand contain floods, but on the other hand, by narrowing the natural floodplains, accelerate the flood discharge and increase the danger of flooding for the residents downstream. Such larger connections must be included in the assessment of flood risk. However, in current procedures this is accompanied by simplifying assumptions. Risk assessments are therefore fuzzy and associated with uncertainties.
This thesis investigates the benefits and possibilities of new data sources for improving flood risk assessment. New methods and models are developed, which take the mentioned interrelations better into account and also quantify the existing uncertainties of the model results, and thus enable statements about the reliability of risk estimates. For this purpose, data on flood events from various sources are collected and evaluated. This includes precipitation and flow records at measuring stations as well as for instance images from social media, which can help to delineate the flooded areas and estimate flood damage with location information. Machine learning methods have been successfully used to recognize and understand correlations between floods and impacts from a wide range of data and to develop improved models. 
Risk models help to develop and evaluate strategies to reduce flood risk. These tools also provide advanced insights into the interplay of various factors and on the expected consequences of flooding. This work shows progress in terms of an improved assessment of flood risks by using diverse data from different sources with innovative methods as well as by the further development of models. Flood risk is variable due to economic and climatic changes, and other drivers of risk. In order to keep the knowledge about flood risks up-to-date, robust, efficient and adaptable methods as proposed in this thesis are of increasing importance.
N2  - Flüsse haben seit jeher ihre Auen überflutet. In den vergangenen Jahrzehnten waren weltweit über 2,5 Milliarden Menschen durch Hochwasser betroffen. Auch der ökonomische Schaden ist mit durchschnittlich 100 Milliarden US Dollar pro Jahr erheblich. Zweifelsohne können Schäden und andere negative Auswirkungen von Hochwasser vermieden werden. Allerdings hat dies einen Preis: finanziell und politisch. Kosten und Nutzen lassen sich durch Risikobewertungen abschätzen. Dabei werden in der Wasserwirtschaft, von Versicherungen und der Politik Fragen nach dem Ort und der Häufigkeit von Überflutungen, nach den Dingen, die betroffen sein könnten und deren Anfälligkeit untersucht. Somit spielen sowohl Größen und Faktoren aus den Bereichen der Hydrologie und Sozioökonmie mit vielschichtigen Zusammenhängen eine Rolle. Ein anschauliches Beispiel sind Deiche entlang eines Flusses, die einerseits in ihrem Abschnitt Überflutungen eindämmen, andererseits aber durch die Einengung der natürlichen Vorländer den Hochwasserabfluss beschleunigen und die Gefährdung für die Anlieger flussab verschärfen. Solche größeren Zusammenhänge müssen in der Bewertung des Hochwasserrisikos einbezogen werden. In derzeit gängigen Verfahren geht dies mit vereinfachenden Annahmen einher. Risikoabschätzungen sind daher unscharf und mit Unsicherheiten verbunden.
Diese Arbeit untersucht den Nutzen und die Möglichkeiten neuer Datensätze für eine Verbesserung der Hochwasserrisikoabschätzung. Es werden neue Methoden und Modelle entwickelt, die die angesprochenen Zusammenhänge stärker berücksichtigen und auch die bestehenden Unsicherheiten der Modellergebnisse beziffern und somit die Verlässlichkeit der getroffenen Aussagen einordnen lassen. Dafür werden Daten zu Hochwasserereignissen aus verschiedenen Quellen erfasst und ausgewertet. Dazu zählen neben Niederschlags-und Durchflussaufzeichnungen an Messstationen beispielsweise auch Bilder aus sozialen Medien, die mit Ortsangaben und Bildinhalten helfen können, die Überflutungsflächen abzugrenzen und Hochwasserschäden zu schätzen. Verfahren des Maschinellen Lernens wurden erfolgreich eingesetzt, um aus vielfältigen Daten, Zusammenhänge zwischen Hochwasser und Auswirkungen zu erkennen, besser zu verstehen und verbesserte Modelle zu entwickeln. 
Solche Risikomodelle helfen bei der Entwicklung und Bewertung von Strategien zur Minderung des Hochwasserrisikos. Diese Werkzeuge ermöglichen darüber hinaus Einblicke in das Zusammenspiel verschiedener Faktoren sowie Aussagen zu den zu erwartenden Folgen auch von Hochwassern, die das bisher bekannte Ausmaß übersteigen. Diese Arbeit verzeichnet Fortschritte in Bezug auf eine verbesserte Bewertung von Hochwasserrisiken durch die Nutzung vielfältiger Daten aus unterschiedlichen Quellen mit innovativen Verfahren sowie der Weiterentwicklung von Modellen. Das Hochwasserrisiko unterliegt durch wirtschaftliche Entwicklungen und klimatische Veränderungen einem steten Wandel. Um das Wissen über Risiken aktuell zu halten sind robuste, leistungs- und anpassungsfähige Verfahren wie sie in dieser Arbeit vorgestellt werden von zunehmender Bedeutung.
T2  - Verbesserte Hochwasserrisikobewertung: Neue Datenquellen und Methoden für die Risikomodellierung
KW  - flood
KW  - risk
KW  - vulnerability
KW  - machine learning
KW  - uncertainty
KW  - Hochwasser
KW  - Risiko
KW  - Vulnerabilität
KW  - Maschinelles Lernen
KW  - Unsicherheiten
Y1  - 2020
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-480240
ER  - 
TY  - JOUR
A1  - Kreibich, Heidi
A1  - Müller, Meike
A1  - Schröter, Kai
A1  - Thieken, Annegret
T1  - New insights into flood warning reception and emergency response by affected parties
JF  - Natural hazards and earth system sciences
N2  - Flood damage can be mitigated if the parties at risk are reached by flood warnings and if they know how to react appropriately. To gain more knowledge about warning reception and emergency response of private households and companies, surveys were undertaken after the August 2002 and the June 2013 floods in Germany. Despite pronounced regional differences, the results show a clear overall picture: in 2002, early warnings did not work well; e.g. many households (27 %) and companies (45 %) stated that they had not received any flood warnings. Additionally, the preparedness of private households and companies was low in 2002, mainly due to a lack of flood experience. After the 2002 flood, many initiatives were launched and investments undertaken to improve flood risk management, including early warnings and an emergency response in Germany. In 2013, only a small share of the affected households (5 %) and companies (3 %) were not reached by any warnings. Additionally, private households and companies were better prepared. For instance, the share of companies which have an emergency plan in place has increased from 10% in 2002 to 34% in 2013. However, there is still room for improvement, which needs to be triggered mainly by effective risk and emergency communication. The challenge is to continuously maintain and advance an integrated early warning and emergency response system even without the occurrence of extreme floods.
Y1  - 2017
U6  - https://doi.org/10.5194/nhess-17-2075-2017
SN  - 1561-8633
VL  - 17
SP  - 2075
EP  - 2092
PB  - Copernicus
CY  - Göttingen
ER  - 
TY  - GEN
A1  - Kreibich, Heidi
A1  - Müller, Meike
A1  - Schröter, Kai
A1  - Thieken, Annegret
T1  - New insights into flood warning reception and emergency response by affected parties
T2  - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
N2  - Flood damage can be mitigated if the parties at risk are reached by flood warnings and if they know how to react appropriately. To gain more knowledge about warning reception and emergency response of private households and companies, surveys were undertaken after the August 2002 and the June 2013 floods in Germany. Despite pronounced regional differences, the results show a clear overall picture: in 2002, early warnings did not work well; e.g. many households (27 %) and companies (45 %) stated that they had not received any flood warnings. Additionally, the preparedness of private households and companies was low in 2002, mainly due to a lack of flood experience. After the 2002 flood, many initiatives were launched and investments undertaken to improve flood risk management, including early warnings and an emergency response in Germany. In 2013, only a small share of the affected households (5 %) and companies (3 %) were not reached by any warnings. Additionally, private households and companies were better prepared. For instance, the share of companies which have an emergency plan in place has increased from 10% in 2002 to 34% in 2013. However, there is still room for improvement, which needs to be triggered mainly by effective risk and emergency communication. The challenge is to continuously maintain and advance an integrated early warning and emergency response system even without the occurrence of extreme floods.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 659 
KW  - june 2013 Flood
KW  - circulation patterns
KW  - affected residents
KW  - extreme flood
KW  - august 2002
KW  - Germany
KW  - risk
KW  - damage
KW  - preparedness
KW  - recovery
Y1  - 2019
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-418381
SN  - 1866-8372
IS  - 659
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  - Thieken, Annegret
A1  - Kienzler, Sarah
A1  - Kreibich, Heidi
A1  - Kuhlicke, Christian
A1  - Kunz, Michael
A1  - Mühr, Bernhard
A1  - Müller, Meike
A1  - Otto, Antje
A1  - Petrow, Theresia
A1  - Pisi, Sebastian
A1  - Schröter, Kai
T1  - Review of the flood risk management system in Germany after the major flood in 2013
N2  - Widespread flooding in June 2013 caused damage costs of €6 to 8 billion in Germany, and awoke many memories of the floods in August 2002, which resulted in total damage of €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.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 294 
KW  - August 2002 flood
KW  - Central Europe
KW  - Floods Directive
KW  - June 2013 flood
KW  - governance
KW  - risk management cycle
Y1  - 2016
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-100600
SN  - 1866-8372
ER  - 
TY  - JOUR
A1  - Thieken, Annegret
A1  - Kienzler, Sarah
A1  - Kreibich, Heidi
A1  - Kuhlicke, Christian
A1  - Kunz, Michael
A1  - Mühr, Bernhard
A1  - Müller, Meike
A1  - Otto, Antje
A1  - Petrow, Theresia
A1  - Pisi, Sebastian
A1  - Schröter, Kai
T1  - Review of the flood risk management system in Germany after the major flood in 2013
JF  - Ecology and society : E&S ; a journal of integrative science for resilience and sustainability
N2  - Widespread flooding in June 2013 caused damage costs of €6 to 8 billion in Germany, and awoke many memories of the floods in August 2002, which resulted in total damage of €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.
KW  - August 2002 flood
KW  - Central Europe
KW  - Floods Directive
KW  - governance
KW  - June 2013 flood
KW  - risk management cycle
Y1  - 2016
U6  - https://doi.org/10.5751/ES-08547-210251
SN  - 1708-3087
SN  - 1195-5449
VL  - 21
IS  - 2
PB  - Resilience Alliance
CY  - Wolfville, NS
ER  -