Articles | Volume 16, issue 4
https://doi.org/10.5194/nhess-16-1005-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/nhess-16-1005-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
20 Apr 2016
Research article |
| 20 Apr 2016
Preface: Flood-risk analysis and integrated management
Philip Bubeck
CORRESPONDING AUTHOR
University of Potsdam, Institute of Earth and Environmental Science,
Karl-Liebknecht-Strasse 24-25, 14476 Potsdam, Germany
Jeroen C. J. H. Aerts
Institute for Environmental Studies (IVM), VU University Amsterdam, the
Netherlands
Hans de Moel
Institute for Environmental Studies (IVM), VU University Amsterdam, the
Netherlands
Heidi Kreibich
Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences,
Section 5.4 Hydrology, Telegrafenberg, 14473 Potsdam, Germany
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Annegret H. Thieken, Guilherme Samprogna Mohor, Heidi Kreibich, and Meike Müller
Nat. Hazards Earth Syst. Sci., 22, 165–185, https://doi.org/10.5194/nhess-22-165-2022, https://doi.org/10.5194/nhess-22-165-2022, 2022
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Various floods hit Germany recently. While there was a river flood with some dike breaches in 2013, flooding in 2016 resulted directly from heavy rainfall, causing overflowing drainage systems in urban areas and destructive flash floods in steep catchments. Based on survey data, we analysed how residents coped with these different floods. We observed significantly different flood impacts, warnings, behaviour and recovery, offering entry points for tailored risk communication and support.
Valeria Cigala, Giulia Roder, and Heidi Kreibich
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Lucas Wouters, Anaïs Couasnon, Marleen C. de Ruiter, Marc J. C. van den Homberg, Aklilu Teklesadik, and Hans de Moel
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Gustavo Andrei Speckhann, Heidi Kreibich, and Bruno Merz
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Marco Cerri, Max Steinhausen, Heidi Kreibich, and Kai Schröter
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Effective flood management requires information about the potential consequences of flooding. We show how openly accessible data from OpenStreetMap can support the estimation of flood damage for residential buildings. Working with methods of machine learning, the building geometry is used to predict flood damage in combination with information about inundation depth. Our approach makes it easier to transfer models to regions where no detailed data of flood impacts have been observed yet.
Daniela Molinari, Anna Rita Scorzini, Chiara Arrighi, Francesca Carisi, Fabio Castelli, Alessio Domeneghetti, Alice Gallazzi, Marta Galliani, Frédéric Grelot, Patric Kellermann, Heidi Kreibich, Guilherme S. Mohor, Markus Mosimann, Stephanie Natho, Claire Richert, Kai Schroeter, Annegret H. Thieken, Andreas Paul Zischg, and Francesco Ballio
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Flood risk management requires a realistic estimation of flood losses. However, the capacity of available flood damage models to depict real damages is questionable. With a joint effort of eight research groups, the objective of this study was to compare the performances of nine models for the estimation of flood damage to buildings. The comparison provided more objective insights on the transferability of the models and on the reliability of their estimations.
Jens A. de Bruijn, James E. Daniell, Antonios Pomonis, Rashmin Gunasekera, Joshua Macabuag, Marleen C. de Ruiter, Siem Jan Koopman, Nadia Bloemendaal, Hans de Moel, and Jeroen C. J. H. Aerts
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2020-282, https://doi.org/10.5194/nhess-2020-282, 2020
Revised manuscript not accepted
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Following hurricanes and other natural hazards, it is important to quickly estimate the damage caused by the hazard such that recovery aid can be granted from organizations such as the European Union and the World Bank. To do so, it is important to estimate the vulnerability of buildings to the hazards. In this research, we use post-disaster observations from social media to improve these vulnerability assessments and show its application in the Bahamas following Hurricane Dorian.
Patric Kellermann, Kai Schröter, Annegret H. Thieken, Sören-Nils Haubrock, and Heidi Kreibich
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The flood damage database HOWAS 21 contains object-specific flood damage data resulting from fluvial, pluvial and groundwater flooding. The datasets incorporate various variables of flood hazard, exposure, vulnerability and direct tangible damage at properties from several economic sectors. This paper presents HOWAS 21 and highlights exemplary analyses to demonstrate the use of HOWAS 21 flood damage data.
Timothy Tiggeloven, Hans de Moel, Hessel C. Winsemius, Dirk Eilander, Gilles Erkens, Eskedar Gebremedhin, Andres Diaz Loaiza, Samantha Kuzma, Tianyi Luo, Charles Iceland, Arno Bouwman, Jolien van Huijstee, Willem Ligtvoet, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 20, 1025–1044, https://doi.org/10.5194/nhess-20-1025-2020, https://doi.org/10.5194/nhess-20-1025-2020, 2020
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We present a framework to evaluate the benefits and costs of coastal adaptation through dikes to reduce future flood risk. If no adaptation takes place, we find that global coastal flood risk increases 150-fold by 2080, with sea-level rise contributing the most. Moreover, 15 countries account for 90 % of this increase; that adaptation shows high potential to cost-effectively reduce flood risk. The results will be integrated into the Aqueduct Global Flood Analyzer web tool.
Ayse Duha Metin, Nguyen Viet Dung, Kai Schröter, Sergiy Vorogushyn, Björn Guse, Heidi Kreibich, and Bruno Merz
Nat. Hazards Earth Syst. Sci., 20, 967–979, https://doi.org/10.5194/nhess-20-967-2020, https://doi.org/10.5194/nhess-20-967-2020, 2020
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For effective risk management, flood risk should be properly assessed. Traditionally, risk is assessed by making the assumption of invariant flow or loss probabilities (the chance that a given discharge or loss is exceeded) within the river catchment during a single flood event. However, in reality, flooding is more severe in some regions than others. This study indicates the importance of representing the spatial dependence of flood peaks and damage for risk assessments.
Dominik Paprotny, Heidi Kreibich, Oswaldo Morales-Nápoles, Paweł Terefenko, and Kai Schröter
Nat. Hazards Earth Syst. Sci., 20, 323–343, https://doi.org/10.5194/nhess-20-323-2020, https://doi.org/10.5194/nhess-20-323-2020, 2020
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Houses and their contents in Europe are worth trillions of euros, resulting in high losses from natural hazards. Hence, risk assessments need to reliably estimate the size and value of houses, including the value of durable goods kept inside. In this work we show how openly available or open datasets can be used to predict the size of individual residential buildings. Further, we provide standardized monetary values of houses and contents per square metre of floor space for 30 countries.
Johanna Englhardt, Hans de Moel, Charles K. Huyck, Marleen C. de Ruiter, Jeroen C. J. H. Aerts, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 19, 1703–1722, https://doi.org/10.5194/nhess-19-1703-2019, https://doi.org/10.5194/nhess-19-1703-2019, 2019
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Large-scale risk assessments can be improved by a more direct relation between the type of exposed buildings and their flood impact. Compared to the common land-use-based approach, this model reflects heterogeneous structures and defines building-material-based vulnerability classes. This approach is particularly interesting for areas with large variations of building types, such as developing countries and large scales, and enables vulnerability comparison across different natural disasters.
Heidi Kreibich, Thomas Thaler, Thomas Glade, and Daniela Molinari
Nat. Hazards Earth Syst. Sci., 19, 551–554, https://doi.org/10.5194/nhess-19-551-2019, https://doi.org/10.5194/nhess-19-551-2019, 2019
Ayse Duha Metin, Nguyen Viet Dung, Kai Schröter, Björn Guse, Heiko Apel, Heidi Kreibich, Sergiy Vorogushyn, and Bruno Merz
Nat. Hazards Earth Syst. Sci., 18, 3089–3108, https://doi.org/10.5194/nhess-18-3089-2018, https://doi.org/10.5194/nhess-18-3089-2018, 2018
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We present a comprehensive sensitivity analysis considering changes along the complete flood risk chain to understand how changes in different drivers affect flood risk. Results show that changes in dike systems or in vulnerability may outweigh changes in often investigated components, such as climate change. Although the specific results are conditional on the case study and assumptions, they highlight the need for a broader consideration of potential drivers of change in a comprehensive way.
Giuliano Di Baldassarre, Heidi Kreibich, Sergiy Vorogushyn, Jeroen Aerts, Karsten Arnbjerg-Nielsen, Marlies Barendrecht, Paul Bates, Marco Borga, Wouter Botzen, Philip Bubeck, Bruna De Marchi, Carmen Llasat, Maurizio Mazzoleni, Daniela Molinari, Elena Mondino, Johanna Mård, Olga Petrucci, Anna Scolobig, Alberto Viglione, and Philip J. Ward
Hydrol. Earth Syst. Sci., 22, 5629–5637, https://doi.org/10.5194/hess-22-5629-2018, https://doi.org/10.5194/hess-22-5629-2018, 2018
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One common approach to cope with floods is the implementation of structural flood protection measures, such as levees. Numerous scholars have problematized this approach and shown that increasing levels of flood protection can generate a false sense of security and attract more people to the risky areas. We briefly review the literature on this topic and then propose a research agenda to explore the unintended consequences of structural flood protection.
Francesca Carisi, Kai Schröter, Alessio Domeneghetti, Heidi Kreibich, and Attilio Castellarin
Nat. Hazards Earth Syst. Sci., 18, 2057–2079, https://doi.org/10.5194/nhess-18-2057-2018, https://doi.org/10.5194/nhess-18-2057-2018, 2018
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By analyzing a comprehensive loss dataset of affected private households after a recent river flood event in northern Italy, we tackle the problem of flood damage estimation in Emilia-Romagna (Italy). We develop empirical uni- and multivariable loss models for the residential sector. Outcomes highlight that the latter seem to outperform the former and, in addition, results show a higher accuracy of univariable models based on local data compared to literature ones derived for different contexts.
Iris Manola, Bart van den Hurk, Hans De Moel, and Jeroen C. J. H. Aerts
Hydrol. Earth Syst. Sci., 22, 3777–3788, https://doi.org/10.5194/hess-22-3777-2018, https://doi.org/10.5194/hess-22-3777-2018, 2018
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In a warmer climate, it is expected that precipitation intensities will increase and form a considerable risk of high-impact precipitation extremes. We investigate how observed extreme precipitation events would look like if they took place in a future warmer climate. This study applies three methods to transform a historic extreme precipitation event in the Netherlands to a similar event in a future warmer climate, thus compiling a
future weatherscenario.
Marlies Holkje Barendrecht, Alberto Viglione, Heidi Kreibich, Sergiy Vorogushyn, Bruno Merz, and Günter Blöschl
Proc. IAHS, 379, 193–198, https://doi.org/10.5194/piahs-379-193-2018, https://doi.org/10.5194/piahs-379-193-2018, 2018
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The aim of this paper is to assess whether a Socio-Hydrological model can be calibrated to data artificially generated from it. This is not trivial because the model is highly nonlinear and it is not clear what amount of data would be needed for calibration. We demonstrate that, using Bayesian inference, the parameters of the model can be estimated quite accurately from relatively few data, which could be available in real case studies.
Rui Figueiredo, Kai Schröter, Alexander Weiss-Motz, Mario L. V. Martina, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 18, 1297–1314, https://doi.org/10.5194/nhess-18-1297-2018, https://doi.org/10.5194/nhess-18-1297-2018, 2018
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Flood loss modelling is subject to large uncertainty that is often neglected. Most models are deterministic, and large disparities exist among them. Adopting a single model may lead to inaccurate loss estimates and sub-optimal decision-making. This paper proposes the use of multi-model ensembles to address such issues. We demonstrate that this can be a simple and pragmatic approach to obtain more accurate loss estimates and reliable probability distributions of model uncertainty.
Kai Schröter, Daniela Molinari, Michael Kunz, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 18, 963–968, https://doi.org/10.5194/nhess-18-963-2018, https://doi.org/10.5194/nhess-18-963-2018, 2018
Konstantinos Bischiniotis, Bart van den Hurk, Brenden Jongman, Erin Coughlan de Perez, Ted Veldkamp, Hans de Moel, and Jeroen Aerts
Nat. Hazards Earth Syst. Sci., 18, 271–285, https://doi.org/10.5194/nhess-18-271-2018, https://doi.org/10.5194/nhess-18-271-2018, 2018
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Preparedness activities and flood forecasting have received increasing attention and have led towards new science-based early warning systems. Understanding the flood triggering mechanisms will result in increasing warning lead times, providing sufficient time for early action. Findings of this study indicate that the consideration of short- and long-term antecedent conditions can be used by humanitarian organizations and decision makers for improved flood risk management.
Heidi Kreibich, Meike Müller, Kai Schröter, and Annegret H. Thieken
Nat. Hazards Earth Syst. Sci., 17, 2075–2092, https://doi.org/10.5194/nhess-17-2075-2017, https://doi.org/10.5194/nhess-17-2075-2017, 2017
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Early warning is essential for protecting people and mitigating damage in case of flood events. To gain more knowledge, surveys were taken after the 2002 and the 2013 floods in Germany. Results show that early warning and preparedness improved substantially. However, there is still room for further improvement, which needs to be triggered mainly by effective risk and emergency communication.
Matthieu Spekkers, Viktor Rözer, Annegret Thieken, Marie-Claire ten Veldhuis, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 17, 1337–1355, https://doi.org/10.5194/nhess-17-1337-2017, https://doi.org/10.5194/nhess-17-1337-2017, 2017
Jens de Bruijn, Hans de Moel, Brenden Jongman, Jurjen Wagemaker, and Jeroen C. J. H. Aerts
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2017-203, https://doi.org/10.5194/nhess-2017-203, 2017
Revised manuscript not accepted
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In this work we present TAGSS, an algorithm that extracts and geolocates tweets using locations mentioned in the text of a tweet. We have applied TAGGS to flood events. However, TAGGS has enormous potential for application in the broad field of geosciences and natural hazards of any kind in particular, where availability of timely and accurate information about the impacts of an ongoing event can assist relief organizations in enhancing their disaster response activities.
Annegret H. Thieken, Tina Bessel, Sarah Kienzler, Heidi Kreibich, Meike Müller, Sebastian Pisi, and Kai Schröter
Nat. Hazards Earth Syst. Sci., 16, 1519–1540, https://doi.org/10.5194/nhess-16-1519-2016, https://doi.org/10.5194/nhess-16-1519-2016, 2016
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In June 2013, widespread flooding and consequent damage and losses occurred in central Europe, especially in Germany. The 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 good data and information fulfil requirements that were recently proposed for disaster reporting on the European and international level, e.g. by the Sendai Framework for Disaster Risk Reduction 2015–2030.
Heidi Kreibich, Kai Schröter, and Bruno Merz
Proc. IAHS, 373, 179–182, https://doi.org/10.5194/piahs-373-179-2016, https://doi.org/10.5194/piahs-373-179-2016, 2016
Paolo Scussolini, Jeroen C. J. H. Aerts, Brenden Jongman, Laurens M. Bouwer, Hessel C. Winsemius, Hans de Moel, and Philip J. Ward
Nat. Hazards Earth Syst. Sci., 16, 1049–1061, https://doi.org/10.5194/nhess-16-1049-2016, https://doi.org/10.5194/nhess-16-1049-2016, 2016
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Assessments of flood risk, on global to local scales, are becoming more urgent with ongoing climate change and with rapid socioeconomic developments. Such assessments need information about existing flood protection, still largely unavailable. Here we present the first open-source database of FLood PROtection Standards, FLOPROS, which enables more accurate modelling of flood risk. We also invite specialists to contribute new information to this evolving database.
D. J. Wagenaar, K. M. de Bruijn, L. M. Bouwer, and H. de Moel
Nat. Hazards Earth Syst. Sci., 16, 1–14, https://doi.org/10.5194/nhess-16-1-2016, https://doi.org/10.5194/nhess-16-1-2016, 2016
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This paper discusses the differences that are found between flood damage estimation models. Based on an explanation of these differences, a method to quantify the uncertainty in flood damage models is proposed. An uncertainty estimate is made for a case study and the potential implications of uncertainty in flood damage estimation for investment decisions is shown.
J. Fohringer, D. Dransch, H. Kreibich, and K. Schröter
Nat. Hazards Earth Syst. Sci., 15, 2725–2738, https://doi.org/10.5194/nhess-15-2725-2015, https://doi.org/10.5194/nhess-15-2725-2015, 2015
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During and shortly after a disaster, data about the hazard and its consequences are scarce and not readily available. This research proposes a methodology that leverages social media content to support rapid inundation mapping, including inundation extent and water depth in the case of floods. The case study of the June 2013 flood in the city of Dresden shows that social media may help to bridge the information gap when traditional data sources are lacking or are sparse.
S. Kienzler, I. Pech, H. Kreibich, M. Müller, and A. H. Thieken
Nat. Hazards Earth Syst. Sci., 15, 505–526, https://doi.org/10.5194/nhess-15-505-2015, https://doi.org/10.5194/nhess-15-505-2015, 2015
P. Hudson, W. J. W. Botzen, H. Kreibich, P. Bubeck, and J. C. J. H. Aerts
Nat. Hazards Earth Syst. Sci., 14, 1731–1747, https://doi.org/10.5194/nhess-14-1731-2014, https://doi.org/10.5194/nhess-14-1731-2014, 2014
R. Lasage, T. I. E. Veldkamp, H. de Moel, T. C. Van, H. L. Phi, P. Vellinga, and J. C. J. H. Aerts
Nat. Hazards Earth Syst. Sci., 14, 1441–1457, https://doi.org/10.5194/nhess-14-1441-2014, https://doi.org/10.5194/nhess-14-1441-2014, 2014
I. Seifert, W. J. W. Botzen, H. Kreibich, and J. C. J. H. Aerts
Nat. Hazards Earth Syst. Sci., 13, 1691–1705, https://doi.org/10.5194/nhess-13-1691-2013, https://doi.org/10.5194/nhess-13-1691-2013, 2013
V. Meyer, N. Becker, V. Markantonis, R. Schwarze, J. C. J. M. van den Bergh, L. M. Bouwer, P. Bubeck, P. Ciavola, E. Genovese, C. Green, S. Hallegatte, H. Kreibich, Q. Lequeux, I. Logar, E. Papyrakis, C. Pfurtscheller, J. Poussin, V. Przyluski, A. H. Thieken, and C. Viavattene
Nat. Hazards Earth Syst. Sci., 13, 1351–1373, https://doi.org/10.5194/nhess-13-1351-2013, https://doi.org/10.5194/nhess-13-1351-2013, 2013
B. Merz, H. Kreibich, and U. Lall
Nat. Hazards Earth Syst. Sci., 13, 53–64, https://doi.org/10.5194/nhess-13-53-2013, https://doi.org/10.5194/nhess-13-53-2013, 2013
B. Jongman, H. Kreibich, H. Apel, J. I. Barredo, P. D. Bates, L. Feyen, A. Gericke, J. Neal, J. C. J. H. Aerts, and P. J. Ward
Nat. Hazards Earth Syst. Sci., 12, 3733–3752, https://doi.org/10.5194/nhess-12-3733-2012, https://doi.org/10.5194/nhess-12-3733-2012, 2012
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Fuchs, S., Keiler, M., and Zischg, A.: A spatiotemporal multi-hazard exposure assessment based on property data, Nat. Hazards Earth Syst. Sci., 15, 2127–2142, https://doi.org/10.5194/nhess-15-2127-2015, 2015.
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