Articles | Volume 26, issue 1
https://doi.org/10.5194/nhess-26-103-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-26-103-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
FLEMOflash – Flood Loss Estimation MOdels for companies and households affected by flash floods
Apoorva Singh
Section 4.4 Hydrology, GFZ Helmholtz Centre for Geosciences, 14473 Potsdam, Germany
Department of Civil Engineering, Indian Institute of Technology Delhi, 110016 New Delhi, India
Section 4.4 Hydrology, GFZ Helmholtz Centre for Geosciences, 14473 Potsdam, Germany
Department of Civil Engineering, Birla Institute of Technology and Science, Pilani, 333031 Rajasthan, India
Nivedita Sairam
Section 4.4 Hydrology, GFZ Helmholtz Centre for Geosciences, 14473 Potsdam, Germany
Kasra Rafiezadeh Shahi
Section 4.4 Hydrology, GFZ Helmholtz Centre for Geosciences, 14473 Potsdam, Germany
Anna Buch
Institute of Geography, University of Heidelberg, 69117 Heidelberg, Germany
Melanie Fischer
Section 4.4 Hydrology, GFZ Helmholtz Centre for Geosciences, 14473 Potsdam, Germany
Chandrika Thulaseedharan Dhanya
Department of Civil Engineering, Indian Institute of Technology Delhi, 110016 New Delhi, India
Heidi Kreibich
Section 4.4 Hydrology, GFZ Helmholtz Centre for Geosciences, 14473 Potsdam, Germany
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Ravikumar Guntu, Guilherme Samprogna Mohor, Annegret H. Thieken, Meike Müller, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 26, 163–186, https://doi.org/10.5194/nhess-26-163-2026, https://doi.org/10.5194/nhess-26-163-2026, 2026
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The 2021 flood in Germany caused severe damage to companies, with over half reporting losses above € 100 000. Using probabilistic models, we identify key factors driving direct damage and business interruption. Water depth, flow velocity and company exposure were key factors, but preparedness played a crucial role. Companies that took good precaution recovered faster. Our findings stress the value of early warnings and risk communication to reduce damage from unprecedented flood events.
Nivedita Sairam and Marleen C. de Ruiter
Nat. Hazards Earth Syst. Sci., 26, 119–130, https://doi.org/10.5194/nhess-26-119-2026, https://doi.org/10.5194/nhess-26-119-2026, 2026
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This paper highlights gaps in disaster risk assessments, particularly regarding disease outbreaks after natural hazards. It calls for: (1) learning from compound risk models to understand disaster and disease probabilities, (2) including health metrics in risk frameworks, and (3) improving data and modeling for health impacts. The authors propose a research agenda to enhance disaster risk management.
Aaron Buhrmann, Cecilia I. Nievas, Nivedita Sairam, James E. Daniell, Heidi Kreibich, and Seth Bryant
EGUsphere, https://doi.org/10.5194/egusphere-2025-5172, https://doi.org/10.5194/egusphere-2025-5172, 2025
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Our research lays the groundwork for the next generation of disaster risk modelling by improving how building-level value and use are estimated across Germany. By testing multiple data sources and methods, we identify a transparent, adaptable approach that enhances forecasts of damage and recovery—helping protect lives, property, and communities.
Alina Bill-Weilandt, Nivedita Sairam, Dennis Wagenaar, Kasra Rafiezadeh Shahi, Heidi Kreibich, Perrine Hamel, and David Lallemant
EGUsphere, https://doi.org/10.5194/egusphere-2025-3706, https://doi.org/10.5194/egusphere-2025-3706, 2025
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Flooding is a major cause of agricultural loss globally. We introduce a framework for developing and evaluating flood damage models for crops. The study presents the most comprehensive review of such models for rice to date and offers practical guidance on model selection and expected errors when transferring models across regions. We provide models and lookup tables that can be used in flood risk assessments in rice-producing regions.
Kasra Rafiezadeh Shahi, Nivedita Sairam, Lukas Schoppa, Le Thanh Sang, Do Ly Hoai Tan, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 25, 2845–2861, https://doi.org/10.5194/nhess-25-2845-2025, https://doi.org/10.5194/nhess-25-2845-2025, 2025
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Ho Chi Minh City (HCMC) faces severe flood risks from climatic and socio-economic changes, requiring effective adaptation solutions. Flood loss estimation is crucial, but advanced probabilistic models accounting for key drivers and uncertainty are lacking. This study presents a probabilistic flood loss model with a feature selection paradigm for HCMC’s residential sector. Experiments using new survey data from flood-affected households demonstrate the model's superior performance.
Timothy Tiggeloven, Colin Raymond, Marleen C. de Ruiter, Jana Sillmann, Annegret H. Thieken, Sophie L. Buijs, Roxana Ciurean, Emma Cordier, Julia M. Crummy, Lydia Cumiskey, Kelley De Polt, Melanie Duncan, Davide M. Ferrario, Wiebke S. Jäger, Elco E. Koks, Nicole van Maanen, Heather J. Murdock, Jaroslav Mysiak, Sadhana Nirandjan, Benjamin Poschlod, Peter Priesmeier, Nivedita Sairam, Pia-Johanna Schweizer, Tristian R. Stolte, Marie-Luise Zenker, James E. Daniell, Alexander Fekete, Christian M. Geiß, Marc J. C. van den Homberg, Sirkku K. Juhola, Christian Kuhlicke, Karen Lebek, Robert Šakić Trogrlić, Stefan Schneiderbauer, Silvia Torresan, Cees J. van Westen, Judith N. Claassen, Bijan Khazai, Virginia Murray, Julius Schlumberger, and Philip J. Ward
EGUsphere, https://doi.org/10.5194/egusphere-2025-2771, https://doi.org/10.5194/egusphere-2025-2771, 2025
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Natural hazards like floods, earthquakes, and landslides are often interconnected which may create bigger problems than when they occur alone. We studied expert discussions from an international conference to understand how scientists and policymakers can better prepare for these multi-hazards and use new technologies to protect its communities while contributing to dialogues about future international agreements beyond the Sendai Framework and supporting global sustainability goals.
Anna Buch, Dominik Paprotny, Kasra Rafiezadeh Shahi, Heidi Kreibich, and Nivedita Sairam
Nat. Hazards Earth Syst. Sci., 25, 2437–2453, https://doi.org/10.5194/nhess-25-2437-2025, https://doi.org/10.5194/nhess-25-2437-2025, 2025
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Many households in Vietnam depend on revenue from micro-businesses (shop houses). However, losses caused by regular flooding are not modelled. Business turnover, building age, and water depth were found to be the main drivers of flood losses of micro-businesses. We built and validated probabilistic models (non-parametric Bayesian networks) that estimate flood losses of micro-businesses. The results help with flood risk management and adaption decision making for micro-businesses.
Debankana Bhattacharjee and Chandrika Thulaseedharan Dhanya
EGUsphere, https://doi.org/10.5194/egusphere-2025-1886, https://doi.org/10.5194/egusphere-2025-1886, 2025
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India has been increasingly facing simultaneous drought and heatwave events over the past six decades. Using a new index to capture variability in precipitation spells, we tracked the spread and intensification of the compound events toward historically humid and less vulnerable regions. These events are becoming more frequent, severe, and harder to mitigate—even with short wet spells—highlighting the urgent need to rethink climate preparedness across both traditionally dry and wet regions.
André Felipe Rocha Silva, Julian Cardoso Eleutério, Heiko Apel, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 25, 1501–1520, https://doi.org/10.5194/nhess-25-1501-2025, https://doi.org/10.5194/nhess-25-1501-2025, 2025
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This work uses agent-based modelling to evaluate the impact of flood warning and evacuation systems on human losses during the 2021 Ahr Valley flood in Germany. While the first flood warning with evacuation instructions is identified as timely, its lack of detail and effectiveness resulted in low public risk awareness. Better dissemination of warnings and improved risk perception and preparedness among the population could reduce casualties by up to 80 %.
Maurice W. M. L. Kalthof, Jens de Bruijn, Hans de Moel, Heidi Kreibich, and Jeroen C. J. H. Aerts
Nat. Hazards Earth Syst. Sci., 25, 1013–1035, https://doi.org/10.5194/nhess-25-1013-2025, https://doi.org/10.5194/nhess-25-1013-2025, 2025
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Our study explores how farmers in India's Bhima basin respond to consecutive droughts. We simulated farmers' individual choices – like changing crops or digging wells – and their effects on profits, yields, and water resources. Results show these adaptations, while improving incomes, ultimately increase drought vulnerability and damage. Such insights emphasize the need for alternative adaptations and highlight the value of socio-hydrological models in shaping policies to lessen drought impacts.
Nadja Veigel, Heidi Kreibich, Jens A. de Bruijn, Jeroen C. J. H. Aerts, and Andrea Cominola
Nat. Hazards Earth Syst. Sci., 25, 879–891, https://doi.org/10.5194/nhess-25-879-2025, https://doi.org/10.5194/nhess-25-879-2025, 2025
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This study explores how social media, specifically Twitter (X), can help us understand public reactions to floods in Germany from 2014 to 2021. Using large language models, we extract topics and patterns of behavior from flood-related tweets. The findings offer insights to improve communication and disaster management. Topics related to low-impact flooding contain descriptive hazard-related content, while the focus shifts to catastrophic impacts and responsibilities during high-impact events.
Belinda Rhein and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 25, 581–589, https://doi.org/10.5194/nhess-25-581-2025, https://doi.org/10.5194/nhess-25-581-2025, 2025
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In July 2021, flooding killed 190 people in Germany, 134 of them in the Ahr valley, making it the deadliest flood in recent German history. The flash flood was extreme in terms of water levels, flow velocities and flood extent, and early warning and evacuation were inadequate. Many died on the ground floor or in the street, with older and impaired individuals especially vulnerable. Clear warnings should urge people to seek safety rather than save belongings, and timely evacuations are essential.
Bruno Merz, Günter Blöschl, Robert Jüpner, Heidi Kreibich, Kai Schröter, and Sergiy Vorogushyn
Nat. Hazards Earth Syst. Sci., 24, 4015–4030, https://doi.org/10.5194/nhess-24-4015-2024, https://doi.org/10.5194/nhess-24-4015-2024, 2024
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Flood risk assessments help us decide how to reduce the risk of flooding. Since these assessments are based on probabilities, it is hard to check their accuracy by comparing them to past data. We suggest a new way to validate these assessments, making sure they are practical for real-life decisions. This approach looks at both the technical details and the real-world situations where decisions are made. We demonstrate its practicality by applying it to flood emergency planning.
Jürgen Mey, Ravi Kumar Guntu, Alexander Plakias, Igo Silva de Almeida, and Wolfgang Schwanghart
Nat. Hazards Earth Syst. Sci., 24, 3207–3223, https://doi.org/10.5194/nhess-24-3207-2024, https://doi.org/10.5194/nhess-24-3207-2024, 2024
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The Himalayan road network links remote areas, but fragile terrain and poor construction lead to frequent landslides. This study on the NH-7 in India's Uttarakhand region analyzed 300 landslides after heavy rainfall in 2022 . Factors like slope, rainfall, rock type and road work influence landslides. The study's model predicts landslide locations for better road maintenance planning, highlighting the risk from climate change and increased road use.
Dominik Paprotny, Belinda Rhein, Michalis I. Vousdoukas, Paweł Terefenko, Francesco Dottori, Simon Treu, Jakub Śledziowski, Luc Feyen, and Heidi Kreibich
Hydrol. Earth Syst. Sci., 28, 3983–4010, https://doi.org/10.5194/hess-28-3983-2024, https://doi.org/10.5194/hess-28-3983-2024, 2024
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Long-term trends in flood losses are regulated by multiple factors, including climate variation, population and economic growth, land-use transitions, reservoir construction, and flood risk reduction measures. Here, we reconstruct the factual circumstances in which almost 15 000 potential riverine, coastal and compound floods in Europe occurred between 1950 and 2020. About 10 % of those events are reported to have caused significant socioeconomic impacts.
Viet Dung Nguyen, Jeroen Aerts, Max Tesselaar, Wouter Botzen, Heidi Kreibich, Lorenzo Alfieri, and Bruno Merz
Nat. Hazards Earth Syst. Sci., 24, 2923–2937, https://doi.org/10.5194/nhess-24-2923-2024, https://doi.org/10.5194/nhess-24-2923-2024, 2024
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Our study explored how seasonal flood forecasts could enhance insurance premium accuracy. Insurers traditionally rely on historical data, yet climate fluctuations influence flood risk. We employed a method that predicts seasonal floods to adjust premiums accordingly. Our findings showed significant year-to-year variations in flood risk and premiums, underscoring the importance of adaptability. Despite limitations, this research aids insurers in preparing for evolving risks.
Seth Bryant, Heidi Kreibich, and Bruno Merz
Proc. IAHS, 386, 181–187, https://doi.org/10.5194/piahs-386-181-2024, https://doi.org/10.5194/piahs-386-181-2024, 2024
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Our study found that simplifying data in flood risk models can introduce errors. We tested 344 damage functions and found errors up to 40 % of the total asset value. This means large-scale flood risk assessments may have significant errors due to the modelling approach. Our research highlights the need for more attention to data aggregation in flood risk models.
Seth Bryant, Guy Schumann, Heiko Apel, Heidi Kreibich, and Bruno Merz
Hydrol. Earth Syst. Sci., 28, 575–588, https://doi.org/10.5194/hess-28-575-2024, https://doi.org/10.5194/hess-28-575-2024, 2024
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A new algorithm has been developed to quickly produce high-resolution flood maps. It is faster and more accurate than current methods and is available as open-source scripts. This can help communities better prepare for and mitigate flood damages without expensive modelling.
C. Ludwig, J. Psotta, A. Buch, N. Kolaxidis, S. Fendrich, M. Zia, J. Fürle, A. Rousell, and A. Zipf
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-4-W7-2023, 109–116, https://doi.org/10.5194/isprs-archives-XLVIII-4-W7-2023-109-2023, https://doi.org/10.5194/isprs-archives-XLVIII-4-W7-2023-109-2023, 2023
Heidi Kreibich, Kai Schröter, Giuliano Di Baldassarre, Anne F. Van Loon, Maurizio Mazzoleni, Guta Wakbulcho Abeshu, Svetlana Agafonova, Amir AghaKouchak, Hafzullah Aksoy, Camila Alvarez-Garreton, Blanca Aznar, Laila Balkhi, Marlies H. Barendrecht, Sylvain Biancamaria, Liduin Bos-Burgering, Chris Bradley, Yus Budiyono, Wouter Buytaert, Lucinda Capewell, Hayley Carlson, Yonca Cavus, Anaïs Couasnon, Gemma Coxon, Ioannis Daliakopoulos, Marleen C. de Ruiter, Claire Delus, Mathilde Erfurt, Giuseppe Esposito, Didier François, Frédéric Frappart, Jim Freer, Natalia Frolova, Animesh K. Gain, Manolis Grillakis, Jordi Oriol Grima, Diego A. Guzmán, Laurie S. Huning, Monica Ionita, Maxim Kharlamov, Dao Nguyen Khoi, Natalie Kieboom, Maria Kireeva, Aristeidis Koutroulis, Waldo Lavado-Casimiro, Hong-Yi Li, Maria Carmen LLasat, David Macdonald, Johanna Mård, Hannah Mathew-Richards, Andrew McKenzie, Alfonso Mejia, Eduardo Mario Mendiondo, Marjolein Mens, Shifteh Mobini, Guilherme Samprogna Mohor, Viorica Nagavciuc, Thanh Ngo-Duc, Huynh Thi Thao Nguyen, Pham Thi Thao Nhi, Olga Petrucci, Nguyen Hong Quan, Pere Quintana-Seguí, Saman Razavi, Elena Ridolfi, Jannik Riegel, Md Shibly Sadik, Nivedita Sairam, Elisa Savelli, Alexey Sazonov, Sanjib Sharma, Johanna Sörensen, Felipe Augusto Arguello Souza, Kerstin Stahl, Max Steinhausen, Michael Stoelzle, Wiwiana Szalińska, Qiuhong Tang, Fuqiang Tian, Tamara Tokarczyk, Carolina Tovar, Thi Van Thu Tran, Marjolein H. J. van Huijgevoort, Michelle T. H. van Vliet, Sergiy Vorogushyn, Thorsten Wagener, Yueling Wang, Doris E. Wendt, Elliot Wickham, Long Yang, Mauricio Zambrano-Bigiarini, and Philip J. Ward
Earth Syst. Sci. Data, 15, 2009–2023, https://doi.org/10.5194/essd-15-2009-2023, https://doi.org/10.5194/essd-15-2009-2023, 2023
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As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management. We present a dataset containing data of paired events, i.e. two floods or two droughts that occurred in the same area. The dataset enables comparative analyses and allows detailed context-specific assessments. Additionally, it supports the testing of socio-hydrological models.
Thulasi Vishwanath Harish, Nivedita Sairam, Liang Emlyn Yang, Matthias Garschagen, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 23, 1125–1138, https://doi.org/10.5194/nhess-23-1125-2023, https://doi.org/10.5194/nhess-23-1125-2023, 2023
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Coastal Asian cities are becoming more vulnerable to flooding. In this study we analyse the data collected from flood-prone houses in Ho Chi Minh City to identify what motivates the households to adopt flood precautionary measures. The results revealed that educating the households about the available flood precautionary measures and communicating the flood protection measures taken by the government encourage the households to adopt measures without having to experience multiple flood events.
Jürgen Mey, Ravi Kumar Guntu, Alexander Plakias, Igo Silva de Almeida, and Wolfgang Schwanghart
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2022-295, https://doi.org/10.5194/nhess-2022-295, 2023
Manuscript not accepted for further review
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The current socioeconomic development in the Himalayan region leads to a rapid expansion of the road network and an increase in the exposure to landslides. Our study along the NH-7 demonstrates the scale of this challenge as we detect more than one partially or fully road-blocking landslide per road kilometer. We identify the main controlling variables, i.e. slope angle, rainfall amount and lithology. As our approach uses a minimum of data, it can be extended to more complicated road networks.
Alberto Caldas-Alvarez, Markus Augenstein, Georgy Ayzel, Klemens Barfus, Ribu Cherian, Lisa Dillenardt, Felix Fauer, Hendrik Feldmann, Maik Heistermann, Alexia Karwat, Frank Kaspar, Heidi Kreibich, Etor Emanuel Lucio-Eceiza, Edmund P. Meredith, Susanna Mohr, Deborah Niermann, Stephan Pfahl, Florian Ruff, Henning W. Rust, Lukas Schoppa, Thomas Schwitalla, Stella Steidl, Annegret H. Thieken, Jordis S. Tradowsky, Volker Wulfmeyer, and Johannes Quaas
Nat. Hazards Earth Syst. Sci., 22, 3701–3724, https://doi.org/10.5194/nhess-22-3701-2022, https://doi.org/10.5194/nhess-22-3701-2022, 2022
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In a warming climate, extreme precipitation events are becoming more frequent. To advance our knowledge on such phenomena, we present a multidisciplinary analysis of a selected case study that took place on 29 June 2017 in the Berlin metropolitan area. Our analysis provides evidence of the extremeness of the case from the atmospheric and the impacts perspectives as well as new insights on the physical mechanisms of the event at the meteorological and climate scales.
Brunella Bonaccorso, Carmelo Cammalleri, Athanasios Loukas, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 22, 1857–1862, https://doi.org/10.5194/nhess-22-1857-2022, https://doi.org/10.5194/nhess-22-1857-2022, 2022
Animesh K. Gain, Yves Bühler, Pascal Haegeli, Daniela Molinari, Mario Parise, David J. Peres, Joaquim G. Pinto, Kai Schröter, Ricardo M. Trigo, María Carmen Llasat, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 22, 985–993, https://doi.org/10.5194/nhess-22-985-2022, https://doi.org/10.5194/nhess-22-985-2022, 2022
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To mark the 20th anniversary of Natural Hazards and Earth System Sciences (NHESS), an interdisciplinary and international journal dedicated to the public discussion and open-access publication of high-quality studies and original research on natural hazards and their consequences, we highlight 11 key publications covering major subject areas of NHESS that stood out within the past 20 years.
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
Nat. Hazards Earth Syst. Sci., 22, 85–96, https://doi.org/10.5194/nhess-22-85-2022, https://doi.org/10.5194/nhess-22-85-2022, 2022
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Non-male scientists constitute a minority in the geoscience professional environment, and they are underrepresented in disaster risk reduction planning. So far the international agenda has failed to effectively promote gender inclusion in disaster policy, preventing non-male scientists from career development and recognition. Here we share the thoughts, experiences, and priorities of women and non-binary scientists as a starting point to expand the discourse and promote intersectional research.
Gustavo Andrei Speckhann, Heidi Kreibich, and Bruno Merz
Earth Syst. Sci. Data, 13, 731–740, https://doi.org/10.5194/essd-13-731-2021, https://doi.org/10.5194/essd-13-731-2021, 2021
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Dams are an important element of water resources management. Data about dams are crucial for practitioners, scientists, and policymakers. We present the most comprehensive open-access dam inventory for Germany to date. The inventory combines multiple sources of information. It comprises 530 dams 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.
Marco Cerri, Max Steinhausen, Heidi Kreibich, and Kai Schröter
Nat. Hazards Earth Syst. Sci., 21, 643–662, https://doi.org/10.5194/nhess-21-643-2021, https://doi.org/10.5194/nhess-21-643-2021, 2021
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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.
Cited articles
Amadio, M., Scorzini, A. R., Carisi, F., Essenfelder, A. H., Domeneghetti, A., Mysiak, J., and Castellarin, A.: Testing empirical and synthetic flood damage models: the case of Italy, Nat. Hazards Earth Syst. Sci., 19, 661–678, https://doi.org/10.5194/nhess-19-661-2019, 2019.
Barendrecht, M. H., Sairam, N., Cumiskey, L., Metin, A. D., Holz, F., Priest, S. J., and Kreibich, H.: Needed: A systems approach to improve flood risk mitigation through private precautionary measures, Water Secur., 11, 100080, https://doi.org/10.1016/j.wasec.2020.100080, 2020.
Berghäuser, L., Bubeck, P., Hudson, P., and Thieken, A. H.: Identifying and characterising individual flood precautionary behaviour dynamics from panel data, Int. J. Disast. Risk Reduct., 94, 103835, https://doi.org/10.1016/j.ijdrr.2023.103835, 2023.
Breiman, L.: Random Forests, Mach. Learn., 45, 5–32, https://doi.org/10.1023/A:1010933404324, 2001.
Bronstert, A., Agarwal, A., Boessenkool, B., Crisologo, I., Fischer, M., Heistermann, M., Köhn-Reich, L., López-Tarazón, J. A., Moran, T., Ozturk, U., Reinhardt-Imjela, C., and Wendi, D.: Forensic hydro-meteorological analysis of an extreme flash flood: The 2016-05-29 event in Braunsbach, SW Germany, Sci. Total Environ., 630, 977–991, https://doi.org/10.1016/j.scitotenv.2018.02.241, 2018.
Bubeck, P., Botzen, W. J. W., Kreibich, H., and Aerts, J. C. J. H.: Detailed insights into the influence of flood-coping appraisals on mitigation behaviour, Global Environ. Change, 23, 1327–1338, https://doi.org/10.1016/j.gloenvcha.2013.05.009, 2013.
Chen, T. and Guestrin, C.: XGBoost: A Scalable Tree Boosting System, in: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD'16: The 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, California, USA, 785–794, https://doi.org/10.1145/2939672.2939785, 2016.
Chughtai, A.: Mapping the scale of damage by the catastrophic Pakistan floods infographic news Al Jazeera, https://www.aljazeera.com/news/longform/2022/9/16/mapping-the-scale-of-destruction-of-the-pakistan-floods (last access: 28 March 2025), 2022.
Dottori, F., Figueiredo, R., Martina, M. L. V., Molinari, D., and Scorzini, A. R.: INSYDE: a synthetic, probabilistic flood damage model based on explicit cost analysis, Nat. Hazards Earth Syst. Sci., 16, 2577–2591, https://doi.org/10.5194/nhess-16-2577-2016, 2016.
Dougherty, E. and Rasmussen, K. L.: Changes in Future Flash Flood–Producing Storms in the United States, J. Hydrometeorol., 21, 2221–2236, https://doi.org/10.1175/JHM-D-20-0014.1, 2020.
Gerl, T., Kreibich, H., Franco, G., Marechal, D., and Schröter, K.: A Review of Flood Loss Models as Basis for Harmonization and Benchmarking, PLoS ONE, 11, e0159791, https://doi.org/10.1371/journal.pone.0159791, 2016.
GFZ Helmholtz Centre for Geosciences: HOWAS21, GFZ Helmholtz Centre for Geosciences [data set], https://doi.org/10.1594/GFZ.SDDB.HOWAS21, 2025.
Ghaedi, H., Reilly, A. C., Baroud, H., Perrucci, D. V., and Ferreira, C. M.: Predicting flood damage using the flood peak ratio and Giovanni Flooded Fraction, PLoS ONE, 17, e0271230, https://doi.org/10.1371/journal.pone.0271230, 2022.
Gneiting, T. and Katzfuss, M.: Probabilistic Forecasting, Annu. Rev. Stat. Appl., 1, 125–151, https://doi.org/10.1146/annurev-statistics-062713-085831, 2014.
Hasanzadeh Nafari, R., Ngo, T., and Mendis, P.: An Assessment of the Effectiveness of Tree-Based Models for Multi-Variate Flood Damage Assessment in Australia, Water, 8, 282, https://doi.org/10.3390/w8070282, 2016.
Hübl, J., Heiser, M., Braito, S., Tscharner, S., Kuntner, K., Schraml, K., Falkensteiner, M., and Rabanser, E.: Ereignisdokumentation und Ereignisanalyse Rottal-Inn 2016: Band 1: Ergebnisdokumentation, Universitaet fuer Bodenkultur, Vienna, Austria, https://boku.ac.at/fileadmin/data/H03000/H87000/H87100/DAN_IAN_Reports/Rep180_Band_1_mit_Anhang.pdf (last access: 28 March 2025), 2017.
Jensen, F. V. and Nielsen, T. D.: Bayesian Networks and Decision Graphs, Springer, New York, NY, https://doi.org/10.1007/978-0-387-68282-2, 2007.
Kellermann, P., Schröter, K., Thieken, A. H., Haubrock, S.-N., and Kreibich, H.: The object-specific flood damage database HOWAS 21, Nat. Hazards Earth Syst. Sci., 20, 2503–2519, https://doi.org/10.5194/nhess-20-2503-2020, 2020.
Kitson, N. K., Constantinou, A. C., Guo, Z., Liu, Y., and Chobtham, K.: A survey of Bayesian Network structure learning, Artif. Intell. Rev., 56, 8721–8814, https://doi.org/10.1007/s10462-022-10351-w, 2023.
Kreibich, H. and Dimitrova, B.: Assessment of damages caused by different flood types, FRIAR 2010, Milan, Italy, 3–11, https://doi.org/10.2495/FRIAR100011, 2010.
Kreibich, H., Thieken, A. H., Petrow, T., Müller, M., and Merz, B.: Flood loss reduction of private households due to building precautionary measures – lessons learned from the Elbe flood in August 2002, Nat. Hazards Earth Syst. Sci., 5, 117–126, https://doi.org/10.5194/nhess-5-117-2005, 2005.
Kreibich, H., Müller, M., Thieken, A. H., and Merz, B.: Flood precaution of companies and their ability to cope with the flood in August 2002 in Saxony, Germany, Water Resour. Res., 43, 2005WR004691, https://doi.org/10.1029/2005WR004691, 2007.
Kreibich, H., Seifert, I., Merz, B., and Thieken, A. H.: Development of FLEMOcs – a new model for the estimation of flood losses in the commercial sector, Hydrolog. Sci. J., 55, 1302–1314, https://doi.org/10.1080/02626667.2010.529815, 2010.
Kreibich, H., Thieken, A., Haubrock, S., and Schröter, K.: HOWAS21, the German Flood Damage Database, in: Geophysical Monograph Series, edited by: Molinari, D., Menoni, S., and Ballio, F., Wiley, 65–75, https://doi.org/10.1002/9781119217930.ch5, 2017.
Kreibich, H., Hudson, P., and Merz, B.: Knowing What to Do Substantially Improves the Effectiveness of Flood Early Warning, B. Am. Meteorol. Soc., 102, E1450–E1463, https://doi.org/10.1175/BAMS-D-20-0262.1, 2021.
Krüger, F., Lerch, S., Thorarinsdottir, T., and Gneiting, T.: Predictive Inference Based on Markov Chain Monte Carlo Output, Int. Stat. Rev., 89, 274–301, https://doi.org/10.1111/insr.12405, 2021.
Laudan, J., Zöller, G., and Thieken, A. H.: Flash floods versus river floods – a comparison of psychological impacts and implications for precautionary behaviour, Nat. Hazards Earth Syst. Sci., 20, 999–1023, https://doi.org/10.5194/nhess-20-999-2020, 2020.
LfU – Bayerisches Landesamt für Umwelt (Ed.): Sturzfluten- und Hochwasserereignisse Mai/Juni 2016 – Wasserwirtschaftlicher Bericht, https://files.hnd.bayern.de/berichte/lfu_SturzflutenMaiJuni2016.pdf (last access: 28 March 2025), 2017.
Lüdtke, S., Schröter, K., Steinhausen, M., Weise, L., Figueiredo, R., and Kreibich, H.: A Consistent Approach for Probabilistic Residential Flood Loss Modeling in Europe, Water Resour. Res., 55, 10616–10635, https://doi.org/10.1029/2019WR026213, 2019.
Merz, B., Kreibich, H., and Lall, U.: Multi-variate flood damage assessment: a tree-based data-mining approach, Nat. Hazards Earth Syst. Sci., 13, 53–64, https://doi.org/10.5194/nhess-13-53-2013, 2013.
Middelmann-Fernandes, M. H.: Flood damage estimation beyond stage–damage functions: an Australian example, J. Flood Risk Manage., 3, 88–96, https://doi.org/10.1111/j.1753-318X.2009.01058.x, 2010.
Mohor, G. S., Hudson, P., and Thieken, A. H.: A Comparison of Factors Driving Flood Losses in Households Affected by Different Flood Types, Water Resour. Res., 56, e2019WR025943, https://doi.org/10.1029/2019WR025943, 2020.
Mohor, G. S., Thieken, A. H., and Korup, O.: Residential flood loss estimated from Bayesian multilevel models, Nat. Hazards Earth Syst. Sci., 21, 1599–1614, https://doi.org/10.5194/nhess-21-1599-2021, 2021.
Mühr, B., Daniell, J., Ehmele, F., Kron, A., Dittrich, A., and Kunz, M.: Hochwasser/Überschwemmungen Süddeutschland Mai/Juni 2016, CEDIM FDA – Forensic Disaster Analysis Group, https://www.cedim.kit.edu/download/Hochwasser_S%C3%BCddeutschland_Report_1.pdf (last access: 28 March 2025), 2016.
Munich Re: Flood risks on the rise – Greater loss prevention is needed, https://www.munichre.com/en/risks/natural-disasters/floods.html (last access: 28 March 2025), 2025.
Nofal, O. M., Van De Lindt, J. W., and Do, T. Q.: Multi-variate and single-variable flood fragility and loss approaches for buildings, Reliabil. Eng. Syst. Safe., 202, 106971, https://doi.org/10.1016/j.ress.2020.106971, 2020.
Pearl, J.: Probabilistic Reasoning in Intelligent Systems, Elsevier, https://doi.org/10.1016/C2009-0-27609-4, 1988.
Plapp, S. T.: Risk perception of natural catastrophes – an empirical investigation in six endangers areas in south and west Germany, in: Vol. 2, Karlsruher Reihe II – Risikoforschung und Versicherungsmanagement, https://books.google.co.in/books?hl=en&lr=&id=6gJvbjhXV_cC&oi=fnd&pg=PA1&dq=Wahrnehmung+von+Risiken+aus+Naturkatastrophen+Eine+...&ots=AuLYOXuVUv&sig=GYvzBl_dpwRaXt653R4E-V9gLec&redir_esc=y#v=onepage&q=Wahrnehmung von Risiken aus Naturkatastrophen Eine ...&f=false (last access: 9 January 2026), 2003.
Rözer, V., Peche, A., Berkhahn, S., Feng, Y., Fuchs, L., Graf, Haberlandt, U., Kreibich, H., Sämann, R., Sester, M., Shehu, B., Wahl, J., and Neuweiler, I.: Impact-Based Forecasting for Pluvial Floods, Earth's Future, 9, 2020EF001851, https://doi.org/10.1029/2020EF001851, 2021.
Sairam, N., Schröter, K., Lüdtke, S., Merz, B., and Kreibich, H.: Quantifying Flood Vulnerability Reduction via Private Precaution, Earth's Future, 7, 235–249, https://doi.org/10.1029/2018EF000994, 2019.
Sairam, N., Schröter, K., Carisi, F., Wagenaar, D., Domeneghetti, A., Molinari, D., Brill, F., Priest, S., Viavattene, C., Merz, B., and Kreibich, H.: Bayesian Data-Driven approach enhances synthetic flood loss models, Environ. Model. Softw., 132, 104798, https://doi.org/10.1016/j.envsoft.2020.104798, 2020.
Sairam, N., Brill, F., Sieg, T., Farrag, M., Kellermann, P., Nguyen, V. D., Lüdtke, S., Merz, B., Schröter, K., Vorogushyn, S., and Kreibich, H.: Process-Based Flood Risk Assessment for Germany, Earth's Future, 9, e2021EF002259, https://doi.org/10.1029/2021EF002259, 2021.
Salas, J., Saha, A., and Ravela, S.: Learning inter-annual flood loss risk models from historical flood insurance claims, J. Environ. Manage., 347, 118862, https://doi.org/10.1016/j.jenvman.2023.118862, 2023.
Schoppa, L., Sieg, T., Vogel, K., Zöller, G., and Kreibich, H.: Probabilistic Flood Loss Models for Companies, Water Resour. Res., 56, e2020WR027649, https://doi.org/10.1029/2020WR027649, 2020.
Schröter, K., Kreibich, H., Vogel, K., Riggelsen, C., Scherbaum, F., and Merz, B.: How useful are complex flood damage models?, Water Resour. Res., 50, 3378–3395, https://doi.org/10.1002/2013WR014396, 2014.
Scutari, M. and Denis, J.-B.: Bayesian Networks: With Examples in R, in: 2nd Edn., Chapman and Hall/CRC, Boca Raton, https://doi.org/10.1201/9780429347436, 2021.
Sieg, T., Vogel, K., Merz, B., and Kreibich, H.: Tree-based flood damage modeling of companies: Damage processes and model performance, Water Resour. Res., 53, 6050–6068, https://doi.org/10.1002/2017WR020784, 2017.
Surminski, S. and Thieken, A. H.: Promoting flood risk reduction: The role of insurance in Germany and England, Earth's Future, 5, 979–1001, https://doi.org/10.1002/2017EF000587, 2017.
Thieken, A. H., Olschewski, A., Kreibich, H., Kobsch, S., and Merz, B.: Development and evaluation of FLEMOps – a new Flood Loss Estimation MOdel for the private sector, in: WIT Transactions on Ecology and the Environment, Flood recovery, innovation and response 2008, WIT Press, London, England, 315–324, https://doi.org/10.2495/friar080301, 2008.
Thieken, A. H., Samprogna Mohor, G., Kreibich, H., and Müller, M.: Compound inland flood events: different pathways, different impacts and different coping options, Nat. Hazards Earth Syst. Sci., 22, 165–185, https://doi.org/10.5194/nhess-22-165-2022, 2022.
Vogel, K., Weise, L., Schröter, K., and Thieken, A. H.: Identifying Driving Factors in Flood-Damaging Processes Using Graphical Models, Water Resour. Res., 54, 8864–8889, https://doi.org/10.1029/2018WR022858, 2018.
Wagenaar, D., Lüdtke, S., Schröter, K., Bouwer, L. M., and Kreibich, H.: Regional and Temporal Transferability of Multivariable Flood Damage Models, Water Resour. Res., 54, 3688–3703, https://doi.org/10.1029/2017WR022233, 2018.
Wang, K., Wang, L., Wei, Y.-M., and Ye, M.: Beijing storm of July 21, 2012: observations and reflections, Nat. Hazards, 67, 969–974, https://doi.org/10.1007/s11069-013-0601-6, 2013.
Zain, A., Legono, D., Rahardjo, A. P., and Jayadi, R.: Review on Co-factors Triggering Flash Flood Occurrences in Indonesian Small Catchments, IOP Conf. Ser.: Earth Environ. Sci., 930, 012087, https://doi.org/10.1088/1755-1315/930/1/012087, 2021.
Zander, K. K., Nguyen, D., Mirbabaie, M., and Garnett, S. T.: Aware but not prepared: understanding situational awareness during the century flood in Germany in 2021, Int. J. Disast. Risk Reduct., 96, 103936, https://doi.org/10.1016/j.ijdrr.2023.103936, 2023.
Zou, H. and Hastie, T.: Regularization and Variable Selection Via the Elastic Net, J. Roy. Stat. Soc. Ser. B, 67, 301–320, https://doi.org/10.1111/j.1467-9868.2005.00503.x, 2005.
Short summary
We develop novel probabilistic models to estimate flash flood losses of companies and households in Germany. Using multiple flash flood events, we identify key drivers of flash floods loss. FLEMO flash model reveals that for companies, the effectiveness of emergency measures is crucial in mitigating losses. In contrast, household benefit more from knowledge about emergency action, suggesting adaptation strategies can effectively reduce flash flood losses.
We develop novel probabilistic models to estimate flash flood losses of companies and households...
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