Articles | Volume 26, issue 1
https://doi.org/10.5194/nhess-26-163-2026
© 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-26-163-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Jan 2026
Research article |
| 16 Jan 2026
| 16 Jan 2026
Deciphering the drivers of direct and indirect damages to companies from an unprecedented flood event: A data-driven, multivariate probabilistic approach
GFZ Helmholtz Centre for Geosciences, Section Hydrology, 14473 Potsdam, Germany
Department of Civil Engineering, Birla Institute of Technology and Science, Pilani, Rajasthan 333031, India
Guilherme Samprogna Mohor
Institute of Environmental Science and Geography, University of Potsdam, 14476 Potsdam, Germany
Annegret H. Thieken
Institute of Environmental Science and Geography, University of Potsdam, 14476 Potsdam, Germany
Meike Müller
Deutsche Rückversicherung AG, 40549 Düsseldorf, Germany
Heidi Kreibich
GFZ Helmholtz Centre for Geosciences, Section Hydrology, 14473 Potsdam, Germany
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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.
Guilherme S. Mohor, Annegret H. Thieken, and Oliver Korup
Nat. Hazards Earth Syst. Sci., 21, 1599–1614, https://doi.org/10.5194/nhess-21-1599-2021, https://doi.org/10.5194/nhess-21-1599-2021, 2021
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We explored differences in the damaging process across different flood types, regions within Germany, and six flood events through a numerical model in which the groups can learn from each other. Differences were found mostly across flood types, indicating the importance of identifying them, but there is great overlap across regions and flood events, indicating either that socioeconomic or temporal information was not well represented or that they are in fact less different within our cases.
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
Aria, M., Cuccurullo, C., and Gnasso, A.: A comparison among interpretative proposals for Random Forests, Machine Learning with Applications, 6, 100094, https://doi.org/10.1016/j.mlwa.2021.100094, 2021.
Askr, H., Abdel-Salam, M., and Hassanien, A. E.: Copula entropy-based golden jackal optimization algorithm for high-dimensional feature selection problems, Expert Systems with Applications, 238, 121582, https://doi.org/10.1016/j.eswa.2023.121582, 2024.
Blöschl, G., Hall, J., Parajka, J., Perdigão, R. A. P., Merz, B., Arheimer, B., Aronica, G. T., Bilibashi, A., Bonacci, O., Borga, M., Čanjevac, I., Castellarin, A., Chirico, G. B., Claps, P., Fiala, K., Frolova, N., Gorbachova, L., Gül, A., Hannaford, J., Harrigan, S., Kireeva, M., Kiss, A., Kjeldsen, T. R., Kohnová, S., Koskela, J. J., Ledvinka, O., Macdonald, N., Mavrova-Guirguinova, M., Mediero, L., Merz, R., Molnar, P., Montanari, A., Murphy, C., Osuch, M., Ovcharuk, V., Radevski, I., Rogger, M., Salinas, J. L., Sauquet, E., Šraj, M., Szolgay, J., Viglione, A., Volpi, E., Wilson, D., Zaimi, K., and Živković, N.: Changing climate shifts timing of European floods, Science, 357, 588–590, https://doi.org/10.1126/science.aan2506, 2017.
BMI and BMF: Report on the 2021 flood disaster: disaster relief, reconstruction and evaluation processes, https://www.bmi.bund.de/SharedDocs/downloads/DE/veroeffentlichungen/2022/finalreport-hochwasserkatastrophe.html (last access: 16 September 2024), 2022.
Breiman, L.: Random Forests, Machine Learning, 45, 5–32, https://doi.org/10.1023/A:1010933404324, 2001.
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.
Destatis: Small and medium-sized enterprises (SME), https://www.destatis.de/EN/Themes/Economic-Sectors-Enterprises/Enterprises/Small-Sized-Enterprises-Medium-Sized-Enterprises/ExplanatorySME.html (last access: 24 March 2025), 2003.
Destatis: Klassifikation der Wirtschaftszweige, Ausgabe 2008 (WZ 2008), https://www.destatis.de/DE/Methoden/Klassifikationen/Gueter-Wirtschaftsklassifikationen/klassifikation-wz-2008.html (last access: 25 March 2025), 2008.
Endendijk, T., Botzen, W. J. W., De Moel, H., Slager, K., Kok, M., and Aerts, J. C. J. H.: Enhancing resilience: Understanding the impact of flood hazard and vulnerability on business interruption and losses, Water Resources and Economics, 46, 100244, https://doi.org/10.1016/j.wre.2024.100244, 2024.
Eurostat: Micro & small businesses make up 99 % of enterprises in the EU, https://ec.europa.eu/eurostat/web/products-eurostat-news/w/ddn-20241025-1 (last access: 25 March 2025), 2024.
Fisher, A., Rudin, C., and Dominici, F.: All Models are Wrong, but Many are Useful: Learning a Variable's Importance by Studying an Entire Class of Prediction Models Simultaneously, Journal of Machine Learning Research, 20, 1–81, 2019.
GDV: Facts and figures: Flood disaster “Bernd” July 2021, General Association of Insurers, Berlin, https://www.gdv.de/resource/blob/137346/c81a749e02503cb41a3e5a61966f3d31/pdf- Schadenbalance-data.pdf (last access: 16 September 2024), 2023.
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 [data set], https://doi.org/10.1594/GFZ.SDDB.HOWAS21, 2025.
Glover, F.: Future paths for integer programming and links to artificial intelligence, Computers & Operations Research, 13, 533–549, https://doi.org/10.1016/0305-0548(86)90048-1, 1986.
Goudet, O., Kalainathan, D., Caillou, P., Guyon, I., Lopez-Paz, D., and Sebag, M.: Learning Functional Causal Models with Generative Neural Networks, in: Explainable and Interpretable Models in Computer Vision and Machine Learning, edited by: Escalante, H. J., Escalera, S., Guyon, I., Baró, X., Güçlütürk, Y., Güçlü, U., and Van Gerven, M., Springer International Publishing, Cham, 39–80, https://doi.org/10.1007/978-3-319-98131-4_3, 2018.
Heckerman, D., Geiger, D., and Chickering, D. M.: Learning Bayesian networks: The combination of knowledge and statistical data, Mach. Learn., 20, 197–243, https://doi.org/10.1007/BF00994016, 1995.
Hirabayashi, Y., Mahendran, R., Koirala, S., Konoshima, L., Yamazaki, D., Watanabe, S., Kim, H., and Kanae, S.: Global flood risk under climate change, Nature Clim. Change, 3, 816–821, https://doi.org/10.1038/nclimate1911, 2013.
Hudson, P. and Thieken, A. H.: The presence of moral hazard regarding flood insurance and German private businesses, Nat. Hazards, 112, 1295–1319, https://doi.org/10.1007/s11069-022-05227-9, 2022.
Hudson, P., Bubeck, P., and Thieken, A. H.: A comparison of flood-protective decision-making between German households and businesses, Mitig. Adapt. Strateg. Glob. Change, 27, 5, https://doi.org/10.1007/s11027-021-09982-1, 2022.
Jehmlich, C., Hudson, P., and Thieken, A. H.: Short contribution on adaptive behaviour of flood-prone companies: A pilot study of Dresden-Laubegast, Germany, Journal of Flood Risk Management, 13, https://doi.org/10.1111/jfr3.12653, 2020.
Jongman, B., Kreibich, H., Apel, H., Barredo, J. I., Bates, P. D., Feyen, L., Gericke, A., Neal, J., Aerts, J. C. J. H., and Ward, P. J.: Comparative flood damage model assessment: towards a European approach, Nat. Hazards Earth Syst. Sci., 12, 3733–3752, https://doi.org/10.5194/nhess-12-3733-2012, 2012.
Kabirzad, S. A., Rehan, B. M., Zulkafli, Z., Yusuf, B., Hasan-Basri, B., and Toriman, M. E.: Examining direct and indirect flood damages in residential and business sectors through an empirical lens, Water Science and Technology, 90, 142–155, https://doi.org/10.2166/wst.2024.202, 2024.
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.
Koks, E. E., Bočkarjova, M., de Moel, H., and Aerts, J. C. J. H.: Integrated Direct and Indirect Flood Risk Modeling: Development and Sensitivity Analysis, Risk Analysis, 35, 882–900, https://doi.org/10.1111/risa.12300, 2015.
Kowarik, A. and Templ, M.: Imputation with the R Package VIM, J. Stat. Soft., 74, https://doi.org/10.18637/jss.v074.i07, 2016.
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 Resources Research, 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, Hydrological Sciences Journal, 55, 1302–1314, https://doi.org/10.1080/02626667.2010.529815, 2010.
Leitold, R., Garschagen, M., Tran, V., and Revilla Diez, J.: Flood risk reduction and climate change adaptation of manufacturing firms: Global knowledge gaps and lessons from Ho Chi Minh City, International Journal of Disaster Risk Reduction, 61, 102351, https://doi.org/10.1016/j.ijdrr.2021.102351, 2021.
Li, W., Wen, J., Xu, B., Li, X., and Du, S.: Integrated Assessment of Economic Losses in Manufacturing Industry in Shanghai Metropolitan Area Under an Extreme Storm Flood Scenario, Sustainability, 11, 126, https://doi.org/10.3390/su11010126, 2018.
Ma, M., Zhao, G., He, B., Li, Q., Dong, H., Wang, S., and Wang, Z.: XGBoost-based method for flash flood risk assessment, Journal of Hydrology, 598, 126382, https://doi.org/10.1016/j.jhydrol.2021.126382, 2021.
Merz, B., Blöschl, G., Vorogushyn, S., Dottori, F., Aerts, J. C. J. H., Bates, P., Bertola, M., Kemter, M., Kreibich, H., Lall, U., and Macdonald, E.: Causes, impacts and patterns of disastrous river floods, Nat. Rev. Earth Environ., 2, 592–609, https://doi.org/10.1038/s43017-021-00195-3, 2021.
Mohor, G. S., Hudson, P., and Thieken, A. H.: A Comparison of Factors Driving Flood Losses in Households Affected by Different Flood Types, Water Resources Research, 56, e2019WR025943, https://doi.org/10.1029/2019WR025943, 2020.
Mohr, S., Ehret, U., Kunz, M., Ludwig, P., Caldas-Alvarez, A., Daniell, J. E., Ehmele, F., Feldmann, H., Franca, M. J., Gattke, C., Hundhausen, M., Knippertz, P., Küpfer, K., Mühr, B., Pinto, J. G., Quinting, J., Schäfer, A. M., Scheibel, M., Seidel, F., and Wisotzky, C.: A multi-disciplinary analysis of the exceptional flood event of July 2021 in central Europe – Part 1: Event description and analysis, Nat. Hazards Earth Syst. Sci., 23, 525–551, https://doi.org/10.5194/nhess-23-525-2023, 2023.
Munich Re: Hurricanes, cold waves, tornadoes: Weather disasters in USA dominate natural disaster losses in 2021, https://www.munichre.com/en/company/media-relations/media-information-and-corporate-news/media-information/2022/natural-disaster-losses-2021.html (last access: 24 January 2025), 2022.
Munich Re: Climate change is showing its claws: The world is getting hotter, resulting in severe hurricanes, thunderstorms and floods, https://www.munichre.com/en/company/media-relations/media-information-and-corporate-news/media-information/2025/natural-disaster-figures-2024.html (last access: 15 January 2025), 2025.
Nafari, R. H., Ngo, T., and Lehman, W.: Development and evaluation of FLFAcs – A new Flood Loss Function for Australian commercial structures, International Journal of Disaster Risk Reduction, 17, 13–23, https://doi.org/10.1016/j.ijdrr.2016.03.007, 2016.
Narin, O. G.: Gap filling of water level time series with water area using remote sensing data: a comparative performance analysis of polynomial functions, XGBoost, Random Forest and Support Vector Machine, Hydrological Sciences Journal, 70, 750–760, https://doi.org/10.1080/02626667.2025.2458555, 2025.
Neise, T. and Revilla Diez, J.: Adapt, move or surrender? Manufacturing firms' routines and dynamic capabilities on flood risk reduction in coastal cities of Indonesia, International Journal of Disaster Risk Reduction, 33, 332–342, https://doi.org/10.1016/j.ijdrr.2018.10.018, 2019.
Pearl, J.: Probabilistic Reasoning in Intelligent Systems, Elsevier, https://doi.org/10.1016/C2009-0-27609-4, 1988.
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, É.: Scikit-learn: Machine Learning in Python, Journal of Machine Learning Research, 12, 2825–2830, 2011.
Pfurtscheller, C. and Vetter, M.: Assessing entrepreneurial and regional-economic flood impacts on a globalized production facility, J. Flood Risk Management, 8, 329–342, https://doi.org/10.1111/jfr3.12102, 2015.
Rhein, B. and Kreibich, H.: Causes of the exceptionally high number of fatalities in the Ahr valley, Germany, during the 2021 flood, Nat. Hazards Earth Syst. Sci., 25, 581–589, https://doi.org/10.5194/nhess-25-581-2025, 2025.
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.
Sakai, P. and Yao, Z.: Financial losses and flood damages experienced by SMEs: Who are the biggest losers across sectors and sizes?, International Journal of Disaster Risk Reduction, 91, https://doi.org/10.1016/j.ijdrr.2023.103677, 2023.
Schoppa, L., Sieg, T., Vogel, K., Zöller, G., and Kreibich, H.: Probabilistic Flood Loss Models for Companies, Water Resources Research, 56, e2020WR027649, https://doi.org/10.1029/2020WR027649, 2020.
Schoppa, L., Barendrecht, M., Sieg, T., Sairam, N., and Kreibich, H.: Augmenting a socio-hydrological flood risk model for companies with process-oriented loss estimation, Hydrological Sciences Journal, 67, 1623–1639, https://doi.org/10.1080/02626667.2022.2095207, 2022.
Schröter, K., Kreibich, H., Vogel, K., Riggelsen, C., Scherbaum, F., and Merz, B.: How useful are complex flood damage models?, Water Resources Research, 50, 3378–3395, https://doi.org/10.1002/2013WR014396, 2014.
Seifert, I., Kreibich, H., Merz, B., and Thieken, A. H.: Application and validation of FLEMOcs – a flood-loss estimation model for the commercial sector, Hydrological Sciences Journal, 55, 1315–1324, https://doi.org/10.1080/02626667.2010.536440, 2010.
Sieg, T., Vogel, K., Merz, B., and Kreibich, H.: Tree-based flood damage modeling of companies: Damage processes and model performance, Water Resources Research, 53, 6050–6068, https://doi.org/10.1002/2017WR020784, 2017.
Sieg, T., Schinko, T., Vogel, K., Mechler, R., Merz, B., and Kreibich, H.: Integrated assessment of short-term direct and indirect economic flood impacts including uncertainty quantification, PLoS ONE, 14, e0212932, https://doi.org/10.1371/journal.pone.0212932, 2019.
Sucar, L. E.: Probabilistic Graphical Models: Principles and Applications, Springer International Publishing, Cham, https://doi.org/10.1007/978-3-030-61943-5, 2021.
Sultana, Z., Sieg, T., Kellermann, P., Müller, M., and Kreibich, H.: Assessment of Business Interruption of Flood-Affected Companies Using Random Forests, Water, 10, 1049, https://doi.org/10.3390/w10081049, 2018.
Tay, J. K., Narasimhan, B., and Hastie, T.: Elastic Net Regularization Paths for All Generalized Linear Models, J. Stat. Soft., 106, https://doi.org/10.18637/jss.v106.i01, 2023.
Thieken, A., Kreibich, H., Müller, M., and Lamond, J.: Data Collection for a Better Understanding of What Causes Flood Damage–Experiences with Telephone Surveys, in: Geophysical Monograph Series, edited by: Molinari, D., Menoni, S., and Ballio, F., Wiley, 95–106, https://doi.org/10.1002/9781119217930.ch7, 2017.
Thieken, A., Bubeck, P., and Zenker, M.-L.: Fatal incidents during the flood of July 2021 in North Rhine-Westphalia, Germany: what can be learnt for future flood risk management?, JCRFR, 2, https://doi.org/10.59490/jcrfr.2023.0005, 2023a.
Thieken, A. H., Bessel, T., Kienzler, S., Kreibich, H., Müller, M., Pisi, S., and Schröter, K.: The flood of June 2013 in Germany: how much do we know about its impacts?, Nat. Hazards Earth Syst. Sci., 16, 1519–1540, https://doi.org/10.5194/nhess-16-1519-2016, 2016.
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.
Thieken, A. H., Bubeck, P., Heidenreich, A., von Keyserlingk, J., Dillenardt, L., and Otto, A.: Performance of the flood warning system in Germany in July 2021 – insights from affected residents, Nat. Hazards Earth Syst. Sci., 23, 973–990, https://doi.org/10.5194/nhess-23-973-2023, 2023b.
Trenczek, J., Lühr, O., Lukas, E., and Viktoria, L.: Damage from flash floods and floods in July 2021 in Germany. An ex-post analysis. Project report, Prognos AG, Düsseldorf, https://www.prognos.com/sites/default/files/2022-07/Prognos_ClimatechangeConsequencesDeutschland_Detailprobe Flut_AP2_3b_.pdf (last access: 25 October 2024), 2022.
Wagenaar, D., Lüdtke, S., Schröter, K., Bouwer, L. M., and Kreibich, H.: Regional and Temporal Transferability of Multivariable Flood Damage Models, Water Resources Research, 54, 3688–3703, https://doi.org/10.1029/2017WR022233, 2018.
Wutzler, B., Hudson, P., and Thieken, A. H.: Adaptation strategies of flood-damaged businesses in Germany, Frontiers in Water, 4, https://doi.org/10.3389/frwa.2022.932061, 2022.
Yang, L., Kajitani, Y., Tatano, H., and Jiang, X.: A methodology for estimating business interruption loss caused by flood disasters: insights from business surveys after Tokai Heavy Rain in Japan, Nat. Hazards, 84, 411–430, https://doi.org/10.1007/s11069-016-2534-3, 2016.
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, International Journal of Disaster Risk Reduction, 96, 103936, https://doi.org/10.1016/j.ijdrr.2023.103936, 2023.
Zhang, Z. and Tian, H.: Hybrid imputation-based optimal evidential classification for missing data, Appl. Intell., 55, 69, https://doi.org/10.1007/s10489-024-05950-9, 2025.
Zou, H. and Hastie, T.: Regularization and Variable Selection Via the Elastic Net, Journal of the Royal Statistical Society Series B: Statistical Methodology, 67, 301–320, https://doi.org/10.1111/j.1467-9868.2005.00503.x, 2005.
Short summary
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.
The 2021 flood in Germany caused severe damage to companies, with over half reporting losses...
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