• Angrist, J., and J. Piske, 2009: Mostly Harmless Econometrics. Princeton University Press, 373 pp.

  • Bubeck, P., W. J. W. Botzen, H. Kreibich, and J. C. J. H. Aerts, 2013: Detailed insights into the influence of flood-coping appraisals on mitigation behavior. Global Environ. Change, 23, 13271338, https://doi.org/10.1016/j.gloenvcha.2013.05.009.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • CRED and UNISDR, 2018: Economic losses, poverty & disasters: 1998–2017. CRED and UNISDR Rep., 33 pp., www.preventionweb.net/files/61119_credeconomiclosses.pdf.

    • Search Google Scholar
    • Export Citation
  • de Perez, E. C., B. van den Hurk, M. K. van Aalst, B. Jongman, T. Klose, and P. Suarez, 2015: Forecast-based financing: An approach for catalyzing humanitarian action based on extreme weather and climate forecasts. Nat. Hazards Earth Syst. Sci., 15, 895904, https://doi.org/10.5194/nhess-15-895-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Deutsch, M., and K.-H. Pörtge, 2001: Die Hochwassermeldeordnung von 1889—Ein Beitrag zur Geschichte des Hochwasserwarn und Meldedienstes in Mitteldeutschland. Forum Katastrophenvorsorge 2001, Leipzig, Germany, DKKV, 396405.

    • Search Google Scholar
    • Export Citation
  • Dietz, H., 1999: Wohngebäudeversicherung: Kommentar. 2nd ed. VVW Verlag Versicherungswirtschaft GmbH, 756 pp.

  • Fields, A., 2009: Discovering Statistics Using SPSS. SAGE, 821 pp.

  • Grundfest, E., G. F. White, T. C. Downing, 1978: Big Thompson flood exposes need for better flood reaction system to save lives. Civil Eng., 48, 7273.

    • Search Google Scholar
    • Export Citation
  • Hudson, P., W. Botzen, H. Kreibich, P. Bubeck, and J. C. J. H. Aerts, 2014: Evaluating the effectiveness of flood damage mitigation measures by the application of propensity score matching. Nat. Hazards Earth Syst. Sci., 14, 17311747, https://doi.org/10.5194/nhess-14-1731-2014.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hudson, P., W. Botzen, J. Czajkowski, and H. Kreibich, 2017: Moral hazard in natural disaster insurance markets: Empirical evidence from Germany and the United States. Land Econ., 93, 179208, https://doi.org/10.3368/le.93.2.179.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hudson, P., A. H. Thieken, and P. Bubeck, 2019: The challenges of longitudinal surveys in the flood risk domain. J. Risk Res., 23, 642663, https://doi.org/10.1080/13669877.2019.1617339.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kienzler, S., I. Pech, H. Kreibich, M. Müller, and A. H. Thieken, 2015: After the extreme flood in 2002: Changes in preparedness, response and recovery of flood-affected residents in Germany between 2005 and 2011. Nat. Hazards Earth Syst. Sci., 15, 505526, https://doi.org/10.5194/nhess-15-505-2015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kreibich, H., S. Christenberger, and R. Schwarze, 2011a: Economic motivation of households to undertake private precautionary measures against floods. Nat. Hazards Earth Syst. Sci., 11, 309321, https://doi.org/10.5194/nhess-11-309-2011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kreibich, H., I. Seifert, A. H. Thieken, E. Lindquist, K. Wagner, and B. Merz, 2011b: Recent changes in flood preparedness of private households and businesses in Germany. Reg. Environ. Change, 11, 5971, https://doi.org/10.1007/s10113-010-0119-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kreibich, H., M. Müller, K. Schröter, and A. H. Thieken, 2017: New insights into flood warning reception and emergency response by affected parties. Nat. Hazards Earth Syst. Sci., 17, 20752092, https://doi.org/10.5194/nhess-17-2075-2017.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lopez, A., E. C. de Perez, J. Bazo, P. Suarez, B. van den Hurk, and M. van Aalst, 2020: Bridging forecast verification and humanitarian decisions: A valuation approach for setting up action-oriented early warnings. Wea. Climate Extremes, 27, 100167, https://doi.org/10.1016/j.wace.2018.03.006.

    • Search Google Scholar
    • Export Citation
  • Merz, B., H. Kreibich, and U. Lall, 2013: Multi-variate flood damage assessment: A tree-based data-mining approach. Nat. Hazards Earth Syst. Sci., 13, 5364, https://doi.org/10.5194/nhess-13-53-2013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Molinari, D., and J. Handmer, 2011: A behavioural model for quantifying flood warning effectiveness. J. Flood Risk Manage., 4, 2332, https://doi.org/10.1111/j.1753-318X.2010.01086.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Morss, R., K. J. Mulder, J. K. Lazo, and J. L. Demuth, 2016: How do people perceive, understand, and anticipate responding to flash flood risks and warnings? Results from a public survey in Boulder, Colorado, USA. J. Hydrol., 541, 649664, https://doi.org/10.1016/j.jhydrol.2015.11.047.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Osberghaus, D., 2015: The determinants of private flood mitigation measures in Germany—Evidence from a nationwide survey. Ecol. Econ., 110, 3650, https://doi.org/10.1016/j.ecolecon.2014.12.010.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pappenberger, F., H. L. Cloke, D. J. Parker, F. Wetterhall, D. S. Richardson, and J. Thielen, 2015: The monetary benefit of early flood warnings in Europe. Environ. Sci. Policy, 51, 278291, https://doi.org/10.1016/j.envsci.2015.04.016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Perera, D., O. Seidou, J. Agnihotri, M. Rasmy, V. Smakhtin, P. Coulibaly, and H. Mehmood, 2019: Flood early warning systems: A review of benefits, challenges and prospects. UNU-INWEH Rep. Series 08, 30 pp., https://inweh.unu.edu/wp-content/uploads/2019/08/Flood-Early-Warning-Systems-A-Review-Of-Benefits-Challenges-And-Prospects.pdf.

    • Search Google Scholar
    • Export Citation
  • Poussin, J. K., W. J. W. Botzen, and J. C. J. H. Aerts, 2014: Factors of influence on flood damage mitigation behavior by households. Environ. Sci. Policy, 40, 6977, https://doi.org/10.1016/j.envsci.2014.01.013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rai, R. K., M. J. C. van den Homberg, G. P. Ghimire, and C. McQuistan, 2020: Cost-benefit analysis of flood early warning system in the Karnali River basin of Nepal. Int. J. Disaster Risk Reduct., 47, 101534, https://doi.org/10.1016/j.ijdrr.2020.101534.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rosenbaum, P., 2002: Observational Studies. Springer, 375 pp.

  • Rosenbaum, P., and D. Rubin, 1983: The central role of the propensity score in observational studies for causal effects. Biometrika, 70, 4155, https://doi.org/10.1093/biomet/70.1.41.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sairam, N., K. Schröter, S. Lüdtke, B. Merz, and H. Kreibich, 2019: Quantifying flood vulnerability reduction via private precaution. Earth’s Future, 7, 235249, https://doi.org/10.1029/2018EF000994.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sarmiento, J. P., V. Sandoval, and M. Jerath, 2020: The influence of land tenure and dwelling occupancy on disaster risk reduction. The case of eight informal settlements in six Latin American and Caribbean countries. Prog. Disaster Sci., 5, 100054, https://doi.org/10.1016/j.pdisas.2019.100054.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stephens, E., and H. Cloke, 2014: Improving flood forecasts for better flood preparedness in the UK (and beyond). Geogr. J., 180, 310316, https://doi.org/10.1111/geoj.12103.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thieken, A. H., M. Müller, H. Kreibich, and B. Merz, 2005: Flood damage and influencing factors: New insights from the August 2002 flood in Germany. Water Resour. Res., 41, W12430, https://doi.org/10.1029/2005WR004177.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thieken, A. H., H. Kreibich, M. Müller, and B. Merz, 2007: Coping with floods: Preparedness, response and recovery of flood-affected residents in Germany in 2002. Hydrol. Sci. J., 52, 10161037, https://doi.org/10.1623/hysj.52.5.1016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • UN, 2015: GAR15—Global Assessment Report on Disaster Risk Reduction 2015—Making development sustainable: The future of disaster risk management. UNISDR Rep., 310 pp., www.preventionweb.net/english/hyogo/gar/2015/en/home/GAR_2015/GAR_2015_1.html.

    • Search Google Scholar
    • Export Citation
  • UNDP, 2018: Five approaches to build functional early warning systems. UNDP Rep., 67 pp., www.eurasia.undp.org/content/dam/rbec/docs/UNDP%20Brochure%20Early%20Warning%20Systems.pdf.

    • Search Google Scholar
    • Export Citation
  • UNISDR, 2015: Sendai framework for disaster risk reduction 2015–2030. UNISDR Rep., 37 pp., www.preventionweb.net/files/43291_sendaiframeworkfordrren.pdf.

    • Search Google Scholar
    • Export Citation
  • WMO, 2019: Hazard warnings must reach the last mile, metre—and bucket. WMO, https://public.wmo.int/en/media/news/hazard-warnings-must-reach-last-mile-metre-and-bucket.

    • Search Google Scholar
    • Export Citation
  • Wooldridge, J. M., 2002: Econometric Analysis of Cross Section and Panel Data. MIT Press, 1064 pp.

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Knowing What to Do Substantially Improves the Effectiveness of Flood Early Warning

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  • 1 Section Hydrology, GFZ German Research Centre for Geosciences, Potsdam, Germany
  • | 2 Institute for Environmental Sciences and Geography, University of Potsdam, Potsdam, Germany
  • | 3 Section Hydrology, GFZ German Research Centre for Geosciences, and Institute for Environmental Sciences and Geography, University of Potsdam, Potsdam, Germany
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Abstract

Flood warning systems are longstanding success stories with respect to protecting human life, but monetary losses continue to grow. Knowledge on the effectiveness of flood early warning in reducing monetary losses is scarce, especially at the individual level. To gain more knowledge in this area, we analyze a dataset that is unique with respect to detailed information on warning reception and monetary losses at the property level and with respect to amount of data available. The dataset contains 4,468 loss cases from six flood events in Germany. These floods occurred between 2002 and 2013. The data from each event were collected by computer-aided telephone interviews in four surveys following a repeated cross-sectional design. We quantitatively reveal that flood early warning is only effective in reducing monetary losses when people know what to do when they receive the warning. We also show that particularly long-term preparedness is associated with people knowing what to do when they receive a warning. Thus, risk communication, training, and (financial) support for private preparedness are effective in mitigating flood losses in two ways: precautionary measures and more effective emergency responses.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Heidi Kreibich, Heidi.Kreibich@gfz-potsdam.de

Abstract

Flood warning systems are longstanding success stories with respect to protecting human life, but monetary losses continue to grow. Knowledge on the effectiveness of flood early warning in reducing monetary losses is scarce, especially at the individual level. To gain more knowledge in this area, we analyze a dataset that is unique with respect to detailed information on warning reception and monetary losses at the property level and with respect to amount of data available. The dataset contains 4,468 loss cases from six flood events in Germany. These floods occurred between 2002 and 2013. The data from each event were collected by computer-aided telephone interviews in four surveys following a repeated cross-sectional design. We quantitatively reveal that flood early warning is only effective in reducing monetary losses when people know what to do when they receive the warning. We also show that particularly long-term preparedness is associated with people knowing what to do when they receive a warning. Thus, risk communication, training, and (financial) support for private preparedness are effective in mitigating flood losses in two ways: precautionary measures and more effective emergency responses.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Heidi Kreibich, Heidi.Kreibich@gfz-potsdam.de
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