Flood risk management in the USA is largely embedded in the National Flood Insurance Program (NFIP). Climate change and increasing exposure in flood plains pose a challenge to flood risk managers and make it vital to reduce risk in the future. The proposed reforms are steering the NFIP to risk-based premiums, but it is uncertain if the reforms will result in unaffordability and incentivize risk-reduction investments or how the NFIP is affected by large-scale adaptation efforts. Using an agent-based model approach for current and future scenarios, we demonstrate that risk-based premiums will yield a positive societal benefit (US$10 billion) because they will incentivize household risk-reduction investments. Moreover, our results show that proactive investment in large-scale adaptation measures complements a transition to risk-based premiums to yield a higher overall societal benefit (US$26 billion). We suggest that transitioning the NFIP to risk-based premiums can only be secured by additional investments in large-scale flood protection infrastructure.
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Land-cover data were obtained from GlobeLand30,42. Inundation data were obtained from the GLOFRIS cascade model33. Vulnerability curves were obtained from HAZUS-MH model44. Maximum damage values are available at ref. 43. NFIP insurance data are available at ref. 55. Income data were obtained from the US Census Bureau59. Protection standard database was obtained from FLOPROS50. NFIP Redacted Claims dataset is available from FEMA73. FEMA and the Federal Government cannot vouch for the data or analyses derived from these data after the data have been retrieved from the Agency’s website(s) and/or Data.gov. Socio-economic data were obtained from the International Institute for Applied Systems Analysis74. The generated data that support the finding of this study are available in figshare with the identifiers: https://doi.org/10.6084/m9.figshare.17049416.v1. There are no restrictions on data availability.
The code for DYNAMO is available in Zenodo with the identifiers: https://doi.org/10.5281/zenodo.7025225. There are no restrictions on code availability.
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We would like to thank M. Montgomery for sharing data and M. Tesselaar for his feedback. This research received funding from the Netherlands Organization for Scientific Research VIDI (45214005 to W.J.W.B.) and VICI (016140067 and 453-13-006 to J.A.) grant programmes and ERC advanced grant (884442 to J.A.).
The authors declare no competing interests.
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A schematic overview of the primary modelling steps, showing the main buildings blocks of the DYNamic climate impact Adaptation Model (DYNAMO): (a) modelling schematic: a flood risk model and an agent-based model, (b) input data: flood maps, exposure data, flood protection data, income, (c) scenarios: socio-economic and climate change scenarios until 2050, (d) policy scenarios: governmental adaptation policies and NFIP market structures, (e) outputs: flood risk (EAD), insurance penetration rates, affordability, disaster risk reduction (DRR), and flood protection standards, (f) validation: damage and premium income. The framework builds upon earlier applications and version of DYNAMO by Haer et al.21 for the EU and de Ruig et al.28 for New York City.
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de Ruig, L.T., Haer, T., de Moel, H. et al. How the USA can benefit from risk-based premiums combined with flood protection. Nat. Clim. Chang. 12, 995–998 (2022). https://doi.org/10.1038/s41558-022-01501-7