The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
Dynamic flood modeling essential to assess the coastal impacts of climate change
Open accessAbstract
Coastal inundation due to sea level rise (SLR) is projected to displace hundreds of millions of people worldwide over the next century, creating significant economic, humanitarian, and national-security challenges. However, the majority of previous efforts to characterize potential coastal impacts of climate change have focused primarily on long-term SLR with a static tide level, and have not comprehensively accounted for dynamic physical drivers such as tidal non-linearity, storms, short-term climate variability, erosion response and consequent flooding responses. Here we present a dynamic modeling approach that estimates climate-driven changes in flood-hazard exposure by integrating the effects of SLR, tides, waves, storms, and coastal change (i.e. beach erosion and cliff retreat). We show that for California, USA, the world’s 5 th largest economy, over $150 billion of property equating to more than 6% of the state’s GDP and 600,000 people could be impacted by dynamic flooding by 2100; a three-fold increase in exposed population than if only SLR and a static coastline are considered. The potential for underestimating societal exposure to coastal flooding is greater for smaller SLR scenarios, up to a seven-fold increase in exposed population and economic interests when considering storm conditions in addition to SLR. These results highlight the importance of including climate-change driven dynamic coastal processes and impacts in both short-term hazard mitigation and long-term adaptation planning.
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Cites
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Sea-level rise exponentially increases coastal flood frequency
Taherkhani, M., Vitousek, S., Barnard, P. L., Frazer, N., Anderson, T. R., & Fletcher, C. H. (2020) · Scientific Reports · doi:10.1038/s41598-020-62188-4 · Cited by 346
Self-citationAhmed, L. I., Ibrahim, N., Abdel-Salam, A. B., & Fahim, K. M. (2021) · Food Bioscience · doi:10.1016/j.fbio.2021.101177 · Cited by 83
Cai, Z. (2021) · npj Quantum Information · doi:10.1038/s41534-021-00404-3 · Cited by 76
Stuldreher, I. V., Thammasan, N., van Erp, J. B. F., & Brouwer, A.-M. (2020) · Journal of Neural Engineering · doi:10.1088/1741-2552/aba87d · Cited by 58
Metadata
- Authors
- Barnard, P. L., Erikson, L. H., Foxgrover, A. C., Hart, J. A. F., Limber, P., O’Neill, A. C., van Ormondt, M., Vitousek, S., Wood, N., Hayden, M. K., & Jones, J. M.
- Venue
- Scientific Reports
- Published
- 2019-03-13
- Volume
- 9
- Issue
- 1
- Pages
- 4309-4309
- ISSN
- 2045-2322 (ISSN-L)
- OpenAlex
- W2922004938
- Cited by
- 375
- References
- 55
- FWCI
- 46.12
- Type
- journal article
- Language
- en
- Open access
- gold
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- Barnard, P. L., Erikson, L. H., Foxgrover, A. C., Hart, J. A. F., Limber, P., O’Neill, A. C., van Ormondt, M., Vitousek, S., Wood, N., Hayden, M. K., & Jones, J. M. (2019). Dynamic flood modeling essential to assess the coastal impacts of climate change. Scientific Reports. https://doi.org/10.1038/s41598-019-40742-z
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