The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
Inequitable patterns of US flood risk in the Anthropocene
Open accessAbstract
Current flood risk mapping, relying on historical observations, fails to account for increasing threat under climate change. Incorporating recent developments in inundation modelling, here we show a 26.4% (24.1–29.1%) increase in US flood risk by 2050 due to climate change alone under RCP4.5. Our national depiction of comprehensive and high-resolution flood risk estimates in the United States indicates current average annual losses of US$32.1 billion (US$30.5–33.8 billion) in 2020’s climate, which are borne disproportionately by poorer communities with a proportionally larger White population. The future increase in risk will disproportionately impact Black communities, while remaining concentrated on the Atlantic and Gulf coasts. Furthermore, projected population change (SSP2) could cause flood risk increases that outweigh the impact of climate change fourfold. These results make clear the need for adaptation to flood and emergent climate risks in the United States, with mitigation required to prevent the acceleration of these risks.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Changing Character of Precipitation
Trenberth, K. E., Dai, A., Rasmussen, R. M., & Parsons, D. B. (2003) · Bulletin of the American Meteorological Society · doi:10.1175/bams-84-9-1205 · Cited by 3,196
Global flood risk under climate change
Hirabayashi, Y., Mahendran, R., Koirala, S., Konoshima, L., Yamazaki, D., Watanabe, S., Kim, H., & Kanae, S. (2013) · Nature Climate Change · doi:10.1038/nclimate1911 · Cited by 3,013
Flood risk and climate change: global and regional perspectives
Kundzewicz, Z. W., Kanae, S., Seneviratne, S. I., Handmer, J., Nicholls, N., Peduzzi, P., Mechler, R., Bouwer, L. M., Arnell, N., Mach, K., et al. (2014) · Hydrological Sciences Journal · doi:10.1080/02626667.2013.857411 · Cited by 1,651
A simple raster-based model for flood inundation simulation
Bates, P. D., & De Roo, A. P. J. (2000) · Journal of Hydrology · doi:10.1016/s0022-1694(00)00278-x · Cited by 1,460
Self-citationNew elevation data triple estimates of global vulnerability to sea-level rise and coastal flooding
Kulp, S. A., & Strauss, B. H. (2019) · Nature Communications · doi:10.1038/s41467-019-12808-z · Cited by 1,288
Global drivers of future river flood risk
Winsemius, H. C., Aerts, J. C. J. H., van Beek, L. P. H., Bierkens, M. F. P., Bouwman, A., Jongman, B., Kwadijk, J. C. J., Ligtvoet, W., Lucas, P. L., van Vuuren, D. P., et al. (2016) · Nature Climate Change · doi:10.1038/nclimate2893 · Cited by 1,151
Probabilistic 21st and 22nd century sea‐level projections at a global network of tide‐gauge sites
Kopp, R. E., Horton, R. M., Little, C. M., Mitrovica, J. X., Oppenheimer, M., Rasmussen, D. J., Strauss, B. H., & Tebaldi, C. (2014) · Earth's Future · doi:10.1002/2014ef000239 · Cited by 966
Hurricanes and Global Warming: Results from Downscaling IPCC AR4 Simulations
Emanuel, K., Sundararajan, R., & Williams, J. (2008) · Bulletin of the American Meteorological Society · doi:10.1175/bams-89-3-347 · Cited by 928
Global projections of river flood risk in a warmer world
Alfieri, L., Bisselink, B., Dottori, F., Naumann, G., de Roo, A., Salamon, P., Wyser, K., & Feyen, L. (2017) · Earth's Future · doi:10.1002/2016ef000485 · Cited by 899
Downscaling CMIP5 climate models shows increased tropical cyclone activity over the 21st century
Emanuel, K. A. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1301293110 · Cited by 832
Cited by
Steinberg-McElroy, I., Tangtrakul, K., Alizadehtazi, B., Rosenzweig, B. R., Gurian, P. L., & Montalto, F. (2023) · doi:10.2139/ssrn.4571518 · Cited by 3
Metadata
- Authors
- Wing, O. E. J., Lehman, W., Bates, P. D., Sampson, C. C., Quinn, N., Smith, A. M., Neal, J. C., Porter, J. R., & Kousky, C.
- Venue
- Nature Climate Change
- Published
- 2022-01-31
- Volume
- 12
- Issue
- 2
- Pages
- 156-162
- ISSN
- 1758-678X (ISSN-L)
- 1758-6798
- OpenAlex
- W4210287559
- Cited by
- 482
- References
- 41
- FWCI
- 36.66
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Inequitable patterns of US flood risk in the Anthropocene. https://app.cochat.ai/papers/10.1038/s41558-021-01265-6
- The paper
- Wing, O. E. J., Lehman, W., Bates, P. D., Sampson, C. C., Quinn, N., Smith, A. M., Neal, J. C., Porter, J. R., & Kousky, C. (2022). Inequitable patterns of US flood risk in the Anthropocene. Nature Climate Change. https://doi.org/10.1038/s41558-021-01265-6
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
