The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
Validation of a 30 m resolution flood hazard model of the conterminous United States
Open accessAbstract
This paper reports the development of a ∼30 m resolution two‐dimensional hydrodynamic model of the conterminous U.S. using only publicly available data. The model employs a highly efficient numerical solution of the local inertial form of the shallow water equations which simulates fluvial flooding in catchments down to 50 km 2 and pluvial flooding in all catchments. Importantly, we use the U.S. Geological Survey (USGS) National Elevation Dataset to determine topography; the U.S. Army Corps of Engineers National Levee Database to explicitly represent known flood defenses; and global regionalized flood frequency analysis to characterize return period flows and rainfalls. We validate these simulations against the complete catalogue of Federal Emergency Management Agency (FEMA) Special Flood Hazard Area (SFHA) maps and detailed local hydraulic models developed by the USGS. Where the FEMA SFHAs are based on high‐quality local models, the continental‐scale model attains a hit rate of 86%. This correspondence improves in temperate areas and for basins above 400 km 2. Against the higher quality USGS data, the average hit rate reaches 92% for the 1 in 100 year flood, and 90% for all flood return periods. Given typical hydraulic modeling uncertainties in the FEMA maps and USGS model outputs (e.g., errors in estimating return period flows), it is probable that the continental‐scale model can replicate both to within error. The results show that continental‐scale models may now offer sufficient rigor to inform some decision‐making needs with dramatically lower cost and greater coverage than approaches based on a patchwork of local studies.
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Cites
World map of the Köppen-Geiger climate classification updated
Kottek, M., Grieser, J., Beck, C., Rudolf, B., & Rubel, F. (2006) · Meteorologische Zeitschrift · doi:10.1127/0941-2948/2006/0130 · Cited by 11,456
High-resolution mapping of global surface water and its long-term changes
Pekel, J.-F., Cottam, A., Gorelick, N., & Belward, A. S. (2016) · Nature · doi:10.1038/nature20584 · Cited by 5,513
(2015) · Photogrammetric Engineering & Remote Sensing · doi:10.1016/s0099-1112(15)30100-2 · Cited by 2,584
New Global Hydrography Derived from Spaceborne Elevation Data
Lehner, B., Verdin, K., & Jarvis, A. (2008) · Eos, Transactions American Geophysical Union · doi:10.1029/2008eo100001 · Cited by 2,411
Rabus, B., Eineder, M., Roth, A., & Bamler, R. (2003) · ISPRS Journal of Photogrammetry and Remote Sensing · doi:10.1016/s0924-2716(02)00124-7 · Cited by 1,820
Bates, P. D., Horritt, M. S., & Fewtrell, T. J. (2010) · Journal of Hydrology · doi:10.1016/j.jhydrol.2010.03.027 · Cited by 1,273
Self-citationEvaluation of 1D and 2D numerical models for predicting river flood inundation
Horritt, M. S., & Bates, P. D. (2002) · Journal of Hydrology · doi:10.1016/s0022-1694(02)00121-x · Cited by 1,195
Self-citationDong, J., Xiao, X., Menarguez, M. A., Zhang, G., Qin, Y., Thau, D., Biradar, C., & Moore, B. (2016) · Remote Sensing of Environment · doi:10.1016/j.rse.2016.02.016 · Cited by 767
Height Above the Nearest Drainage – a hydrologically relevant new terrain model
Nobre, A. D., Cuartas, L. A., Hodnett, M., Rennó, C. D., Rodrigues, G., Silveira, A., Waterloo, M., & Saleska, S. (2011) · Journal of Hydrology · doi:10.1016/j.jhydrol.2011.03.051 · Cited by 757
Rennó, C. D., Nobre, A. D., Cuartas, L. A., Soares, J. V., Hodnett, M. G., Tomasella, J., & Waterloo, M. J. (2008) · Remote Sensing of Environment · doi:10.1016/j.rse.2008.03.018 · Cited by 645
Cited by
Inequitable patterns of US flood risk in the Anthropocene
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) · Nature Climate Change · doi:10.1038/s41558-021-01265-6 · Cited by 482
Self-citationGlobal evidence of rapid urban growth in flood zones since 1985
Rentschler, J., Avner, P., Marconcini, M., Su, R., Strano, E., Vousdoukas, M., & Hallegatte, S. (2023) · Nature · doi:10.1038/s41586-023-06468-9 · Cited by 459
Operational Flood Mapping Using Multi-Temporal Sentinel-1 SAR Images: A Case Study from Bangladesh
Uddin, K., Matin, M. A., & Meyer, F. J. (2019) · Remote Sensing · doi:10.3390/rs11131581 · Cited by 348
Managed retreat through voluntary buyouts of flood-prone properties
Mach, K. J., Kraan, C. M., Hino, M., Siders, A. R., Johnston, E. M., & Field, C. B. (2019) · Science Advances · doi:10.1126/sciadv.aax8995 · Cited by 225
Exposure to Floods, Climate Change, and Poverty in Vietnam
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Metadata
- Authors
- Wing, O. E. J., Bates, P. D., Sampson, C. C., Smith, A. M., Johnson, K. A., & Erickson, T. A.
- Venue
- Water Resources Research
- Publisher
- American Geophysical Union (AGU)
- Published
- 2017-09
- Volume
- 53
- Issue
- 9
- Pages
- 7968-7986
- ISSN
- 0043-1397 (ISSN-L)
- 1944-7973
- OpenAlex
- W2740993754
- Cited by
- 357
- References
- 30
- FWCI
- 13.82
- Type
- journal article
- Language
- en
- Open access
- hybrid
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