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Role of dams in reducing global flood exposure under climate change
Open accessAbstract
Globally, flood risk is projected to increase in the future due to climate change and population growth. Here, we quantify the role of dams in flood mitigation, previously unaccounted for in global flood studies, by simulating the floodplain dynamics and flow regulation by dams. We show that, ignoring flow regulation by dams, the average number of people exposed to flooding below dams amount to 9.1 and 15.3 million per year, by the end of the 21 st century (holding population constant), for the representative concentration pathway (RCP) 2.6 and 6.0, respectively. Accounting for dams reduces the number of people exposed to floods by 20.6 and 12.9% (for RCP2.6 and RCP6.0, respectively). While environmental problems caused by dams warrant further investigations, our results indicate that consideration of dams significantly affect the estimation of future population exposure to flood, emphasizing the need to integrate them in model-based impact analysis of climate change.
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An Introduction to Statistical Learning
James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013) · Springer Texts in Statistics · doi:10.1007/978-1-4614-7138-7 · Cited by 12,106
Global hydrological cycles and world water resources
Oki, T., & Kanae, S. (2006) · Science · doi:10.1126/science.1128845 · Cited by 4,392
L-Moments: Analysis and Estimation of Distributions Using Linear Combinations of Order Statistics
Hosking, J. R. M. (1990) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1990.tb01775.x · Cited by 3,146
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
Self-citationAn Introduction to Statistical Learning: with Applications in R
James, G. M., Witten, D., Hastie, T. J., & Tibshirani, R. J. (2018) · doi:10.25334/q4ht55 · Cited by 2,912
High‐resolution mapping of the world's reservoirs and dams for sustainable river‐flow management
Lehner, B., Liermann, C. R., Revenga, C., Vörösmarty, C., Fekete, B., Crouzet, P., Döll, P., Endejan, M., Frenken, K., Magome, J., et al. (2011) · Frontiers in Ecology and the Environment · doi:10.1890/100125 · Cited by 2,515
Mapping the world’s free-flowing rivers
Grill, G., Lehner, B., Thieme, M., Geenen, B., Tickner, D., Antonelli, F., Babu, S., Borrelli, P., Cheng, L., Crochetiere, H., et al. (2019) · Nature · doi:10.1038/s41586-019-1111-9 · Cited by 2,473
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
A global boom in hydropower dam construction
Zarfl, C., Lumsdon, A. E., Berlekamp, J., Tydecks, L., & Tockner, K. (2015) · Aquatic Sciences · doi:10.1007/s00027-014-0377-0 · Cited by 2,181
Increasing risk of great floods in a changing climate
Milly, P. C. D., Wetherald, R. T., Dunne, K. A., & Delworth, T. L. (2002) · Nature · doi:10.1038/415514a · Cited by 1,758
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The global value of freshwater lakes
Li, X., & Tsigaris, P. (2024) · Ecology Letters · doi:10.1111/ele.14388 · Cited by 20
Metadata
- Authors
- Boulange, J., Hanasaki, N., Yamazaki, D., & Pokhrel, Y.
- Venue
- Nature Communications
- Published
- 2021-01-18
- Volume
- 12
- Issue
- 1
- Pages
- 417-417
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W3125401559
- Cited by
- 380
- References
- 50
- FWCI
- 23.36
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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