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| Titel |
Annual flood sensitivities to El Niño–Southern Oscillation at the global scale |
| VerfasserIn |
P. J. Ward, S. Eisner, M. Flörke, M. D. Dettinger, M. Kummu |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 18, no. 1 ; Nr. 18, no. 1 (2014-01-06), S.47-66 |
| Datensatznummer |
250120244
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| Publikation (Nr.) |
 copernicus.org/hess-18-47-2014.pdf |
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| Zusammenfassung |
| Floods are amongst the most dangerous natural hazards in terms of economic
damage. Whilst a growing number of studies have examined how river floods
are influenced by climate change, the role of natural modes of interannual
climate variability remains poorly understood. We present the first global
assessment of the influence of El Niño–Southern Oscillation (ENSO) on
annual river floods, defined here as the peak daily discharge in a given
year. The analysis was carried out by simulating daily gridded discharges
using the WaterGAP model (Water – a Global Assessment and Prognosis), and examining statistical relationships between
these discharges and ENSO indices. We found that, over the period 1958–2000,
ENSO exerted a significant influence on annual floods in river basins
covering over a third of the world's land surface, and that its influence on
annual floods has been much greater than its influence on average flows. We
show that there are more areas in which annual floods intensify with La
Niña and decline with El Niño than vice versa. However, we also
found that in many regions the strength of the relationships between ENSO
and annual floods have been non-stationary, with either strengthening or
weakening trends during the study period. We discuss the implications of
these findings for science and management. Given the strong relationships
between ENSO and annual floods, we suggest that more research is needed to
assess relationships between ENSO and flood impacts (e.g. loss of lives or
economic damage). Moreover, we suggest that in those regions where useful
relationships exist, this information could be combined with ongoing
advances in ENSO prediction research, in order to provide year-to-year
probabilistic flood risk forecasts. |
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