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Titel |
Future hydrological extremes: the uncertainty from multiple global climate and global hydrological models |
VerfasserIn |
I. Giuntoli, J.-P. Vidal, C. Prudhomme, D. M. Hannah |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
2190-4979
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Digitales Dokument |
URL |
Erschienen |
In: Earth System Dynamics ; 6, no. 1 ; Nr. 6, no. 1 (2015-05-18), S.267-285 |
Datensatznummer |
250115424
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Publikation (Nr.) |
copernicus.org/esd-6-267-2015.pdf |
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Zusammenfassung |
Projections of changes in the hydrological cycle from global hydrological
models (GHMs) driven by global climate models (GCMs) are critical for
understanding future occurrence of hydrological extremes. However,
uncertainties remain large and need to be better assessed. In particular,
recent studies have pointed to a considerable contribution of GHMs that can
equal or outweigh the contribution of GCMs to uncertainty in hydrological
projections. Using six GHMs and five GCMs from the ISI-MIP multi-model ensemble,
this study aims: (i) to assess future changes in the frequency of both high
and low flows at the global scale using control and future (RCP8.5)
simulations by the 2080s, and (ii) to quantify, for both ends of the runoff
spectrum, GCMs and GHMs contributions to uncertainty using a two-way ANOVA.
Increases are found in high flows for northern latitudes and in low flows for
several hotspots. Globally, the largest source of uncertainty is associated
with GCMs, but GHMs are the greatest source in snow-dominated regions. More
specifically, results vary depending on the runoff metric, the temporal
(annual and seasonal) and regional scale of analysis. For instance,
uncertainty contribution from GHMs is higher for low flows than it is for
high flows, partly owing to the different processes driving the onset of the
two phenomena (e.g. the more direct effect of the GCMs' precipitation
variability on high flows). This study provides a comprehensive synthesis of
where future hydrological extremes are projected to increase and where the
ensemble spread is owed to either GCMs or GHMs. Finally, our results
underline the need for improvements in modelling snowmelt and runoff processes
to project future hydrological extremes and the importance of using multiple
GCMs and GHMs to encompass the uncertainty range provided by these two
sources. |
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