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| Titel |
Quantifying different sources of uncertainty in hydrological projections in an Alpine watershed |
| VerfasserIn |
C. Dobler, S. Hagemann, R. L. Wilby, J. Stötter  |
| 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 ; 16, no. 11 ; Nr. 16, no. 11 (2012-11-22), S.4343-4360 |
| Datensatznummer |
250013578
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| Publikation (Nr.) |
 copernicus.org/hess-16-4343-2012.pdf |
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| Zusammenfassung |
| Many studies have investigated potential climate change impacts on regional
hydrology; less attention has been given to the components of uncertainty
that affect these scenarios. This study quantifies uncertainties resulting
from (i) General Circulation Models (GCMs), (ii) Regional Climate Models
(RCMs), (iii) bias-correction of RCMs, and (iv) hydrological model
parameterization using a multi-model framework. This consists of three GCMs,
three RCMs, three bias-correction techniques, and sets of hydrological model
parameters. The study is performed for the Lech watershed (~ 1000 km2), located in the Northern Limestone Alps, Austria.
Bias-corrected climate data are used to drive the hydrological model HQsim
to simulate runoff under present (1971–2000) and future (2070–2099) climate
conditions. Hydrological model parameter uncertainty is assessed by Monte
Carlo sampling. The model chain is found to perform well under present
climate conditions. However, hydrological projections are associated with
high uncertainty, mainly due to the choice of GCM and RCM. Uncertainty due
to bias-correction is found to have greatest influence on projections of
extreme river flows, and the choice of method(s) is an important
consideration in snowmelt systems. Overall, hydrological model
parameterization is least important. The study also demonstrates how an
improved understanding of the physical processes governing future river
flows can help focus attention on the scientifically tractable elements of
the uncertainty. |
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