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| Titel |
Extreme heat and runoff extremes in the Swiss Alps |
| VerfasserIn |
M. Zappa, C. Kan |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1561-8633
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| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Science ; 7, no. 3 ; Nr. 7, no. 3 (2007-06-07), S.375-389 |
| Datensatznummer |
250004542
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| Publikation (Nr.) |
 copernicus.org/nhess-7-375-2007.pdf |
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| Zusammenfassung |
| The hydrological response of Swiss river basins to the 2003 European summer
heatwave was evaluated by a combined analysis of historical discharge
records and specific applications of distributed hydrological modeling. In
the summer of 2003, the discharge from headwater streams of the Swiss
Central Plateau was only 40%–60% of the long-term average. For alpine
basins runoff was about 60%–80% of the average. Glacierized basins
showed the opposite behavior. According to the degree of glacierization, the
average summer runoff was close or even above average. The hydrological
model PREVAH was applied for the period 1982–2005. Even if the model was not
calibrated for such extreme meteorological conditions, it was well able to
simulate the hydrological responses of three basins. The aridity index
φ describes feedbacks between hydrological and meteorological anomalies, and
was adopted as an indicator of hydrological drought. The anomalies of φ and
temperature in the summer of 2003 exceeded the 1982–2005 mean by more than 2
standard deviations. Catchments without glaciers showed negative
correlations between φ and discharge R. In basins with about 15%
glacierization, φ and R were not correlated. River basins with higher glacier
percentages showed a positive correlation between φ and R. Icemelt was
positively correlated with φ and reduced the variability of discharge with
larger amounts of meltwater. Runoff generation from the non-glaciated
sub-areas was limited by high evapotranspiration and reduced precipitation.
The 2003 summer heatwave could be a precursor to similar events in the near
future. Hydrological models and further data analysis will allow the
identification of the most sensitive regions where heatwaves may become a
recurrent natural hazard with large environmental, social and economical
impacts. |
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