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| Titel |
Monthly hydrometeorological ensemble prediction of streamflow droughts and corresponding drought indices |
| VerfasserIn |
F. Fundel, S. Jörg-Hess, M. Zappa |
| 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 ; 17, no. 1 ; Nr. 17, no. 1 (2013-01-29), S.395-407 |
| Datensatznummer |
250017698
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| Publikation (Nr.) |
 copernicus.org/hess-17-395-2013.pdf |
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| Zusammenfassung |
Streamflow droughts, characterized by low runoff as consequence of a drought
event, affect numerous aspects of life. Economic sectors that are impacted by
low streamflow are, e.g., power production, agriculture, tourism, water
quality management and shipping. Those sectors could potentially benefit from
forecasts of streamflow drought events, even of short events on the monthly
time scales or below. Numerical hydrometeorological models have increasingly
been used to forecast low streamflow and have become the focus of recent
research. Here, we consider daily ensemble runoff forecasts for the river
Thur, which has its source in the Swiss Alps. We focus on the evaluation of
low streamflow and of the derived indices as duration, severity and
magnitude, characterizing streamflow droughts up to a lead time of one month.
The ECMWF VarEPS 5-member ensemble reforecast, which covers 18 yr, is used
as forcing for the hydrological model PREVAH. A thorough verification reveals
that, compared to probabilistic peak-flow forecasts, which show skill up to a
lead time of two weeks, forecasts of streamflow droughts are skilful over the
entire forecast range of one month. For forecasts at the lower end of the
runoff regime, the quality of the initial state seems to be crucial to
achieve a good forecast quality in the longer range. It is shown that the
states used in this study to initialize forecasts satisfy this requirement.
The produced forecasts of streamflow drought indices, derived from the
ensemble forecasts, could be beneficially included in a decision-making
process. This is valid for probabilistic forecasts of streamflow drought
events falling below a daily varying threshold, based on a quantile derived
from a runoff climatology. Although the forecasts have a tendency to
overpredict streamflow droughts, it is shown that the relative economic
value of the ensemble forecasts reaches up to 60%, in case a forecast
user is able to take preventive action based on the forecast. |
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