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| Titel |
Performance and robustness of probabilistic river forecasts computed with quantile regression based on multiple independent variables |
| VerfasserIn |
F. Hoss, P. S. Fischbeck |
| 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 ; 19, no. 9 ; Nr. 19, no. 9 (2015-09-25), S.3969-3990 |
| Datensatznummer |
250120814
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| Publikation (Nr.) |
 copernicus.org/hess-19-3969-2015.pdf |
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| Zusammenfassung |
| This study applies quantile regression (QR) to predict exceedance
probabilities of various water levels, including flood stages, with
combinations of deterministic forecasts, past forecast errors and rates of
water level rise as independent variables. A computationally cheap technique
to estimate forecast uncertainty is valuable, because many national flood
forecasting services, such as the National Weather Service (NWS), only
publish deterministic single-valued forecasts. The study uses data from the
82 river gauges, for which the NWS' North Central River Forecast Center
issues forecasts daily. Archived forecasts for lead times of up to 6 days
from 2001 to 2013 were analyzed. Besides the forecast itself, this study uses
the rate of rise of the river stage in the last 24 and 48 h and the
forecast error 24 and 48 h ago as predictors in QR configurations. When
compared to just using the forecast as an independent variable, adding the
latter four predictors significantly improved the forecasts, as measured by
the Brier skill score and the continuous ranked probability score. Mainly,
the resolution increases, as the forecast-only QR configuration already
delivered high reliability. Combining the forecast with the other four
predictors results in a much less favorable performance. Lastly, the forecast
performance does not strongly depend on the size of the training data set
but on the year, the river gauge, lead time and event threshold that are
being forecast. We find that each event threshold requires a separate
configuration or at least calibration. |
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