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| Titel |
Analysis of projected hydrological behavior of catchments based on signature indices |
| VerfasserIn |
M. C. Casper, G. Grigoryan, O. Gronz, O. Gutjahr, G. Heinemann, R. Ley, A. Rock |
| 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. 2 ; Nr. 16, no. 2 (2012-02-09), S.409-421 |
| Datensatznummer |
250013172
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| Publikation (Nr.) |
 copernicus.org/hess-16-409-2012.pdf |
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| Zusammenfassung |
| To precisely map the changes in hydrologic response of catchments (e.g.
water balance, reactivity or extremes), we need sensitive and interpretable
indicators. In this study we defined nine hydrologically meaningful
signature indices: five indices were sampled on the flow duration curve,
four indices were closely linked to the distribution of event runoff
coefficients. We applied these signature indices to the output from a
hydrologic catchment model for three different catchments located in the
Nahe basin (Western Germany) to detect differences in runoff behavior
resulting from different meteorological input data. The models were driven
by measured and simulated (COSMO-CLM) meteorological data. It could be shown
that the application of signature indices is a very sensitive tool to assess
differences in simulated runoff behavior resulting from climatic data sets
of different sources. Specifically, the selected signature indices allow
assessing changes in water balance, vertical water distribution, reactivity,
seasonality and runoff generation. These indices showed that the
hydrological model is very sensitive to biases in mean and spatio-temporal
distribution of precipitation and temperature because it acts as a filter
for the meteorological input. Besides model calibration and model structural
deficits, we found that bias correction of temperature fields and further
adjustment of bias correction of precipitation fields is absolutely
essential. We conclude that signature indices can act as indirect
"efficiency measures" or "similarity measures" for output from regional
or local climate models. |
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