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| Titel |
Benchmarking hydrological models for low-flow simulation and forecasting on French catchments |
| VerfasserIn |
P. Nicolle, R. Pushpalatha, C. Perrin, D. François, D. Thiéry, T. Mathevet, M. Le Lay, F. Besson, J.-M. Soubeyroux, C. Viel, F. Regimbeau, V. Andréassian, P. Maugis, B. Augeard, E. Morice |
| 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 ; 18, no. 8 ; Nr. 18, no. 8 (2014-08-05), S.2829-2857 |
| Datensatznummer |
250120424
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| Publikation (Nr.) |
 copernicus.org/hess-18-2829-2014.pdf |
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| Zusammenfassung |
| Low-flow simulation and forecasting remains a difficult issue for
hydrological modellers, and intercomparisons can be extremely instructive for
assessing existing low-flow prediction models and for developing more efficient
operational tools. This research presents the results of a collaborative
experiment conducted to compare low-flow simulation and forecasting models
on 21 unregulated catchments in France. Five hydrological models (four
lumped storage-type models – Gardenia, GR6J, Mordor and Presages – and one
distributed physically oriented model – SIM) were applied within a common
evaluation framework and assessed using a common set of criteria. Two simple
benchmarks describing the average streamflow variability were used to set
minimum levels of acceptability for model performance in simulation and
forecasting modes. Results showed that, in simulation as well as in
forecasting modes, all hydrological models performed almost systematically
better than the benchmarks. Although no single model outperformed all the
others for all catchments and criteria, a few models appeared to be more
satisfactory than the others on average. In simulation mode, all attempts to
relate model efficiency to catchment or streamflow characteristics remained
inconclusive. In forecasting mode, we defined maximum useful forecasting
lead times beyond which the model does not bring useful information compared
to the benchmark. This maximum useful lead time logically varies between
catchments, but also depends on the model used. Simple multi-model
approaches that combine the outputs of the five hydrological models were
tested to improve simulation and forecasting efficiency. We found that the
multi-model approach was more robust and could provide better performance
than individual models on average. |
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