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| Titel |
State updating of a distributed hydrological model with Ensemble Kalman Filtering: effects of updating frequency and observation network density on forecast accuracy |
| VerfasserIn |
O. Rakovec, A. H. Weerts, P. Hazenberg, P. J. J. F. Torfs, R. Uijlenhoet |
| 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. 9 ; Nr. 16, no. 9 (2012-09-24), S.3435-3449 |
| Datensatznummer |
250013481
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| Publikation (Nr.) |
 copernicus.org/hess-16-3435-2012.pdf |
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| Zusammenfassung |
This paper presents a study on the optimal setup for discharge assimilation
within a spatially distributed hydrological model. The Ensemble Kalman filter
(EnKF) is employed to update the grid-based distributed states of such an
hourly spatially distributed version of the HBV-96 model. By using a
physically based model for the routing, the time delay and attenuation are
modelled more realistically. The discharge and states at a given time step
are assumed to be dependent on the previous time step only (Markov property).
Synthetic and real world experiments are carried out for the Upper Ourthe
(1600 km2), a relatively quickly responding catchment in the Belgian
Ardennes. We assess the impact on the forecasted discharge of (1) various
sets of the spatially distributed discharge gauges and (2) the filtering
frequency. The results show that the hydrological forecast at the catchment
outlet is improved by assimilating interior gauges. This augmentation of the
observation vector improves the forecast more than increasing the updating
frequency. In terms of the model states, the EnKF procedure is found to
mainly change the pdfs of the two routing model storages, even when the
uncertainty in the discharge simulations is smaller than the defined
observation uncertainty. |
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