 |
| Titel |
Operational aspects of asynchronous filtering for flood forecasting |
| VerfasserIn |
O. Rakovec, A. H. Weerts, J. Sumihar, R. Uijlenhoet |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1027-5606
|
| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 19, no. 6 ; Nr. 19, no. 6 (2015-06-23), S.2911-2924 |
| Datensatznummer |
250120750
|
| Publikation (Nr.) |
 copernicus.org/hess-19-2911-2015.pdf |
|
|
|
|
|
| Zusammenfassung |
| This study investigates the suitability of the asynchronous ensemble Kalman
filter (AEnKF) and a partitioned updating scheme for hydrological
forecasting. The AEnKF requires forward integration of the model for the
analysis and enables assimilation of current and past observations
simultaneously at a single analysis step. The results of discharge
assimilation into a grid-based hydrological model (using a soil moisture
error model) for the Upper Ourthe catchment in the Belgian Ardennes show that
including past predictions and observations in the data assimilation method
improves the model forecasts. Additionally, we show that elimination of the
strongly non-linear relation between the soil moisture storage and
assimilated discharge observations from the model update becomes beneficial
for improved operational forecasting, which is evaluated using several
validation measures. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|