 |
| Titel |
Operational hydrological data assimilation with the recursive ensemble Kalman filter |
| VerfasserIn |
H. K. McMillan, E. Ö. Hreinsson, M. P. Clark, S. K. Singh, C. Zammit, M. J. Uddstrom |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1027-5606
|
| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 17, no. 1 ; Nr. 17, no. 1 (2013-01-10), S.21-38 |
| Datensatznummer |
250017673
|
| Publikation (Nr.) |
 copernicus.org/hess-17-21-2013.pdf |
|
|
|
|
|
| Zusammenfassung |
| This paper describes the design and use of a recursive ensemble Kalman
filter (REnKF) to assimilate streamflow data in an operational flow
forecasting system of seven catchments in New Zealand. The REnKF iteratively
updates past and present model states (soil water, aquifer and surface
storages), with lags up to the concentration time of the catchment, to
improve model initial conditions and hence flow forecasts. We found the
REnKF overcame instabilities in the standard EnKF, which were associated with
the natural lag time between upstream catchment wetness and flow at the
gauging locations. The forecast system performance was correspondingly
improved in terms of Nash–Sutcliffe score, persistence index and bounding of
the measured flow by the model ensemble. We present descriptions of filter
design parameters and explanations and examples of filter behaviour, as an
information source for other groups wishing to assimilate discharge
observations for operational forecasting. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|