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| Titel |
Variational assimilation of streamflow into operational distributed hydrologic models: effect of spatiotemporal scale of adjustment |
| VerfasserIn |
H. Lee, D.-J. Seo, Y. Liu, V. Koren, P. McKee, R. Corby |
| 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. 7 ; Nr. 16, no. 7 (2012-07-23), S.2233-2251 |
| Datensatznummer |
250013376
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| Publikation (Nr.) |
 copernicus.org/hess-16-2233-2012.pdf |
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| Zusammenfassung |
| State updating of distributed rainfall-runoff models via streamflow
assimilation is subject to overfitting because large dimensionality of the
state space of the model may render the assimilation problem seriously
under-determined. To examine the issue in the context of operational
hydrologic forecasting, we carried out a set of real-world experiments in
which streamflow data is assimilated into the gridded Sacramento Soil
Moisture Accounting (SAC-SMA) and kinematic-wave routing models of the US
National Weather Service (NWS) Research Distributed Hydrologic Model (RDHM)
via variational data assimilation (DA). The nine study basins include four
in Oklahoma and five in Texas. To assess the sensitivity of the performance
of DA to the dimensionality of the control vector, we used nine different
spatiotemporal adjustment scales, with which the state variables are
adjusted in a lumped, semi-distributed, or distributed fashion and biases in
precipitation and PE are adjusted at hourly or 6-hourly scale, or at the
scale of the fast response of the basin. For each adjustment scale, three
different assimilation scenarios were carried out in which streamflow
observations are assumed to be available at basin interior points only, at
the basin outlet only, or at all locations. The results for the nine basins
show that the optimum spatiotemporal adjustment scale varies from basin to
basin and between streamflow analysis and prediction for all three
streamflow assimilation scenarios. The most preferred adjustment scale for
seven out of the nine basins is found to be distributed and hourly. It was
found that basins with highly correlated flows between interior and outlet
locations tend to be less sensitive to the adjustment scale and could
benefit more from streamflow assimilation. In comparison with outlet flow
assimilation, interior flow assimilation produced streamflow predictions
whose spatial correlation structure is more consistent with that of observed
flow for all adjustment scales. We also describe diagnosing the complexity
of the assimilation problem using spatial correlation of streamflow and
discuss the effect of timing errors in hydrograph simulation on the
performance of the DA procedure. |
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