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| Titel |
A new data assimilation approach for improving runoff prediction using remotely-sensed soil moisture retrievals |
| VerfasserIn |
W. T. Crow, D. Ryu |
| 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 ; 13, no. 1 ; Nr. 13, no. 1 (2009-01-07), S.1-16 |
| Datensatznummer |
250011722
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| Publikation (Nr.) |
 copernicus.org/hess-13-1-2009.pdf |
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| Zusammenfassung |
| A number of recent studies have focused on enhancing runoff prediction via
the assimilation of remotely-sensed surface soil moisture retrievals into a
hydrologic model. The majority of these approaches have viewed the problem
from purely a state or parameter estimation perspective in which
remotely-sensed soil moisture estimates are assimilated to improve the
characterization of pre-storm soil moisture conditions in a hydrologic
model, and consequently, its simulation of runoff response to subsequent
rainfall. However, recent work has demonstrated that soil moisture
retrievals can also be used to filter errors present in satellite-based
rainfall accumulation products. This result implies that soil moisture
retrievals have potential benefit for characterizing both antecedent
moisture conditions (required to estimate sub-surface flow intensities and
subsequent surface runoff efficiencies) and storm-scale rainfall totals
(required to estimate the total surface runoff volume). In response, this
work presents a new sequential data assimilation system that exploits
remotely-sensed surface soil moisture retrievals to simultaneously improve
estimates of both pre-storm soil moisture conditions and storm-scale rainfall
accumulations. Preliminary testing of the system, via a synthetic twin data
assimilation experiment based on the Sacramento hydrologic model and data
collected from the Model Parameterization Experiment, suggests that the new
approach is more efficient at improving stream flow predictions than data
assimilation techniques focusing solely on the constraint of antecedent soil
moisture conditions. |
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