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| Titel |
Calibration and sequential updating of a coupled hydrologic-hydraulic model using remote sensing-derived water stages |
| VerfasserIn |
M. Montanari, R. Hostache, P. Matgen, G. Schumann, L. Pfister, L. Hoffmann |
| 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. 3 ; Nr. 13, no. 3 (2009-03-18), S.367-380 |
| Datensatznummer |
250011801
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| Publikation (Nr.) |
 copernicus.org/hess-13-367-2009.pdf |
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| Zusammenfassung |
| Two of the most relevant components of any flood forecasting system, namely
the rainfall-runoff and flood inundation models, increasingly benefit from
the availability of spatially distributed Earth Observation data. With the
advent of microwave remote sensing instruments and their all weather
capabilities, new opportunities have emerged over the past decade for
improved hydrologic and hydraulic model calibration and validation. However,
the usefulness of remote sensing observations in coupled hydrologic and
hydraulic models still requires further investigations. Radar remote sensing
observations are readily available to provide information on flood extent.
Moreover, the fusion of radar imagery and high precision digital elevation
models allows estimating distributed water levels. With a view to further
explore the potential offered by SAR images, this paper investigates the
usefulness of remote sensing-derived water stages in a modelling sequence
where the outputs of hydrologic models (rainfall-runoff models) serve as
boundary condition of flood inundation models. The methodology consists in
coupling a simplistic 3-parameter conceptual rainfall-runoff model with a
1-D flood inundation model. Remote sensing observations of flooded areas
help to identify and subsequently correct apparent volume errors in the
modelling chain. The updating of the soil moisture module of the
hydrologic model is based on the comparison of water levels computed by
the coupled hydrologic-hydraulic model with those estimated using remotely
sensed flood extent. The potential of the proposed methodology
is illustrated with data collected during a storm event on the Alzette River
(Grand-Duchy of Luxembourg). The study contributes to assess the
value of remote sensing data for evaluating the saturation status of a river
basin. |
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