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| Titel |
Assimilation of satellite data to optimize large-scale hydrological model parameters: a case study for the SWOT mission |
| VerfasserIn |
V. Pedinotti, A. Boone, S. Ricci, S. Biancamaria, N. Mognard |
| 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 ; 18, no. 11 ; Nr. 18, no. 11 (2014-11-10), S.4485-4507 |
| Datensatznummer |
250120524
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| Publikation (Nr.) |
 copernicus.org/hess-18-4485-2014.pdf |
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| Zusammenfassung |
| During the last few decades, satellite measurements have been widely used to
study the continental water cycle, especially in regions where in situ
measurements are not readily available. The future Surface Water and Ocean
Topography (SWOT) satellite mission will deliver maps of water surface
elevation (WSE) with an unprecedented resolution and provide observation of
rivers wider than 100 m and water surface areas greater than approximately
250 x 250 m over continental surfaces between 78° S and 78° N. This study aims
to investigate the potential of SWOT data for parameter optimization for
large-scale river routing models. The method consists in applying a data
assimilation approach, the extended Kalman filter (EKF) algorithm, to correct
the Manning roughness coefficients of the ISBA (Interactions between Soil,
Biosphere, and Atmosphere)-TRIP (Total Runoff Integrating Pathways) continental hydrologic
system. Parameters such as the Manning coefficient, used within such models
to describe water basin characteristics, are generally derived from
geomorphological relationships, which leads to significant errors at reach
and large scales. The current study focuses on the Niger Basin, a
transboundary river. Since the SWOT observations are not available yet and
also to assess the proposed assimilation method, the study is carried out
under the framework of an observing system simulation experiment (OSSE). It
is assumed that modeling errors are only due to uncertainties in the Manning
coefficient. The true Manning coefficients are then supposed to be known and
are used to generate synthetic SWOT observations over the period 2002–2003.
The impact of the assimilation system on the Niger Basin hydrological cycle
is then quantified. The optimization of the Manning coefficient using the EKF
(extended Kalman filter) algorithm over an 18-month period led to a significant improvement of the
river water levels. The relative bias of the water level is globally improved
(a 30% reduction). The relative bias of the Manning coefficient is also
reduced (40% reduction) and it converges towards an optimal value.
Discharge is also improved by the assimilation, but to a lesser extent than
for the water levels (7%). Moreover, the method allows for a better simulation
of the occurrence and intensity of flood events in the inner delta and shows
skill in simulating the maxima and minima of water storage anomalies,
especially in the groundwater and the aquifer reservoirs. The application of
the assimilation method in the framework of an observing system simulation
experiment allows evaluating the skill of the EKF algorithm to improve
hydrological model parameters and to demonstrate SWOT's promising potential for
global hydrology issues. However, further studies (e.g., considering multiple
error sources and the difference between synthetic and real observations) are
needed to achieve the evaluation of the method. |
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