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| Titel |
Hydrological real-time modelling in the Zambezi river basin using satellite-based soil moisture and rainfall data |
| VerfasserIn |
P. Meier, A. Frömelt, W. Kinzelbach |
| 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 ; 15, no. 3 ; Nr. 15, no. 3 (2011-03-23), S.999-1008 |
| Datensatznummer |
250012696
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| Publikation (Nr.) |
 copernicus.org/hess-15-999-2011.pdf |
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| Zusammenfassung |
| Reliable real-time forecasts of the discharge can provide valuable
information for the management of a river basin system. For the
management of ecological releases even discharge forecasts with
moderate accuracy can be beneficial. Sequential data assimilation
using the Ensemble Kalman Filter provides a tool that is both
efficient and robust for a real-time modelling framework. One key
parameter in a hydrological system is the soil moisture, which
recently can be characterized by satellite based measurements. A
forecasting framework
for the prediction of discharges is developed and applied to three
different sub-basins of the Zambezi River Basin. The model is solely
based on remote sensing data providing soil moisture and rainfall
estimates. The soil moisture product used is based on the
back-scattering intensity of a radar signal measured by a radar
scatterometer. These soil moisture data correlate well with the
measured discharge of the corresponding watershed if the data are
shifted by a time lag which is dependent on the size and the dominant
runoff process in the catchment. This time lag is the basis for the
applicability of the soil moisture data for hydrological
forecasts. The conceptual model developed is based on two storage
compartments. The processes modeled include evaporation losses,
infiltration and percolation. The application of this model in a
real-time modelling framework yields good results in watersheds where
soil storage is an important factor. The lead time of the forecast
is dependent on the size and the retention capacity of the
watershed. For the largest watershed a
forecast over 40 days can be provided. However, the quality
of the forecast increases significantly with decreasing prediction
time. In a watershed with little soil storage and a quick response to
rainfall events, the performance is relatively poor and the lead time
is as short as 10 days only. |
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