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| Titel |
Assimilating ASCAT-derived soil moisture data into hydrological model for improved discharge forecast: a proof-of-concept study |
| VerfasserIn |
Davide Corrado, Giovanni Corato, Patrick Matgen, Pierluigi Claps |
| Konferenz |
EGU General Assembly 2013
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 15 (2013) |
| Datensatznummer |
250082641
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| Zusammenfassung |
| Data assimilation techniques can be of great support in hydrologic modelling, especially in the reduction of uncertainty and the improvement of discharge prediction in flood forecast activities. Using remotely sensed soil moisture indices, data assimilation can be used to correct the hydrological state and improve the performance of the model. In this context, we aim at testing the forecasting model and validating an assimilation procedure of remote sensing data derived by ASCAT (Advanced SCATterometer), into a hydrological SUPERFLEX model through synthetic experiments. A particle filter scheme is used for the data assimilation. The filter was modified adding a temporal decay function which allows take into account not only the remote sensing observation at the time of assimilation but also past records. In particular, the function allows make a weighting of past records ranked according to their proximity in time to the moment of assimilation.
This procedure was tested on the Alzette river basin (1100 km2), located in the south-west of the Grand Duchy of Luxembourg. The period analysed spans from 1 January 2006 to 31 December 2009. The results show an improvement in discharge forecasts. However, the assimilation efficiency depends on the period considered and on the weight assigned to the particles using the temporal function. In particular, the performance improves with increasing memory of the function. Greater efficiency was obtained during dry (summer) and transition (spring-autumn) periods than for wet periods (winter). |
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