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| Titel |
Improving runoff prediction through the assimilation of the ASCAT soil moisture product |
| VerfasserIn |
L. Brocca, F. Melone, T. Moramarco, W. Wagner, V. Naeimi, Z. Bartalis, S. Hasenauer |
| 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 ; 14, no. 10 ; Nr. 14, no. 10 (2010-10-12), S.1881-1893 |
| Datensatznummer |
250012441
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| Publikation (Nr.) |
 copernicus.org/hess-14-1881-2010.pdf |
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| Zusammenfassung |
The role and the importance of soil moisture for meteorological,
agricultural and hydrological applications is widely known. Remote sensing
offers the unique capability to monitor soil moisture over large areas
(catchment scale) with, nowadays, a temporal resolution suitable for
hydrological purposes. However, the accuracy of the remotely sensed soil
moisture estimates has to be carefully checked. The validation of these
estimates with in-situ measurements is not straightforward due the
well-known problems related to the spatial mismatch and the measurement
accuracy. The analysis of the effects deriving from assimilating remotely
sensed soil moisture data into hydrological or meteorological models could
represent a more valuable method to test their reliability. In particular,
the assimilation of satellite-derived soil moisture estimates into
rainfall-runoff models at different scales and over different regions
represents an important scientific and operational issue.
In this study, the soil wetness index (SWI) product derived from the Advanced
SCATterometer (ASCAT) sensor onboard of the Metop satellite was tested. The
SWI was firstly compared with the soil moisture temporal pattern derived from a
continuous rainfall-runoff model (MISDc) to assess its relationship with
modeled data. Then, by using a simple data assimilation technique, the
linearly rescaled SWI that matches the range of variability of modelled data
(denoted as SWI*) was assimilated into MISDc and the model performance on flood
estimation was analyzed. Moreover, three synthetic experiments considering
errors on rainfall, model parameters and initial soil wetness conditions
were carried out. These experiments allowed to further investigate the SWI
potential when uncertain conditions take place. The most significant flood
events, which occurred in the period 2000–2009 on five subcatchments of the
Upper Tiber River in central Italy, ranging in extension between 100 and 650 km2,
were used as case studies. Results reveal that the SWI derived from
the ASCAT sensor can be conveniently adopted to improve runoff prediction in
the study area, mainly if the initial soil wetness conditions are unknown. |
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