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| Titel |
Using globally available soil moisture indicators for flood modelling in Mediterranean catchments |
| VerfasserIn |
C. Massari, L. Brocca, S. Barbetta, C. Papathanasiou, M. Mimikou, T. Moramarco |
| 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. 2 ; Nr. 18, no. 2 (2014-02-28), S.839-853 |
| Datensatznummer |
250120294
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| Publikation (Nr.) |
 copernicus.org/hess-18-839-2014.pdf |
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| Zusammenfassung |
Floods are one of the most dangerous natural hazards in Mediterranean
regions. Flood forecasting tools and early warning systems can be very
beneficial to reducing flood risk. Event-based rainfall–runoff models are
frequently employed for operational flood forecasting purposes because of
their simplicity and the reduced number of parameters involved with respect
to continuous models. However, the advantages related to the reduced
parameterization oppose to the need of a correct initialization of the
model, especially in areas characterized by strong climate seasonality. In
this case, the use of continuous models could be desirable but it is very
problematic in poorly gauged areas where continuous rainfall and temperature
data are not available. This paper introduces a Simplified Continuous
Rainfall–Runoff model (SCRRM), which uses globally available soil moisture
retrievals to identify the initial wetness condition of the catchment, and,
only event rainfall data to simulate discharge hydrographs. The model
calibration involves only three parameters. For soil moisture, besides in situ data,
satellite products from the Advanced SCATterometer (ASCAT) and the Advanced
Microwave Scanning Radiometer for Earth observation (AMSR-E) sensors were
employed. Additionally, the ERA-Land reanalysis soil moisture product of the
European Centre for Medium-Range Weather Forecasting (ECMWF) was used.
SCRRM was tested in the small catchment of the Rafina River, 109 km2,
located in the eastern Attica region, Greece. Specifically, sixteen recorded
rainfall–runoff events were simulated by considering the different
indicators for the estimation of the initial soil moisture conditions from in
situ, satellite and reanalysis data. By comparing the performance of the
different soil moisture products, we conclude that: (i) all global indicators
allow for a fairly good reproduction of the selected flood events, providing
much better results than those obtained from setting constant initial
conditions; (ii) the use of all the indicators yields similar results when
compared with a standard continuous simulation approach that, however, is
more data demanding; (iii) SCRRM is robust since it shows good performances
in validation for a significant flood event that occurred on February 2013
(after calibrating the model for small to medium flood events). Due to the
wide diffusion of globally available soil moisture retrievals and the limited
number of parameters used, the proposed modelling approach is very suitable
for runoff prediction in poorly gauged areas. |
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