Title: The use of H-SAF soil moisture products for operational hydrology: flood modelling over Italy
Language: English
Authors: Massari, Christian 
Brocca, Luca 
Ciabatta, Luca 
Moramarco, Tommaso 
Gabellani, Simone 
Albergel, Clement 
De Rosnay, Patricia 
Puca, Silvia 
Wagner, Wolfgang 
Category: Research Article
Issue Date: 2015
Journal: Hydrology
ISSN: 2306-5338
The ever-increasing availability of new remote sensing and land surface model datasets opens new opportunities for hydrologists to improve flood forecasting systems. The current study investigates the performance of two operational soil moisture (SM) products provided by the “EUMETSATSatellite Application Facility in Support of Operational Hydrology and Water Management” (H-SAF, http://hsaf.meteoam.it/) within a recently-developed hydrological model called the “simplified continuous rainfall-runoff model” (SCRRM) and the possibility of using such a model at an operational level. The model uses SM datasets derived from external sources (i.e., remote sensing and land surface models) as input for calculating the initial wetness conditions of the catchment prior to the flood event. Hydro-meteorological data from 35 Italian catchments ranging from 800 to 7400 km2 were used for the analysis for a total of 593 flood events. The results show that H-SAF operational products used within SCRRM satisfactorily reproduce the selected flood events, providing a median Nash–Sutcliffe efficiency index equal to 0.64 (SM-OBS-1) and 0.60 (SM-DAS-2), respectively. Given the results obtained along with the parsimony, the simplicity and independence of the model from continuously-recorded rainfall and evapotranspiration data, the study suggests that: (i) SM-OBS-1 and SM-DAS-2 contain useful information for flood modelling, which can be exploited in flood forecasting; and (ii) SCRRM is expected to be beneficial as a component of real-time flood forecasting systems in regions characterized by low data availability, where a continuous modelling approach can be problematic.
Keywords: soil moisture; floods; remote sensing; hydrological modelling
DOI: 10.3390/hydrology2010002
Library ID: AC11360593
URN: urn:nbn:at:at-ubtuw:3-2156
Organisation: E120 - Department für Geodäsie und Geoinformation 
Publication Type: Article
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