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L. Brocca, F. Melone, T. Moramarco, W. Wagner, V. Naeimi, Z. Bartalis, S. Hasenauer:
"Potential Of Ascat Soil Moisture Product To Improve Runoff Prediction";
Talk: Earth Observation and Water Cycle Science Symposium, Frascati, Italy; 2009-11-18 - 2009-11-20; in: "ESA Special Publications SP-674", (2009), ISBN: 978-92-9221-238-4; 8 pages.

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 have to be carefully checked. Therefore, the
assessment of the effects of assimilating satellitederived
soil moisture estimates into rainfall-runoff
models at different scales and over different regions
represents an important scientific and operational issue.
In this context, the soil wetness index (SWI) product
derived from the Advanced Scatterometer (ASCAT)
sensor was tested in this study. The SWI was firstly
compared with the soil moisture temporal pattern
derived from a continuous rainfall-runoff model
(MISDc). Then, by using a simple data assimilation
technique, the 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 for 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 used to improve runoff
prediction in the study area, mainly if the initial soil
wetness conditions are unknown.