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FLOODMAN Résumé de rapport

Project ID: EVG1-CT-2002-00085
Financé au titre de: FP5-EESD
Pays: Italy

Flood forecasting - Algorithms for estimating soil moisture content from SAR C-band acquisitions (ERS/ENVISAT)

The Soil Moisture Content (SMC), besides representing a water resource for plants, is a very important parameter of the hydrological cycle, since it is able to influence the runoff during precipitative events. In particular, the amount of water in the first 10 cm of soil, as boundary between the atmosphere and the land surface, is able to influence the mechanisms driving the runoff, the evapotranspiration, the surface heat fluxes and the biogeochemical cycles.

Therefore the moisture of the first layer of soil plays an important role in flood prediction as an initial condition of the watershed system and as a soil state variable that controls the evapotranspiration fluxes. SMC is an essential input variable required by the hydrological models. With the algorithm, which is based on most recent techniques of statistical approaches and the employ of Neural Networks, we expect to obtain in near real time the moisture values of the first centimetres layer from the SAR (ENVISAT or ERS) C-band acquisitions.

Respect to the traditional ground based techniques, this method allows observing large areas in a very short time and measures integrated values instead of several sparse samples. Algorithm will be tested on the images of the test sites selected for the project and can be used in other river-catchments for some extent.

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