First results of an integrated flood forecast system based on remote sensing data

First results of an Integrated Flood Forecast System (IFFS) which is under development are presented. IFFS integrates multisensoral remote sensing data within an operational spatially distributed rainfall-runoff model for a better estimation of spatial input parameters with the aim to improve flood forecast. In this paper the setup and structure of IFFS is described with special focus on the potential of SAR data within the flood model. SAR data are used for the determination of topographic information (elevation, slopes, flow paths, etc.) and for soil moisture parameterisation. Optical data are used for the classification of the land cover, which also influences the runoff process. A first demonstration run of IFFS for the Ammer watershed (700 km(2)) in Southern Bavaria is presented to show the applicability of the system and the sensitivity of the model towards soil moisture information. It has been shown that ERS SAR data can successfully be used to initialise the soil moisture characterisation of the watershed in the flood forecast model. However, the application of the methodology is actually limited due to the poor temporal revisit time of ERS, which does not allow the observation of soil moisture changes with the requested temporal resolution.