Small-catchment flood forecasting and drainage network extraction using computational intelligence

— Forecast, detection and warning of severe weather and related hydro-geological risks is becoming one of the major issues for civil protection. The use of computational intelligence techniques such as artificial neural network and cellular automata algorithm can be suitable for such problems especially for real time forecasting system. Nowcasting (short-term forecasting) of extreme rainfall events is an example that invites to exploit remote sensing systems from satellites, such geostationary and low-orbit radiometers. A rainfall estimation algorithm based on artificial neural network has been developed for this purpose. Satellite data sources can be globally provided but at a quite coarse spatial resolution, therefore, the coupling of rain remote sensing data with regional raingauge networks is also essential for ensuring a calibration of remotely sensed rainfall fields in terms of ground effects. An overwhelming issue is the spatial integration of these rainfall data sources havin...

• Type: Conference
• Year: 2006
• Where: IJCNN
• Authors: Erika Coppola, Barbara Tomassetti, Marco Verdecchia, Frank S. Marzano, Guido Visconti
• Keywords: Artificial Neural Network, IJCNN 2006, Remote Sensing, Remote Sensing Data