In order to make accurate flood predictions it is necessary to be able to map surface water. Satellites allow large areas to be monitored with minimum acquisition time and can also cover remote areas, which are inaccessible from the ground. One limitation to the use of satellites is that the information from optical sensors is limited in bad weather condition such as heavy cloud cover or during floods. Since Synthetic Aperture Radars (SARs) can acquire data independently and in all weather conditions, SAR data are often considered the optimal system for such measurements. The method developed for mapping flood extent is texture based. In other words the detector monitors differences in the backscattered radar waves corresponding to the different scattering mechanisms of land and water. Generally, high incident radar angles are used to collect information since the contrast between land and water is greater with increased incidence angle. However, through the project it was discovered that an angle of 23° was comparable to the traditional 45°. It operates independently of user input, which is important since any aspect of human error is removed. The method is combined with in situ data from distributed hydrological and hydraulic models to provide a system for successful monitoring and management of water bodies. It has been found to work accurately for monitoring open surface water, although windy and icy conditions result in lower degrees of accuracy. It can accommodate changes in topography and vegetation. Further support is required to perfect its operation.
Near real-time flood forecasting, warning and management system based on satellite radar images, hydrological and hydraulic models and in-situ data
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28 January 2020