The increasing number of floods and the severity of their consequences, which is caused by phenomena, such as climate change and uncontrolled urbanization, create a growing need to develop operational procedures and tools for accurate and timely flood mapping and management. Synthetic Aperture Radar (SAR), with its day, night, and cloud-penetrating capacity, has proven to be a very useful source of information during calibration of hydrodynamic models considered indispensable tools for near real-time flood forecasting and monitoring. The paper begins with the analysis of radar signatures of temporal series of SAR data, by exploiting the short revisit time of the images that are provided by the Cosmo-SkyMed constellation of four satellites, in combination with a Digital Elevation Model for the extraction of flood extent and spatially distributed water depth in a flat area with complex topography during a flood event. These SAR-based hazard maps were then used to perform a bi-dimensional hydraulic model calibration on the November 2010 flood event at the mouth of the Bradano River in Basilicata, Italy. Once the best fit between flood predictions of hydrodynamic models was identified and the efficacy of SAR data in correcting hydrodynamic inconsistencies with regard to reliable assessment of flood extent and water-depth maps was shown by validation with the December 2013 Bradano River event. Based on calibration and validation results, the paper aims to show how the combination of the time series of Synthetic Aperture Radar (SAR) and Digital Elevation Model (DEM) derived water-depth maps with the data from the hydrodynamic model can provide valuable information for flood dynamics monitoring in a flat area with complex topography. Future research should focus on the integration and implementation of the semi-automatic proposed method in an operational system for near real-time flood management.
CITATION STYLE
Scarpino, S., Albano, R., Cantisani, A., Mancusi, L., Sole, A., & Milillo, G. (2018). Article multitemporal SAR data and 2D hydrodynamic model flood scenario dynamics assessment. ISPRS International Journal of Geo-Information, 7(3). https://doi.org/10.3390/ijgi7030105
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