# Multitemporal SAR Data and 2D Hydrodynamic Model Flood Scenario Dynamics Assessment
## 5 Conclusions
A general consistency between SAR-derived and model-predicted flood extension was found and proved the reliability of the methods that were used to perform the flood hazard assessment. Moreover, the results of the model calibration, in terms of water depth estimation highlight that a tight sequence of SAR images could improve model predictions. Combining observations in this way appears to focus the location of the roughness parameter more clearly than is possible using single images. Results for different sets of Manning coefficient values have also shown that successful water- depth calibration could only be obtained when channel roughness values were confined to a plausible range. Lastly, the selected sets of Manning coefficient values were used in the hydraulic model to formulate predictions for the 2-3 December 2013 Bradano River flood event. The results of the validation process proved the robustness of the model under different operating conditions. In particular, using variable spatio-temporal Manning coefficient values, the model successfully simulated the dynamics of the two considered flood events, in terms of flood extent and water depth, thanks to the use of SAR-derived time-series flood maps for calibration and validation purposes. The combination of information from the hydrodynamic model and the CSK observation time series provided reliable information about the evolution of the scenario, and thus shows great potential for implementation in an operating system for near-real-time flood forecasting and monitoring. Further development of an operating system for inundation dynamics prediction depends on access to high-accuracy synoptic images at multiple points during an event. For example, during the emergency, the most urgent demands of civil protection operators were to have indications on the timing of the flood recession stage, which indicates, for instance, which areas will be accessible first and which roads should be restored in a short time. Furthermore, the areas in which the model indicates water stagnation should be those where recession has to be accelerated artificially through pumping [14]. Last, but not least, it must be noted that future work should concern automation levels for proposed processes and the assimilation of SAR- and DEM-derived flood information into hydraulic models to operationalize forecasting or near-real-time monitoring of flood dynamics. Other limitation sources for rendering operational the proposed methodological framework might involve the availability of high spatio-temporal resolution CSK images for a specific event or in a different phase of an event (pre-peak, during the peak or in the recession stage), and, in a defined area, when considering potential SAR strip limitations. The authors gratefully acknowledge ASI (Italian Space Agency) for providing the SAR images used in this study under the terms of the cooperation agreement within the scope of the University of Basilicata's PhD School for Engineering for Innovation and Sustainable Development. Moreover, the work of the RSE author has been financed by the Research Fund for the Italian Electrical System under the Contract Agreement between RSE S.p.A. and the Ministry of Economic Development--General Directorate for Nuclear Energy, Renewable Energy and Energy Efficiency in compliance with the Decree of 8 March 2006. All authors have contributed equally to this work. The authors declare no conflict of interest.