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.

Mapping the delineation of areas that are flooded due to water control infrastructure failure is a critical issue. Practical difficulties often present challenges to the accurate and effective analysis of dam-break hazard areas. Such studies are expensive, lengthy, and require large volumes of incoming data and refined technical skills. The creation of cost-efficient geospatial tools provides rapid and inexpensive estimates of instantaneous dam-break (due to structural failure) flooded areas that complement, but do not replace, the results of hydrodynamic simulations. The current study implements a Geographic Information System (GIS) based method that can provide useful information regarding the delineation of dam-break flood-prone areas in both data-scarce environments and transboundary regions, in the absence of detailed studies. Moreover, the proposed tool enables, without advanced technical skills, the analysis of a wide number of case studies that support the prioritization of interventions, or, in emergency situations, the simulation of numerous initial hypotheses (e.g., the modification of initial water level/volume in the case of limited dam functionality), without incurring high computational time. The proposed model is based on the commonly available data for masonry dams, i.e., dam geometry (e.g., reservoir capacity, dam height, and crest length), and a Digital Elevation Model. The model allows for rapid and cost-effective dam-break hazard mapping by evaluating three components: (i) the dam-failure discharge hydrograph, (ii) the propagation of the flood, and (iii) the delineation of flood-prone areas. The tool exhibited high accuracy and reliability in the identification of hypothetical dam-break flood-prone areas when compared to the results of traditional hydrodynamic approaches, as applied to a dam in Basilicata (Southern Italy). In particular, the over- and under-estimation rates of the proposed tool, for the San Giuliano dam, Basilicata, were evaluated by comparing its outputs with flood inundation maps that were obtained by two traditional methods whil using a one-dimensional and a two-dimensional propagation model, resulting in a specificity value of roughly 90%. These results confirm that most parts of the flood map were correctly classified as flooded by the proposed GIS model. A sensitivity value of over 75% confirms that several zones were also correctly identified as non-flooded. Moreover, the overall effectiveness and reliability of the proposed model were evaluated, for the Gleno Dam (located in the Central Italian Alps), by comparing the results of literature studies concerning the application of monodimensional numerical models and the extent of the flooded area reconstructed by the available historical information, obtaining an accuracy of around 94%. Finally, the computational efficiency of the proposed tool was tested on a demonstrative application of 250 Italian arch and gravity dams. The results, when carried out using a PC, Pentium Intel Core i5 Processor CPU 3.2 GHz, 8 GB RAM, required about 73 min, showing the potential of such a tool applied to dam-break flood mapping for a large number of dams.

This paper is intended to highlight the need to use data at high spatial resolution, such as those obtained through the use of Airborne Laser Scanning (ALS) techniques, to support hydraulic models for the assessment of flood hazards in urban territory. In fact, the significant structural features (houses, walls, roads, etc.) in the city are important in relation to both the volume of the floodplain that can be occupied by the flow and the direction that the flow takes across the floodplain. ALS data can range up to several terabytes in size and is a function of the geographic scale of the mission. Also, this data is typically irregular with uneven point density. Therefore, a quick method is described to ride out the difficulties to handle the large datasets with uneven point densities and to improve the extracting of feature information for further use in Geographic Information System (GIS) analysis. Finally, a comparison is made between the maximum inundated area obtained from ALS data and that one calculated using a traditional topographic map. The results show that the high-resolution data obtained from airborne remote sensing can increase the opportunities for representation of small-scale structural elements in complex systems using two-dimensional models of flood inundation.