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The statistical characterization of extreme floods largely benefits from the reconstruction of historical floods, making use of various documentary sources and of hydrodynamic models. The two-dimensional (2D) modelling approach provides a higher accuracy and detail with respect to one-dimensional (1D) modelling. On the other hand, 2D models require a large amount of topographic and hydraulic information for calibration, having several parameters to be determined, which makes the calibration prone to underdetermination. To address this issue, we provide here practical guidance for the effective calibration of 2D models for the reconstruction of historical floods in urban areas with a limited amount of information available. Specifically, we show how to constrain model parameters by distinguishing among "static," "dynamic" and "global" data and their role in the calibration procedure. The latter is exemplified by a relevant application to the reconstruction of the great 1870 flood of Rome, Italy. [ABSTRACT FROM AUTHOR]

Coastal regions below the sea level, subject to reclamation, are becoming more and more exposed to flooding following increasing urbanization and hydrological changes. In these areas, groundwater and water table dynamics during intense rainfall events can be an important component of flooding and inundation, leading to groundwater flooding. Thus, the commonly employed hydrological models based on only the surface component of flow may result in a poor estimation of the extension and persistence of inundation events. We introduce here a simple and parsimonious approach for handling the groundwater contribution to flooding in such areas, which can be easily implemented and introduced into surface hydraulic models for flood management and the delineation of inundation maps. The approach involves few relevant parameters, requiring a minimum of information regarding the hydrogeological setup. The method is exemplified through the flood analysis of a wide reclamation area located in the southern part of Rome, Italy. The introduction of the groundwater component could explain the large water volumes pumped by the stations, which are much larger than excess rainfall. The application confirmed the validity of the proposed approach, emphasizing the important role played by groundwater to flooding in areas similar to the one considered here. [ABSTRACT FROM AUTHOR]

The presence of flood control structures, such as levees, often reduces the perception of risk by the population, triggering the development of human settlements in floodplain areas. This circumstance, often denoted as levee effect, exposes the population to a residual risk, for instance when a breach occurs in the levee during a significant flood; the quantification of such risk is often difficult and prone to uncertainty. Starting from the definition proposed by Varnes, where the risk R is defined by the product of the hazard H, the elements at risk E and their vulnerability V, we develop a risk-based framework in order to define the above residual risk. The framework builds over the risk pertaining to two scenarios: (i) before, and (ii) after the building of control structures; it is made up of three main components: (i) a structural term, linked to the probabilistic nature of the phenomenon, (ii) a dynamic term, which expresses the hydraulic component of risk, and (iii) an anthropic term, that represents the change of the elements at risk before and after the flood control measures. The framework is exemplified through an application to the Arrone river near Rome (Italy) for the analysis of the residual risk after the formation of a breach for piping in the levee. We performed extensive numerical simulations of flood propagation, modelling the occurrence of random breaches in the river reach of interest, along a Monte Carlo approach. The dynamic and the characteristics of the breach caused by piping was studied considering empirical analyses based on regression equations. Results are presented in terms of frequencies of significant quantities, comparing risk for the two scenarios of reference. The application example shows that the proposed risk analysis can be a relatively simple and valuable tool for analyzing the residual risk, along a rational and sound framework. [ABSTRACT FROM AUTHOR]