Flood modeling by numerical solution of the two-dimensional (2D) shallow-water equations is ordinary practice. HEC-RAS 2D was recently released along with a suite of test cases showing the very good performance of the code in many practical situations. However, validation test cases aimed at demonstrating the capability of the software to deal with dam-break floods on very steep and irregular bathymetries are very limited. This paper tests HEC-RAS 2D against the discharge hydrographs measured in a historical physical model built in Froude similitude to analyze the consequences of the hypothetical collapse of the Cancano I dam (northern Italy) and the propagation of the resulting dam-break wave along the 15-km reach of the downstream alpine valley. The experimental hydrographs and the measured extent of the flooded areas are well reproduced by the numerical simulations. Moreover, the results obtained with HEC-RAS 2D are in very good agreement with those obtained using TELEMAC 2D, which confirms the suitability of the HEC-RAS 2D software for dam-break flood studies in steep alpine valleys. The data of the test case are made available to the scientific community for validation purposes.

The objective of this study is to investigate the “inversion approach” for flood defense optimization in an inundated area. This new methodology within this engineering field consists in defining a “safety criterion” (for instance, “the water level in a given location must be lower than a given value”) and the combined analysis of all the uncertain controlled parameters (i.e., flood defense geometry, location, etc.) that ensure the safety objective for all the possible combinations of uncontrolled parameters (i.e., the flow hydrograph parameters) representing the natural phenomenon is not exceeded. To estimate this safety set, a metamodeling approach will be used which significantly reduces the number of model evaluations required. This algorithm relies on a kriging surrogate built from a few model evaluations, sequentially enriched with new numerical model evaluations as long as the remaining uncertainty of the entire safety set remains too high. Also known as “Stepwise Uncertainty Reduction,” this algorithm is embedded in the “Funz” engine (https://github.com/Funz) tasked with bridging the numerical model and any design of experiments algorithm. We applied this algorithm to a real two-dimensional numerical model of the Garonne river (France), constructed using the open-source TELEMAC-2D model. We focused our attention mainly on the maximum water depth in a given area (the “safety criterion”) when considering the influence of a simplified flood defense during a flooding event. We consider the two safety control parameters describing the slab and dyke elevations of the flood defense system, to design against the full operating range of the river in terms of possible watershed flooding. For this application case, it appears that less than 200 simulations are needed to properly evaluate the restricted zone of the design parameters (the “safety zone”) where the safety criterion is always met. This provides highly valuable data for full risk-informed management of the area requiring protection.

Selecting appropriate performance measures is crucial for calibrating numerical flood models with satellite images, as differences between performance measures can significantly impact model predictions. The present study reports a step‐by‐step methodology to guide the selection of performance measures to compare numerical simulations of a flood event with a satellite image, for purposes of model calibration or validation. Faced with a set of performance measures, practitioners need to assess which are most suitable for comparing observed and simulated flood maps. First, a correlation analysis was conducted to determine the relationships between various performance measures. A series of criteria were then applied to evaluate the sensitivity of the performance measures with respect to flood extent, satellite characteristics (position and orientation), and errors in measurement or processing (raw satellite values or extraction of flood maps). The performance measures meeting the most criteria were then ranked based on the identifiability of parameter values with regard to observation errors. The methodology is discussed numerically in the context of a single flood event (on the Garonne River in France in February 2021), using a distribution of water depths simulated from a shallow‐water model (parameterized by an uncertain friction field). The methodology was shown to be useful in the study case in identifying 4 performance measures out of 24. The proposed methodology is intended to be generic, and therefore, applicable to any flood model or flood event.

This paper illustrates how an emulator (or meta-model) of a tsunami code can be a useful tool to evaluate or qualify tsunami hazard levels associated with both specific and unknown tsunamigenic seismic sources. The meta-models are statistical tools permitting to drastically reduce the computational time necessary for tsunami simulations. As a consequence they can be used to explore the tsunamigenic potential of a seismic zone, by taking into account an extended set of tsunami scenarios. We illustrate these concepts by studying the tsunamis generated by the Azores-Gibraltar Plate Boundary (AGPB) and potentially impacting the French Atlantic Coast. We first analyze the impact of two realistic scenarios corresponding to potential sources of the 1755-Lisbon tsunami (when uncertainty on seismic parameters is considered). We then show how meta-models could permit to qualify the tsunamis generated by this seismic area. All the results are finally discussed in light of tsunami hazard issued by the TSUMAPS-NEAM research project available online (http://ai2lab.org/tsumapsneam/interactive-hazard-curve-tool/). From this methodological study, it appears that tsunami hazard issued by TSUMAPS-NEAM research project is envelop, even when compared to all the likely and unlikely tsunami scenarios generated in the AGPB area.