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This work presents the approach used to estimate coastal flood impact, developed within the EU H2020 European Coastal Flood Awareness System (ECFAS) Project, for assessing flood direct impacts on population, buildings, and roads along the European coasts. The methodology integrates object-based and probabilistic evaluations to provide uncertainty estimates for damage assessment. The approach underwent a user-driven co-evaluation process, it was applied to 16 test cases across Europe and validated against reported impact data in three major reference cases: Xynthia at La Faute-sur-Mer (France) in 2010, Xaver at Norfolk (UK) in 2013, and Emma at Cadiz (Spain) in 2018. A comparison with grid-based damage evaluation methods was also conducted. The findings demonstrate that the ECFAS Impact approach offers valuable estimates for affected populations, reliable damage assessments for buildings and roads, and improved accuracy compared to traditional grid-based approaches. The methodology also provides information for prevention and preparedness activities, facilitates further evaluations of risk scenarios and cost-benefit analysis of disaster risk reduction strategies. The approach is a tool suitable for large-scale coastal flood impact assessments, offering improved accuracy and operational capability for coastal flood forecasts. It represents a potential advancement of the existing EU-scale impact method used by the European Flood Awareness System (EFAS) for riverine flood warnings. The integration of object-based and probabilistic evaluations, along with uncertainty estimation, enhances the understanding and management of flood impacts along the European coasts. [ABSTRACT FROM AUTHOR]

Coastal communities and assets are exposed to flooding and erosion hazards due to extreme storm events, which may increase in intensity due to climatological factors in the incoming future. Coastal managers are tasked with developing risk-management plans mitigating risk during all phases of the disaster cycle. This necessitates rapid, time-efficient post-event beach surveys that collect physical data in the immediate aftermath of an event. Additionally, the inclusion of local stakeholders in the assessment process via personal interviews captures the social dimension of the impact of the event. In this study, a local protocol for post-event assessment, the quick-response protocol, was tested on a pilot site on the Emilia–Romagna (Italy) coast in the aftermath of an extreme meteorological event that occurred in February 2015. Physical data were collected using both real-time kinematic Geographical Positions Systems and unmanned aerial vehicle platforms. Local stakeholders were interviewed by collecting qualitative information on their experiences before, during, and after the event. Data comparisons between local and regional surveys of this event highlighted higher data resolution and accuracy at the local level, enabling improved risk assessment for future events of this magnitude. The local survey methodology, although improvable from different technical aspects, can be readily integrated into regional surveys for improved data resolution and accuracy of storm impact assessments on the regional scale to better inform coastal risk managers during mitigation planning. [ABSTRACT FROM AUTHOR]

The Italian coasts are threatened by coastal flooding and erosion. The Emilia-Romagna region coastline is exposed to marine storms because of its low-lying nature and massive urbanization. Regional managers need comprehensive tools for coastal storm risk assessment. The RISC-KIT Coastal Risk Assessment Framework (CRAF) provides a conceptual framework, which includes hazard, exposure and vulnerability evaluation, to implement a screening process able to identify littoral zones that can be classified as hotspots (Phase 1) and to successively rank the identified hotspots to select the most critical ones (Phase 2). This study includes the results of the implementation of CRAF Phase 1 in the Emilia-Romagna coast. The method is based on a Coastal Index approach, calculated for 1 km length coastal sectors, applied taking into account both hazard and exposure indicators. The general methodology was partly modified thanks to the strong collaboration with the End-User (Servizio Geologico Sismico e dei Suoli, SGSS) which provided data, suggestions and comments at every step of the implementation. The SGSS also provided data to validate the outcomes of the CRAF methodology. Thus, the critical areas identified by the CRAF were compared with historical (1946–2010) storm impacts, resulting in a reasonable agreement between the identified hotspots. [ABSTRACT FROM AUTHOR]

Coastal flooding estimation at large scale, e.g. pan-European is usually performed using static method while dynamic method, in which numerical flood models are used to solve hydrodynamic equations, have proven to perform better. However, a numerical flood model can rapidly become computationally demanding. Thus, to respect the balance between efficiency and quality, models need to be properly configured. Usually, the model configuration is supported by calibration and validation. In the cases where it is not possible to appropriately implement calibration and validation through comparison against observed and measured data, sensitivity analyses can be applied in order to identify the key parameters that could influence the model capability to properly represent the modelled process. The present work aimed to identify influential model parameters across Europe and their relative importance in flood model configuration. Seventeen test cases were selected for which a LISFLOOD-FP model was developed, covering several sites across Europe and considering different storm events. A panoply of local morphologies and boundary conditions derived from the sites and storm event characteristics were used. For each test case, 72 simulations with different configurations were performed by varying the grid resolution, the numerical solver, the bottom friction and the wave set-up formulation used to estimate the total water level as a boundary condition. Two sensitivity analyses were performed on the modelled maximum flooded areas and water volumes using One-Driver-At-a-Time and variance-based methods. By using a k-means clustering method, the results of these sensitivity analyses allowed us to identify patterns through the test cases related to the geographical region, providing important information for the configuration of flood models across Europe. Both sensitivity analysis methods led to similar results highlighting dominant relative influences from the floodplain solver on the Atlantic coasts and from the boundary conditions on the Mediterranean ones. In addition the grid resolution was found to have great effect on the North and Baltic seas, while globally the friction was shown to impact the model's results less. The test cases were clustered using a k-means method using as input both the sensitivity analysis results and morphological factors. Depending upon the inputs, two different sets of clusters were generated revealing a complex relationship between the influence of the model's parameters and the selected morphological indicators. • 17 test cases of coastal flooding in Europe were simulated using LISFLOOD-FP model. • One-Driver-At-a-Time and variance based sensitivity analyses identified key parameter. • Significant influence of the floodplain solver, wave set-up and grid resolution. • Result models were relatively not sensitive to the friction configuration. [ABSTRACT FROM AUTHOR]