气候变化领域集成服务门户

Managing coastal flood risk at the regional scale requires a prioritization of economic resources along the shoreline. Advanced modeling assessment and open-source tools are now available to support transparent and rigorous risk evaluation and to inform managers and stakeholders in their choices. However, the issues lay in data availability and data richness to estimate coastal vulnerability and impacts. The Coastal Risk Assessment Framework (CRAF) has been developed as part of the Resilience Increasing Strategies for Coasts - Toolkit (RISC-KIT) EU FP7 project. The framework provides two levels of analysis. In the first phase, a coastal index approach is applied to identify a restricted number of potential critical areas for different hazards (i.e., erosion and flooding). In the second phase, an integrated hazard and impact modeling approach is applied in the critical areas to assess the direct and indirect impacts of storm events using a matrix-based approach and a systemic analysis. The framework was tested on the coastline of the Emilia-Romagna region (northern Italy) for two probabilistic coastal storms with representative return periods of 10 and 100 years. In this work, the application of the second phase of the CRAF is presented for two sites, Lido degli Estensi-Spina (Ferrara province) and Milano Marittima (Ravenna province). The hazard modeling of floods was implemented using a coupling between XBeach and Lisflood-FP. The Integrated Disruption Assessment (INDRA) model was applied to quantify direct and indirect impacts. The impact assessment focused on household's financial recovery, business disruption and financial recovery, transport network disruption and risk to life. The considered business sector comprised the key economic activities related to the sun-and-beach tourism, which is one of the main drivers of the regional economy. A Multi-Criteria Analysis was applied to support decision-makers to identify the most critical site. The importance of detailed physical and socio-economic data collected at the regional and local levels is highlighted and discussed, together with the importance to involve different stakeholders in the process (e.g., through interviews and surveys). The limitations of the applied approach due to data quality and availability and to the assumptions introduced in the hazard and disruption models are highlighted.