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The intensifying urban flood risks due to climate change necessitate innovative decision-support systems (DSS) for risk assessment and emergency management. The SaferPlaces cloud web platform emerges as a transformative DSS, utilizing AI-based algorithms and cloud computing power to enhance flood hazard preparedness in urban areas. By enabling users to conduct large-scale, high-speed simulations economically, SaferPlaces stands at the vanguard of urban resilience against flooding. At its core, SaferPlaces harnesses Digital Twin technology to create a virtual replica of urban environments, allowing for comprehensive pluvial, fluvial, and coastal flood risk assessment. This digital replication assists in formulating risk mitigation strategies, addressing challenges posed by present and future climate conditions. As an ex-ante tool, SaferPlaces integrates climate forecasts into urban planning, fostering scientifically grounded disaster risk reduction and detailed risk profiling. SaferPlaces distinguishes itself by amalgamating high spatial resolution topographic data, climate information from Copernicus CDS, hydrological data, and open-data platform resources. These inputs feed into advanced models and algorithms, producing high-fidelity hazard and damage estimates. Utilizing Amazon AWS Cloud's computing prowess, the platform generates real-time, cost-effective flood maps for historical and projected climate scenarios. The platform's user-friendly GUI empowers users to swiftly execute multiple flood hazard and damage scenarios, rendering high-resolution maps within minutes. These maps are readily downloadable, supporting an array of potential stakeholders in their operational tasks. Moreover, SaferPlaces offers specialized tools within its GUI to assist users in identifying, designing, and evaluating the effectiveness of various climate mitigation interventions. SaferPlaces' cross-sectoral appeal extends to municipal planners, disaster risk reduction professionals, public authorities, environmental and civil protection agencies, emergency organizations, water management entities, insurance sectors, and real estate industries. Real case application will be discussed in the study
Renzi et al. (Mon,) studied this question.
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