Flood Evacuation Models in Urban Areas: Towards a Digital Twin Framework for Emergency Management

Urban areas face increasing risks from flooding events due to the combined effects of climate change, increase in the frequency and intensity of extreme precipitation events, rapid urbanization, and aging infrastructures. In this context, mitigation strategies have a key role in reducing the impact and increasing resiliency. Over the last decades, several strategies have been developed to reduce loss of lives and economic damages and, among those, the Evacuation Plans (EPs) aim at mitigating water-related risks in numerous case studies worldwide. Traditional methods and plans are usually based on static-data without integration with real-time data, hence lacking the adaptability and stakeholder-specific focus required for effective response. To address these limitations and leverage the increasing engagement of Building and City Information Modelling, Internet of Things (IoT) and Semantic Web technologies, this paper proposes a Digital Twin (DT) framework to manage flood evacuation in urban areas based on an in-depth study of the usable datasets, modelling, and management techniques to reach the goal. The first phase involves creating a comprehensive digital representation of the physical urban environment which includes gathering and integrating heterogeneous data to capture the context of the system. The second phase focuses on the proposal of the Digital Twin system framework that addresses (a) Dynamic Data Acquisition and Integration, (b) Flood Modeling and Simulation, (c) Visualization and Decision Support. In the last phase, the pivotal role of the stakeholder engagement with the proposed DT framework is specified. By focusing on the aforementioned aspects, the proposed framework paves the way for the development of a DT system for efficient and effective emergency management in real-world scenarios.