Integrated Digital Twin Architecture for Water Contamination Emergency Management

During emergencies such as floods or earthquakes, first responders, water authorities, and public health experts must collaborate to manage water contamination risks. Decision-support tools, such as digital twins, are critical for real-time risk assessment and the evaluation of response measures within limited timeframes. Digital twins integrate real-time sensor data and dynamic models, along with algorithms for state estimation, to support risk assessment, anomaly detection, and event management. However, a holistic framework for water contamination emergency response is currently lacking. We introduce a novel, integrated digital twin reference architecture for risk-based water contamination emergency management, built on insights from various European research and innovation projects. This architecture integrates multiple water systems (surface, urban, sewerage), wastewater surveillance, public health and open data, portable sensors, emergency data spaces, simulation tools to forecast incident evolution, and time-bounded algorithms for event diagnosis, co-simulation, and risk assessment. A realistic use case is presented based on a large-scale field exercise.