Review on tsunami research and risk mitigation: from prediction models to resilient coastal communities

This study examines the evolution of tsunami early warning systems since the 2004 Indian Ocean tsunami, highlighting the growing complexity of tsunami hazards generated not only by earthquakes but also by volcanic eruptions, landslides, and other non-seismic sources. It explores how advances in real-time monitoring, modelling, and data integration have improved detection and response capacities, while also identifying persistent challenges in forecasting and communicating risk, especially in complex, multi-hazard environments.

The article finds that while significant progress has been made in tsunami detection and early warning capabilities, major gaps remain in accurately forecasting non-seismic tsunamis and ensuring timely communication to at-risk communities. It emphasizes the potential of emerging technologies, particularly artificial intelligence and enhanced sensor networks, to improve predictive accuracy and decision-making. The study concludes that strengthening integrated, multi-hazard early warning systems and improving coordination between scientific and operational communities are essential to reduce future tsunami risk and enhance coastal resilience.