Earthquakes remain among the most disruptive natural hazards worldwide, capable of causing sudden loss of life, severe economic damage, and long-lasting societal impacts. One of the most effective tools developed in recent decades to mitigate these effects is Earthquake Early Warning (EEW), a real-time monitoring strategy that exploits a fundamental physical property of earthquakes: seismic waves do not propagate instantaneously, and their speed is much slower than the light-speed at which the information travel through communication channels.
When an earthquake initiates, the first, low-amplitude signals to radiate are primary, or P waves, which travel rapidly through the Earth but generally cause little damage. They are followed by slower secondary (S) and surface waves, which carry most of the destructive energy. EEW systems are designed to detect the first, weak signals and to rapidly analyse their characteristics to forecast the expected ground shaking before it affects vulnerable targets [1, 2] (Figure 1). Even a few seconds of advance notice can be crucial, allowing automated or human responses that reduce risk, such as stopping trains, slowing industrial processes, or warning people to take self-protective actions (Figure 2).
Figure 1. EEWS principles. a) P-waves are quickly detected from one or more sensors and used to estimate the potential impact of ground shaking at target sites. b) Real-time estimates are used to alert sites before the arrival of the most damaging waves. (Image credit: Authors; produced by SciAni. Screenshots from the video “Earthquake early warning: how to and what for?)
Figure 2. Example of different real-life situations that could benefit from EEW alerts: from the protection of children in schools, to the activation of automatic emergency actions. (Image credit: Authors; produced by SciAni. Screenshots from the video “Earthquake early warning: how to and what for?)
Over the last twenty years, earthquake early warning has transitioned from a scientific concept to an operational reality in several earthquake-prone regions, including Japan, Mexico, Taiwan, China, and parts of the United States, while Europe has increasingly explored its feasibility and potential benefits [3, 4, 5, 6]. This post explores how a new, end-to-end EEW system is being used to protect Italy’s high-speed rail network, transforming seconds of seismic data into automated safety actions.
Why High-Speed Trains Need Early Warning
Railway infrastructures represent one of the most challenging and strategic applications of earthquake early warning, especially for high-speed trains travelling at hundred kilometres per hour, and relying on sophisticated safety control systems. Earthquakes can threaten railways in multiple ways: they may damage tracks, bridges, tunnels, and embankments, or produce sudden ground deformations that compromise track geometry. Even in the absence of visible structural damage, strong ground shaking can significantly increase the risk of derailment if trains are travelling at high speed. For this reason, the main objective of EEW for railways is not to prevent damage itself, which cannot be avoided once strong shaking occurs, but to manage train operations in real time. By slowing down or stopping trains before they enter potentially damaged sections, EEW can substantially reduce accident risk and support safer post-event inspections (Figure 3). International experience has demonstrated both the feasibility and the complexity of this task.
Figure 3. Example of applications of EEWS to high-speed railways. Alerts provided by EEWS can be used to slow down trains travelling along the line, to avoid derailment or passing over damaged tracks (Image credit: Authors; produced by SciAni. Screenshots from the video “Earthquake early warning: how to and what for?)
Japan pioneered the integration of EEW into railway operations decades ago, protecting the Shinkansen network through automated responses [7, 8]. China has rapidly expanded similar capabilities alongside its extensive high-speed rail system [9, 10]. Urban and regional rail networks in other countries have also explored EEW-based control, including pilot integrations of the ShakeAlert system with transit operations in California (e.g., Bay Area Rapid Transit), as well as applications of EEW-enabled railway protection strategies developed in Taiwan [11,12]. In Euro-Mediterranean countries, feasibility studies and prototype implementations have developed the use of EEW for high-speed rail protection along the TGV Lyon–Marseille corridor [13] and for the Marmaray rail tunnel in Istanbul, where rapid train control following seismic alerts has been evaluated as a mitigation strategy [14].
From Research to Reality: Building an Early Warning System for Railways
This end-to-end philosophy lies at the heart of the first operational EEW system developed for a high-speed railway in Italy, on a pilot railway segment between Rome and Naples, a corridor of about 200 km that runs close to the central–southern Apennines, one of the most seismically active regions of the country [15].
At its core, the system relies on a dedicated network of accelerometric stations installed along the railway line, roughly every 10 km to measure rapid ground shaking during earthquakes. These stations are equipped with strong-motion accelerometers, that are instruments designed to measure rapid ground shaking during earthquakes. The sensors continuously record seismic-wave-triggered ground vibrations and transmit data in real time to a central processing unit. When an earthquake occurs, the system rapidly detects the first P waves and analyses the earliest portion of the recorded signals to predict the expected peak ground acceleration along the line. Rather than focusing on earthquake magnitude, the system adopts a threshold-based, shaking-forecast-oriented approach, centered on whether ground shaking is expected to exceed user-defined levels that require operational intervention.
The system identifies in real-time the specific portion of the railway where strong shaking is expected to exceed the user-set threshold and defines the Alerted Segment of the Railway (ASR). Here, automatic train-blocking devices – fully integrated with the traffic control system – prevent trains approaching the alerted segment from entering it and trains already within it to decelerate and stop automatically (Figure 3). Crucially, the system is also designed to manage the end of the alert, using real-time strong-motion data to confirm when shaking has ceased and to support rapid, informed decisions on the resumption of normal operations.
Alerted Segments and Real Benefits: Measuring EEW in Practice
A key feature of the system is the quantitative evaluation of its performance and operational benefits. For extended targets such as railways, traditional EEW metrics based solely on magnitude estimation or single-site lead time and expected shaking level are insufficient. Instead, the system was assessed through a combination of massive numerical simulations and tests using real earthquake recordings from the 2016–2017 Central Italy seismic sequence [15]. Hundreds of synthetic earthquakes were simulated near a virtual railway line to explore a wide range of magnitudes, distances, and geometries, allowing researchers to systematically analyze alert timing, prediction accuracy, and the spatial extent of alerts. These simulations were complemented by real data to ensure realism and robustness.
The results demonstrate that alerts can be issued within a few seconds from earthquake initiation (typically between three and ten seconds) and that the system correctly predicts whether shaking thresholds will be exceeded in most cases. By combining seismic scenarios with real traffic data from the Naples–Rome line, the study shows that for most realistic earthquakes only limited portions of the line require restrictions, and most trains can be managed efficiently without unnecessary disruption. Even when trains are already within the alerted segment, early deceleration can significantly reduce risk. Very large earthquakes close to the line would affect longer segments, but such earthquake scenarios have historically very long return periods. Beyond immediate safety, the system also provides near-real-time strong-motion information that can be used to map potentially damaged sections of the infrastructure, supporting faster and more targeted post-earthquake inspections of the railway.
Designed with scalability and adaptability in mind, the system can be exported to other railway lines and integrated with different seismic networks. In this sense, the Italian experience represents not only a national first, but also a reference model for transforming Earthquake Early Warning from a scientific capability into a concrete, operational tool for protecting critical infrastructure and enhancing societal resilience.
References
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Post edited by: Hedieh Soltanpour and Navakanesh M Batmanathan
