Toward the Next Generation of the Earthquake Early Warning System

Which kind of disasters can affect human life and how can science help to reduce the consequence of tragedy? Indeed, there is a range of challenges including technological or man-made hazards and natural hazards. Here in this thesis, one of the very critical natural hazards which has a major impact on human living i.e., earthquake hazards, is investigated. Population growth and patterns of economic development are two important issues directly affected by an earthquake occurrence and induced impacts, leading to dramatic disaster situations. The main aim of this thesis is to discuss how science can help to reduce the effect of the earthquake on human life. To human knowledge, precise earthquake prediction i.e., specification of the time, location, and magnitude of future earthquakes are almost impossible. Moreover, earthquake prediction is sometimes distinguished from earthquake forecasting, which can be defined as the probabilistic assessment of general earthquake hazards, including the magnitude and frequency of damaging earthquakes in a given area over the years or decades. Both earthquake prediction and forecasting are also different from earthquake warning systems, in which the latter can provide a warning to neighboring regions that might be affected for an ongoing earthquake. The Earthquake Early Warning (EEW) systems rapidly provide in-advanced warnings of impending strong ground motion in real-time as soon as detection of the ongoing earthquakes and before the impact of the ground vibrations. The initial part of the primary waves which is typically low-amplitude ground motion waveform i.e., P-waves is normally used to estimate the potentially large-amplitude ground motion. Note that issuing and transmitting the alarms information using telecommunication is faster than seismic wave propagation speed, thus, the early warnings may arrive at a target site before the strong shaking itself, thereby providing invaluable time for both people and automated systems to take actions to mitigate earthquake-related injury and losses. These actions might range from complex automated procedures as stopping high-speed trains to simple procedures as warning people to get themselves to a safe location.History of implementation of the first EEW system backs to 1991 (SASMEX) in Mexico City [Espinosa-Aranda, et al., 2009]. Nowadays, there is a significant improvement of EEW systems throughout the world which are operating in many parts of the world to provide warnings at high seismic hazard regions. Japan Meteorological Agency (JMA) and ShakeAlert EEW systems are two important examples developed in Japan and the west coast of the United States, respectively. In addition, EEW systems are being tested in other countries as Italy, Taiwan, Romania, China, South Korea, Turkey, and Switzerland. EEW standard approaches estimate the location and magnitude of an earthquake, the key ingredients among the other parameters which are used in a ground motion prediction equation (GMPE) to calculate expected ground shaking. If the expected ground motion is greater than a manually specified threshold, the user is alerted. For instance, the JMA system provides alarms to subprefectures whenever ground motions are expected to exceed JMA intensity 4 within that subprefecture. The JMA system has released hundreds of alerts, including alerts sent to several million people during the 2011 M9.0 Tohoku earthquake [Fujinawa and Noda, 2013].Although nowadays EEWS is one of the various important challenges in seismology and that a lot of scientific efforts have been done to develop it, there is still a long way to consider it as a consolidated technology. The physical theory behind EEWS is not fully clear and all parameters measured from early motion with rather non-negligible uncertainty are used to predict the final earthquake characteristics. The main assumption of most models, both the processes and algorithms, used in standard EEWS approaches and induced wave propagation are based on some simplifications to model the earthquake source and wave propagation. Standard approaches for the peak motion prediction in EEW methods are typically based on the point-source approximation and on simple empirical attenuation relationships, depending on the magnitude and hypocentral distance. On average, few portions of the P-waves, 3 seconds are used to the real-time computation of the event magnitude and location, which could be a problem for any estimation of large events in which have a complex rupture process over tens of seconds.Several efforts are done in the last decade to measure a rupture during its early stages. Here in this thesis, we mainly focus on filling this gap, developing the algorithms to measure rupture characteristics and then consider the refined extended source to generate the shake map. Therefore, the thesis results can open a new research topic in real-time ground-shaking prediction for ongoing seismic events. All these concepts can be considered all together to issue the alarm and they will trigger “the next generation of EEW systems”. In the framework of SERA infrastructure (Seismology and Earthquake Engineering Research Infrastructure Alliance for Europe, call INFRAIA-01-2016-2017), and JRA 6 (Joint Research Action, “Real-Time earthquake Shaking”), different methodologies are being developed and tested to generate evolutionary ground shaking maps by considering a rupture kinematic description and reliable finite-fault model. In this regard, we have refined and tested various methodologies to retrieve the earthquake source. Same as the standard EEW approaches, the initial P-wave signals will be explored to identify the best proxies for the rapid source characterization (moment, length and duration). Updated kinematic rupture models (space-time slip function) are inferred by the consideration of progressively enlarged P-wave time windows as they are available at the network probes. The final output is the time-varying predicted-ground motion at the Earth surface at sites of interest in a recurrent manner. For this purpose, we first, evaluate many possibilities and algorithms in the offline analysis of the initial P-wave signals. In particular, the time evolution of peak amplitude parameters will be used for the rapid prediction of the source magnitude and for estimating and then modeling the moment rate function. These estimates are used to build simplified kinematic source models. The rupture speed and the rise time are selected accounting for the medium elastic properties and the event magnitude. A single patch slip distribution is imposed: its extension and position with respect to the nucleation are controlled by the moment estimates and by preliminary directivity estimates, respectively. The convolution of these models with pre-computed Green’s functions provides complete wavefield synthetic seismograms and thus early estimates of the expected amplitude vibrations (PGA/PGV) at the EEW target sites. The alert decision scheme is thus defined upon the exceedance of a user-compliant PGA/PGV threshold by the predicted synthetic values.In addition, the inversion methodology will be implemented and tested on synthetic and real waveforms in off-line acquisition mode. A database of synthetic waveforms will be generated for a variety of case-studies (Ischia and Norcia earthquakes occurred in Italy). The off-line application will be checked, but the main objective is the development, the implementation and validation of efficient algorithms for the real-time signal processing, slip inversion and ground-shaking forecast that will improve the predictive performance of EEWS. The structure of the thesis is based on four main chapters as follows: The first chapter, as an introduction, describes concepts of the earthquake early warning system from standard approaches to those expected in the next-generation tools. The second chapter illustrates the new model to compute the earthquake source characteristics. In the third chapter, using the source model resulted from the previous chapter, the evolutionary ground shaking prediction considering the Norcia event as a case study is evaluated. Finally, the last chapter is about calculating the source mechanism and rupture model from the inversion of a near-Source record.