Earthquake Early Research Articles

Early earthquake warning for hospital preparedness: Safeguarding vulnerable populations in Mexico city

While some literature exists on the necessity of Early Earthquake Warning (EEW) for the general population, establishing its usefulness in high-risk environments like working with hazardous materials, machines, and in operating rooms, little is known about the relevance of this tool in safeguarding vulnerable people. Existing studies on the Mexican population's reactions to EEW have shown that people are likely not to differentiate their protective actions in response to an EEW or ground motion without an EEW. However, it is not possible to ascertain the same for specific population segments, such as healthcare professionals with responsibilities for individuals with physical vulnerabilities (i.e., hearing, mobility, vision, among others). This study explores the use of protocols in relation to EEW in Mexico City's hospitals, comparing them to the baseline results from three hospitals in the US, with the purpose to better understand the pertinence of the warning. In-depth interviews were conducted with hospitals' civil protection officials, staff, and representatives responsible for EEW provision and maintenance. Our findings indicate that the capacity (financial and human) to train and continuously perform drills is a limiting factor for protocol adoption, as well as the lack of clarity on where within the hospital the EEW should be located, how it should emit the warning, and who should do what in response. The challenges identified by the interviewees in Mexico and the US are very similar, while the practical employment of the EEW differs vastly.

Demystifying response to EEW in Mexico: Socio-technical motivations in protective action

In countries where earthquakes are pertinent, research has explored the motivations for human response to such natural hazards, showing that a variety of factors, including socio-demographics matter in decision-making. However, human response to Early Earthquake Warnings (EEW) is as important as a response to a natural hazard itself, as it has the potential for life safety. Nonetheless, few studies focus on these characteristics when it comes to human response to EEW, even to a lesser extent in Mexico, where public EEW has been available since 1991. This study uses survey questionnaire data (N = 285) to explore socio-technical and socio-demographic factors in taking protective action in response to EEW among Mexican population, including decision to evacuate, stay-in-place, and crucially investigates what influences individuals’ choices instead of copying other’s behavior, which may have implications for personal safety. The study is complemented with in-depth interviews with representatives of the key institutions shaping information dissemination about EEW and earthquake response in Mexico, and those with expertise in structural resilience in earthquakes. It is found that directed and inclusive communications regarding what to do in response EEW in Mexico often face lack of continuity, and while earthquake drills are performed routinely (initiated the sound of EEW), they may not be representative of real-life situations, or people with mobility / hearing issues. Importantly, the study shows that positive expectations of EEW performance were also related to higher self-efficacy in individuals, which resulted in lesser occurrence of copying others’ behavior.

Early Earthquake Disaster Response Management: The BSMI Humanitarian Aid Experience in Turkey

On February 6, 2023, the regions of Turkey and Syria were struck by a devastating earthquake during the winter season, resulting in numerous casualties, injuries, displacement, and infrastructure damage. In response, the Turkish president appealed for international assistance, prompting the Indonesian Red Crescent to deploy a humanitarian aid team. The methods employed encompassed three stages: preparation, implementation, and evaluation. The implementation phase involved coordination, collaboration, and the distribution of humanitarian aid. The distribution of essential items such as ready-to-eat food, winter clothing, and medicine took place in Hatay Province and Kahramanmaras, Turkey. Effective coordination was established with the governments of Indonesia and Turkey, alongside collaboration with humanitarian agencies and Turkish medical organizations. Additionally, plans for the subsequent deployment of the medical team were reviewed. All activities were successfully executed and received positive feedback. The Indonesian Red Crescent successfully provided crucial assistance in response to the earthquake disaster in Turkey. The efforts encompassed various aspects, including aid distribution, coordination with relevant authorities, collaboration with partner organizations, and future planning. The outcomes achieved were noteworthy and yielded a positive impact.

Developing the Earthquake Early Warning and Evacuation Systems (EEWES) for Schools in Ranau District

This article presents the main development components Early Earthquake Warning and Evacuation System (EEWES) for the Ranau District of Sabah. Many early earthquake warning systems have been developed since the last major earthquake in Ranau in 2015, but none has appropriately investigated the school children evacuation processes/exercises. The system was developed not just to expedite the evacuation process at these schools but also to help evacuate the school children and to get in touch with the children’s parents who are outstation. Those parents will be updated on the evacuation initiative that is taking place on a real-time basis. The system may also transfer the evacuation details to the local and federal emergency services and other agencies concerned with the evacuation exercises. The system mainly utilised the APIs released by regional disaster centres, which may deliver speedy transmission alerts. The future research direction is to incorporate the local tremor sensor details into the system.

Early Earthquake Detection Using Batch Normalization Graph Convolutional Neural Network (BNGCNN)

Earthquake is a major hazard to humans, buildings, and infrastructure. Early warning systems should detect an earthquake and issue a warning with earthquake information such as location, magnitude, and depth. Earthquake detection from raw waveform data using deep learning models such as graph neural networks (GNN) is becoming an important research area. The multilayered structure of the GNN with a number of epochs takes more training time. It is also hard to train the model with saturating nonlinearities. The batch normalization technique is applied to each mini-batch to reduce epochs in training and obtain a steady distribution of activation values. It improves model training and prediction accuracy. This study proposes a deep learning model batch normalization graph convolutional neural network (BNGCNN) for early earthquake detection. It consists of two main components: CNN and GNN. Input to the CNN model is multi-station and three-component waveform data with magnitude ≥3.0 were collected from January 2000 to January 2015 for Southern California. The extracted features of CNN are appended with location information and input to GNN model for earthquake detection. After hyperparameter tuning of the BNGCNN, when testing and evaluating the model on the Southern California dataset, our method shows promising results to the baseline model GNN by obtaining a low error rate to predict the magnitude, depth, and location of an earthquake.

P-Wave detection using deep learning in time and frequency domain for imbalanced dataset

Early tsunami and earthquake warning systems need a good Automatic First Arrival Picking (AFAP) subsystem to determine the earthquake arrival time. This subsystem has a time-domain earthquake signal as the input and the arrival time of the primary earthquake wave (P-Wave) as the output. There are several methods of AFAP that are widely used nowadays, one of them is Short Term Average/Long Term Average (STA/LTA) fused with the AR-AIC method. Even though this method is real-time, its performance is still relatively low. With similar characteristics between the seismic signals and image data, utilising deep learning on AFAP can further increase its performance. The seismogram channels can be seen as the image height, and the signal at a certain window can be seen as the image width. Unfortunately, these image data will be considered an imbalanced dataset. In this research, deep learning with time domain and frequency domain are proposed as inputs with the Synthetic Minority Oversampling Technique (SMOTE) method. Deep learning is used because of its ability to generalise well on a huge dataset, while SMOTE is used to overcome the imbalanced dataset problem. With this proposed system, the accuracy is 99.3%, the Root Mean Square Error (RMSE) is 0.202 seconds, and the maximum execution time is 0.17 seconds with a periodic time of 0.4 seconds. With these results, the AFAP system has good results for estimating the first arrival earthquake time.

Harnessing the Computing Continuum for Urgent Science

Urgent science describes time-critical, data-driven scientific work-flows that can leverage distributed data sources in a timely way to facilitate important decision making. While our capacity for generating data is expanding dramatically, our ability to manage, analyze, and transform this data into knowledge in a timely manner has not kept pace. This paper explores how the computing continuum, spanning resources at the edges, in the core, and in-between, can be harnessed to support urgent science and discusses associated research challenges. Using an Early Earthquake Warning (EEW) workflow, which combines data streams from geo-distributed seismometers and high-precision GPS stations to detect large ground motions, as a driver, we propose a system stack that can enable the fluid integration of distributed analytics across a dynamic infrastructure spanning the computing continuum.

Backpropagation neural network as earthquake early warning tool using a new modified elementary Levenberg–Marquardt Algorithm to minimise backpropagation errors

Abstract. A new modified elementary Levenberg–Marquardt Algorithm (M-LMA) was used to minimise backpropagation errors in training a backpropagation neural network (BPNN) to predict the records related to the Chi-Chi earthquake from four seismic stations: Station-TAP003, Station-TAP005, Station-TCU084, and Station-TCU078 belonging to the Free Field Strong Earthquake Observation Network, with the learning rates of 0.3, 0.05, 0.2, and 0.28, respectively. For these four recording stations, the M-LMA has been shown to produce smaller predicted errors compared to the Levenberg–Marquardt Algorithm (LMA). A sudden predicted error could be an indicator for Early Earthquake Warning (EEW), which indicated the initiation of strong motion due to large earthquakes. A trade-Off decision-making process with BPNN (TDPB), using two alarms, adjusted the threshold of the magnitude of predicted error without a mistaken alarm. With this approach, it is unnecessary to consider the problems of characterising the wave phases and pre-processing, and does not require complex hardware; an existing seismic monitoring network-covered research area was already sufficient for these purposes.

High-Resolution Early Earthquake Damage Assessment System for Mexico City Based on a Single-Station

A high-resolution early earthquake damage assessment system is presented for Mexico City based on real-time computations of seismic spectral intensities at a reference site. To obtain intensities for the entire Mexico Valley, pre-calculated response spectral ratios at soft sites are used. The estimates of seismic intensities (peak ground acceleration, peak ground velocity and spectral ordinates for selected structural periods), together with intensity-damage relations for buildings, fatalities and water supply network were used to obtain the spatial distribution of expected damage throughout the city. The process takes approximately 10 minutes with no human intervention. Since the available time to carry out all the computations is short, we have built a representative building and population database that concentrates all the information in a square mesh of 400 • 400 m. Results are sent to an Emergency Center and to decision makers to trigger previously set emergency plans and to provide information before emergency plans are in full operation.

High-Resolution Early Earthquake Damage Assessment System for Mexico City Based on a Single-Station

Se presenta un sistema de evaluacion temprana de danos de alta resolucion desarrollado para la Ciudad de Mexico basado en calculos en tiempo real de intensidades espectrales sismicas en un sitio de referencia. Para obtener las intensidades en todo el Valle de Mexico, se usan relaciones espectrales de respuesta pre-calculadas en sitios blandos. Se utilizan las estimaciones de las intensidades sismicas (aceleracion maxima del suelo, velocidad maxima del suelo y ordenadas espectrales para determinados periodos estructurales), junto con las relaciones de intensidad-dano de edificios, de victimas y de la red de distribucion de agua potable para obtener la distribucion espacial del dano esperado en toda la ciudad. El proceso dura aproximadamente 10 minutos sin intervencion humana. Dado que el tiempo disponible para realizar todos los calculos es corto, se construyo una base de datos representativa de edificios y poblacion que concentra toda la informacion en una malla cuadrada de 400 × 400 m. Los resultados se envian a un Centro de Emergencia y a los tomadores de decisiones para activar planes de emergencia previamente establecidos y proporcionar informacion antes de que los planes de emergencia esten en pleno funcionamiento

Early Earthquake Detection and Warning Alarm System in Iran by a Telegraph Operator: A 116-Year-Old Disaster Prevention Attempt

According to an article printed in 1909 in a local Iranian newspaper, the New Iran ( Irān‐e Nau ; Fig. 1), a telegraph operator at the remote desert town of Kermān in southeast Iran, using coils of a single wire with return circuit through the ground of his telegraph instrument, picked up the Earth’s movement as an unusual electromagnetic signal on the magnetic needle, which gave a few seconds warning of an earthquake. Apparently, the operator was using a Wheatstone/Cooke‐type needle magneto‐electric telegraph built in the late nineteenth century. Figure 1. Yusef the telegraph operator’s 1909 account of his observations of unusual electromagnetic signals detected just before earthquakes in 1897 and 1909. He first noticed this anomaly on his telegraph instrument during an earthquake in 1897. Two medium‐magnitude earthquakes during that year were strongly felt and documented in Kermān. These were (1) the 22 May 1897 MMI∼VII+ M S∼5.5, Kuhbanān earthquake with its epicenter about 145 km northwest of Kermān; and (2) the 27 May 1897, MMI∼VIII M S∼>5.5 Chatrud earthquake located about 25 km north‐northwest of Kermān (see fig. 3 in Berberian, 2005). The telegraph operator observed that the first earthquake took place during the evening, suggesting that he was referring to the 27 May 1897 event. His second observation of a seismically induced disturbance was during the 27 October 1909, ∼ M S>5.5, MMI>VII+, Jowshān earthquake, with its damage zone located about 58 km to the east‐southeast of Kermān (fig. 5 in Berberian, 2005). The article, translated below from Persian into English, is signed by “Yusef Telegerāfchi va Tahvildār‐e Telegerāf‐khāneh‐ye Kermān” (“Yusef /Joseph, the telegraph operator and cashier of the Kermān Telegraph Office”). The article was printed nine months after the occurrence of the …

Online Data Processing Methods in Xlet Applications for Seismic Early Warning and Emergency Services on Interactive Digital Television

In this paper, I described the methods that I used for the creation of Xlets, which are Java applets that are developed for the IDTV environment; and the methods for online data retrieval and processing that I utilized in these Xlets. The themes that I chose for the Xlets of the IDTV applications are Earthquake and Tsunami Early Warning; Recent Seismic Activity Report; and Emergency Services. The online data regarding the Recent Seismic Activity Report application are provided by the Kandilli Observatory and Earthquake Research Institute (KOERI) of Bogazici University in Istanbul; while the online data for the Earthquake and Tsunami Early Warning and the Emergency Services applications are provided by the Godoro website which I used for storing (and retrieving by the Xlets) the earthquake and tsunami early warning simulation data, and the DVB network subscriber data (such as name and address information) for utilizing in the Emergency Services (Police, Ambulance and Fire Department) application. I have focused on the methodologies to use digital television as an efficient medium to convey timely and useful information regarding seismic warning data to the public, which forms the main research topic of this paper.

Stratigraphic evidence for an early Holocene earthquake in Aceh, Indonesia

Stratigraphic evidence for an early Holocene earthquake in Aceh, Indonesia

S101023 東日本大震災における半導体製造工場の被害状況 : 地震被害の概要,復旧状況と提言-その1

The devastating earthquake of Mw9.0 hit the Tohoku district, north-east part of Japan on March 11, 2011. About 16,000 people died and 3,000 people were missing by the strong motion and tsunami, and the economic damage was estimated about 16.9 trillion yen except for the influence by the nuclear accident of Fukushima Danchi Nuclear Power Plant. The industrial facilities, power plants, or research facilities were damaged in this earthquake, and various kinds of mechanical equipment set in these facilities were also damaged. The Japan Society of Mechanical Engineers (JSME) have set up the investigation committee and investigated the seismic damage of mechanical equipment of these industrial facilities for the purpose to understand the situation and cause of the damages in such facilities and contribute to improvement of preparedness for the forthcoming earthquake. This paper provides a summary of the typical damages of a semiconductor manufacturing factory. This facility had been promoting various measures such as not only seismic reinforcement of the facilities but also one of the earliest introduction of the Early Earthquake Warning system. Thereby, although the facility was hit by unexpected massive earthquake, the structural damage was considered to be kept to a minimum.

Re-evaluation of early instrumental earthquake locations: methodology and examples

The difficulties of locating earthquakes in the early instrumental period are not always fully appreciated. The networks were sparse, and the instruments themselves were of low gain, often had inappropriate frequency response and recording resolution, and their timing could be unreliable and inaccurate. Additionally, there was only limited knowledge of earth structure and consequent phase identification and propagation. The primitive Zöppritz tables for P and S, with no allowance for the core, did not come into use until 1907, and remained the main model until the adoption of the Jeffreys-Bullen tables in the mid-1930s. It was not until the early 1920s that studies of Hindu Kush earthquakes revealed that earthquake foci could have significant depth. Although many early locations are creditably accurate, others can be improved by use of more modern techniques. Early earthquakes in unusual places often repay closer investigation. Many events after about 1910 are well enough recorded to be re-located by computer techniques, but earlier locations can still be improved by using more recent knowledge and simpler techniques, such as phase re-identification and graphical re-location. One technique that helps with early events is to locate events using the time of the maximum phase of surface waves, which is often well reported. Macroseismic information is also valuable in giving confirmation of earthquake positions or helping to re-assess them, including giving indications of focal depth. For many events in the early instrumental period macroseismic locations are to be preferred to the poorly-controlled instrumental ones. Macroseismic locations can also make useful trial origins for computer re-location. Even more recent events, which appear to be well located, may be grossly in error due to mis-interpretation of phases and inadequate instrumental coverage. A well converging mathematical solution does not always put the earthquake in the right place, and computer location programs may give unrealistically small estimates of error. Examples are given of improvements in locations of particular earthquakes in various parts of the world and in different time periods.

Does the Early Earthquake Warning Promote Self-Defense Actions of Residents?

Does the Early Earthquake Warning Promote Self-Defense Actions of Residents?

The Early Earthquake Warning as a New tool for Disaster Prevention.

The Early Earthquake Warning as a New tool for Disaster Prevention.

Development of General Evaluation System for Seismographs and its Installation in Early Earthquake Detection Systems

Compared with their predecessor, the new systems (DataStation, DataCraft) that we have developed offer various advantages such as an increase in the number of types of seismographic equipment applications, the provision of an early earthquake detection process function and the capability to process a large quantity of data collectively. Early earthquake alarm seismographs will be installed along the meter gauge lines in the near future. Before the existing seismographs are replaced with these early earthquake alarm seismographs, we should confirm the suitability of the new system based on the analysis of past data.