An Earthquake Early Warning System in Fujian, China

Zhang, Hongcai; Jin, Xing; Wei, Yongxiang; Li, Jun; Kang, Lanchi; Wang, Shicheng; Huang, Lingzhu; Yu, Peiwu

doi:10.1785/0120150143

Cited by 46 publications

(16 citation statements)

References 42 publications

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“…The accuracies in this study were lower than those obtained by other authors [26][27][28][29], who achieved an accuracy of 7 kilometers on average. However, it is important to note that this study was carried out with information from a single seismological station and additional descriptors such as the predominant period.…”

Section: Conclusion and Recommendationscontrasting

confidence: 95%

Support vector machines applied to fast determination of the geographical coordinates of earthquakes, The case of El Rosal seismological station, Bogotá Colombia

Gutiérrez

Niño

Vargas

2019

DYNA

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The objective of this research was to determine the latitude and longitude of seismic events using support vector machines (SVMs) and seismic records from El Rosal station, which is located 40 kilometers northwest of Bogotá, Colombia. A total of 504 SVM models were tested to determine latitude and 504 models for longitude, with various combinations of the complexity factor and kernel function exponent, applied to earthquakes of 2, 2.5, 3 and 3.5 ML in time windows of 15, 10 and 5 seconds. The best results showed errors of 40 kilometers for latitude and 30 kilometers for longitude when identifying where tremors occurred. These outcomes might be improved by applying additional descriptors during the SVMs' training stages, such descriptors can be related to Fourier frequency spectra, predominant period and wavelet transform coefficients.

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Section: Conclusion and Recommendationscontrasting

confidence: 95%

Support vector machines applied to fast determination of the geographical coordinates of earthquakes, The case of El Rosal seismological station, Bogotá Colombia

Gutiérrez

Niño

Vargas

2019

DYNA

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show abstract

“…Earthquake early warning (EEW) is a technology that automatically processes seismic signals and issues warnings of imminent strong motion. EEW systems have been developed and/or operated in many locations such as Japan (Hoshiba et al, ; Nakamura, ), Mexico (Espinosa‐Aranda et al, ), California (Böse et al, ), Taiwan (Chen et al, ), Korea (Sheen et al, ), China (Zhang et al, ), and Europe (Clinton et al, ).…”

Section: Introductionmentioning

confidence: 99%

Real‐Time Detection of Rupture Development: Earthquake Early Warning Using P Waves From Growing Ruptures

Kodera

2018

Geophysical Research Letters

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Large earthquakes with long rupture durations emit P wave energy throughout the rupture period. Incorporating late‐onset P waves into earthquake early warning (EEW) algorithms could contribute to robust predictions of strong ground motion. Here I describe a technique to detect in real time P waves from growing ruptures to improve the timeliness of an EEW algorithm based on seismic wavefield estimation. The proposed P wave detector, which employs a simple polarization analysis, successfully detected P waves from strong motion generation areas of the 2011 Mw 9.0 Tohoku‐oki earthquake rupture. An analysis using 23 large (M ≥ 7) events from Japan confirmed that seismic intensity predictions based on the P wave detector significantly increased lead times without appreciably decreasing the prediction accuracy. P waves from growing ruptures, being one of the fastest carriers of information on ongoing rupture development, have the potential to improve the performance of EEW systems.

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“…EEW systems of Taiwan have been in operation since 1993, and are capable of sending predicted intensity and warning times to school attendees [6,7,8,9]. Besides, some other EEW systems were also developed and tested in many countries and regions, such as California [10,11], southern Italy [12], Southwest Iberia [13], India [14], and China [15,16].…”

Section: Introductionmentioning

confidence: 99%

Performance Evaluation of Low-Cost Seismic Sensors for Dense Earthquake Early Warning: 2018–2019 Field Testing in Southwest China

Wang

et al. 2019

Sensors

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Earthquake Early Warning (EEW) was proved to be a potential means of disaster reduction. Unfortunately, the performance of the EEW system is largely determined by the density of EEW network. How to reduce the cost of sensors has become an urgent problem for building a dense EEW. A low-cost seismic sensor integrated with a Class C MEMS accelerometer was proposed in this paper. Based on minimal structure design, the sensor’s reliability was enhanced, while the costs were cut down as well. To fully reveal the performance, ten of the seismic sensors were installed and tested in Sichuan Province, southwest of China from May 2018 to February 2019. The seismic records obtained by the MNSMSs were compared with those by the traditional strong motion seismographs. The records obtained by the MNSMSs have good consistency with the data obtained by the Etnas. The MNSMSs can obtain clear seismic phases that are enough to trigger earthquake detections for EEW. By noise analysis, different channels of the same sensor and different sensors have good consistency. The tested dynamic range (over 87 dB) and useful resolution (over 14.5 bits) are completely in conformity with the designed parameters. Through real field testing, small earthquakes (M 3.1–3.6) can be detected by all three components E-W, N-S, and U-D within 50 km. In all, the low-cost seismic sensor proposed as a high-performance Class C MEMS sensor can meet the needs of dense EEW in terms of noise, dynamic range, useful resolution, reliability, and detecting capabilities.

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An Earthquake Early Warning System in Fujian, China

Cited by 46 publications

References 42 publications

Support vector machines applied to fast determination of the geographical coordinates of earthquakes, The case of El Rosal seismological station, Bogotá Colombia

Support vector machines applied to fast determination of the geographical coordinates of earthquakes, The case of El Rosal seismological station, Bogotá Colombia

Real‐Time Detection of Rupture Development: Earthquake Early Warning Using P Waves From Growing Ruptures

Performance Evaluation of Low-Cost Seismic Sensors for Dense Earthquake Early Warning: 2018–2019 Field Testing in Southwest China

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