A Prototype Earthquake Early Warning System for Northern India

Chamoli, Bhanu Pratap; Kumar, Ashok; Chen, Da‐Yi; Gairola, Ajay; Jakka, Ravi S.; Pandey, Bhavesh; Kumar, Pankaj; Rathore, Govind

doi:10.1080/13632469.2019.1625828

Cited by 28 publications

(20 citation statements)

References 36 publications

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“…The state is still lacking effective warning systems like Earthquake Early Warning System (EEWS). The EEWS is used to describe a real-time earthquake information system that can provide a warning prior to significant ground shaking (Chamoli et al, 2019). EEWSs are already introduced in many countries, and meanwhile, Japan and Taiwan got success stories from these systems (Chamoli et al, 2019).…”

Section: Discussion About the Awareness On Earthquakementioning

confidence: 99%

“…The EEWS is used to describe a real-time earthquake information system that can provide a warning prior to significant ground shaking (Chamoli et al, 2019). EEWSs are already introduced in many countries, and meanwhile, Japan and Taiwan got success stories from these systems (Chamoli et al, 2019). In India, several seismologists at the Indian Institute of Technology (IIT), Roorkee already started a project to implement the EEWS in northern India (Chamoli et al, 2019), but the result is awaiting.…”

Section: Discussion About the Awareness On Earthquakementioning

confidence: 99%

See 1 more Smart Citation

Assessment on the impact of the Tripura earthquake (January 3, 2017, mw = 5.6) in Northeast India

Debbarma

Debnath

2021

J GEOGR INST CVIJIC

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The northeastern part of the Indian subcontinent, considered as the most active seismic zone of the Indian subcontinent, was hit by an earthquake of Mw 5.6 on January 3, 2017. The epicenter of this earthquake was Kanchanbari located in the Dhalai district of Tripura. The present study aims to assess the environmental and socio-economic impact of this earthquake in the vicinity of the epicenter. To assess and determine the level of damage, the affected areas were visited during the first week of the 2017 earthquake. Various Government offices were also consulted to acquire data on damages caused by the earthquake. Moreover, Remote Sensing and Geographical Information System (RS & GIS) techniques were applied to address the influence of this earthquake on bank erosion. During the field visit, the striking features of soil liquefaction generated by the earthquake were observed in the flood plain area of the Manu River. Landslide, with three casualties in India and the neighbor Bangladesh, and damages of infrastructure were also reported. Additionally, an assessment of the bank erosion study revealed that the rate of the post-earthquake bank erosion increased to 592%, compared to the pre-earthquake bank erosion within the study length of the Manu River. The findings highlighted that the impact of this earthquake is minimal. However, the seismotectonic features and observation of the liquefaction within the risk zone of the earthquake indicate a possible significant threat for the future.

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Section: Discussion About the Awareness On Earthquakementioning

confidence: 99%

Section: Discussion About the Awareness On Earthquakementioning

confidence: 99%

Assessment on the impact of the Tripura earthquake (January 3, 2017, mw = 5.6) in Northeast India

Debbarma

Debnath

2021

J GEOGR INST CVIJIC

View full text Add to dashboard Cite

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“…In such situations, it is common for EEW systems to have poor earthquake location estimates and significant alert delays due to their restricted azimuthal coverage and the time needed for the wavefront to reach the required number of sensors and generate an alert [27]. The array-based approach consisting of MEMS-based accelerometers has demonstrated improvements in EEW capabilities; this can be seen in cases such as those in Southern California [13], Northern India [38], Central Italy [39], Taiwan [25,40] and the Sichuan-Yunnan Province [12].…”

Section: Current State-of-the-art Of Low-cost Eew Solutionsmentioning

confidence: 99%

“Saving Precious Seconds”—A Novel Approach to Implementing a Low-Cost Earthquake Early Warning System with Node-Level Detection and Alert Generation

et al. 2022

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This paper presents findings from ongoing research that explores the ability to use Micro-Electromechanical Systems (MEMS)-based technologies and various digital communication protocols for earthquake early warning (EEW). The paper proposes a step-by-step guide to developing a unique EEW network architecture driven by a Software-Defined Wide Area Network (SD-WAN)-based hole-punching technology consisting of MEMS-based, low-cost accelerometers hosted by the general public. In contrast with most centralised cloud-based approaches, a node-level decentralised data-processing is used to generate warnings with the support of a modified Propagation of Local Undamped Motion (PLUM)-based EEW algorithm. With several hypothetical earthquake scenarios, experiments were conducted to evaluate the system latencies of the proposed decentralised EEW architecture and its performance was compared with traditional centralised EEW architecture. The results from sixty simulations show that the SD-WAN-based hole-punching architecture supported by the Transmission Control Protocol (TCP) creates the optimum alerting conditions. Furthermore, the results provide clear evidence to show that the decentralised EEW system architecture can outperform the centralised EEW architecture and can save valuable seconds when generating EEW, leading to a longer warning time for the end-user. This paper contributes to the EEW literature by proposing a novel EEW network architecture.

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“…Under this project, instrumentation of 84 Micro-Electro-Mechanical System (MEMS) accelerometers has been done in the Garhwal region of Uttarakhand (Chamoli et al, 2019;Kumar et al, 2021). These sensors are installed on the ground floor of governmentowned offices of Base Transceiver Station (BTS) of Bharat Sanchar Nigam Limited (BSNL) and Point of Presence (PoP) of State Wide Area Network (SWAN) available in the Garhwal region of Uttarakhand.…”

Section: Earthquake Dataset Used In H/v Spectral Ratio Analysismentioning

confidence: 99%

Site classification of seismic recording stations of Garhwal region of earthquake early warning system for Uttarakhand, India

Kumar

Pandey

Kamal

et al. 2022

Vietnam J. Earth Sci.

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Site classification is vital to carry out seismic hazard analysis of a region and get the damage patterns caused by earthquakes. In the present study, the ground motion of earthquakes recorded from 2015 to 2019 at 84 sites of the seismic network array of Earthquake Early Warning System for Uttarakhand are analyzed for site classification purposes. The predominant period from the mean horizontal to vertical spectral ratio curves was estimated. The classification schemes devised by Japan Road Association and National Earthquake Hazards Reduction Program are applied to classify the sites. Along with this, two other site classification indexes schemes are also applied for classification purposes. Data winnowing techniques are used over the ground motion records to pick out desirable quality records. Conclusively, the site class with the highest recurrence rate amongst the used methods is selected as the final class for that particular site. The effect of magnitude, distance and depth on horizontal to vertical spectral ratio are described and concluded that these factors do not significantly affect the ratio curves. The average horizontal to vertical spectral ratio curves obtained for all the sites matches well with the existing literature. The classification of a few sites are verified from the classification done by other methods in recent studies. It is evident from the results that the classification done in this study matches well with them.

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A Prototype Earthquake Early Warning System for Northern India

Cited by 28 publications

References 36 publications

Assessment on the impact of the Tripura earthquake (January 3, 2017, mw = 5.6) in Northeast India

Assessment on the impact of the Tripura earthquake (January 3, 2017, mw = 5.6) in Northeast India

“Saving Precious Seconds”—A Novel Approach to Implementing a Low-Cost Earthquake Early Warning System with Node-Level Detection and Alert Generation

Site classification of seismic recording stations of Garhwal region of earthquake early warning system for Uttarakhand, India

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