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Reducing Latencies in Earthquake Early Warning


Yin, Lucy (2018) Reducing Latencies in Earthquake Early Warning. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/Z9TH8JW4.


Existing Earthquake Early Warning (EEW) algorithms use waveform analysis for earthquake detections, estimation of source parameters (i.e., magnitude and hypocenter location), and prediction of peak ground motions at sites near the source. The latency of warning delivery due to data collection significantly restricts the usefulness of the system, especially for users in the vicinity of the earthquake source, as the warning may not arrive before the strong shaking. This presentation discusses several methods to reduce the warning latency, while maintaining reliability and robustness, so that the warning time can be maximized for users to take appropriate actions to reduce causalities and economic losses.

Firstly, we incorporated the seismicity forecast information from Epidemic-Type Aftershock Sequence (ETAS) model into EEW as prior information, under the Bayesian probabilistic inference framework. Similar to human’s decision-making process, the Bayesian approach updates the probability of the estimations as more information becomes available. This allows us to reduce the required time for reliable earthquake signal detection from at least 3 seconds to 0.5 second. Furthermore, the initial error of hypocenter location estimation is reduced by 58%. The performance of the algorithm is further improved during aftershock sequences and swarm earthquakes.

Secondly, we introduce the use of multidimensional (KD tree) data structure to organize seismic database, so that the querying time can be reduced for the nearest neighbor search during earthquake source parameter estimation. The processing time of KD tree is approximately 15% of the processing time of linear exhaustive search, which allows the potential use of large seismic databases in real-time.

EEW is an interdisciplinary subject that involves collaboration among different scientific and engineering communities. Only by optimizing the warning time, such a unified system could be successful in taking protective actions before, during, and after earthquake natural disasters.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:Earthquake Early Warning
Degree Grantor:California Institute of Technology
Division:Engineering and Applied Science
Major Option:Civil Engineering
Minor Option:Applied And Computational Mathematics
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Heaton, Thomas H.
Thesis Committee:
  • Asimaki, Domniki (chair)
  • Ampuero, Jean-Paul
  • Yue, Yisong
  • Heaton, Thomas H.
  • Page, Morgan
Defense Date:3 August 2017
Funding AgencyGrant Number
Natural Science and Engineering Research Council of Canada UNSPECIFIED
Gordon and Betty Moore FoundationUNSPECIFIED
Record Number:CaltechTHESIS:09242017-121200052
Persistent URL:
Yin, Lucy0000-0002-0652-9330
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:10451
Deposited By: Lucy Yin
Deposited On:04 Oct 2017 19:45
Last Modified:18 Dec 2020 00:54

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