Advances in Earthquake Prediction

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Earth Sciences".

Deadline for manuscript submissions: closed (30 April 2022) | Viewed by 1824

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National Institute for Earth Physics, Calugareni str. 12, P.O. Box MG-2, 077125 Magurele-Bucharest, Ilfov, Romania
Interests: earth science; seismology; seismic source; seismic hazard
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Special Issue Information

Dear Colleagues,

Despite the efforts made for more than 100 years to predict earthquakes, the results are rather disappointing. Knowledge of physical processes at regional and local scales prior to earthquake nucleation is poor due to the complexity and non-linearity of geosystems. Research has focused on statistical approaches to detect relevant precursory signals (seismicity, geophysical, geochemical and biological patterns). However, reported precursors are contradictory and unsuitable for rigorous statistical evaluation. Increasingly large geo-datasets and development of computationally intensive simulations provide opportunities for systematic analysis and model testing. New high-performance tools (e.g., machine learning) and multidisciplinary approaches give opportunity to assign a confidence level to each prediction.

The Special Issue promotes new ideas and approaches to answer numerous questions on earthquake prediction topics. Original research contributions are welcome from multidisciplinary fields of investigation (seismicity, geophysics and geodesy, hydrology, geochemistry, ionosphere and biological systems, etc.). Applications of advanced statistics, decision-making science, and physics of complex non-linear systems are encouraged.

Dr. Mircea Radulian
Guest Editor

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Keywords

  • earthquake prediction
  • earthquake precursors
  • physics of faulting
  • machine learning
  • numerical simulations
  • statistical significance
  • complex non-linear systems

Published Papers (1 paper)

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Research

14 pages, 6492 KiB  
Article
Source Model and Seismogenic Environment of the Ms 6.4 Yangbi Earthquake in Yunnan, China—Based on InSAR Observation
by Wei Li, Yutong Huang, Xiaohang Wang, Xin Jiang, Xiaotong Li, Xukang Xie, Qianwen Wang and Haowen Yan
Appl. Sci. 2022, 12(12), 5908; https://0-doi-org.brum.beds.ac.uk/10.3390/app12125908 - 10 Jun 2022
Cited by 1 | Viewed by 1370
Abstract
On 21 May 2021, an Ms 6.4 earthquake struck Yangbi County, Dali Prefecture, Yunnan Province, China, which is the largest earthquake to hit this area since 1976. In this paper, we obtained the coseismic deformation of the Yangbi earthquake in Yunnan Province based [...] Read more.
On 21 May 2021, an Ms 6.4 earthquake struck Yangbi County, Dali Prefecture, Yunnan Province, China, which is the largest earthquake to hit this area since 1976. In this paper, we obtained the coseismic deformation of the Yangbi earthquake in Yunnan Province based on the interferometric synthetic aperture radar (InSAR) observation. After that, we obtained the fault geometry and slip distribution model of this earthquake via the two-step inversion method. The maximum deformation in the ascending orbit along the line of sight (LOS) direction was 7.3 cm, and the maximum deformation in the descending orbit along the LOS direction was 8.9 cm; the slip distribution model showed that the slip distribution of this earthquake was concentrated at a depth of 1–14 km, and the maximum slip was 0.6 m at a depth of 5 km. Based on the modeling result, it was inferred that the seismogenic fault of this earthquake was a dextral strike-slip fault on the west side of the Weixi-Qiaohou–Weishan fault. Combining the existing geological data and the changes in Coulomb stress caused by this earthquake, the seismic hazard and seismogenic structure in the area near the epicenter were analyzed and discussed, and the results showed that, in the northwest of the Weixi-Qiaohou fault zone, there will be an increased hazard of a future earthquake in the NW trend; thus, we should pay attention to this area. Full article
(This article belongs to the Special Issue Advances in Earthquake Prediction)
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