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Decoding Earthquake Complexity: From Earthquake Ruptures and Slip Styles to...
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Decoding Earthquake Complexity: From Earthquake Ruptures and Slip Styles to Seismic Sequences and Faulting

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Complexity".

Deadline for manuscript submissions: 15 May 2026 | Viewed by 2876

Special Issue Editors

Dr. Davide Zaccagnino

E-Mail Website
Guest Editor
1. Institute of Risk Analysis, Prediction and Management (Risks-X), Southern University of Science and Technology (SUSTech), Shenzhen, China
2. National Institute of Geophysics and Volcanology (INGV), Rome, Italy
Interests: earthquake physics; seismic hazard; earthquake forecasting; earthquake predictability; statistical seismology; tectonophysics; physics of faulting
Prof. Dr. Filippos Vallianatos

E-Mail Website
Guest Editor
1. Faculty of Geology and Geoenvironment, Department of Geophysics–Geothermics, National and Kapodistrian University of Athens, Athens, Greece
2. Institute of Physics of the Earth’s Interior and Geohazards, Solid Earth Physics and Geohazards Risk Reduction, Hellenic Mediterranean University Research Center, Crete, Greece
Interests: non-extensive statistical mechanics; fractals; self-similarity; earthquakes; statistical seismology; nonlinear geophysics
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Robert Shcherbakov

E-Mail Website
Guest Editor
Department of Earth Sciences and Department of Physics and Astronomy, Western University, London, ON, Canada
Interests: statistical seismology; physics of earthquakes; induced seismicity; earthquake forecasting; nonlinear dissipative complex systems; geomechanics; earthquake clustering and aftershocks; machine learning in earthquake seismology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Modern geophysical networks are now able to capture fault system behavior with unprecedented resolution, revealing complex interactions between seismic ruptures, slow slip events, and aseismic creep. These observations consistently challenge existing physical models, demanding new theoretical frameworks and analytical approaches to understand nonlinear fault zone processes across temporal and spatial scales.

Understanding complexity in seismicity and faulting is crucial for improving our knowledge of the physics of faulting and, above all, of how large earthquakes emerge in previously stable fault systems from the whole spectrum of fault slip styles, with an outstanding future impact on next-generation physics-based earthquake forecasting. To better understand emergent phenomena in seismology (e.g., preparatory processes of large earthquakes) and the complexity of seismicity and faulting, innovative and interdisciplinary research is needed that can handle large amounts of data with more accurate physical, computational, and AI-enhanced models that are able to investigate the chaotic and nonlinear nature of fault systems across multiple scales, from microfractures to global tectonic settings.

This Special Issue aims to highlight interdisciplinary studies that go beyond phenomenological descriptions to reveal the fundamental mechanics governing fault system behavior. We particularly encourage contributions demonstrating how new observations can constrain physical models to embrace complexity in earthquake occurrences.

Dr. Davide Zaccagnino
Prof. Dr. Filippos Vallianatos
Prof. Dr. Robert Shcherbakov
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • fault system behavior
  • complexity in seismicity
  • earthquake clustering
  • earthquake triggering
  • preparatory processes
  • complexity in faulting
  • fault slip styles
  • fractality
  • synchronization
  • earthquake cycle-related crustal deformation

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Published Papers (3 papers)

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Research

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17 pages, 24664 KB  
Article
Forecasting the Largest Expected Earthquake in Canadian Seismogenic Zones
by Kanakom Thongmeesang and Robert Shcherbakov
Entropy 2026, 28(2), 164; https://doi.org/10.3390/e28020164 - 31 Jan 2026
Viewed by 363
Abstract
Significant earthquakes can cause widespread infrastructure damage, social implications, and substantial economic losses. To mitigate these impacts, earthquake forecasting models have been developed to estimate earthquake occurrences and improve recovery efforts, with the Epidemic-Type Aftershock Sequence (ETAS) model being the most informative statistical [...] Read more.
Significant earthquakes can cause widespread infrastructure damage, social implications, and substantial economic losses. To mitigate these impacts, earthquake forecasting models have been developed to estimate earthquake occurrences and improve recovery efforts, with the Epidemic-Type Aftershock Sequence (ETAS) model being the most informative statistical framework for characterizing earthquake sequences. In this study, the ETAS model is used to estimate the model parameters for seismicity in Canada using the historical earthquake catalogue and to forecast long-term seismicity for seven different regions in Canada. Furthermore, the model is used to generate synthetic earthquake catalogues in order to assess its ability to replicate observed seismic patterns. The study identifies the southwestern region of Canada, associated with the coastal area of British Columbia, as being at the highest seismic risk, with a 66% exceedance probability for M7.5 events or above to occur in 30 years. In contrast, Alberta features the least seismic risk, with a 4% exceedance probability for events above 6.5 magnitude. For southeastern Canada, associated with Eastern Ontario and Southern Quebec, an exceedance probability of 74% for events above 6.0 magnitude poses the potential for significant damage due to the larger exposed population. Moreover, the resulting seismicity maps show the model’s capability for real-events analysis, but improvements are needed for further applications. Full article
(This article belongs to the Special Issue Decoding Earthquake Complexity: From Earthquake Ruptures and Slip Styles to Seismic Sequences and Faulting)
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15 pages, 2092 KB  
Article
Improved NB Model Analysis of Earthquake Recurrence Interval Coefficient of Variation for Major Active Faults in the Hetao Graben and Northern Marginal Region
by Jinchen Li and Xing Guo
Entropy 2026, 28(1), 107; https://doi.org/10.3390/e28010107 - 16 Jan 2026
Viewed by 218
Abstract
This study presents an improved Nishenko–Buland (NB) model to address systematic biases in estimating the coefficient of variation for earthquake recurrence intervals based on a normalizing function TTave. Through Monte Carlo simulations, we demonstrate that traditional NB methods [...] Read more.
This study presents an improved Nishenko–Buland (NB) model to address systematic biases in estimating the coefficient of variation for earthquake recurrence intervals based on a normalizing function TTave. Through Monte Carlo simulations, we demonstrate that traditional NB methods significantly underestimate the coefficient of variation when applied to limited paleoseismic datasets, with deviations reaching between 30 and 40% for small sample sizes. We developed a linear transformation and iterative optimization approach that corrects these statistical biases by standardizing recurrence interval data from different sample sizes to conform to a common standardized distribution. Application to 26 fault segments across 15 major active faults in the Hetao graben system yields a corrected coefficient of variation of α = 0.381, representing a 24% increase over the traditional method (α0 = 0.307). This correction demonstrates that conventional approaches systematically underestimate earthquake recurrence variability, potentially compromising seismic hazard assessments. The improved model successfully eliminates sampling bias through iterative convergence, providing more reliable parameters for probability distributions in renewal-based earthquake forecasting. Full article
(This article belongs to the Special Issue Decoding Earthquake Complexity: From Earthquake Ruptures and Slip Styles to Seismic Sequences and Faulting)
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Review

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19 pages, 2533 KB  
Review
b-Value Evaluation and Applications to Seismic Hazard Assessment
by Ying Chang, Rui Wang, Peng Han, Jinhong Wang, Miao Miao, Zhiyi Zeng, Weiwei Wu, Changsheng Jiang, Lingyuan Meng, Haixia Shi and Katsumi Hattori
Entropy 2025, 27(9), 958; https://doi.org/10.3390/e27090958 - 15 Sep 2025
Cited by 2 | Viewed by 1876
Abstract
Earthquake forecast and risk assessment are of key importance in reducing casualties and property losses. However, they have not been fully achieved due to the complexity of earthquakes. Numerous studies have explored the correspondence of the b-value with changes in effective stress, [...] Read more.
Earthquake forecast and risk assessment are of key importance in reducing casualties and property losses. However, they have not been fully achieved due to the complexity of earthquakes. Numerous studies have explored the correspondence of the b-value with changes in effective stress, leveraging temporal and spatial variations to identify precursor characteristics of destructive events in both natural and induced seismic activities. However, robust interpretation of predictive b-values hinges on rigorous estimation, as biased results can mislead conclusions. This paper provides a comprehensive review of spatiotemporal b-value estimation methods alongside statistical significance tests. A pilot b-value analysis of natural earthquakes and induced seismicity manifested the valid impression. The expansion of monitoring datasets with the development of acquisition technology or dense array and advanced estimation methodology will augment the utility of b-value analysis in seismic research and hazard assessment. Full article
(This article belongs to the Special Issue Decoding Earthquake Complexity: From Earthquake Ruptures and Slip Styles to Seismic Sequences and Faulting)
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