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Geosciences
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Earthquake Hazard Modelling
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Earthquake Hazard Modelling

A special issue of Geosciences (ISSN 2076-3263). This special issue belongs to the section "Natural Hazards".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 1408

Special Issue Editors

Dr. Cristiano Fidani

E-Mail Website
Guest Editor
Istituto Nazionale di Geofisica e Vulcanologia, Rome, Italy
Interests: statistical analysis of time series; electromagnetic interactions; earthquake forecasting; magnetic field effects; macroscopic earthquake phenomena; electric field effects; statistical correlations and effects; ionization effects; statistical correlation; climate
Prof. Dr. Pan Xiong

E-Mail Website
Guest Editor
Institute of Earthquake Forecasting, China Earthquake Administration, Beijing, China
Interests: satellite big data; AI-based earthquake anomaly detection; intelligent recognition systems; earthquake prediction models; machine learning in seismology
Dr. Serena D'Arcangelo

E-Mail Website
Guest Editor
Istituto Nazionale di Geofisica e Vulcanologia, Rome, Italy
Interests: time series forecasting; earthquake prediction

Special Issue Information

Dear Colleagues,

We invite you to contribute an original research paper to the Special Issue on “Earthquake Hazard Modeling”. Earthquakes, with their catastrophic effects, are natural phenomena that are studied from various perspectives to understand their triggering mechanisms and improve our predictive capabilities to mitigate damage. Over the past decade, numerous studies have proposed seismic hazard models (SHMs) utilizing earthquake catalogs, consistent tectonic zonation, geological data, active fault datasets and subduction zone sources. The primary goal of these models is to generate hazard curves, maps and uniform hazard spectra for the regions that are most affected by seismic events.

This Special Issue welcomes contributions across a wide spectrum of research areas and case studies focused on seismic hazard modeling and earthquake risk mitigation. We encourage submissions on a variety of topics, including but not limited to physics-based seismicity models, ground motion models, site response characterization and the limitations of seismic hazard analyses. Additionally, we invite studies that incorporate machine learning techniques and advanced statistical methods in the context of seismic hazard assessment.

Dr. Cristiano Fidani
Prof. Dr. Pan Xiong
Dr. Serena D'Arcangelo
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Geosciences 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 1800 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

  • seismic hazard modeling
  • machine learning
  • ground motion modeling
  • site response characterization
  • earthquake forecasting

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Published Papers (2 papers)

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Research

16 pages, 6946 KiB  
Article
Earthquake Damage Susceptibility Analysis in Barapani Shear Zone Using InSAR, Geological, and Geophysical Data
by Gopal Sharma, M. Somorjit Singh, Karan Nayak, Pritom Pran Dutta, K. K. Sarma and S. P. Aggarwal
Geosciences 2025, 15(2), 45; https://doi.org/10.3390/geosciences15020045 - 1 Feb 2025
Viewed by 379
Abstract
The identification of areas that are susceptible to damage due to earthquakes is of utmost importance in tectonically active regions like Northeast India. This may provide valuable inputs for seismic hazard analysis; however, it poses significant challenges. The present study emphasized the integration [...] Read more.
The identification of areas that are susceptible to damage due to earthquakes is of utmost importance in tectonically active regions like Northeast India. This may provide valuable inputs for seismic hazard analysis; however, it poses significant challenges. The present study emphasized the integration of Interferometric Synthetic Aperture Radar (InSAR) deformation rates with conventional geological and geophysical data to investigate earthquake damage susceptibility in the Barapani Shear Zone (BSZ) region of Northeast India. We used MintPy v1.5.1 (Miami INsar Timeseries software in PYthon) on the OpenSARLab platform to derive time series deformation using the Small Baseline Subset (SBAS) technique. We integrated geology, geomorphology, gravity, magnetic field, lineament density, slope, and historical earthquake records with InSAR deformation rates to derive earthquake damage susceptibility using the weighted overlay analysis technique. InSAR time series analysis revealed distinct patterns of ground deformation across the Barapani Shear Zone, with higher rates in the northern part and lower rates in the southern part. The deformation values ranged from 6 mm/yr to about 18 mm/yr in BSZ. Earthquake damage susceptibility mapping identified areas that are prone to damage in the event of earthquakes. The analysis indicated that about 46.4%, 51.2%, and 2.4% of the area were low, medium, and high-susceptibility zones for earthquake damage zone. The InSAR velocity rates were validated with Global Positioning System (GPS) velocity in the region, which indicated a good correlation (R2 = 0.921; ANOVA p-value = 0.515). Additionally, a field survey in the region suggested evidence of intense deformation in the highly susceptible earthquake damage zone. This integrated approach enhances our scientific understanding of regional tectonic dynamics, mitigating earthquake risks and enhancing community resilience. Full article
(This article belongs to the Special Issue Earthquake Hazard Modelling)
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20 pages, 14857 KiB  
Article
Modification of IPI Method for Extraction of Short-Term and Imminent OLR Anomalies and Case Study of Two Large Earthquakes
by Maoning Feng, Pan Xiong, Weixi Tian, Yue Liu, Changhui Ju, Cheng Song and Yongxian Zhang
Geosciences 2024, 14(12), 325; https://doi.org/10.3390/geosciences14120325 - 1 Dec 2024
Viewed by 692
Abstract
The Pattern Informatics Method (PI) was initially developed for medium-to-long-term earthquake prediction by analyzing changes in seismic activity. It has since been refined and extended to identify ionospheric anomalies associated with earthquakes. Notable advancements include the development of modified and improved methods, which [...] Read more.
The Pattern Informatics Method (PI) was initially developed for medium-to-long-term earthquake prediction by analyzing changes in seismic activity. It has since been refined and extended to identify ionospheric anomalies associated with earthquakes. Notable advancements include the development of modified and improved methods, which have demonstrated their capability to detect significant short-term and ionospheric anomalies preceding earthquake events. In this study, the IPI method was applied to infrared satellite observation data for the first time, and a new algorithm for extracting short-term and imminent anomalies from infrared earthquakes was explored based on the IPI method, from which we obtained the MIPI (Modified Improved Pattern Informatics Method). Using 1° × 1° nighttime Outgoing Longwave Radiation (OLR) data from NOAA_18 satellites of the National Oceanic and Atmospheric Administration’s Climate Prediction Center (NOAA-CPC) of the United States, the evolution of OLR anomalies before the Ridgecrest Ms 6.9 earthquake in the United States on 6 July 2019 as recorded by the China Earthquake Networks Center (CENC) and the Maduo Ms 7.4 earthquake in China on 21 May 2021 as recorded by the China Earthquake Networks Center (CENC) were studied. In order to make the IPI method suitable for the calculation of OLR data, two modifications were made to the IPI algorithm: (1) the quartile method was applied for automatically determining the abnormal changes in the OLR observation data and they were used as the input data instead of ionospheric data; (2) the standard deviation of the multi-year OLR residual data of each grid was used instead of the maximum anomaly index used in the original method to re-assign and obtain the relative anomaly index, and finally the anomaly evolution time series diagram was drawn. The results show the following: (1) The MIPI method can effectively extract short-term and imminent OLR anomalies prior to earthquakes. (2) Short-term and imminent OLR anomalies appeared about two weeks before each earthquake and lasted until the earthquake occurrence, disappearing after the earthquake. During this process, the anomalies exhibited a certain evolutionary trend. (3) The short-term and imminent OLR anomalies prior to each earthquake were distributed near the epicenter or near the seismogenic fault, about 200 KM away from the epicenters. The above results are similar to the spatiotemporal evolution characteristics of seismic infrared short-term anomalies previously studied, which indicates that the MIPI method can effectively extract seismic infrared anomalies and might provide a practical method for the extraction of seismic infrared short-term and imminent anomalies. Full article
(This article belongs to the Special Issue Earthquake Hazard Modelling)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Seismic Site Amplification Characteristics of Makran Subduction Zone using 1D Non-Linear Ground Response Analysis
Author: Ahmad
Highlights: • Conducted 1D Nonlinear Ground Response Analysis for representative site profiles in the Gwadar region within the Makran Subduction Zone. • Generated a target response spectrum to ensure compatibility with anticipated seismic events. • Analyzed variations in shear stress ratio, PGA, and shear strain. • Assessed site amplification characteristics for stiff and soft soils, comparing proposed design spectra with code spectra to identify discrepancies.

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