Earthquake Events Research Articles

Unwrap Intractable C‐Band Coseismic Interferograms: An Improved SNAPHU Method With Range Offset Gradients as Prior Information

AbstractC‐band Interferometric Synthetic Aperture Radar (InSAR) data are widely used to map coseismic deformation. However, phase unwrapping errors are commonly distributed near faults owing to decorrelation and steep phase gradients from short radar wavelengths. Here, we propose an improved SNAPHU phase‐unwrapping algorithm that considers the prior information of the range offset gradients (P‐SNAPHU) to overcome the constraints imposed by the phase continuity assumption. P‐SNAPHU exploits median filtering of homogeneous pixels for initial denoising of range offset and then refines range offset gradients divisionally through saliency extraction. The derived gradients are used to estimate the expected values of the cost functions for the low‐coherence fringes. The synthetic experiments show significant improvements in the phase‐unwrapping accuracy of the P‐SNAPHU method compared with classical unwrapping methods. We apply the P‐SNAPHU method to unwrap Sentinel‐1 coseismic interferograms of three large (Mw > 6.5) strike‐slip earthquake events that the existing classical methods could not successfully unwrap. In the comparison of the unwrapped interferograms with the external global navigation satellite system (GNSS) displacements and those from the classical methods, we find that P‐SNAPHU significantly reduces the phase unwrapping errors with the mean absolute error of 7.2, 2.3, and 1.8 cm for the 2023 Kahramanmaraş earthquake doublet, the 2016 Kumamoto earthquake, and the 2019 Ridgecrest earthquakes, respectively. Based on the unwrapped results derived from P‐SNAPHU, an estimate is made regarding the shallow slip deficit of the 2023 Kahramanmaraş earthquake doublet, which is approximately 7%. Therefore, P‐SNAPHU is useful for developing and applying C‐band InSAR data for large earthquakes and volcanic activity.

Investigating the Last Millennium Coulomb Stress Transfer in the Central Apennine Fault System (CAFS)

AbstractThe Central Apennine Fault System (CAFS) characterizes an active tectonic region of significant importance, witnessing numerous destructive seismic events over the last millennia. Although numerous studies have underscored the role of Coulomb stress transfer (CST) in initiating some of the most catastrophic earthquakes, investigations focusing on its specific influence within the CAFS are limited. This research delves into a thorough examination of the effects of CST on both historical and instrumental seismic events of significant magnitude associated with the CAFS. We selected nine seismic events for the CST investigation, dating from 1279 CE to present. Beyond analyzing the static stress transfer for each individual seismic event, the cumulative CST of recent instrumental earthquakes was also examined to provide a comprehensive overview of the current stress scenario. Leveraging an innovative approach, faults were modeled adopting a variable strike three‐dimensional elliptical shape, ensuring enhanced calculation accuracy. Significant findings emerge from the analysis: CST has played a pivotal role in either activating or inhibiting the faults of the CAFS over the centuries. Several examined instances showcase fault reactivation following increased transferred stress within relatively short time frames, while others highlight the inhibitory effect of stress shadows. Examining the differences in seismic moment release across three seismicity windows (the first one between 1300 and 1400, the second around 1700, and the last one from 1979 to 2016) reveals distinct periods of higher seismicity in the past millennium. The latter shows the lowest cumulative seismic moment, suggesting a potential seismic gap equivalent to a Mw 6.67 earthquake. Deepening our understanding of CST illuminates the role of fault interactions in past earthquake occurrences, offering valuable insights into forecasting potential future seismic sequences. This awareness is vital in crafting targeted seismic risk mitigation strategies, thereby safeguarding local communities from the profound consequences of earthquakes.

3D seismic bearing capacity of rectangular foundations near rock slopes using upper bound method

The analysis of foundation's bearing capacity is generally conducted under the assumption of plane strain. However, the damage of rectangular foundation usually presents obvious three-dimensional (3D) effect. This article considers this 3D effect, which, for the first time, provides a theoretical framework for assessing the bearing capacity of rectangular foundations placed on rock slopes under seismic condition. In order to apply the kinematic method of limit analysis, a new 3D kinematically admissible collapse mechanism is first constructed. Owing to the point-to-point discretized technique, this 3D mechanism can avoid complex surface integration and effectively reduce spatial coordinate iterative calculations while maintaining high accuracy. The pseudo-static method is adopted to simulate the effects of earthquakes. Generalized multi‑tangential technique is employed to derive the Mohr-Coulomb constants from Hoek-Brown criterion. The comparison between the present results and results of previous literatures proves the validity of the theoretical framework in this paper. Shape factor and reduction factor are introduced in the parametric study, showing that the 3D effect is more obvious when the rectangular foundation aspect ratio is reduced. As the rectangular foundation location moves away from the slope, its bearing capacity gradually converges towards that of the horizontal foundation. The critical collapse mechanism is also explored, demonstrating that the collapse extent expands with increasing internal friction angle of the rock.

Back‐Propagating Rupture: Nature, Excitation, and Implications

AbstractRecent observations show that certain rupture phase can propagate backward relative to the earlier one during a single earthquake event. Such back‐propagating rupture (BPR) was not well considered by the conventional earthquake source studies and remains a mystery to the seismological community. Here we present a comprehensive analysis of BPR, by combining theoretical considerations, numerical simulations, and observational evidences. First, we argue that BPR in terms of back‐propagating stress wave is an intrinsic feature during dynamic ruptures; however, its signature can be easily masked by the destructive interference behind the primary rupture front. Then, we propose an idea that perturbation to an otherwise smooth rupture process may make some phases of BPR observable. We test and verify this idea by numerically simulating rupture propagation under a variety of perturbations, including a sudden change of stress, bulk or interfacial property and fault geometry along rupture propagation path. We further cross‐validate the numerical results by available observations from laboratory and natural earthquakes, and confirm that rupture “reflection” at free surface, rupture coalescence and breakage of prominent asperity are very efficient for exciting observable BPR. Based on the simulated and observed results, we classify BPR into two general types: interface wave and high‐order re‐rupture, depending on the stress recovery and drop before and after the arrival of BPR, respectively. Our work clarifies the nature and excitation of BPR, and can help improve the understanding of earthquake physics, the inference of fault property distribution and evolution, and the assessment of earthquake hazard.

Near Real‐Time Earthquake Monitoring in Texas Using the Highly Precise Deep Learning Phase Picker

AbstractArtificial intelligence (AI) seismology has witnessed enormous success in a variety of fields, especially in earthquake detection and P and S‐wave arrival picking. It has become widely accepted that DL techniques greatly help routine seismic monitoring by enabling more accurate picking than traditional pickers like STA/LTA. However, a completely automatic AI‐driven earthquake monitoring framework has not been reported due to the concerns of potential false positives using DL pickers. Here, we propose a novel AI‐facilitated near real‐time monitoring framework using a recently developed deep learning (DL) picker (EQCCT) that has been deployed in the Texas seismological network (TexNet). For the West Texas area, TexNet's seismic monitoring relies on the EQCCT picker to report earthquake events. For earthquakes with a magnitude above two, the picks are further validated by analysts to output the final TexNet catalog. Due to the fast‐increasing seismicity caused by continuing oil&gas production in West Texas, this AI‐facilitated framework significantly relieves the workload of TexNet analysts. We show the mean absolute error (MAE) of automatic magnitude estimation for the magnitude‐above‐two earthquakes is smaller than 0.15 in West Texas and MAEs of hypocenter locations within 2.6 km in both distance and depth estimates. This research provides more evidence that DL pickers can play a fundamental role in daily earthquake monitoring.

A systemic approach for assessing infrastructure component importance in hazard-prone communities

Investing in pre-event disaster mitigation interventions for physical infrastructure, such as structural retrofits and enhancements, can be costly due to limited resources. To prioritize investments, infrastructure components are ranked by their criticality within the overall system. To be effective in real-world deployment, this approach must account for the complex interactions between components, as failures can occur simultaneously across large geographical areas due to the hazard footprint. As a result, hazard-specific uncertainties and spatial correlations may lead to distinctive failure patterns. In this study, we propose a novel data-driven framework leveraging Monte Carlo simulation, that harnesses the individual realizations to capture and model realistic component damage patterns under a specified hazard scenario. This framework addresses a gap in literature by moving beyond traditional methods that often treat component failures as independent events. By capturing the interdependence between bridges, primarily through failure interactions, and system-wide effects, our method provides a more comprehensive criticality assessment. The simulation data provides a foundation for the framework, which applies to a wide variety of infrastructure networks and performance metrics. To demonstrate the method's effectiveness, a simplified transportation network from Shelby County, TN subjected to an earthquake event is analyzed. The proposed framework provides an effective approach for component ranking, suitable for decision-making where human intuition and simple methods are insufficient. Its broad applicability suggests a potential for large-scale and interdependent network problems.

An end-to-end multi-task network for early prediction of the instrumental intensity and magnitude in the north–south seismic belt of China

The seismic activity in the north–south seismic belt of China is among the highest in the world. Predicting instrumental intensity and magnitude after an earthquake mitigates regional seismic disasters. The standard workflow for prediction involves building empirical formulas using characteristic parameters of the initial arrival seismic wave, but this method has limitations in accuracy. Recent data-driven models have shown promise in predicting instrument intensity and magnitude. Still, this is currently done mainly on a single-task basis and does not consider whether a multi-task model can utilize complementary information from different tasks to improve overall performance. This study proposes a data-driven multi-task model called SeismNet, which can simultaneously predict instrument intensity and magnitude. We tested the effectiveness of SeismNet using ground motion records of the north–south seismic belt of China. The model can predict instrument intensity and magnitude more rapidly and accurately than the baseline and single-task models, with increasing accuracy as the input seismic wave duration increases. We also tested the method on three destructive earthquake events (Ms > 6.5) that occurred in China and found that at 3 s after the P-wave arrival, the prediction is almost consistent with the observation. Overall, this study offers a new method for improving earthquake prediction accuracy in the North-South seismic belt of China.

Deep CO2 emissions facilitated by localized shear deformation: A case study of the Karakoram fault system, western Tibet

Strike-slip faults play a significant role in creating deeply penetrating fractures with high permeability, thus promoting rapid migration of CO2-rich fluids to the surface. However, there are rare observations regarding how strike-slip movement could affect deep CO2 emissions. Here, we focus on the Karakoram fault system (KKFS), western Tibet, to estimate diffuse soil CO2 fluxes and to unravel potential controlling factors for CO2 emissions. Average CO2 fluxes of geothermal fields range in 22–2475 g m−2 d−1, significantly higher than the across-fault profiles (6–116 g m−2 d−1). A mass balance model based on δ13C-CO2 and CO2 concentration of soil gases reveals that deep carbon constitutes 49.1–91.5 % (average = 73.9 %) and 0.2–40.5 % (average = 25.5 %) of soil-gas carbon released from geothermal fields and across-fault profiles, respectively. Deep carbon could be produced by thermal decomposition of crustal rocks considering CO2-rich fluids with radiogenic helium isotopes. Strikingly, higher CO2 fluxes preferentially occur in geothermal fields along a bending segment of the KKFS, where localized shear deformation is prominent as documented by high slip rates over geological timescales, dense splay faults, clustering of earthquake events, and elevated strain rates. We suggest that high stress acting on the KKFS bend could enhance the deformation and fracturing of fault zone rocks, leading to production of metamorphic CO2 and efficient release of CO2-rich fluids through the highly permeable fault system. Our results could shed new light on CO2 origins and fluxes of strike-slip faults that are characterized by spatially heterogeneous strain partitioning and thus localized enhanced shear deformation.

Fast Fourier Transform (FFT) Application For Short-Term Earthquake Precursor Analysis Using Geomagnetic Data (Case Study of Kupang Geomagnetic Station, East Nusa Tenggara, Indonesia)

Abstract Earthquake (EQ) precursors have been identified from ULF geomagnetic enhancements related to a moderate EQ in Kupang, East Nusa Tenggara, Indonesia. Three components of geomagnetic data (X, Y, and Z) collected during January-June 2010 were analyzed. The EQ occurred on May 7, 2010, and its epicenter was 27.78 km from the KPG Geomagnetic Station. The magnitude and depth of the EQ were 5 and 11.3 km, respectively. This study investigated the energy of ULF geomagnetic signals in the frequency range of 0.03 to 0.04 Hz using SDR based on FFT. The results showed that the geomagnetic energy increased approximately three days before the EQ. Due to the significant magnitude and relative proximity of the EQ to the observation station, it can be concluded that the closer the geomagnetic station from the EQ source, the more likely it is to detect anomalies caused by the EQ. Despite the increase in geomagnetic energy, the Dst index which measures the global activity of the geomagnetic variation in low-latitude regions does not indicate any extraordinary global geomagnetic activity. This indicates that geomagnetic anomalies are most likely related to EQ events.

The landform Deformation at the Iraq-Iran Border due to Earthquakes in the Period (2017-2018)

The study targets to assess the potential of Interferometric Synthetic Aperture Radar (InSAR) in detecting ground distortion caused by earthquakes. The inSAR technique integrates Synthetic Aperture Radar (SAR) and interferometry to reveal the slightest changes on the earth's surface through a specified period, impregnable to climate or time of day. The research analyses some scholarly articles to demonstrate the interest of InSAR in examining earthquakes and their outcome. These articles demonstrate the practical application of InSAR in enhancing fault slip analysis, ground deformation assessment, and early post-seismic changes in earthquakes. InSAR is beneficial with measurements from other tools, such as GPS and time series analysis, but it still offers valuable insights into earthquake characteristics and associated effects. The insights from these methodologies can help devise solutions to mitigate the impacts of earthquakes. In addition, the paper presents information about three earthquake swarm events and their corresponding fault types. The first event occurred on November 12th, 2017, while the second happened on November 25th, 2018. Despite their differences in magnitude and location, the second event was associated with a strike-slip fault. InSAR provides extensive practical applications, from natural hazard monitoring to infrastructure projects and topographic mapping.

Earthquake and Sleep Health Effects

Earthquake and Sleep Health Effects

Earthquake Sequence Simulation and Hazard Analysis in the Tianshan Orogenic Belt and Adjacent Areas

ABSTRACT The Tianshan orogenic belt is located in central Eurasia. Its tectonic deformation and seismicity are primarily influenced by the far-field effect of the India–Eurasia collision. It is one of the regions with the most intensive seismicity in China. Understanding the mechanisms of earthquake nucleation in this region is a hot topic in the seismicity community. The numerical simulation of earthquake sequences is an efficient measure for comprehensively exploring earthquake occurrence characteristics, tectonic loading, and subsequence patterns. It is also an important method for predicting and mitigating earthquake disasters. This study utilized a finite-element model to investigate the evolution of regional historical earthquakes via the split-node method. Coulomb failure stress analyses from interactions of simulated historical earthquakes since 1900 indicate that the Taxkorgan fault may be prone to the next significant earthquake event.

Declustering characteristics of the North China Plain seismic belt and its effect on probabilistic seismic hazard analysis

The accurate and impartial identification of background seismic activity is an important foundation for earthquake model construction and probabilistic seismic hazard analysis (PSHA). We use the Gardner and Knopoff, Reasenberg, nearest-neighbor and stochastic declustering methods to decluster in the North China Plain seismic belt, analyzing the effect of declustering. We optimize the input parameters of the algorithms through Kolmogorov-Smirnov Poisson distribution tests (e.g., the clustering threshold of the nearest-neighbor method is set to 0.6). Four algorithms demonstrate good declustering effects, removing the impact of the strong seismicity in Tangshan while retaining similar trends to all events. The occurrence of major earthquake events can significantly impact the declustering characteristics in terms of time, space and magnitude. There is a difference in the overall hazard between the four declustering algorithms and the Fifth Generation Seismic Ground Motion Parameters Zonation Map of China. The difference in seismic hazard curves is mainly influenced by the annual average occurrence rate (background rates) and the Gutenberg-Richter b value, with the effect of the b value being more pronounced. The analysis of the effect of algorithms and their impact on PSHA can provide reference for earthquake risk assessment, engineering seismic design and disaster research.

Earthquake Risk in Bangladesh: Lesson Learned from Turkiye-Morocco Earthquake

Turkey, Morocco, and Bangladesh are all located in active seismic zones of the Earth’s surface. Recent studies have predicted catastrophic earthquakes in Bangladesh in the near future. Since disasters can act as catalysts for learning by exposing the shortcomings and vulnerabilities of communities or governments, it is believed that Bangladesh has much to learn from the 2023 mega-disasters in Turkey and Morocco. Therefore, this study aims to understand the causes of the catastrophic earthquakes in Turkey and Morocco. The main objective is to analyze the strengths and weaknesses of the disaster management stages during the 2023 earthquakes in Turkey and Morocco, and to compare these with the situation in Bangladesh to better understand potential earthquake risks there. Moreover, the study seeks to develop a framework for Disaster Learning. It follows a qualitative research methodology, with most of the necessary data gathered from existing literature and Key Informant Interviews. The findings suggest that infrastructural vulnerabilities and noncompliance with land use regulations were significant causes of the catastrophic damage in Turkey and Morocco, which are also relevant to the earthquake risks in Bangladesh. Key strengths identified in Turkey include the availability of open spaces for emergency services, wide roads, modern equipment, skilled manpower, military-civilian coordination, and a robust humanitarian response—all areas where Bangladesh has significant deficiencies. Lessons from this study reveal that climatic conditions and debris management could pose major challenges for Bangladesh in the event of a significant earthquake.

Swarm Investigation of Ultra-Low-Frequency (ULF) Pulsation and Plasma Irregularity Signatures Potentially Associated with Geophysical Activity

Launched on 22 November 2013, Swarm is the fourth in a series of pioneering Earth Explorer missions and also the European Space Agency’s (ESA’s) first constellation to advance our understanding of the Earth’s magnetic field and the near-Earth electromagnetic environment. Swarm provides an ideal platform in the topside ionosphere for observing ultra-low-frequency (ULF) waves, as well as equatorial spread-F (ESF) events or plasma bubbles, and, thus, offers an excellent opportunity for space weather studies. For this purpose, a specialized time–frequency analysis (TFA) toolbox has been developed for deriving continuous pulsations (Pc), namely Pc1 (0.2–5 Hz) and Pc3 (22–100 mHz), as well as ionospheric plasma irregularity distribution maps. In this methodological paper, we focus on the ULF pulsation and ESF activity observed by Swarm satellites during a time interval centered around the occurrence of the 24 August 2016 Central Italy M6 earthquake. Due to the Swarm orbit’s proximity to the earthquake epicenter, i.e., a few hours before the earthquake occurred, data from the mission may offer a variety of interesting observations around the time of the earthquake event. These observations could be associated with the occurrence of this geophysical event. Most notably, we observed an electron density perturbation occurring 6 h prior to the earthquake. This perturbation was detected when the satellites were flying above Italy.

Developing and evaluating a risk-informed decision support system for earthquake early warning at a railway bridge

Earthquake early warning (EEW) systems provide timely information on the arrival of strong seismic waves at a site. Such information can help mitigate the consequences of earthquakes on the operation of infrastructure assets. EEW-informed mitigation actions should stem from risk-based decision-making protocols, and EEW benefits should be evaluated for the range of possible rupture scenarios that affect an asset of interest. This paper addresses these challenges specifically for railway bridges by: (1) developing a risk-informed EEW decision support system (DSS) for these assets; and (2) quantifying the effectiveness of the proposed EEW-DSS in mitigating seismic risks for railway bridges across relevant rupture scenarios. The proposed EEW-DSS combines information on site-specific seismic hazard, time-dependent EEW algorithm outputs, probabilistic seismic demand modeling, damage/derailment fragilities, and seismic loss models. These modeling components compose a multi-criteria decision-making framework. Value of information theory is then proposed to estimate the loss-mitigation benefits of the EEW-DSS, accounting for varied stakeholder risk priorities as well as dynamic lead-time/accuracy tradeoffs related to EEW performance. A railway bridge with multiple piers is adopted for the case study, which demonstrates the importance of risk-based, uncertainty-informed decision-making to the overall effectiveness of EEW in potentially reducing seismic losses.

Tsunami propagation and flooding maps: An application for the Island of Lampedusa, Sicily Channel, Italy

AbstractThe Mediterranean coastlines are densely populated zones which host key socio‐economic and commercial activities. For this reason, coastal areas are vulnerable sites in case of natural disasters as tsunamis that can strike coasts causing widespread damage to the population and facilities. For these reasons, several studies were performed over the last decade to study the impact of tsunami waves on the coasts. This research assessed the inundation risk due to a tsunami wave which can hit the southeastern coast of Lampedusa Island. The coastal low‐lying geomorphological setting of the southeastern part of the island led to significant socio‐economic growth, but Lampedusa falls within the Mediterranean Sea, a high‐tsunamigenic area, therefore, the need to investigate tsunami propagation and coastal flooding of this sensitive site emerged. For this scope, a calculation chain model was implemented incorporating three steps: the DELFT‐3D software for earthquake effects modelling, MIKE 21 Flow Model FM for nearshore propagation and HEC‐RAS for onshore tsunami inundation modelling. The simulations illustrate the impact of three tsunami scenarios with different magnitudes (Mw 8.5, 7.5, 6.5) generated by hypothetical earthquakes in the Hellenic Arc. In the Mw 8.5 magnitude scenario, significant flooding occurs in the harbour region, with maximum water depths reaching approximately 3.5 m. The maximum water velocity in this scenario reaches about 15 m/s in the eastern portion, adjacent to cliffs impacted by the tsunami wave. In contrast, the Mw 7.5 magnitude scenario demonstrates reduced flooded areas, with the cliffs containing the waves and preventing further flooding. Water depths and velocities in the Mw 7.5 scenario remain minimal. Changes in both propagation and flooding are not significant between scenarios Mw 7.5 and Mw 6.5. This methodology can be employed for more accurate tsunami wave simulations not only in the Mediterranean region but also in various case studies.

A Case Study on the Effect of Multiple Earthquakes on Mid-rise RC Buildings with Mass and Stiffness Irregularity in Height

A Case Study on the Effect of Multiple Earthquakes on Mid-rise RC Buildings with Mass and Stiffness Irregularity in Height

The Idea of ‘Loosening the Bond Between Ground and Structure’ in Antiquity and Archaeological Evidence on Antiseismic Foundations

Antiseismic structures in antiquity are often overlooked or disputed by those working in the field, even though they are not mentioned in written sources. At the very least, it should be recognized that some of the traditional structures and building techniques of ancient cultures in Anatolia and surrounding regions were antiseismic before today’s concrete structures. In fact, these techniques were sometimes applied over a wide geographical area and sometimes in a narrower region, as if under the control of a central government, administration or idea, and continue to be used for a long time. Archaeological studies reveal that some construction methods were widely used to support structures affected by dynamic loads. Such methods were applied and developed by engineers, architects and artisans who were fully aware of the effects of earthquakes on structures. Therefore, antiseismic structures must have emerged due to awareness of earthquake hazards. Wood in foundations and walls in Anatolia in the Bronze Ages, sand in Mesopotamia and Egypt, sand, ash, coal and lime in Greek architecture, and opus caementicum in Rome were applied in and under the foundation in more durable or long-lasting building construction techniques. Undoubtedly, wood and wood foundations have been known and used since the Bronze Age. Unfortunately, with the emergence of new materials and technologies, the traditional architectural understanding of Anatolia was almost wholly removed from construction practice. As in modern constructions, in archaeological studies, attention is paid to the structures’ above- ground units, while the underground foundation sections are overlooked. Data about the use of wood in the groundwork is sometimes discovered by chance. This article demonstrates that the idea of loosening the bond between structure and ground was known in ancient times. Although the technical solutions used in the past match the principles of base insulation, it is arguable whether they are genuinely antiseismic as they are today.

Artificial intelligence for assessing the planets' positions as a precursor to earthquake events

Questions about interconnection possibilities between planets’ positions and seismic events on the earth have emerged recently in TV channels, social media, etc. In this study, an Artificial Neural Network (ANN) and Random Forest Regression (RFR) are used to predict the number of earthquakes that can occur on Earth, depending on the Earth’s position relative to other planets and solar positions. Our new integration dataset contains 9809 observations and nine features firstly from the global earthquake archive, which is an authoritative layer by Esri, and secondly from the accurate data web portal “theskylive.com.”.The results obtained from RFR and ANN prove the partial influence of planets positions on sesimic activity on the earth. In other words, quantitatively through the ANN that gets an accuracy of 68.27 %, MAE of 5.36, MSE of 52.78, RMSE of 7.26, R-Squared of 0.65, and also through the RFR that gets an accuracy of 65.06 %, MAE of 5.60, MSE of 58.21, RMSE of 7.63, R-Squared of 0.67, prove the partial influence on one hand. Qualitatively through the curve of the training phase of the ANN, which is a decreasing and convex function, reinforces the aforementioned proof on the other hand. For these reasons, it can be deduced that there is a possible connection between tectonic stress triggers and the positions of the planets in the solar system. Our dataset was uploaded to the github(https://github.com/mouddentarik/Earthquake01.) as well as the code will be publicly available at the github(https://github.com/mouddentarik/PythonCode_Earthquakes-.) to share our results.