Search Results (68)

An earthquake lethality model was employed to assess the casualty distribution in Yunnan, Guizhou, and Sichuan provinces, taking into account the ground motion acceleration with different 50-year exceedance probabilities. When the probability is 63%, fatalities are predominantly concentrated in central and south-western Yunnan, as well as central, southern, and western Sichuan. At a 10% probability, the peaks of the casualties are observed in southern, eastern, and central Sichuan. In Yunnan (excluding the northwest and southeast regions), the casualty density exhibits unevenness, whereas Guizhou experiences relatively low casualties (except in the eastern and western mountainous areas). Xichang incurs the most substantial losses, followed by Lancang. Xundian, Songming, and Dongchuan demonstrate a high propensity for fatalities, and the risk is relatively high in the vicinity of the Longjiang and Nujiang faults. If a destructive earthquake occurs near these areas within the next 50 years, the probability of a Level-I emergency response exceeds 10%. When the ground motion acceleration doubles (especially when the exceedance probability drops to 2% in 50 year and 0.1% in a year), the predicted number of casualties remains relatively stable. However, the grid of the casualty population exhibits a higher degree of spatial concentration of casualties, and the disaster-affected area expands. There exists no linear correlation between earthquake-induced fatalities and the ground motion level. When the 50-year exceedance probability decreases from 63% to 10%, the casualty rate may increase by several dozen times. Full article

Baguio City, a highly populated city in the mountainous portion of the Cordillera, is vulnerable to earthquake hazards due to its proximity to earthquake generators. For this reason, identifying its threats by generating seismic hazard assessments such as peak ground acceleration (PGA) is one of the important necessities to be considered in order to mitigate damages and reduce casualties. Further, the effects of topography, aside from the site conditions, play an important role in the amplification of ground motions. In this study, a peak ground acceleration (PGA) is generated with the influence of topographic effects. Data gathered from geophysical surveys were utilized as inputs in generating the site amplification for Baguio City. The amplification values are then incorporated into the composite peak ground acceleration (PGA) generated by simulating each individual fault source surrounding Baguio City, thereby generating the final PGA for Baguio City. Results revealed that 39% of Baguio City may experience a ground acceleration value of 0.71 g to 0.8 g. Specific places, such as the Pinsao Proper area, may experience higher acceleration. Full article

A key component of research on disaster risk in modern-age society in the inland areas of the Campania Region, southern Italy, was discovered in parish registers. Ecclesiastical archives, containing thousands of largely unpublished pages, served as a rich source of information on disruption and casualties. The parish registers preserved in these archives from the 16th century provide demographic records as well as notes on the most terrible events that affected society at the time. They include the catastrophic effects of seismic events recorded in this sector of the southern Apennines, an area characterised by high seismicity due to the complex dynamics of the convergence zone between the African and Eurasian plates. New findings reveal a more precise number and previously unreported deaths in several villages, confirming and suggesting some macroseismic intensities for the 1694 seismic event; moreover, further evidence was found for the hypothesised 1692 seismic event. A greater number of deaths was observed in some villages during the 1702 and 1732 events. Parish documents provided details about local construction techniques adopted after the well-known earthquake of 1732, including the use of more resilient materials and design modifications. Full article

Afghanistan is located within one of the world’s most seismically active regions, where recurrent earthquakes pose a persistent threat to human life and the built environment. The 7 October 2023 Herat earthquake exposed critical vulnerabilities in both the construction sector and institutional frameworks, manifested through the widespread presence of non-engineered buildings, poor construction quality, and the absence of mandatory and enforceable seismic design regulations. This study examines the structural, construction-related, and governance deficiencies that significantly contributed to extensive building damage and high casualty rates, while also assessing shortcomings in public preparedness and disaster risk governance. A comparative case-study approach is adopted to evaluate seismic resilience and disaster management practices in India, Pakistan and Iran. The findings indicate that the elevated vulnerability observed in Herat primarily resulted from deficient construction practices, the lack of codified seismic standards, weak regulatory enforcement, and limited technical capacity within the construction industry. In contrast, regions characterized by well-established seismic codes, engineered structural systems, and coordinated institutional mechanisms experienced substantially reduced levels of structural damage and human losses, although earthquake impacts are also influenced by factors such as hazard characteristics, site conditions, exposure levels, and population distribution. The study highlights that seismic safety and sustainable development are inherently interdependent objectives. Improving earthquake resilience in Afghanistan requires the integration of earthquake-resistant engineering with sustainable construction practices, enhancement of technical and professional capacity, rigorous enforcement of region-specific seismic regulations, and strengthened community-based awareness programs. The adoption of internationally recognized best practices and risk-informed planning strategies is essential for fostering safer, more resilient, and environmentally sustainable urban development capable of withstanding future seismic events. Full article

The earthquake doublet on 6 February 2023 served as an important test in Türkiye. It helped assess the vulnerability of Türkiye’s building stock under different seismic loading conditions across a large region. The widespread destruction and casualties observed in heavily damaged cities following the 6 February 2023 earthquakes served as a warning. This urged a re-evaluation of the seismic performance assessment framework and risk mitigation strategies. Seismic isolation technology is considered the best method for earthquake-resilient design. Passive control systems are primarily preferred for use in critical facilities, such as healthcare complexes and data centers. Properly designed seismically isolated hospital buildings exhibited superior performance during the 6 February 2023 earthquakes compared to fixed-base counterparts. However, their use in residential buildings in Türkiye is still limited due to impediments such as stringent code requirements and peer review processes. This study evaluates the effectiveness of the ELF procedure in the Turkish Seismic Design Code-2018, incorporating two site-specific studies and earthquake record scaling in Antakya city center. Moreover, it examines the influence of considering directivity effects for using seismic isolation systems in regions with high seismicity. An effective and rapid evaluation procedure is employed for the inelastic response of seismically isolated residential buildings in accordance with the TSDC-2018 without needing any particular academic or commercial software. A suite of differential equations using the design parameters is arranged to represent the overall dynamics of seismically isolated buildings. Disregarding the directivity effects in site-specific studies for the selected construction site in Antakya city center can result in large earthquake demands and careful attention should be given to reconstruction studies for urban planning and more detailed studies should be carried out including other complex mechanisms experienced during the 6 February 2023 Türkiye earthquake doublet. Full article

Afghanistan experiences frequent damaging earthquakes, and the widespread use of unreinforced adobe and Pakhsa construction leads to high casualty rates and severe housing losses. Traditional earthen buildings exhibit low tensile capacity, rapid stiffness degradation, and brittle failure, often collapsing at drift levels below 0.5–0.6% or at modest ground motions. Reinforcement techniques evaluated in international experimental studies—such as timber confinement, flexible steel wire mesh, geogrids, and high-quality plastic fencing—have demonstrated measurable improvements, including 30–200% increases in lateral strength, three- to seven-fold increases in ductility, and out-of-plane capacity enhancements of more than two-fold when properly anchored. This study synthesises research findings and global earthen building codes and guidelines to develop a practical, context-appropriate benchmark house model for Afghanistan. The proposed model integrates representative wall geometries, concentrated flat-roof loading, and realistic construction capabilities observed across the country. Three reinforcement alternatives are presented, each designed to be low-cost, compatible with locally available materials, and constructible without specialised equipment. By linking quantitative performance evidence with context-specific construction constraints, the study provides a technically grounded and implementable pathway for improving the seismic safety of rural earthen dwellings in Afghanistan. The proposed benchmark model offers a robust foundation for future national guidelines and for the design and retrofitting of safer, more resilient housing. Full article

Dam collapse is a catastrophic event involving an artificial reservoir usually filled with water for hydropower or irrigation purposes. Several cases of dam collapses have overwhelmed entire valleys, reconfiguring their geomorphology, redesigning their landscape, and causing several thousand casualties. These episodes led to more careful regulations and the activation of more effective monitoring and mitigation strategies. A fundamental tool in defining appropriate procedures for alert and risk scenarios is the Dam Emergency Plan (PED), an operational document that establishes the actions and procedures required to manage potential hazards (e.g., geo-hydrological and seismic risk). The aim of this study is to describe a reference methodology for identifying geo-hydrological criticalities based on historical and geomorphological data, applied to civil protection activities. A further objective is to provide a structured inventory of Italian reservoirs, assigning each a potential risk index based on an analytical approach considering several factors (age and construction methodology of the dam, morphological and environmental settings, anthropized environment, and exposed population). The approach identifies that the most significant change in risk over time is not only the dam itself but also the transformation of the territory. This methodology does not incorporate probabilistic forecasting of flood or climate change; instead, it objectively characterizes the exposed territory, offering insights into existing vulnerabilities on which to base effective mitigation strategies. Full article

Earthquakes are unpreventable natural disasters that result in many casualties and economic losses in the regions where they occur. Earthquake prediction and seismic risk assessments are essential in minimising these losses. Due to the complex nature of seismic events, it is necessary to use a cutting-edge methodology to predict earthquake occurrence effectively. Machine learning methods have been among the most efficient and current methods for solving complex nonlinear problems and analysing big datasets. Because of this feature, they are widely used for predicting earthquakes and earthquake parameters. This study focuses on applying machine learning methods to analyse seismic events in Western Turkey from 1975 to 2024. The aim is to compare the effectiveness of five machine learning approaches for predicting earthquake magnitudes: Long Short-Term Memory (LSTM), Adaptive Neuro-Fuzzy Inference Systems (ANFIS), Decision Tree (DT), Random Forest (RF), and Convolutional Neural Network (CNN). The outcomes of these applied methods are encouraging in terms of the prediction of magnitude. Among all the results, the LSTM method is slightly more successful than the other methods, with a Root Mean Square Error (RMSE) of 0.1391, Mean Square Error (MSE) of 0.0193, Mean Absolute Error (MAE) of 0.1046 and Mean Absolute Percentage Error (MAPE) of 3.0631%, respectively. Full article

Widespread casualties and property damage due to structural failures following devastating earthquakes have once again highlighted the critical significance of evaluating the seismic performance of existing buildings. In this context, a fundamental part of modern pre-disaster management is to evaluate the potential seismic risks of existing structures and implementing the necessary precautions. This study focuses on determining regional risk priorities using a rapid assessment methodology applied to a sample of reinforced-concrete (RC) structures in the Centre of Bitlis city, situated in the high-seismic-risk Lake Van Basin. Risk prioritization was made among the buildings based on the Turkish Rapid Assessment technique revised in 2019 for 100 different RC buildings with one to seven stories. The negative parameters utilized in this method were analyzed both in relation to the 6 February 2023, Kahramanmaraş earthquakes and the assessed building stock. Additionally, the study provides a comprehensive review of the existing building inventory across the region and offers recommendations for potential precautions to mitigate earthquake risks. Full article

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

Coseismic landslides are geological events in which slopes, either on the verge of instability or already in a fragile state, experience premature failure due to seismic shaking. On 5 September 2022, an Ms 6.8 earthquake struck Luding County, Sichuan Province, China, triggering numerous landslides that caused severe casualties and property damage. This study systematically interprets 13,717 coseismic landslides in the Luding earthquake’s epicentral area, analyzing their spatial distribution concerning various factors, including elevation, slope gradient, slope aspect, plan curvature, profile curvature, surface cutting degree, topographic relief, elevation coefficient variation, lithology, distance to faults, epicentral distance, peak ground acceleration (PGA), distance to rivers, fractional vegetation cover (FVC), and distance to roads. The analytic hierarchy process (AHP) was improved by incorporating frequency ratio (FR) to address the subjectivity inherent in expert scoring for factor weighting. The improved AHP, combined with the Pearson correlation analysis, was used to identify the dominant controlling factor and assess the landslide susceptibility. The accuracy of the model was verified using the area under the receiver operating characteristic (ROC) curve (AUC). The results reveal that 34% of the study area falls into very-high- and high-susceptibility zones, primarily along the Moxi segment of the Xianshuihe fault and both sides of the Dadu river valley. Tianwan, Caoke, Detuo, and Moxi are at particularly high risk of coseismic landslides. The elevation coefficient variation, slope aspect, and slope gradient are identified as the dominant controlling factors for landslide development. The reliability of the proposed model was evaluated by calculating the AUC, yielding a value of 0.8445, demonstrating high reliability. This study advances coseismic landslide susceptibility assessment and provides scientific support for post-earthquake reconstruction in Luding. Beyond academic insight, the findings offer practical guidance for delineating priority zones for risk mitigation, planning targeted engineering interventions, and establishing early warning and monitoring strategies to reduce the potential impacts of future seismic events. Full article

China is one of the countries severely affected by earthquakes, making precise and timely identification of earthquake precursors essential for reducing casualties and property damage. A novel method is proposed that combines a rock acoustic emission (AE) detection technique with deep learning methods to facilitate real-time monitoring and advance earthquake precursor detection. The AE equipment and seismometers were installed in a granite tunnel 150 m deep in the mountains of eastern Guangdong, China, allowing for the collection of experimental data on the correlation between rock AE and seismic activity. The deep learning model uses features from rock AE time series, including AE events, rate, frequency, and amplitude, as inputs, and estimates the likelihood of seismic events as the output. Precursor features are extracted to create the AE and seismic dataset, and three deep learning models are trained using neural networks, with validation and testing. The results show that after 1000 training cycles, the deep learning model achieves an accuracy of 98.7% on the validation set. On the test set, it reaches a recognition accuracy of 97.6%, with a recall rate of 99.6% and an F₁ score of 0.975. Additionally, it successfully identified the two biggest seismic events during the monitoring period, confirming its effectiveness in practical applications. Compared to traditional analysis methods, the deep learning model can automatically process and analyse recorded massive AE data, enabling real-time monitoring of seismic events and timely earthquake warning in the future. This study serves as a valuable reference for earthquake disaster prevention and intelligent early warning. Full article

The main causes of damage include poor site selection, such as building on fault lines or on fill soil, as well as deficiencies in design, materials, and workmanship. Damage levels are also linked to the economic conditions of the region. In the 1939 earthquake, there were high casualties due to the magnitude of the earthquake, lack of engineering design in traditional structures and unsuitable soil conditions. Similarly, in the 1992 earthquake, unexpected damage occurred due to faulty designs created by inexperienced engineers who lacked sufficient knowledge of the seismic behavior of structures, errors in craftsmanship and workmanship, and unsuitable residential area selection for construction. These problems continue today and put most of the building stock at risk in case of a major earthquake. Seismic steel isolators are used in two new buildings in the city; if they are effective, they should be made mandatory in new construction. Otherwise, consideration should be given to relocating the city to the more stable southern rocky areas, which were unaffected in both 1939 and 1992. Full article

Induced seismicity resulting from mining activities is one of the major challenges faced by the mining industry. Although such events have been documented for over a century in countries with extensive mining traditions, such as Canada, Australia, and Chile, their impact has intensified over time. This increase is primarily attributed to the greater extraction depths, where elevated stress levels and environmental conditions heighten the likelihood of rockburst occurrences. Seismic events within mines lead to significant human casualties and substantial infrastructure damage, necessitating the implementation of various safety protocols. Among these, seismic indicators are employed to identify periods when high-magnitude seismic events are most likely to occur through the analysis of parameters such as magnitude, energy, time, and decay rate. In this context, the present study aims to utilize the accumulated frictional energy generated by microearthquakes within the Bobrek mine, Poland, as a seismic indicator (variation of frictional energy in time), establishing its correlation with the occurrence of high-magnitude seismic events exceeding the background activity. Thousands of combinations of seismic parameters were tested to maximize the performance of this frictional energy-based indicator, parameters such as moment magnitude, frictional energy, and rock properties. The optimal set of parameters was determined using the Piece Skill Score (PSS) and subsequently applied to the Accumulated Frictional Heat (AFH) methodology. According to the results, the seismic indicator forecasts 86.6% of events with magnitudes M_w ≥ 2.3, with an average forecasting time of 9.76 h, indicating that, on average, these events can be anticipated approximately 10 h before their occurrence. Full article

Earthquakes and the secondary hazards they trigger, such as landslides, collapses, and debris flows, profoundly reshape the land surface and cause significant casualties, property damage and ecological disruption. This study collected 312 strong ground motion records from 19 seismic events in China, with magnitudes ranging from Ms5.2 to Ms8.0. Using the Newmark sliding block method and programming, permanent displacements for earthquake-induced landslides with varying yield accelerations were calculated. Two models (Model 1 and Model 2) for predicting permanent displacements of earthquake-induced landslides were developed through multiple regression analysis. Results show that the goodness of fit (R²) for the permanent displacement (logu) in Model 1 and Model 2 is 0.866 and 0.923, respectively. Model 2 incorporates higher-order terms of yield acceleration ratio (a_y/PGA), which effectively reduce nonlinearity in the residuals observed in Model 1 and enhance its accuracy. Finally, these models were compared with classical empirical models. Models 1 and 2, by calculating permanent displacement from ground motion data, provide critical insights into the mechanisms of earthquake-induced landslides, and play a key role in enhancing emergency response strategies for seismic geological hazards. Full article