Search Results (963)

Recently, the usage of mobile phone-based games has increased due to the growing accessibility and convenience they provide. Using a descriptive-quantitative design, a disaster-based mobile application was developed in this study to enhance disaster literacy among the private senior high schools in science, technology, engineering, and mathematics (STEM) education in Davao City, the Philippines. The developed application was provided together with survey questionnaires to 364 students randomly selected from different schools in Davao City usingF a simple random sampling method. The technology acceptance (TAM) model was used to explain how users accepted the new technology. The mobile application was designed with features in four disaster scenarios—fire, flood, volcano, and earthquake. The results revealed a high acceptance, with an average score of the perceived usefulness (PE) of 4.52, perceived ease of use (PEOU) of 4.44, and a behavioral intention (BI) of 4.12. The students accepted the application to enhance disaster risk reduction and management. Aligned with SDG 4 and SDG 11, the application can be used to equip users with the knowledge to respond to disasters and ensure community resilience. Full article

Earthquakes, as one of the most destructive natural disasters, often cause significant casualties and severe economic losses. Accurate prediction of earthquake fatalities is of great importance for pre-disaster prevention and mitigation planning, as well as post-disaster emergency response deployment. To address the challenges of small sample sizes, high dimensionality, and strong nonlinearity in earthquake fatality prediction, this paper proposes an integrated modeling approach (PCA-IWOA-XGBoost) combining Principal Component Analysis (PCA), the Improved Whale Optimization Algorithm (IWOA), and Extreme Gradient Boosting (XGBoost). The method first employs PCA to reduce the dimensionality of the influencing factor data, eliminating redundant information and improving modeling efficiency. Subsequently, the IWOA is used to intelligently optimize key hyperparameters of the XGBoost model, enhancing the prediction accuracy and stability. Using 42 major earthquake events in China from 1970 to 2025 as a case study, covering regions including the west (e.g., Tonghai in Yunnan, Wenchuan, Jiuzhaigou), central (e.g., Lushan in Sichuan, Ya’an), east (e.g., Tangshan, Yingkou), north (e.g., Baotou in Inner Mongolia, Helinger), northwest (e.g., Jiashi in Xinjiang, Wushi, Yongdeng in Gansu), and southwest (e.g., Lancang in Yunnan, Lijiang, Ludian), the empirical results showed that the PCA-IWOA-XGBoost model achieved an average test set accuracy of 97.0%, a coefficient of determination (R²) of 0.996, a root mean square error (RMSE) and mean absolute error (MAE) reduced to 4.410 and 3.430, respectively, and a residual prediction deviation (RPD) of 21.090. These results significantly outperformed the baseline XGBoost, PCA-XGBoost, and IWOA-XGBoost models, providing improved technical support for earthquake disaster risk assessment and emergency response. Full article

The coastal developments in the Middle East put low priority on tsunami risk assessment due to the rare occurrence and absence of genuine tsunami track records on the coastline in the past. Tsunami-vulnerable coasts, including the east coast of the UAE, need to prepare for, and pay attention to, the impact of future tsunamis due to increased earthquake activity in the region. This study investigated the tsunami characteristics of the nearshore from hypothetical tsunami conditions by applications of numerical modeling and Artificial Neural Network (ANN) methods. The modeling results showed that the maximum tsunami depth at the shore was highest in Khor Fakkan and Mirbih for the given tsunami boundary conditions, while the tsunami withdrawal was greater on the southern bathymetry compared to that on the northern bathymetry when the tsunami period increased. ANN results confirmed that the still sea depth and seabed slope were more important than the tsunami period when predicting the maximum tsunami depth at the shore. Full article

After the 2011 earthquake, lake water depletion has become a widespread issue in Sikkim, especially in regions classified as high to very high seismic zones, where many lakes have turned into seasonal water bodies. This study investigates Chochen Lake in the Barapathing area of Sikkim’s Pakyong district, which is facing severe water seepage and instability. The problem, intensified by the 2011 seismic event and ongoing local construction, is examined through subsurface fracture mapping using Vertical Electrical Sounding (VES) and profiling techniques. A statistical factor method, applied to interpret VES data, helped identify fracture patterns beneath the lake. Results from two sites (VES-1 and VES-2) reveal significant variations in weathered and semi-weathered soil layers, indicating fractures at depths of 17–50 m (VES-1) and 20–55 m (VES-2). Higher fracture density near VES-1 suggests increased settlement risk and ground displacement compared to VES-2. Contrasting resistivity values emphasize the greater instability in this zone and the need for cautious construction practices. The findings highlight the role of seismic-induced fractures in ongoing water depletion and underscore the importance of continuous dewatering to stabilize the swampy terrain. Full article

In this study, we analyzed the lithospheric seismic background of the Tianshan and adjacent areas by combining various geophysical methods (effective elastic thickness, time-varying gravity, apparent density, and InSAR), and explored the genesis mechanism of the Wushi Ms7.1 earthquake as an example, which led to the following conclusions: (1) The effective elastic thickness (Te) of the Tianshan lithosphere is low (13–28 km) and weak, while the Tarim and Junggar basins have Te > 30 km with high intensity, and the loads are all mainly from the surface (F < 0.5). Earthquakes occur mostly in areas with low values of Te. (2) Medium and strong earthquakes are prone to occur in regions with alternating positive and negative changes in the gravity field during the stage of large-scale reverse adjustment. It is expected that the risk of a moderate-to-strong earthquake occurring again in the vicinity of the survey area between 2025 and 2026 is relatively high. (3) Before the Wushi earthquake, the positive and negative boundaries of the apparent density of the crust at 12 km shifted to be approximately parallel to the seismic fault, and the earthquake was triggered after undergoing a “solidification” process. (4) The Wushi earthquake is a leptokurtic strike-slip backwash type of earthquake; coseismic deformation shows that subsidence occurs in the high-visual-density zone, and vice versa for uplift. The results of this study reveal the lithosphere-conceiving environment of the Tianshan and adjacent areas and provide a basis for regional earthquake monitoring, early warning, and post-disaster disposal. Full article

On 22 May 2012, a magnitude Mw 5.6 earthquake struck the Pernik region of western Bulgaria, causing structural damage in nearby cities, including Sofia. This study assesses the seismic response of a six-story reinforced concrete building in central Sofia, utilizing real accelerogram data recorded at the basement (SGL1) and sixth floor (SGL2) levels during the earthquake. Using the Kanai–Yoshizawa (KY) model, the study estimates inter-story motion and assesses amplification effects across the structure. Analysis of peak ground acceleration (PGA), velocity (PGV), displacement (PGD), and spectral ratios reveals significant dynamic amplification of peak ground acceleration and displacement on the sixth floor, indicating flexible and dynamic behavior, as well as potential resonance effects. The analysis combines three spectral techniques—Horizontal-to-Vertical Spectral Ratio (H/V), Floor Spectral Ratio (FSR), and the Random Decrement Method (RDM)—to determine the building’s dynamic characteristics, including natural frequency and damping ratio. The results indicate a dominant vibration frequency of approximately 2.2 Hz and damping ratios ranging from 3.6% to 6.5%, which is consistent with the typical damping ratios of mid-rise concrete buildings. The findings underscore the significance of soil–structure interaction (SSI), particularly in sedimentary basins like the Sofia Graben, where localized geological effects influence seismic amplification. By integrating accelerometric data with advanced spectral techniques, this research can enhance ongoing site-specific monitoring and seismic design practices, contributing to the refinement of earthquake engineering methodologies for mitigating seismic risk in earthquake-prone urban areas. Full article

Modeling mainshock–aftershock ground motions is essential for seismic risk assessment, especially in regions experiencing frequent earthquakes. Recent studies have often employed Copula-based joint distributions or machine learning techniques to simulate the statistical dependency between mainshock and aftershock parameters. While effective at capturing nonlinear correlations, these methods are typically black box in nature, data-dependent, and difficult to generalize across tectonic settings. More importantly, they tend to focus solely on marginal or joint parameter correlations, which implicitly treat mainshocks and aftershocks as independent stochastic processes, thereby overlooking their inherent spectral interaction. To address these limitations, this study proposes an explicit and parameterized modeling framework based on the evolutionary power spectral density (EPSD) of random ground motions. Using the magnitude difference between a mainshock and an aftershock as the control variable, we derive attenuation relationships for the amplitude, frequency content, and duration. A coherence function model is further developed from real seismic records, treating the mainshock–aftershock pair as a vector-valued stochastic process and thus enabling a more accurate representation of their spectral dependence. Coherence analysis shows that the function remains relatively stable between 0.3 and 0.6 across the 0–30 Rad/s frequency range. Validation results indicate that the simulated response spectra align closely with recorded spectra, achieving R² values exceeding 0.90 and 0.91. To demonstrate the model’s applicability, a case study is conducted on a representative frame structure to evaluate seismic vulnerability and economic loss. As the mainshock PGA increases from 0.2 g to 1.2 g, the structure progresses from slight damage to complete collapse, with loss rates saturating near 1.0 g. These findings underscore the engineering importance of incorporating mainshock–aftershock spectral interaction in seismic damage and risk modeling, offering a transparent and transferable tool for future seismic resilience assessments. Full article

In earthquake-prone areas such as Tokyo, accurate estimation of bearing stratum depth is crucial for foundation design, liquefaction assessment, and urban disaster mitigation. However, traditional methods such as the standard penetration test (SPT), while reliable, are labor-intensive and have limited spatial distribution. In this study, 942 geological survey records from the Tokyo metropolitan area were used to evaluate the performance of three machine learning algorithms, random forest (RF), artificial neural network (ANN), and support vector machine (SVM), in predicting bearing stratum depth. The main input variables included geographic coordinates, elevation, and stratigraphic category. The results showed that the RF model performed well in terms of multiple evaluation indicators and had significantly better prediction accuracy than ANN and SVM. In addition, data density analysis showed that the prediction error was significantly reduced in high-density areas. The results demonstrate the robustness and adaptability of the RF method in foundation soil layer identification, emphasizing the importance of comprehensive input variables and spatial coverage. The proposed method can be used for large-scale, data-driven bearing stratum prediction and has the potential to be integrated into geological risk management systems and smart city platforms. Full article

The seismic risk assessment of large building stocks is crucial for informed asset management in earthquake-prone regions, providing decision-support for retrofit intervention planning. Many existing methodologies focus on a single structural typology or asset class (e.g., ordinary buildings or industrial facilities), thus limiting their applicability to mixed portfolios. This study proposes a comprehensive and adaptable methodology for the seismic assessment of diverse building stocks—a cross-typology approach encompassing masonry, reinforced concrete (r.c.), precast r.c., and steel structures. The approach integrates deficiency-based qualitative evaluations with simplified mechanical models tailored for each building class. Where validated methodologies were unavailable, new assessment tools were developed. The proposed framework was applied to an industrial-oriented building stock comprising 79 structural units at regional scale, demonstrating its capability to identify priority structures for retrofitting interventions. By overcoming the constraints of typology- or asset-specific approaches, this methodology enables a more comprehensive and scalable assessment. This ultimately contributes to effective risk mitigation planning and seismic resilience enhancing. Full article

On 18 December 2023, a M_w 6.2 earthquake occurred in close proximity to Jishishan County, located on the northeastern edge of the Qinghai–Tibet Plateau. The event struck the structural intersection of the Haiyuan fault, Lajishan fault, and West Qinling fault, providing empirical evidence for investigating the crustal compression mechanisms associated with the northeastward expansion of the Qinghai–Tibet Plateau. In this study, we successfully acquired a high-resolution coseismic deformation field of the earthquake by employing interferometric synthetic aperture radar (InSAR) technology. This was accomplished through the analysis of image data obtained from both the ascending and descending orbits of the Sentinel-1A satellite, as well as from the ascending orbit of the ALOS-2 satellite. Our findings indicate that the coseismic deformation is predominantly localized around the Lajishan fault zone, without leading to the development of a surface rupture zone. The maximum deformations recorded from the Sentinel-1A ascending and descending datasets are 7.5 cm and 7.7 cm, respectively, while the maximum deformation observed from the ALOS-2 ascending data reaches 10 cm. Geodetic inversion confirms that the seismogenic structure is a northeast-dipping thrust fault. The geometric parameters indicate a strike of 313° and a dip angle of 50°. The slip distribution model reveals that the rupture depth predominantly ranges between 5.7 and 15 km, with a maximum displacement of 0.47 m occurring at a depth of 9.6 km. By integrating the coseismic slip distribution and aftershock relocation, this study comprehensively elucidates the stress coupling mechanism between the mainshock and its subsequent aftershock sequence. Quantitative analysis indicates that aftershocks are primarily located within the stress enhancement zone, with an increase in stress ranging from 0.12 to 0.30 bar. It is crucial to highlight that the structural units, including the western segment of the northern margin fault of West Qinling, the eastern segment of the Daotanghe fault, the eastern segment of the Linxia fault, and both the northern and southern segment of Lajishan fault, exhibit characteristics indicative of continuous stress loading. This observation suggests a potential risk for fractures in these areas. Full article

Urban disaster risks are escalating, and university campus emergency shelters (UCESs) are key to alleviating the supply–demand imbalance in emergency shelter services (ESSs) within high-density central urban areas. However, existing studies lacked the measurement of UCES service effectiveness from a regional supply–demand perspective, limiting the ability to guide planning practices. Therefore, we focused on the capacity of UCESs to improve regional supply–demand relationships and developed a service effectiveness evaluation framework for UCESs in the central urban area of Tianjin under an earthquake scenario. We identified emergency shelter spaces within the campuses and developed a campus–city collaborative shelter capacity model to determine their service supply capacity. Then we quantified regional service demand driven by seismic risk. Finally, we quantified the service effectiveness of each UCES by constructing a service effectiveness evaluation model. Results showed that (1) the total shelter capacity and service coverage of 13 UCESs accounted for approximately 32.1% of the central district’s population and 67.5% of its land area, indicating their strong potential to provide large-scale ESSs. (2) Average seismic risk values ranged from 0.200 to 0.260, exhibiting the characteristic of being higher in the south and lower in the north. (3) Service effectiveness was classified into three levels—higher (1.150–1.257), medium (0.957–0.988), and lower (0.842–0.932)—corresponding to planning interventions that can be implemented based on them. This study aims to reveal differences between different UCESs to improve regional supply–demand relationships by evaluating their service effectiveness and supporting refined emergency management and planning decisions. Full article

Field surveys focused on detailed mapping and measurements of coseismic surface ruptures along the causative fault of the 6 February 2023, Mw 7.8 Kahramanmaraş earthquake. The aim was filling gaps in the previously available surface-faulting trace, validating the accuracy of data obtained from remote sensing, refining fault offset estimates, and gaining a deeper understanding of both the local and overall patterns of the main rupture strands. Measurements and observations confirm dominating sinistral strike-slip movement. An integrated and comprehensive slip distribution curve shows peaks reaching over 700 cm, highlighting the near-fault expressing up to 70% of the deep net offset. In general, the slip distribution curve shows a strong correlation with the larger north-eastern deformation of the geodetic far field dislocation field and major deep slip patches. The overall rupture trace is generally straight and narrow with significant geometric complexities at a local scale. This results in transtensional and transpressional secondary structures, as multi-strand positive and negative tectonic flowers, hosting different patterns of the mole-tracks at the outcrop scale. The comprehensive and detailed field survey allowed characterizing the structural framework and geometric complexity of the surface faulting, ensuring accurate offset measurements and the reliable interpretation of both morphological and geometric features. Full article

Urban water supply pipelines play a critical role in ensuring the continuous delivery of water, and their failure during earthquakes can result in significant societal disruptions. This study proposes a seismic damage prediction method for urban buried water supply pipelines affected by seismic wave propagation, grounded in empirical data from past earthquake events. The method integrates key influencing factors, including pipeline material, diameter, joint type, age, and soil corrosivity. To enhance its practical applicability and address the challenge of quantifying soil corrosivity, a simplified classification approach is introduced. The proposed model is validated using observed pipeline damage data from the 2008 Wenchuan earthquake, with predicted results showing relatively good agreement with actual failure patterns, thereby demonstrating the model’s reliability for seismic risk assessment. Furthermore, the model is applied to assess potential earthquake-induced damage to buried pipelines in the city center of Ganzhou, and the corresponding results are presented. The findings support earthquake risk mitigation and the protection of urban infrastructure, while also providing valuable guidance for the replacement of aging pipelines and the enhancement of urban disaster resilience. Full article

This study adopted the event study method to explore the effect of the Hualien earthquake on the performance of tourism stocks in Taiwan. This earthquake occurred on 3 April 2024 and affected Hualien and Taitung. The present study examined the short-term (10 trading days), medium-term (12 weeks), and long-term (5 months) performance of all listed tourism companies in Taiwan (overall sample) and six listed tourism companies with a branch in Hualien or Taitung (six-company sample). The results indicated that the stocks of the overall sample rebounded soon after the earthquake but declined over the long-term period. By contrast, the stocks of the six-company sample exhibited a persistent negative return immediately after the earthquake and gradually recovered in the long term. The findings of this study enhance theoretical understanding regarding the effects of a disaster on the stock market. Moreover, they serve as a reference for practical decision-making related to government risk response, investor behavior, and corporate crisis management in high-risk industries, such as tourism. Strengthening disaster preparedness and corporate branding after a disaster is critical for stabilizing market sentiment and industry resilience. Full article

Amid intensifying climatic threats, university campuses are increasingly vulnerable. Morphological resilience offers a practical pathway to strengthen disaster response in higher-education institutions. However, research on University Campus Morphological Resilience (UCMR) remains underexplored, with gaps in theory, quantitative methodology, and empirical application. The study established a theoretical framework and an assessment system for UCMR, focusing on four core resilience attributes—robustness, redundancy, connectivity, and diversity—in three common disaster scenarios: earthquakes, flooding, and extreme heat. The Weijinlu (WJL) and Beiyangyuan (BYY) campuses of Tianjin University were selected as case studies. We used Unmanned Aerial Vehicle (UAV) photogrammetry to collect morphological data at a high spatial resolution of 0.1 m. UCMR was evaluated for each disaster scenario, followed by a multi-scenario cluster coupling analysis. The results indicate that, first, the WJL Campus exhibited a lower overall UCMR across various disaster scenarios compared to the BYY Campus, particularly during earthquakes and flooding, with less pronounced differences observed under extreme heat. Second, both campuses demonstrate significant spatial heterogeneity in UCMR across three disaster scenarios. Third, the WJL Campus performs better in redundancy and diversity but worse in connectivity, with lower robustness under earthquakes and flooding, and higher robustness under extreme heat. Fourth, UCMR in BYY Campus displayed consistent spatial patterns characterized by high-resilience clusters, while UCMR in WJL Campus presented greater variability across the three disaster scenarios, showcasing complex multi-scenario cluster types and spatial fragmentation. Based on the above findings, we developed tailored UCMR optimization strategies. The study offers a scientific reference for resilience-oriented campus planning and disaster risk management. Full article