Search Results (372)

The Turpan–Hami Basin, a critical energy hub in northwestern China, is plagued by frequent ground collapses induced by extensive mining over karst geology, threatening ecology and safety. Current hazard assessment methods, mainly single linear or traditional machine learning models, fail to capture the complex nonlinear interactions inherent to this coupled geo-mining environment. This study addresses this gap by establishing a multi-dimensional “Geology-Mining-Hydrology-Environment” index system comprising 14 critical factors—including lithology, goaf distribution, mining intensity, and their interaction terms. A coupled gradient boosting decision tree and logistic regression (GBDT-LR) model, optimized for the multi-factor coupling characteristics of ground collapse in arid mining basins, was applied for the hazard assessment. The results reveal a distinct spatial pattern of “core agglomeration with multi-level gradient differentiation.” Extremely high-hazard areas, covering 9.21% of the area, are concentrated in the core mining areas northwest of Turpan and southwest of Hami, while high-hazard areas (4.63%) form surrounding belts. The GBDT-LR model (AUC = 0.871) demonstrated significantly superior performance over a single logistic regression model (AUC = 0.813), proving its enhanced capability to identify high-hazard areas by modeling complex factor interactions. This work provides an essential scientific foundation for implementing zonal hazard management and prioritizing disaster prevention projects in key areas of the basin. Full article

The 2023 Kahramanmaraş earthquakes caused unprecedented structural damage across South-Eastern Türkiye, highlighting the critical need for rapid post-disaster assessment and understanding the root causes of failure in reinforced concrete (RC) structures. This study provides a comprehensive comparative analysis of 207 RC buildings located in Adıyaman, Hatay, and Kahramanmaraş. A novel methodological approach was employed by integrating post-earthquake field observations with pre-earthquake digital data obtained via Google Street View to identify structural irregularities and damage patterns. The investigated buildings were classified based on their damage levels, with 11.1% categorized as heavily damaged, 34.3% as to-be-demolished, and 54.6% as collapsed. Significant structural irregularities, including soft stories (ranging from 64.9% to 82.7%), heavy overhangs, and vertical discontinuities, were found to be the primary drivers of severe damage. Furthermore, pounding and short-column effects were identified as the most prevalent damage types across all three provinces. The results demonstrate that pre-existing structural irregularities significantly exacerbated the seismic vulnerability of the RC building stock. This research emphasizes the importance of stringent adherence to design codes and suggests that integrating digital imagery into post-disaster surveys can significantly enhance the accuracy of damage classification for future earthquake resilience. Full article

Natural disasters disrupt maritime operations, yet their environmental consequences remain underexplored. This study quantifies CO₂ emission changes following the February 2023 İskenderun Bay earthquakes (7.6 Mwg and 7.5 Mwg) using AIS-derived port visit data and graph neural network modeling. Analyzing 25,837 port visits across a 36-month period (January 2022–December 2024), we compared emissions during baseline (pre-earthquake), acute disruption (February–June 2023), and recovery phases. Results revealed a statistically significant 35.9% increase in per-visit CO₂ emissions during the acute phase (t = 11.79, p < 0.001, Cohen’s d = 0.27), driven by extended port visit durations (from 77.87 to 105.82 h). Counterfactual analysis estimated 27,574 tonnes of excess CO₂ emissions directly attributable to earthquake disruption. Network analysis showed 23.8% reduction in edge density during the acute phase. The graph neural network (GNN) emission prediction model achieved R² = 0.985 (baseline) and R² = 0.997 (recovery) in predicting emission patterns, while acute phase showed predictability collapse (R² = −1.591). These findings demonstrate that seismic events generate sustainability-relevant externalities beyond immediate physical damage, and that quantifying disruption-driven excess emissions supports sustainability-oriented port resilience planning and more robust maritime emission accounting (e.g., under the EU MRV framework). Full article

Landslides occurring on reservoir banks in steep, high-gradient canyon areas pose a significant risk of surge disasters when they slide into the water. This can endanger the lives and property of downstream residents and damage coastal infrastructure. Therefore, researching the formation mechanisms, disaster evolution, and risk assessment of the landslide-surge disaster chain in such areas is essential. This paper takes the Laowuchang landslide in the Shuibuya Reservoir area of the Qingjiang River, China, as its research object. Using GeoStudio 2018 software, it evaluates the landslide’s stability under varying reservoir water levels and rainfall conditions. For potential unstable scenarios identified, a full-chain numerical simulation of the landslide–tsunami disaster was conducted based on the Tsunami Squares method, with a focus on analyzing the wave characteristics during generation, propagation, and run-up processes. Furthermore, the paper assesses the risk of landslide–tsunami disasters in the Laowuchang landslide area. The research findings indicate that: (1) Under the long-term continuous river incision, limestone of the Triassic Daye Formation slides along weak interlayers, inducing large-scale collapses. Subsequently, part of the landslide mass is transported by water, while most accumulates in the near-shore area of the Qingjiang River, ultimately shaping the present morphology of the landslide. (2) The Laowuchang landslide is stable under static water levels of 375 m and 400 m, with corresponding safety factors of 1.137 and 1.167, respectively. Under combined static water level and heavy rainfall conditions, the slope stability decreases significantly, with safety factors of 1.034 and 1.064, respectively. Under reservoir drawdown conditions, the slope tends to be unstable, with a safety factor of 1.047. (3) Numerical simulation results indicate that if the Laowuchang landslide fails into water by the speed of 12 m/s and with a volume of 2 million m³, the maximum initial wave height can reach 15.9 m. The tsunami’s affected range spans 10 km upstream and downstream from the landslide mass, with four houses and one substation within a 2 km up and downstream falling into high-risk areas. If abnormal increases in landslide displacement occur, relocation and risk avoidance measures should be implemented. The findings of this study provide a scientific basis for the prevention and response to landslide–tsunami disasters in similar high and steep canyon terrains. Full article

Deep time-series forecasting models can achieve strong average accuracy under normal conditions, yet they often struggle with rare, high-impact extremes, where severe class imbalance biases learning toward majority dynamics. Although infrequent, these extremes frequently correspond to critical events such as natural disasters or power outages. We address this challenge with a weak-label-guided mixture of experts (WL-MoE) that routes each input window to lightweight specialists designed to capture distinct temporal regimes. To prevent routing collapse during early optimisation, WL-MoE follows a two-stage training curriculum. In Stage I, cluster-derived weak labels encourage diverse expert utilisation and promote specialisation under imbalance. In Stage II, guidance is removed and training proceeds solely with the forecasting objective, ensuring that inferences remain fully data-driven. The expert-based structure also supports interpretable routing via expert-usage profiling, enabling regime-level auditing of model behaviour in high-stakes settings. Across seven benchmark datasets, WL-MoE reduces the average MSE by approximately $7.9\%$ and the extreme-case MSE by approximately $23.58\%$ relative to the best baseline. In a UK flood forecasting study, it reduces the all-water MSE by $31.6\%$ and the high-water MSE by approximately $35.0\%$. These results indicate that weak-label guidance can stabilise specialisation and improve reliability under rare extremes while keeping model behaviour auditable for real-world deployment. Full article

Studying the slumping disintegration, movement speed, impact intensity, accumulation characteristics, and energy conversion laws of tower-column unstable rock masses (TCURM) is crucial for high-altitude rockfall hazard risk evaluation. Existing PFC-based rockfall simulations rarely target the unique “top-hard-bottom-weak” structural characteristics of TCURM and lack in-depth integration of on-site monitoring videos to verify dynamic evolution processes. Taking the large-scale collapse of W12^# unstable rock mass at Zengziyan, Jinfo Mountain in Chongqing as an example, a combination method of orthogonal test and PFC^3D discrete element simulation is used. Mesoscopic parameters are calibrated via comparison with on-site video and investigation data, accurately reproducing the entire slumping disintegration process and revealing its dynamic characteristics. Results confirm the simulation is basically consistent with field data, verifying the model and parameter rationality. The total duration from instability to stagnation is 121 s (15 s to impact the secondary steep cliff base, 106 s for debris accumulation). Movement speed time-histories of deteriorated and non-deteriorated zones are generally consistent, both exhibiting a “double-peak” feature. Rockfall impact force first increases, stabilizes in the middle, and declines to stability afterward, with a maximum of 2.1 × 10⁹ N. The kinetic energy curve also shows a “double-peak” distribution, closely related to the on-site two-level steep cliff morphology. The findings provide important references for analyzing the dynamic evolution of such rockfalls and designing disaster prevention/mitigation engineering. Full article

Polymer additives in well cement slurry filtrate would affect the stability of natural gas hydrate (NGH), which could lead to formation collapse and cause marine disasters. It is necessary to clarify the critical conditions for the stability of NGH, i.e., NGH phase equilibrium. LAMMPS software and the TIP4P model were used to develop a method for calculating NGH phase equilibrium. Based on the single functional groups and combined functional groups of polymer additives, the potential energy, angular order parameter (AOP) of water molecules, and NGH phase equilibrium temperatures under different pressures were calculated, and a phase equilibrium curve was characterized. Results show that amide groups promote NGH decomposition more strongly than carboxyl and sulfonate groups, with a 1.5% dodecylamide system causing NGH phase equilibrium temperature to decrease by 1.68–2.77 K. AM/AA promotes NGH decomposition more strongly than AA/AMPSNa, AM/AMPSNa, and AA/AMPSNa/AM, with a 1.5% AM/AA system causing NGH phase equilibrium temperature to decrease by 2.33–3.56 K. To ensure the safety of well cementing and marine environments, the contents of amide groups and carboxyl groups should be reduced when developing polymer additives for cement slurry used in NGH formation cementing. Full article

Natural disasters disrupt maritime operations; yet, their environmental consequences remain underexplored. This study quantifies CO₂ emission changes following the February 2023 İskenderun Bay earthquakes (7.6 Mwg and 7.5 Mwg) using AIS-derived port visit data and graph neural network modeling. Analyzing 25,837 port visits across a 36-month period (January 2022–December 2024), we compared emissions during baseline (pre-earthquake), acute disruption (February–June 2023), and recovery phases. Results revealed a statistically significant 35.9% increase in per-visit CO₂ emissions during the acute phase (t = 11.79, p < 0.001, Cohen’s d = 0.27), driven by extended port visit durations (from 77.87 to 105.82 h). Counterfactual analysis estimated 27,574 tonnes of excess CO₂ emissions directly attributable to earthquake disruption. Network analysis showed a 23.8% reduction in edge density during the acute phase. The graph neural network (GNN) emission prediction model achieved R² = 0.985 (baseline) and R² = 0.997 (recovery) in predicting emission patterns, while the acute phase showed predictability collapse (R² = −1.591). These findings demonstrate that seismic events generate sustainability-relevant externalities beyond immediate physical damage, and that quantifying disruption-driven excess emissions supports sustainability-oriented port resilience planning and more robust maritime emission accounting (e.g., under the EU MRV framework). Full article

Coal mining in plain regions and its related surface subsidence and geological hazards have been extensively studied, whereas research on mining-induced hazards in mountainous areas remains limited. This knowledge gap has contributed to the frequent occurrence of mining disasters, particularly under steep ridge-type mountain geometry, where deformation characteristics, large-scale slope failure risks, and mining-induced hazard mechanisms remain poorly understood. In this study, a mining area in Zhenxiong, Zhaotong, Yunnan Province, China, is investigated using SBAS-InSAR, GNSS observations, UAV surveys, optical satellite imagery, and detailed field investigations. Surface hazards triggered by coal extraction are identified, and the response relationship between surface subsidence and mining activities is analyzed to reveal the development mechanisms of surface deformation beneath steep ridge-type mountain geometry. The results show that: (1) deep coal mining can still induce significant surface deformation due to the combined amplification effects of steep slopes and lithological conditions; (2) mining-induced deformation does not necessarily evolve into large-scale slope collapse and may gradually stabilize through natural adjustment processes; (3) SBAS-InSAR, validated by GNSS and field observations, provides an effective approach for detecting mining-related subsidence; (4) surface deformation in the study area is jointly influenced by multiple working faces; and (5) strong coupling between the unique steep ridge-type mountain geometry and underlying coal extraction leads to a compound disaster chain under multi-source interactions. These findings offer a critical scientific understanding of mining-induced deformation beneath steep ridge-type mountain geometry and provide important guidance for geological hazard prevention and control in similar mountainous mining areas. Full article

On 10 March 1933, an earthquake of roughly 6.4 on the Richter scale (retrospectively estimated) hit the City of Long Beach, California, and the counties surrounding it. Seismically, the quake was of moderate magnitude. However, to this day it remains one of the most destructive quakes in California history in terms of structural damage and fatalities, largely because of faults in building construction of the time that resulted in widespread collapses resulting from earth movement. This article tells the story of the quake itself in full detail; examines its role in the passage of the Field Act, tracing out how that act has impacted earthquake-resistant building design policy, law and practice in California and beyond; assesses the way in which the earthquake altered the trajectory of earthquake science; and details the economic policy response to the quake and the short-term stimulative effects this had on Long Beach and Southern California economies (referred to here as “Disaster Keynesianism”). While there is a large historiographical literature on the Long Beach quake and some of its singular impacts, this research is unique in that it describes and analyzes impacts across multiple dimensions and puts them in the context of contemporary literature on disaster studies, economic analysis, and the history of science, all based on extensive archival research. The paper concludes by positing that the policy, technical and economic response to the Long Beach earthquake represented a sort of “high modern” example of socially and institutionally constructed “disaster” that firmly set in place the notion that “natural disaster” could be managed and ultimately prevented by material and technical means. It is argued that such a view is still contained within more current and broader concepts of “Resilience” and “Anti-fragility”. Full article

Integrating Geostationary (GEO), Medium Earth Orbit (MEO), and Low Earth Orbit (LEO) satellite systems offers a promising solution for enhancing communication resilience in disaster-prone island regions. However, effective integration via Software-Defined Wide Area Networks (SD-WANs) faces challenges due to the heterogeneous stochastic characteristics of these links. This study presents a comprehensive performance benchmark of GEO, MEO, and LEO satellite links based on long-duration empirical campaigns conducted in Taiwan. Our findings quantify critical integration hurdles, specifically the “long-tail” latency distribution in LEO links induced by frequent handovers and significant TCP throughput degradation modeled by the Mathis equation. Furthermore, empirical tests demonstrate that simplistic link aggregation across these heterogeneous orbits results in severe packet reordering and goodput collapse. Based on these results, we propose a conceptual resilience-oriented SD-WAN architecture incorporating intelligent failover thresholds and application-aware routing policies. This work provides foundational data and a design framework to guide the future development of robust multi-layered satellite communication systems for disaster management. Full article

Tornadoes represent a significant natural hazard to critical infrastructure worldwide, as they can cause sudden and severe damage with far-reaching societal consequences. In this study, the authors investigate the vulnerability and resilience of public and critical infrastructure buildings in the Czech Republic to tornado impacts, with a particular focus on the 2021 South Moravian tornado. The research identifies key structural weaknesses, damage patterns, and protective factors through a detailed field survey of 46 tornado-affected buildings. The results highlight that building size, construction quality, material durability, and maintenance significantly influence tornado resistance. Buildings of reinforced concrete and steel frames showed higher resistance, while older, inadequately maintained masonry and timber buildings were highly susceptible to collapse. The conclusions recommend regular maintenance of building, structural reinforcement, installation of protection elements and robust roof system of public buildings. These insights provide a practical foundation for strengthening disaster preparedness policies at regional or national levels. Full article

Mining-induced ground fissures in the Ordos Basin pose critical threats to coal mine safety and ecological stability. This study integrated multi-source monitoring data (improves data acquisition efficiency by 60%) with theoretical models to elucidate the dynamic response mechanism between overlying strata failure and ground fissure development. The results demonstrate that: (1) Two rock beam structural models for initial and periodic fracturing of thick, hard rock strata are established, demonstrating that both failure modes are dominated by tensile–shear mechanisms. (2) Ground fissures exhibit distinct zonal characteristics, displaying a gradient pattern of “strong disturbance in the near field and weak response in the far field.” Quantitative data support this pattern: average fissure density is 36/hm², with a maximum of 45/hm² recorded in the immediate vicinity of the working face, declining steadily outward. (3) Overlying strata failure forms three distinct zones—caving zone (42 m), fissure zone (158 m), and longitudinal penetrating zone—reflecting the heterogeneous fracture characteristics of medium-hard rock strata under mining influence. (3) The proposed “virtual main arch—virtual auxiliary arch” equivalent support system theory elucidates the mechanistic differences between step fissures (attributed to local support system instability) and collapse fissures (driven by global support system instability) from a mechanical perspective. The developed chain response theory fills a critical theoretical gap and provides a novel method for predicting and preventing geological disasters in mining areas. Full article

Cascade dams describe an arrangement of several dam structures built along a flow path. Failure of one upstream dam in the cascade system can trigger catastrophic consequences to the downstream dams, as evidenced recently in the Edenville Dam and Sanford Dam. Previous research has mainly focused on rainfall-induced dam failures, although recent failures have demonstrated a combination of floods and earthquakes. Moreover, limited studies have analyzed the sensitivity of dam breach parameters, such as dam breach height and width in dams arranged in a cascade system for seismic events. Most hydraulic simulations that model seismic-induced dam failures assume the complete collapse of dams to analyze the downstream consequences. Hence, this study presents a novel analysis in simulating earthquake-induced failures in a cascade dam system, considering the sensitivity of dam breach parameters. In addition, dam breach parameters have been derived from the structural analysis of dams employing Finite Element Models (FEMs) to a critical Peak Ground Acceleration (PGA) of 0.3 g. Two-dimensional hydrodynamic simulations, along with the full dynamic wave equations, are undertaken in the study to model the earthquake-induced cascade dam failures. The results further elaborate on the significance of modeling cascade dam failures in terms of the consecutive arrival of floods and total flow compared to individual dam failures. Sensitivity analysis of dam breach parameters shows that the breach height is more significant than the breach width and breach slope. However, its significance decreases as the dam breach flood flow path increases in distance. The study further confirms the novel utilization of structural analysis to derive dam breach parameters for seismic-induced dam failures of concrete arch dams and rockfill dams, which will guide the optimization of disaster mitigation strategies and the operational resilience of the dams. Full article

Background/Objectives: The 2024 Noto Peninsula earthquake in Japan severely affected community care for persons with psychiatric disabilities. This study analyzed the difficulties and adaptive coping strategies of psychiatric visiting nurses (PVN) to inform disaster mental health practice. Methods: A qualitative, descriptive design was used. Semi-structured interviews were conducted with six PVN, and the data were analyzed thematically. Results: Key findings indicated two main challenges: a system-level paralysis of care owing to infrastructure collapse and the ethical dilemmas experienced by the role of PVN as “dual victims.” In response, nurses leveraged pre-existing therapeutic relationships to ensure care continuity and acted as essential liaisons to external teams. The study also documented substantial and unexpected patient resilience. Conclusions: Based on the findings, this study’s primary contribution is a recommendation to reframe disaster policy by shifting focus from merely deploying external aid to empowering existing, trusted community care networks and adopting a strengths-based model for mental health support. Full article