Destructive earthquakes result in significant damage to a wide variety of buildings. The resulting damage data is crucial for evaluating the seismic resilience of buildings in the region and investigating urban resilience. Field damage data from 38 destructive earthquakes in Sichuan Province were collected, classified, and statistically analysed according to the criteria of the latest Chinese seismic intensity scale for evaluating building damage levels. Meanwhile, the construction features and seismic damage characteristics of these buildings were also examined. These results facilitated the development of a damage probability matrix (DPM) for various building typologies, such as raw-soil structures (RSSs), stone-wood structures (SWSs), brick-wood structures (BWSs), masonry structures (MSs), and reinforced concrete frame structures (RCFSs). The damage ratio was employed as the parameter for vulnerability assessment, and a comprehensive analysis was performed on the differences in damage levels among all buildings in various intensity zones and time frames. Furthermore, the DPMs were further refined by simulating additional data from high-intensity zones to more accurately represent the seismic resistance of existing buildings in multiple-intensity zones. Vulnerability prediction models were developed using the biphasic Hill model, which elucidates varying damage trends across different construction typologies. Finally, empirical fragility curves were established based on horizontal peak ground acceleration (PGA) as the damage indicator. This study is based on multiple seismic damage samples from various regions, accounting for the influence of earthquake age. The DPMs, representative of the regional characteristics of Sichuan Province, were developed for different building types. Furthermore, multidimensional vulnerability regression models and empirical fragility curves are established based on these DPMs. These models and curves provide a theoretical foundation for seismic disaster scenario simulations and the seismic capacity analysis of buildings within Sichuan Province.

This paper investigated the influence of chloride ion erosion and aftershocks on the seismic performance of transmission tower structures in Xinjiang, China. Based on chloride ion diffusion laws and steel corrosion mechanisms, the time-dependent deterioration of reinforced concrete was analyzed. Finite element models considering corrosion effects were established for different ages(0a,50a,70a,100a) in a saline soil environment using ANSYS/LS-DYNA. Ten mainshock-aftershock sequences tailored to the site type was constructed, and the cumulative damage index (DI) was adopted as a metric for structural damage. The results indicate that aftershocks and steel corrosion significantly impact transmission tower damage, with damage extent influenced by the intensity of the main shock. Stronger aftershocks cause greater additional damage, potentially exceeding 50 % cumulative damage when their amplitude matches the main shock. Steel corrosion alone can lead to nearly 40 % damage. Its influence on seismic fragility varies with damage state, especially under moderate to complete damage, where longer service life increases vulnerability. The coupling of corrosion and aftershocks further elevates structural vulnerability. Hence, in seismic assessments of transmission towers in saline soil environments, combined effects of main and aftershocks, and corrosion, must be accounted for.

This study evaluates the impact of varying bedrock depths on local site amplification factors and their consequent influence on the vulnerability of buildings under seismic actions. An index-based methodology is implemented to analyze the seismic vulnerability of old masonry buildings in the historic center of Galata, & Idot;stanbul. As part of a site-specific analysis, soil models are developed to replicate a dipping bedrock at six different depths varying between 5 and 30 m beneath the ground surface. Consequently, potential damage scenarios are generated employing a seismic attenuation relation and damage distributions are compared for the cases with/without amplification effects. The findings point out that, the structural response undergoes the greatest amplification at a bedrock depth of 20 m, exceeding 1.6 and attaining its maximum value of 2.89 at the structural period of 0.22 s. The maximum shift in damage grades occurs for buildings with natural periods between 0.16 and 0.20 s on 15 m bedrock depth, whereas, for longer periods, the greatest increase occurs at 20 m bedrock depth compared to the scenarios without site amplification. As a result, this study emphasizes the significance of site-specific conditions that might amplify structural response and consequently, increase the seismic damage level in assessing the vulnerability of built heritage. By integrating geo-hazard-based evaluation into the large-scale seismic assessments, this study offers a framework for more accurate damage forecasting and highlights the need to include local site amplification effects in seismic risk mitigation plans, enhancing strategies for preserving built heritage.

Permafrost roughly affects half of the boreal region in Alaska and varies greatly in its thermo-physical properties and genesis. In boreal ecosystems, permafrost formation and degradation respond to complex interactions among climate, topography, hydrology, soils, vegetation, and disturbance. We synthesized data on soil thermal conditions and permafrost characteristics to assess current permafrost conditions in central Alaska, and classified and mapped soil landscapes vulnerable to future thaw and thermokarst development. Permafrost soil properties at 160 sites ranged from rocky soils in hillslope colluvium and glacial till, to silty loess, to thick peats on abandoned floodplains and bogs, across 64 geomorphic units. Ground-ice contents (% moisture) varied greatly across geomorphic units. Mean annual ground temperatures at similar to 1 m depth varied 12.5 degrees C across 77 sites with most permafrost near thawing or actively thawing. To assess the vulnerability of permafrost to climate variability and disturbance, we differentiated permafrost responses in terms of rate of thaw, potential thaw settlement, and thermokarst development. Using a rule-based model that uses geomorphic units for spatial extrapolation at the landscape scale, we mapped 10 vulnerability classes across three areas in central Alaska ranging from high potential settlement/low thaw rate in extremely ice-rich loess to low potential settlement/high thaw rate in rocky hillslope colluvium. Permafrost degradation is expected to result in 10 thermokarst landform types. Vulnerability classes corresponded to thermokarst features that developed in response to past climates. Differing patterns in permafrost vulnerability have large implications for ecosystem trajectories, land use, and infrastructure damage from permafrost thaw.

Climate change has led to increased frequency, duration, and severity of meteorological drought (MD) events worldwide, causing significant and irreversible damage to terrestrial ecosystems. Understanding the impact of MD on diverse vegetation types is essential for ecological security and restoration. This study investigated vegetation responses to MD through a drought propagation framework, focusing on the Yangtze River Basin in China, which has been stricken by drought frequently in recent decades. By analyzing propagation characteristics, we assessed the sensitivity and vulnerability of different vegetation types to drought. Using Copula modeling, the occurrence probability of vegetation loss (VL) under varying MD conditions was estimated. Key findings include: (1) The majority of the Yangtze River Basin showed a high rate of MD to VL propagation. (2) Different vegetation types exhibited varied responses: woodlands had relatively low sensitivity and vulnerability, grasslands showed medium sensitivity with high vulnerability, while croplands demonstrated high sensitivity and moderate vulnerability. (3) The risk of extreme VL increased sharply with rising MD intensity. This framework and its findings could provide valuable insights for understanding vegetation responses to drought and inform strategies for managing vegetation loss.

This study examines the failure mechanisms of offshore caisson-type composite breakwaters (OCCBs) under seismic loading through 1g shaking table model tests, comparing cases with and without remediation measures against seabed soil liquefaction. For this purpose, several countermeasures are implemented, comprising wraparound geogrid inclusions within the rubble mound layer, stone columns and compacted improvement zones in the seabed soil, all aimed at enhancing the seismic resilience and stability of OCCBs. Six physical model tests are conducted to evaluate the effectiveness of the applied remediation measures in minimizing liquefactioninduced deformations of OCCBs, including settlement, lateral movement, and tilting. Experimental findings indicate that the caisson settlement is primarily caused by the lateral flow of the foundation soil and the rubble mound layer. The combined use of stone columns and wraparound geogrid reinforcements efficiently mitigates this lateral flow. Notably, remediating just 2.8 % of the liquefiable seabed soil with stone columns decreases OCCB settlement and tilting by 45.4 % and 31 %, respectively, compared to the non-remediated model. Additionally, incorporating wraparound geogrid reinforcements within the rubble mound layer results in even further reductions of settlement and tilting by 90.6 % and 91.3 %, respectively. This research offers valuable insights for developing effective countermeasures to mitigate seismic-induced damage to OCCBs seated on liquefiable seabed soils.

Slow-moving landslides, characterized by sustained destructive potential, are widely distributed in northwest China. However, research on the damage mechanisms of masonry buildings caused by slow-moving landslide-induced surface deformation is significantly lacking, which severely restricts the physical vulnerability assessment of masonry structures and the quantitative risk evaluation of slow-moving landslides. Through field investigations, CDEM numerical simulations, and statistical analyses, this study reveals the cooperative deformation characteristics and progressive failure mechanisms of masonry buildings subjected to ground cracks in slow-moving landslides, and establishes physical vulnerability curves for four distinct ground crack scenarios. The key findings indicate that masonry buildings affected by slow-moving landslides primarily exhibit transverse wall cracking and longitudinal wall inclination due to ground crack propagation. As crack propagation continues, the first-floor walls exhibit significantly higher Mises stresses compared to those on the second floor. Wall inclination rates demonstrate a distinct threshold effect during crack propagation: below the threshold, inclination increases linearly with crack displacement, while above the threshold, it exhibits exponential growth. Under identical crack displacement conditions, wall inclination rates decrease in the following order: horizontal tension, combined tension, settlement, and combined uplift scenarios. The differential effects of these scenarios on wall inclination become more pronounced with increasing crack displacement. Weibull functions were employed to fit vulnerability curves for masonry structures under four ground crack scenarios, revealing displacement thresholds of 22 cm, 26 cm, 27 cm, and 37 cm for complete structural vulnerability (V = 1) in each respective scenario. These findings provide valuable insights for vulnerability prediction and emergency rapid assessment of buildings subjected to slow-moving landslides across various disaster scenarios.

Hurricanes are one of the most destructive natural disasters that can cause catastrophic losses to both communities and infrastructure. Assessment of hurricane risk furnishes a spatial depiction of the interplay among hazard, vulnerability, exposure, and mitigation capacity, crucial for understanding and managing the risks hurricanes pose to communities. These assessments aid in gauging the efficacy of existing hurricane mitigation strategies and gauging their resilience across diverse climate change scenarios. A systematic review was conducted, encompassing 94 articles, to scrutinize the structure, data inputs, assumptions, methodologies, perils modelled, and key predictors of hurricane risk. This review identified key research gaps essential for enhancing future risk assessments. The complex interaction between hurricane perils may be disastrous and underestimated in the majority of risk assessments which focus on a single peril, commonly storm surge and flood, resulting in inadequacies in disaster resilience planning. Most risk assessments were based on hurricane frequency rather than hurricane damage, which is more insightful for policymakers. Furthermore, considering secondary indirect impacts stemming from hurricanes, including real estate market and business interruption, could enrich economic impact assessments. Hurricane mitigation measures were the most under-utilised category of predictors leveraged in only 5% of studies. The top six predictive factors for hurricane risk were land use, slope, precipitation, elevation, population density, and soil texture/drainage. Another notable research gap identified was the potential of machine learning techniques in risk assessments, offering advantages over traditional MCDM and numerical models due to their ability to capture complex nonlinear relationships and adaptability to different study regions. Existing machine learning based risk assessments leverage random forest models (42% of studies) followed by neural network models (19% of studies), with further research required to investigate diverse machine learning algorithms such as ensemble models. A further research gap is model validation, in particular assessing transferability to a new study region. Additionally, harnessing simulated data and refining projections related to demographic and built environment dynamics can bolster the sophistication of climate change scenario assessments. By addressing these research gaps, hurricane risk assessments can furnish invaluable insights for national policymakers, facilitating the development of robust hurricane mitigation strategies and the construction of hurricaneresilient communities. To the authors' knowledge, this represents the first literature review specifically dedicated to quantitative hurricane risk assessments, encompassing a comparison of Multi-criteria Decision Making (MCDM), numerical models, and machine learning models. Ultimately, advancements in hurricane risk assessments and modelling stand poised to mitigate potential losses to communities and infrastructure both in the immediate and long-term future. (c) 2025 China University of Geosciences (Beijing) and Peking University. Published by Elsevier B.V. on behalf of China University of Geosciences (Beijing). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Here, a seismic-response analysis model was proposed for evaluating the nonlinear seismic response of a pile-supported bridge pier under frozen and thawed soil conditions. The effect of a seasonally frozen soil layer on the seismic vulnerability of a pile-supported bridge pier was evaluated based on reliability theory. Although the frozen soil layer inhibited the seismic response of the ground surface to a certain extent, it exacerbated the acceleration response at the bridge pier top owing to the low radiation damping effect of the frozen soil layer. Furthermore, the frozen soil layer reduced the lateral displacement of the bridge pier top relative to the ground surface by approximately 80%, thereby preventing damage caused by earthquakes, such as falling girders. Compared to the thawed state of the ground surface, the bending moment of the bridge pier in frozen ground increases. However, the bending moment of the pile foundation in frozen ground decreases, thereby lessening the seismic vulnerability of the bridge pile foundation. The results of this can provide a reference for the seismic response analysis and seismic risk assessment of pile-supported bridges in seasonally frozen regions.

The current Indian Standard Seismic Code IS 1893: Part 1 (2016) for general buildings lacks detailed guidelines on modeling soil-structure interaction (SSI) in the estimation of seismic demand and earthquake-induced damage in reinforced concrete buildings. Therefore, this study aims to investigate the effects of SSI, with a focus on its nonlinear behavior, on the seismic demand of ductile reinforced concrete frames designed as per IS 1893: Part 1. The selected RC buildings are designed for second-highest seismic risk zone in India and represent short, medium, and long-period structures commonly found across Indian sub-continent. The influence of SSI is studied for soil type II and type III, as specified in the Indian Code, which corresponds to medium stiff and soft soil sites, respectively. Using a nonlinear Winkler-based model, numerical finite element models of linear and nonlinear SSI have been developed for isolated shallow foundations. This study utilizes the results of incremental dynamic analysis to evaluate the fragility parameters for code specified performance limit states. Further, the estimated fragility parameters are integrated with the regional hazard curve coefficients to quantify the annual exceedance probability of specified damage levels. The simulation results highlight the critical impact of nonlinear SSI on the earthquake resilience of IS code designed low- to high-rise reinforced concrete buildings. Notably, the percentage increase in estimated fragilities is higher for low-rise buildings than high-rise buildings when subjected to ground motions on soil sites. Additionally, the vulnerability to failure of these buildings elevates significantly when they are analyzed on soft soil sites compared to medium soil and bedrock sites. Therefore, it is recommended to account for the significance of nonlinear SSI while assessing the expected structural performance and fragility of IS 1893: Part 1 designed stiff low- to medium-rise reinforced concrete buildings, as this step can substantially enhance the resiliency of such buildings in the aftermath of a disastrous earthquake.