Existing landslide susceptibility prediction methods often fail to fully account for the spatial heterogeneity of environmental factors such as topography, soil, and vegetation, nor do they accurately reflect the impact of extreme rainfall on landslide susceptibility. To overcome these limitations, this study proposes two innovative methods. First, to address the issue of spatial heterogeneity, a Deep Embedding Clustering (DEC) approach is introduced. DEC utilizes an autoencoder to map environmental factors to a lower-dimensional space, capturing nonlinear relationships between variables and performing clustering in this space. Unlike traditional methods, DEC does not rely on simple distance measures; instead, it jointly optimizes clustering centers and feature representations, enabling more precise regional delineation, which significantly enhances prediction accuracy and adaptability to varying environments. Second, to address the static nature of rainfall thresholds, a mixed distribution modeling strategy is proposed for both non-extreme and extreme rainfall. In this strategy, non-extreme rainfall is modeled using the Gamma distribution to describe cumulative effects, while extreme rainfall is modeled using the Generalized Pareto Distribution (GPD) to model extreme values, with thresholds dynamically determined using the Pickands theorem. Additionally, a Bayesian online parameter updating mechanism is implemented to dynamically adjust distribution parameters, recalibrating the model when real-time rainfall data deviates from historical distributions, significantly reducing response time and improving the model's adaptability to changing rainfall patterns. By combining Deep Embedding Clustering (DEC) and the mixed distribution rainfall threshold model, this study achieves more precise spatial zoning and dynamic rainfall responses, greatly improving prediction accuracy and timeliness. Compared to traditional models relying on uniform thresholds, the experimental results show that landslide density and event numbers have increased from 0.038 events/km2 and 44 events to 0.044 events/km2 and 59 events, respectively, validating the importance of incorporating spatial heterogeneity and distinct rainfall event types in landslide susceptibility prediction.
A large number of stone masonry buildings have been constructed in the southeastern coastal region of Fujian Province, China. However, most of these structures exhibit poor seismic performance, likely due to low mortar strength and the absence of effective seismic-resistant system. By analyzing the construction characteristics and seismic vulnerabilities of stone masonry walls between windows, this study proposed a novel retrofitting technique that utilizes POM fiber-reinforced ultra-high performance concrete (POM-UHPC) for mortar joint reinforcement. To investigate the seismic behavior of the retrofitted stone masonry walls between windows, pseudo-static tests were conducted on three wall specimens with an aspect ratio of 1.43 (i.e., one specimen with full-embedding mortar joint reinforcement, one specimen with discrete-point-embedding (localized) mortar joint reinforcement, and one unreinforced specimen for comparison). The results show that the cracking load, initial stiffness, and shear capacity of the specimens with both full- and discrete-point joint reinforcement are significantly increased, and varying degrees of enhancement in their deformation capacity and energy dissipation are observed. When the effective area of POM-UHPC replacing low-strength mortar is similar, the discrete-point-embedding reinforcement method provides a greater improvement in the shear capacity of the wall between windows compared to the full-joint embedding method, but its energy dissipation capacity is lower. In practical engineering in the study area, the discrete-point-embedding mortar joint reinforcement method is recommended as the preferred approach. The findings of this study provide new technical support for the seismic reinforcement of stone masonry buildings in Fujian Province.
The 2008 Wenchuan earthquake significantly accelerated the adoption of base isolation in seismic-prone regions in China. While traditionally used for short-period structures on stiff sites, base isolation has also been increasingly applied to high-rises on soft soils. However, most current designs still rely on conventional methods used in the past. This paper investigates the seismic performance of a 26-story base-isolated shear wall building constructed on a near-fault site of deep alluvial deposits near Beijing. A numerical model incorporating soil-structure interaction (SSI) is developed to evaluate the combined effects of seismic isolation and deep site conditions on structural responses. The results indicate that base isolation effectively reduces the lateral force demands of the superstructure, even in the presence of deep soils. However, the soft site tends to amplify the horizontal and rotational deformations of the isolation layer, increasing the risk of isolator failure during major earthquake events. Meanwhile, the routine design method tends to underestimates these responses. These findings highlight the necessity of considering both SSI effects and a more refined assessment of soil nonlinearity in amplifying seismic motions in the design of high-rise base-isolated buildings on soft soil.
China's southwestern region is characterised by active geological structures and frequent seismic activities. These conditions frequently trigger landslides that obstruct rivers and form landslide dams. The failure of these dams represents a significant threat to downstream populations, as exemplified by the breach of the Tangjiashan landslide dam during the Wenchuan earthquake. This study focuses on the overtopping breach type of landslide dams. It conducts large-scale experiments to investigate the impacts of various grading materials on the breach process. Furthermore, the DABA (Dam Breach Analysis) numerical simulation model is employed to conduct an in-depth analysis of the breach process in landslide dams. Based on the experimental and simulated results, the following characteristics of landslide dam breaches were analyzed. Under identical inflowing conditions, the peak discharge of the fine-grained dam is 1.6 times that of the widely-graded dam, which has a significantly higher susceptibility to breaching. Although both dams failed due to overtopping, their erosion mechanisms differed substantially. For the widely graded dam, coarse particles led to scouring and retrogressive erosion, significantly prolonging the breaching process. In contrast, the fine-grained dam primarily failed through layered scouring. The results show a high degree of consistency between the DABA numerical simulation outcomes and the large-scale experiment data, thus validating the model's reliability. The parameter sensitivity analysis revealed that breach development duration and peak discharge were significantly influenced by dam height, dam crest width, and initial water level. Scientific simulation models can more precisely predict the breach time and impact range of landslide dams, aiding in the development of more effective prevention methods.
The characteristics of the active faults in the region around the megacity of Jakarta are poorly understood. This study investigates slip rate of the Jakarta Fault using new GNSS data obtained from campaign measurements conducted between 2019 and 2023. This is a recently discovered active fault that forms part of the broader Baribis Fault system, which runs across most of northern Java. The Jakarta Fault cuts across the southern portion of Jakarta, a city with over 32 million people in the metropolitan region. In this study, we apply a 2-D screw dislocation model to the north-south component of the GNSS velocities, which are projected onto a profile perpendicular to the approximately east-west trending fault. Our analysis estimates a fault slip rate of 3.2 mm/yr, with a locking depth of 7.2 km and a dip angle of 63◦. Previous studies have estimated the fault length to be approximately 50 km, with a return period of around 210 years. By combining this information with our findings, we estimate that a potential earthquake of magnitude between 6.49 and 6.54 could occur on the fault. Our research highlights the active deformation occurring along the Jakarta Fault, emphasizing the urgent need for greater attentions from stakeholders, as an earthquake of this magnitude could pose significant seismic risks to the Jakarta region.
Loess is a Quaternary aeolian sediment that has been deposited over an undulating bedrock landscape, forming the Chinese Loess Plateau. Where this bedrock comprises mudstones, the loess-bedrock interface conditions the landscape in a state of high landslide susceptibility. In this neo-tectonically active region, earthquakes and rainfall are highly likely to act as triggers. This study focuses on a representative loess–mudstone interface landslide located on a hillside behind the Vehicle Management Office in Wuqi County, Yan'an City, Central China, to investigate the coupled effects of rainfall infiltration and seismic loading on slope deformation and failure mechanisms. Numerical simulations were developed to better understand how co-seismic landslides are affected by different rainfall conditions, and how this resulted in different mechanisms of failure and runout. The results show that rainfall infiltration progressively weakens the mudstone layer, leading to the upward extension of the potential slip zone and a marked reduction in slope stability. Under subsequent seismic loading, deformation is concentrated along the loess–mudstone contact, and topographic amplification further increases peak ground acceleration at the slope crest. The interaction between rainfall-induced softening and seismic excitation significantly accelerates slope failure, highlighting the critical control of the mudstone layer's post-softening strength on overall stability. The findings of this study provide a valuable reference for analyzing the disaster mechanisms of similar loess landslides.
The MW 8.8 Kamchatka earthquake in Russia's Kamchatka Peninsula is one of the top ten largest earthquakes worldwide since 1900. This event occurred in a tectonically active Kurile–Kamchatka subduction zone where several large earthquakes (M > 8) have occurred over the past 100 years. Here, we combine the teleseismic vertical-component P-wave back-projection method and finite fault inversion with teleseismic P and SH waveforms to investigate the kinematic features of this earthquake. The results indicate that the ruptured area spans approximately 600 km in length and 175 km in width, with a total source duration of about 220 s. Moreover, the coseismic slip occurred mainly within the subducting interface away from the trench, reaching a maximum slip of about 8 m. Notably, the rupture propagated approximately 500 km southwestward from the hypocenter, consistent with the aftershock distribution. These results imply that the rupture zone of this earthquake might spatially overlap with that of the 1952 MW 8.8–9.0 Kamchatka earthquake. Furthermore, the smaller than anticipated tsunami generated by this megathrust event could be attributed to its limited shallow slip near the trench. This study provides preliminary kinematic insights into this event and lays a certain foundation for subsequent in-depth studies.
Recently, with rapid developments in distributed acoustic sensing (DAS) techniques, optical fibers are widely used as seismometers to carry out dense and broadband seismic observation. However, the frequency responses, especially the low-frequency responses of submarine cables, which are of key importance in focal mechanism and deep seismic imaging, are still poorly understood. In this study, we comprehensively evaluated the phase and amplitude responses of the submarine DAS array by comparing teleseismic records from the DAS array and traditional broadband seismometers. Our 21 km long DAS array is located around 1 500 km from the epicentre, and two fixed seismometers from the Shandong Provincial Seismic Network are positioned at either end of the array. Our results show that for phase response, the data from DAS and seismometers are of great similarity, with a cross-correlation coefficient reaching 80 %. For amplitudes, the velocity value recorded by CHD (Shandong Provincial Seismic Network Changdao Seismic Station) seismometers is about 1.6 times the value obtained by DAS. In terms of surface wave dispersion, the differences between the different data sets are generally less than 3 %. Our results verify the sensitivity of submarine optical fibers to low-frequency seismic signals and the feasibility of deep structure imaging using submarine DAS arrays.
Ghana and its surrounding West African region are often regarded as a stable intraplate area far from active plate boundaries, characterized by relatively low seismicity compared to tectonically active zones like the East African Rift. However, the region has experienced significant earthquakes (including a magnitude ~6.5 event in 1939 in Ghana) and a growing number of small-to-moderate events in recent decades, underscoring a critical need to resolve its seismotectonic framework. Seismic hazard studies have largely overlooked West Africa, and the causes and tectonic controls of its earthquakes remain poorly understood. To address this, we synthesize geological, geophysical, and seismic data in a comprehensive review to examine the regional tectonic setting, the spatial distribution of historical and recent seismicity, stress field characteristics, and the status of earthquake monitoring. We conclude that West African intraplate earthquakes are predominantly driven by the reactivation of pre-existing crustal weaknesses under far-field plate forces, augmented by stress transfer from the Atlantic margin (along offshore transform fracture zones) and the Cameroon Volcanic Line. Our observations highlight the region's current geodynamics and provide a basis for improved seismic hazard assessment. Given the rapidly growing population and infrastructure in seismically vulnerable areas across West Africa, these findings are crucial for informing earthquake preparedness and risk mitigation strategies.