GeoHazards

The failure of large gravity dams during an earthquake could lead to calamitous flooding, severe infrastructural damage, and massive environmental destruction. This paper aims to demonstrate reliable methods for evaluating dam performance after a seismic event. The work included a seismic hazard analysis and nonlinear finite element modelling of concrete cracking for two large dams (D1 and D2, of 35 and 90 m in height, respectively) in Eastern Canada. Dam D1 is located in Montreal, and Dam D2 is located in La Malbaie, Quebec. The modelling approach was validated using the Koyna Dam, which was subjected to the 1967 Mw 6.5 earthquake. This paper reports tensile cracks of D1 and D2 under combined hydrostatic and seismic loading. The latter was generated from ground motion records from 11 sites during the 1988 Mw 5.9 Saguenay earthquake. These records were each scaled to two times the design level. It is shown that D1 remained stable, with minor localised cracking, whereas D2 experienced widespread tensile damage, particularly at the crest and base under high-energy and transverse inputs. These findings highlight the influence of dam geometry and frequency characteristics on seismic performance. The analysis and modelling procedures reported can be adopted for seismic risk classification and safety compliance verification of other dams and for recommendations such as monitoring and upgrading. Full article

The Tokara Islands, a volcanic archipelago located south of Japan’s main islands, experienced earthquake swarm activity in 2025. Public concern has emerged regarding the potential triggering of the anticipated Nankai Trough earthquake, which the Japan Meteorological Agency has dismissed; however, the underlying mechanisms of this seismic activity remain inadequately explained. This study employs Exploratory Data Analysis (EDA) to characterise the statistical properties of the swarm and compare them with historical patterns. Earthquake intervals followed exponential distributions, but swarm events exhibited distinctive short intervals that clearly distinguished them from background seismicity. Similarly, whilst earthquake magnitudes conformed to normal distributions, swarm events demonstrated low mean values and reduced variability, characteristics markedly different from regional background activity. The frequency and magnitude distributions of the 2025 swarm demonstrate remarkable similarity to two previous swarms that occurred in 2021. All the episodes coincided with volcanic activity at Suwanose Island, located approximately 10 km from the epicentral region, suggesting a causal relationship between magmatic processes and seismic activity. Statistical analysis reveals that the earthquake swarm exhibits exceptionally low magnitude scale, characteristics consistent with magma-driven seismicity rather than tectonic stress accumulation. The parameter contrasted markedly with pre-seismic conditions observed before the 2011 Tohoku earthquake, where it was substantially elevated. Our findings indicate that the current seismic activity represents localised volcanic-related processes rather than precursory behaviour associated with major tectonic earthquakes. These results demonstrate the utility of statistical seismology in distinguishing between volcanic and tectonic seismic processes for hazard assessment purposes. Full article

Both studies and conservation of mountain waters are essential because of the primary role of mountains as “natural water towers” for the preservation and optimized exploitation of water reserves. In particular, under climate change stresses which induce reductions in rain and snow precipitation, especially in areas with rain-snow transition zones, increasing knowledge of the geological setting and hydrogeological context of mountain springs is pivotal for their preservation and optimized exploitation. However, the complexity and remoteness of mountain waters make them difficult to conceptualize and analyse, both observationally and instrumentally. In this context, using detailed geological mapping and hydrogeological surveys, geophysical data can provide useful information on the subsurface setting. Electrical resistivity tomography (ERT) surveys are utilized in this work for the investigation of the Montellina Spring (MS), which is located in the low Dora Baltea Valley and represents a significant drinking water source in the alpine context. Geophysical surveys, complemented by specific geological and hydrogeological observations, allowed a detailed reconstruction of the water circuit that supplies the spring along an articulated buried glacial valley and a loose bedrock in a DSGSD (deep-seated gravitational slope deformation) environment. The methodological approach also provides the basis for its successful application in similar geological contexts. Full article

Tunnel linings play a vital role in underground infrastructure, yet their performance can be severely affected by pre-existing cracks. This study investigates the mechanical behavior and failure mechanisms of C30 concrete with artificial cracks under uniaxial compression, simulating various crack conditions observed in tunnel linings. Specimens were designed with varying crack lengths and orientations. Acoustic emission (AE) monitoring was employed to capture the evolution of internal damage and micro-cracking activity during loading. Fractal dimension analysis was performed on post-test crack patterns to quantitatively evaluate the complexity and branching characteristics of crack propagation. The AE results showed clear correlations between amplitude characteristics and macroscopic crack growth, while fractal analysis provided an effective metric for assessing the extent of damage. To complement the experiments, discrete element modeling (DEM) using PFC3D was applied to simulate crack initiation and propagation, with results compared against experimental data for validation. The study demonstrates the effectiveness of DEM in modeling cracked concrete and highlights the critical role of crack orientation and size in strength degradation. These findings provide a theoretical and numerical foundation for assessing tunnel lining defects and support the development of preventive and reinforcement strategies in tunnel engineering. Full article

Geohazard investigation in volcanic fields is essential for understanding and mitigating risks associated with volcanic activity. Volcanic vents are often concealed by processes such as faulting, subsidence, or uplift, which complicates their detection and hampers hazard assessment. To address this challenge, we developed a predictive framework that integrates high-resolution gravity data with multiple machine learning algorithms. Logistic Regression, Gradient Boosting Machine (GBM), Decision Tree, Support Vector Machine (SVM), and Random Forest models were applied to analyze the gravitational characteristics of known volcanic vents and predict the likelihood of undiscovered vents at other locations. The problem was formulated as a binary classification task, and model performance was assessed using accuracy, precision, recall, F1-score, and the Area Under the Receiver Operating Characteristic Curve (AUC-ROC). The Random Forest algorithm yielded optimal outcomes: 95% classification accuracy, AUC-ROC score of 0.99, 75% geographic correspondence between real and modeled vent sites, and a 95% certainty degree. Spatial density analysis showed that the distribution patterns of predicted and actual vents are highly similar, underscoring the model’s reliability in identifying vent-prone areas. The proposed method offers a valuable tool for geoscientists and disaster management authorities to improve volcanic hazard evaluation and implement effective mitigation strategies. These results represent a significant step forward in our ability to model volcanic dynamics and enhance predictive capabilities for volcanic hazard assessment. Full article

Landslide susceptibility assessment constitutes a pivotal method of preventing and reducing losses caused by geological disasters. However, traditional models are often influenced by subjective grading factors, which can result in unscientific and inaccurate assessment outcomes. In this study, we thoroughly analyze various landslide causative factors, including geological, topographical, hydrological, and environmental components. A quantitative continuous model was employed, with methods such as frequency ratio (FR), cosine amplitude (CA), information value (IV), and certainty factor (CF) being applied in order to assess the landslide susceptibility of the Wanzhou coastline in the Three Gorges Reservoir area. The results were then compared with methods such as Bias-Standardised Information Value (BSIV), Support Vector Machine (SVM), Random Forest (RF), and Gradient Boosted Decision Tree (GBDT). This process led to the following key conclusions: (1) Most landslide susceptibility zones are predominantly banded and clustered on both sides of the Dewuidu River, particularly along the left bank of the Yangtze River from Dewuidu Town to Wanzhou City, as well as in the main urban area of Wanzhou. Clusters of the Yangtze River mainstem and surrounding towns characterize these areas. (2) The enhanced statistical analysis model shows a notable increase in sensitivity to landslides, achieving an Area Under the Curve (AUC) of 0.8878 for the IV model—an improvement of 0.0639 over the traditional BSIV model. This enhancement aligns closely with machine learning capabilities, and the spatial results obtained are more continuous. (3) By substituting manual grading with a quantitative continuous model, we achieve a balance between interpretability and computational efficiency. These findings lay a scientific foundation for the prevention and management of geological disasters in Wanzhou and provide valuable insights for comparable regions undertaking landslide susceptibility assessments. Full article

The analysis of earthquake source mechanisms is key for seismotectonic studies, but it is often limited to traditional methods plagued with issues of precision and automation. This is particularly true in low-seismicity areas with deep and/or hidden seismogenic sources, where the identification of precise source mechanisms is a difficult and non-trivial task. In this study, we present a detailed application of TESLA (Tool for automatic Earthquake low-frequency Spectral Level estimAtion), a novel tool designed to overcome these limitations. We demonstrated TESLA’s effectiveness in defining source mechanism analysis by applying it to seismic sequences that occurred near Asti (AT), in the Monferrato area (Southern Piedmont, Italy). Our analysis reveals that the observed clusters consist of two distinct seismic sequences, occurring in 1991 and 2012, which were activated by the same seismogenic source. We relocated a total of 36 events with magnitudes ranging from 1.1 to 3.7, using a 3D velocity model, and computed 12 well-constrained focal mechanism solutions using the first motion polarities and the low-frequency spectral level ratios. The results highlight a relatively small seismogenic source located at approximately 5 km north of Asti (AT), at a depth of between 10 and 25 km, trending SW–NE with strike-slip kinematics. A smaller cluster of three events shows an activation of a different fault segment at around 60 km of depth, also showing strike-slip kinematics. These findings are in good agreement with the regional stress field acting in the Monferrato area and support the use of investigation tools such as TESLA for microseismicity analysis. Full article

Seismo-stratigraphic data of the Gulf of Pozzuoli have been revised with the aim of identifying the tectonic structures controlling the area in more detail and to highlight the possible relationships of the morpho-structures with the new bradyseismic crisis, still in course. In particular, the relationships between the tectonic structures, consisting of both normal faults and folds, and the possible rising of fluids have been analyzed based on seismic interpretation. We hypothesize that the normal faults occurring in this area have possibly controlled the rising of fluids in these extensional structures. The fluid uprising could possibly be related to the increasing gas activity of the Solfatara–Pisciarelli area onshore during the active bradyseismic crisis (2024–2025). The proposed mechanism is controlled by the occurrence of a heat source, possibly a magmatic reservoir, in the continental crust and/or the mantle, genetically related to the presence of submerged hydrothermal discharges in the coastal areas of the Campania region. To achieve this objective, detailed seismo-stratigraphic sections of the Gulf of Pozzuoli have been constructed, focusing on the areas characterized by tectonic activity. Fluid uprising is mainly controlled by the tectonic setting of the Gulf of Pozzuoli, characterized by anticlines and synclines, representing important structural and stratigraphic traps. Full article

Debris flows are rapid mass movements of water-laden debris that flow down mountainsides into valley channels and eventually settle on valley floors. The risk of debris flows can be significantly increased after wildfires. Following the destructive 2021 debris flows in Glenwood Canyon, the Colorado Geological Survey (CGS) initiated a LiDAR-Based Alluvial Fan Mapping Project to improve geologic hazard delineation of alluvial and high-angle fans in response to developing wildfire-ready watersheds. These landforms, shaped by episodic sediment-laden flows, pose significant risks and are often misrepresented on conventional geologic maps. CGS delineated fan-shaped landforms with improved precision using 1-m resolution LiDAR-based DEMs, DEM-derived terrain metrics, hydrologic analysis, and geospatial analysis tools within the ArcGIS Pro platform. Our results reveal previously unmapped or misclassified alluvial or high-angle fans in areas undergoing increasing development pressure, where low-gradient terrain indicates a high hazard potential. Through this study, over 3200 alluvial and high-angle fan polygons were delineated across six Colorado counties, encompassing approximately 81 km² of alluvial fans and 54 km² of high-angle fans. High-resolution LiDAR data, geospatial analytical techniques, and systematic QA/QC protocols were used to support refined hazard awareness. The resulting dataset enhances proactive land-use planning and wildfire resilience by identifying areas prone to debris flow and flood hazards. These maps are intended for regional screening and planning purposes and are not intended for site-specific design. These maps also serve as a critical resource for prioritizing geologic evaluations and guiding mitigation planning across Colorado’s wildfire-affected landscapes. Full article

Levee failures caused by prolonged flooding and elevated upstream water levels pose a significant risk to floodplain communities, especially as the number of extreme hydrological events increases under climate change. Understanding seepage-induced weakening and failure mechanisms is essential for improving levee design and resilience. This study develops a numerical framework that integrates unsaturated and saturated seepage analysis with slope stability evaluation to simulate seepage front progression and predict failure initiation. The model employs van Genuchten-based soil water retention properties and experimentally derived hydraulic conductivities, with results validated against five experimental cases with varying hydraulic conductivity contrasts between the levee body and foundation soils. The simulations reproduced seepage front evolution and slope deformation patterns with good agreement with experimental observations. In cases with high permeability contrasts, the model captured foundation-dominant seepage behavior, while moderate- and low-contrast scenarios showed close alignment with observed phreatic line development. Slight deviations were noted in failure timing, but the framework demonstrated potential for reproducing seepage-induced instability in levees. The findings contribute to understanding how the internal soil composition governs levee performance under flooding and provide a basis for developing seepage countermeasures and early warning tools. This approach offers practical value for risk-informed levee design and flood management. Full article

Soil erosion threatens agricultural sustainability in tropical upland areas. This study evaluated soil erosion in Nam Dong district, Central Vietnam, using the Universal Soil Loss Equation (USLE) model and the Analytic Hierarchy Process (AHP) based on local stakeholder input. The USLE employed spatial data on rainfall, soil, topography, and land cover, while the AHP incorporated the perspectives of nine diverse community members. Both models identified the mountainous central region as most at risk; the USLE classified 62% of land as extreme erosion, whereas the AHP classified 82% as severe. These differences reflect the empirical approach of USLE versus the perception-driven results of the AHP. The study found that applying both methods independently and comparing their outcomes can yield different soil erosion scenarios. Furthermore, additional research is recommended to explore the use of the AHP as a tool for calibrating the relative importance of input factors in the USLE model. This approach could enhance the accuracy of soil erosion risk assessments and support more effectively targeted conservation strategies in complex upland landscapes. 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 light of the increasing frequency and intensity of natural phenomena, whether climatic or telluric, the relevance of multi-risk assessment approaches has become an important issue for understanding and estimating the impacts of disasters on complex socioeconomic systems. Two aspects contribute to the worsening of this situation. First, climate change has heightened the incidence and, in conjunction, the seriousness of geohazards that often occur with each other. Second, the complexity of these impacts on societies is drastically exacerbated by the interconnections between urban areas, industrial sites, power or water networks, and vulnerable ecosystems. In front of the recent research on this problem, and the necessity to figure out the best scientific positioning to address it, we propose, through this review analysis, to revisit existing literature on multi-risk assessment methodologies. By this means, we emphasize the new recent research frameworks able to produce determinant advances. Our selection corpus identifies pertinent scientific publications from various sources, including personal bibliographic databases, but also OpenAlex outputs and Web of Science contents. We evaluated these works from different criteria and key findings, using indicators inspired by the PRISMA bibliometric method. Through this comprehensive analysis of recent advances in multi-risk assessment approaches, we highlight main issues that the scientific community should address in the coming years, we identify the different kinds of geohazards concerned, the way to integrate them in a multi-risk approach, and the characteristics of the presented case studies. The results underscore the urgency of developing robust, adaptable methodologies, effectively able to capture the complexities of multi-risk scenarios. This challenge should be at the basis of the keys and solutions contributing to more resilient socioeconomic systems. Full article

This study aims to investigate the processes associated with mass movements and their relationship with the behavior of the Amazon River delta-estuary (ADE) wetlands. The methodological approach involves using water spectral indices and ground-penetrating radar (GPR) to diagnose areas of soil water saturation and characterize regions affected by mass movements in Amazonian cities. It also involves identifying areas of critical saturation content and consequent mass movements. Analysis of risk and land use data revealed that the affected areas coincide with zones of high susceptibility to mass movements induced by water. The results showed the following: the accumulated annual precipitation ranged from 70.07 ± 55.35 mm·month⁻¹ to 413.34 ± 127.51 mm·month⁻¹; the response similarity across different sensors obtained an accuracy greater than 90% for NDWI, MNDWI, and AWEI for the same targets; and a landfill layer with a thickness variation between 1 and 2 m defined the mass movement concentration in Abaetetuba city. The interaction between infiltration, water saturation, and human-induced land alteration suggests that these areas act as wetlands with unstable dynamics. The analysis methodology developed for this study aimed to address this scenario by systematically mapping areas with mass movement potential and high-water saturation. Due to the absence of geological and geotechnical data, remote sensing was employed as an alternative, and in situ ground-penetrating radar (GPR) evaluation was suggested as a means of investigating the causes of a previously observed movement. Full article

In the landslide chain from pre-disaster conditions to landslide mitigation and recovery, time is an important factor in understanding the geological hazards process and managing landsides. Static knowledge graphs are unable to capture the temporal dynamics of landslide events. To address this limitation, we propose a systematic framework for constructing a multi-temporal knowledge graph of landslides that integrates multi-source temporal data, enabling the dynamic tracking of landslide processes. Our approach comprises three key steps. First, we summarize domain knowledge and develop a temporal ontology model based on the disaster chain management system. Second, we map heterogeneous datasets (both tabular and textual data) into triples/quadruples and represent them based on the RDF (Resource Description Framework) and quadruple approaches. Finally, we validate the utility of multi-temporal knowledge graphs through multidimensional queries and develop a web interface that allows users to input landslide names to retrieve location and time-axis information. A case study of the Zhangjiawan landslide in the Three Gorges Reservoir Area demonstrates the multi-temporal knowledge graph’s capability to track temporal updates effectively. The query results show that multi-temporal knowledge graphs effectively support multi-temporal queries. This study advances landslide research by combining static knowledge representation with the dynamic evolution of landslides, laying the foundation for hazard forecasting and intelligent early-warning systems. Full article

The city of Uvira, located in the eastern Democratic Republic of Congo (DRC), is increasingly experiencing flood events with devastating impacts on human life, infrastructure, and livelihoods. This study evaluates flood susceptibility in Uvira using Geographic Information Systems (GISs), and an Analytical Hierarchy Process (AHP)-based Multi-Criteria Decision Making approach. It integrates eight factors contributing to flood occurrence: distance from water bodies, elevation, slope, rainfall intensity, drainage density, soil type, topographic wetness index, and land use/land cover. The results indicate that proximity to water bodies, drainage density and slope are the most influential factors driving flood susceptibility in Uvira. Approximately 87.3% of the city’s land area is classified as having high to very high flood susceptibility, with the most affected zones concentrated along major rivers and the shoreline of Lake Tanganyika. The reliability of the AHP-derived weights is validated by a consistency ratio of 0.008, which falls below the acceptable threshold of 0.1. This research provides valuable insights to support urban planning and inform flood management strategies. Full article

Earth fill dams are susceptible to internal erosion and instability when founded over cavity-prone formations such as gypsum or karstic limestone. Subsurface voids can significantly compromise dam performance, particularly under seismic loading, by altering seepage paths, raising pore pressures, and inducing structural deformation. This study examines the influence of cavity presence, location, shape, and size on the behavior of zoned earth dams. A 1:25 scale physical model was tested on a uniaxial shake table under varying seismic intensities, and seepage behavior was observed under steady-state conditions. Numerical simulations using SEEP/W and QUAKE/W in GeoStudio complemented the experimental work. Results revealed that upstream and double-cavity configurations caused the greatest deformation, including crest displacements of up to 0.030 m and upstream subsidence of ~7 cm under 0.47 g shaking. Pore pressures increased markedly near cavities, with peaks exceeding 2.7 kPa. Irregularly shaped and larger cavities further amplified these effects and led to dynamic factors of safety falling below 0.6. In contrast, downstream cavities produced minimal impact. The excellent agreement between experimental and numerical results validates the modeling approach. Overall, the findings highlight that cavity geometry and location are critical determinants of dam safety under both static and seismic conditions. Full article

The seismicity levels in Oklahoma and southern Kansas have increased dramatically over the last 15 years. Past studies have identified the massive disposal of wastewater co-produced during oil and gas extraction as the driving force behind some earthquake clusters, with a small number of events directly linked to hydraulic fracturing (HF) stimulations. The present investigation is the first one to examine the role both of these activities played throughout the two states, under the same framework. Our findings confirm that wastewater disposal is the main causal factor, while also identifying several previously undocumented clusters of seismicity that were triggered by HF. We were able to identify areas where both causal factors spatially coincide, even though they act at distinct depth intervals. Overall, oil and gas operations are probabilistically linked at high confidence levels with more than 7000 felt earthquakes (M ≥ 2.5), including 46 events with M ≥ 4.0 and 4 events with M ≥ 5. Our analysis utilized newly compiled regional earthquake catalogs and established physics-based principles. It first hindcasts the seismicity rates after 2012 on a spatial grid using either real or randomized HF and wastewater data as the input, and then compares them against the null hypothesis of purely tectonic loading. In the end, each block is assigned a p-value, reflecting the statistical confidence in its causal association with either HF stimulations or wastewater disposal. Full article

Mechanically stabilized earth (MSE) retaining walls have become a favored substitute for traditional poured concrete walls due to their affordability, minimal site preparation needs, and practical construction advantages. However, using backfill material with too many small particles and poor drainage qualities may cause the wall to rotate and shift a lot or collapse completely, especially when water pressure is present. This study examines an MSE wall considering different variables, such as water pressure, the type of soil materials in the backfill materials, external load, and the type of analysis. To this aim, both PLAXIS V20 and SLOPE/W (GeoStudio 2019 Suite) software were employed, and after the verification, further investigations were carried out. These numerical analyses aligned with the real-world failure reported by previous researchers, departments, and companies. The findings suggest that the elevated presence of fine particles likely contributed to the wall’s excessive shift. Also, hydrostatic pressure behind a wall, especially in the rainy season, plays a crucial role in the factor of safety reduction by 45% and wall failure, which leads us to consider it an appropriate factor of safety for the MSE wall. Full article