GeoHazards doi: 10.3390/geohazards7040119

Authors: Tengiz Kiria Tamaz Chelidze Luca Brocca Avtandil Amiranashvili David Svanadze Nodar Varamashvili Tamar Tsamalashvili

Georgia, due to its high mountains, growth of population, intensive land use, and the number of vulnerable infrastructures (roads, large engineering constructions, etc.), as well as climate change, belongs to the one of most vulnerable regions in the world, as it is prone to hazardous geological processes such as landslides (LSs). As the statistical data on LSs in Georgia are of low quality, due to political turmoils in the first decades of XXI-th century, a three-stage methodology was applied for assessing LS susceptibility. On the first stage, we perform the initial statistical assessment of LS susceptibility, using 11 weighted objective factors analysis. Then the machine learning (ML) methods were used for obtaining the final map of LS susceptibility. In conditions of Georgia, the intensive and prolonged precipitation is one of the main triggering factors for activation of LS processes. Therefore, in this study we also use hourly precipitation data, meteorological station observations, a historical landslide catalogue and hybrid machine learning approaches to construct spatial-temporal LS hazard maps under 24 h, 3-day, 5-day, and 30-day cumulative precipitation conditions. Predictive performance was evaluated retrospectively using a balanced sample of 309 landslide events and 309 susceptibility-matched controls, including a temporal train–test split. The results characterize discrimination under this sampling design; performance at the natural frequency of landslides requires independent evaluation. The results obtained show that the acceleration of global warming in recent decades affects the assessment of LS susceptibility/hazard.

GeoHazards doi: 10.3390/geohazards7040118

Authors: Yuxuan Chen Fuqiong Huang Leyin Hu Zhiguo Wang Kongyan Han Peixue Hua Xiaoru Sun Mingbo Yang Shijun Zhong

Groundwater level responses to solid tides in confined wells provide a means for investigating aquifer parameter variations and earthquake-related effects. Using hourly water-level observations from eight confined wells of the Beijing seismic monitoring well network (January 2017–December 2025), this study applied the Baytap-G program to extract the M2 tidal constituent contribution, amplitude, tidal factor, and phase lag, and analyzed their temporal variations and responses to earthquakes. The eight wells are classified into five groups: Group 1 (BQ, CP), stable during non-interference intervals but with permanent instrument-induced jumps; Group 2 (MF, XJ), stable background references; Group 3 (LX), reflecting genuine hydrological processes; Group 4 (DHC, XXZ), signals too weak for reliable analysis; and Group 5 (WLY), dominated by persistent instrumental disturbances. Using mean ±3σ thresholds derived from seismically quiet periods, nine persistent ≥3σ anomaly segments were identified; none coincides in time with the 14 Ms ≥ 4.0 earthquakes or the 41 coseismic water-level response events, and all can be attributed to documented instrument events. The hypothesis that earthquakes alter M2 parameters before or after their occurrence is not supported, nor is the hypothesis that coseismic water-level responses produce short-term M2 parameter changes; the hypothesis that instrument operational conditions and long-term hydrological changes dominate the observed variations is supported. The absence of earthquake-triggered M2 parameter responses is attributed to basin attenuation, limited strain conversion efficiency, response mechanism decoupling, and observational resolution. These results provide a background reference for applying well water-level tidal parameters to earthquake precursor monitoring in the Beijing area, showing that independent baselines must be established for each well and that instrument operational records are necessary for anomaly identification.

GeoHazards doi: 10.3390/geohazards7040117

Authors: Omar Djoukbala Salim Djerbouai Samra Harkat Nikola Milentijević Aleksandar Valjarević

Floods are among the most destructive natural hazards worldwide, causing significant environmental degradation, economic losses, and social disruption. This study aims to delineate flood-susceptible zones within the Mekerra Wadi Watershed in northwestern Algeria by applying an integrated approach combining remote sensing techniques, Geographic Information Systems (GIS), and the Analytical Hierarchy Process (AHP), a widely used multi-criteria decision analysis method. Ten conditioning factors influencing flood occurrence were considered, including elevation, slope, precipitation, Topographic Wetness Index (TWI), Normalized Difference Vegetation Index (NDVI), drainage density, distance from streams, Stream Power Index (SPI), soil type, and Land Use/Land Cover (LULC). The AHP method was employed to determine the relative importance of each factor, and the resulting weights were integrated through GIS-based weighted overlay analysis to generate a spatial flood susceptibility map. The findings classified the basin into five susceptibility categories, ranging from very low to very high flood susceptibility. The highest susceptibility areas were mainly associated with low-lying terrain, gentle slopes, high drainage accumulation, and proximity to river networks, whereas elevated regions with steeper slopes exhibited lower flood susceptibility. Model performance assessment using the Receiver Operating Characteristic (ROC) curve yielded an Area Under the Curve (AUC) value of 0.915, indicating a high predictive capability. Furthermore, the reliability of the model was confirmed through validation using historical flood events recorded between 2017 and 2019 and in 2022, showing a strong spatial correspondence between predicted susceptibility zones and observed flood occurrences. The resulting flood susceptibility map provides an effective decision-support tool for flood hazard assessment, sustainable land-use planning, and the development of targeted disaster risk reduction strategies in the Mekerra Wadi Watershed.

GeoHazards doi: 10.3390/geohazards7040116

Authors: Mostafa Sadeghnejad Ali Moradi Laura Moley

Landslides are among the most destructive natural hazards in mountainous and environmentally sensitive regions, causing significant damage to infrastructure, ecosystems, and human life. This study proposes a framework as a prototype Geo Digital Twin for landslide susceptibility assessment and scenario analysis in Eastern Kentucky, USA. A Random Forest model was developed using topographic, hydrological, geological, and environmental conditioning factors, including aspect, elevation, lithology, distance to streams, and NDVI. The model achieved strong predictive performance, with an accuracy of 0.87, an F1 score of 0.85, and a ROC–AUC of 0.94. The trained model was integrated into a service-oriented prototype Geo Digital Twin platform implemented with Django and Mapbox, enabling interactive spatial visualization and scenario simulation. In particular, vegetation change scenarios were evaluated by modifying NDVI values to examine their influence on landslide susceptibility. To improve the interpretation of these scenario outcomes, a fuzzy inference system was introduced by combining changes in predicted susceptibility (ΔP) with NDVI values into a Fuzzy Impact Index (FII). The fuzzy analysis indicates that vegetation reduction can substantially alter slope responses depending on baseline environmental conditions. The results demonstrate that the proposed framework not only provides accurate susceptibility mapping but also facilitates explainable scenario analysis to support geospatial decision-making regarding landslides.

GeoHazards doi: 10.3390/geohazards7040115

Authors: Zicheng Yi Cuiqiong Zhou Cheng Huang Hongbo Mei

Traditional hazard assessment often relies on simple spatial overlays of static susceptibility and dynamic rainfall thresholds, ignoring the spatial heterogeneity of geological responses to rainfall. To address this limitation, this study proposes a meteorological hazard assessment and dynamic early warning framework for Nujiang Prefecture, Yunnan Province, driven by heuristic spatial heterogeneity weighting. Specifically, this study introduces an S-T-C (Susceptibility–Rainfall trigger index–Causal-heuristic modulation factor) coupling framework that employs Causal Forest Double Machine Learning (CF-DML) to approximate conditional rainfall–geohazard associations and integrates them with static susceptibility and dynamic rainfall threshold modeling for warning zoning. The framework combines an antecedent effective rainfall threshold model (Antecedent Effective Rainfall Intensity–Duration–Daily Rainfall, EI-D-R) with an AutoGluon-based susceptibility model (AUC = 0.9178), and uses CF-DML as a flexible non-linear estimator to approximate conditional responses modulated by environmental factors. This heuristic adjustment is then incorporated into the S-T-C coupling framework. A retrospective case application shows that at the same observed Probability of Detection (POD = 76.5%), the S-T-C framework produces a more spatially selective warning footprint compared to traditional S-T product coupling, with very low-hazard zones expanding from 32.67% to 70.64% (a relative increase of 116.19%). Rather than claiming validated causal identification, this work illustrates that using CF-DML as an association-based, heuristic spatial-heterogeneity weighting approach can provide a more spatially explicit and retrospectively evaluated basis for geohazard assessment and regional risk management, subject to the data and modeling limitations discussed.

GeoHazards doi: 10.3390/geohazards7040114

Authors: Nida Khursheed Asif Sajjad Mazhar Iqbal Rana Waqar Aslam

Floods in monsoon-dominated river basins exhibit high spatio-temporal variability, necessitating high-resolution, multi-sensor approaches for reliable monitoring and impact assessment. In flood-prone agricultural regions, continuous monitoring using optical remote sensing is frequently hindered by dense monsoon cloud cover. This study establishes a comprehensive multi-sensor framework within the Google Earth Engine (GEE) to examine the spatio-temporal dynamics and land surface impacts of the 2025 monsoon floods in Punjab, Pakistan. Flood inundation mapping was executed using a 12-day Sentinel-1 Synthetic Aperture Radar (SAR) time series via a dual-threshold change detection methodology. Concurrently, Sentinel-2 imagery facilitated the derivation of land use/land cover (LULC) changes and vegetation dynamics using a Random Forest classifier, achieving overall accuracy of 93% (pre-flood), 91% (during flood), and 94% (post-flood). These accuracy levels were consistent across all three phases despite spectral confusion between water, saturated soil, and vegetation during peak inundation, indicating consistent classification performance under monsoon conditions. The analysis revealed a distinct bimodal flooding regime, characterized by an early monsoon peak in July–August and a more severe late monsoon peak in August-September. The cumulative maximum flood extent reached 9495.33 km2, with peak single-date inundation reaching 5449 km2. Mapped cropland declined by 6.7% (8181 km2) during peak flooding, with 3.9% (4796 km2) remaining non-cropland by the end of the observation period; 5892 km2 of pre-flood cropland was identified as inundated through spatial intersection. In addition, the Normalized Difference Vegetation Index (NDVI) declined by 28.6%, from 0.28 to 0.20, indicating a substantial reduction in vegetation greenness. Spatial consistency was checked with the United Nations Satellite Centre (UNOSAT) and the Food and Agriculture Organization (FAO), independently collected data showing moderate spatial agreement. The proposed framework is highly scalable for continuous flood monitoring, offering critical insights for disaster management and climate adaptation planning in monsoon regions plagued by data scarcity and persistent cloudiness. The approach is particularly relevant for near-real-time operational monitoring, given its reliance on freely available Sentinel data and cloud-based processing that requires no specialized ground infrastructure.

GeoHazards doi: 10.3390/geohazards7040113

Authors: Weizhen Gui Yuanjian Wang Yahui Qiu Yan Chen Peixian Li

Surface deformation triggered by coal extraction activities, together with the consequent development of unstable slopes within rugged mountainous landscapes, constitutes a critical focus for geological risk assessment and mitigation strategies. Conventional SBAS-InSAR processing pipelines suffer from inadequate tropospheric phase mitigation in topographically complex environments, while existing clustering-based recognition approaches fail to incorporate sufficient geophysical constraints. To overcome these deficiencies, the present investigation introduces a refined methodology that synergizes InSAR measurements with an enhanced clustering scheme for the automated screening of potentially unstable slope units. First, a two-stage coupled atmospheric correction framework is constructed within the SBAS-InSAR processing chain, comprising spatially varying stratified atmosphere estimation based on geographically weighted robust regression (GWRR-M) and turbulent atmosphere compensation based on structure-guided deformation-preserving interpolation (SGDPI); both stages require no external meteorological data and effectively protect deformation signals from overcorrection. Second, a spatiotemporally constrained density peak clustering algorithm (STC-DPC) is developed, which constructs a multi-dimensional feature space integrating spatial location, deformation rate, temporal evolution characteristics, and topographic-geological background, and introduces a spatiotemporally constrained distance metric together with an Unstable Slope Index (USI) to achieve automatic identification and quantitative discrimination of unstable slopes. The proposed method was evaluated using 120 ascending-track Sentinel-1A SAR images acquired from 2019 to 2023 over the coal-mining mountainous areas of Mentougou and Fangshan districts in western Beijing, China. The results show that the improved atmospheric correction reduces the phase standard deviation of a representative interferogram from 1.6 rad to 0.6 rad, with an average reduction of 42.3% across all interferograms. A total of 187 unstable slopes were identified by the STC-DPC algorithm, mainly distributed in abandoned mining areas and steep terrain with gradients of 10–35°, with a mean deformation rate of −25.3 mm/a; field investigations at representative sites confirmed significant deformation evidence (e.g., tension cracks and bulging), providing qualitative support for the identification results. Compared with the identification results obtained without atmospheric correction (79 unstable slopes), the improved method improves the detectability of weak deformation signals in areas with strong topographic relief and diverse deformation patterns. This study provides a practical technical pathway for the early screening and monitoring of geological hazards in coal-mining mountainous areas and holds great significance for mine ecological restoration and regional disaster prevention and mitigation.

GeoHazards doi: 10.3390/geohazards7040112

Authors: Agust Gudmundsson

In comparison with stratovolcanoes, shield volcanoes tend to have more frequent dike-fed eruptions and large lateral and vertical collapses, as well as more gently dipping flanks. In many stratovolcanoes, dike-fed eruptions occur once every several hundred or thousand years but once every few years in many shield volcanoes. Using Hamilton’s principle of least action as a basis for determining potential dike/sheet propagation paths, it is shown that the probability of arrest of an injected dike/sheet is normally much greater in a stratovolcano than in a shield volcano. This is primarily because in stratovolcanoes rock layers and units are of contrasting mechanical properties, so that many dikes become arrested and thus do not feed eruptions. Similarly, many faults in stratovolcanoes become confined to one or several layers/units and do not reach the surface to generate landslides or ring faults. Consequently, the formation of large landslides is generally more difficult—requires more energy—in composite volcanoes than in shield volcanoes. For the same reason, formation of calderas in stratovolcanoes is normally more difficult than in shield volcanoes. More energy is needed to propagate fractures through many layers/units in stratovolcanoes than in shield volcanoes. It follows that stratovolcanoes tend to be tougher, more resistant to tectonic fracture propagation, and thus mechanically stronger than shield volcanoes. This may partly explain differences in the frequencies of dike-fed eruptions, large landslides, and caldera collapses between shield volcanoes and stratovolcanoes.

GeoHazards doi: 10.3390/geohazards7040111

Authors: Tilia Battaglini-Fischer Tran Van Ty Dinh Van Duy Lam Tan Phat Mireille Martens Nigel K. Downes

Riverbank erosion threatens settlements, infrastructure, and river-dependent livelihoods along the Bassac River in the Vietnamese Mekong Delta. This study examines long-term bankline change from 2001 to 2025 and develops expert-informed priorities for assessing livelihood vulnerability within the Can Tho reach. Six Landsat images were analysed in QGIS using the Linear Regression Rate method, while present-day hydraulic conditions were investigated through Acoustic Doppler Current Profiler measurements at five representative locations. An Analytic Hierarchy Process based on interviews with 10 experts was used to derive relative weights for livelihood sensitivity and adaptive-capacity indicators and variables. Accretion was more spatially extensive than erosion along both banks; however, the left bank experienced a greater total extent and magnitude of erosion. Spatially extensive erosion was identified in Binh Thuy, whereas more intense but localised hotspots occurred near Cai Rang and Cai Von. The exploratory hydraulic observations varied among the five selected locations but showed no consistent correspondence with historical erosion magnitude and are therefore interpreted only as a snapshot of conditions on the survey date. Experts assigned weights of 0.547 to sensitivity and 0.453 to adaptive capacity. Savings capacity, decreased food production, extent of land loss, and the ability to shift livelihoods were among the highest-ranked variables. The physical and expert-derived findings support a differentiated and staged approach to riverbank-risk management, but they should be interpreted as complementary evidence rather than as a household-level vulnerability assessment. Future research should combine repeated seasonal hydraulic and bathymetric surveys, bank-material investigations, exposed-asset mapping, and household-based vulnerability assessments.

GeoHazards doi: 10.3390/geohazards7040110

Authors: Sibonakaliso Goodman Chiliza Egerton D. C. Hingston Molla Demlie

Rainfall-induced landslides pose a significant threat to communities and infrastructure in the eThekwini Metropolitan Region, South Africa. This paper presents a geotechnical–hydrogeological property zonation and parameterisation framework developed to support future physically based slope stability modelling. Using a weighted sum analysis in a GIS environment, the landscape was subdivided into distinct property zones by integrating lithology, slope gradient, and landform, with weights derived from a fully reproducible renormalisation of a previously published regional frequency ratio (FR) susceptibility model. This procedure provided the foundation for assigning zone-specific parameters, including effective shear strength parameters (c′ and ϕ′) and saturated hydraulic conductivity (Ksat), derived from laboratory testing, borehole pump testing analysis, and empirical relationships. The approach delineated four geotechnical–hydrogeological zones. A correlation of these zones against an inventory of 819 landslides revealed that over 82% of failures have occurred within Zones 2 and 3. While the hydrogeological conditions of these two susceptible zones range from intermediate to low permeability (Ksat = 10−5 to 10−8 m/s), which promotes transient pore pressure build-up, their high failure frequency corresponds closely with shared low shear strength (c′ = 5 kPa) and comparatively low effective friction angle (ϕ′ = 27.5–30°). This identifies shear strength as an important predisposing control on instability, relative to the inherently more stable Zones 1 and 4 (c′ = 10–15 kPa, ϕ′ = 30–35°). Consequently, this zonation and parameterisation approach advances landslide hazard assessment by providing a reproducible, model-ready dataset intended for future transient rainfall-infiltration simulations (e.g., TRIGRS), laying the groundwork for physically based early-warning systems, and supporting risk-informed urban development.

GeoHazards doi: 10.3390/geohazards7040109

Authors: Álvaro-Francisco Morote Daniel López-Rodríguez Bàrbara Micó-Vicent Jorge Jordán-Núñez Antonio Belda

Education on natural hazards is a non-structural component of Disaster Risk Reduction (DRR), but the evidence base spans curriculum studies, risk-perception research, educational interventions, geospatial approaches and analyses of education-system continuity. This systematic narrative review synthesizes 27 outcome-bearing studies published between 2013 and the partial year 2026. PRISMA 2020 was used as a reporting framework, while PRISMA-S informed a retrospective audit of the search documentation. A structured design-sensitive appraisal recorded evidence family, comparison or temporal structure, outcome directness, permitted inference and principal limitation. The studies were coded into six mutually exclusive primary axes: reviews and frameworks; curriculum and policy; knowledge and risk perception; educational interventions and active methodologies; GIS and geospatial technologies; and educational continuity and system resilience. The included literature suggests that locally situated problems, maps, simulations and inquiry can support knowledge, risk appraisal and preparedness intentions, although demonstrated effects on sustained performance or actual preparedness behavior remain limited. Cross-cutting gaps include weak longitudinal assessment, sparse attention to teacher professional development, limited treatment of indigenous or local knowledge, and no core study centered on learners with disabilities or special educational needs. The review defines critical territorial risk literacy as the capacity to interpret hazard, exposure, vulnerability, capacity and uncertainty through spatial evidence; evaluate their unequal territorial distribution; and translate that understanding into inclusive, proportionate preparedness and collective action.

GeoHazards doi: 10.3390/geohazards7040108

Authors: Ariana Rivera Luis E. Pineda

Landslide susceptibility assessment in data-scarce environments remains challenging. In the northern Andes of Ecuador, the interaction of hypothesized triggers with confounding predisposing factors of landslide occurrences is limited. We investigate the relationship between landslide records and geological, topographic, land use, vegetation and climatic factors in the province of Imbabura using generalized linear models (GLM) and generalized additive models (GAM). Both models are instrumental in identifying that a rainfall increase of one standard deviation in monthly precipitation raises the odds of landslide occurrence, with estimates of 8.84 and 15.84, respectively. The GAM slightly outperformed the GLM by capturing modest non-linear effects, particularly for elevation and profile curvature. Elevation and slope aspect show non-linear and linear tendencies, respectively, although their effects were marginal rather than significant at the 5% level in the selected GAM. Landslides were more likely under wetter conditions at intermediate elevations and on northwestern-facing slopes where ground moisture gradients condition slope stability. Furthermore, the combined effect of agricultural and livestock land uses did not show influence, calling for attention on effects that the scale of analysis did not address. The results provide a baseline framework for rainfall-related landslide occurrence assessment in developing regions with limited data availability.

GeoHazards doi: 10.3390/geohazards7040107

Authors: Lawrence Madziwa Heike Wanke

Geohazards are present at every stage of a mine’s life cycle (initial exploration, site investigations, active operations, closure, reclamation, legacy management). This study has reviewed the literature covering mining and geohazards gathered from the Scopus bibliographic database. Quantitative metadata analysis was conducted on keyword co-occurrence within the 150 selected publications, and thematic clustering was mapped. In addition, five case studies were analysed to add further in-depth analysis. The publication volume shows a sharp uptrend starting around 2015, and 45% of the articles indicate a corresponding author from China. Publications more often cover geohazards in underground mines than open-pit/surface mining. AI methods are a rapidly evolving subject. Overall, the review reveals an imbalance in research attention across different stages of the mine life cycle. While only approximately 6% of the literature addresses exploration-stage geohazards, the case studies demonstrate that early identification is critical. In conclusion, technical capabilities for geohazard monitoring have advanced dramatically, especially with interferometric synthetic aperture radar (InSAR) deformation analysis, machine learning classification, and multi-sensor data fusion; however, the field suffers from systematic integration of geohazards across the mine life cycle.

GeoHazards doi: 10.3390/geohazards7040106

Authors: Muhammad Zain Bin Riaz Umair Iqbal Huda Zain Muhammad Naveed Anjum Saddam Hussain

The global active satellite population has increased from fewer than 3000 objects in 2020 to more than 14,000 by the end of 2025, while filed megaconstellation plans suggest that tens of thousands of additional satellites may be deployed over coming decades. This rapid expansion of low Earth orbit (LEO) infrastructure has raised concerns regarding novel anthropogenic inputs to the upper atmosphere, particularly black carbon from rocket launches and aluminium oxide nanoparticles generated during satellite re-entry. This review synthesises literature published between 2000 and 2026 across atmospheric chemistry, aerosol science, climate dynamics, and hydrology to evaluate the potential pathways through which these emissions may influence precipitation processes and flood risk. The evidence indicates strong support for several upstream mechanisms, including alumina-mediated ozone chemistry, anthropogenic metal accumulation in stratospheric aerosols, and the disproportionately high radiative forcing efficiency of rocket-derived black carbon. However, substantial uncertainties remain regarding the extent to which these atmospheric perturbations propagate through climate and hydrological systems. This review identifies the current state of knowledge, highlights areas of agreement, uncertainty, and contradiction within the literature, and outlines priority directions for future research, monitoring, modelling, and governance. The findings suggest that while satellite-driven changes to precipitation and flood risk remain unconfirmed, the rapid expansion of megaconstellation activity warrants further investigation within integrated Earth-system frameworks.

GeoHazards doi: 10.3390/geohazards7040105

Authors: Jaime Bonachea

In recent decades, there has been a marked increase in the frequency of natural disasters on a global scale. This increase is particularly notable in the context of climatological disasters, such as wildfires, which have become increasingly prevalent and intense in past years. It is evident that as the planet experiences the repercussions of climate change, the severity of these fires will intensify. The present study focuses on the analysis of wildfires that have occurred in Spain in recent years, both in terms of their number and the area affected, using data collected from the national and international databases. Since the beginning of this century, there has been an increasing trend in the number of large wildfires (>500 ha) in this country. In contrast, there has been a decline in the overall number of wildfires. However, when analyzing a more extended period, spanning from 1970 onward, these trends become less discernible. The study also analyzes the differences between some of these databases and notes that, despite the fact that certain databases offer exhaustive documentation of burned areas, others exhibit specific limitations due to a variety of factors. These limitations may include the nature of the recorded data, the resolution of wildfire detection or wildfire perimeter identification detection systems, or the recent initiation of data collection for such events. The development of strategies based on historical data and predictive models is necessary for anticipating future scenarios and mitigating the impacts of wildfires.

GeoHazards doi: 10.3390/geohazards7040104

Authors: Fabio Lucioli Valerio Baiocchi Luca Maria Falconi Lorenzo Moretti Rosario Napoli Maurizio Pollino Claudio Puglisi Gaia Righini

The role of land use/land cover (LULC) dynamics in predisposing slopes to shallow landsliding is widely acknowledged but seldom translated into operational susceptibility modelling. Most data-driven approaches still treat LULC as a static factor, neglecting the legacy effects of recent transitions. This study presents a methodological framework to quantify the influence of multi-temporal LULC changes on shallow landslide initiation and to incorporate this information into susceptibility mapping. The procedure was tested in the Metropolitan City of Messina (formerly known as the Province of Messina), Southern Italy, a representative Mediterranean area repeatedly affected by rainfall-triggered slope failures. Freely available LULC maps from 1990 to 2006 were processed through post-classification change detection to identify dominant land cover trajectories. Preliminary analyses within buffer areas showed higher landslide indices (LI, LAI) and Frequency Ratios for some transition classes, suggesting a potential role of LULC changes. These findings motivated the comparison between a static LULC configuration and a dynamic one incorporating the detected transitions within a Frequency Ratio susceptibility model. The dynamic model did not improve the mean Area Under the Curve (AUC) compared to the static model (0.7774 vs. 0.7742), and the observed reduction in variability across five independent random splits (standard deviation 0.012 vs. 0.064) should be considered preliminary. The proposed workflow, based entirely on open data and GIS-based processing, offers a transparent and reproducible methodology for integrating LULC transitions into dynamic susceptibility maps. The use of higher-resolution input data could potentially reduce the scale mismatch and improve the detection of fine-scale transitions, supporting more effective landslide risk mitigation and evidence-based land planning.

GeoHazards doi: 10.3390/geohazards7040103

Authors: Tingting Wei Xi Chen Peiyao Li Jianxun Yang

The shear behavior of loess is closely linked to its microstructural evolution, and understanding this relationship is essential for deciphering the mechanisms of loess hazards. In this study, consolidated-drained (CD) triaxial tests were conducted on intact Q3 Malan loess from the Dongzhi tableland, China, under varying water contents and confining pressures. Scanning electron microscopy (SEM) and mercury intrusion porosimetry (MIP) analyses were performed on specimens before and after shearing to quantitatively and qualitatively characterize the changes in pore and particle properties and their connection to shear deformation. The results reveal three failure modes, including shear, homogeneous, and plastic failure. They are governed by the combined effects of microstructural variation and microcrack development, depending on confining pressure and water content. Quantitatively, as water content increases from 9% to 20%, cohesion decreases by 86.8% and peak shear strength reduces by 68.4%, while the internal friction angle decreases only slightly. Water-induced strength deterioration is governed primarily by cohesion loss rather than friction angle reduction. Thus, 20% water content was identified as the critical threshold marking the transition from cohesion-dominated to friction-dominated strength degradation. A critical threshold at approximately 27% water content is identified, beyond which about 70% of mesopore and macropore volumes undergo collapse, after which the strength is almost entirely sustained by interparticle friction. Based on these findings, the water-induced strength decay mechanism is categorized into three stages: rapid cement degradation, friction-dominated transition, and slow attenuation. These macroscopic phenomena are closely linked to the continuous adjustment of the microstructure, manifested by the softening, dispersion, and disintegration of cementations, particle movement and rearrangement, and the reduction and mutual transformation of inter-aggregate pores under loading and wetting. The three-stage mechanism and threshold characteristics of loess strength degradation upon wetting revealed in this study can provide theoretical support for early slope-instability warning in loess irrigation and heavy rainfall regions, as well as engineering reinforcement prioritizing the recovery of cohesion.

GeoHazards doi: 10.3390/geohazards7040102

Authors: Aleksandar Dedić Srdjan Svrzić Marija V. Paunović Milan Milenković Violeta Babić Stefan Denda Uroš Durlević

This study presents an integrated statistical framework for identifying representative large-scale climate teleconnection indices associated with total burned area and for supporting the selection of climate predictors in wildfire-related statistical models. A large set of seasonally resolved climate indices, including the North Atlantic Oscillation (NAO—two versions), the Arctic Oscillation (AO), the Atlantic Multidecadal Oscillation (AMO), the Mediterranean Oscillation (MO—two versions), the East Atlantic–West Russia pattern (EAWR), the Tropical North Atlantic (TNA), and the Atlantic Meridional Mode (AMM), was examined. Because many of these indices describe related atmospheric and oceanic processes, dimensionality reduction and predictor selection were required to limit multicollinearity. Principal component analysis (PCA) was first used to identify groups of interrelated climate indices, followed by partial correlation analysis to distinguish redundant predictors from those retaining independent information with respect to total burned area. Finally, LASSO regression was applied to evaluate the relative explanatory contribution of candidate indices and to perform automatic variable selection. The PCA solution identified ten rotated components explaining 82.31% of the total variance. The results indicate that several seasonal NAO and MO indices contain highly overlapping information, whereas selected indices, particularly MOI2 spring and MOI2 summer, retain comparatively stronger independent associations with total burned area. The integrated PCA–partial correlation–LASSO framework provides a systematic approach for reducing redundant climate predictors and identifying large-scale climate signals that may be informative for understanding variability in total burned area and for supporting statistical analyses of wildfire–climate relationships.

GeoHazards doi: 10.3390/geohazards7030101

Authors: Ioannis Vlachos Dionysios T. G. Katerelos Markos Avlonitis Nikos Aravantinos-Zafiris Ioannis Karydis

Unstable rock blocks and cliffs pose a widespread geohazard, and their mechanical state can be tracked through their ambient-vibration resonance frequencies, whose decrease anticipates progressive failure. Such monitoring is usually performed with expensive broadband instrumentation, limiting spatial and temporal coverage. Here we assess whether a low-cost, IoT-enabled node—built around a Raspberry Pi single-board computer, a 24-bit sigma-delta digitiser and a force- balance accelerometer (Geobit FBA-200)—can identify the resonance of an unstable coastal rock block at the celebrated “moving rock” of Kounopetra (Paliki peninsula, Kefalonia, Greece), a site historically renowned for visually perceptible rocking boulders. We stress that the low-amplitude 7.7 Hz structural eigenvibration characterised here is a distinct phenomenon from the historically documented ∼0.3 Hz macroscopic, quasi-rigid rocking of the boulder: the former is the ambient–vibration resonance of the fractured rock mass, the latter a large-amplitude rigid-body oscillation. Two identical nodes recorded ground acceleration simultaneously for nine hours: one on the fractured Kounopetra rock mass and one on stable ground 25 m away, used as a reference. The rock station exhibits a clear, temporally stable fundamental resonance at f0 = 7.7 Hz (Q ≈ 50, damping ζ ≈ 1%), amplified by up to an order of magnitude relative to the reference and entirely absent from it, whereas a narrow 20.5 Hz line present on both nodes is identified as instrument-related and discarded. A simultaneous two-station analysis further shows that the ambient sources are extremely local (only 0.4% of transient activity is common to the two nodes 25 m apart), quantifying a design constraint for differential schemes. The results demonstrate that a low-cost force-balance node is sufficient to establish a resonance baseline for an unstable rock block, opening the way to dense, affordable early-warning networks; the main limitations are the single vertical component and the short record, which preclude polarisation analysis and long-term tracking of f0.

GeoHazards doi: 10.3390/geohazards7030100

Authors: Zeyu Liang Aixia Dou

On 18 May 2026, a M5.2 double earthquake struck the Taiyangzhen area of Liunan District, Liuzhou City, Guangxi, China, triggering shallow surface collapses in this karst terrain. We conducted three UAV orthophoto surveys of the meizoseismal area on 20 May, 23 May, and 24 May, and interpreted 17 collapse monitoring units from the imagery. The total collapse area increased from 75.3 m2 on 20 May to 499.1 m2 on 23 May, and further to 553.9 m2 on 24 May. On 20 May, only 7 of 17 units exhibited collapses; by 23 May, all 17 units were affected. Among them, 7 pre-existing collapse patches expanded, and 10 new collapses emerged between 20 and 23 May. Depth measurements revealed measurable depths of 0.18–7.60 m for 7 collapses, and all 6 units with bi-temporal depth data showed continued deepening from 23 to 24 May. Ponding water was observed in up to 10 units, consistent with the 98.7 mm of rainfall recorded during 18–24 May. Multi-temporal UAV surveys reveal that post-seismic surface collapse development in karst terrain extends well beyond the mainshock, with both rapid expansion of pre-existing failures and delayed emergence of new collapses driven by the coupled effects of seismic weakening and hydrologic forcing.

GeoHazards doi: 10.3390/geohazards7030099

Authors: Asmae El Karma Benaissa Kissi Hamza Khatib

Weathered marl hillslopes fail repeatedly across peri-urban Morocco, yet engineers investigating them rarely know which soil or geometric property most deserves their limited testing budget. This study answers that question for the landslide-prone slopes of Moulay Yacoub, in the northern pre-Rifian domain, by ranking the sensitivity of the factor of safety (FoS) to cohesion (c), friction angle (φ), unit weight (γ), slope height (H) and slope angle (β) under dry, deep-water-table conditions. Latin hypercube sampling generated 400 configurations over ranges drawn from site data; the FoS of each was computed by Bishop’s simplified method in Talren, and regional sensitivity analysis—the two-sample Kolmogorov–Smirnov statistic with a relative sensitivity index—ranked the five inputs. Cohesion governs the response by a wide margin (D = 0.470; 38.2% of total sensitivity at FoS = 1.2), ahead of slope height and friction angle (D ≈ 0.26); slope angle is marginal, and unit weight is not discriminating. Repeating the analysis at four thresholds (1.1–1.4) shows that the primacy of cohesion is threshold-independent, and that the apparent significance of slope angle at stricter thresholds is a statistical power effect, not a mechanical one. Site investigation in comparable marl settings should prioritise cohesion characterisation.

GeoHazards doi: 10.3390/geohazards7030098

Authors: Mikayel Gevorgyan Gohar Hovhannisyan Arkadi Karakhanyan Hektor Babayan Suren Arakelyan Gevorg Babayan Elya Sahakyan Lilit Sargsyan

Armenia is located within the Arabia–Eurasia collision zone and is exposed to a significant seismic hazard associated with active fault systems capable of generating destructive earthquakes. The 1988 Spitak earthquake highlighted the vulnerability of Armenian urban areas and the need for reliable seismic risk assessment methods. This study presents the first harmonized scenario-based seismic risk assessment framework for six major Armenian cities by integrating seismotectonic source characterization, deterministic ground-motion modeling, locally derived Vs30-based site characterization, GIS-based exposure modeling, and vulnerability assessment within the ELER (Earthquake Loss Estimation Routine) platform. Vulnerability functions were adapted to Armenian building typologies and calibrated using observed damage from the 1988 Spitak earthquake. Deterministic earthquake scenarios (Mw 6.5–7.3) were developed based on the seismic potential of the country’s principal active fault systems. The results reveal substantial spatial variability in seismic risk controlled by differences in ground-motion intensity, local site conditions, building vulnerability, and population exposure. Masonry-dominated urban areas exhibit the highest relative structural losses, whereas Yerevan experiences the greatest absolute losses because of its large population and concentrated building stock. Severe damage and collapse (D4–D5) may affect more than 20–25% of buildings in the most vulnerable cities. Validation against observed 1988 earthquake damage demonstrates the applicability of the proposed framework for seismic risk reduction, emergency preparedness, and long-term urban resilience planning in Armenia.

GeoHazards doi: 10.3390/geohazards7030097

Authors: Jin Li Shu Zhu Yanbing Wang Xuwen Tian Xin Yao Zhenkai Zhou

The southeastern Tibetan engineering corridor hosts the densest transportation network in Tibet, China, and is traversed by large-scale railway and power corridor projects under construction. This region is home to numerous glacial lakes, some of which are prone to glacial lake outburst floods (GLOFs), posing potential threats to the infrastructure. However, the spatiotemporal evolution and GLOF susceptibility of these lakes remain unclear. Using Landsat 5–9 and Sentinel-2 satellite imagery, we analyzed the spatiotemporal characteristics of glacial lakes from 1990 to 2020. Based on historical GLOF events, we established a susceptibility assessment criterion and determined the susceptibility levels of all glacial lakes in the study area. Results show that the number and area of glacial lakes increased by 40.4% and 26.2%, respectively, from 1990 to 2020, with expansion rates of 2.47 lakes/year and 0.26 km2/year. We identified 31 very highly and 48 highly susceptible lakes, mainly distributed along the Gongrigabu River and the Parlung Tsangpo River. Among them, 35 lakes are most likely to impact National Highways G219 and G318 within the study area. Additionally, three channels with glacial lake clustering amplification effects were found, which may lead to the superposition and amplification of flood impacts, significantly increasing GLOF risks and hazards. Our findings provide crucial references for ensuring the safe operation of local transportation networks and reducing GLOF risks in ongoing large-scale construction projects.

GeoHazards doi: 10.3390/geohazards7030096

Authors: Rolly E. Rimando Deo Carlo E. Llamas Bryan J. Marfito

Arduino-based creepmeters utilizing a Linear Variable Differential Transformer (LVDT) and ultrasonic sensors were fabricated to monitor displacement changes along the creeping segment of the West Valley Fault (WVF) in southeastern Metro Manila, Philippines. Along with a custom-assembled, Arduino-based rain gauge, these instruments were initially intended to prevent data gaps during the COVID-19 pandemic when commercial data recorders experienced operational downtime. However, they have since proven to be cost-effective alternatives for determining short-term slip rates and monitoring displacement variations driven by episodic and seasonal precipitation changes. The LVDT creepmeter provides higher accuracy for displacement and slip rate determination. Conversely, the ultrasonic creepmeter is better suited for tracking abrupt displacement changes and, to some extent, longer-term displacement trends as it is more sensitive to environmental conditions. Deploying low-cost monitoring instruments in active fault regions bridges critical data gaps and improves the understanding of creep triggers and mechanisms. Although vertical creep occurs along pre-existing tectonic features of the WVF creeping segment, our creepmeter monitoring reveals sustained, accelerated creep within its southern portion. This localized movement is driven primarily by nontectonic forces—chiefly groundwater extraction, with episodic and seasonal precipitation influences. Consequently, this implies a continued ground rupture hazard and the potential for induced seismicity.

GeoHazards doi: 10.3390/geohazards7030095

Authors: Assiel Mugabe Telesphore Kabera Felicien Majoro Leopold Mbereyaho Ma-Lyse Nema

Flood susceptibility mapping is crucial for understanding flood-prone areas and mitigating the associated risks in vulnerable regions like the Sebeya Catchment. This study adopted a GIS-based Analytical Hierarchy Process (GIS-AHP) integrated with local community knowledge to evaluate flood susceptibility using 10 conditioning factors: Topographic Wetness Index (TWI), Elevation, Rainfall, Slope, Land use/Land cover (LULC), Soil types, Normalized Difference Vegetative Index (NDVI), Distance to roads, Distance to rivers, and drainage density. These factors were selected based on their established influence on flood susceptibility as identified through literature review, expert consultation, and local community experience in the flood-affected zones. Spatial datasets were gathered from remote sensing platforms, Digital Elevation Models, Meteorological records, and existing geospatial databases, and were processed within a GIS environment. The pairwise comparison matrix of the AHP was used to derive weighting coefficients representing the relative contribution of each factor in inducing flood, with Rainfall (0.23), Slope (0.15), Distance to river (0.12), drainage density (0.12), and Elevation (0.11) as the most influential criteria. The findings revealed that 88.4% of the study area falls within a moderate flood-susceptible zone, whereas 6.4% and 5.2% fall within high and low susceptible zones, respectively. The current study indicates that damage to infrastructure, loss of livelihoods, displacement of communities, and increased costs of disaster response are key consequences observed in affected regions. A confusion matrix approach was employed to validate the flood susceptibility map, and the results indicate 0.97 as an overall accuracy, confirming strong model performance and reliability. The proposed adaptive strategies for enhancing flood resilience include improvement in land use planning, use of early warning systems, and sustainable catchment management.

GeoHazards doi: 10.3390/geohazards7030094

Authors: Sara Guerra Fardin José Luís Zêzere Tatiana Sussel Gonçalves Mendes Silvio Jorge Coelho Simões

Data-driven models are increasingly used for flood and landslide susceptibility mapping in rapidly urbanizing regions, particularly in the Global South. In this context, land use and land cover (LULC) is routinely adopted as a conditioning factor, although its geomorphological meaning and temporal consistency with hazard inventories are seldom evaluated. Information Value (IV) models have been widely applied to landslide susceptibility, but their use for flood susceptibility in complex coastal cities remains limited. This study evaluates IV-based flood and landslide susceptibility in Vitória, Brazil, a predominantly insular city characterized by sharp geomorphological contrasts and high population density. Two LULC datasets with different levels of urban detail were tested as conditioning factors alongside topographic and hydrological variables. Eighteen models were constructed for each hazard and validated using Area Under the Curve (AUC) metrics and expert judgement. Morphological attributes were the most important predictors: slope alone achieved an AUC of 0.90 for landslides, whereas elevation reached 0.71 for floods. The inclusion of LULC increased AUC values to 0.94–0.95 for landslides and 0.85–0.89 for floods, but also introduced spatial and temporal biases associated with stationary and coarsely classified land cover. Our findings highlight the limitations of incorporating LULC as a conditioning factor without temporal harmonization with hazard inventories or adequate urban class disaggregation. We argue that, in complex urban settings, LULC is more appropriately interpreted as a proxy for exposure and vulnerability than as a dominant predisposing factor, and that its use in predictive models should be critically assessed to avoid misleading conclusions.

GeoHazards doi: 10.3390/geohazards7030093

Authors: Rekan Shafiq Mohammed Ali Qahtan Ahmed Mohammed Alnuaimy Arsalan Ahmed Othman

Mountainous road corridor landslides pose major dangers to infrastructure and transportation networks in areas with rugged terrain, fractured limestone lithology, and road-induced instability. This research presents a segment-based Random Forest (RF) model to evaluate landslide susceptibility along a mountainous road corridor spanning about 20 km in northeastern Iraq. Ten conditioning factors for landslide susceptibility were determined using Google Earth Engine (GEE) and GIS analysis. The model, validated using a 70/30 train/test split, achieved a mean cross-validation AUC of 0.783 ± 0.072 and an independent test AUC of 0.725 (accuracy = 0.735; Cohen’s Kappa = 0.401; recall = 0.750). To carry out independent multi-scale validation, the RF susceptibility maps were compared with a high-resolution SLAM LiDAR–AHP susceptibility approach within an overlapping ~2 km subsection, providing cross-scale validation of corridor-scale RF susceptibility predictions using a high-resolution susceptibility mapping framework. Comparison of the two approaches showed high spatial agreement, with 88.9% of the 18 overlapping segments exhibiting exact or one-class agreement between the two approaches.

GeoHazards doi: 10.3390/geohazards7030092

Authors: Auguste Benoit Nicolas Bollot Théo Krauffel Julien Berthe Delphine Combaz Alain Devos Olivier Lejeune

The slopes of the Champagne vineyards are regularly affected by landslides. Given the high societal and economic stakes, these processes cause significant damage and pose a major challenge for the wine industry, forestry and heritage preservation. Numerous studies have already been conducted to understand their behavior and hydrodynamic functioning. They show varied morphologies and a dominant influence of water resources. However, this forcing does not explain the spatial distribution of current landslides, which occur in upper-slope positions, on the steepest terrain recently planted with vines. Using the two shallow landslides at Reuil, located in the heart of the Marne Valley in the Champagne vineyards, as a study site, recent landslide activity is analyzed through a comparative analysis of three DTMs derived from LiDAR HD data and two UAV photogrammetric surveys. This study reveals the affected areas and displaced volumes, which can reach up to 900 m3. Landslide activity was then correlated with regional climatic data. This research shows that landslides are more likely to occur during a period of excessive rainfall following a drier period. Diachronic analysis of aerial images also demonstrates the influence of land use on landslide activity. In particular, land clearing and vineyard operations on the steepest plots constitute a significant anthropogenic forcing affecting slope stability. Taken together, these results provide greater insight into the changing geomorphological dynamics of the Champagne vineyards. On the one hand, they clarify how landslides occur at vineyard plot scale. On the other hand, they provide initial insights into the resilience of stakeholders (winegrowers, etc.) affected by these instabilities.

GeoHazards doi: 10.3390/geohazards7030091

Authors: Changchun Li Jin Xu Bei Zhang Xiaogang Wu Yansen Wang

Based on urban subway foundation pit projects in typical limestone areas, this paper employs 3DEC numerical simulation to investigate the effects of the thickness and burial depth of weak interlayers on the deformation characteristics and stability of the dip slope and anti-dip sides of rock foundation pits. The results reveal asymmetric deformation responses between the two slope types. The anti-dip side undergoes bending and toppling deformation; the displacement within the weak interlayer is greater than that of the overlying rock mass, and the spatial position of the weak interlayer governs the maximum deformation of the anti-dip side. In comparison, the thickness and burial depth of the weak interlayer exert a significant influence on the horizontal displacement of the dip slope side. Two quantitative critical thresholds are identified: (1) an interlayer thickness threshold—when t ≥ 4 m, the extrusion displacement of the weak interlayer is distinctly larger than that of the adjacent hard rock, while t ≤ 3 m shows no obvious displacement difference due to the clamping effect of surrounding rock—and (2) a burial depth threshold—slope displacement rises sharply when interlayer burial depth reaches 22.66~26.15 m, while shallow-buried interlayers (12.20~19.18 m) only cause limited deformation. Additionally, the existence of weak interlayers leads to substantially larger displacement in the upper hard rock stratum relative to the lower stratum. These findings provide a reliable reference for the supporting optimization and stability design of rock foundation pits.

GeoHazards doi: 10.3390/geohazards7030090

Authors: Armin Soltan Alberto González-Martínez

NASA’s Fire Information for Resource Management System (FIRMS) provides near-real-time thermal anomaly detections from VIIRS, but not all detections correspond to wildfire incidents: industrial heat, agricultural burning, and sensor artifacts produce false alarms that contribute to alert fatigue for emergency-management analysts. We study whether contextual machine learning (ML) features improve wildfire-incident classification from FIRMS detections, and—more importantly—whether reported gains survive leakage-controlled evaluation. We construct a labeled dataset by matching 521,395 VIIRS SNPP detections across CONUS in 2024 to 3766 NIFC 2024 wildfire perimeters, yielding 131,771 (25.3%) wildfire-matched and 389,624 candidate non-wildfire detections spanning 1067 distinct wildfire incidents. We benchmark five operational baselines and six classifiers under four validation regimes (random, event-aware, 5° spatial-block, and temporal holdout) with and without raw geographic coordinates. A naive random split inflates LightGBM to F1 = 0.985, but a leakage-controlled event-aware split reduces it to F1 = 0.767, and a spatial-block holdout to F1 = 0.627. Feature attribution shows geographic coordinates account for 88.9% of model gain—the summed share of LightGBM’s total split-gain attributed to the three coordinate features within the full-feature model; removing coordinates improves spatial-block generalization from F1 = 0.627 to 0.818, demonstrating that raw coordinates drive memorization of where 2024 fires occurred rather than transferable discrimination. We further show that spatiotemporal clustering must be causal: a model using full-partition clustering appears strong (F1 = 0.908) but leaks future detections, whereas a properly causal trailing-window version ties plain LightGBM in-distribution (F1 = 0.762). Combining causal clustering with no raw coordinates is the most robust configuration under spatial transfer (spatial-block F1 = 0.868 vs. 0.627 for the coordinate model). Bootstrap 95% confidence intervals show these gaps far exceed statistical uncertainty, and sensitivity analyses show the conclusions are robust to the spatial-block size and to the clustering-window choice. Under natural class prevalence (14%), precision falls to 0.69, and results are sensitive to the labeling buffer. All ML models nonetheless far exceed FIRMS high-confidence thresholding (F1 = 0.128). We argue that spatial leakage—not raw accuracy—is the central methodological issue for FIRMS wildfire-incident classification, and recommend coordinate-free, causal spatiotemporal-clustering features evaluated under spatial holdout. The system is intended as an analyst-prioritization decision-support layer, not autonomous incident confirmation.

GeoHazards doi: 10.3390/geohazards7030089

Authors: Zhanrong Zhu Shiyue Fang Husheng Cao Qihao Zou Kehua Li Chi Li

The loess gully region is characterized by complex terrain with crisscrossing gullies, where coal mining can readily induce surface subsidence and slope deformation. Such deformation often leads to geological hazards and ecological issues, including collapses, landslides, soil erosion, vegetation dry up, and land degradation. Therefore, understanding the deformation behavior of mining-induced slopes is essential for the restoration and management of mine geological environments. This study focuses on five slopes within working faces 50205 and 50206 of the Zhen’er Coal Mine in Fugu County. Using a combination of 3DEC numerical simulations and orthophoto-based fracture identification, we systematically investigated mining-induced slope deformation under the complex topographic conditions of the loess gully region. The goal is to answer three key questions: where mining-induced slope deformation primarily occurs, how it evolves over time, and what the main controlling factors are. Spatially, the primary deformation zones and their propagation paths vary significantly among the five slopes. The largest deformation occurs in the slope body directly above the main section of the working face, gradually decreasing toward the edges of the working face. Temporally, mining-induced slope deformation exhibits a time lag, meaning that surface responses lag behind underground mining activities and continue to develop even after the working face is fully extracted. In the loess gully region, slope deformation induced by mining is controlled not only by mining activities but also by topographic factors such as slope shape, aspect, gradient, and height. The spatiotemporal evolution of deformation becomes even more complex for slopes that span multiple working faces. These findings provide a scientific basis for monitoring mining-induced slope deformation and preventing geological disasters in the loess gully region, while also offering practical guidance for safe mining operations and hazard control in similar settings.

GeoHazards doi: 10.3390/geohazards7030088

Authors: Xi Wang Rongjiang Cai Shufang Zhao

Landslide susceptibility assessment is essential for disaster-risk reduction, land-use regulation, and territorial spatial planning in mountainous and hilly regions. However, the practical application of machine learning-based susceptibility models is often limited by the trade-off between predictive accuracy and model interpretability, as well as the instability of factor importance across different algorithms and study areas. Taking Longchuan County in northeastern Guangdong Province, China, as a case study, this research develops a comparative explainable machine learning framework to evaluate landslide susceptibility and examine the cross-model stability of SHAP-based factor attribution under local geo-environmental conditions. Fifteen conditioning factors were initially derived from multi-source geological, topographic, hydrological, environmental, and anthropogenic datasets. After multicollinearity screening using Pearson correlation analysis, twelve key factors were retained for model construction. A total of 363 historical landslide points and an equal number of non-landslide samples were divided into training and testing datasets using a stratified 70:30 sampling strategy. Eight machine learning models were optimized through grid-search parameter tuning and then comparatively evaluated. The results show that all models achieved strong predictive performance, with test-set AUC values exceeding 0.938. Among them, the Gradient Boosting Decision Tree model performed best, with an AUC of 0.9520 and the most stable control of overfitting, followed closely by CatBoost with an AUC of 0.9512. SHAP-based interpretation further revealed that the normalized difference water index, relief, and distance to rivers were the dominant factors controlling landslide susceptibility in the study area, with the normalized difference water index serving as a key explanatory factor across models. The proposed framework improves the transparency and reliability of landslide susceptibility assessment and provides a methodological reference for localized, explainable machine learning applications in geohazard risk management.

GeoHazards doi: 10.3390/geohazards7030087

Authors: Kumari Kanchana Mallika Achchillage Tsuyoshi Wakatsuki Chiaki T. Oguchi Masahiko Osada

Landslide susceptibility mapping (LSM) is an essential tool for hazard assessment and land-use planning in landslide-prone areas. This study compares three statistical models—Frequency Ratio (FR), Weight of Evidence (WoE), and Logistic Regression (LR)—with six machine-learning algorithms: Support Vector Machine (SVM), Random Forest (RF), Extreme Gradient Boosting (XGBoost), Artificial Neural Network (ANN), k-Nearest Neighbor (KNN), and Decision Tree (DT), for regional landslide susceptibility assessment in Hiroshima Prefecture, Japan. A balanced dataset comprising 1936 landslide and 1936 non-landslide samples was developed from the 2018 rainfall-induced landslide inventory, utilizing seven conditioning factors: slope angle, profile curvature, aspect, elevation, lithology, soil water index, and 24 h cumulative rainfall. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, and F1-score. Among the statistical models, WoE exhibited the highest performance, while SVM provided the most balanced results among the machine-learning models. Both modeling approaches consistently identified lithology and slope angle as the primary controls on landslide occurrence. Independent validation demonstrated comparable predictive performance for both models; however, spatial validation showed that WoE assigned 96.72% of observed landslides to the High and Very High susceptibility classes, compared to 72.54% for SVM. These findings underscore the importance of integrating conventional classification metrics with spatial validation to enhance the evaluation and interpretation of landslide susceptibility models for regional hazard assessment.

GeoHazards doi: 10.3390/geohazards7030086

Authors: Olga Petrucci Giovanna De Chiara Angela Di Perna Vera Corbelli

This study presents DEDICA (Database of Hydrogeological Instability Events in Calabria, southern Italy), developed by the District Basin Authority of the Southern Apennines (ABDAM) in collaboration with the CNR-IRPI. The database integrates digitized historical sources, chronicle-based records, and previously unpublished archival data that were systematically analyzed, validated, and georeferenced within a GIS environment. After two years of development, DEDICA includes 5329 landslides, 2097 flood events, and 1711 urban flooding occurrences spanning the period 1900–2025. The system supports continuous data updating, enabling both the integration of recent events and the refinement of historical records. The database provides a comprehensive tool for identifying areas prone to geo-hydrological hazards based on historical recurrence, supporting hazard assessment, land-use planning, and risk management strategies. The methodological framework, database structure, and data processing workflow are described in detail. Spatio-temporal analyses highlight the distribution of instability processes, identifying the most affected sectors and revealing seasonal patterns and long-term trends. DEDICA represents a pilot initiative within a broader program aimed at extending the inventory to all regions under ABDAM jurisdiction, ultimately contributing to the development of a unified geo-hydrological hazard database for southern Italy.

GeoHazards doi: 10.3390/geohazards7030085

Authors: John McBride Kevin A. Rey Stephen T. Nelson Luke K. McBride Jakobi D. Baumann Jacob Ramsey

Integrating geophysical techniques at two contrasting locations—fractured young lavas in southwestern Iceland and older layered basalts in eastern Iceland—constrains the structure and shear-wave velocity of the volcanic subsurface. The results show that relying on a single geophysical method often yields non-unique solutions that can obscure velocity profiles and overlook sharp structural contrasts. Findings from southwestern Iceland reveal that young, faulted ‘a‘ā flows have a complex architecture with shallow, eroded layers, resulting in a reduced Vs30. Conversely, older Miocene bedrock in eastern Iceland shows a well-layered, consolidated structure with a higher Vs30. We demonstrate that modelling Scholte waves from legacy marine seismic data can generate regional velocity models consistent with onshore measurements.

GeoHazards doi: 10.3390/geohazards7030084

Authors: A. S. M. Fahad Hossain Saif Ahmed Santo Miroslav Nastev

Vertical seismic forces may exceed horizontal components under certain conditions; however, they are often neglected in engineering practice. The primary justification in pseudo-static slope stability analysis is that the simultaneous increase/decrease in resisting and driving forces due to vertical loading results in a negligible net change in the factor of safety (FS); peak horizontal and vertical accelerations rarely occur simultaneously; and standard horizontal coefficients are generally sufficiently conservative. The present study systematically quantifies the combined influence of horizontal and vertical seismic forces on slope stability. Three representative slope geometries with inclinations of 1:1.5, 1:2, and 1:3 were analyzed using the pseudo-static limit equilibrium method (PS-LEM); the framework was additionally validated using the pseudo-static finite element method (PS-FEM) against a documented landslide case history. Horizontal seismic coefficients (Kh) of 0.025, 0.05, 0.10, and 0.20 were evaluated in combination with PVA/PHA ratios of 0, 0.25, 0.50, and 1.0 under both upward and downward vertical loading. Three analytical parameters are introduced: (i) Factor of Safety Reduction Index (FSRI), (ii) Vertical Force Sensitivity Ratio (VSR), and (iii) Asymmetry Index (AI). The results show FS reductions up to 10.6% under critical downward loading and a consistently asymmetric response. A preliminary validation against the 2008 Sichuan Daguangbao landslide supports the predictive capability of the framework, although broader validation across additional case histories is required to establish general applicability. The findings support the explicit inclusion of vertical seismic forces in slope stability assessments, particularly in near-field regions with PVA/PHA ratios exceeding 0.5.

GeoHazards doi: 10.3390/geohazards7030083

Authors: Maria Eleni Diamantidou Panagiota S. Katsimpini George A. Papagiannopoulos George D. Hatzigeorgiou

This study investigates the three-dimensional seismic response of plan-irregular reinforced concrete (RC) frame structures subjected to near-fault pulse-like ground motions. The primary scientific contribution lies in evaluating how perimeter-distributed, short-stroke displacement-activated hysteretic dampers interact with complex structural torsional modes under the coupled influence of soil–structure interaction (SSI). Through unscaled nonlinear time–history analyses, this research exposes a critical vulnerability: foundation flexibility elongates the structural period, moving the system into close resonance with near-fault pulse content and more than doubling peak inter-storey drift demands. Concurrently, we demonstrate that the supplemental hysteretic system provides immediate elastic stiffness that successfully counteracts this SSI-induced period elongation, restricting peak drift amplifications to under 0.21% while actively mitigating torsional twisting. These findings provide a quantitative framework for the dual management of foundation flexibility and torsional irregularity using short-stroke metallic yielding devices.

GeoHazards doi: 10.3390/geohazards7030082

Authors: Dimitrios Malamataris Philippos Ganoulis Panagiota Galiatsatou Iraklis Nikoletos Haris Prapas Dimitrios Galiatsatos

Land Use and Land Cover (LULC) change is widely acknowledged as a pivotal driver of environmental change, exerting an escalating influence on surface hydrological processes. The accelerating pace of LULC alterations in response to burgeoning human populations underscores the pressing need for a comprehensive evaluation of their ramifications on surface runoff dynamics. This study investigates the impacts of LULC changes on flood behavior in a Mediterranean watershed in Crete, Greece (Geropotamos watershed). LULC data spanning the years 1990, 2006, and 2018 were procured from the European CORINE Land Cover database at a refined spatial resolution. The HEC-HMS hydrological model is employed to simulate peak discharge and associated hydrograph characteristics under varying recurrence intervals. Subsequently, selected river segments within the studied catchments undergo hydrodynamic flood modelling using the HEC-RAS hydraulic model. Flood depth maps are generated to illustrate the evolution of inundated areas relative to LULC change. The overarching objective of this research is to furnish a comprehensive understanding of how spatiotemporal variations in land use and land cover in-fluence flood characteristics, thereby facilitating informed decision making for sustainable planning.

GeoHazards doi: 10.3390/geohazards7030081

Authors: Chia-Hao Chang Kuo-Chen Ma An-Chi Li

In large-scale seismic scenarios, the operational continuity of evacuation shelters is frequently compromised by limited governmental capacity, necessitating the strategic integration of Disaster Relief Volunteers (DRVs). Traditional assessments often rely on coarse regional aggregates, overlooking the critical spatial mismatch between volunteer availability and localized demand. In this study, a high-resolution, spatially explicit framework was developed to evaluate urban operational resilience in New Taipei City. Utilizing the TERIA platform, a nocturnal magnitude 6.8 Shanjiao Fault rupture was simulated, identifying that approximately 460,000 individuals would be affected, with shelter demand reaching 300,000—double the current capacity. Service areas were delineated using ArcGIS Network Analyst (Dijkstra’s algorithm) based on an 800 m walking threshold, further refined by a secondary assignment rule to redistribute “shadow demand” from peripheral populations. Quantitative analysis of the newly introduced “DRV shortfall” metric reveals that 74% of shelters (148/200) face concurrent spatial and manpower saturation. Notably, 42 analysis units lack resident volunteers entirely, with the most severe shortfall magnitude reaching 361 DRVs at a single “high-risk convergence node”. These results uncover a profound deficiency in urban disaster resilience driven by significant spatial mismatch. This research contributes a three-fold advancement: (i) the high-resolution coupling of volunteer residential data with dynamic demand patterns; (ii) the formalization of the DRV shortfall as a standardized metric for resource adequacy; and (iii) the formulation of a strategic policy framework for multi-shelter activation sequencing, “Support Hub” designation, and resource synchronization in hyper-dense urban environments.

GeoHazards doi: 10.3390/geohazards7030080

Authors: Zafarjon Sultonov Hari K. Pant

Lake Sarez in Tajikistan, formed by a major earthquake-induced landslide in 1911, is located in the highly seismically active Pamir–Hindu Kush region. The lake is impounded by the Usoi Dam, one of the largest natural landslide dams in the world, which has raised concerns regarding its long-term stability and associated downstream flood hazards. Due to its geomorphological setting and potential exposure to multiple triggering mechanisms, including seismic activity and landslides, Lake Sarez is widely considered a high-consequence hazard system. Although the dam has remained stable for over a century and is currently monitored using modern geodetic and satellite-based technologies, uncertainties remain regarding its internal structure and response to extreme external forcing. While existing early warning systems enhance preparedness in downstream communities, effective long-term risk reduction requires continued monitoring, improved hazard modeling, and strengthened regional cooperation. This review synthesizes existing studies on the geological setting, hazard potential, stability assessments, and disaster risk management strategies related to Lake Sarez. It highlights the importance of integrated multi-hazard analysis and precautionary risk governance in managing low-probability but high-impact natural dam failure scenarios.

GeoHazards doi: 10.3390/geohazards7030079

Authors: Jing Zhang Yang Cheng Liang Wang Helong Liu Jiajia Zhu Zhengwei Li Tianzheng Li

Accurate characterization of subsurface stratigraphy is essential for reliable landslide stability assessment. However, stratigraphic models constructed solely from sparse borehole data are often constrained by incomplete spatial coverage and substantial interpretive uncertainty. To address this issue, this study developed an integrated probabilistic stratigraphic modeling framework that combines borehole data with electrical resistivity tomography (ERT) data. In the proposed framework, borehole logs provide direct lithological labels and spatial prior information, while the inverted ERT resistivity profile is introduced as a continuous geophysical constraint. Specifically, logarithmic resistivity and the borehole-derived expected stratigraphic configuration were combined into a support vector machine classifier to establish a nonlinear mapping between geophysical responses and stratigraphic categories. A bootstrapping strategy was also used to quantify the stratigraphic uncertainty. The proposed method was then applied to the Panzhuangzu Landslide in Henan Province, China. Based on the probabilistic stratigraphic models, multiple plausible stratigraphic realizations were generated, and their corresponding stability responses are evaluated through numerical analysis. Monte Carlo simulations were further performed to examine how stratigraphic uncertainty propagates into landslide stability predictions. The results show that incorporating ERT data improves the geological plausibility of the inferred stratigraphy. Compared with the borehole-only case, the results obtained from the integrated framework exhibited reduced uncertainty in both the inferred stratigraphic model and the corresponding landslide stability assessment. These findings indicate that the proposed borehole–geophysical data fusion method can provide a more reliable geological basis for landslide stability analysis.

GeoHazards doi: 10.3390/geohazards7020078

Authors: John B. Rundle Ian Baughman Andrea Donnellan Lisa Grant Ludwig Geoffrey Fox Kazuyoshi Nanjo

In this paper, we describe a method for computing calendar time forecasts in a local area for large earthquakes of a target magnitude MT using a count of small earthquakes in the magnitude range MS to MT in the area. Using the idea that the Gutenberg–Richter (GR) relation is valid throughout the surrounding region, we define an ensemble of earthquakes in larger surrounding regions to be used in computing the forecast. What follows is simple data mining. “Local” is defined by the probability of a large earthquake occurring within a defined circle of arbitrary radius surrounding a point of interest. The main (and for that matter, the only) assumption for all these works is that the GR magnitude–frequency relation holds. The method has significant skill, as defined by the Receiver Operating Characteristic (ROC) test, which improves as the time since the last major earthquake increases. The probability is conditioned on the number of small earthquakes n(t), with M ≥ MS = 3.49, that have occurred since the last large earthquake. The probability is computed directly as the Positive Predictive Value (PPV) associated with the ROC curve. The method is compared with the UCERF3 forecasts for the UCERF3-defined geographic boxes centered on Los Angeles and San Francisco and serves as an indicative benchmark. The method is then applied to a 125 km radius circular area around Los Angeles, California, following the 17 January 1994 magnitude M6.7 Northridge earthquake, and short-term forecasts (1-year and 5-year) are computed. We further apply the method to six additional geographic regions with validation by comparison with an estimate of the time-independent conditional Poisson probability. These regions are Athens, Greece; Chengdu, China; Jakarta, Indonesia; Lima, Peru; Santiago, Chile; and Tangshan, China.

GeoHazards doi: 10.3390/geohazards7020077

Authors: Batuhan Kahvecioğlu Sinan Melih Nigdeli Gebrail Bekdaş Sanghun Kim Zong Woo Geem

This study investigates the comparative effectiveness of Lead Rubber Bearing (LRB) and Friction Pendulum System (FPS) isolation units under varying seismic hazard levels and soil classes, within the framework of the Turkish Building Earthquake Code (TBEC 2018). The assessment was conducted in two stages. First, keeping the site class constant, multiple locations characterized by different seismic hazard levels are examined. Second, a fixed geographical location is considered to evaluate the influence of different site classes on isolator response. The performance of the isolation systems is evaluated in terms of displacement demand, base shear ratio, and code-based verification criteria. Additional sensitivity checks were performed using selected limit values to better understand the response trends under changing hazard and soil parameters. The findings highlight how soil amplification effects and seismic intensity levels influence the relative advantages of LRB and FPSs. The results provide practical insight for the selection of seismic isolation systems in hazard-prone regions, contributing to improved performance-based decision-making in earthquake-resistant design. The isolator parameter choices were set based on average catalogue values provided by manufacturers to make this research an example. As a result of the analysis of the isolators’ performance, it was concluded that the FPS-type isolator performed better as acceleration values increased.

GeoHazards doi: 10.3390/geohazards7020076

Authors: Hajar Mrabet Ibtissam Latachi Tajjeeddine Rachidi Mohammed Karim

Wildfires are a growing threat in Mediterranean regions where climate variability and land-use practices increase vulnerability to fire risk. Developing effective prediction models is essential for robust wildfire management, particularly in such data-scarce environments. Focusing on data-scarce Mediterranean environments, with reference to environmental conditions observed in Morocco, this review presents prediction models across three methodological categories: spatial risk mapping, temporal forecasting, and fire spread simulation, alongside the satellite data products that support their deployment. Each category is assessed in terms of predictive performance, data requirements, and adaptability to low-resource environments. XGBoost showed strong applicability in data-scarce Mediterranean contexts, while ARIMA was validated for forecasting fire-relevant time series under limited data resources. Freely accessible MODIS-derived products represent a significant asset to the region. Based on this synthesis, a hybrid XGBoost-ARIMA framework incorporating MODIS-derived inputs and SHAP-based interpretability is proposed as a promising candidate architecture to be validated after further investigation. The findings aim to support researchers, land managers, and policymakers in strengthening local wildfire prevention and mitigation efforts by aligning model capabilities with regional data and environmental constraints.

GeoHazards doi: 10.3390/geohazards7020075

Authors: Xin Zhang Fang Wang Hao Yang Shixiao Liu

Rainfall is a critical factor inducing slope instability, and accurate prediction of the factor of safety (FOS) of slopes under rainfall conditions is of paramount importance for disaster prevention and mitigation. Conventional numerical simulation methods incur high computational costs, while individual machine learning models are often insufficient to adequately capture the nonlinear spatiotemporal evolution characteristics of multiple factors under coupled multi-physics fields. To address these limitations, this paper proposes a Transformer–LSTM prediction framework. First, a fluid–structure coupling model for rainfall-affected slopes is constructed using COMSOL, and multi-factor orthogonal experiments are performed to generate multi-dimensional time-series data. Subsequently, a Transformer–LSTM fusion deep learning model is built, in which LSTM is employed to extract the temporal dynamic characteristics of rainfall infiltration, and the self-attention mechanism of the Transformer is leveraged to enhance feature extraction and global dependency modeling of key disaster-causing factors. Experimental results demonstrate that the Transformer–LSTM model significantly outperforms traditional PSO-LSTM, PSO-SVM, and standalone Transformer or LSTM models in terms of both prediction accuracy and generalization capability. Its coefficient of determination (R2) remains above 0.94, and key evaluation metrics—including mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE)—attain the lowest values among the compared models. Furthermore, the SHAP (SHapley Additive exPlanations) interpretability framework is introduced to quantitatively elucidate the model’s predictive decision-making and to establish a physically grounded causal mapping with geotechnical mechanisms. It is confirmed that effective cohesion and slope angle exert a dominant interactive effect on the degradation of slope stability, providing data-driven support for wide-area monitoring of rainfall-induced landslides.

GeoHazards doi: 10.3390/geohazards7020073

Authors: Nadir Murtaza Ghufran Ahmed Pasha

Flooding has become increasingly severe due to rapid urbanization and changing hydrological conditions, necessitating effective and sustainable mitigation strategies. This study investigates the hydraulic performance of a hybrid flood defense system comprising a dike, a moat, and vegetation under varying surface roughness conditions. The results demonstrate that increasing roughness significantly enhances flood mitigation performance by improving energy dissipation and delaying the propagation of floodwater. A maximum energy reduction of approximately 75.56% and a delay in floodwater arrival of up to 65% were observed under higher roughness conditions. In contrast, increasing flow intensity reduced system efficiency, highlighting the importance of optimizing roughness under varying hydraulic conditions. The findings reveal that surface roughness is the dominant factor controlling flow resistance, turbulence generation, and hydraulic jump formation within the system. The novelty of this study lies in systematically quantifying the combined effect of roughness across structural and vegetative components within a hybrid defense framework. These results provide a practical basis for the design and optimization of eco-engineered flood defense systems, offering a cost-effective approach for reducing flood risk in riverine environments.

GeoHazards doi: 10.3390/geohazards7020074

Authors: Stelios Karozis Maria Gavrouzou Diamando Vlachogiannis Athanasios Sfetsos

Greece and the eastern Mediterranean are among the regions that are most exposed to climate-driven natural hazards, with wildfires, floods, and extreme rainfall events consistently producing significant socioeconomic and environmental impacts. Although previous literature has addressed each hazard type individually, a systematic, comparative analysis of the atmospheric circulation regimes associated with all three hazard categories within a unified Lagrangian framework has not yet been conducted for Greece. In this study, a 96 h HYSPLIT back-trajectory analysis driven by ERA5 reanalysis data, combined with k-means clustering, is employed to characterise the air mass origins associated with extreme events in Greece from 2000 to 2020 at two atmospheric levels: 750 m and 3000 m above sea level. Wildfire events are predominantly linked to short-distance northeast airflow at 750 m, and are directly associated with the Etesian wind system and to a coherent northwest-west Mediterranean signal at 3000 m, reflecting the influence of the summer blocking anticyclone over Europe. Conversely, flood events are dominated by northerly flow at 750 m, driven by the eastern flank of Mediterranean depressions. These results indicate that flooding in Greece is primarily conditioned by surface cyclogenesis, regardless of the upper-level flow geometry. Extreme rainfall events exhibit the most complex structure, with a dominant upper-level cluster that describes a recurving trajectory consistent with cut-off low dynamics. Cross-hazard comparisons demonstrate that similar near-surface trajectory patterns may arise from different atmospheric drivers, underscoring the necessity of integrating Lagrangian trajectory classification with additional context, such as thermodynamic and seasonal, to enable robust multi-hazard attribution and enhance early warning capabilities in the eastern Mediterranean.

GeoHazards doi: 10.3390/geohazards7020072

Authors: Gemma Musacchio Elena Eva Fabrizio Meroni Stefano Solarino Luigi Zarrilli

Earthquake risk communication often remains centered on event parameters and structural collapse, while local site effects, building response and non-structural elements vulnerability shape how earthquakes are experienced and what people can do to reduce risk. This study examines whether a multi-modal, experience-based strategy focused on these dimensions, which are referred to as “last mile” of seismic risk, can improve public understanding and support actionable preparedness behaviors. The case study is the exhibition “Terremoti: Attenti agli Elementi!—Dettagli che salvano la vita” (Earthquakes: Beware of the Elements!—Details that Save Lives), designed for school audiences and the general public. Its effectiveness was assessed through five multiple-choice questions administered before (N = 183) and after (N = 174) the visit to the Genoa Science Festival; responses were analyzed overall and by topic and demographic group. Correct answers increased significantly from pre- to post-visit, with the largest gains concerning local site effects (+43.29%) and household prevention measures (+49.45%), whereas building vulnerability (+14.97%) and building dynamic response (+0.49%) showed more limited improvement. These exploratory results suggest that seismic risk communication is more effective when abstract concepts are translated into observable, manipulable, and everyday experiences, and support a shift toward a “last-mile” framework of seismic risk communication.

GeoHazards doi: 10.3390/geohazards7020071

Authors: Gerassimos A. Papadopoulos

The Santorini volcano attracts global interest. The 17th century BCE Minoan eruption was likely the largest ever occurring in the Holocene. The evaluation of an enriched collection of documentary sources combined with geological observations showed that in historical times, 15 eruption episodes were recorded from the 2nd century BCE up to 1950 CE. Little-known episodes occurring in 1667 CE and 1773 CE were uncovered, analyzed and included in the catalogue. Due to many uncertainties and inconsistencies involved in the historical sources, a reliability score ranging from 1 (lowest) to 4 (highest) has been assigned to each one of the 15 episodes. This procedure was based on a Reliability Assessment Matrix, which is a novelty in historical volcanology. The size of an eruption was evaluated in terms of the 8-grade Volcanic Explosivity Index (VEI) by introducing a bimodal assignment form of “V or V + 1”, an approach used for the first time, instead of the traditional unimodal assignment of “V”. The VEI of 4–5 was assigned to the eruptions of 725/726 CE in the Santorini caldera and of 1650 CE in the Kolumbo submarine volcano. The rest of the eruptions were assigned with smaller VEIs. Completeness analysis of the catalogue with statistical tests and Monte Carlo simulation with random and non-random models as baselines showed a 10-fold increase in the eruption record in 450 years after the breakpoint of 1572 CE eruption compared to the 1747 years before that point implying that there are about 30 missing eruption events that escaped record in the pre-1572 CE historical interval. This statistically significant difference is interpreted as a bias discovery effect of anthropogenic origin, but further research is needed to show that it does not represent a drastic change of magma plumbing rate.

GeoHazards doi: 10.3390/geohazards7020070

Authors: Dionysios Chatzidakis Nikolaos Makrakis Prodromos N. Psarropoulos Yiannis Tsompanakis

Offshore high-pressure gas pipelines comprise critical infrastructure that often cross seismic regions for hundreds of kilometers. The intersection of such pipelines with seismic fault zones is frequently inevitable due to high costs or technical constraints of alternative routes. While typical mitigation measures, such as stronger materials or cross-sections and flexible joints, ensure pipeline integrity against earthquake-related geohazards, options for deep-water pipelines are more limited compared to onshore or even near-shore pipelines. This paper numerically investigates the efficiency of various mitigation approaches for surface-laid steel pipelines subjected to normal or reverse seismic faulting. Using ABAQUS finite-element software, the pipeline is simulated under realistic conditions for cohesive and non-cohesive seabed sediments. Critical fault displacements for different pipe steel materials, cross-sections, coatings, pressures, and orientations are calculated according to international standards. Results demonstrate that a 30° fault-pipe intersection angle is the most effective approach, increasing pipe’s capacity to fault dislocation by up to 90% for normal and 75% for reverse faults. Additionally, coating materials can increase a pipe’s resistance by up to 15%, whereas pressure difference variations may also have an impact. This study provides useful conclusions regarding the efficiency of the mitigation measures, the applicability of international standards, and the simulation of pipe–soil interaction.

GeoHazards doi: 10.3390/geohazards7020069

Authors: Swarna Bhowmick Renato Macciotta

Rockfall records for hazard assessments commonly present rockfall volume–cumulative frequency curves based on observations of rockfall occurrences that are noticed at or in the vicinity of infrastructure. These curves are in log–log scale, where the curves for larger volumes are fitted to a power law (linear fit in the log–log plot). The slope of this linear fit in log–log plots has been qualitatively attributed to rock mass characteristics (lithology, rock mass quality, discontinuities); however, there are not many direct insights that greenfield sites (new sites or areas with scarce to no data) could adopt for an order-of-magnitude estimation of rockfall hazard. This paper collects data from the literature, past and current, and presents details of these rockfall volume–cumulative frequency curves for different lithologies and rock mass qualities. Importantly, recent databases on rockfall frequency and volumes as obtained through change detection are utilized, which can provide more detailed and less biased rockfall occurrence data.

GeoHazards doi: 10.3390/geohazards7020068

Authors: Adnane Medrari Brahim Benzougagh Ibrahim Ouchen Halah Kadhim Tayyeh Ahmed Mageed Hussein Mohamed Mastere Taj Benyounes Najat El Ghazi Khaled Mohamed Khedher

The study analyzes a major deep-seated landslide affecting National Road 16 at KP 178+000 in the Rif region of northern Morocco, a corridor repeatedly impacted by geotechnical instability. Using historical information, detailed geological mapping, multiple field campaigns, and extensive subsurface investigations (core drilling, inclinometers), the authors characterize the site as a complex setting of metamorphosed, fractured, and altered peridotites overlain by Quaternary sediments dipping negatively toward the Mediterranean. The landslide is interpreted as deep-seated planar translational landslide and has been exacerbated by human activity, specifically the placement of excavated material on the downslope side during road upgrade works in late 2019. Inclinometer data show active movement extending to at least 20 m depth, confirming the deep-seated nature of the instability. Three remediation strategies were implemented: shifting the road alignment with terracing, combining road realignment with soil nailing and slope reprofiling, and installing large bored piles tied back with anchors, following recommendations from an external expert. The authors emphasize that robust geological investigations and properly regulated construction practices are essential to reduce landslide risk for infrastructure built in mountainous coastal regions.

GeoHazards doi: 10.3390/geohazards7020067

Authors: Igor Chiambretti Luca Lanteri Alessio Salandin Davide Tiranti

Slush flows are rapid mass movements of water-saturated snow and debris that develop when the liquid water content of the snowpack exceeds the critical threshold for the fully funicular regime, resulting in viscoplastic flow behavior fundamentally distinct from that of dry snow avalanches. These phenomena have been extensively documented globally as responsible for fatalities and economic damage comparable to those of snow avalanches. In the northwestern Italian Alps, the situation is markedly different. Until 2025, rain-on-snow (ROS) events in this region had produced amplified effects on the ground in the form of increased landslide activity, debris flow mobilization, and flooding, as typical consequences of snowmelt superimposed on pre-saturated soils but had not generated widespread slush flow phenomena. The 2025 season marked a critical threshold: for the first time, diffuse and unambiguous slush flow events were documented in Italian northwestern Alpine sectors, signaling a qualitative shift in the hazard regime rather than a mere quantitative intensification of known processes. Documented emergence of slush flows in the Italian Alps must be interpreted not as an anomaly but as a measurable indicator of climate change and of its progressive effects on the Alpine environment.

GeoHazards doi: 10.3390/geohazards7020066

Authors: Lorenzo Massa Franz A. Livio Maria Francesca Ferrario

Seismically triggered landslides represent a major secondary hazard of earthquakes, often causing widespread damage over large areas. Rapid and reliable mapping of such phenomena is therefore essential, particularly in emergency contexts. While numerous studies have addressed landslide detection in vegetated regions using optical remote sensing, arid and desert environments remain relatively underexplored due to the limited spectral contrast between stable and failed slopes. In this study, we evaluate the potential of an automatic pixel-based method for the rapid detection of seismic landslides in arid settings, using high-resolution optical imagery. The analysis focuses on the Mw 5.5 earthquake that struck the Northern Red Sea Region of Eritrea on 26 December 2022. A detailed inventory of 1393 coseismic landslides was manually mapped from pre- and post-event PlanetScope multispectral images and used both for geomorphological and macroseismic analyses and as training data for a threshold-based classification approach. Landslide detection was based on changes in the Redness Soil Index (RSI) and its differential (ΔRSI), combined with a One-Class Asymmetric Robust Gaussian classifier. Results show a good capability to delineate landslide-affected areas, although commission errors remain significant. Despite these limitations, the proposed approach, still in need of a more trained implementation in the future, proves its potential effectiveness for rapid mapping purposes, owing to its simplicity and minimal computational requirements. These results open the possibility to implement a fully automatic methodology in the future, when more landslides will be mapped and a model trained on different and normalized datasets will be implemented. The results demonstrate that pixel-based optical methods, particularly those relying on red-band spectral changes, represent a valuable tool for the preliminary assessment of earthquake-induced landslides in arid environments and may support emergency response and first-order hazard evaluation.

GeoHazards doi: 10.3390/geohazards7020065

Authors: Álvaro-Francisco Morote Jorge Olcina Brenda Tévar Alberto Alfonso-Torreño

The aim of this study is to analyze the perceptions of students in Primary Education (5th and 6th grades; n = 260; Valencian Community, Spain) regarding natural hazards, based on their personal experiences, memories, school-based instruction and preventive measures. Methodologically, the study is based on the administration of a mixed-type questionnaire. The high proportion of students reporting strong awareness (68.5%) suggests that school-based instruction is already contributing to a foundational level of risk perception. Floods associated with torrential rainfall are the most frequently recalled hazard, influenced by the cut-off low event of 29 October 2024 (Valencia) (72.3%). Furthermore, no significant differences were found between students who experienced or remembered a flood and those who did not, in terms of preventive measures received, indicating a consistent and homogeneous instruction. In conclusion, this study highlights that students hold a strong awareness of natural hazards, particularly floods, with uniform school-based training. The cut-off low 2024 event in Valencia stood out among other disasters, reinforcing the educational importance of water-related hazards in high-risk regions and underscoring the need to strengthen hydrological awareness as a key component for enhancing socio-territorial risk perception.

GeoHazards doi: 10.3390/geohazards7020064

Authors: Riazud Din Faheem Butt Farhan Ahmad Ali Raza

Earthquakes pose a serious threat to urban areas located in seismically active regions, particularly in developing countries where rapid urbanization and weak enforcement of building regulations increase the vulnerability of the built environment. Pakistan is highly exposed to seismic hazards due to its tectonic setting, and many residential buildings are constructed without adequate seismic design considerations. Therefore, assessing building vulnerability and understanding community perception of earthquake risk are essential for effective disaster risk reduction. This study investigates the relationship between the structural vulnerability of residential buildings and earthquake risk perception among residents in Peshawar, Pakistan. Two contrasting urban settlements were selected as case studies: WAPDA Town, representing a planned residential area, and Hashtnagri, representing an older unplanned settlement. A total of 400 buildings were surveyed through field investigations. Seismic vulnerability was assessed using the Rapid Visual Screening (RVS) method based on structural characteristics such as building age, number of floors, construction materials, structural irregularities, construction quality, and presence of seismic reinforcement features. A Physical Vulnerability Index (PVI) was developed to categorize buildings into different vulnerability levels. In addition, a questionnaire survey was conducted to evaluate earthquake risk perception among residents, and a risk perception index (RPI) was calculated. The results indicate that buildings located in the unplanned settlement exhibit significantly higher seismic vulnerability compared to those in the planned residential area due to poor construction practices, irregular structural configurations, and the absence of seismic-resistant features. Statistical analysis further reveals a positive relationship between physical vulnerability and earthquake risk perception, suggesting that residents living in structurally vulnerable environments tend to perceive higher earthquake risk. The findings highlight the importance of integrating structural vulnerability assessment with community awareness and preparedness programs. Implementation of seismic design provisions and improved enforcement of construction regulations, such as those specified in the Building Code of Pakistan 2022, can significantly reduce earthquake risk in rapidly growing urban areas. However, the present study did not directly evaluate the level of enforcement or compliance with the Building Code of Pakistan 2022 in either WAPDA Town or Hashtnagri. Therefore, the policy recommendations are intended as general implications derived from the observed vulnerability patterns.

GeoHazards doi: 10.3390/geohazards7020063

Authors: Jean-Paul Deroin Belkacem Boumaraf Hacini Messaoud

Multisource remote sensing data is utilised for the purpose of monitoring annual and interannual changes associated with climate change in the water bodies of the Chotts of Merouane and Melrhir, which are located in the Zone of Chotts in North Africa. These endorheic depressions are distinguished by recurrent flooding events of varying magnitude and frequency, which are contingent on fluctuations in climate parameters. It has been determined that certain cities located within the surrounding watersheds, such as Biskra, are subject to the intermittent threat of severe flooding. This has been shown to result in land degradation and soil salinisation during the drying-up process. A detailed examination of chronological data from the 1960s onwards reveals a decline in the frequency of flooding in Chott Melrhir in recent years. It is noteworthy that the region has not experienced any substantial flooding since 2020. This phenomenon is concomitant with the marked decline in precipitation levels observed in the region. Since 1980, there have been at least ten significant floods, resulting in varying degrees of damage and disruption. In contrast, Chott Merouane exhibits a more consistent hydrological pattern, with water flowing almost year-round due to wastewater and the drainage of the palm groves by the Oued Righ. Until the 1970s, the occurrence of flooding in the region was exclusively attributable to the direct overflow of the Biskra River and its tributaries. However, from the 1980s onwards, a new type of flooding emerged, linked to insufficient infiltration and drainage capacity in the soil and sewage systems during rainfall that was sometimes considered normal. The hydrological regime in the area has severe ramifications for the water supply and the state of the oases, which are vulnerable to salinisation.

GeoHazards doi: 10.3390/geohazards7020062

Authors: Diana Contreras Enes Veliu Dimosthenis Antypas Javier Hervas Matthieu Landès Laure Fallou Damiano Koxhaj Rémy Bossu Sean Wilkinson Jose Camacho-Collados Edmond Dushi

Collecting and analysing data after an earthquake is essential to determine its impact. In 2014, the European Mediterranean Seismological Centre launched the LastQuake system. Its app collects reports on the intensity users feel, along with comments that provide situational awareness. However, text data collected through crowdsourcing platforms is unstructured. Therefore, natural language processing techniques such as sentiment analysis and aspect-based sentiment analysis are necessary to extract meaningful information. On the 26 November 2019, following an earthquake in Albania, the LastQuake app recorded 28,220 reports with user comments. For the current analysis, we sampled comments posted on the exact day of the earthquake, in Albanian: 1678 comments (6%). The most frequent polarity detected in comments from LastQuake app users was negative (52%), followed by positive and neutral. However, manual classification is time-consuming and not feasible during the emergency phase. Therefore, we tested the accuracy of two automatic classification models for sentiment analysis: ‘troberta’ and ‘txlm’. These models were fine-tuned using already-classified text data from the 2020 Aegean earthquake. Using the manual classification as the reference to evaluate the accuracy of the automatic classification models for sentiment analysis yields accuracies of 71% for the ‘troberta’ model and 56% for the ‘txlm’ model.

GeoHazards doi: 10.3390/geohazards7020061

Authors: Davide Tiranti

Landslides, defined as downslope movements of rock, soil, or debris under the action of gravity [...]

GeoHazards doi: 10.3390/geohazards7020060

Authors: Zhiyun Liu Ziyang Wang Fuqing Cui Xiang Long Li Wang Te Liu Zhou Yang

Permafrost foundations are prone to settlement during thawing, resulting from both thaw settlement and thaw-induced compression. The relative contributions of these components are strongly influenced by soil structure and loading conditions. Therefore, clarifying their interaction and identifying the conditions for significant compressive deformation are essential for accurate predictions. Laboratory tests were conducted to determine the thaw-settlement and thaw-compression coefficients. A new index, the thaw proportion of thaw settlement, was introduced to quantify the relative contributions of the two deformation components. By combining this ratio with compressive strain characteristics, criteria for identifying significant thaw-compression deformation and the corresponding load–porosity conditions were established. In addition, multiple machine learning models were developed, and their predictive performance was systematically evaluated. The main findings are outlined as follows: (1) The thaw proportion of thaw settlement is controlled by soil type, natural water content, dry density, and external load, with clear differences among soil types. It increases with water content, but decreases with increasing dry density and load. (2) Significant thaw-compression deformation is defined by a compressive strain of 8%, and the corresponding load–porosity conditions are identified. (3) Machine learning models effectively predict permafrost deformation. After Bayesian Optimisation (BO), performance improves markedly, with the BO-Support Vector Machine (SVM) model achieving the highest accuracy for thaw-settlement-coefficient prediction (R2 = 0.85), and the BO-Extreme Gradient Boosting (XGBoost) model performing best for post-thaw compressive strain (R2 = 0.95).

GeoHazards doi: 10.3390/geohazards7020059

Authors: Fuhua Peng Weijun Wang Jingyun Hu Yinghua Huang Congcong Zhao

Dynamically grasping the scope of the caving zone and fractured zone in overlying strata is crucial for ground pressure control in sublevel caving mining. Taking Dahongshan Iron Mine as the research object, this study systematically analyzed the evolutionary characteristics of overlying strata caving during sublevel caving mining from 2009 to 2013. Microseismic monitoring was employed as the main method to monitor and locate rock mass fracturing, while roadway monitoring and borehole monitoring were used as auxiliary means to determine the caving boundary and fractured zone scope of overlying strata. Comprehensive analysis of the monitoring data showed that the elevation of the overlying strata caving zone expanded from 930 m to 1215 m, and the width of the fractured zone varied from 50 m to 75 m in different periods. To clarify the rock mass fracture mechanism, P-wave first-motion moment tensor inversion and the Ohtsu moment tensor decomposition method were adopted to classify fracture types. The results indicated that tensile fracturing-related microseismic events accounted for 76.2–80.2% of all events in different periods, demonstrating that tensile failure dominated the fracturing of overlying strata. After December 2012, the caving scope extended to the surface, and a surface collapse area of 290,000 m2 was formed by December 2013, which effectively eliminated the threat of sudden overlying strata caving disasters to the mine. The research results provide reliable technical support for ensuring mine safety production and can serve as a reference for similar sublevel caving mining projects.

GeoHazards doi: 10.3390/geohazards7020058

Authors: Mohammad Alamgir Hossain Md. Moklesur Ra​​hman Md. Anik Hossain

This study examines the relationship between land use–land cover (LULC) changes and drought risk dynamics in southwestern Bangladesh, focusing on the Kushtia District, Chuadanga District, Jhenaidah District, and Jashore District. Multi-temporal Landsat data (1994–2018) were used to classify six LULC types, and future scenarios (2028–2050) were projected using a CA–Markov chain model. The Combined Drought Index (CDI) was integrated with LULC fractions through Pearson correlation and linear regression to assess drought variability. Results reveal significant landscape transformation, with settlement areas expanding sharply (≈18–27% in 1994 to 66–85% by 2050), while agricultural land, vegetation, and water bodies declined across all districts. Strong statistical associations were observed between CDI and settlement (negative relationship), as well as agricultural land, barren land, and char land (R2 = 0.63–0.82, p < 0.05). Future projections indicate increasing drought vulnerability, particularly in Jashore District, where CDI may decrease from 0.67 (2028) to 0.35 (2050), suggesting a transition toward extreme drought conditions. The Jhenaidah District may shift toward mild drought conditions, while the Kushtia District and Chuadanga District show gradual declines in CDI values, remaining largely within the normal drought range. The findings highlight spatially varying linkages between land use dynamics and drought variability, underscoring the importance of sustainable land management strategies to mitigate potential future drought risks.

GeoHazards doi: 10.3390/geohazards7020057

Authors: Melti Roza Adry Akhmad Fauzi Bambang Juanda Andrea Emma Pravitasari

Indonesia experiences some of the world’s highest seismic activity, making earthquakes a major source of physical, economic, and social losses. To better quantify these impacts, this study proposes a comprehensive evaluation framework with two new metrics: the Seismic Severity Index (SSI) and the Seismic Impact Index (SII). The indices are derived using four weighting methods—Grey Relational Analysis (GRA), Equal Weights, the Entropy Weight Method (EWM), and Criteria Importance Through Intercriteria Correlation (CRITIC)—and applied to 28 regencies and municipalities affected by damaging earthquakes from 2016 to 2022. Results show that the 2018 earthquake, intensified by a tsunami and liquefaction, caused the most severe losses. Palu Municipality and Donggala Regency consistently recorded high SSI values across all weighting schemes. The SII further identifies Sigi Regency, Donggala Regency, and Palu Municipality as the most heavily impacted areas, although rankings varied by method. Overall, Sigi Regency, Palu City, Donggala Regency, North Lombok, West Lombok and Cianjur exhibit the highest combined severity and impact, while Garut, Ciamis, and Cilacap experienced relatively minor effects. The study concludes that integrating GRA with EWM and CRITIC yields a robust earthquake loss index to support future disaster risk reduction policies.

GeoHazards doi: 10.3390/geohazards7020056

Authors: Kushal Acharja Topu Fei Wang William Jenkins Coleman Vaughan

Cover-collapse sinkholes are one of the most hazardous geohazards, causing severe damage to civil infrastructure, roadway networks, and substantial economic disruptions. In the United States alone, the economic loss caused by cover-collapse sinkholes exceed USD 300 million annually. Despite extensive research on the causes and formation mechanisms of cover-collapse sinkholes, reliable prediction of the collapse range remains a significant challenge because the development of cover-collapse sinkholes occurs underground and is generally undetectable at the ground surface until collapse occurs. This study presents a comprehensive review of 162 peer-reviewed journal articles, technical reports, and case studies to systematically identify the key factors governing the collapse range of cover-collapse sinkholes. This paper covers several influencing factors for collapse range of cover-collapse sinkholes, including soil properties, geometric characteristics of cavities and soil cover, hydraulic conditions, and the presence of buried structures. Among these factors, soil cohesion, friction angles, void ratio, soil cover thickness, and cavity geometry are identified as the key influencing factors for the collapse range of cover-collapse sinkholes. In addition, existing prediction methods were also summarized, which are predominantly empirical and have limited capability to capture the influence of multiple factors on the collapse range. Based on the literature review, this study finally identifies current research gaps and suggests future directions for developing more accurate and integrated models to predict collapse range of cover-collapse sinkholes.

GeoHazards doi: 10.3390/geohazards7020055

Authors: Kostas Kalabokidis Olga Roussou Christos Vasilakos Palaiologos Palaiologou Dimitrios Zianis Katerina Trepekli Pau Brunet-Navarro José Ramón González-Olabarria José G. Borges Susete Marques Dagm F. Abate William M. Jolly Alan A. Ager

Greece is facing a wildfire crisis that parallels many other countries in fire-prone regions around the globe. Recent wildfire data for Greece point to an alarming trend of increasing fire size and severity catalyzed by climate change, lack of forest and fuel management, urban expansion into wildlands around major population centers, and rural exodus from areas that traditionally supported fire-resilient land uses. Fire management in Greece has long emphasized suppression with relatively little attention to prevention and coordination. In this paper, we identify key factors that are slowing progress towards a solution to the Greek wildfire crisis, including the current legislative framework around wildfire management that has contributed to conflicts and inefficiency. We then discuss specific policies to rebalance the current suppression emphasis by integrating new prevention strategies aiming to create fire-resilient landscapes and reduce wildfire impacts, widely adopt the use of technology, and enhance stakeholder cooperation for more efficient fire suppression. We also highlight how optimizing landscape scale management of fuels is contributing solutions to the wildfire crisis, specifically from the EU-funded FIRE-RES project.

GeoHazards doi: 10.3390/geohazards7020054

Authors: Betty Namugenyi Hadir Abdelmoneim Chérifa Abdelbaki Sameh Ahmed Kantoush Navneet Kumar Bayongwa Samuel Ahana Mohamed Saber

Floods increasingly threaten communities and infrastructure in Uganda due to climate variability and land use changes. This study assessed flood hazard, vulnerability, and risk in the Mpanga River Catchment using the Rainfall–Runoff–Inundation (RRI) model integrated with the Analytical Hierarchy Process (AHP). The RRI model showed good performance during calibration (NSE = 0.83) and validation (NSE = 0.71), enabling the generation of hazard maps for different return periods. Results revealed a clear escalation in flood extent with increasing return period, where inundation expanded from about 120.5 km2 in the 5-year event to nearly 348.4 km2 under the 100-year flood scenario. Vulnerability was evaluated through AHP using nine indicators (Land use, population density, distance to river, elevation, rainfall, slope, drainage density, Total Wetness Index, and soil type); however, only Land Use and population density were retained in the final mapping due to data relevance and weight dominance. Combining hazard and vulnerability produced risk maps that revealed most of the catchment falls under low to moderate risk, with high-risk areas concentrated in upstream urbanized zones. Validation with satellite-derived flood maps confirmed model reliability. Evaluation of mitigation strategies showed dams and channel improvements to be the most effective in reducing flood extent. The study provides a practical framework for flood risk management in data-scarce environments, supporting evidence-based planning and interventions.

GeoHazards doi: 10.3390/geohazards7020053

Authors: Michele Sisto Cristiano Fidani

A key component of research on disaster risk in modern-age society in the inland areas of the Campania Region, southern Italy, was discovered in parish registers. Ecclesiastical archives, containing thousands of largely unpublished pages, served as a rich source of information on disruption and casualties. The parish registers preserved in these archives from the 16th century provide demographic records as well as notes on the most terrible events that affected society at the time. They include the catastrophic effects of seismic events recorded in this sector of the southern Apennines, an area characterised by high seismicity due to the complex dynamics of the convergence zone between the African and Eurasian plates. New findings reveal a more precise number and previously unreported deaths in several villages, confirming and suggesting some macroseismic intensities for the 1694 seismic event; moreover, further evidence was found for the hypothesised 1692 seismic event. A greater number of deaths was observed in some villages during the 1702 and 1732 events. Parish documents provided details about local construction techniques adopted after the well-known earthquake of 1732, including the use of more resilient materials and design modifications.

GeoHazards doi: 10.3390/geohazards7020052

Authors: Muhammad Zubair Zafar Shah Junji Yagisawa

Rainfall-induced erosion poses a serious threat to river levee slopes, where raindrop impact and surface runoff trigger particle detachment, rill initiation, and gully development, leading to rapid soil loss and local instability. This study experimentally evaluated short-fiber reinforcement as an erosion-control measure for levee slopes under controlled rainfall conditions. Laboratory embankment models were constructed using a uniform soil mixture and compacted under consistent moisture conditions. Simulated rainfall was applied at intensities of 50 and 100 mm/h. Erosion progression was monitored through time-series observations and quantified using sediment collection and three-dimensional surface measurements. Comparative tests were performed on unreinforced and fiber-reinforced slopes to examine the influence of fiber bridging and surface anchoring on the initiation and development of erosion. The results showed that short-fiber reinforcement delayed rill formation and reduced soil loss. Under 50 mm/h rainfall, 1% coir fiber reduced the eroded mass by approximately 70%, whereas polypropylene fiber achieved approximately 42% reduction compared with the unreinforced control. These findings suggest that short natural fibers can effectively enhance the erosion resistance of compacted levee slopes under rain.

GeoHazards doi: 10.3390/geohazards7020051

Authors: Phil J. Watson Hak-Soo Lim

The Korean Peninsula is critically exposed to impacts associated with current and projected rising mean sea-levels (MSLs) associated with climate change. Rising MSL will continue to exacerbate existing coastal hazards (e.g., typhoon-driven storm surges, tidal inundation, beach erosion, etc.). This study updates the previous 2019 national sea-level rise assessment with an additional 7 years of tidal and satellite altimetry data. Having corrected the rate of “relative” MSL rise for vertical land motion, only Busan and Ulsan tide gauge records have not experienced an increase in the rate of “geocentric” MSL rise since the 2019 Assessment. At the 95% CL, the current rate of “geocentric” MSL rise at all stations accord with recent published estimates of the rate of global MSL rise. From satellite altimetry of the sea margins around the Korean Peninsula, there has been a small (≈1%) increase in the average regional trend of sea-level anomalies (SLAs) compared to the previous assessment. The most significant trend estimates in SLAs continue to increase in margins of the East Sea (Sea of Japan) between 35° N and 40° N with increases of around 11% in the average rate of trend above the 2019 Assessment.

GeoHazards doi: 10.3390/geohazards7020050

Authors: Mohammed Mussa Abdulahi Pascal E. Egli Zinabu Bora

Landslides are a critical environmental hazard in mountainous regions like eastern Uganda, posing serious threats to lives, infrastructure, and ecosystems. While recent advances in geospatial technology have improved hazard assessment, existing research often lacks high-resolution, cloud-based analysis for dynamic landscapes such as the Mount Elgon region. This study addresses that gap by developing a landslide susceptibility map (LSM) using Google Earth Engine (GEE), which integrates remote sensing and geospatial data for scalable analysis. The main objective is to identify landslide-prone zones by analyzing eight conditioning factors, namely slope, elevation, vegetation cover, rainfall, land use land cover, soil type, soil moisture, and groundwater levels using the weighted overlay method (WOM). The methodology produced a classified LSM with zones of high (37.7%), moderate (58%), low (2%), and very low (2.3%) susceptibility, with validation via historical landslide data and ROC analysis yielding an AUC of 0.76, confirming strong predictive performance. The study underscores the value of GEE in hazard modeling and provides actionable insights for targeted risk mitigation, sustainable land use planning, and early warning system development in landslide-prone areas.

GeoHazards doi: 10.3390/geohazards7020049

Authors: Gemma Aiello

In order to assess their influence on the marine hazard offshore the Cilento Promontory, the gassy sediments of the Cilento offshore have been thoroughly examined using the geological interpretation of a closely spaced grid of Sub-bottom Chirp profiles. Based on the general stratigraphic framework three areas have been previously identified, highlighting the different acoustic features occurring in the Cilento area. The acoustic anomalies include acoustic blanking, shallow gas pockets, and seismic units impregnated of gas, showing distinct acoustic responses. Understanding these anomalies and the related seismo-stratigraphic units in the offshore Cilento Promontory provides a valuable foundation for evaluating marine geohazards and may assist in developing strategies to mitigate geohazards in the Cilento area.

GeoHazards doi: 10.3390/geohazards7020048

Authors: Ke Ren Cheng Song Na Li Xiaodong Wang Zeming Wang Yanhai Liu

With the expansion of seismic exploration targets to deeper and more complex geological structures, traditional fault interpretation methods face significant challenges in terms of efficiency and accuracy. The extensive application of artificial intelligence (AI) technologies is driving the evolution of fault recognition techniques toward automation and intelligence. This paper systematically reviews the development of AI technologies in fault recognition, from traditional machine learning-based seismic attribute fusion analysis to deep learning-based end-to-end recognition and semantic segmentation. It provides a detailed discussion of key technological advancements, such as sample set construction, weak signal enhancement, and noise suppression. To address the current challenges, including the insufficient authenticity of synthetic data, poor model interpretability, and weak quantitative representation capabilities, this study proposes three future research directions: the development of benchmark datasets based on real geological evolution, the construction of interpretable model architectures that incorporate geological prior information, and the realization of multi-parameter collaborative intelligent fault system analysis. These directions aim to provide theoretical support for advancing the practical and industrial applications of intelligent fault recognition technology.

GeoHazards doi: 10.3390/geohazards7020047

Authors: Mikayel Gevorgyan Arkadi Karakhanyan Avetis Arakelyan Suren Arakelyan Hektor Babayan Gevorg Babayan Elya Sahakyan Lilit Sargsyan

Armenia is located within the central segment of the Arabia–Eurasia continental collision zone and is exposed to significant seismic hazard. This study presents an updated probabilistic seismic hazard assessment (PSHA) for Armenia based on an integrated seismotectonic framework incorporating active fault data, paleoseismological evidence, and historical and instrumental seismicity. A hybrid seismic source model was developed by combining fault-based characteristic earthquake sources with distributed background seismicity. Hazard calculations were performed using the OpenQuake engine within a logic-tree framework to account for epistemic uncertainties in earthquake occurrence and ground-motion prediction. Ground motion was estimated using a weighted set of ground motion prediction equations (GMPEs). Peak ground acceleration (PGA) hazard maps were computed for several return periods, with emphasis on the 475-year return period (10% probability of exceedance in 50 years). The results indicate PGA values across Armenia ranging from approximately 0.2 g to 0.5 g, with the highest hazard levels in northwestern Armenia along the Pambak–Sevan–Syunik Fault System. Hazard deaggregation shows that seismic hazard in major Armenian cities is primarily controlled by shallow earthquakes with magnitudes Mw 6.8–7.4 occurring within ~30 km of urban centers. The results provide a scientific basis for seismic hazard assessment, zonation, and earthquake risk mitigation in Armenia.

GeoHazards doi: 10.3390/geohazards7020046

Authors: Shouguo Yang Shuxin Mei Xiaofei Zhang Jun Liang

This study experimentally investigates the propagation characteristics of static pressure waves (S-waves) and dynamic pressure waves (D-waves) induced by coal and gas outbursts of varying intensities, utilizing a self-built 1:30 scaled laboratory mine ventilation model. Systematic measurements and quantitative analyses were conducted to determine waveform morphology, propagation velocities, attenuation laws, and frequency distributions. The results demonstrate that outburst-induced D-waves exhibit a distinct full-sinusoidal waveform, whereas S-waves present a half-sinusoidal profile. Notably, the wavelength of both wave types remains highly stable regardless of initial outburst intensity and propagation distance. Conversely, the wave amplitude is positively correlated with the outburst intensity and attenuates progressively with distance. Furthermore, D-waves demonstrate a significantly higher sensitivity to propagation distance than S-waves. Spectral analysis confirms that the primary energy of both pressure waves is concentrated in the ultra-low-frequency range below 1.0 Hz. The average propagation velocities of S-waves and D-waves were measured at 395.67 m/s and 280.27 m/s, respectively, indicating that S-waves propagate considerably faster. It should be noted that since these findings were derived under scaled laboratory conditions, direct extrapolation to full-scale, long-distance field roadways requires further validation. Ultimately, this work elucidates the fundamental propagation mechanisms of attenuated pressure waves within mine ventilation networks, providing critical waveform signatures for the remote identification and localization of underground disaster sources.

GeoHazards doi: 10.3390/geohazards7020045

Authors: Osman Nasanlı Devrim Türkan Kejanlı

Population growth and unplanned land use significantly contribute to transforming natural hazards into disasters. Earthquake-induced losses of life and property are often linked to inadequate planning decisions. The city center of Şanlıurfa provides a recent example, where the 6 February 2023 earthquake resulted in 340 fatalities and substantial material damage. Variations in urban planning over different periods have caused disaster risk to fluctuate even across short distances. This study examines Şanlıurfa’s urban development in terms of earthquake vulnerability. Using Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP), the earthquake risk map reveals elevated risk in areas near fault lines and regions with high groundwater levels. Approximately 7% of the area is classified as very low risk, 54% as low risk, 37% as moderate risk, and 2% as high risk. Limited consideration of disaster-focused planning has led to both planned and unplanned developments in hazardous zones. Consequently, construction should prioritize low-risk areas, with necessary precautions applied in high-risk zones when unavoidable.

GeoHazards doi: 10.3390/geohazards7020044

Authors: Jing Meng Yulu Fan Chengjun Feng Peng Zhang Bangshen Qi Chengxuan Tan

The aim of this paper is to investigate dynamic adjustment of the in situ stress field and the stability of main faults in the Zhangbei strong seismic region. Firstly, we utilized in situ stress measurement and monitoring data to discuss the dynamic adjustment process of the in situ stress field. Subsequently, the Fault Slip Potential (FSP) v.1.0 software package was employed to calculate the fault slip potential of the main faults. Finally, the potential hazard of fault activity was assessed. The conclusions are as follows. (1) Since November 2015, the in situ stress field has been primarily influenced by NEE compressive tectonic action, with a slight enhancement in the near SN compressive tectonic action. (2) In the initial stage, NE-trending faults exhibited the highest stress accumulation levels, with near-EW-trending faults the lowest. Influenced by the enhanced near-SN-trending compressive action, as of 19 October 2020, near-EW-trending faults displayed the highest stress accumulation, followed by NW-trending faults, with NE-trending faults showing the least accumulation. (3) From November 2015 to October 2020, the in situ stress field was in a continuous accumulation process. Using the Shangyi–Pingquan fault as a boundary, fault activity in the southern part of the strong seismic region is more hazardous than that in the northern part.

GeoHazards doi: 10.3390/geohazards7020043

Authors: Xiaoyi Hu Jian Ye Yani Huang Haolin Liu Menghao Zhai Xue Li

This study develops a framework to capture spatiotemporal population dynamics and assess future earthquake exposure risk, using Hubei Province as a case study. Future population changes at the county level were projected under different shared socioeconomic pathways (SSPs). These projections were then integrated with NPP-VIIRS nighttime light data and the normalized difference vegetation index (NDVI) to simulate the spatiotemporal dynamics of the population from 2020 to 2070 at a 500 m grid resolution. Combined with seismic hazard zoning, the evolution of population exposure risk under different pathways was assessed. The results indicate the following: 1. Different SSPs profoundly influence future population exposure patterns. Under the SSP3 (regional rivalry) pathway, population growth is the fastest with the strongest agglomeration effect and significantly elevated exposure levels. 2. The refined spatiotemporal population model can more realistically reveal the heterogeneity and evolutionary trajectory of population distribution, providing a high-precision data foundation for exposure analysis and effectively enhancing the scientific rigor of risk assessment. 3. Population exposure risk under various pathways exhibits distinct spatiotemporal dynamics, and monitoring its evolution under different scenarios helps identify high-risk counties that require priority attention. This study is expected to provide precise scientific evidence for implementing differentiated disaster prevention and mitigation strategies and territorial spatial resilience planning in Hubei Province, while it demonstrates the forward-looking value of combining long-term scenario simulations with refined exposure assessments.

GeoHazards doi: 10.3390/geohazards7020042

Authors: Patsani Gregory Kumambala Grivin Chipula Ponyadira Corner Chikondi Makwiza

Malawi lies within the southern segment of the East African Rift System and is exposed to infrequent but potentially damaging earthquakes. While recent advances in fault mapping, seismic monitoring, and hazard modelling have substantially improved scientific understanding of earthquake hazard in the Malawi Rift Zone, the practical reduction in seismic risk remains limited. This Perspective paper argues that earthquake resilience in Malawi is constrained less by scientific uncertainty than by challenges in integrating existing hazard knowledge into governance, planning, and preparedness. Drawing exclusively on published geological, geophysical, engineering, and policy literature, the paper synthesises evidence on seismic hazard, historical earthquake impacts, institutional preparedness, and barriers to the operational use of scientific risk assessments. An integrated, multi-pillar framework is proposed to support improved coordination between science, governance, infrastructure practice, and community preparedness. The framework is conceptual in nature and is intended to inform policy dialogue, prioritisation, and future empirical research rather than to provide a validated operational model. While grounded in the Malawian context, the insights presented are relevant to other low-income, rift-hosted regions facing similar challenges in translating earthquake science into effective disaster risk reduction.

GeoHazards doi: 10.3390/geohazards7020041

Authors: Rhommel N. Grutas Margarita P. Dizon Gilbert A. Ramilo Jeanne Benette P. Pabello Maria Leonila P. Bautista

Prior studies have shown that socio-economic and structural risks can be correlated with earthquake effects. The quantification of these effects was used to formulate robust disaster risk reduction (DRR) strategies and building codes. This is more pronounced in countries with complex tectonic settings, such as the Philippines, where strong-to-major earthquakes can occur. Here, we report the evaluation of deterministic ground shaking (GS) intensity measurements for Camarines Norte, the Philippines, with the objective of assessing and mapping the susceptibility of communities to intense ground motion. GS intensities and peak ground acceleration (PGA) were computed using the Rapid Earthquake Damage Assessment System (REDAS) software developed by the Philippine Institute of Volcanology and Seismology (PHIVOLCS). The PGA was computed as a fraction of acceleration due to gravity, while GS used the PHIVOLCS Earthquake Intensity Scale (PEIS). Simulations were based on recorded earthquakes and mapped active faults near the province. Geographic information systems were used to stack and refine each simulation. Results showed that 13 earthquakes and 13 seismic source zones classified most of the province as PEIS VIII or higher, with the PGA maximum at 0.66 g. The results implied that the province is susceptible to very destructive to completely devastating ground shaking, and it is recommended to incorporate these results into DRR policymaking.

GeoHazards doi: 10.3390/geohazards7020040

Authors: Wenjia Li Yongzhang Zhou

Geohazards such as landslides, earthquakes, debris flows, and floods are governed by complex interactions among geological, hydrological, and human processes. Traditional data-driven models have improved hazard prediction but often lack interpretability and adaptability. This review examines the evolution of knowledge-guided approaches in geohazard research, highlighting how knowledge representation and artificial intelligence have progressively converged to enhance understanding, reasoning, and model transparency. A bibliometric analysis of 1410 publications indexed in the Web of Science reveals an evolution from early ontology-based knowledge engineering for expert reasoning to knowledge graphs (KG), frameworks enabling multi-source data integration and relational inference, and more recently, to large language model (LLM), augmented systems for automated knowledge extraction and cognitive geoscience. This review synthesizes advances in knowledge representation, knowledge graphs, and LLM-based reasoning, demonstrating how hybrid models that embed physical laws and expert knowledge can improve the interpretability and generalization of machine learning. These developments enable new forms of knowledge-driven geohazard intelligence and support applications in hazard monitoring, early warning, and risk communication. There are challenges we still face, including semantic fragmentation, limited causal reasoning, and sparse data for extreme events. Future directions require unified knowledge–data–mechanism architectures, causality-aware modeling, and interoperable standards to advance trustworthy and explainable geohazard intelligence.

GeoHazards doi: 10.3390/geohazards7020039

Authors: Massimo Conforti Olga Petrucci

Rainfall-induced landslides represent one of the most recurrent geohazards affecting the transportation network of southwestern Calabria (Italy). This study provides an integrated assessment of landslide occurrence and road damage along the Costa Viola by combining detailed geomorphological mapping, multi-temporal analyses, historical documentation (1950–2025), and GIS-based spatial data processing. A total of 261 landslides were mapped, affecting approximately 19% of the study area. Slides constitute the dominant movement type (66.7%), followed by complex landslides, flows, and falls. Landslide distribution is strongly controlled by geological and morphometric factors: more than 80% of mapped phenomena occur in highly fractured granitic and gneissic rocks, over 70% lie within 500 m of faults, and more than 90% are located within 300 m of streams. Slope gradient (25–55°) and local relief (350–550 m) further contribute to slope instability patterns. The historical dataset documents 237 landslide-induced road damage events over 75 years, with a marked increase in occurrence since the early 2000s. Most damage events affected the SS18 road and frequently corresponded to reactivations of pre-existing landslides, highlighting the long-term persistence of slope instability and the seasonal influence of intense autumn–winter precipitation. Overall, the results demonstrate that landslide hazard in the Costa Viola is governed by the interplay between structural, lithological, geomorphic, and climatic factors, compounded by anthropogenic modifications along road corridors. The combined landslide inventory and historical database provide a robust basis for risk mitigation, identification of critical road sectors, and future susceptibility and predictive modelling to support effective territorial planning.

GeoHazards doi: 10.3390/geohazards7020038

Authors: Andreas Karakonstantis Vasilis Kapetanidis Nikolaos Madonis Haralambos Kranis George Kaviris

We present an enhanced earthquake catalog for Central Evia and the Northern Gulf of Evia, in Central Greece, between June 2018 and November 2023. The area is characterized by a low background seismicity rate, with occasional clustered events and seismic swarms, including those of February–April 2022 near Drosia and of October 2022 near Styra. The seismic catalog was enhanced by integrating additional data acquired through the application of the EQ-Transformer deep-learning model. A total of ~1400 events were analyzed, with ~1200 of them being successfully relocated with the double-difference method. The available focal mechanisms indicate predominantly normal, oblique-normal, and pure strike-slip faulting. The relocated seismicity was examined in conjunction with known mapped faults to investigate the activated structures at depth, providing insight into their degree of activity. In Drosia, the seismicity, at a depth of ~14 km, can be related to an E–W dextral strike-slip fault, with subtle surficial expression. In Psachna, the epicenters are oriented in an NE–SW direction, not matching the strike of the mainshock’s normal focal mechanism, but roughly coinciding with NE–SW-oriented topographic spurs and the local drainage pattern. In Markates and Prokopi, the seismicity is sparse, but the focal mechanisms are consistent with SW–NE dextral strike-slip faulting, aligned with the trend of the Nileas depression and the Prokopi–Pelion fault zone. Finally, in Mouriki, the seismic cluster is characterized by WNW-ESE normal faulting, most likely related to the SSW-dipping Messapio fault.

GeoHazards doi: 10.3390/geohazards7020037

Authors: Muhammad Rizki Nandika Herlambang Aulia Rachman Martiwi Diah Setiawati Abd. Rahman As-syakur Atika Kumala Dewi La Ode Alifatri Tri Atmaja Takahiro Osawa A. A. Md. Ananda Putra Suardana

Utilizing the InVEST coastal exposure model and multi-source geospatial data, this study evaluates coastal vulnerability to sea-level rise along a critical stretch of the North Coast of Central Java, Indonesia, specifically focusing on the Semarang, Demak, and Jepara regions. A Coastal Exposure Index (CEI) was constructed for 256.63 km of shoreline by integrating key environmental variables, including wave climate, high-resolution coastal topography, shoreline geomorphology, bathymetry, coastal habitat distribution, and observed sea-level rise trends-based satellite altimetry from AVISO. The CEI classified coastal segments into five risk categories from Very Low to Very High exposure. A comparative analysis was performed between a scenario incorporating coastal habitats and a scenario without habitats to determine the protective role of natural ecosystems. The results of the analysis show that the average sea-level rise in the study area is 4.3 mm/year. Moreover, the findings also show that the inclusion of coastal habitats significantly reduces extreme exposure levels. Without accounting for habitats, 22.8% of the coastline was classified as Very High exposure, whereas with habitats included this portion dropped to 1.8%. For example, in Jepara Regency the length of shoreline in Very High exposure class decreased from 53.7% (no habitat scenario) to 5.5% when habitats were considered. Overall, the presence of coastal ecosystems shifted large stretches of the coast to lower exposure classes. This study demonstrates that natural habitats have a critical influence on coastal exposure, substantially mitigating the vulnerability of North Java’s coastline to sea-level rise.

GeoHazards doi: 10.3390/geohazards7010036

Authors: Kevin Potoczny Katsuichiro Goda Abouzar Sadrekarimi

Landslide hazard potential is high across the St. Lawrence lowlands of Québec, Canada, due to sensitive glaciomarine clay deposits and the presence of moderate seismic activity, causing slope failures in the region. The main objectives of the study are to develop a working database for landslides in the region and use that database to improve regional landslide susceptibility analysis. Using high-resolution (1 m by 1 m cells) digital terrain models dated from 2009 and validated with satellite photogrammetry from 2012, a landslide inventory of 263 cases related to the 2010 Val-des-Bois earthquake (moment magnitude 5.0) is created. Relationships between landslide susceptibility factors, such as slope angle, and seismic conditioning factors, such as peak ground acceleration, are examined through machine learning methods. For landslide detection, an overall accuracy of approximately 85% (AUC 0.914) is achieved using random forest and logistic regression models cross-validated through 5-fold analysis, showing improvement over the currently employed Hazus method, which achieves an accuracy of approximately 67%. From a regional perspective, the developed inventory and resultant susceptibility models are unique and form the foundation for future studies to improve the understanding of earthquake-induced landslides in the Western Québec Seismic Zone, which historically lacks detailed landslide inventories.

GeoHazards doi: 10.3390/geohazards7010035

Authors: Adnan Ahmed Abi Sen Fares Hamad Aljohani Nour Mahmoud Bahbouh Adel Ben Mnaouer Omar Tayan Ahmad. B. Alkhodre

Smart cities require effective disaster management (like flooding, solar storms, sandstorms, or hurricanes), as it directly impacts people’s lives. The key challenges of disaster management are timely detection and effective notification during the crisis. This research presents a smart multi-layer framework for notification classification and management before and during flooding disasters. The framework includes an early detection module as the main phase in the alerting process. This step depends on an Ensemble Learning (EL) model based on a triad of the three best selected models (Deep Learning (DL), Random Forest (RF), and K-nearest Neighbor (KNN)) to analyze data collected continuously from the Internet of Things (IoT) layer. In the boosting phase, the framework utilizes Large Language Models (LLMs) with DL to analyze social textual crowdsourcing data. The results will enable the framework to identify the most affected areas during a flood. The framework adds a fog computing layer alongside a cloud layer to enable instantaneous processing of user responses and generate specialized alerts based on contextual factors such as location, time, risk level, alert type, and user characteristics. Through testing and implementation, the proposed algorithms demonstrated an accuracy rate of over 98% in detecting threats using a dataset of real, collected weather and flooding data. Additionally, the framework proposes a centralized control panel and a design of a smartphone application that offers essential services and facilitates communication among managed civil defense teams, citizens, and volunteers.

GeoHazards doi: 10.3390/geohazards7010033

Authors: Károly Németh Abdulrahman Sowaigh Mahmoud Ashor Mostafa Toni Vladimir Sokolov

Saudi Arabia is experiencing interactions between ongoing urbanization, tourism growth, infrastructure projects in western regions along the Red Sea, and volcanic hazards. The area contains extensive monogenetic volcanic fields with hundreds of volcanoes formed during the Quaternary period. The large scale of the region often limits and fragments volcanological research, resulting in insufficient age and chemical data to understand the spatial and temporal development of many volcanic fields. Increased tourism has created a need for volcanic hazard assessments, particularly since some volcanic fields are considered possible tourist destinations. Harrat Lunayyir, in northwestern Saudi Arabia, is an example where such assessments have been conducted. Hazard assessments seek to provide information about potential future eruption types, locations, and impacts over timeframes relevant to urban planning and risk management. Due to rapid local development, these assessments may be required on short notice for specific small areas within larger volcanic fields, even when geological data are limited. This report presents a deterministic, scenario-based method for addressing such requests in the Lunayyir Volcanic Field. Results indicate a young Holocene eruption site characterized by a complex scoria cone associated with lava spattering, Strombolian, violent Strombolian activity and extensive transitional-type lava effusion.

GeoHazards doi: 10.3390/geohazards7010034

Authors: Zeinab Bayati Arash K. Pour Ali Saeidi Ehsan Noroozinejad Farsangi

This study evaluates the stability of slopes supported by mechanically stabilized earth walls under combined hydrostatic and seismic loading conditions. Limit equilibrium, pseudo-static methods and permanent displacement approaches, including the Newmark rigid block method as well as coupled and decoupled techniques, are employed to assess the static and seismic performance of the soil slope under investigation. Parametric analyses are conducted using the Slide2 software package (Version 9.041) and verified against geotechnical design criteria to examine the effects of groundwater level and seismic intensity on factors of safety, failure mechanisms, and seismic-induced displacements of the slope. Results based on multiple strong ground motion records indicate that elevated water tables and hydrostatic pressures behind the wall, up to levels near the wall toe, do not significantly increase the failure potential or slope displacement. This behavior is attributed to the MSE wall acting as a rigid stabilizing system that enhances overall slope stability.

GeoHazards doi: 10.3390/geohazards7010032

Authors: Ioannis Grendas Nikolaos Theodoulidis

In the 20th century, several large-magnitude earthquakes (M > 7.0) occurred in Greece and surrounding areas, some of which caused extensive structural damage and significant loss of life. Unfortunately, for these earthquakes, there was no recorded ground motion intensity data to extract information about the macroseismic intensity distribution within the affected areas. A characteristic example of such an earthquake is the M7.2 of 12 August 1953 on Cephalonia island, which led to the almost complete destruction of settlements across the Cephalonia, Zakynthos, and Ithaca islands in western Greece. Although the vulnerability of the buildings affected in 1953 substantially differs from modern structures, the intensity and spatial extent of the shaking indicate that an event of similar magnitude could, even today, place the built environment and critical infrastructure of the region at high seismic risk. This study aims to estimate peak ground acceleration and velocity (PGA–PGV) and macroseismic intensity for the Cephalonia, Zakynthos, and Ithaca islands associated with earthquake scenarios comparable to the 1953 event (M7.2), incorporating seismotectonic information about active faults linked to the historical earthquake and considering associated uncertainties. Ground motion prediction models recently developed for Greece are employed. High PGA values (0.41–0.44 g) are estimated for the M7.2 earthquake, for rock site conditions (Vs30 ≥ 790 m/s), covering almost the entire island of Cephalonia; these can be considered as the minimum values expected on rock site conditions for a similar earthquake scenario.

GeoHazards doi: 10.3390/geohazards7010031

Authors: Gumbert Maylda Pratama Takashi Gomi Rozaqqa Noviandi Rasis Putra Ritonga Teuku Faisal Fathani Wahyu Wilopo

Tropical mountain watersheds contain heterogeneous land cover and land use (LCLU) mosaics, yet the relationship between these mosaics and landslide morphometry and occurrence at the watershed scale remains unclear. We compiled landslide inventory from 2002 to 2023 for the 152.3 km2 Upper Ciliwung Watershed, West Java, Indonesia. We mapped morphometry for a subset of 84 landslides, classified the events into seven LCLU classes, and compared landslide size–frequency distributions across vegetation groups. Principal component analysis (PCA) revealed that LCLU type influences landslide size and mobility. Forested terrain produced narrower, longer-runout landslides on steeper slopes, whereas agricultural and other herbaceous-dominated terrain generated wider landslides on gentler slopes. Clarifying landslides by vegetation characteristics as either tree- or herbaceous-dominated areas (including urban areas) revealed distinct size–frequency patterns, especially for small landslides (tree-dominated: 133 m2, herbaceous-dominated and other: 97 m2; overall 112 m2), which are consistent with the contrasting vegetation structures and hydrological responses. PCA supported these patterns, with PC1 describing a morphometric axis and PC2 capturing gradients in event rainfall and antecedent wetness. Together, these results support the conclusion that vegetation structure and land-use conditions influence slope stability by affecting soil reinforcement and hydrological responses. This provides a foundation for land–use–specific geohazard mitigation and vegetation-based slope stability planning.

GeoHazards doi: 10.3390/geohazards7010030

Authors: Noureddine Dael Gouem Sepehr Saedi Mohsen Seyedi

Earthfill dams located in seismic regions are highly vulnerable to earthquake-induced deformations, particularly when founded on soft alluvial soils. This study presents a comparative numerical investigation of earthfill dams with asphalt and clay cores subjected to seismic loading. A 20 m-high zoned embankment dam founded on soft alluvial deposits was modeled in PLAXIS2D and subjected to four earthquake records. The dynamic responses at the crest and downstream slope were evaluated in terms of acceleration, settlement, and lateral displacement. The results indicate that while lateral displacements are nearly identical for both core types, dams with clay cores experience significantly higher seismic settlements, reaching up to 35% more than those with asphalt cores under strong earthquake loading. Overall, the asphalt core demonstrated enhanced resilience, exhibiting reduced settlement due to its higher stiffness, viscoelastic behavior, and inherent capacity for self-healing following seismic loading.

GeoHazards doi: 10.3390/geohazards7010027

Authors: Joaquín Raul Rodríguez Erik Esteban Ramírez Mario González-Durán

Mexicali, capital of Baja California, has 1,049,792 inhabitants and lies in a high-seismic-hazard zone in northwestern Mexico, according to CENAPRED, the MDOC-CFE-2015 seismic regionalization, and the ASCE 7-22 “Hazard Toolkit”. This study develops a probabilistic seismic hazard map to estimate peak ground accelerations with a 2% probability of exceedance in 50 years, using the OpenQuake platform. The study area coincides with the 2025 urban development plan polygon for the central population area defined by the Municipal Institute for Research and Urban Planning of Mexicali. The Imperial and Cerro Prieto faults, the Pescaderos–Indiviso fault system, and the Laguna Salada fault were modeled as seismic sources. Four PEER-NGA ground motion prediction equations and regional geophysical and geotechnical data were employed to characterize shear-wave velocity (Vs30). Design response spectra were generated for each grid point for the 21 periods specified in ASCE 7-22. A representative Vs30 of 236 m/s was obtained, and the a, b, and Mc parameters were derived for the seismic catalog. Resulting peak ground accelerations range from 0.842 g to 1.221 g, with a maximum spectral pseudo-acceleration of 2.23 g at 0.30 s.

GeoHazards doi: 10.3390/geohazards7010029

Authors: Essi Nadège Parkoo Kossi Adjonou Atsu K. Dogbeda Hlovor Afi Amen Christèle Attiogbé Kossi Komi Kodjovi Senanou Gbafa Kouami Kokou

The Upper Mono Basin Valley (UMBV) in Togo faces recurrent flooding hazards. This study assesses spatial flood susceptibility using an integrated approach combining Geographic Information Systems (GISs), Multi-Criteria Decision Making (MCDM), and the Analytic Hierarchy Process (AHP). Eight factors were weighted according to their influence: accumulation flow, annual precipitation, soil permeability, land use/land cover, slope, elevation, distance from drainage networks, and drainage network density. With a consistency ratio of 0.052, the AHP method proved coherent and enabled the development of a normalized Flood Hazard Index (FHI). Results revealed accumulation flow (weight = 0.33), distance to drainage networks (0.18), and network density (0.16) as the most critical drivers, while precipitation and soil permeability are secondary. Spatial classification revealed heterogeneity: 55% (871,046 ha) of the UMBV has very low susceptibility, while 1% (10,034 ha) is highly vulnerable, mainly in Est-Mono, Ogou, Anié, Tchamba, and Tchaoudjo. In contrast, Blitta and Sotouboua show lower vulnerability due to higher altitudes. This reveals that the UMBV is relatively less prone to flooding. The comparison of data from 28 focus groups in 14 municipalities with the flood susceptibility map shows a strong concordance between local perceptions and the mapping (r = 0.805, p < 0.001). These findings highlight the need for differentiated territorial strategies integrating physical parameters, land use dynamics, and community risk perceptions to strengthen flood risk management in the UMBV.

GeoHazards doi: 10.3390/geohazards7010028

Authors: Robert E. Kayen

The 1964 M7.5 Niigata earthquake remains one of the most significant natural laboratories for understanding seismic–induced soil liquefaction and its dependence on geological setting. Among global field case histories, Niigata stands out for the exceptional documentation of liquefaction triggering, lateral spread displacements, and soil–structure interaction. This paper reexamines the event from an engineering–geologic perspective, emphasizing how Holocene coastal and fluvial depositional processes beneath the Echigo Plain controlled the spatial and stratigraphic distribution of liquefaction during the 1964 earthquake. The most severe ground deformations occurred in fluvially reworked sands derived from three major Holocene dune and barrier island systems (CSD1,2,3) formed along the paleo–shoreline of the Sea of Japan. The largest of these, a mid–Holocene transgressive barrier complex deposited to a thickness of 50–60 m of beach and aeolian sand between 8 and 5 ka B.P., now lies buried 5–8 km inland beneath fine–grained alluvial deposits. Tectonic downwarping and deltaic progradation by the Shinano and Agano rivers redistributed these sands into loose, saturated fluvial facies beneath modern Niigata city. Quantitative geotechnical analyses demonstrate that liquefaction occurs within these reworked Holocene units rather than anthropogenic fills.

GeoHazards doi: 10.3390/geohazards7010026

Authors: Emmanuel Zúñiga Enrique Pérez-Campuzano

Mexico City (CDMX) is located in an endorheic basin historically prone to flooding and waterlogging, the recurrence and magnitude of which have intensified in recent decades. However, flood risk assessment tends to focus primarily on the occurrence of intense rainfall to explain this phenomenon. The main objective of this study is to demonstrate that the risk of flooding in Mexico City (CDMX) depends not only on intense rainfall, but also on changes in hydrological vulnerability resulting from the loss of natural vegetation cover. The curve number (CN) method is used to determine hydrological vulnerability and flood risk in CDMX, integrating environmental information and precipitation values. Changes in surface runoff are also determined for 10 watersheds located west of Mexico City, considering urbanization in 1992 and 2021, as well as a non-urbanized scenario. The results indicate that hydrological vulnerability and flood risk increased from acceptable levels to “high” and “very high” levels, mainly in regions where urbanization increased and natural vegetation decreased. It was also identified that, under different levels of precipitation, agricultural and urban land cover have considerably lower infiltration capacities compared to natural land cover, such as forests, which infiltrate more than half of the precipitation. Finally, the increase in surface runoff in the watersheds located west of the city is closely related to the urbanization process and the physical characteristics of the territory. It was also observed that a degraded watershed can generate approximately 90% more runoff than a non-urbanized watershed.

GeoHazards doi: 10.3390/geohazards7010025

Authors: José Luis Pérez-García José Miguel Gómez-López Antonio Tomás Mozas-Calvache Diego Vico-García

Precise modeling of narrow gorges is challenging due to extreme confinement, hindering visibility and accessibility. These environments often render Global Navigation Satellite Systems (GNSS)-based positioning unfeasible, a difficulty compounded by water and dense vegetation. Consequently, multi-technique data fusion is required. This study proposes a robust methodology to generate high-resolution 3D models of such complex environments by integrating multiple aerial (e.g., Unmanned Aerial Vehicles, UAVs) and terrestrial techniques. A multi-sensor approach combined UAV-Light Detection and Ranging (LiDAR) and UAV-photogrammetry for external areas with Terrestrial laser scanning (TLS), Mobile Mapping System (MMS), and Spherical Photogrammetry (SP) for the canyon floor. Furthermore, the representativeness of these 3D models was analyzed against standard Digital Terrain Models (DTMs) for determining water height levels during flood events. A one-dimensional hydraulic (1DH) model compared the 3D mesh approach with the traditional 2.5D perspective in a challenging, narrow canyon prone to flooding. Our results show that traditional 2.5D DTMs significantly over- or underestimate water levels in narrow sections—failing to account for overhangs and vertical wall irregularities—whereas high-resolution 3D meshes provide a more realistic representation of hydraulic behavior. This work demonstrates that multi-sensor data fusion is essential for accurate flood risk management and infrastructure planning in complex fluvial environments.

GeoHazards doi: 10.3390/geohazards7010024

Authors: Mohammad Reza Yeganegi Nadejda Komendantova

Building resilience is largely affected by the socioeconomic characteristics of the community as well as the physical and environmental local characteristics. The effectiveness of the adopted policies for resilience building partly relies on considering public concerns and insights. Insights from public narratives can enrich the resilience-building policies by sharing experiences or evidence from past disasters. Furthermore, it reveals priorities and concerns that society is expecting to be addressed. Even if the concerns are triggered by misinformation, addressing them (e.g., by disseminating corrective information) can increase the success of resilience-building policies. Tracing the public narrative over time shows how much people’s perspectives have changed after the disaster and how the relief and resilience-building efforts were compatible with society’s expectations. This study is aimed at extracting such insights from the public narrative on social media platforms after Morocco’s 2023 earthquake.

GeoHazards doi: 10.3390/geohazards7010023

Authors: Irshad Ali Zardari Ningsheng Chen Surih Sibaghatullah Jagirani Shufeng Tian Rosette Niyirora

A dam breach is an uncommon but profoundly destructive event that transpires when a dam collapses, releasing accumulated water downstream and leading to extensive damage. This study focuses on the Jure landslide dam, located in the Sindhupalchowk district, Nepal. The region is characterized by complex river channels and steep terrains, which are significantly influenced by flood dynamics. This study aims to establish a compressive numerical simulation of a two-dimensional dam breach unsteady flow hydraulic model to simulate the dam breach process and downstream flood propagation. The study analyzes the dynamics of the Jure landslide dam outburst flood, emphasizing the flood characteristics, inundation, and velocity hazards in the mitigation of flood impacts. The results reveal that the peak discharge of the Jure landside dam was 5336.7 m3/s, while it decreased to 1181.4 m3/s when traveling 35 km. The flood depth obtained by 2D (HEC-RAS) downstream of the dam rages between 0.0334 and 55.9 m, while the corresponding estimated peak flow velocity of simulated breaches was 21.46 m/s, demonstrating extreme hydraulic force conditions, capable of catastrophe. The proposed hydraulic simulations reveal significant variations in overflow dynamics across different terrain types, with narrower sections exhibiting faster flood progression and greater water depths. The findings underscore the necessity of accounting for terrain heterogeneity in future flood risk assessments. This work offers valuable insights into the emergency management of landslide dams in similar regions.

GeoHazards doi: 10.3390/geohazards7010022

Authors: Constantin D. Athanassas Vassiliki Kanavou Regis Braucher Ioannis Vakalas Ioannis Ladas Katerina Theodorakopoulou Harris Zampoukos

This work deals with the quantification of long-term fault slip rates as a basis for seismic hazard assessment along a segment of the Eastern Messinia Fault Zone (EMFZ) in southwestern Peloponnese, Greece. Using cosmogenic 36Cl exposure dating, it provides independent numerical constraints on recent deformation. The resulting late Holocene slip-rate estimates (~0.32–0.46 mm/yr) confirm ongoing fault activity, consistent with earlier paleoseismological and geomorphic studies, while indicating spatially distributed extension. These rates imply loading timescales of several hundred years for moderate (Mw ≈ 5.8–6.0) earthquakes. Although individual exposure ages cannot be uniquely associated with single seismic events, they offer robust benchmarks for cumulative displacement and long-term strain accumulation. Overall, this work demonstrates how numerical dating methods (particularly cosmogenic nuclide techniques applied to carbonate bedrock) can link geological observations with engineering requirements by constraining fault behavior over 103–105 year timescales and improving long-term seismic hazard evaluation in complex tectonic settings.

GeoHazards doi: 10.3390/geohazards7010021

Authors: Mikayel Gevorgyan Dmitri Arakelyan Hayk Igityan Hayk Baghdasaryan Hektor Babayan Gevorg Babayan Suren Arakelyan Khachatur Meliksetian Elya Sahakyan

The territory of the Republic of Armenia (RA) lies within the central Arabia–Eurasia collision zone and is characterized by rugged mountain landscapes, complex geology, active faulting, and seismicity. Armenia is highly vulnerable to seismic and landslide hazards, with more than 2504 active landslides mapped in the country. A significant landslide in the Tumanyan Community, Lori Marz, was activated in January 2018 and threatened critical infrastructure, including the railway linking Armenia to Georgia and the M6 interstate highway. The landslide’s activation was driven by groundwater, a nearby water reservoir leak, and adjacent infrastructure. Preliminary hazard analysis revealed that further movement of the landslide could dam the Debed River, leading to potentially catastrophic downstream impacts. In response, the Minister of Emergency Situations of RA requested urgent studies by the Institute of Geological Sciences of NAS RA. Surveys began on 22 January 2018, involving an interdisciplinary approach including geotechnical study, UAV-based digital mapping, and application of geophysical methods, such as MASW, microtremor recordings, GPR, and VES. The combination of these methods provided reliable information on the landslide’s geotechnical structure, identified the sliding plane, and allowed for numerical slope stability modeling, which confirmed the landslide’s unstable condition and susceptibility to reactivation from earthquakes or elevated groundwater. Based on this complex research, protective measures were developed and applied, including, in particular, horizontal drilling to dewater the sliding plane. These emergency measures stabilized the landslide, mitigating immediate threats to infrastructure and ensuring relative safety.

GeoHazards doi: 10.3390/geohazards7010020

Authors: Javedullah Hemat Sherzai Yoshiya Igarashi Norio Tanaka Hokuto Kato Takuma Takeda

Levee overtopping poses a significant risk to flood defense infrastructure by inducing severe erosion and scour, particularly along the landward slope and toe regions. This study investigates the effectiveness of an integrated protection system combining seamless cement coating with strategically placed H-type piles to mitigate scour and modify flow dynamics under prolonged overflowing. A series of physical model tests were conducted to evaluate full and partial concrete slope protection with and without pile integration. Results showed that the seamless concrete revetment significantly delayed slope failure, resisted joint-related seepage, acted as a rigid cantilever, and maintained the structural integrity despite surrounding erosion. The inclusion of emergent H-type piles at the downstream toe disrupted the overflow jet, enhanced early energy dissipation, and reduced scour dimensions. The FC + P_ES (fully coated with emergent piles) configuration exhibited the strongest performance, reducing downstream scour length by 40%, upstream extent by 66.7%, and maximum scour depth by 7.7% compared to the FC_NP (fully coated, no-piles) condition. Partial slope coverage combined with emergent piles delayed scour initiation by approximately threefold, highlighting the synergistic effect of combined surface and flow-deflected structures measures. Conversely, bed-level piles redirected jet energy beneath the surface layer, intensifying vertical scour and upstream erosion, indicating the critical importance of pile placement and elevation. The findings emphasize the importance of integrating seamless surface protection with vertical flow disrupters to effectively manage flow-induced erosion and enhance levee resilience against overtopping floods. This hybrid approach offers a practical solution for flood-prone riverine levee systems.