Search Results (206)

The submarine topography in the canyon area of the Qiongdongnan Basin is complex, with severe risks of shallow gas hazards threatening marine engineering safety. To accurately characterize seabed morphology and assess shallow gas risks, this study employed multi-source data fusion technology, integrating 3D seismic data, shipborne multibeam bathymetry data, and high-precision AUV topographic data from key areas to construct a refined seabed terrain inversion model. For the first time, the spatial distribution characteristics of complex geomorphological features such as scarps, mounds, fissures, faults, and mass transport deposits (MTDs) were systematically delineated. Based on attribute analysis of 3D seismic data and geostatistical methods, the enrichment intensity of shallow gas was quantified, its distribution patterns were systematically identified, and risk level evaluations were conducted. The results indicate: (1) multi-source data fusion significantly improved the resolution and accuracy of terrain inversion, revealing intricate geomorphological details in deep-water regions; and (2) seismic attribute analysis effectively delineated shallow gas enrichment zones, clarifying their spatial distribution patterns and risk levels. This study provides critical technical support for deep-water drilling platform site selection, submarine pipeline route optimization, and engineering geohazard prevention, offering significant practical implications for ensuring the safety of deep-water energy development in the South China Sea. Full article

Isolated permafrost is widely distributed in freeze–thaw transition zones, characterized by blurred boundaries and strong spatial variability. Traditional methods such as drilling and electrical resistivity surveys are often limited in achieving efficient and continuous boundary identification. This study focuses on a typical isolated permafrost region in Northeast China and proposes a boundary detection strategy based on multi-frequency electromagnetic (EM) measurements using the GEM-2 sensor. By designing multiple frequency combinations and applying joint inversion, a boundary identification framework was developed and validated against borehole data. Results show that the multi-frequency joint inversion method improves the spatial identification accuracy of permafrost boundaries compared to traditional point-based techniques. In areas lacking boreholes, the method still demonstrates coherent boundary imaging and strong adaptability to geomorphological conditions. The multi-frequency joint inversion strategy significantly enhances imaging continuity and effectively captures electrical variations in complex freeze–thaw transition zones. Overall, this study establishes a complete non-invasive technical workflow—“acquisition–inversion–validation–imaging”—providing an efficient and scalable tool for engineering site selection, foundation design, and permafrost degradation monitoring. It also offers a methodological paradigm for electromagnetic frequency optimization and subsurface electrical boundary modeling. Full article

Nieuwerkerk Volcano, located in the Banda Sea, Indonesia, is a submarine volcano whose entire edifice lies beneath sea level. Its proximity to several inhabited islands raises significant concerns regarding potential impacts from future volcanic hazards. Despite historical unrest recorded in 1925 and 1927, a comprehensive geological and geophysical understanding of Nieuwerkerk remains notably limited, with the last research expedition being in 1930. This study seeks to advance our understanding of the geomorphological structure and subsurface characteristics of the region, contributing to a preliminary hazard assessment and delineating key directions for future geoscientific investigation. The data were obtained during our most recent expedition conducted in 2022. High-resolution multibeam bathymetry data were analyzed to delineate the volcano’s morphology, while marine magnetic survey data were processed to interpret magnetic anomalies associated with its structure beneath volcano. Our updated morphological analysis reveals the following: (1) Nieuwerkerk Volcano is among the largest submarine volcanic edifices in the Banda Sea (length = 80 km, width = 30 km, height = 3460 m); (2) there is the presence of twin peaks (depth~300m); (3) there are indications of sector collapse (diameter = 10–12 km); (4) there are significant fault lineaments; and (5) there are landslide deposits, suggesting a complex volcanic edifice shaped by various constructive and destructive processes. The magnetic data show a low magnetic anomaly beneath the surface, where one of the indications is the presence of active magma. These findings significantly enhance our understanding of Nieuwerkerk’s current condition and volcanic evolution for an initial assessment of potential hazards, including future eruptions, edifice collapse, and landslides, which could subsequently trigger tsunamis. Further investigation, including comprehensive geophysical surveys covering the entire Nieuwerkerk area, rock sample analysis, visual seafloor observation, and seawater characterization, is crucial for a comprehensive understanding of its magmatic system and a more robust hazard assessment. This research highlights the critical need for detailed investigations of active submarine volcanoes, particularly those with sparse historical records and close proximity to populated areas, within tectonically complex settings such as the Banda Sea. Full article

Rainfall-induced slope failures are among the most frequent and destructive natural hazards in Japan’s mountainous regions, often causing severe loss of life and damage to infrastructure. This study presents an integrated statistical framework for regional-scale landslide hazard mapping, with a focus on 0-order basins. To enhance spatial prediction accuracy, both bivariate and multivariate statistical models are employed. Bivariate models efficiently assess the relationship between individual conditioning factors and landslide occurrences but assume variable independence. Conversely, multivariate models account for multicollinearity and the combined effects of interacting factors, although they often require more complex data processing and may lack spatial clarity. To leverage the strengths of both approaches, two hybrid models were developed and applied to a 242.94 km² area in Fukuoka Prefecture, Japan. Model validation was performed using a matrix-based evaluation supported by a threshold optimization algorithm. Among the models tested, the hybrid Frequency Ratio–Logistic Regression (FR + LR) model demonstrated the highest predictive performance, achieving a success rate of 84.30%, a false alarm rate of 17.88%, and a miss rate of 12.30%. It effectively identified critical slip surfaces within zones classified as ‘High’ to ‘Very High’ susceptibility. This integrated approach offers a statistically robust, scalable, and interpretable solution for landslide hazard assessment in geomorphologically complex terrains. It provides valuable support for regional disaster risk reduction and contributes directly to achieving the Sustainable Development Goals (SDGs). Full article

As an integral component of humanity’s cultural heritage, traditional villages universally confront challenges such as population loss and cultural discontinuity amid rapid urbanization. Cluster-based protection models have increasingly become the international consensus for addressing the survival crisis of such settlements. This study selects the Central Yunnan region of Southwest China—characterized by its complex geography and multi-ethnic habitation—as the research area. Employing ArcGIS spatial analysis techniques alongside clustering algorithms, we examine the spatial distribution characteristics and clustering patterns of 251 traditional villages within this region. The findings are as follows. In terms of spatial distribution, traditional villages in Central Yunnan are unevenly dispersed, predominantly aggregating on mid-elevation gentle slopes; their locations are chiefly influenced by rivers and historical courier routes, albeit with only indirect dependence on waterways. Regarding single-cluster attributes, the spatial and geomorphological features exhibit a composite “band-and-group” pattern shaped by river valleys; culturally, two dominant modes emerge—“ancient-route-dependent” and “ethnic-symbiosis”—reflecting an economy-driven cultural mechanism alongside latent marginalization risks. Concerning construction characteristics, the “Qionglong-Ganlan” and Han-style “One-seal” residential features stand out, illustrating both adaptation to mountainous environments and the cumulative effects of historical culture. Based on these insights, we propose a three-tiered clustering classification framework—“comprehensive-element coordination”, “feature-led”, and “potential-cultivation”—to inform the development of contiguous and typological protection strategies for traditional villages in highland, multi-ethnic regions. Full article

Based on the new high-resolution multibeam bathymetry data collected by the “Dongfanghong 3” vessel in 2023 in the Parece Vela Basin (PVB) and previous magnetic anomaly data, we systematically analyze the seafloor topographical changes of abyssal hills and oceanic core complexes (OCCs) in the “Chaotic Terrain” region, and the revised seafloor spreading model is constructed in the PVB. Using detailed analysis of the seafloor topography, we identify typical geomorphological features associated with seafloor spreading, such as regularly aligned abyssal hills and OCCs in the PVB. The direction variations of seafloor spreading in the PVB are closely related to mid-ocean ridge rotation and propagation. The formation of OCCs in the “Chaotic Terrain” can be explained by links to the continuous and persistent activity of detachment faults and dynamic adjustments controlled by variations of deep magma supply in the different segments in the PVB. We use 2D discrete Fourier image analysis of the seafloor topography to calculate the aspect ratio (AR) values of abyssal hills in the western part of the PVB. The AR value variations reveal a distinct imbalance in magma supply across various regions during the basin spreading process. Compared to the “Chaotic Terrain” area, the region with abyssal hills indicates a higher magma supply and greater linearity on seafloor topography. AR values fluctuated between 2.1 and 1.7 of abyssal hills in the western segment, while in the “Chaotic Terrain”, they dropped to 1.3 due to the lower magma supply. After the formation of the OCC-1, AR values increased to 1.9 in the eastern segment, and this shows the increase in magma supply. Based on changes in seafloor topography and variations in magma supply across different segments of the PVB, we propose that the seafloor spreading process in the magnetic anomaly linear strip 9-6A of the PVB mainly underwent four formation stages: ridge rotation, rift propagation, magma-poor supply, and the maturation period of OCCs. Full article

Accurate prediction of drifting trajectories is essential for improving the operational efficiency of maritime search and rescue (SAR), particularly within the complex geomorphological settings of island and reef regions, such as those in the South China Sea. This study investigates the drift characteristics of life rafts under varying loading conditions across both open-sea and island–reef regions. Comprehensive field experiments were conducted over 15 days in the waters around the Wanshan Archipelago, using advanced instruments to collect wind, current, and drift trajectory data. Based on these observations, two models—the AP98 leeway model and a BP neural network model—were developed and validated. The results show that the AP98 model performs better in open-sea conditions, whereas the BP neural network provides more accurate predictions in island and reef areas with complex environmental factors. A Monte Carlo simulation was also integrated to enhance the robustness of drift area predictions. These findings offer valuable insights into life raft drift behavior in complex marine environments and provide technical support for improving SAR operations in island–reef regions. Full article

Riverbed dynamics are natural processes that are strongly driven by human and climatic factors. In the last two centuries, the anthropogenic influence and impact of climate change on European rivers has resulted in significant degradation of riverbeds. This research paper aims to determine the historical evolution (1856–2021) and future trends of the Ialomița riverbed (Romania) under the influence of anthropogenic impact and climate change. The case study is a reach of 66 km between the confluences with the Ialomicioara and Pâscov rivers. The localisation in a contact zone between the Curvature Subcarpathians and the Târgoviște Plain, the active recent tectonic uplift of the area, and the intense anthropogenic intervention gives to this river reach favourable conditions for pronounced riverbed dynamics over time. To achieve the aim of the study, we developed a complex methodology which involves the use of Geographical Information System (GIS) techniques, hierarchical cluster analysis (HCA), the Mann–Kendall test (MK), and R programming. The results indicate that the evolution of the Ialomița River aligns with the general trends observed across Europe and within Romania, characterised by a reduction in riverbed geomorphological complexity and a general transition from a braided, multi-thread into a sinuous, single-thread fluvial style. The main processes consist of channel narrowing and incision alternating with intense meandering. However, specific temporal and spatial evolution patterns were identified, mainly influenced by the increasingly anthropogenic local influences and confirmed climate changes in the study area since the second half of the 20th century. Future evolutionary trends suggest that, in the absence of river restoration interventions, the Ialomița riverbed is expected to continue degrading on a short-term horizon, following both climatic and anthropogenic signals. The findings of this study may contribute to a better understanding of recent river behaviours and serve as a valuable tool for the management of the Ialomița River. Full article

Reliable gridded precipitation products (GPPs) are essential for effective hydrological simulations, particularly in mountainous regions with limited ground-based observations. This study evaluates the performance of two widely used GPPs, CHIRPS and ERA5, in estimating precipitation and supporting runoff generation using the Soil and Water Assessment Tool (SWAT) across three headwater catchments (Sill, Drava and Isel) in the Austrian Alps from 1991 to 2018. The region’s complex topography and climatic variability present a rigorous test for GPP application. The evaluation methods combined point-to-point comparisons with gauge observations and assessments of generated runoff and runoff trends at annual, seasonal and monthly scales. CHIRPS showed a lower precipitation error (RMAE = 25%) and generated more consistent runoff results (RMAE = 12%), particularly in smaller catchments, whereas ERA5 showed higher spatial consistency but higher overall precipitation bias (RMAE = 37%). Although both datasets successfully reproduced the seasonal runoff regime, CHIRPS outperformed ERA5 in trend detection and monthly runoff estimates. Both GPPs systematically overestimate annual and seasonal precipitation amounts, especially at lower elevations and during the cold season. The results highlight the critical influence of GPP spatial resolution and its alignment with catchment morphology on model performance. While both products are viable alternatives to observed precipitation, CHIRPS is recommended for hydrological modelling in smaller, topographically complex alpine catchments due to its higher spatial resolution. Despite its higher precipitation bias, ERA5’s superior correlation with observations suggests strong potential for improved model performance if bias correction techniques are applied. The findings emphasize the importance of selecting GPPs based on the scale and geomorphological and climatic conditions of the study area. Full article

The integration of traditional geomorphological approaches with advanced artificial intelligence techniques represents a promising frontier in flood risk assessment for arid regions. This study presents a comprehensive analysis of the Wadi Ranuna basin in Medina, Saudi Arabia, combining detailed morphometric parameters with advanced Geospatial Artificial Intelligence (GeoAI) algorithms to enhance flood susceptibility modeling. Using digital elevation models (DEMs) and geographic information systems (GISs), we extracted 23 morphometric parameters across 67 sub-basins and applied XGBoost, Random Forest, and Gradient Boosting (GB) models to predict both continuous flood susceptibility indices and binary flood occurrences. The machine learning models utilize morphometric parameters as input features to capture complex non-linear interactions, including threshold-dependent relationships where the stream frequency impact intensifies above 3.0 streams/km², and the compound effects between the drainage density and relief ratio. The analysis revealed that the basin covers an area of 188.18 km² with a perimeter of 101.71 km and contains 610 streams across six orders. The basin exhibits an elongated shape with a form factor of 0.17 and circularity ratio of 0.23, indicating natural flood-moderating characteristics. GB emerged as the best-performing model, achieving an RMSE of 6.50 and an R² value of 0.9212. Model validation through multi-source approaches, including field verification at 35 locations, achieved 78% spatial correspondence with documented flood events and 94% accuracy for very high susceptibility areas. SHAP analysis identified the stream frequency, overland flow length, and drainage texture as the most influential predictors of flood susceptibility. K-Means clustering uncovered three morphometrically distinct zones, with Cluster 1 exhibiting the highest flood risk potential. Spatial analysis revealed 67% of existing infrastructure was located within high-risk zones, with 23 km of major roads and eight critical facilities positioned in flood-prone areas. The spatial distribution of GBM-predicted flood susceptibility identified high-risk zones predominantly in the central and southern parts of the basin, covering 12.3% (23.1 km²) of the total area. This integrated approach provides quantitative evidence for informed watershed management decisions and demonstrates the effectiveness of combining traditional morphometric analysis with advanced machine learning techniques for enhanced flood risk assessment in arid regions. Full article

The possibility of collecting new archaeological elements useful in reconstructing the dynamics of population, production and commercial activities in the Bronze Age at the edge of the central-southern Venice Lagoon was provided between 2023 and 2024 thanks to an intervention of rescue archaeology planned during some water restoration works in the Giare–Mira area. Three small excavations revealed, approximately one meter below the current surface and covered by alluvial sediments, a rather complex palimpsest dated to the late Recent and the early Final Bronze Age. Three large circular pits containing exclusively purified grey/blue clay and very rare inclusions of vegetable fibres, and many large, fired clay vessels’ bases, walls and rims clustered in concentrated assemblages and random deposits point to potential on-site production. Two pyro-technological structures, one characterised by a sub-circular combustion chamber and a long inlet channel/praefurnium, and the second one with a sub-rectangular shape with arched niches along its southern side, complete the exceptional context here discovered. To analyse the relationship between the site and the natural sedimentary succession and to evaluate the possible extension of this site, three electrical resistivity tomography (ERT) and low-frequency electromagnetic (FDEM) measurements were collected. Several manual core drillings associated with remote sensing integrated the geophysical data in the analysis of the geomorphological evolution of this area, clearly related to different phases of fluvial activity, in a framework of continuous relative sea level rise. The typology and chronology of the archaeological structures and materials, currently undergoing further analyses, support the interpretation of the site as a late Recent/early Final Bronze Age productive site. Geophysical and geomorphological data provide information on the palaeoenvironmental setting, suggesting that the site was located on a fine-grained, stable alluvial plain at a distance of a few kilometres from the lagoon shore to the south-east and the course of the Brenta River to the north. The archaeological site was buried by fine-grained floodplain deposits attributed to the Brenta River. The good preservation of the archaeological structures buried by fluvial sediments suggests that the site was abandoned soon before sedimentation started. Full article

This study explores the water harvesting systems of mgouds in southern Tunisia and boqueras in southeastern Spain to understand their adaptation to semi-arid conditions and geomorphic contexts. These systems use ephemeral water through medieval-origin infrastructures to increase the water supply to rainfed crops. The hypothesis is that the diversity of these systems stems from environmental rather than cultural factors. By employing a qualitative–analytical approach, this study compares concentrated runoff diversion systems to investigate the use of boqueras/mgouds in terraces and glacis in the arid and semi-arid areas of Tunisia and the southeastern Iberian Peninsula. The research involved performing detailed geomorphological and climatological analyses and comparing structural complexities and water management strategies across different regions. The results indicate significant variability in system size and complexity. Tunisian mgouds are typically simpler and more individualised, while Spanish boqueras are larger and more complex due to more frequent and intense torrential rainfall. No common patterns were identified between the two regions. This study reveals that both types of systems reflect sophisticated adaptations to manage water scarcity and mitigate the impacts of intense rainfall, with geomorphic and climatic factors playing a decisive role. The primary conclusion is that the design and functionality of these water systems are predominantly influenced by environmental conditions rather than cultural factors. This research provides insights for developing sustainable water management strategies in other semi-arid regions. Full article

The complex geological environment in western Sichuan, China, leads to frequent debris flow disasters, posing significant threats to the lives and property of local residents. In this study, debris flow susceptibility models were developed using three machine learning algorithms: Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost). The models were trained with data in Songpan County and used for debris flow susceptibility prediction in Mao County, using small watersheds as assessment units. Seventeen key feature factors based on multi-source remote sensing data encompassing topography and geomorphology, geological structures, environmental elements, and human activities were selected as input parameters after assessment with Pearson correlation analysis. Model performance was rigorously evaluated through ten-fold cross-validation, and hyperparameter optimization was employed to enhance predictive accuracy. To assess the models’ robustness, the trained models were applied to the neighboring Mao County for cross-regional validation. The results consistently indicate that elevation, seismic nucleation density, population density, and distance to roads are the primary controlling factors influencing susceptibility. Comparative analysis between the Songpan and Mao County reveals that the RF model significantly outperforms SVM and XGBoost in accuracy and robustness. Therefore, the RF model is better suited for debris flow susceptibility assessment in western Sichuan. Although the effectiveness of this model may be limited by the relatively small sample size of debris flow events in the dataset and potential variations in environmental conditions across different regions, it still holds promise for providing a scientific basis and decision-making support for disaster mitigation in comparable areas of western Sichuan. Full article

Potentially toxic elements such as cadmium (Cd) in agricultural soils represent a global concern due to their toxicity and potential accumulation in the food chain. However, our understanding of cadmium’s complex sources and the mechanisms controlling its spatial distribution across diverse edaphic and geological contexts remains limited, particularly in underexplored agricultural regions. Our study aimed to assess the total accumulated Cd content in soils under avocado cultivation and its association with edaphic, geochemical, and geomorphological variables. To this end, we considered the total concentrations of other metals and explored their associations to gain a better understanding of Cd’s spatial distribution. We analyzed 26 physicochemical properties, the total concentrations of 22 elements (including heavy and trace metals such as As, Ba, Cr, Cu, Hg, Ni, Pb, Sb, Se, Sr, Tl, V, and Zn and major elements such as Al, Ca, Fe, K, Mg, and Na), and six geospatial variables in 410 soil samples collected from various avocado-growing regions in Peru in order to identity potential associations that could help explain the spatial patterns of Cd. For data analysis, we applied (1) univariate statistics (skewness, kurtosis); (2) multivariate methods such as Spearman correlations and principal component analysis (PCA); (3) spatial modeling using the Geodetector tool; and (4) non-parametric testing (Kruskal–Wallis test with Dunn’s post hoc test). Our results indicated (1) the presence of hotspots with Cd concentrations exceeding 3 mg·kg⁻¹, displaying a leptokurtic distribution (skewness = 7.3); (2) dominant accumulation mechanisms involving co-adsorption and cation competition (Na⁺, Ca²⁺), as well as geogenic co-accumulation with Zn and Pb; and (3) significantly higher Cd concentrations in Leptosols derived from Cretaceous intermediate igneous rocks (diorites/tonalites), averaging 1.33 mg kg⁻¹ compared to 0.20 mg·kg⁻¹ in alluvial soils (p < 0.0001). The factors with the greatest explanatory power (q > 15%, Geodetector) were the Zn content, parent material, geological age, and soil taxonomic classification. These findings provide edaphogenetic insights that can inform soil cadmium (Cd) management strategies, including recommendations to avoid establishing new plantations in areas with a high risk of Cd accumulation. Such approaches can enhance the efficiency of mitigation programs and reduce the risks to export markets. Full article

Urban expansion in coastal areas involves infrastructure development, industrial growth, and mining activities. These coastal environments face various environmental and geological hazards that require geo-engineers to devise solutions. An integrated geophysical approach aims to address such complex challenges as sea level rise, sea water intrusion, shoreline erosion, landslides and previous anthropogenic activity in coastal settings. In this study, the proposed methodology involves the systematic application of geophysical methods (FDEM, 3D GPR, 3D ERT, seismic), starting with a broad-scale survey and then proceeding to a localized exploration, in order to identify lithostratigraphy, bedrock depth, sea water intrusion and detect anthropogenic buried features. The critical aspect is to leverage the unique strengths and limitations of each method within the coastal environment, so as to derive valuable insights for survey design (extension and orientation of measurements) and data interpretation. The coastal zone of Throrikos valley, Attica, Greece, serves as the test site of our geophysical investigation methodology. The planning of the geophysical survey included three phases: The application of frequency-domain electromagnetic (FDEM) and 3D ground penetrating radar (GPR) methods followed by a 3D electrical resistivity tomography (ERT) survey and finally, using the seismic refraction tomography (SRT) and multichannel analysis of surface waves (MASW). The FDEM method confirmed the geomorphological study findings by revealing the paleo-coastline, superficial layers of coarse material deposits and sea water preferential flow due to the presence of anthropogenic buried features. Subsequently, the 3D GPR survey was able to offer greater detail in detecting the remains of an old marble pier inland and top layer relief of coarse material deposits. The 3D ERT measurements, deployed in a U-shaped grid, successfully identified the anthropogenic feature, mapped sea water intrusion, and revealed possible impermeable formation connected to the bedrock. ERT results cannot clearly discriminate between limestone or deposits, as sea water intrusion lowers resistivity values in both formations. Finally, SRT, in combination with MASW, clearly resolves this dilemma identifying the lithostratigraphy and bedrock top relief. The findings provide critical input for engineering decisions related to foundation planning, construction feasibility, and preservation of coastal infrastructure. The methodology supports risk-informed design and sustainable development in areas with both natural and cultural heritage sensitivity. The applied approach aims to provide a complete information package to the modern engineer when faced with specific challenges in coastal settings. Full article