Search Results (357)

This study introduces a novel methodology for assessing ice-jam flood hazards along river channels. It employs empirical equations that relate non-dimensional ice-jam stage to discharge, enabling the generation of an ensemble of longitudinal profiles of ice-jam backwater levels through Monte-Carlo simulations. These simulations produce non-exceedance probability profiles, which indicate the likelihood of various flood levels occurring due to ice jams. The flood levels associated with specific return periods were validated using historical gauge records. The empirical equations require input parameters such as channel width, slope, and thalweg elevation, which were obtained from bathymetric surveys. This approach is applied to assess ice-jam flood hazards by extrapolating data from a gauged reach at Fort Simpson to an ungauged reach at Jean Marie River along the Mackenzie River in Canada’s Northwest Territories. The analysis further suggests that climate change is likely to increase the severity of ice-jam flood hazards in both reaches by the end of the century. This methodology is applicable to other cold-region rivers in Canada and northern Europe, provided similar fluvial geomorphological and hydro-meteorological data are available, making it a valuable tool for ice-jam flood risk assessment in other ungauged areas. Full article

This study investigated the presence and distribution of macrolitter along four beach sites on the Ferrara coast, North-eastern Italy. At each site, monitoring campaigns were conducted from summer 2023 to summer 2024 to assess seasonal and cross-shore fluctuations of litter items and their relations with local geomorphological features. Following the Marine Strategy Framework Directive, 5627 litter items were collected, with an average density of 0.61 ± 0.23 items/m². Plastic was the dominant material, representing 94% of the total. The Clean Coast Index (CCI) was applied to evaluate beach cleanliness, seasonal patterns, and cross-shore litter distribution. Although the sites were generally classified as “Clean”, CCI values revealed a progressive decline in cleanliness from summer to spring. Litter was especially accumulated in the upper backshore and at the dune foot. All macrolitter items were classified by material, typology, and usage category to identify potential sources of release, following the Joint List of Litter Categories for Marine Macrolitter Monitoring. The “Top 10” of the most collected items was compiled per each site, season, and geomorphological zone. The results underscore the relevance of high-resolution monitoring programs to support the development of targeted management strategies for effective beach litter mitigation. Full article

The number of publications in the scientific literature dealing with geomorphological mapping has increased over the last two decades. Although geomorphological maps are utilised in various contexts, such as hazard assessment, archaeology, and tourism, there is a noticeable lack of interaction between geomorphological products and the social sciences. This study aims to provide a qualitative assessment of the literature on geomorphological maps published in the 2000s with the intent of identifying the purpose of mapping and its field of application. Additionally, a comparative analysis was conducted of the articles relating to both geomorphological maps and social issues to identify the tools that facilitate this interdisciplinary collaboration. The results facilitated the identification of the primary fields of interest for map production, showing that only a limited number of articles employed geomorphological maps for social purposes, for instance, enhancing risk awareness and educating the population about natural hazards. Moreover, the analysis reveals that only a limited number of geomorphological maps are intended to be accessible to people without a high degree of education in earth sciences. In particular, this study highlights a lack of attention to non-specialist users who may struggle to understand the information contained in geomorphological maps. This issue limits the dissemination of geomorphological maps, which are, however, vital for territorial planning and practical purposes. The analyses prompted the authors to consider novel applications of research tools to enhance the dissemination of geomorphological maps, even among non-specialist users. Full article

Active continental margins, generally characterized by narrow shelves incised by canyons, are pervasively shaped by submarine landslides that can occur near coastal areas. In this context, creating landslide susceptibility maps is the first step in landslide geohazard assessment. This paper focuses on shallow-water submarine landslides along the Capo d’Orlando continental margin and presents a related susceptibility map using the Weight of Evidence method. This method quantifies the strength of the association between a landslide inventory and predisposing factors. A geomorphological analysis of the continental shelf and upper slope yielded a landslide inventory of 450 initiation points, which were combined with five specifically selected preconditioning factors. The results revealed that the most favourable conditions for shallow-water landslides include slopes between 5° and 15°, proximity to faults (<1 km), proximity to river mouths (<2 km), the presence of consolidated lithologies and sandy terraces, and slopes facing NE and E. The landslide susceptibility map indicates that susceptible areas are in canyon heads and flanks, as well as in undisturbed slope portions near canyon heads where retrogressive landslides are likely. The model results are robust (AUC = 0.88), demonstrating that this method can be effectively applied in areas with limited geological data for preliminary susceptibility assessments. 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 Xixia Imperial Tombs (XITs) represent a crucial, yet still largely mysterious, component of the Tangut civilization’s legacy. Located in northwestern China, this extensive necropolis offers invaluable insights into the Tangut state, culture, and burial practices. This study employs an integrated approach utilizing multi-resolution and multi-temporal satellite remote sensing data, including Gaofen-2 (GF-2), Landsat-8 OLI, declassified GAMBIT imagery, and Google Earth, combined with deep learning techniques, to conduct a comprehensive archaeological investigation of the XITs’ burial landscape. We performed geomorphological analysis of the surrounding environment and automated identification and mapping of burial mounds and mausoleum features using YOLOv5, complemented by manual interpretation of very-high-resolution (VHR) satellite imagery. Spectral indices and image fusion techniques were applied to enhance the detection of archaeological features. Our findings demonstrated the efficacy of this combined methodology for archaeology prospect, providing valuable insights into the spatial layout, geomantic considerations, and preservation status of the XITs. Notably, the analysis of declassified GAMBIT imagery facilitated the identification of a suspected true location for the ninth imperial tomb (M9), a significant contribution to understanding Xixia history through remote sensing archaeology. This research provides a replicable framework for the detection and preservation of archaeological sites using readily available satellite data, underscoring the power of advanced remote sensing and machine learning in heritage studies. Full article

Impact cratering determined by collisions with meteorites and asteroids is considered one of the main natural processes in the Solar System, modifying the planets and their satellites surface during time. The Earth includes in its impact record a small number of such events due to active plate tectonics, sedimentation, and volcanism, with these geological processes destroying and burying their impact geomorphological signatures. To enlarge the Earth’s impacts database, new concepts and research methods are necessary, as well as the reinterpretation of old geological and geophysical models. Geomorphological, Geological, and Geophysical (3G) signatures in concealed impacted areas are discussed in this paper; the first offers the target characteristics, while the others give means for detecting their unseen remnants. The 3G signatures have been applied to the Transylvanian Depression, a fascinating geological structure, with difficulties in explaining the direct overlapping of regionally developed thick tuff and thick salt layers, and undecided interpretation of the regional magnetic anomaly. Large and deep sedimentary basins, such as the Precaspian, Alexandria and Transylvanian depressions, are interpreted to have started as impacted areas during the Permian or the Lower Neogene. Geophysical and geological existing information have been reinterpreted, offering a new way in understanding deeply located geological structures. Full article

Coastal wetlands play important environmental roles. However, their hydrogeomorphological dynamics remain poorly understood under scenarios of extreme climate events. The aim of this study was to characterize the temporal and spatial variability of hydrogeomorphological attributes (vegetation, water, and soil) in the wetlands of Lagoa do Peixe National Park, Brazil. The methodology involved applying Principal Component Analysis (PCA) in both temporal (T) and spatial (S) modes, decomposing spectral indices for each attribute to identify variability patterns. The results revealed that vegetation and water are strongly correlated with seasonal dynamics influenced by ENSO (El Niño/La Niña) events. Soils reflected their textural characteristics, with a distinct temporal response to the water balance. PCA proved to be a useful tool for synthesizing large volumes of multitemporal data and detecting dominant variability patterns. It highlighted the Lagoon Terraces and the Lagoon Fringe, where low slopes amplified hydrological variations. Temporal variability was more responsive to climate extremes, with implications for ecosystem conservation, while spatial variability was modulated by geomorphology. Full article

This study investigates the spatial distribution of transition metals—iron (Fe), titanium (Ti), and chromium (Cr)—within the Dryden crater on the Moon using hyperspectral data from the Moon Mineralogy Mapper (M³). By applying spectral parameters and false color composite techniques, geospatial maps of chromite distribution and FeO, TiO₂ wt.% distribution were generated at a resolution of ~140 m. The findings reveal distinct elemental enrichments along geomorphologically active regions such as crater walls, terraces, and central peaks, highlighting impact-driven material differentiation, the influence of morphology, degradation, and space weathering. These results enhance our understanding of lunar crustal evolution and support future exploration and resource utilization efforts. Full article

This article focuses on forecasting morphological changes in small rivers, using the Ulken Almaty River, located on the northern slope of the Ile Alatau range in the Tien Shan mountain system, as a case study. One of the key components of river morphology is the dynamics of channel processes, including erosion, accretion, and the shifting of channel forms. Understanding these processes in rivers flowing through urbanized areas is essential for mitigating environmental and infrastructural risks. Despite their importance, studies of this nature in Kazakhstan remain at a formative stage and are largely fragmentary, underscoring the need for modern approaches to river morphology analysis. Three representative sections of the Ulken Almaty River (upstream, midstream, and downstream) were selected for analysis. Satellite imagery from 2012 to 2021 was used for manual digitisation of river channel outlines. Annual erosion and accretion areas were calculated based on these data. The DSAS 5.1 module, integrated into ArcGIS 10.8.1, was applied to determine the rates of erosion and accretion over the ten-year period. To forecast future channel changes, the Kalman filter model was employed, enabling projections for 10 and 20 years into the future. A comparative analysis of the intensity of the erosion and accretion processes was conducted for each river section. Spatial and temporal variations in bank dynamics were identified, with the most significant changes occurring in the middle and lower reaches. Forecasted scenarios indicate the possible deformation pathways of the river channel influenced by both natural and anthropogenic factors. The results provide valuable insights into the spatiotemporal dynamics of fluvial processes in small mountain rivers under the pressure of urban development and climatic variability. The methodology employed in this study offers practical applications for urban planning, river management, and the mitigation of geomorphological hazards. 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

Geoarchaeological work and excavations of the Helike Project over the last 30 years in the Helike coastal plain, Gulf of Corinth, have yielded abundant evidence on ancient settlements, as well as the surrounding landscape and environmental changes that resulted from geological phenomena and catastrophic events. The research methods applied by the Helike Project followed a multidisciplinary approach, including combined archaeological excavations and palaeoseismological trenching, geophysical prospection, archaeometric, environmental, and soil micromorphology analyses, and computer-based landscape modelling. A wealth of settlement remains that were unearthed across the plain, ranging in date from the Early Helladic period (3rd millennium BC) to the Late Antiquity (5th century AD), indicates that the ancient inhabitants of the area chose to always resettle in the area by adjusting their ways of living to the geomorphology and natural hazards, prevailing each time. Our results show that disasters in the area increased between the Geometric and Roman times due to severe earthquakes that occurred approximately every 300 years. In particular, archaeological and geological finds recovered from the Late Classical–Hellenistic Helike settlement, which was revived in the western part of the plain shortly after the disastrous 373 BC earthquake, have enriched our knowledge regarding the historical seismicity of the region and past human–environment relationships. 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