Permafrost creep is manifested by the presence of rock glaciers in mountainous areas, which are climatically driven landforms. Under degrading permafrost conditions, these ice-rich bodies tend to slow down until deactivation through a transition phase. However, the ongoing processes and their associated geomorphic responses remain are still poorly understood. This study aims to better understand the relationship between their activity, topo-climate conditions, and associated geomorphic responses of transitional rock glaciers. The activity of 520 landforms in the French Alps was assessed through Differential Interferometry Single Aperture Radar (DInSAR). Kinematic attributes were then correlated with topo-climatic and geomorphic characteristics using statistical exploration (Multiple Correspondence Analysis, MCA) and modelling (Multinomial/Binomial Logistic Regression, MLR/BLR). Results show that 71% of rock glaciers are stabilized or slow-moving landforms, while 23% exhibit surface velocities greater than 10 cm/year. Both MCA and MLR/BLR highlight that fast-moving rock glaciers are strongly correlated with higher latitudes, high elevations, steep slopes and convex morphologies, in contrast to slow-moving rock glaciers. MLR analysis revealed further differences between slow and fast classes. Rock glaciers with velocities <1 cm/year and 1-10 cm/year are located at lower latitudes and elevations, and in regions with unfavourable permafrost conditions. However, the <1 cm/year class is still found on steep slopes, suggesting that these landforms may not contain enough ice to maintain permafrost creep. Rock glaciers with velocities between 1 and 10 cm/year are more likely on smoother slopes, but they also show high occurrence probabilities at high elevations, indicating dynamic deactivation processes. Finally, the 10-30 cm/year class is slightly more probable under unfavourable permafrost conditions, which may suggest ongoing climatic deactivation. High-speed ranges were also associated with heterogeneous and small-moving areas within rock glacier systems, suggesting the presence of restricted permafrost conditions within a deactivating system. This finding raises important questions about spatial transitions and the temporal evolution of such kinematic behaviour.
Landslide activity in the Qilian Mountains is increasing due to permafrost thawing driven by global warming, where also developed numerous reverse strike-slip active faults with frequent and high-intensity earthquakes. While many studies have examined the influence of climate change on landslide activity in permafrost regions, the role of earthquakes in modulating landslide behaviour in such environments remains less well quantified. In this study, Interferometric Synthetic Aperture Radar (InSAR) was employed to investigate whether the 2022 Menyuan earthquake induced post-seismic acceleration of landslides in permafrost areas. The results show that the earthquakes exerted a pronounced impact on landslide deformation, producing an instantaneous subsidence of approximately 24.83 mm, which is substantially larger than the maximum annual displacement observed before the event. Moreover, post-seismic landslide velocities increased by up to 21 mm/year, and the seasonal deformation amplitude after the earthquake was approximately twice that observed during the pre-seismic period. To further elucidate the mechanisms underlying these responses, we quantified the dominant controlling factors of landslide deformation using a Geographic Detector approach. The results indicate that landslides located closer to active faults exhibit larger displacement rates, although no clear hanging-wall or footwall effect was observed. Landslides at higher elevations, particularly above 3,450 m, are more susceptible to deformation. Importantly, we find that landslides under colder ground temperature conditions are more strongly affected by seismic shaking and tend to exhibit larger post-seismic deformation, with a 0.2 degrees C decrease in ground temperature corresponding to an increase of approximately 5 mm/year in displacement rate. These findings provide new quantitative insights into the role of earthquakes in controlling landslide activity in permafrost regions and highlight the importance of permafrost thermal conditions in modulating post-seismic landslide behaviour.
Large wood (LW) entrainment and transport observations of naturally occurring wood in rivers are critical for understanding wood dynamics. However, they remain limited and sparse, primarily originating from single-site studies. As a result, broader spatial or temporal variability of wood dynamics may not be adequately captured. We compiled a database of tracked, natural pieces of wood from 11 low-order and relatively steep streams in the Chilean Andes, Swiss Alps, United Kingdom and United States. From decades to single-year studies, we gathered 59,739 observations of tracked wood, which all include at least a recorded length and transport distance. River characteristics varied according to channel width, less than 5 m to wider than 15 m, and gradient, between < 0.02 and > 0.04 m/m. The meta-analysis enabled us to calculate probabilities and identify general patterns. Wood mobilization varied significantly interannually, reflecting the complex interplay between flood events and wood storage. Overall, a small proportion of tagged wood moved during study periods, primarily during events associated with return periods exceeding 10 years. Most mobile pieces travelled less than 1 km, and longer distances had relatively low probabilities, typically occurring during high-magnitude flood events associated with return periods over 10 years. Results showed that large wood mobility in rivers is generally infrequent and highly variable, influenced by a combination of wood characteristics, river size and flood magnitude. Understanding variability can help inform risk-based flood hazard planning, river management and river restoration projects implementing large wood. Future studies should expand upon the current dataset.
The primary drivers of river morphology and dynamics are the hydrologic and sedimentologic regimes, but the wood regime is also important. Fallen wood will typically float at the water surface during floods, and the movement and deposition of large pieces can alter the trajectory of sedimentary bedforms, aquatic habitat, and flood hazards. Accurate quantification of floating wood in rivers is now possible, which is enabling us to better understand the role of this key variable, but frequency analysis is rare due to the relatively recent application of monitoring methods and a lack of standard analytical methods. The current study assembles the longest and most complete record of riverine wood transport yet available. Specific objectives are to (a) synthesize and validate a long time series of wood transport from available observations using a neural network model and (b) describe the probability of wood transport events at a river station. The wood record was assembled from manual observations of large wood in multiple flood events and an automated analysis of the full video record, which was estimated to have a precision of 85% and recall of 86%. The neural network predicted wood transport volume from climate and hydrologic records and was found to have Nash-Sutcliffe efficiencies of over 75%. Comparison of model predictions with wood-mobilization estimates from aerial photos were within 30% for 5-10 year periods and 2% for a 40-year period. The wood regime was characterized with (i) an assessment of seasonality; (ii) a rating curve of wood volume from event peak discharge; and (iii) an extreme event analysis of daily maximum and yearly wood transport volume. The methods are useful for characterizing a river's large wood transport regime and hindcasting historical wood mass transfer from flow records. This information will help to understand river dynamics and facilitate sustainable river management.
Rivers are fundamental water bodies supporting a wide range of ecosystem services. However, during the last century, river dynamics have been considerably modified by human engineering, notably channelized and dyked to prevent floods. In many Alpine rivers, this has led to the formation of a complex of alternate bars, gradually colonized by vegetation. Therefore, assessing spatial and temporal dynamics over large extents of these alternate bar systems represents a challenge to better understand the functioning of ecosystems in Alpine river and eventually to prevent flood risk. The three objectives of this study were 1) to create a database characterizing bars along a 30 km segment of the River Arc, in the French Alps, 2) to create a bar typology and to compare it to expert point of view, and 3) to assess the dynamics of the system after a 10-year return period flood event that occurred in June 2013. High-resolution LiDAR data and aerial photographs were used to localize major bed evolutions through a DEM of Difference (DoD), and to delineate and characterize gravel bars, including their volume, between two dates covering the flood event (in Sept. 2010 and Nov. 2013, respectively). Other river parameters such as sinuosity and river width were also calculated. A hierarchical clustering applied to the whole dataset revealed some bar morphological patterns, with three types of bars, depending in their functioning and age: large old vegetated bars with no mobility, very young, small and low elevated free bars without vegetation, and less mobile and more elongated bars, mostly corresponding to hybrid alternate bars. The results also highlight strong sediment dynamics resulting from the June 2013 flood. Bars were indeed statistically slightly thinner and shorter in 2013 than in 2010, corresponding to an enlargement of the main channel. Finally, these results proved the strong potential of remote sensing data-especially LiDAR data-to characterize sediment bars in channelized river over large extents.
Many estuaries worldwide face increasing sediment loading caused by catchment land use change and intensification, creating subsequent adverse effects on estuarine ecosystems. Extreme weather events can disproportionately alter sediment pathways and loading. Although storm-driven sediment exchange has been widely examined at open coasts and inlets, key transport mechanisms within constricted, sheltered estuaries remain understudied.This study presents an observational dataset capturing the impact of a 99th percentile water-level event (based on 20 years of records) on sediment transport pathways in a sheltered, barrier-enclosed estuary. This event, driven by a 3-day storm surge (>0.5 m) combined with a spring tide, was recorded during a 3-week field campaign.Sediment transport pathways and riverine contributions were analysed, and observations revealed substantial changes in suspended sediment concentrations increasing from 18 mg/l to 70 mg/l during the event. The elevated water levels and resulting pressure gradient at the constricted study site entrance caused by the storm surge increased local flood dominance. Combined with higher flow velocities and resuspension, the storm led to a sixfold increase in sediment import at the estuary entrance and a 600-fold increase in sediment flux to the upper estuary.The decoupling of peak suspended sediment concentrations from streamflow indicates that the resuspension of estuarine legacy sediment, rather than catchment inputs, dominated the system's response.These findings challenge assumptions about estuarine sediment budgets and emphasise that incorporating high water-level surge events into models can enhance the prediction of long-term estuarine evolution. Given projected increases in storm frequency under climate change, understanding these episodic but highly consequential sediment pulses can support the assessment of wetland resilience and inform estuarine management strategies.
The Tibetan Plateau, known as the 'Third Pole' of the Earth, has become a hotspot for landform classification studies due to its young tectonics, complex terrain and diverse landforms. Strong internal and external forces have shaped highly distinctive landscapes, posing significant challenges to landform classification. Previous studies mainly focused on landform morphology, whereas classifications that integrate morphology and genesis remain limited. Existing genetic classifications of the Plateau are based mainly on visual interpretation, hardly meeting the demand for large-scale automated landform classification. To address this issue, this study selected plains within the Tibetan Plateau as the study area and developed an automated classification method for plain genetic types by integrating multisource data. The results show that: (1) plains account for 25% of the Tibetan Plateau, with a mountain-to-plain ratio of about 3:1. (2) Fluvial and periglacial processes are the dominant external forces shaping the plains, with fluvial and periglacial plains comprising 51.73% and 26.07% of the total plain area, respectively, followed by lacustrine plains (10.55%), arid plains (7.55%), aeolian plains (3.21%) and loess plains (0.89%). (3) Accuracy evaluation results indicate that the classification accuracy for different genetic types of plains ranges from 75% to 91.89%, with an overall classification accuracy of 85.33%. Comparison with the 1:1 000 000 Geomorphological Atlas of China confirms that the overall distribution patterns are consistent, and the results of this study provide finer detail. The proposed hierarchical classification strategy and multisource data fusion framework provide a transferable approach for landform genetic classification in complex geomorphic regions.
Understanding floodplain wood transport, deposition and storage is necessary to fully close wood budgets in river corridors (the channel, floodplain and hyporheic zone). However, most work on wood in river corridors has focussed on in-channel wood. Here, we review current understanding of wood dynamics in floodplains using a floodplain wood budget to highlight the processes that change floodplain wood storage. We discuss autochthonous and hillslope recruitment to the floodplain, floodplain wood decay and burial/exhumation, controls on lateral wood fluxes between the floodplain and the channel, and fluvial wood transport within the floodplain itself. We compile wood load data for floodplains and channels in locations in which data on floodplain wood loads exist, finding that floodplains are an important storage location for wood within the river corridor across diverse environments. We briefly review the impacts of floodplain wood on physical and ecological processes and then summarise important knowledge gaps that limit understanding of floodplain wood dynamics. We emphasise that future research should address methods to determine wood piece source location and track wood within the river corridor; mechanistically explore coupled flow-sediment-vegetation-wood processes across spatial and temporal scales; extend observations of floodplain wood loads and storage characteristics and explore multiple size classes of organic matter; and work to inform management decisions related to floodplain wood. Because it may be less likely to be transported downstream and interact with infrastructure, floodplain wood may be less hazardous than in-channel wood but can still provide ecological benefits and enhance physical complexity. Improving our understanding of wood dynamics on floodplains is thus important for supporting river management.
Extreme precipitation events can rapidly reshape mountain landscapes, even in tectonically inactive regions like the Southern Appalachians. Here, we illustrate how discrete storm events drive rapid geomorphic change with a repeat-lidar analysis of impacts from Hurricane Helene (September 2024) in the Hickory Nut Gorge, North Carolina, USA. Airborne lidar collected before and after Helene reveals characteristic patterns of landslide initiation, sediment delivery, and river channel evolution. Our observations augment the current understanding of landslide reactivation, highlight debris flows as a key process of coarse sediment transport, and demonstrate how episodic flooding can reshape river channel geometry and roughness. Geomorphic signatures of extreme events quickly obscure as vegetation regrows and infrastructure is repaired, underscoring the need for both pre-event and rapid postevent lidar to detect and quantify change. Together, these insights clarify how infrequent, high-intensity storms drive both immediate landscape change and long-term geomorphic evolution in steep mountain terrain.
Shoreline erosion and coastal flooding are two major hazards causing significant losses of life and property in a warming climate. To enhance coastal resilience against climate change, this study offers an integrated assessment of long-term shoreline erosion (the combined shoreline retreats driven by ambient dynamics and sea level rise) and potential flooding risk (PFR, quantified by the annual cumulative exceedance hours of extreme sea levels) along China's sandy beaches. We further examine the concurrent coastal hazard (CCH) of shoreline erosion and PFR, and evaluate the associated exposure of physical assets and population. Our findings suggest that under the high emission scenario SSP5-8.5, China's sandy beaches are projected to experience intensified erosion and elevated PFRs, primarily attributable to rising mean sea levels. Moreover, shoreline erosion is proportionally more prevalent along the southern coasts. Coastlines projected to experience fewer PFR hours tend to exhibit higher severity, and vice versa. As a result, more than 65% of sandy shorelines are threatened by CCH, and over 80% of coastal physical assets and populations along sandy beaches are exposed to CCH. Among the cities in China's Greater Bay Area, Hong Kong and Shenzhen are projected to face the highest levels of exposure for both physical assets and population. This study identifies future hotspots of shoreline erosion and coastal flooding along China's sandy coastlines and provides scientific evidence to support adaptation strategies aimed at mitigating climate-induced coastal hazards.
Remnants of thick alluvial fills in Himalayan valleys and intermontane basins record past disruptions in sediment routing. However, the climatic drivers of these aggradational phases remain debated. Do they reflect enhanced hillslope sediment supply during intensified monsoon phases, or reduced fluvial transport capacity under drier conditions? To address this question, we analyze an 55-m-thick late Pleistocene alluvial fan succession deposited in the structurally confined Pinjore Basin of the Northwestern Himalaya, sourced from an 350-km(2) unglaciated catchment. Using optically stimulated luminescence dating and in situ Be-10 measurements from buried sediments, we reconstruct the timing of fan deposition and catchment-scale paleo-erosion rates to assess links between monsoon variability, sediment supply and fluvial transport capacity. Fan aggradation persisted for 39 kyr between 52 and 13 ka, coinciding with the prolonged weakening of the Indian Summer Monsoon. Low and relatively stable erosion rates throughout most of this interval suggest that aggradation was primarily driven by reduced runoff and limited fluvial transport capacity, rather than increased sediment supply. After 26 ka, declining sedimentation rates, sediment coarsening and lower inherited Be-10 concentrations may reflect reduced slope stability due to vegetation changes associated with glacial cooling. Renewed fan incision after 13 ka coincides with monsoon strengthening, indicating a shift toward increased transport capacity. These results highlight a climate-sensitive, threshold-controlled sediment-routing system in which changes in runoff and vegetation drive aggradation-incision cycles. The Pinjore Basin record underscores the potential for nonlinear fluvial responses to hydroclimatic variability in tectonically active mountain landscapes.
Floods are one of the most critical environmental threats in Central Europe. In Germany, they are responsible for more than half of the economic damage caused by environmental hazards. The magnitude of the 2021 Ahr flood has far exceeded what was forecast in previous flood hazard assessments. This was due to a significant underestimation of hazards, as the former hydrological models considered instrumental discharge records exclusively. Because the recording period only began in the second half of the 20th century, high-magnitude flood events prior to that period were not considered in flood hazard assessments. Historical flood events from written sources were also not included in official flood hazard assessments. In this study, we show the importance of geomorphological records from Ahr flood deposits for reconstructing past high-magnitude flood events. Our chemo- and lithostratigraphical analysis of four recovered cores from the Ahr floodplain shows that centennial- to millennial-scale high-energy flood deposits are not the exception but the rule. The four floodplain sediment cores record the catastrophic flood of 2021 and the two historical floods of 1804 and 1910, as well as a previously unidentified flood event dated approximately to the end of the 5th century A.D. In addition, the geomorphological analysis in combination with near-surface geophysical prospection shows that the Ahr floodplain is dominated by high-energy flood deposits and that low to medium-magnitude flood events are not preserved in the floodplain stratigraphy. The fluvial geomorphological record proves that the 2021 flood event is not an exception in the Ahr floodplain stratigraphy. In fact, at least three other flood events have been identified in the last 1,500 years that, based on lithostratigraphic parameters, had a comparable magnitude. The results document the high potential of floodplain archives for reconstructing high-magnitude flood events in Central European rivers, allowing a systematic reassessment in terms of the occurrence and frequency of high-magnitude flood events. The occurrence of the large floods in the Ahr valley does not show any clear coupling with the Central European hydroclimatic history. However, what is noticeable is that the historically documented high-magnitude Ahr floods occur during the summer season, which is in parallel with high atmospheric moisture loads.
Real-time monitoring and early warning systems for landslides are crucial for minimizing casualties and property losses. The tangential angle method, which assesses the deformation rate of the displacement-time curve at specific instances, has been successfully applied in some cases. However, this method often results in omissions, false alarms and frequent alerts due to its reliance on fixed time windows and single-point displacement measurements. Ground-Based Interferometric Synthetic Aperture Radar (GB-InSAR) is an advanced deformation monitoring technology offering high frequency and accuracy. Nonetheless, it currently lacks a quantitative early warning method that fully leverages surface scene information. To address these challenges, this paper proposes a hybrid intelligent early warning approach based on surface deformation monitoring, comprising a point-based early warning (PEW) method and an area-based early warning (AEW) method. The PEW method enhances the traditional tangential angle approach by adopting a self-adaptive time window, thereby reducing warning errors associated with fixed time intervals. The AEW method facilitates early warnings by detecting landslide expansion behaviours, effectively utilizing the extensive data from surface scene monitoring. The proposed early warning system was validated through a detailed case study of the Jianshan landslide monitored by GB-InSAR. The results demonstrate that both PEW and AEW methods perform effectively within their respective scopes, although each possesses certain information blind spots. The integrated method capitalizes on the strengths of both approaches while mitigating their individual limitations, thereby achieving more accurate and reliable early warnings.
Forest blowdown, or the widespread felling and snapping of trees due to high wind speeds, can substantially increase the amount of downed large wood (LW) on the landscape. Despite high recruitment potential, few studies have investigated the influence of blowdown on in‐channel LW volumes and the subsequent capacity for sediment and water storage. In June 2021, a frontal storm caused widespread blowdown across parts of southeastern Australia, creating an opportunity to better understand interactions between landscape morphology, blowdown intensity, large wood recruitment and in‐channel hydrogeomorphic changes. Blowdown area and density (trees per unit area) were mapped remotely across the Wombat State Forest (WSF), Victoria and paired with field‐based measurements of in‐channel LW and associated sediment and water storage in the Lerdederg River and tributaries. Study reaches were characterized by a range of hillslope gradients, aspects, blowdown intensity and channel and floodplain widths. Eleven percent of the treed area of the WSF was blown down by the June 2021 storm, with winds that exceeded 100 km/hr from a non‐typical direction. The blowdown event was the dominant source of in‐channel LW, delivering 88% of the volume. LW volumes were more strongly influenced by valley morphology, particularly valley bottom width, than blowdown characteristics (affected area or downed wood density). Most LW (85% by volume) accumulated in porous jams, and about 33% of LW stored sediment and/or water, with storage more likely behind pieces that touched the channel bed. Substantial amounts of LW still remained on the floodplain or spanned above the channel, suggesting that LW loads attributed to the June 2021 storm could continue to increase as overbank flows and wood decay continue to recruit wood into the active channel. Catastrophic blowdown like the June 2021 storm could exert significant control on the wood regime and morphology of forested, headwater channels, particularly as extreme wind events are expected to increase in magnitude and severity in the future.
Understanding and predicting bankfull stage is essential for geomorphic analysis, hydraulic modelling and river corridor management, especially regarding floods and connectivity. This study evaluates traditional geomorphic and hydrologic methods and introduces a machine learning (ML) approach to predict bankfull stage along the upper Apalachicola River, Florida, United States. First, we integrated LiDAR point cloud data with a 2010 hydrographic survey through a triangular irregular network (TIN) following coordinate transformation, producing a 1.5‐m resolution digital elevation model (DEM) that captures riverbed elevation. After extracting cross‐sections, we applied two geomorphic methods, Width‐to‐Depth Ratio (WDR) and Hydraulic Mean Depth (HMD), and three (1.1‐, 1.5‐, 2.0‐year) hydrologic return intervals to 344 cross‐sections to determine bankfull stage and assessed their agreement with visual and field‐verified bankfull elevations. A refined HMD method using shape ratio (Rs) and slope inflection corrections improved geomorphic estimates in 131 cross‐sections. Bankfull estimates based on return intervals exhibited substantially lower reliability relative to geomorphic methods, with associated confidence levels falling below 70%. This reduced performance is attributable to stage‐based spatial averaging and limited sensitivity to local topographic variability. By contrast, the geomorphic methods (WDR and HMD) achieved confidence levels exceeding 95%, underscoring their stronger agreement and robustness. To improve accuracy, we developed ML models: Random Forest (RF), Gradient Boosting (GB) and Ensemble model trained on cross‐sectional elevation profiles and engineered features such as cross‐sectional area, top width, maximum depth, symmetry, etc. The GB model outperformed all others ( R 2 = 0.94, MSE = 0.21), with feature importance analysis revealing that elevation at the top bank as well as channel area, top width and maximum depth dominated predictions. While this study advances the integration of ML into fluvial systems and provides a replicable framework for large rivers with limited hydrologic data, we recommend that multiple ML models be evaluated across individual reaches to account for the unique geomorphic and hydraulic characteristics of each river reach.
Desert pavements are a global phenomenon in arid environments, representing one of the most extensive geomorphological and geoecological features on Earth. To a large extent, they determine the interplay of key processes governing current and past landscape dynamics including landform evolution, surface runoff, soil water dynamics, weathering and soil formation, microbial processes, dust deposition and entrainment into the atmosphere. Hence, desert pavements and their future trajectories of change have a strong local to global impact on coupled Earth system components. However, knowledge of the comprehensive role that desert pavements play in the Earth surface–atmosphere system is still limited, and a profound interdisciplinary understanding of their evolution, spatial extent, microbiological processes, and inherent environmental feedback mechanisms is lacking. This article provides an overview of the current state of knowledge of desert pavements as an important Earth system component and offers an interdisciplinary perspective on the key processes interacting within desert pavements, which improves our understanding of the role and importance of desert pavements within the Earth system.
Excessive fine sediment (particles <2 mm) in riverbeds negatively impacts river ecology. Riverbed fine sediment measurements are therefore critical in research, monitoring and management seeking to protect, maintain or restore riverine ecosystems. However, there is no single, widely adopted method and limited evidence‐based guidance about how to choose between numerous available field techniques to achieve accurate, repeatable and consistent results. We therefore compared the intercorrelations of six commonly employed fine sediment methods across 29 sites (constituting 667 independent observations): the original resuspension method and two alternative turbidity derivatives (turbidity tube and turbidimeter), Wolman pebble counts, McNeil sampling and visual estimations at reach and patch scales. Performance evaluation focused on issues of practical significance, including comparisons of fines content between surface and subsurface measures, local substrate composition, spatial scale of application (reach and patch) and sample replication. Most methods yielded estimates of fines that were strongly correlated with each other, but these differed depending on local substrate composition, suggesting that different methods are better applied to certain substrate types. Differences between reach fine sediment estimates were typically larger as the proportion of fine sediment increased, whilst the converse was true for patch‐scale measures. On average, surface measures do not provide reliable information about subsurface fines content. We also found that an inexpensive, rapid version of the resuspension method utilising a turbidity tube performs as well as costlier alternatives, providing a valuable means of estimating fines in most riverine environments. The spatial scale of sampling (reach or patch) and the number of replications made a significant difference to the estimates obtained using visual observations. We make pragmatic recommendations, providing a significant step forward in standardising fine sediment measurement in riverbeds. Practitioners and researchers should select methods that suit local substrate conditions, while recognising that their choices will influence the results obtained.
We evaluate the effectiveness of Ground Penetrating Radar (GPR), soil granulometry and geomorphometric analysis in identifying shallow variations of sandy and clayey materials in a colluvial‐alluvial plain. In addition, 2D Electrical Resistivity Tomography (2D ERT) was used to provide complementary information about deeper subsurface features, beyond the resolution limit of GPR. Geophysical methods were combined with unmanned aerial vehicle (UAV) data and particle size analysis to achieve high‐resolution detections of sediment variations in a colluvial‐alluvial plain. A Digital Terrain Model (DTM) was derived from remote sensing data, providing topographic attributes. Two pieces of equipment were tested for acquiring GPR images: one with a 400 MHz antenna and another with dual frequencies of 250 and 700 MHz. However, GPR data were acquired using a 400 MHz antenna along 16 transects, as it provided the best balance between resolution and electromagnetic (EM) wave penetration depth. The ERT data were collected along a single profile using the dipole–dipole array. Soil cores were sampled at 0.20 m intervals to a depth of 1 m to validate the geophysical interpretations. GPR images showed two distinct patterns: one towards the footslope (West sector) and another towards the lowland (East sector). The topographic attribute LS Factor, with a maximum value of 1.55, on the footslope in the West sector, represents colluvial ramps. Mean TWI (> 10) directly related to mean MrVBF (>2) illustrates areas with higher sediment deposition and moisture accumulation in the East sector. Principal Component Analysis (PCA) and Spearman's correlation demonstrated that the depth of soil core samples is positively correlated with sand (r = 0.26) and negatively correlated with clay (r = −0.18). GPR images revealed variations in sediment composition (horizontal resolution) at depths of up to approximately 4 m (vertical resolution). The GPR efficiently mapped strong returning signals from sandy lenses and weaker signals from clay, highlighting its potential for areas with similar geomorphology. The real resistivity model revealed a resistive surface layer across the entire line, corresponding to massive migmatite gneiss. The inclusion of geomorphometric data in geophysical analyses contributes to interpreting interactions between surface morphology, soil texture and geophysical properties. Our results encourage further on‐site research to characterize materials in terms of colluvial and alluvial origins.
Boulder fields are low‐angle, open‐work clast accumulations and are among the most distinctive geomorphic expressions of long‐term periglacial processes. Although boulder fields are widely used as indicators of past periglacial environments, uncertainty remains regarding the specific climatic conditions and processes responsible for their formation. The Hickory Run Boulder Field (HRBF) in Carbon County, Pennsylvania (41°03′02” N, 75°38′44” W), located ~2 km south of the Last Glacial Maximum margin, is the largest and most striking feature of its kind in the eastern USA, covering approximately 6.5 ha. The dominant hypothesis suggests allochthonous formation, whereby frost wedging of scarp‐like bedrock source outcrops and slow downslope movement of weathered material over impermeable permafrost resulted in HRBF's development. However, direct quantitative analyses of this hypothesis remain sparse, and the geological history of HRBF is incompletely resolved. This study presents a sedimentological investigation evaluating the allochthonous hypothesis through a combination of relative weathering indices (clast volume, sphericity, flatness and rebound hardness) and clast macrofabric analysis. Field data were collected from 22 sites along two subparallel transects, including locations in both the major and minor boulder fields. Statistical analyses, including polynomial regression of relative weathering indices and eigenvalue‐based macrofabric assessments, reveal dynamic spatial trends in clast weathering and orientation. Results indicate systematic increases in clast weathering with distance from a local bedrock outcrop and non‐random macrofabric orientations consistent with mass movement. These findings confirm that HRBF represents a time‐transgressive surface formed under periglacial conditions, with flow‐like integration of clasts from bordering upslope areas. The study provides quantitative evidence supporting emplacement by periglacial mass movement, reinforcing the utility of HRBF in paleoclimatic reconstructions of the Appalachian Highlands.
This study developed a thermosensitive shear zone material composed of paraffin‐quartz sand‐clay composites. By constructing artificial shear zones with this material and selectively activating embedded electric heating plates to generate localized shear strength reduction, experimental simulations of both retrogressive and translational landslides are achieved. The results demonstrate that the mechanical parameters of this material exhibit temperature‐dependent degradation: cohesion ( c ) follows a negative exponential decay with temperature increase, while the internal friction angle ( φ ) decreases linearly. The thermally induced shear strength reduction progressively diminishes the anti‐sliding capacity of slip surfaces, ultimately triggering gravity‐driven landslide deformation and failure. During testing, tensile cracks initiated at the slope rear edge, with internal deformations dominated by extensional mechanisms. PIV displacement monitoring revealed steep displacement gradient transitions spatially coinciding with tensile crack development. For translational landslides, earth pressure variations in shallow, mid‐depth and deep zones displayed synchronized reduction patterns throughout deformation. In contrast, retrogressive landslides exhibited distinct phase differences in earth pressure evolution across depth zones, with the frontal slope's traction effect on the rear being substantially weaker than that of the central part. This research establishes an innovative methodology for simulating landslide disasters through controlled internal weakening of shear zones, which may provide new insights into failure mechanisms and prediction techniques driven by shear strength deterioration.
