Search Results (188)

Fibrous organic soils are widespread and associated with long-term settlement of transportation infrastructure owing to their low bearing capacity, high compressibility, and pronounced creep, particularly in seasonally frozen regions. Undisturbed samples with fiber contents of 21%, 34%, 48%, 59%, and 73% from Northeast China underwent one-dimensional consolidation creep tests under consolidation pressures of 12.5–400 kPa. Results showed that higher-fiber-content groups exhibited larger axial strains under the same pressure. At 400 kPa, the final axial strain increased from 48.35% for the 21% fiber-content group to 61.98% for the 73% group. The coefficient of consolidation decreased rapidly as pressure increased and stabilized at 100–200 kPa, consistent with progressive compression and restricted drainage. The secondary compression index ranged from 0.022 to 0.064, generally increased with fiber content, and peaked at 50–100 kPa. Based on the ternary viscoelastic rheological (TVR) model, a finite-deformation TVR (FD-TVR) model was developed by introducing logarithmic strain and evolving drainage geometry while retaining the spring-Kelvin structure. Relationships between the model parameters, fiber content, and consolidation pressure were established, and FD-TVR predictions showed good agreement with the measured settlement curves. These findings may support settlement assessment and durable subgrade design, with implications for reduced maintenance and resource use. Full article

Urban-forest monitoring increasingly requires intelligent sensor-driven systems capable of characterizing short-term tree responses while operating efficiently within Internet of Things (IoT) and edge-computing environments. This study proposes a fusion-based artificial intelligence framework that integrates Quantization-Aware Training (QAT)-optimized PointNet++ models with machine-learning regression to predict a short-term dendrometer-derived stem-diameter response expressed in biomass-equivalent units. The framework combines 1024-point LiDAR tree representations, geometric measurements, and environmental sensor data through three components: QAT-optimized PointNet++ models for 34-species classification and trunk–crown part segmentation, frozen model-based prediction and geometric feature extraction, and MLP and XGBoost regression models for prediction of the short-term target. The dataset contained 2694 trees from five regions of South Korea, with the target derived from dendrometer-based stem-diameter measurements recorded over a 14-day interval between 8 September 2022 and 22 September 2022. Importantly, this short-term signal reflects both structural and reversible water-status-related stem dynamics and is therefore not interpreted as direct dry-biomass accumulation or carbon sequestration. The QAT-optimized models retained 92.52% segmentation accuracy (82.67% mIoU) and 80.46% species-classification accuracy, while the regression model reached R² = 0.9663 and RMSE = 0.4437 kg for the defined biomass-equivalent target. Quantization reduced the saved model size of both encoders by approximately 10.5× (21 MB → 2 MB) and accelerated CPU inference by up to 4.1×. These efficiency measurements were obtained on an ×86 desktop CPU and therefore characterize computational compression benefits rather than completed deployment or field validation on a low-power embedded device. These results demonstrate the computational feasibility of combining compressed point-cloud perception with multimodal prediction of short-term dendrometer-derived stem dynamics. Validation over seasonal and multi-year periods using independent biomass-reference measurements would be required before extending the framework to long-term biomass accumulation or carbon-sequestration assessment. Full article

To elucidate the recharge relationships and hydrological processes among different water bodies in the Qinghai Lake Basin, precipitation, river water, groundwater, and lake water samples were collected from April to November 2024. The hydrogen and oxygen stable isotope compositions (δ²H and δ¹⁸O) were determined to characterize their spatiotemporal variations, and the MixSIAR model was applied to quantitatively evaluate the recharge contributions among different water bodies. The results show significant differences in stable isotope compositions among the various water bodies. Overall, lake water exhibited the most enriched isotopic signatures, whereas groundwater was the most depleted and isotopically stable, while precipitation displayed the largest variability. Precipitation isotopes exhibited pronounced seasonal effects. River water showed a depletion–enrichment–depletion pattern, reflecting the important recharge contributions from wet season precipitation and frozen-soil meltwater. Groundwater exhibited relatively weak seasonal variations and a distinct smoothing effect. In contrast, the isotopic composition of lake water was jointly controlled by evaporative fractionation and multiple recharge sources, with the highest enrichment occurring in spring and gradual depletion during wet season and dry season. Spatially, significant isotopic differences were observed among rivers. Groundwater was relatively enriched in the western part of the basin and depleted in the eastern part, whereas lake water exhibited an opposite pattern, characterized by enrichment in the east and depletion in the west. The Local Meteoric Water Line (LMWL) of the Qinghai Lake Basin was defined as δ²H = 8.07δ¹⁸O + 37.48 (R² = 0.96). Both the slope and intercept were higher than those of the Global Meteoric Water Line (GMWL), indicating that locally recycled evaporated moisture played an important role in regional precipitation formation. The river water line showed characteristics similar to those of the groundwater line, suggesting strong hydraulic connectivity between river water and groundwater. In contrast, the lake water line deviated markedly from the meteoric water line, indicating significant evaporative fractionation of lake water. The MixSIAR results indicate that the contributions of river water, groundwater, and precipitation to lake water were 37.5%, 33.9%, and 28.6%, respectively. These findings reveal the complex hydrological connections and transformation processes among multiple water bodies in the Qinghai Lake Basin and provide a scientific basis for water resource management and ecological environmental protection in inland basins of the Qinghai–Tibet Plateau. Full article

Dispersive soils are widely distributed in the seasonally frozen regions of northeastern China, where hydrothermal dynamics driven by seasonal freeze–thaw (FT) cycles dominate the hydrological evolution and mechanical deterioration of soil masses, posing a serious threat to the long-term stability of hydraulic engineering in cold regions. However, the hydro–thermo–mechanical (HTM) coupled degradation mechanisms of dispersive clay from the South Nenjiang Main Canal remain poorly understood, particularly the linkage between FT-induced microstructural evolution and macroscopic mechanical behavior. In this study, low-plasticity dispersive clay specimens were subjected to 0–12 FT cycles. Unconsolidated undrained (UU) triaxial tests were conducted to evaluate mechanical behavior, while scanning electron microscopy (SEM) combined with the Pore and Crack Analysis System (PCAS) was used to quantify microstructural evolution. Results indicated that increasing FT cycles transformed the stress–strain response from mild strain-softening to strain-hardening, with the failure mode evolving toward bulging-type ductile failure. Cohesion exhibited a pronounced exponential decay, with the most significant degradation occurring within the first three FT cycles and stabilizing after approximately six FT cycles, whereas the internal friction angle showed only minor variation. At the microscale, porosity and total pore area increased continuously through micropore coalescence and macropore development, with a slight decrease in fractal dimension indicating reduced pore boundary complexity and smoothed pore interfaces due to frost heave-induced pore merging. The FT-induced hydrothermal disturbance promoted pore-water phase transition and redistribution, resulting in progressive pore enlargement and loss of structural integrity. Because the specimens were tested in sealed, closed-system conditions with a nearly constant total water content, this degradation chain is attributable specifically to in situ ice–water phase transitions and internal pore-water redistribution, i.e., water-phase-change-driven processes, rather than to external water supply. It is demonstrated that interparticle bond breakage and pore expansion–coalescence driven by ice–water phase transitions dominate strength degradation, promoting a transition from structure-dominated to friction-dominated strength behavior. A normalized cohesion reduction factor and a cohesion degradation index are further proposed to quantify the progressive loss of structural integrity and to provide a design-oriented tool for cold-region geotechnical practice. These findings provide a basis for stability assessment and hazard mitigation of dispersive soils in cold-region engineering. Full article

Frost heave in seasonally frozen loess regions is fundamentally governed by pore water migration towards the freezing front driven by temperature gradients, forming ice lenses that damage engineered infrastructure. Because both freezing intensity and moisture availability evolve with climate, frost heave susceptibility is itself dynamic, yet existing assessments remain static and ignore future climate trajectories. This paper presents a physics-constrained machine learning framework that couples soil freezing characteristic curve (SFCC) prior knowledge with multi-source open data and CMIP6 climate projections to achieve dynamic frost heave susceptibility mapping for the Loess Plateau. Monotonicity constraints derived from the coupled phase-transition and cryosuction mechanisms described by the SFCC and the segregation potential theory are enforced during gradient-boosted tree training, ensuring that predictions respect the established relationships among freezing intensity, fine-grained content and ice segregation potential. An ordinal decomposition strategy is adopted to guarantee that the monotonicity constraint on each binary sub-model translates into monotonicity of the predicted ordinal susceptibility level. The best performer, physics-constrained XGBoost, reaches an overall accuracy of 88.7% and an AUC of 0.942 on a four-class susceptibility scheme. Independent validation against 156 field records and Sentinel-1 InSAR observations confirms that the model captures genuine frost heave patterns. Under SSP5-8.5, the area classified as high or very-high susceptibility contracts by approximately 38% by the 2080s owing to warming, while under SSP1-2.6 the reduction is only 12%, and transitional zones of moderate risk expand in both scenarios. These findings provide a temporally explicit and physically grounded basis for climate-adaptive infrastructure planning in cold loess regions. Full article

Cold recycled mixtures with bitumen emulsion (CRME) serving in seasonally frozen regions are susceptible to mechanical deterioration under repeated freeze-thaw (F-T) cycles, which is primarily manifested as interfacial damage and crack propagation. However, the micro-mechanical processes associated with the transmission and dissipation of frost-heaving stresses induced by water-ice phase transition within the interfacial transition zone (ITZ) between reclaimed asphalt pavement (RAP) and asphalt mortar remain to be further characterized. In this study, a numerical simulation approach coupling frost heave effects with the phase transition of water-ice particles was developed based on X-ray computed tomography (CT) and the discrete element method (DEM), and the micro-mechanical parameters of the RAP-asphalt mortar ITZ were determined through laboratory experiments. Combined with acoustic emission (AE) monitoring, the damage evolution characteristics of cold recycled mixtures and the associated interfacial damage mechanisms under freeze-thaw action were systematically investigated. The results indicate that the optimal micro-parameters of the RAP-asphalt mortar ITZ can be taken as approximately 85% of those of virgin asphalt mortar. After 20 freeze-thaw cycles, the number of shear cracks and tensile cracks in ITZ on RAP surface reached 493 and 92, respectively, which were much higher than 11 and five on the surface of new aggregate. ITZ was the main control weak area of freeze-thaw damage. Compared with the unfrozen specimens, the minimum effective contact number of mortar decreased by 1.63%, 4.52% and 8.52% respectively after 5, 10 and 20 freeze-thaw cycles, and the total effective contact number decreased from 75,842 to 69,383. Freeze-thaw cycles significantly reduce the strain energy storage capacity of CRME: the maximum energy storage capacity of the adhesive spring decreased from 2.15 J in the non-freeze-thaw state to 1.28 J in 10 cycles (a decrease of 40.47%) and 1.16 J in 20 cycles (a decrease of 46.05%), and the damage mode changed from brittle fracture to interface-controlled energy dissipation. The proposed water-ice phase transition-based DEM framework provides a reliable numerical tool for investigating freeze-thaw damage mechanisms and supporting durability-oriented design of cold recycled pavement materials. Full article

Soil moisture is critical to the ecological stability and hydrological cycle. Optical remote sensing is severely constrained by cloud cover, snow, and frozen soil in alpine regions, hindering long-term soil moisture monitoring. Taking Nagqu region in the Tibetan Plateau as the study area, this paper constructs a pure microwave soil moisture inversion framework based on multi-temporal Sentinel-1 SAR data to avoid optical data dependence. Four SAR vegetation indices (DpRVI, RVI, DpSVI and PRVIc) were integrated into the coupled WCM–Oh2004 model to dynamically correct vegetation attenuation and surface scattering. The results show that the DpRVI-based model performs best, with R = 0.85 and RMSE = 0.0709 cm³/cm³, outperforming other indices. The framework maintains stable accuracy in the growing season and effectively captures spatiotemporal soil moisture variations. The proposed SAR-only method agrees well with official downscaled soil moisture products, proving its applicability for continuous soil moisture monitoring in optically inaccessible alpine regions. Full article

This study investigates the automatic classification of crop phenological stages from low-altitude UAV RGB imagery. The dataset included 11,489 images of five crops: sunflower, rapeseed, soybean, wheat, and barley. The images were annotated using the Biologische Bundesanstalt, Bundessortenamt und Chemische Industrie (BBCH) scale, with labels corresponding to either single stages or stage ranges to reflect heterogeneous field conditions and transitional crop states. A pretrained ResNet18 model was adapted to the task using transfer learning. Training was conducted in two stages: first, the classification head was optimized while the backbone remained frozen; second, the entire network was fine-tuned. The model achieved strong internal test accuracy across all crops, with 100% test accuracy for rapeseed and barley, more than 99% for the remaining crops, and a mean accuracy of 99.73% under the studied survey conditions. The results also compare favorably with previously reported studies on UAV-based phenological classification. Overall, the findings support the potential of low-altitude UAV imagery and deep learning for localized phenological assessment of selected field zones in precision agriculture, while broader deployment requires validation across independent fields, seasons, regions, and survey conditions. Full article

Freeze–thaw cycling can strongly disturb the pore-water environment, soil fabric, and contaminant mobility of heavy-metal-contaminated loess, thereby threatening the long-term effectiveness of stabilization treatments in seasonally frozen regions. This study investigated the coupled hydro-environmental and geotechnical performance of Pb-contaminated loess (untreated control group, CK) treated with microbially induced calcium carbonate precipitation (MICP), graphene (GR)-assisted MICP, and graphene oxide (GO)-assisted MICP under controlled freeze–thaw cycles. One-dimensional consolidation tests, toxicity characteristic leaching procedure (TCLP) tests, zeta-potential measurements, X-ray fluorescence (XRF), and scanning electron microscopy (SEM) were conducted to evaluate compressibility evolution, Pb leaching behavior, interfacial electrochemical characteristics, mineralogical changes, and microstructural mechanisms. After 9 days of mineralization, MICP reduced the Pb leaching concentration from 38.05 to 23.00 mg L⁻¹, achieving a 39.55% reduction compared with untreated Pb-contaminated loess. Freeze–thaw cycling increased the susceptibility of treated loess to structural degradation and pore collapse, especially under medium to high vertical stresses. Nevertheless, the void ratio generally followed the order of CK > MICP > MICP + GR > MICP + GO under comparable loading and freeze–thaw conditions, indicating progressively enhanced resistance to compressive deformation. GR-assisted MICP showed an optimum dosage of approximately 1.0%, beyond which Pb leaching increased because of sheet restacking, agglomeration, and non-uniform biomineralization. In contrast, under up to 13 freeze–thaw cycles, GO-assisted MICP maintained the lowest void ratio and the most stable Pb immobilization performance among all treatments, demonstrating improved resistance against freeze–thaw-induced structural degradation. The results suggest that GO-assisted MICP can simultaneously improve Pb leaching control and soil-fabric stability, providing a promising low-carbon strategy for remediating heavy-metal-contaminated loess exposed to water-mediated freeze–thaw disturbance. Full article

Quantifying the soil moisture (SM) response to precipitation is pivotal for predicting hydrologic resilience and ecosystem stability in fragile cold regions. This is true in alpine permafrost environments characterized by variable precipitation phases and strong seasonal freeze–thaw dynamics. However, critical knowledge gaps persist due to the scarcity of high-resolution, multi-layer in situ observations in these remote areas. Using hourly data from three sites in the Tanggula Mountains (2020–2024), this study employs an event-based analytical framework combining logistic regression and linear regression to quantify multi-layer (10–100 cm) SM responses to rain, snow, and mixed-phase precipitation across seasons. Core findings indicate the following: (1) Precipitation thresholds with 80% probability of triggering SM responses rise sharply with depth during the cold period (10 cm: 1–11 mm; 50–100 cm: often >15 mm or unreachable) but increase gradually in the warm period (10 cm: 0.4–5 mm; 50 cm: <15 mm). Mixed-phase precipitation refers to the lowest amount of precipitation (0.4–2.5 mm at 10 cm), followed by rain (1–11 mm) and snow (2–5 mm). (2) Warm-period regression slopes are consistently steeper than cold-period slopes (at 10 cm, 0.0024 vs. 0.0010 for rainfall). Mixed-phase precipitation yields the steepest slopes, approximately 50% higher than rainfall at 10 cm in the warm period (0.0037 vs. 0.0024), due to its longer duration and dual-supply mode. For lag time, cold-period values are more widely dispersed due to multiple interacting factors, while warm-period values are concentrated; only warm-period rainfall exhibits a clear monotonic increase in lag time with depth, consistent with unsaturated flow theory. (3) The quantified regression slopes, threshold values, and phase-specific efficiencies provide transferable metrics for calibrating infiltration models and evaluating frozen-ground hydrology schemes. The finding that mixed-phase events are the primary driver of deep-layer recharge, despite accounting for a smaller fraction of the total event count, has direct implications for water resource assessment in high-altitude catchments where precipitation phase composition is often oversimplified. Overall, this study moves beyond qualitative descriptions by providing quantifiable, transferable metrics that advance the mechanistic understanding of precipitation–SM coupling in alpine permafrost regions. Full article

The prediction of shear strength in seasonally frozen silty clay is restricted by complex physical mechanisms and sparse experimental data. A self-supervised contrastive physics-informed neural network is proposed to overcome these limitations. Robust latent features are extracted from limited datasets via contrastive pretraining. Time-dependent constitutive equations and physical boundary conditions are simultaneously embedded into the loss function. This mathematical constraint ensures strict physical consistency during the modeling process. The proposed framework was validated using 100 independent laboratory samples prepared under controlled moisture content, freezing temperature, and thawing duration. The experimental results demonstrate the superior predictive accuracy of the proposed model. A coefficient of determination ($R^2$) of 0.988 was achieved on the test set, accompanied by minimized error metrics compared to conventional data-driven approaches. Consequently, a highly accurate and reliable methodology is established by this architecture for evaluating soil stability and supporting infrastructure design in cold regions. Full article

Loess in seasonally frozen regions is prone to water-induced softening and dynamic instability, posing severe challenges for geotechnical engineering. Rubber particles, as sustainable waste-tire-derived material, offer potential for loess improvement. This study aims to elucidate the dynamic characteristics and modulus attenuation evolution of rubber particle–loess mixtures under multi-factor coupling effects. Dynamic triaxial tests were conducted to investigate the influences of rubber content, particle size, moisture content, and freeze–thaw cycles. Results reveal that the optimal mix is 5% rubber content with 40-mesh rubber particles, which yields the highest dynamic strength (i.e., the maximum dynamic stress that can be sustained before failure). The dynamic constitutive relationship follows the Hardin–Drnevich hyperbolic model. Increased moisture content and more freeze–thaw cycles reduce the maximum dynamic elastic modulus and strain, while higher confining pressure enhances them. A dynamic elastic modulus attenuation model was established to characterize strain-softening behavior. These findings clarify the dynamic response mechanisms of modified loess, providing a theoretical basis for its engineering application in seasonally frozen regions. Full article

The extreme environment characterized by repeated freeze–thaw cycles poses a severe challenge to the stability and durability of loess in engineering applications. This study systematically investigates the improvement of Weinan loess using a plant-based bio-cement (BC) combined with fly ash (FA) under extreme freeze–thaw environments. Through unconfined compressive strength tests, permeability tests, calcium carbonate content measurements, and microscopic analyses (SEM and XRD), the mechanical properties, microstructural evolution, and crack development characteristics of the improved loess were comprehensively evaluated. The results demonstrate that BC-FA modification significantly enhances the mechanical strength and impermeability of loess. The unconfined compressive strength of the 7% FA-amended specimen increased by 201.6% compared to untreated loess, while the permeability coefficient decreased by 61.58%. Freeze–thaw-induced deterioration predominantly occurred within the first five cycles, with a maximum peak strength reduction of 33.29%, after which the soil structure gradually stabilized beyond ten cycles. Microscopic observations revealed that biomineralized calcium carbonate crystals (calcite, aragonite, and vaterite) filled pores and bridged soil particles, forming a continuous cementation network. Furthermore, a novel Crack Identification Method Based on Multi-Feature Mechanical Responses (CIMBMFMR) was proposed, which establishes a quantitative mapping between mechanical degradation, micro-damage, and crack evolution, offering superior accuracy and physical interpretability over traditional image-based techniques. The BC-FA system exhibits notable low-carbon and eco-friendly advantages, providing a promising green solution for loess reinforcement in seasonally frozen regions. Full article

Climate warming is accelerating permafrost degradation in alpine regions, promoting the development of thaw-related slope deformation through active-layer thickening, ground-ice thaw, and hydro-mechanical weakening. Permafrost degradation margins are particularly sensitive to climatic warming, where enhanced heat transfer and active-layer water migration can accelerate shallow slope instability; however, the underlying mechanisms require further investigation. This study investigates two representative freeze–thaw-related landslides in the western Qilian Mountains: an active-layer detachment developed in degraded discontinuous permafrost and a freeze–thaw-induced shallow creep landslide located near the lower limit of permafrost occurrence. UAV photogrammetry, electrical resistivity tomography, and SBAS InSAR were integrated to characterize geomorphic features, internal frozen ground conditions, and deformation patterns. The active-layer detachment shows strong subsurface heterogeneity, with residual high-resistivity frozen bodies separated by localized thawed zones. Its deformation is mainly concentrated in the upslope detachment zone and central depletion–transport zone, where meadow-mat cracking, turf stripping, and exposed mineral soil coincide with thawed corridors between discontinuous permafrost bodies. In contrast, the freeze–thaw-induced shallow creep landslide exhibits the largest deformation in the upper permafrost-margin sector, where weakly discontinuous permafrost persists, whereas deformation decreases downslope in the seasonally frozen ground sector. This study highlights the critical role of discontinuous permafrost, localized thawing, and active-layer water migration in promoting shallow slope deformation and suggests that permafrost degradation margins may become increasingly susceptible to freeze–thaw-induced landslide activity under continued climate warming. Full article

The Tibetan Plateau sustains major Asian rivers through extensive cryospheric resources. However, hydrological associations of frozen ground degradation on downstream water availability remain insufficiently quantified. This study presents a preliminary assessment of thermal dynamics of frozen ground in the Yangtze–Yellow River source regions and their hydrological associations with the western Sichuan basins during 1961–2017. Using the near-surface ground freezing index (GFI) as a proxy indicator, we quantified contrasting streamflow responses between the Yangtze River source region (YaSR) and Yellow River source region (YeSR), and their connections with four major rivers in the western Sichuan basins. Results reveal divergent streamflow responses across four rivers, with predominantly positive anomalies despite widespread precipitation decline since the 2000s. As a permafrost-dominated basin, the YaSR exhibits enhanced streamflow generation, with contributions increasing from 6.63% to 31.31% as degradation intensifies. Conversely, the YeSR, mainly occupied by seasonally frozen ground, shows immediate streamflow attenuation that diminishes from 65.71% to 13.86% as degradation advances. The YaSR exhibits statistically significant positive associations with Jinsha and Yalong streamflows, while the YeSR develops significant statistical associations with Min River variability despite limited physical connectivity. These findings highlight the importance of frozen ground dynamics in regional water resource assessments under continued climate change. Full article