Search Results (955)

Cement–Soil Mixing (CSM) Pile is an important technology for soft ground reinforcement, and its as-formed compressive strength directly affects engineering design and construction quality. To address the significant discrepancy between laboratory-tested strength and field as-formed strength arising from differing environmental conditions, this study conducted modified laboratory experiments simulating key field formation characteristics. A cement–soil preparation system considering actual immersion conditions was established, based on controlling the initial water content state of the foundation soil before pile formation and applying submerged conditions post-formation. Utilizing data mining on 84 sets of experimental data with various preparation parameter combinations, a prediction model for the as-formed strength of CSM Pile was developed based on the Particle Swarm Optimization-Extreme Gradient Boosting (PSO-XGBoost) algorithm. Engineering validation demonstrated that the model achieved an RMSE of 0.138, an MAE of 0.112, and an R² of 0.961. It effectively addresses the issue of large prediction deviations caused by insufficient environmental simulation in traditional mix proportion tests. The research findings establish a quantitative relationship between as-formed strength and preparation parameters, providing an effective experimental improvement and strength prediction method for the engineering design of CSM Pile. Full article

China’s Loess Plateau is characterized by dense and widely distributed check dams. However, there has been a lack of large-scale and high-temporal-resolution monitoring for the water-filled status of check dams, which is strongly related to their safe operation. In this study, a deep learning-based remote sensing image interpretation technique was developed, which enables long-term, large-scale, and high-frequency monitoring of the water-filled status of check dams. Using object detection algorithms based on deep learning and YOLOv3, an object-detection model was constructed and optimized. Leveraging high spatial resolution optical remote sensing images, the water-filled status of check dams can be identified. The model prediction indicates that the average precision for the check dam and water-filled check dam detection models reached 90.27% and 91.89%, respectively. Case studies were conducted on the check dams in the Jiuyuangou and Xiwuselang small watersheds. The monitoring result based on remote sensing images in the year 2021 shows a good agreement with the actual number of check dams. The proposed monitoring method for the water-filled status of check dams was proven feasible. This provides a reliable and efficient technical approach for monitoring the water-filled status of check dams, which is promising for their daily management and safe operation. Full article

This study projects future Residential Water Use (RWU) under climate change scenarios using a Bayesian Neural Network (BNN) model that quantifies the relationship between observed temperatures and RWU. Eighteen Global Climate Models (GCMs) under the Shared Socioeconomic Pathway 5–8.5 (SSP5–8.5) scenario were used to assess the uncertainties across these models. The findings indicate that RWU in Republic of Korea (ROK) is closely linked to temperature changes, with significant increases projected in the distant future (F3), especially during summer. Under the SSP5–8.5 scenario, RWU is expected to increase by up to 10.3% by the late 21st century (2081–2100) compared to the historical baseline. The model achieved a root mean square error (RMSE) of 11,400 m³/month, demonstrating reliable predictive performance. Unlike conventional deep learning models, the BNN provides probabilistic forecasts with uncertainty bounds, enhancing its suitability for climate-sensitive resource planning. This study also projects inflows to the Paldang Dam, revealing an overall increase in future water availability. However, winter water security may decline due to decreased inflow and minimal changes in RWU. This study suggests enhancing summer precipitation storage while considering downstream flood risks. Demand management strategies are recommended for addressing future winter water security challenges. This research highlights the importance of projecting RWU under climate change scenarios and emphasizes the need for strategic water resource management in ROK. Full article

To investigate the remediation efficiency of different plant species on cadmium (Cd)-contaminated soil, this study conducted a pot experiment with two woody species (Populu adenopoda and Salix babylonica) and two herbaceous species (Artemisia argyi and Amaranthus hypochondriacus). Soils were collected from an abandoned coal mine and adjacent pristine natural areas within the dam-adjacent section of the Three Gorges Reservoir Area to establish three soil treatment groups: unpolluted soil (T1, 0.18 mg·kg⁻¹ Cd), a 1:1 mixture of contaminated and unpolluted soil (T2, 0.35 mg·kg⁻¹ Cd), and contaminated coal mine soil (T3, 0.54 mg·kg⁻¹ Cd). This study aimed to investigate the growth status of plants, Cd accumulation and translocation characteristics, and the relationship between them and soil environmental factors. Woody plants exhibited significant advantages in aboveground biomass accumulation. Under T3 treatment, the Cd extraction amount of S. babylonica (224.93 mg) increased by about 36 times compared to T1, and the extraction efficiency (6.42%) was significantly higher than other species. Among the herbaceous species, A. argyi showed the maximum Cd extraction amount (66.26 mg) and extraction efficiency (3.11%) during T2 treatment. While A. hypochondriacus exhibited a trend of increasing extraction amount but decreasing extraction efficiency with increasing concentration. With the exception of S. babylonica under T1 treatment (BCF = 0.78), the bioconcentration factor was greater than 1 in both woody (BCF = 1.39–6.42) and herbaceous species (BCF = 1.39–3.11). However, herbaceous plants demonstrated significantly higher translocation factors (TF = 1.58–3.43) compared to woody species (TF = 0.31–0.87). There was a significant negative correlation between aboveground phosphorus (P) content and root Cd (p < 0.05), while underground nitrogen (N) content was positively correlated to aboveground Cd content (p < 0.05). Soil total N and available P were significantly positively correlated with plant Cd absorption, whereas total potassium (K) showed a negative correlation. This study demonstrated that woody plants can achieve long-term remediation through biomass advantages, while herbaceous plants, with their high transfer efficiency, are suitable for short-term rotation. In the future, it is suggested to conduct a mixed planting model of woody and herbaceous plants to remediate Cd-contaminated soils in the tailing areas of reservoir areas. This would synergistically leverage the dual advantages of root retention and aboveground removal, enhancing remediation efficiency. Concurrent optimization of soil nutrient management would further improve the Cd remediation efficiency of plants. Full article

This study investigates the dynamic response mechanisms of discharge capacity in the Han River Estuary to hydrological process changes at the Yangtze–Han River confluence. By constructing a one-dimensional hydrodynamic model for the 265 km Xinglong–Hankou reach, we quantitatively decouple the synergistic effects of riverbed scouring (mean annual incision rate: 0.12 m) and Three Gorges Dam (TGD) operation through four orthogonal scenarios. Key findings reveal: (1) Riverbed incision dominates discharge variation (annual mean contribution >84%), enhancing flood conveyance efficiency with a peak flow increase of 21.3 m³/s during July–September; (2) TGD regulation exhibits spatiotemporal intermittency, contributing 25–36% during impoundment periods (September–October) by reducing Yangtze backwater effects; (3) Nonlinear interactions between drivers reconfigure flow paths—antagonism occurs at low confluence ratios (R < 0.15, e.g., Cd increases to 45 under TGD but decreases to 8 under incision), while synergy at high ratios (R > 0.25) reduces Hanchuan Station flow by 13.84 m³/s; (4) The 180–265 km confluence-proximal zone is identified as a sensitive area, where coupled drivers amplify water surface gradients to −1.41 × 10⁻³ m/km (2.3× upstream) and velocity increments to 0.0027 m/s. The proposed “Natural/Anthropogenic Dual-Stressor Framework” elucidates estuary discharge mechanisms under intensive human interference, providing critical insights for flood control and trans-basin water resource management in tide-free estuaries globally. Full article

Termites pose significant threats to the structural integrity of embankments due to their nesting and tunneling behavior, which leads to internal voids, water leakage, or even dam failure. This review systematically classifies and evaluates current termite detection techniques in the context of embankment maintenance, focusing on physical sensing technologies and biological characteristic-based methods. Physical sensing methods enable non-invasive localization of subsurface anomalies, including ground-penetrating radar, acoustic detection, and electrical resistivity imaging. Biological characteristic-based methods, such as electronic noses, sniffer dogs, visual inspection, intelligent monitoring, and UAV-based image analysis, are capable of detecting volatile compounds and surface activity signs associated with termites. The review summarizes key principles, application scenarios, advantages, and limitations of each technique. It also highlights integrated multi-sensor frameworks and artificial intelligence algorithms as emerging solutions to enhance detection accuracy, adaptability, and automation. The findings suggest that future termite detection in embankments will rely on interdisciplinary integration and intelligent monitoring systems to support early warning, rapid response, and long-term structural resilience. This work provides a scientific foundation and practical reference for advancing termite management and embankment safety strategies. Full article

Neonatal calves possess an immature and naïve immune system and are reliant on the intake of maternal colostrum for the passive transfer of immunoglobulins. Maternal antibodies delivered to the calf via colostrum, are crucial to prevent calfhood diseases and death. Failure of transfer of passive immunity (FTPI) is a condition in which calves do not acquire enough maternal antibodies, mostly in the form of IgG, due to inadequate colostrum quality or delayed colostrum feeding. The diagnosis and risk factors for FTPI have been widely studied in dairy cattle; however, in beef calves, the research interest in the topic is relatively recent, and the most adequate diagnostic and preventative methods are still in development, making it difficult to define recommendations for the assessment and prevention of FTPI in cow–calf operations. The objective of this scoping review is to identify the published literature on best practices for colostrum management and transfer of passive immunity (TPI) in neonatal beef calves. The literature was searched using three electronic databases (CAB Direct, Scopus, and PubMed) for publications from 2003 to 2025. The search process was performed during the period from May to July 2023, and was repeated in January 2025. All screening processes were performed using Covidence systematic review software (Veritas Health Innovation, Melbourne, Australia). A total of 800 studies were initially identified through database searches. After removing duplicates, 346 studies were screened based on their titles and abstracts, leading to the exclusion of 260 studies. The remaining 86 studies underwent full-text screening, and 58 studies were considered eligible for data extraction. Hand-searching the references from published review papers on the subject yielded an additional five studies, bringing the total to 63 included articles. The prevalence of FTPI has been estimated to be between 5.8% and 34.5% in beef calves. Factors studied related to colostrum management include quality and quantity of colostrum intake, the timing and method of colostrum feeding, and the microbial content of the colostrum. Studies on risk factors related to the calf include the topics calf sex, twin status, calf vigor, weight, month of birth, cortisol and epinephrine concentrations, and the administration of nonsteroidal anti-inflammatory drugs to calves after difficult calving. The dam-related risk factors studied include dam body condition score and udder conformation, breed, parity, genetics, prepartum vaccinations and nutrition, calving area and difficulty, and the administration of nonsteroidal anti-inflammatory drugs at C-section. Most importantly for beef systems, calves with low vigor and a weak suckling reflex are at high risk for FTPI; therefore, these calves should be given extra attention to ensure an adequate consumption of colostrum. While serum IgG levels of < 8 g/L or < 10 g/L have been suggested as cutoffs for the diagnosis of FTPI, 16 g/L and 24 g/L have emerged as cutoffs for adequate and optimal serum IgG levels in beef calves. Several field-ready diagnostics have been compared in various studies to the reference standards for measuring indicators of TPI in beef calves, where results often differ between models or manufacturers. Therefore, care must be taken when interpreting these results. Full article

Continuous damming in karst rivers fragmented the longitudinal structure of river systems, disrupting plankton habitats, limiting dispersal, and reducing biodiversity. This study examined variations in zooplankton functional diversity in a dammed river system during dry and wet seasons. Sampling across both seasons yielded 44 samples, with 64 zooplankton taxa categorized into seven functional groups based on their traits. Functional diversity indices were calculated. Results revealed significant differences in nutrient concentrations between upstream and downstream sections, particularly during the dry season (R² = 0.11, p < 0.01). Zooplankton functional diversity decreased from upstream to downstream, with more pronounced differences in the dry season (R² = 0.94, p < 0.05), driven by reduced dispersal stochasticity (β_BC close to −1). Continuous damming primarily affected smaller zooplankton, such as rotifers, while dissolved oxygen, water temperature, and pH influenced distribution patterns related to habitat depth, breeding season, life span, and reproduction. These findings underscored the impact of damming on zooplankton functional diversity and informed dam management strategies for biodiversity conservation. Full article

The present study investigates the extent and spatial distribution of metal concentration in stream sediments that flow into Keban Dam Lake, Turkey. Sediment samples were analysed for trace and potentially toxic elements (PTEs), including V, Cr, Co, Ni, Cu, Zn, Pb, Tl, Th, and U. Enrichment Factor (EF), Contamination Factor (CF), Geo-accumulation Index (Igeo), and Pollution Load Index (PLI) were employed to assess contamination levels. Results reveal that Cr exhibited very high enrichment (EF = 15.95) in downstream urban samples, while Cu and Zn showed high enrichment in samples collected from the middle to lower reaches of the stream, probably indicating anthropogenic contributions. Most other elements, such as Pb, Tl, Th, and U, were within natural background levels. Sediment Quality Guidelines (SQGs) indicate that Cr, Ni, and Cu may pose potential ecological risks, especially in samples from urban-influenced and downstream areas where concentrations exceed the Probable Effect Levels (PEL; Cr: 160 mg/kg, Ni: 42.8 mg/kg, Cu: 108 mg/kg). Multivariate statistical analyses, including Pearson correlation and hierarchical clustering, reveal three distinct geochemical groupings. Among these, the most contaminated cluster—corresponding to midstream and downstream regions—is characterized by elevated Cu and Zn concentrations. Strong correlations among Cu–Zn, Ni–Cu, and Th–U suggest there is a combination of anthropogenic and lithogenic sources for most metals. While most sites showed low to moderate pollution, urban downstream locations exhibited significant metal accumulation, necessitating the region’s continued environmental monitoring and management strategies. Full article

Sarez Lake, situated at one of the highest altitudes among naturally dammed lakes, is regarded as potentially hazardous due to its geological setting. Therefore, developing an integrated monitoring and risk assessment framework for slope-related geological hazards in this region holds significant scientific and practical value. In this study, we processed 220 Sentinel-1A SAR images acquired between 12 March 2017 and 2 August 2024, using the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique to extract time-series deformation data with millimeter-level precision. These deformation measurements were combined with key environmental factors to construct a susceptibility evaluation model based on the Information Value and Support Vector Machine (IV-SVM) methods. The results revealed a distinct spatial deformation pattern, characterized by greater activity in the western region than in the east. The maximum deformation rate along the shoreline increased from 280 mm/yr to 480 mm/yr, with a marked acceleration observed between 2022 and 2023. Geohazard susceptibility in the Sarez Lake area exhibits a stepped gradient: the proportion of area classified as extremely high susceptibility is 15.26%, decreasing to 29.05% for extremely low susceptibility; meanwhile, the density of recorded hazard sites declines from 0.1798 to 0.0050 events per km². The spatial configuration is characterized by high susceptibility on both flanks, a central low, and convergence of hazardous zones at the front and distal ends with a central expansion. These findings suggest that mitigation efforts should prioritize the detailed monitoring and remediation of steep lakeside slopes and fault-associated fracture zones. This study provides a robust scientific and technical foundation for the emergency warning and disaster management of high-altitude barrier lakes, which is applicable even in data-limited contexts. Full article

Deformation is a direct manifestation of structural changes that occur during the operation of arch dams, and the development of reliable deformation early warning indicators allows for their timely study. Considering that an arch dam is a systematic overall structure, it is necessary to systematically analyze the formulation of deformation early warning indicators and general early warning methods for this dam type. To this end, this study innovatively proposes a systematic early warning method for arch dams based on deep learning and a multi-measurement point analysis strategy. Firstly, the causal model (HST) is utilized to extract the environmental factors as convolutional neural network (CNN) array samples, and the absolute deformation residual sequences of multiple points are obtained by HST-MultiCNN. Secondly, combining this with principal component analysis, a systematic deformation residual index with multiple points is established. Then, the kernel function is used to simulate the distribution of the abovementioned indicators, and is combined with the idea of small probability to formulate the overall warning indicator. Finally, the Re-CNN strategy is used to train the mapping relationship between the multi-objective residuals and the system indicators, and the mapping relationship outlined above is then used to obtain the system indicators corresponding to real-time prediction values, which in turn determine the overall deformation state of arch dams. Analysis shows that the RMSE of the deformation output of the proposed monitoring method uses a value between 0.2284 and 0.2942, with satisfactory accuracy, and the overall deformation warning accuracy reaches 100%, which is significantly better than the comparison method, and effectively solves the primary defect of the traditional single-point analysis—failure to reflect the overall deformation condition. Full article

River barriers constitute a key factor that is degrading river connectivity and represent a critical research focus in riverine ecosystem conservation. Management authorities and river restoration agencies globally have increasingly employed barrier removal or modification for connectivity restoration projects in recent years, practices that are widely discussed and empirically supported in academia. However, existing research predominantly focuses on large dams in primary rivers, overlooking the more severe fragmentation caused by low-head barriers within low-order streams. This study targets the Yanjing River (total length: 70 km), a third-order tributary of the Yangtze River basin, implementing culvert modification and complete removal measures, respectively, for two river barriers distributed within its terminal 9 km reach. Using differential analysis, principal component analysis (PCA), cluster analysis, Mantel tests, and structural equation modeling (SEM), we systematically examined the mechanisms by which connectivity restoration projects influences aquatic habitat and fish diversity, the evolution of reach heterogeneity, and intrinsic relationships between aquatic environmental factors and diversity metrics. Results indicate that (1) the post-restoration aquatic habitat significantly improved with marked increases in fish diversity metrics, where hydrochemical factors and species diversity exhibited the highest sensitivity to connectivity changes; (2) following restoration, the initially barrier-fragmented river segments (upstream, middle, downstream) exhibited significantly decreased differences in aquatic habitat and fish diversity, demonstrating progressive homogenization across reaches; (3) hydrological factors exerted stronger positive effects on fish diversity than hydrochemical factors did, particularly enhancing species diversity, with a significant positive synergistic effect observed between species diversity and functional diversity. These studies demonstrate that “culvert modification and barrier removal” represent effective project measures for promoting connectivity restoration in low-order streams and eliciting positive ecological effects, though they may reduce the spatial heterogeneity of short-reach rivers in the short term. It is noteworthy that connectivity restoration projects should prioritize the appropriate improvement of hydrological factors such as flow velocity, water depth, and water surface width. Full article

The construction of the Grand Ethiopian Renaissance Dam (GERD) on the Blue Nile has heightened transboundary water tensions in the Nile River Basin, particularly affecting downstream Sudan and Egypt. This study leverages African Earth Observation Data Cubes, specifically Digital Earth Africa’s Water Observations from Space (WOfS) platform, to quantify the hydrological impacts of GERD’s three filling phases (2019–2022) on Sudan’s Roseires Dam. Using Sentinel-2 satellite data processed through the Open Data Cube framework, we analyzed water extent changes from 2018 to 2023, capturing pre- and post-filling dynamics. Results show that GERD’s water spread area increased from 80 km² in 2019 to 528 km² in 2022, while Roseires Dam’s water extent decreased by 9 km² over the same period, with a notable 5 km² loss prior to GERD’s operation (2018–2019). These changes, validated against PERSIANN-CDR rainfall data, correlate with GERD’s filling operations, alongside climatic factors like evapotranspiration and reduced rainfall. The study highlights the potential of Earth Observation (EO) technologies to support transparent, data-driven transboundary water governance. Despite the Cooperative Framework Agreement (CFA) ratified by six upstream states in 2024, mistrust persists due to Egypt and Sudan’s non-ratification. We propose enhancing the Nile Basin Initiative’s Decision Support System with EO data and AI-driven models to optimize water allocation and foster cooperative filling strategies. Benefit-sharing mechanisms, such as energy trade from GERD, could mitigate downstream losses, aligning with the CFA’s equitable utilization principles and the UN Watercourses Convention. This research underscores the critical role of EO-driven frameworks in resolving Nile Basin conflicts and achieving Sustainable Development Goal 6 for sustainable water management. Full article

Suyukou Gully, located on the eastern slope of the Helan Mountains in northwest China, is a typical debris-flow-prone catchment characterized by a steep terrain, fractured bedrock, and abundant loose colluvial material. The area is subject to intense short-duration convective rainfall events, which often trigger destructive debris flows that threaten the Suyukou Scenic Area. To investigate the dynamics and risks associated with such events, this study employed the FLO-2D two-dimensional numerical model to simulate debris flow propagation, deposition, and hazard distribution under four rainfall return periods (10-, 20-, 50-, and 100-year scenarios). The modeling framework integrated high-resolution digital elevation data (original 5 m DEM resampled to 20 m grid), land-use classification, rainfall design intensities derived from regional storm atlases, and detailed field-based sediment characterization. Rheological and hydraulic parameters, including Manning’s roughness coefficient, yield stress, dynamic viscosity, and volume concentration, were calibrated using post-event geomorphic surveys and empirical formulations. The model was validated against field-observed deposition limits and flow depths, achieving a spatial accuracy within 350 m. Results show that the debris flow mobility and hazard intensity increased significantly with rainfall magnitude. Under the 100-year scenario, the peak discharge reached 1195.88 m³/s, with a maximum flow depth of 20.15 m and velocities exceeding 8.85 m·s⁻¹, while the runout distance surpassed 5.1 km. Hazard zoning based on the depth–velocity (H × V) product indicated that over 76% of the affected area falls within the high-hazard zone. A vulnerability assessment incorporated exposure factors such as tourism infrastructure and population density, and a matrix-based risk classification revealed that 2.4% of the area is classified as high-risk, while 74.3% lies within the moderate-risk category. This study also proposed mitigation strategies, including structural measures (e.g., check dams and channel straightening) and non-structural approaches (e.g., early warning systems and land-use regulation). Overall, the research demonstrates the effectiveness of physically based modeling combined with field observations and a GIS analysis in understanding debris flow hazards and supports informed risk management and disaster preparedness in mountainous tourist regions. Full article

To investigate the species composition, reproductive dynamics, and hydrological drivers of fish resources in the early stage in the Guiping section of the Xunjiang River, we conducted a two-year survey (2022–2023) downstream of the Datengxia Dam. A total of 22,464 fish eggs and larvae were collected, representing 6 orders, 17 families, and 67 species, with Cyprinidae (58.2%) as the dominant family. Dominant species included Squaliobarbus curriculus, Gobiidae, Hemiculter leucisculus, and Culter, exhibiting significant interannual variation in abundance. The breeding season peaked from May to September, accounting for 94.6% of annual recruitment. Hydrological conditions strongly influenced reproductive output: the multiple flood pulse periods in 2022 (peak discharge: 29,000 m³/s) yielded 34.997 billion eggs and larvae, whereas reduced flows in 2023 (peak discharge: 12,200 m³/s) led to a 75.4% decline (8.620 billion). Redundancy analysis (RDA) revealed that discharge, water temperature, natural hydrological data, and dissolved oxygen were the primary environmental drivers, explaining 46.11% of variability in larval abundance (p < 0.001). Notably, the proportion of important economic fish, “four major Chinese carps”, plummeted from 4.9% (2022) to less than 0.1% (2023), indicating spawning ground function degradation. Our results demonstrate that flood pulses are essential for sustaining fish recruitment, particularly for pelagic spawning riverine fish like the four major Chinese carps. Their proportion plummeted to less than 0.1% in 2023, highlighting the urgent need for eco-hydrological management in the Xunjiang River. Full article