Search Results (3,159)

Debris flows propagating in natural environments often encounter irregular terrain features, such as bottom roughness and man-made structures like groundsills, which significantly influence their behavior and dynamics. In practice, groundsills are commonly used as debris flow mitigation structures. This study examines the effects of a beam-type groundsill array on the flow behavior of sediment mixtures in an inclined channel using numerical simulations. The sediment mixtures, modeled as Bingham fluids, were tested as they flowed over groundsill arrays with varying densities, characterized by the spacing-to-height ratio (d/h) ranging from 2 to 10. The findings indicate that interaction with the groundsills produces a hydraulic jump-like flow, reaching a height approximately 2.2 times the approach flow depth across different array densities. High-density arrays (d/h≤4) substantially hindered flow propagation, reducing front velocities but leading to sediment buildup upstream of the groundsills. Conversely, low-density arrays (d/h>4) facilitated smoother flow with higher velocities. These insights into the relationship between array density, flow behavior, and sediment trapping provide valuable guidance for optimizing groundsill array designs to effectively reduce the mobility of gravity-driven flows of non-Newtonian fluids (such as snow avalanches, debris, lava, or mudflows) and mitigate the associated risks. Full article

Previous studies on highway_rail grade crossing collisions have primarily focused on identifying factors contributing to the frequency and severity of driver injuries. In recent years, increasing attention has been given to modeling driver injury severity at these crossings. Recognizing the variations in injury severity under different road surface conditions, this study investigates the impact of road surface conditions on driver injury severity at highway_rail grade crossings. Using nearly a decade of accident data (2012–2021), thi study employs a LightGBM model to predict factors influencing injury severity and utilizes SHAP values for result interpretation. The symmetry principle of SHAP esures that factors with identical influence receive equal values, enhancing the reliability of predictive outcomes. The findings reveal that driver injury severity at highway_rail grade crossings varies significantly under different road surface conditions. Key factors identified include train speed, driver age, vehicle speed, annual average daily traffic (AADT), driver presence inside the vehicle, weather conditions, and location. The results indicate that collisions are more frequent when either the vehicle or train travels at high speed. Implementing speed limits for both vehicles and trains under varying road conditions could effectively reduce accident severity. Additionally, older drivers are more prone to severe accidents, highlighting the importance of installing control devices, such as warning signs or signals, to enhance driver alertness and mitigate injury risks. Furthermore, adverse weather conditions, such as rain, snow, and fog, exacerbate accident severity on road surfaces like sand, mud, dirt, oil, or gravel. Timely removal of surface obstacles may help reduce the severity of such accidents. Full article

The intensifying effects of climate change have led to increased flooding, even in desert regions, resulting in significant socio-economic and ecological impacts. This study analyzes the causes and consequences of flooding in the Zhem River basin using data from ground stations, including Kazhydromet, and satellite platforms such as USGS FEWS NET and Copernicus. Spatial analyses conducted in ArcGIS utilized classified raster data to map the dynamics of flooding, snow cover, vegetation, and soil conditions. This enabled a geoecological analysis of flood damage on the vital components of the local landscape. Results show that flooding in the Zhem River basin was driven by heavy winter precipitation, rapid snowmelt, and a sharp rise in spring temperatures. The flood damaged Kulsary city and also harmed the region’s soil, vegetation, and wildlife. In July 2024, the flooded sail area tripled compared to the same period in 2023. Additionally, the area of barren land or temporary water bodies (pools) formed three months after the water receded also tripled, increasing from 84.9 km² to 275.7 km². This study highlights the critical need for continued research on the long-term environmental effects of flooding and the development of adaptive management strategies for sustainable regional development. Full article

Solar panels play a crucial role in producing renewable electricity power for the grid, and this role grows more significant each year. However, defects in solar panels can significantly drop power output, leading to grid instability. Therefore, employing an efficient Artificial Intelligence (AI) algorithm to autonomously detect defects in solar panels is crucial. In this study, we employ the You Only Look Once (YOLO) v9, v10, and v11 algorithms to detect defects in solar panels. To this end, we examined their performance results via training on three datasets. The first dataset includes 191 thermal images with an image size of 200 × 160 pixels to identify a cell, multi-cell levels, and shadow defects. The second dataset consists of 792 optical images of solar panels with an image size of 244 × 244 to identify dust, snow, bird droppings, physical damage, and electrical defects. The third dataset includes 316 thermal images with an image size of 200 × 160 pixels, an enhanced version of the first dataset. Moreover, we examined the training and test performance results of YOLO v5, v9, v10, and v11. We achieved improved performance in detecting defects in solar panels compared to existing solutions by using the YOLO v10 and v11 algorithms. Additionally, we compared their performance results against Support Vector Machine (SVM) and Faster Region-based Convolutional Neural Network (R-CNN) to demonstrate the efficiency of the YOLO v10 algorithm. In conclusion, YOLO v11-X delivered the best performance among the algorithms tested. It reached a precision rate, recall rate, mean average precision, and F1 score of about 89.7%, 87.7%, 92.7%, and 90%, respectively. Full article

In desert ecosystems, litter decomposition is the primary source of soil nutrients and is strongly affected by extreme climate events, which may influence desert plant survival and species diversity. To date, the effects of snowfall changes on litter decomposition in desert species remain poorly understood. Here, a snowfall manipulation experiment was conducted in Northwest China that included snowfall addition and removal treatments, as well as a natural snowfall control. Compared to the control, snowfall addition increased the amount of litter mass lost for Salsola passerina and Reaumuria soongarica during the snow-covered period by 21.54% and 21.8%, respectively. In contrast, snowfall addition effects differed between species during the snow-free period. More carbon was released from the S. passerina litter in the snowfall addition treatment during the snow-free period. Similarly, during the snow-covered period, more carbon and nitrogen were released from the R. soongorica litter in the snowfall addition treatment. Overall, the proportion of litter mass lost (from the annual total) increased with snowfall addition in the snow-covered period but was reduced with snowfall addition in the snow-free period. In the snow-covered period, the snowfall addition treatment affected litter mass loss to the same extent in both species but impacted S. passerina more strongly than R. soongorica in the snow-free period due to differences in soil urease activity. Changes in snowfall, therefore, significantly influenced litter decomposition in both desert species, but these effects differed between the snow-covered and snow-free period, particularly for litter with a higher C:N ratio. Full article

Tetracentron sinense is a tall deciduous tree and represents the only remaining species of Tetracentron. Currently, the spatial distribution pattern of T. sinense and its associated influencing factors remain unclear, thus hindering its protection and rational utilization. In this study, we employed the point pattern method to analyze the spatial distribution patterns of four representative populations of T. sinense distributed in Baima Snow Mountain, Dafengding, Leigong Mountain, and Foping in China. The results reveal that the T. sinense populations in Baima Snow Mountain, Dafengding, and Leigong Mountain exhibited an aggregated distribution on small (0–10 m) or specific scales, with their spatial distribution patterns shifting from aggregated to random as the scale increased. In contrast, the population of T. sinense in Foping showed a random distribution at all scales. In relation to the factors influencing the spatial distribution patterns of T. sinense, we found that young trees played a crucial role and had a substantial impact on their distribution. Furthermore, adult trees contributed to the aggregated distribution of T. sinense saplings on smaller scales (0–10 m). Additionally, we identified Acer erianthum, Prunus conradinae, and Rhododendron anthosphaerum as key associated species that influenced the formation of spatial distribution patterns of T. sinense. Finally, air humidity and soil moisture content were found to exert a significant effect on the spatial distribution patterns of T. sinense populations. For the protection of T. sinense in situ, it is necessary to increase the number of young trees, enhance the availability of microhabitat factors for its seedlings, and utilize key companion species to promote heterogeneity, which can optimize resource utilization and foster population rejuvenation. Full article

Winter precipitation (P) in East Asia (EA) is characterized by a wetter south and a drier north. Most of the existing research has concentrated on elucidating the mechanisms of winter P in southern EA, with relatively less attention given to northern East Asia (NEA). Our analysis showed that the correlation coefficient (c.c.) of average winter precipitation anomaly percentage (PAP) between southern EA and NEA is 0.24 for the period 1950–2023, indicating substantial regional difference. An empirical orthogonal function (EOF) analysis was conducted on the winter PAP in NEA. The first and second mode (EOF1 and EOF2) account for 45.5% and 17.9% of the total variance, respectively. EOF1 is characterized by a region-wide uniform spatial pattern whereas EOF2 exhibits a north–south dipole pattern. Further analysis indicated that the two EOF modes are related to distinct atmospheric circulation and external forcings. Specifically, EOF1 is linked to a wave train from Central Siberia toward Japan, while EOF2 is connected with an anomaly similar to the Western Pacific pattern. Variations in mid–high latitude sea surface temperatures, sea ice, and snow are potential factors influencing EOF1. EOF2 exhibits a close relationship with tropical SST anomalies. Full article

Analysis of the temporal relationship between meteorological drought and hydrological drought is crucial in monitoring water resource availability. This study examined the linear and lagged relationships of the spread of meteorological drought to hydrological drought and their joint effects on low-flow drought variability in the Oum Er-Rbia (OER) watershed. To this end, random forest (RF) model and statistical methods were used to study the characteristics of the temporal relationships between meteorological and hydrological drought indices at monthly, seasonal, and annual scales. The various analyses revealed that the relationship between hydrological and meteorological drought is mainly a function of the time scale considered, the choice of indices to describe each type of drought and the season considered. The hydrological drought of surface water and snow cover is synchronized with the meteorological drought at the monthly, seasonal, and annual scales. In contrast, the transition from meteorological drought to groundwater drought has a lag time of 1 month and is statistically significant up to t − 5 and t + 5, i.e., 6 months. The linear correlation between the annual rainfall deficit and the monthly groundwater storage index was the lowest (0.15) in December and the highest (0.83) in March. This suggests a seasonal response of groundwater drought to the cumulative effects of precipitation deficits. The RF analysis highlighted the importance of the cumulative characteristics of meteorological drought regarding the severity of low-flow drought. The meteorological drought indices at longer time scales have a greater impact on the severity of low-flow drought, with a contribution of approximately 10% per index. However, the relative contributions of meteorological factors and hydrological indices rarely exceed 5%. Thus, by exploring for the first time the complex interactions among the severity of low-flow regimes, meteorological and hydrological drought indices and meteorological factors, this study provides a new perspective for understanding the characteristics of propagation from meteorological to severe hydrological drought. Full article

Background and Objectives: The objective of the study was to evaluate the epidemiology of slope-related accidents in a high-volume trauma center during the winter season. In addition, this study aims to analyze patient-related, equipment-related, and environment-related characteristics. Materials and Methods: A questionnaire containing 22 items was distributed to all adult patients admitted to the emergency department of the Brixen Hospital (Italy) during the 2023/24 winter season because of a ski/snowboard-related injury. Results: The final database included 579 questionnaires from 579 patients who ultimately entered the study: 285 were females and 294 were males. The analysis of risk factors for fractures revealed that patients with fractures were generally older (50.7 ± 16.0 years) compared to those without fractures (45.4 ± 17.2 years, p = 0.0021). Thirty-six percent of injuries were considered as joint sprain/ligament strain: patients in this group were younger (45.5 ± 16.2 years) compared to all patients (48.3 ± 17.3 years, p = 0.0151). Conclusions: In conclusion, this study identified significant risk factors associated with skiing and snowboarding injuries. Fractures were more common among older and more experienced skiers, particularly those who described themselves as experts. Ligamentous distortions were more common among younger and less experienced skiers. Fatigue is generally underestimated, and the general physical preparation is often lacking for sports like skiing and snowboarding. Additionally, the absence of significant correlations between weather conditions, snow quality, equipment type, and the difficulty of the slope with injury risk suggests that individual factors such as age and skill level are more critical determinants of injury risk than environmental or equipment-related factors. Full article

Sea ice motion plays an important role in the seasonal and interannual evolution of the polar sea ice cover. Satellite imagery can be used to track the motion of sea ice via cross-correlation feature tracking algorithms. Such a method has been used for the National Snow and Ice Data Center (NSIDC) sea ice motion product, based largely on passive microwave imagery. This study investigates the use of a new enhanced resolution passive microwave brightness temperature (TB) product to derive ice motion products. The results demonstrate that the new imagery source provides useful daily motion estimates that provide denser spatial coverage and reduced errors. The enhanced TBs yield motions that have a 30% lower Root Mean Square (RMS) difference with motion estimates from buoys. The enhanced resolution TBs will be used in the new version of the NSIDC motion product that is currently in development. Full article

Background: During the COVID-19 pandemic, migrant populations remained under-immunized due to limited access to health care, language barriers, and vaccine hesitancy. The USAID-funded MOMENTUM Routine Immunization Transformation and Equity project supported the government in collaborating with various local health and non-health partners to identify and vaccinate migrants. This case study examines the roles of project partners and the strategies each entity implemented to increase COVID-19 vaccine uptake among migrants, as well as the perceptions regarding the effectiveness of these strategies. Methods: We designed a qualitative explanatory case study guided by the Behavioral and Social Drivers framework and RE-AIM implementation science frameworks. We conducted 31 focus group discussions and 50 in-depth interviews with migrants, project partners, community leaders, and government stakeholders in Tamil Nadu and Punjab. Results: In both states, partnerships with health departments, private employers, and community-based organizations were essential for identifying and vaccinating un- and under-vaccinated migrant groups. In Tamil Nadu, collaboration with the Department of Labor and mobile medical units facilitated vaccination camps at construction sites. In Punjab, religious institutions organized sessions at places of worship, and the Border Security Force enabled health workers to reach migrants living near the border. In both states, key strategies—involving influencers to discuss the importance of vaccine safety and value, bringing vaccination services to migrants’ workplaces and homes at flexible times and mandating workplace vaccination to encourage vaccination—shifted perceptions towards vaccination and increased vaccine uptake among migrants. Conclusions: The strategies and partnerships identified in this study highlight the broader implications for future public health interventions, demonstrating that collaboration with the private sector and faith-based organizations can enhance routine immunization efforts, particularly when localized to organizations that understand community needs and can address specific barriers and motivators. Full article

Coagulase-negative staphylococci form a heterogeneous group defined solely by the lack of coagulase. Initially considered non-pathogenic, they are now known to be opportunistic pathogens of increasing importance. This study was conducted to examine the prevalence of Staphylococcus spp., their taxonomic diversity, antibiotic resistance patterns and genetic determinants of antibiotic resistance in the water resources used within the technical snow production process. The types of samples included (1) river water at intakes where water is drawn for snowmaking, (2) water stored in technical reservoirs, from which it is pumped into the snowmaking systems, (3) and technical snowmelt water. The study was conducted in the catchments of five rivers: Białka, Biały Dunajec, Raba and Wisła in Poland, and Studený Potok in Slovakia. Staphylococcus spp. was detected in all types of samples: in 17% of river water, 25% of reservoir-stored water and in 60% of technical snowmelt water. All staphylococci were coagulase-negative (CoNS) and belonged to 10 species, with S. epidermidis being the most prevalent in river water, S. warneri and S. pasteuri in reservoir-stored water and S. haemolyticus in snowmelt water. The highest resistance rates to erythromycin and macrolide/lincosamid/streptogramin b (MLSb) types of resistance were detected in all types of samples, accompanied by the erythromycin efflux pump-determining msrA gene as the most frequent genetic determinant of antibiotic resistance. This study is the first report of the presence of antibiotic-resistant, including multidrug-resistant, CoNS carrying more than one gene determining antibiotic resistance in technical snow in the mountain areas of the Central European countries. Full article

There are numerous lakes in the Tibetan Plateau (TP) that significantly impact regional climate and aquatic ecosystems, which often freeze seasonally owing to the high altitude. However, the special warming mechanisms of lake water under ice during the frozen period are poorly understood, particularly in terms of solar radiation penetration through lake ice. The limited understanding of these processes has posed challenges to advancing lake models and improving the understanding of air–lake energy exchange during the ice-covered period. To address this, a field experiment was conducted at Qinghai Lake, the largest lake in China, in February 2022 to systematically examine thermal conditions and radiation transfer across air–ice–water interfaces. High-resolution remote sensing technologies (ultrasonic instrument and acoustic Doppler devices) were used to observe the lake surface changes, and MODIS imagery was also used to validate differences in lake surface conditions. Results showed that the water temperature under the ice warmed steadily before the ice melted. The observation period was divided into three stages based on surface condition: snow stage, sand stage, and bare ice stage. In the snow and sand stages, the lake water temperature was lower due to reduced solar radiation penetration caused by high surface reflectance (61% for 2 cm of snow) and strong absorption by 8 cm of sand (absorption-to-transmission ratio of 0.96). In contrast, during the bare ice stage, a low reflectance rate (17%) and medium absorption-to-transmission ratio (0.86) allowed 11% of solar radiation to penetrate the ice, reaching 11.70 W·m⁻², which increased the water temperature across the under-ice layer, with an extinction coefficient for lake water of 0.39 (±0.03) m⁻¹. Surface coverings also significantly influenced ice temperature. During the bare ice stage, the ice exhibited the lowest average temperature and the greatest diurnal variations. This was attributed to the highest daytime radiation absorption, as indicated by a light extinction coefficient of 5.36 (±0.17) m⁻¹, combined with the absence of insulation properties at night. This study enhances understanding of the characteristics of water/ice temperature and air–ice–water solar radiation transfer through effects of different ice coverings (snow, sand, and ice) in Qinghai Lake and provides key optical radiation parameters and in situ observations for the refinement of TP lake models, especially in the ice-covered period. Full article

To mitigate the prevalence of highway accidents in Southwest China during adverse weather conditions, this study introduces a novel method for identifying accident-prone sections in complex meteorological circumstances. The technique, anchored in data mining’s support index, pioneers the concept of meteorological responsiveness, which includes the elucidation of its mechanisms and the development of computational methodologies. Historical meteorological data and accident records from mountainous highways were meticulously analyzed to quantify the spectrum of adverse weather impacts on driving risks. By integrating road geometry, weather data, and accident site information, meteorological events were identified, categorized, and assigned a meteorological responsiveness score. Outlier sections were processed for preliminary screening, enabling the identification of high-risk segments. The Meteorological Response Ratio Index was instrumental in highlighting and quantifying the influence of adverse weather on traffic safety, facilitating the prioritization of critical sections. The case study of the SC2 highway in Southwest China validated the method’s feasibility, successfully pinpointing eight high-risk sections significantly affected by adverse weather, which constituted approximately 19.05% of the total highway length. Detailed analysis of these sections, especially those impacted by rain, fog, and snow, revealed specific zones prone to accidents. The meteorological responsiveness method’s efficacy was further substantiated by correlating accident mechanisms under adverse weather with the road geometry of key sections. This approach stands to significantly enhance the safety management of operational highways. Full article