Search Results (1,424)

The information of sediment flux (Q_s) from hydrometric data-scarce small coastal watersheds is an important supplement for interpreting the sedimentary records of continental shelf sedimentary systems. This paper proposes a solution to estimate their values based upon the empirical formula of small and medium-sized coastal watersheds in adjacent regions, taking the 25 small rivers in Hainan Island as example. Three categories of methods were applied to calculate the Q_s. The first category involves the direct application of global empirical formulas, while the second and third categories utilizes empirical formulas that have been calibrated with regional characteristic data. The Q_s calculation accuracy the above methods was validated by the observed values of typical rivers. Key findings include: (1) The area values of watersheds extracted from SRTM (Shuttle Radar Topography Mission) data exhibit a high correlation with actual values, confirmed the reliability and applicability of SRTM data; (2) The Global equation significantly overestimates Q_s for the validation rivers (average relative error of 18.73), while employing the pristine-modified and disturbed-modified equations effectively improves the calculation accuracy (average relative errors of 0.72 and 1.64, respectively); (3) By averaging the results of different models, the Q_s for the major rivers in Hainan Island was calculated as 6.07 Mt/a before large-scale human activities and 4.56 Mt/a after. This study demonstrates that modification not only needs to be considered to adjust global empirical formulas but also to differentiate between the scenarios of before and after large-scale human activities in small coastal watersheds. Full article

The Yellow River Delta (YRD) is a vital agricultural and ecologically fragile zone in China. Understanding the spatial pattern and evolutionary characteristics of Rural Settlements Area (RSA) in this region is crucial for both ecological protection and sustainable development. This study focuses on Dongying, a key YRD city, and compares four advanced deep learning models—U-Net, DeepLabv3+, TransUNet, and TransDeepLab—using fused Sentinel-1 radar and Landsat optical imagery to identify the optimal method for RSA mapping. Results show that TransUNet, integrating polarization and optical features, achieves the highest accuracy, with Precision, Recall, F1 score, and mIoU of 89.27%, 80.70%, 84.77%, and 85.39%, respectively. Accordingly, TransUNet was applied for the spatiotemporal extraction of RSA in 2002, 2008, 2015, 2019, and 2023. The results indicate that medium-sized settlements dominate, showing a “dense in the west/south, sparse in the east/north” pattern with clustered distribution. Settlement patches are generally regular but grow more complex over time while maintaining strong connectivity. In summary, the proposed method offers technical support for RSA identification in the YRD, and the extracted multi-temporal settlement data can serve as a valuable reference for optimizing settlement layout in the region. Full article

The One Health approach is used to assess health-associated risks resulting from human exposure to antibiotic-resistant bacteria (ARB) that pose a significant public health risk. In this approach, wastewater treatment plants (WWTPs) play an important role in reducing bacteria and antibiotic-resistant genes (ARGs) in the environment. The ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp.) are of significant concern due to their ability to evade the effects of multiple antibiotics, including last-resort treatments such as carbapenems and glycopeptides. This study aimed to investigate the environmental surveillance of ESKAPE bacteria in wastewater and their adjacent receiving water bodies in Limpopo Province, South Africa. Methodology: Over a period of 6 months, all isolates were identified phenotypically, and genomic DNA was extracted using the QIAamp 96 DNA QIAcube^® HT Kit. Species-specific PCR was performed, followed by Sanger sequencing. The relevant sequences were compared to NCBI GenBank references using BLAST for confirmation and to assess the potential human health-associated risks. Results: ESKAPE organisms identified phenotypically were confirmed using PCR in both WWTP samples. Bacteria such as Acinetobacter baumannii and Enterobacter spp. were not detected in upstream or downstream river samples, particularly during August and September. In December and January, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa were not detected in effluent samples at both sites. Phylogenetic analysis revealed a diverse range of clinically significant genera, including Pseudomonas, Klebsiella, Enterobacter, and Staphylococcus, with strains closely related to global clinical isolates. Many of the isolates were associated with resistance to carbapenems, fluoroquinolones, and aminoglycosides. In addition, some strains clustered with both methicillin-sensitive and methicillin-resistant lineages. Conclusions: The findings emphasise the urgent need for increased genomic surveillance in environmental settings affected by wastewater discharge and highlight the importance of integrated antimicrobial resistance monitoring that connects clinical and environmental health sectors. Full article

Unauthorized fossil trafficking violates national legislation and deprives cultural and natural heritage. This study proposes a pilot method to fingerprint the origin of fossils by characterizing the carbon and oxygen stable isotope signatures of fossil-bearing limestones to provide a non-destructive quantitative tool against illegal fossil trade. This promising approach has been applied to the Crato Formation (NE Brazil), which is a renowned Lower Cretaceous fossiliferous lacustrine limestone. This study aims at establishing the range of isotopic oxygen (δ¹⁸O) and carbon (δ¹³C) values of the Crato Formation’s laminated calci-mudstone by compiling isotopic data from previous studies, conducting new analyses, and comparing with other fossiliferous lacustrine limestones from Brazil (Cretaceous Codó Formation) and the USA (Eocene Green River Formation). This preliminary evaluation determined a distinctive isotopic signature of the Crato Formation fossil-bearing “sete cortes” (“seven cuts”) ethnostratum, with VPDB δ¹⁸O and δ¹³C arithmetic means of −5.94‰ and +0.90‰, standard deviations 0.76‰ and 0.61‰, medians of −5.89‰ and +0.73‰, and interquartile ranges of 1.47‰ and 1.24‰, respectively. This pilot investigation establishes a methodological groundwork for the development of a global database integrating lithofacies and geochemical parameters of fossil-bearing limestones to expedite the identification and restitution of illegally extracted paleontological heritage. Full article

This paper presents the results of a research project on the use of stone in Roman architecture in Oderzo and Concordia Sagittaria, located between the Tagliamento and the Piave rivers (Italy). The study involved a documental survey, material sampling and analysis, provenance identification, and interpretation of results to reconstruct ancient stone trade routes. During sampling, 33 carbonate rock specimens were collected from archaeological sites and architectural elements in Oderzo, and 52 from Concordia Sagittaria. In both cities, these rocks were primarily used for architectural elements such as columns and capitals, whereas these lithotypes were less frequently employed in structures and infrastructures. The analysis revealed a significant reliance on regional limestones. Petrographic examinations (PLM-TL) identified six main limestone groups, many of which were linked to quarries located in the Aurisina and in the Triestine Karst region, as well as in the Prealps and Berici Hills. The study encountered several challenges: many analysed samples displayed petrographic characteristics consistent with multiple sources, complicating the precise identification of their extraction site. Despite a detailed understanding of the region’s geology, reference geological datasets often overlook outcrops that may have been exploited in antiquity. Consequently, when samples lacked distinctive features, tracing them to a particular quarrying basin proved difficult. In conclusion, the research underscores the extensive use of local limestones while acknowledging the challenges posed by limited petrographic reference data, which hinder the precise identification of the source basins of the materials used in Roman construction. Full article

River–lake systems are essential for sustaining ecosystems and human livelihoods. However, the complexity and variability of large river–lake systems, coupled with characteristic differences in water bodies across regions, have made quantifying their extent and changes inherently challenging. This study implements a robust water extraction method based on the multidimensional X-means clustering algorithm. This method leverages the advantages of Sentinel-2 imagery for water detection. Utilizing the X-means algorithm, it generates a new seasonal surface water area (SWA) product for the mid-lower reaches of the Yangtze River (MLRYR). The implemented method achieved an overall accuracy of 97.98%, a producer’s accuracy of 98.02%, a user’s accuracy of 96.01%, a Matthews correlation coefficient of 0.954, and a Kappa coefficient of 0.954. Analysis of water body dynamics reveals that over the past six years, the overall trend of SWA in the MLRYR has remained stable. However, within a broad range including multiple sub-basins, a decline in SWA has been observed on an inter-annual scale. Among the large lakes and reservoirs in the MLRYR, the water areas of Poyang Lake, Dongting Lake and Shijiu Lake all showed a marked decline. Among all water bodies with a significant increase in area, the Danjiangkou Reservoir is the largest. Further correlation analysis indicates that SWA exhibited the strongest correlations with precipitation and drought index in most sub-basins. In sub-basins where large lakes and reservoirs exist, the presence of river networks played a buffering role by regulating and storing water, thereby reducing the direct influence of climatic factors on lake and reservoir water extent. These findings highlight the complex interplay of climatic and hydrological factors. By integrating satellite imagery and Earth observation, this study advances understanding of MLRYR surface water dynamics, providing a robust framework for monitoring in other regions. It offers critical insights into drought impacts and informs effective water resource management and conservation strategies. Full article

Studies of microbial degradation of historic woods are essential to help protect and preserve these important cultural properties. The USS Cairo is a historic Civil War gunboat and one of the first steam-powered and ironclad ships used in the American Civil War. Built in 1861, the ship sank in the Yazoo River of Mississippi in 1862 after a mine detonated and tore a hole in the port bow. The ship remained on the river bottom and was gradually buried with sediments for over 98 years. After recovery of the ship, it remained exposed to the environment before the first roofed structure was completed in 1980, and it has been displayed under a tensile fabric canopy with open sides at the Vicksburg National Military Park in Vicksburg, Mississippi. Concerns over the long-term preservation of the ship initiated this investigation to document the current condition of the wooden timbers, identify the fungi that may be present, and determine the elemental composition resulting from past wood-preservative treatments. Micromorphological characteristics observed using scanning electron microscopy showed that many of the timbers were in advanced stages of degradation. Eroded secondary cell walls leaving a weak framework of middle lamella were commonly observed. Soft rot attack was prevalent, and evidence of white and brown rot degradation was found in some wood. DNA extraction and sequencing of the ITS region led to the identification of a large group of diverse fungi that were isolated from ship timbers. Soft rot fungi, including Alternaria, Chaetomium, Cladosporium, Curvularia, Xylaria and others, and white rot fungi, including Bjerkandera, Odontoefibula, Phanerodontia, Phlebiopsis, Trametes and others, were found. No brown rot fungi were isolated. Elemental analyses using induced coupled plasma spectroscopy revealed elevated levels of all elements as compared to sound modern types of wood. High concentrations of boron, copper, iron, lead, zinc and other elements were found, and viable fungi were isolated from this wood. Biodegradation issues are discussed to help long-term conservation efforts to preserve the historic ship for future generations. Full article

The desert riparian forest oasis, dominated by Populus euphratica and Tamarix chinensis, is an important barrier to protect the economic production and habitat of the Tarim River Basin. However, there is still a lack of high-precision spatial distribution data of desert ri-parian forest species below 10 m. The recently launched PlanetScope CubeSat constella-tion, which provides daily earth observation imagery with a resolution of 3 m, offers a highly favorable dataset for mapping the high-resolution distribution of P. euphratica and T. chinensis and an unprecedented opportunity to explore the optimal phenology window to distinguish between them. In this study, time-series PlanetScope images were first used to extract phenological metrics of P. euphratica, dividing the annual life cycle into four phenology windows: duration of leaf expansion (DLE), duration of leaf maturity (DLM), duration of leaf fall (DLF), and duration of the dormancy period (DDP). The random forest model was used to obtain the classification accuracy of 16 phenological window combinations. Results indicate that after gap filling of vegetation index time series, the identification accuracy for P. euphratica and T. chinensis exceeded 0.90. Among individual phenology windows, the DLE window exhibited the highest classification accuracy (average F1-score 0.87). Among the two phenology window combinations, the DLE-DLF and DLE-DLM windows have the highest classification accuracy (average F1-score 0.90). Among the three phenology window combinations, DLE-DLM-DLF displayed the highest classification accuracy (average F1-score 0.91). Nevertheless, the inclusion of features within the DDP window led to a decrease in accuracy by 1–2% points, which was unfavorable for discriminating tree species. Additionally, features observed during the phenology asynchrony period were found to be more valuable for distinguishing between tree species. Our findings highlight the potential of PlanetScope constellation imagery in tree species classification, offering guidance for selecting optimal image acquisition timing and identifying the most valuable images within time series data for future large-scale tree mapping. Full article

The Huangshui River Basin is located in the transition zone between the Loess Plateau and the Qinghai–Tibet Plateau, characterized by a fragile hydrological and ecological environment. Groundwater serves as a vital water source for local economic development and human livelihood. With the acceleration of urbanisation and climate change, groundwater resources face challenges such as pollution and over-exploitation. This study employs an improved DRASTIC model, tailored to the characteristics of the groundwater system in the Huangshui River Valley of the upper Yellow River, to integrate groundwater resources, groundwater environment, and ecological environment systems. Improving the DRASTIC model for groundwater vulnerability assessment. A two-tiered evaluation system with nine indicator parameters was proposed, including six groundwater quality vulnerability indicators and five groundwater quantity vulnerability indicators. Fuzzy analytic hierarchy process and entropy weight method were used to determine the weights, and Geographic Information System (GIS) spatial analysis was employed to evaluate groundwater vulnerability in the Huangshui River basin in 2006 and 2021. The results indicate that the proportion of areas with high groundwater quality vulnerability increased from 10.7% in 2006 to 31.57% in 2021, while the proportion of areas with high groundwater quantity vulnerability decreased from 22.33% to 14.02%. Overall, groundwater quality vulnerability in the Huangshui River basin is increasing, while groundwater quantity vulnerability is decreasing. Based on the evaluation results of water quality and quantity vulnerability, protection zoning maps for water quality and quantity were compiled, and preventive measures and recommendations for water quality and quantity protection zones were proposed. Human activities have a significant impact on groundwater vulnerability, with land use types and groundwater extraction coefficients having the highest weights. This study provides a scientific basis for the protection and sustainable use of groundwater in the Huangshui River basin. Full article

Gully erosion, driven by the interplay of natural processes and human activities, results in severe soil degradation and landscape alteration, yet approaches for accurately quantifying erosion triggered by extreme precipitation using multi-source high-resolution remote sensing remain limited. This study first extracted digital surface models (DSM) for the years 2014 and 2024 using Ziyuan-3 and GaoFen-7 satellite stereo imagery, respectively. Subsequently, the DSM was calibrated using high-resolution unmanned aerial vehicle photogrammetry data to enhance elevation accuracy. Based on the corrected DSMs, gully erosion depths from 2014 to 2024 were quantified. Erosion patches were identified through a deep learning framework applied to GaoFen-1 and GaoFen-2 imagery. The analysis further explored the influences of natural processes and anthropogenic activities on elevation changes within the gully erosion watershed. Topographic monitoring in the Sandu River watershed revealed a net elevation loss of 2.6 m over 2014–2024, with erosion depths up to 8 m in some sub-watersheds. Elevation changes are primarily driven by extreme precipitation-induced erosion alongside human activities, resulting in substantial spatial variability in surface lowering across the watershed. This approach provides a refined assessment of the spatial and temporal evolution of gully erosion, offering valuable insights for soil conservation and sustainable land management strategies in the Loess Plateau region. Full article

Background/Objectives: Idiopathic intracranial hypertension (IIH) often features dural venous sinus stenosis; venous sinus stenting (VSS) improves venous outflow and intracranial pressure, but most stents are off-label, and few are engineered for intracranial venous anatomy. The aim was to synthesize animal models relevant to IIH/VSS, catalogue stents used clinically for VSS and summarize corresponding animal data, appraise current preclinical VSS research, and propose a pragmatic preclinical evaluation framework. Methods: We performed a targeted search (PubMed, Web of Science, Scopus; through to May 2025), dual-screened the records in Nested Knowledge, and extracted the model/device characteristics and outcomes as per the predefined criteria. Results: We identified 65 clinical VSS studies; most were retrospective and used off-label carotid/peripheral/biliary stents (Precise, Zilver, and Wallstent were the most frequent). Recent dedicated systems (River, BosStent) have limited animal evidence; VIVA has GLP porcine venous peripheral data demonstrating its patency, structural integrity, and benign healing outcomes. Rodent models reproduce obesity/androgen drivers with modest, sustained ICP elevation; large animal models show the technical feasibility of in sinus implantation, but no chronic focal venous stenosis model fully mirrors the IIH condition. Conclusions: Despite broad clinical uptake, the translational underpinnings of VSS in IIH remain incomplete: most devices lack intracranial venous-specific preclinical validation, and there is no existing animal model that recapitulates both IIH biology and focal sinus stenosis. Full article

Coasts are critical ecological, economic and social interfaces between terrestrial and marine systems. The current upsurge in the acquisition and availability of remote sensing datasets, such as Landsat remote sensing data series, provides new opportunities for analyzing multi-decadal coastal changes and other components of coastal risk. The emergence of machine learning-based techniques represents a new trend that can support large-scale coastal monitoring and modeling using remote sensing big data. This study presents a comprehensive multi-decadal analysis of coastal changes for the period from 1990 to 2024 using Landsat remote sensing data series along the eastern and southern coasts of Peninsular Malaysia. These coastal regions include the states of Kelantan, Terengganu, Pahang, and Johor. An innovative approach combining deep learning-based shoreline extraction with the Digital Shoreline Analysis System (DSAS) was meticulously applied to the Landsat datasets. Two semantic segmentation models, U-Net and DeepLabV3+, were evaluated for automated shoreline delineation from the Landsat imagery, with U-Net demonstrating superior boundary precision and generalizability. The DSAS framework quantified shoreline change metrics—including Net Shoreline Movement (NSM), Shoreline Change Envelope (SCE), and Linear Regression Rate (LRR)—across the states of Kelantan, Terengganu, Pahang, and Johor. The results reveal distinct spatial–temporal patterns: Kelantan exhibited the highest rates of shoreline change with erosion of −64.9 m/year and accretion of up to +47.6 m/year; Terengganu showed a moderated change partly due to recent coastal protection structures; Pahang displayed both significant erosion, particularly south of the Pahang River with rates of over −50 m/year, and accretion near river mouths; Johor’s coastline predominantly exhibited accretion, with NSM values of over +1900 m, linked to extensive land reclamation activities and natural sediment deposition, although local erosion was observed along the west coast. This research highlights emerging erosion hotspots and, in some regions, the impact of engineered coastal interventions, providing critical insights for sustainable coastal zone management in Malaysia’s monsoon-influenced tropical coastal environment. The integrated deep learning and DSAS approach applied to Landsat remote sensing data series provides a scalable and reproducible framework for long-term coastal monitoring and climate adaptation planning around the world. Full article

The Athabasca River flows through the Lower Athabasca Region (LAR) in Alberta, Canada, which is characterized by variable inter-annual weather, long winters and short summers. LAR is important for the extraction of energy resources and industrial activities that lead to environmental concerns, including river pollution and exploitation. This study attempts to forecast the Athabasca River at Fort McMurray and understand the suitability of HEC-HMS (Hydrologic Engineering Center-Hydrologic Modeling System) in cold weather regions, characterized by poorly gauged streams. Daily temperature and precipitation records (1971–2014) were employed in two calibration–validation schemes: (1) a temporally dependent partition (1971–2000 for calibration; 2001–2014 for validation) and (2) a temporally independent partition (alternating years assigned to calibration and validation). The temporally independent approach achieved superior performance, with a Nash–Sutcliffe efficiency of 0.88, outperforming previously developed regional models. HEC-HMS successfully reproduced hydrologic dynamics and peak discharge events under conditions of sparse hydroclimatic data and limited computational inputs, underscoring its robustness for operational forecasting in data-scarce, cold-climate catchments. However, long-term projections may be subject to uncertainty due to the exclusion of anticipated changes in land use and climate forcing. These results substantiate the applicability of HEC-HMS as a cost-effective and reliable tool for hydrological modeling and flow forecasting in support of water resource management, particularly in regions subject to industrial pressures and associated environmental impacts. Full article

Soil salinization poses a severe threat to agricultural sustainability in the Yellow River Delta, where conventional spectral indices are limited by vegetation interference and seasonal dynamics in coastal saline-alkali landscapes. To address this, we developed an inversion framework integrating spectral indices and vegetation temporal features, combining multi-temporal Sentinel-2 optical data (January 2024–March 2025), Sentinel-1 SAR data, and terrain covariates. The framework employs Savitzky–Golay (SG) filtering to extract vegetation temporal indices—including NDVI temporal extremum and principal component features, capturing salt stress response mechanisms beyond single-temporal spectral indices. Based on 119 field samples and Variable Importance in Projection (VIP) feature selection, three ensemble models (XGBoost, CatBoost, LightGBM) were constructed under two strategies: single spectral features versus fused spectral and vegetation temporal features. The key results demonstrate the following: (1) The LightGBM model with fused features achieved optimal validation accuracy (R² = 0.77, RMSE = 0.26 g/kg), outperforming single-feature models by 13% in R². (2) SHAP analysis identified vegetation-related factors as key predictors, revealing a negative correlation between peak biomass and salinity accumulation, and the summer crop growth process affects soil salinization in the following spring. (3) The fused strategy reduced overestimation in low-salinity zones, enhanced model robustness, and significantly improved spatial gradient continuity. This study confirms that vegetation phenological features effectively mitigate agricultural interference (e.g., tillage-induced signal noise) and achieve high-resolution salinity mapping in areas where traditional spectral indices fail. The multi-temporal integration framework provides a replicable methodology for monitoring coastal salinization under complex land cover conditions. Full article

Rivers, vital for life and civilizations, face severe threats from human activities such as hydropower development, with heavy metal pollution emerging as a critical concern due to altered biogeochemical cycles. Understanding how river damming affects heavy metal transport processes and developing targeted remediation strategies are essential for safeguarding the health of river-reservoir ecosystems and enabling the sustainable utilization of hydropower resources. Therefore, this review first summarizes the global hydropower development, details how damming disrupts hydrology, environments, and ecosystems, and analyzes heavy metal distribution and transport in reservoir water, suspended sediments, and riverbed sediments. It reveals that river damming promotes heavy metal adsorption onto suspended particles, deposition in riverbed sediments, and re-release during reservoir regulation, and anthropogenic activities are a primary driver of significant pollution in key reservoirs worldwide. Additionally, we further evaluate in situ (e.g., stabilizing agents, sediment capping, and phytoremediation) and ex situ (e.g., dredging, chemical washing, electrochemical separation, and ultrasonic extraction) remediation techniques, highlighting the challenges of phytoremediation in deep, stratified reservoir environments. Moreover, solidification/stabilization emerges as a promising in situ strategy, emphasizing the need for specific approaches to balance pollution control with hydropower functionality in dammed river systems. Full article