Search Results (1,293)

Pollution of rivers and large water bodies, including reservoirs, by wastewater from various sources is one of the most critical issues in the Donetsk region, requiring continuous monitoring and assessment of surface water quality. The research aims to assess the state of the Kalmius River under anthropogenic pressure, as well as to find correlations between the species composition, photosynthetic activity of phytoplankton, and the degree of water pollution. This study presents the results of biomonitoring of the Kalmius River and its tributaries within Donetsk City, which are under intense anthropogenic pressure. Pollution of the river channel by phenol, anionic surfactants, Ferrum ions, chlorides, and sulfates was identified. Based on the combinatorial pollution index, the water in the Kalmius River and its tributaries can be classified as polluted. The pigment composition of water samples was analyzed, and the species composition of river phytoplankton was determined. Dominant species include Chlorella vulgaris Beij., Dictyosphaerium pulchellum H.C.Wood, Scenedesmus quadricauda Brébisson, and Oscillatoria agardhii M.A.Gomont. Photosynthetic activity of the river’s algal flora was assessed based on chlorophyll fluorescence induction curves of natural phytoplankton. A correlation was established between surface water pollution levels and changes in the photosynthetic apparatus of microalgae cells. A strong negative correlation was found between the content of nitrate nitrogen in the aquatic environment and the photosynthetic activity, pigment composition, and abundance of the main dominant forms of phytoplankton, particularly the microalgae of the genus Cyclotella. The data obtained shows that the Kalmius River’s pollution has a significant impact on phytoplankton biodiversity, leading to the growth of cyanobacteria species. Full article

Accurate landslide susceptibility assessment remains challenging in mountainous regions with complex terrain, heterogeneous geology, and clustered landslide inventories. This study develops a slope–unit–based landslide susceptibility assessment framework for Tongren County, Qinghai Province, China, using a landslide inventory of 217 events, multi–source environmental data, Certainty Factor (CF)–based conditioning–factor analysis, and machine learning models. Eighteen conditioning factors derived from remote sensing, geological survey, and meteorological datasets were extracted at the slope–unit scale, and their collinearity was evaluated using Pearson’s correlation and the Variance Inflation Factor (VIF). Eight models—Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), AdaBoost, Decision Tree (DT), XGBoost, K–Nearest Neighbors (KNN), and Convolutional Neural Network (CNN)—were evaluated under a 70:30 train/test split. The results show clear performance differences among the tested models: SVM achieved the best overall balance between discrimination and landslide detection (AUC = 0.9489; recall = 0.879). The tested CNN baseline showed relatively weak performance under the current slope–unit–based tabular–data setting. Susceptibility zoning results showed that high– and very–high–susceptibility zones were mainly concentrated along the Longwu River and its tributaries, where middle–elevation dissected terrain, weak lithological materials, river–valley erosion, and human engineering activities spatially coincide. These results provide a practical basis for slope monitoring and land–use planning in Tongren County. Full article

Selenium plays a crucial role in estuarine biogeochemistry, balancing essential nutrient functions with potential environmental toxicity. This study examines the seasonal distribution of dissolved Se species, including volatiles, in the Adour estuary in relation to anthropogenic influences. To characterize major Se inputs from upstream watersheds to downstream tributaries, water samples were collected at low tide during three different seasons in upstream freshwaters, industrial/urban effluents and downstream estuarine waters. A tidal-cycle sampling campaign was conducted under low discharge conditions to assess Se dynamics during downstream estuarine mixing. Total dissolved Se (TDSe) concentrations ranged from 71 (pristine river) to 656 ng L⁻¹ (industrial/urban-impacted tributaries). TDSe correlated strongly with nitrate (r = 0.84) in upstream waters, indicating significant agricultural and livestock contributions at the watershed scale. Selenate was the dominant species, followed by Se(-II+0) fraction and selenite. Volatile Se compound concentrations varied from 51 to 2757 pg L⁻¹. Seasonal changes suggest that Se speciation is mainly controlled by watershed inputs derived from land use (agricultural and livestock practices) rather than downstream estuarine inputs. This speciation study further indicates that Se reactivity/bio-availability in estuarine systems can be largely influenced by anthropogenic activities, although further characterization of the aqueous reduced Se fraction is still needed. Full article

Water scarcity is an increasingly pressing global concern, making the sustainable development of water resources a critical priority. Revered as the “Sacred Sea,” Lake Baikal holds the largest volume of freshwater in any single lake in the world, with exceptional water quality, conferring it with considerable global strategic importance. This study reviews the hydrological dynamics of Lake Baikal, including water level fluctuations and runoff patterns, and examines water resource utilization (including virtual water and long-distance diversion), along with its potential, challenges, and associated ecological risks, in an integrated manner. Previous studies reveal an interannual cycle of fluctuating water levels, with annual peaks typically occurring between September and October. Outflow runoff closely depends on lake water levels, while inflow runoff exhibits considerable variability. The Selenga River, the largest tributary originating from the Mongolian Plateau, significantly influences the lake’s hydrology and ecological integrity. Current water uses primarily include domestic supply, regional industry, and fisheries, while agricultural water use is relatively limited and mainly occurs within tributary catchments. Emerging options, such as virtual water trade, may offer relatively more manageable alternatives to large-scale transboundary water transfers in certain contexts. Given the multiple disturbances and potential impacts on the Lake Baikal ecosystem, this study advocates prioritizing ecological protection in water resource utilization and underscores the necessity of comprehensive, system-level assessments prior to any water extraction or diversion activities. Full article

Conventional physicochemical parameter-based monitoring fails to provide real-time early warning of microbial risks in drinking water sources, highlighting the critical necessity to unravel the inherent associations between microbial activity and water quality dynamics. This study integrated a domestically developed microbial enzymatic analyzer with multivariate analyses to assess real-time microbial activity in a complex reservoir. Measurements of microbial indicators and physicochemical parameters were conducted at eight sites during dry and wet seasons, plus six months of continuous monitoring at a polluted tributary site. Key findings: (1) Water quality showed clear spatiotemporal variation, worse in the wet season than the dry season, with tributaries more polluted than mainstream, and downstream better than upstream; (2) Microbial activity exhibited spatial heterogeneity, with a significant positive correlation between E. coli and Enterococcus (EC); (3) Microbial activity responded to key water quality indicators, and both E. coli and EC correlated positively with NH₃-N. EC also correlated positively with TP. In summary, this study reveals a mechanism-based link between microbial activity and key water quality parameters, providing a theoretical foundation for a microbial-response-centered early warning model. This marks a shift from conventional reactive monitoring to proactive risk management for drinking water safety, offering a new paradigm with ecological indication and practical value. Full article

Acid mine drainage is an important source of heavy metal contamination in mining watersheds, posing persistent risks to aquatic environments and sediment quality. This study evaluated heavy metal pollution in water and sediments of the acid mine drainage-impacted Xiaomi Creek watershed, China. A total of 20 water samples and 13 sediment samples were collected and analyzed for manganese (Mn), lead (Pb), copper (Cu), cadmium (Cd), aluminum (Al), nickel (Ni), iron (Fe), and zinc (Zn). Water pollution was assessed using the single-factor exceedance index and the Nemerow composite pollution index, whereas sediment contamination was evaluated using the geoaccumulation index and potential ecological risk index. The results showed that water in the Xiaomi Creek watershed spanned a broad pH range (3.16–8.05), and heavy metal pollution was generally more severe in the main channel than in the tributaries, indicating a clear influence of upstream pollution inputs. Nickel showed the strongest enrichment in sediments and posed the highest ecological risk among the investigated metals, while Mn, Pb, Zn, and Ni exhibited severe sediment contamination. Overall, upstream stone coal mining activities and associated waste piles were likely major contributors to heavy metal pollution in the watershed, highlighting the need for source control, sediment-associated risk management, and risk-prioritized monitoring to support sustainable watershed management. Full article

The Devene fault system, a major strike–slip structure at the boundary between the Balkan Range and the Moesian Platform in NW Bulgaria, remains a subject of debate regarding its Quaternary activity. This study investigates the shallow expression of the fault at two representative sites, Tri Kladentsi and Beli Breg, using high-resolution electrical resistivity profiling to differentiate tectonic deformation from climatically driven landscape evolution. At Tri Kladentsi, resistivity profiles confirm a steeply dipping structural boundary within the Miocene bedrock, juxtaposing limestone against sands. The overlying 25 m thick loess cover, however, remains sub-horizontal and undisturbed. Likewise, at Beli Breg, the complex architecture of stacked channel sequences and tributary deposits at the Ogosta River confluence reveals no identifiable fault displacement. Our results suggest a high degree of morphological mimicry, where asymmetric river valleys produced by selective erosion and differential loess accumulation superficially converge with tectonic signatures. The long-term left-lateral slip rate is estimated at 0.14–0.19 mm/yr based on a 20 km Miocene offset. Nevertheless, the lack of modern surface rupture indicates a deceleration of the fault slip rate and a transition to a buried fault top during the Quaternary. These findings necessitate a re-evaluation of regional seismic hazard assessments, because the absence of continuous surface traces physically constrains the maximum earthquake potential. Full article

River sediment microbial communities are an integral part of fluvial ecosystems, where they play a central role in nutrient cycling. Although these communities share a core group of microorganisms, their overall composition can be influenced by natural environmental conditions and anthropogenic factors. While anthropogenic influences on river microbial communities have been extensively studied, natural drivers have received comparatively less attention. In this study, we evaluated the impact of tributary inflow on the microbial assemblages of a main river stem. Sediment samples were collected from both the main channel and some of its tributaries, and bacterial community composition was characterized using 16S rRNA gene amplicon sequencing. Taxonomic profiling revealed a largely shared core community typical of riverine sediments across all sites. While alpha diversity did not differ significantly between main river and tributary samples, beta diversity analyses demonstrated clear segregation between the two environments, indicating distinct community structures. Correlation analyses further showed that microbial assemblages in the main river downstream of tributary confluences were significantly associated with tributary community composition, highlighting the influence of tributary inflow on bacterial communities in the main river. Full article

A novel procedure is proposed in this paper to investigate the capacity of parking structures to resist additional live loads that could come from many cars, potentially from heavier or driverless cars. In recent decades, the typical operating weight of passenger vehicles has risen significantly. The anticipated widespread adoption of electric vehicles (EVs), which contain heavy battery systems, may further increase live load demands. As a result, a new robust procedure is needed to assess the live load effects on parking structures. Hence, using the proposed innovative approach based on 3D influence surfaces, tributary areas (AT) and three-dimensional influence surfaces (AI) were calculated (for the first time) to examine the equivalent uniformly distributed load corresponding to selected column axial loads and beam midspan moments that are expected to be experienced during the lifetime of parking structures. As case studies, the responses of two existing multistory parking garages on the Ohio State University campus were investigated under different arrangements of two car types—standard cars and sports utility vehicles (SUVs)—and the calculated maximum live loads were compared with the current code requirements. The results show that the maximum live load for the midspan moment is conservative; however, the maximum axial column loading in the extreme scenarios presented in this paper can be larger than the specified (original) design limit of the selected parking garages. The novel methodology proposed in this paper is based on 3D influence line analysis and can be applied for any vehicle configuration and weight, and different parking arrangements or loading scenarios to investigate the performance of parking garages. Full article

Accurate measurement of streamflow is fundamental for water resources management, ecological conservation, flash flood early warning, and climate change impact studies. This study presents a proof of concept on the usage of Internet of Things (IoT) for automatic streamflow measurements using commercial off-the-shelf (COTS) hardware. The system is designed, implemented, and experimentally evaluated as a low-cost, solar-powered IoT device tailored to small-order streams and headwater tributaries. At its core is the Hall-effect YF-S201 flow sensor. Although primarily designed for closed-conduit applications, the sensor was tested in a controlled setup where stream water was diverted into a short pipe section, enabling continuous monitoring and calibration. This paper provides details on the design and validation of a low-cost (approximately 24 Euros), solar-powered streamflow measurement system based on a water flow sensor, using wireless communications, and cloud storage based on an ESP32 board, PostgreSQL, and a web interface. The device was tested in a simulated environment. Results indicate the proposed device reliably tracks flow variability, while offering portability, energy autonomy, and cost efficiency, and may serve as a feasible alternative for low-infrastructure, temporary deployments. Full article

To understand the distribution characteristics of the fish community and evaluate the effectiveness of the Yangtze River fishing ban, this study selected the Fuhe River (an important tributary of the Yangtze River) as the research area. A total of 30,892 fish (belonging to seven orders, 20 families, and 92 species) were captured in the upper and middle reaches of the Fuhe River from 2022 to 2024. Among them, the Cypriniformes order accounted for the largest proportion, with nine families and 66 species, making up 71.74% of the total number of fish. According to the relative importance index, Carassius auratus was the dominant species for each sampling period and each sampling area. Moreover, the number of dominant species in the main streams was significantly higher than that in the tributaries, while the diversity of the fish community in the tributaries was significantly greater than that in the main streams. Additionally, ANOSIM revealed significant spatial differences in the fish community (p < 0.01). Cluster and NMDS analyses further divided the fish community into three groups. SIMPER indicated that the typical species of each group of fish community were basically the dominant species within that community. Furthermore, RDA indicated that potassium permanganate, ammonia nitrogen, total phosphorus, and chlorophyll a were the main water environmental factors affecting the fish community structure. Compared to the fish community before the fishing ban, the stability of the fish communities during the initial stage of the fishing ban was significantly improved, and the number of fish species also increased. Therefore, the fishing ban was beneficial for enhancing the diversity and stability of the fish community. However, compared with the composition of fish species before the fishing ban, a certain number of fish species in the upper and middle reaches of the Fuhe River were still not collected during the early stage of the fishing ban. Therefore, the ten-year fishing ban in the Yangtze River still needs to be continued and implemented. Full article

Accurate spatial identification of check dams is a key prerequisite for evaluating soil and water conservation benefits and optimizing dam system planning on the Loess Plateau. Current deep learning models face severe misclassification and omission issues under complex terrain due to the scarcity of check dam samples and the lack of prior geographic knowledge. This study proposes a recognition method based on Faster R-CNN, constrained by suitable areas and microtopography. The Xiliugou watershed in Inner Mongolia was selected as the study area. Based on Google Earth imagery and field survey data, a check dam sample dataset was constructed, integrating the morphological features of “linear dam body with a trapezoidal slope.” Using the construction suitable area constraints defined by the Technical Specifications for Check Dams and microtopography standard deviation (δ) derived from DEM as dual spatial filtering mechanisms, these were deeply embedded into the Faster R-CNN model to limit the search space and enhance geographic plausibility. Experimental results show that the constrained Faster R-CNN model achieved a precision and recall of 92.86% and 96.89%, compared with the accuracy rate of only deep learning model recognition (60.61%), which significantly increased by 32.25%, indicating that geographical constraints have an enhancing effect. Using this method, a total of 191 embankment dams were identified in the Xiliugou Basin. New 30 unrecorded embankment dams (21 small dams and 9 micro-dams) were discovered. The model’s good generalization ability was verified in the Han Tiechuan geographical isolation area, which contained 153 embankment dam samples, with an accuracy rate of 72.94%. Spatial analysis further revealed the “successive interception along tributaries” distribution pattern and strong spatial aggregation characteristics (box dimension D ≈ 0.36) of check dams in the Xiliugou watershed. This study confirms the critical role of suitable area and microtopography constraints in improving the accuracy and reliability of deep learning models and provides a transferable technical paradigm for automated, high-precision surveys of regional soil and water conservation projects. Full article

Reconciling hydropower development with aquatic biodiversity conservation is a central challenge for sustainable river management worldwide. Cascade dam configurations, in which multiple impoundments are arranged in series along a single channel, impose longitudinal environmental gradients that restructure biological communities across trophic levels. Whether the resulting multi-trophic responses are independently driven by shared abiotic gradients (environmental filtering) or mechanistically coupled through direct food-web interactions (trophic cascading) remains unresolved. We surveyed phytoplankton, zooplankton, and benthic macroinvertebrates simultaneously at seven stations along a 430 km gradient downstream of Danjiangkou Dam in the Hanjiang River, the largest tributary of the Yangtze River and the source of China’s South-to-North Water Diversion Middle Route, over eight seasonal campaigns (2015–2017). Variance partitioning, piecewise structural equation modeling, Mantel tests, and co-occurrence network analysis were applied to partition environmental and trophic pathways. Environmental filtering dominated community restructuring at all three trophic levels, while the biotic proxy for direct trophic interactions explained less than 0.4% of community variation, consistent with weak detectable trophic coupling at seasonal resolution. Distance from Danjiangkou Dam shaped downstream transparency and turbidity gradients that mediated trophic-level-specific responses along distinct environmental axes (pH and water temperature for phytoplankton, conductivity for zooplankton, and transparency for benthic macroinvertebrates). Benthic macroinvertebrates were systematically decoupled from the pelagic analytical framework, absent from the cross-trophic co-occurrence network and structured more by spatial configuration than by water-column variables. Hub species in the network were associated with downstream mineralized conditions, confirming that network architecture reflects shared environmental preferences rather than biotic interactions. These findings support a management shift from single-dam mitigation toward cascade-scale coordination of environmental flow regimes, sediment connectivity, and substrate restoration as integrated strategies for sustaining multi-trophic biodiversity in regulated rivers. Full article

Global freshwater scarcity is a pressing environmental challenge, particularly in Egypt, which depends entirely on the Nile River and its tributaries. Rapid population growth, domestic wastes, agricultural runoff, and rapid industrial expansion exert highly anthropogenic stress on aquatic ecosystems, including Bahr Yusuf and Ibrahimia Canals in Upper Egypt. This study aimed to evaluate the ecological health and sustainability status of the two canals using an integrated multi-metric framework combining physicochemical variables, microbiological indicators, and community structures of zooplankton and benthic fauna. Multivariate statistical analyses (PCA, CCA), and ecological indices, including the water quality index (WQI), microbial assessment index (MAI), Rotifer-Based Index (TSI_Rot) and Hilsenhoff Biotic Index, were applied to determine pollution gradients. The results revealed that Bahr Yusuf suffers from higher pollution levels than the Ibrahimia Canal. Canonical correspondence analysis (CCA) showed that nutrient enrichment and elevated organic load are responsible for over 72% of the variance in zooplankton and benthic invertebrate assemblage in both water bodies. The dominance of pollution-tolerant species, Philodina roseola and B. calyciflorus of zooplankton and Limnodrilus udekemianus, Chironomidae larvae, Melanoides tuberculate and Cleopatra bulimoides of benthic taxa, further indicates a direct increase in organic loading and nutrient enrichment from agricultural and domestic sources. According to the Integrated Water Quality–Biotic Health Index (IWQ-BHI), the downstream stations of Bahr Yusuf are critical risk zones, with scores below 50.0, while the upstream stations of Ibrahimia Canal fell within the “good” category, with scores exceeding 70.0. Overall, both waterbodies are approaching a critical threshold of ecological instability and require urgent, integrated and sustainable management to restore and preserve these vital freshwater ecosystems. Full article

The Kupa River (Croatia), a tributary of the Danube basin forming part of the Slovenian border, was heavily contaminated with polychlorinated biphenyls (PCBs) between 1962 and 1985 due to improper handling and downstream transport via the Krupa and Lahinja rivers. This study evaluated the occurrence, interspecific distribution, and human health implications of PCBs and polycyclic aromatic hydrocarbons (PAHs) in fish (Northern pike, Common carp, Grass carp, Pike-perch, Wels catfish, Bream, and Chub) from the Croatian Kupa River. PCB concentrations were consistently higher than PAH levels across all species. In 30% of samples, Σ6 non-dioxin-like PCBs exceeded the European Commission maximum permissible level for freshwater fish (125 ng⋅g⁻¹ wet weight). Of the 11 PAHs analyzed, only fluoranthene and pyrene were detected. Self-Organizing Map identified distinct pollutant patterns, with chub showing the highest variability and accumulation. PCB concentrations position the Kupa River among moderately to highly impacted European freshwater systems affected by legacy industrial contamination. Health risk assessment, incorporating updated national consumption data, indicates that long-term, uncontrolled consumption of Kupa River fish may pose risks due to PCB exposure, while PAH-related risks appear negligible. These findings highlight the persistence of legacy PCB pollution and the need for integrated sediment–biota monitoring. Full article