Search Results (5,622)

In recent years, human activities have impacted surface water and groundwater and their interactions with natural water bodies. Lake Cuitzeo is one of Mexico’s most important water bodies but has significantly reduced its flooded area in recent years. Previous studies did not explicitly evaluate the combined effects of hydrological variables on lake dynamics, limiting the understanding of how basin-scale processes influence lake-level. The objective of this study is to evaluate the change in spatio-temporal patterns of hydrological variables under climatic and anthropogenic stress in the Lake Cuitzeo endorheic basin. The proposed methodology uses the SWAT model to analyze at the basin scale, land use and land cover changes, and trends in precipitation and their effect on hydrological processes. Consequently, groundwater flow interactions were assessed for the first time for the Cuitzeo Lake Basin using an automatically coupled SWAT-MODFLOW (v3, 2019), despite limited observational data. A statistically significant change in mean precipitation was detected beginning in 2015, with a decrease of 10.22% compared to the 1973–2014 mean. Land use and land cover changes between 1997 and 2013 resulted in a 26.20% increase in surface runoff. In contrast, estimated evapotranspiration decreased by 1.77%, potentially associated with the reduction in forest cover. As a combined effect of decreased precipitation and land use and land cover change, groundwater percolation declined by 6.34%. Overall, the combined effects of climatic variables and anthropogenic activities have altered lake–aquifer interaction. Full article

In temperate freshwater ecosystems, zooplankton play a crucial role in the pelagic food web and act as sensitive indicators of environmental change. They respond to shifts in water temperature, hydrodynamic mixing, and short-term meteorological events. This study investigated the epilimnetic zooplankton fauna of Lake Karamurat (Bolu, Türkiye), a small tectonic temperate lake, with a specific focus on the influence of rainfall events and wind speed on community structure. The samples were taken seasonally and horizontally using a plankton net (55 µm mesh size) and were analyzed alongside in situ physico-chemical measurements and meteorological data. In total, 74 zooplankton taxa were identified, comprising 54 rotifer species and 20 crustacean species (16 Cladocera and 4 Copepoda). Testudinella greeni was recorded for the first time in Türkiye, representing a new addition to the Turkish Rotifera fauna. Multivariate analyses revealed that electrical conductivity, water temperature, dissolved oxygen, precipitation, and wind speed were key drivers shaping community composition. The findings suggest that wind-driven surface mixing and episodic rainfall events enhanced vertical redistribution, leading to dominance of rotifers and small-bodied cladocerans in the epilimnion. These findings underscore the critical role of sampling strategy in shallow lakes under dynamic conditions and provide new faunistic insights into the zooplankton diversity of Anatolian lakes. Full article

The nitrogen-to-phosphorus ratio (TN:TP) is a key indicator influencing phytoplankton nutrient limitation and growth dynamics, directly regulating algal growth rates, abundance, and community structure, thereby affecting the process of water eutrophication. This study aims to evaluate the modeling performance of integrated machine learning approaches for lake total nitrogen to total phosphorus ratios (TN:TP), utilizing Zhuhai-1 hyperspectral satellite imagery to develop a CNN-SVR ensemble model integrating convolutional neural networks and support vector regression for remote sensing inversion of lake TN:TP ratios. Performance is evaluated against random forest (RF) and convolutional neural network (CNN) models, systematically analyzing spatial distribution patterns and primary drivers. Results indicate that the CNN-SVR model demonstrated superior performance among the tested models, with R², RMSE, MAPD, and RPD values of 0.856, 2.675, 9.516%, and 2.390, respectively. Spatially, the nitrogen-to-phosphorus ratio in lakes during the growing season exhibits an increasing trend from the western to the eastern half of the lake, progressing from northwest to southeast. When TN:TP falls below 9, algal growth becomes nitrogen-limited, indicating a higher degree of eutrophication; when TN:TP exceeds 22.6, phosphorus becomes the limiting factor, indicating lower eutrophication levels. A similar distribution pattern is observed during the non-growing season. Regarding driving mechanisms, the nitrogen-to-phosphorus ratio during the growing season is primarily influenced by TN accumulation and shows significant correlations with dissolved oxygen (DO) and pH. During the non-growing season, while still affected by TN input, its association with other water quality parameters is weaker. The results indicate that the combined use of CNN and SVR improves feature extraction and model fitting in nitrogen-to-phosphorus ratio inversion and helps clarify its ecological significance as an indicator of algal growth. This provides methodologies and evidence for precise diagnosis and ecological management of lake eutrophication. Full article

This study examined the effects of pollution from the Shituru hydrometallurgic complex on the Upper Lufira Basin, Democratic Republic of the Congo, between September 2015 and September 2017. Physico-chemical water variables and trace metal elements in water and sediment, as well as diversity and infection parameters of monopisthocotylan parasites infesting Clarias ngamensis, were assessed at three sites: the Lufira River, Panda River, and Lake Tshangalele. We hypothesised that low pollution would correlate with greater ectoparasite species richness and higher infection parameters. Results indicated severe ecological degradation in the highly polluted Panda River (with high concentrations of TMEs; e.g., 510.830 ± 0.86; 82.470 ± 0.200 µg/L for Co²⁺ and Cu²⁺ in water; 15,771 ± 7068 and 1585 ± 1450 µg/g for Cu²⁺ and Zn²⁺ in the sediment), where neither fish nor parasites were present. Across the other sites, eight parasite species were identified. Seven species occurred on fish from the slightly polluted Lufira River (mean intensity (MI) of 31.28 ± 28.95 parasites per infested fish), while five were found in Lake Tshangalele (MI: 3.23 ± 2.89 parasites per infested fish), confirming the hypothesis. Three species, Quadriacanthus halajiani, Q. domatanai, and Macrogyrodactylus clarii, demonstrated potential as sensitive bioindicators of aquatic pollution in the region. Full article

Accurate estimation of Total Phosphorus, referred to as “Phosphorus, Total” (PPUT; µg/L) in the sourced monitoring data, is essential for understanding eutrophication dynamics and guiding water-quality management in inland lakes. However, lake-wide PPUT mapping at high resolution is challenging to achieve using conventional in-situ sampling, and nearshore gradients are often poorly resolved by medium- or low-resolution satellite sensors. This study exploits multi-generation PlanetScope imagery (Dove Classic, Dove-R, and SuperDove; 3–5 m, near-daily revisit) to develop a hybrid AI framework for PPUT retrieval in Lake Simcoe, Ontario, Canada. PlanetScope surface reflectance, short-term meteorological descriptors (3 to 7-day aggregates of air temperature, wind speed, precipitation, and sea-level pressure), and in-situ Secchi depth (SSD) were used to train five ensemble-learning models (HistGradientBoosting, CatBoost, RandomForest, ExtraTrees, and GradientBoosting) across eight feature-group regimes that progressively extend from bands-only, to combinations with spectral indices and day-of-year (DOY), and finally to SSD-inclusive full-feature configurations. The inclusion of SSD led to a strong and systematic performance gain, with mean R² increasing from about 0.67 (SSD-free) to 0.94 (SSD-aware), confirming that vertically integrated optical clarity is the dominant constraint on PPUT retrieval and cannot be reconstructed from surface reflectance alone. To enable scalable SSD-free monitoring, a knowledge-distillation strategy was implemented in which an SSD-aware teacher transfers its learned representation to a student using only satellite and meteorological inputs. The optimal student model, based on a compact subset of 40 predictors, achieved R² = 0.83, RMSE = 9.82 µg/L, and MAE = 5.41 µg/L, retaining approximately 88% of the teacher’s explanatory power. Application of the student model to PlanetScope scenes from 2020 to 2025 produces meter-scale PPUT maps; a 26 July 2024 case study shows that >97% of the lake surface remains below 10 µg/L, while rare (<1%) but coherent hotspots above 20 µg/L align with tributary mouths and narrow channels. The results demonstrate that combining commercial high-resolution imagery with physics-informed feature engineering and knowledge transfer enables scalable and operationally relevant monitoring of lake phosphorus dynamics. These high-resolution PPUT maps enable lake managers to identify nearshore nutrient hotspots, tributary plume structures. In doing so, the proposed framework supports targeted field sampling, early warning for eutrophication events, and more robust, lake-wide nutrient budgeting. Full article

Japan has largely achieved the “first half” of SDG 6—universal access to safe drinking water and sanitation—through decades of intensive investment in water supply and sewerage systems, implementation of the Total Pollutant Load Control System, and stringent regulation of industrial effluents. National indicators show that coverage of safely managed drinking water and sanitation services is nearly 99%, and domestic statistics report high compliance rates for BOD/COD-based environmental standards in rivers, lakes, and coastal waters. Conversely, the “second half” of SDG 6 reveals persistent gaps: ambient water quality (6.3.2) remains at 57% (2023 data), while water stress (6.4.2) is at approximately 21.6%. Furthermore, SDG 6.6.1 shows that 3% of water basins are experiencing rapid changes in surface water area (2020 data), with ecosystems increasingly threatened by hypoxia in enclosed bays and climate-induced vulnerabilities. Drawing on global comparisons, this review synthesizes Japan’s progress toward SDG 6, elucidates the structural drivers for remaining gaps, and proposes policy pathways for a nature-positive water future. Using national statistics (1970–2023) and the DPSIR framework, our analysis confirms that improvements in BOD/COD compliance plateaued around 2002, reinforcing concerns that point-source measures alone are insufficient to address diffuse pollution, groundwater nitrate contamination, and emerging contaminants like PFAS. We propose six strategic directions: (1) climate-resilient water systems leveraging groundwater; (2) smart infrastructure renewal; (3) advanced treatment for emerging contaminants; (4) basin-scale IWRM enhancing transboundary cooperation; (5) data transparency and citizen engagement; and (6) scaled nature-based solutions (NbS) integrated with green–gray infrastructure. The paper concludes by outlining priorities to close the gaps in SDG 6.3 and 6.6, advancing Japan toward a sustainable, nature-positive water cycle. Full article

Glacier inventories are critical for monitoring glacier response to climate change, providing constraints for glacier modeling studies and for assessing the impacts of glacier retreat on ecosystems and human societies. In the Bhutanese Himalaya, an up-to-date glacier inventory and a systematic analysis of decadal-scale glacier changes is lacking. Here, we present three glacier inventories (1976, 1998, and 2024) for this region. Manual mapping of glacier outlines from multi-source satellite imagery and the Copernicus digital elevation model (DEM) are used to derive a glacier inventory with associated topographic attributes. We found that 1871 glaciers existed in this region in 1976, covering an area of 2297.07 ± 117.15 km². By 1998 this number had reduced to 1803 glaciers, covering 2106.99 ± 90.60 km². In 2024, only 1697 glaciers remained, covering 1584.18 ± 36.37 km². A total of 89 (1976–1998) and 435 (1998–2024) glaciers became extinct in the Bhutanese Himalaya during these two time periods, and glacier area decrease accelerated from ~0.38% yr⁻¹ to ~0.95% yr⁻¹. Lake-terminating glaciers retreated almost three times faster (~32.2 m yr⁻¹) than land-terminating (~10.4 m yr⁻¹) glaciers during the observation period. Debris-covered glacier area increased from 112.79 ± 11.50 km² in 1976 to 128.89 ± 10.50 km² in 2024. Glaciers on the South Bhutanese Himalaya (draining into Bhutan) experienced faster glacier retreat than the glaciers of the North Bhutanese Himalaya (draining into the Tibetan Autonomous Region). ERA5-Land reanalysis data show that summer decadal average temperature in this region increased by 0.003 °C yr⁻¹ between 1976 and 1998 and 0.020 °C yr⁻¹ between 1998 and 2024, with the increase in warming rate coinciding with accelerated glacier retreat after 1998. Our updated glacier inventories will be useful for assessments of global sea level change, mountain hazards, and water resources. Full article

The fish liver, as the main detoxification organ, is highly susceptible to xenobiotic exposure, often resulting in various hepatopathies. The cytochrome P450 system plays a central role in xenobiotic metabolism, with cytochrome P450 reductase (CYPOR) supplying the electrons required for CYP enzyme activity. This study aimed to evaluate the relationship between the ecological state of a reservoir and fish health, including CYPOR levels, through hematological, bacteriological, and histological analyses. Samples of water and fish were collected from 12 littoral sites of Lake Ladoga. A total of 1360 specimens of fish from carp (Cyprinidae) and perch (Percidae) families were examined. For histological examination and CYPOR level determination, we selected 40 specimens using a blind randomization method. This sample size was sufficient for statistical analyses. Hematological smears were stained with azure eosin; bacteriological cultures were grown on multiple media; liver samples were stained with hematoxylin and eosin and Sudan III. CYPOR levels in liver homogenates were measured by ELISA-test. Physical and hydrochemical analyses indicated a high pollution level in the littoral zones. Isolated bacterial species were non-pathogenic but exhibited broad antibiotic resistance. Hematological evaluation revealed erythrocyte vacuolization and anisocytosis. Histological analysis showed marked fatty degeneration in hepatocytes, indicating toxic damage. CYPOR concentrations ranged from 0.3–0.4 ng/mL in healthy fish to 5–6 ng/mL in exposed specimens, showing strong correlation between environmental influence and enzyme activity. These findings demonstrate the potential of CYPOR as a sensitive biomarker for biomonitoring programs. The integrated methodological approach provides a model for assessing aquatic ecosystem health and identifying zones requiring priority remediation. Full article

Coastal lakes require monitoring approaches that capture spatial and temporal variability beyond the limits of conventional in situ measurements. In this study, a SIGMaL framework (Satellite–In situ–GIS-multicriteria decision analysis (MCDA)–Machine Learning (ML)) was developed, a unified methodology that integrates in situ monitoring, GIS MCDA-derived water quality index (WQI), satellite imagery, and ML models for comprehensive coastal lake water quality assessment. A WQI, derived from a 12-month series of in situ measurements and environmental parameters, was used alongside four physicochemical parameters measured by a multiparameter probe. First, satellite reflectance from each sensor was used to train a set of nine regression models for modelling electrical conductivity (EC), turbidity, water temperature (WT), and dissolved oxygen (DO). Second, convolutional neural networks (CNNs) with spectral and temporal inputs were trained to classify WQI classes, enabling a cross-sensor evaluation of their suitability for lake water quality monitoring. Third, the trained CNNs were applied to generate WQI maps for a subsequent 12-month period without in situ data. Across all analyses, WQI-based models provided more stable and accurate models than those trained on raw parameters. Sentinel-2 achieved the most consistent WQI performance (AUC ≈ 1.00, R² ≈ 0.84), PlanetScope captured fine-scale spatial detail (R² ≈ 0.77), while Landsat 8–9 was most effective for WT but less reliable for multi-class WQI discrimination. Sentinel-2 is recommended as the primary satellite sensor for WQI mapping within the SIGMaL framework. These findings demonstrate the advantages of WQI-based modelling and highlight the potential of ML–remote sensing integration to support coastal lake water quality monitoring. Full article

To address the challenge of optimizing hydrological parameters for nitrogen pollution control in paddy polders, this study coupled the Stella eco-dynamics model with an external optimization algorithm and developed a nonlinear programming framework using the water surface ratio and inflow rate as decision variables and the maximum nitrogen removal rate as the objective function. The simulation and optimization conducted for the Hongze Lake polder area indicated that the model exhibited strong robustness, as verified through Monte Carlo uncertainty analysis, with coefficients of variation (CV) of nitrogen outlet concentrations all below 3%. Under the optimal regulation scheme, the maximum nitrogen removal rates (${\eta }_1$, ${\eta }_2$, and ${\eta }_4$) during the soaking, tillering, and grain-filling periods reached 98.86%, 98.74%, and 96.26%, respectively. The corresponding optimal inflow rates ($Q^{*}$) were aligned with the lower threshold limits of each growth period (1.20, 0.80, and 0.50 m³/s). The optimal channel water surface ratios ($A_1^{*}$) were 3.81%, 3.51%, and 3.34%, respectively, while the optimal pond water surface ratios ($A_2^{*}$) were 19.94%, 16.30%, and 17.54%, respectively. Owing to the agronomic conflict between “water retention without drainage” and concentrated fertilization during the heading period, the maximum nitrogen removal rate (${\eta }_3$) during this stage was only 37.34%. The optimal channel water surface ratio ($A_1^{*}$) was 2.37%, the pond water surface ratio ($A_2^{*}$) was 19.04%, and the outlet total nitrogen load increased to 8.39 mg/L. Morphological analysis demonstrated that nitrate nitrogen and organic nitrogen dominated the outlet water body. The “simulation–optimization” coupled framework established in this study can provides quantifiable decision-making tools and methodological support for the precise control and sustainable management of agricultural non-point source pollution in the floodplain area. Full article

Quality control of drinking water is essential for safeguarding public health, particularly in densely populated urban environments. Environmental microbiological monitoring can complement conventional surveillance by providing deeper insights into the dissemination of pathogens and antimicrobial resistance genes within aquatic systems. In this study, we assessed the quality of wastewater and treated water from two urban water supply systems, representing the southern and northern regions of Porto Alegre, Rio Grande do Sul, Brazil, across four climatic seasons between 2024 and 2025. Fifteen water samples were analyzed, including raw water from Guaíba Lake and treated water collected from public distribution points. The Water Quality Index was calculated, microbiological indicators were quantified, and carbapenem resistance genes were detected using molecular assays. Most treated water samples complied with established bacteriological standards; however, the bla_OXA-48-like gene was recurrently detected in both wastewater and treated water. No resistance genes were identified during the summer, whereas the bla_VIM gene was detected exclusively in spring samples. The presence of carbapenem resistance genes in the absence of cultivable coliforms suggests the persistence of extracellular DNA or viable but non-culturable bacteria, highlighting limitations inherent to conventional microbiological monitoring. Integrating classical microbiological methods with molecular assays enables a more comprehensive assessment of water quality and strengthens evidence-based decision-making within a One Health framework. Full article

Designing robust drinking water treatment schemes for eutrophic sources requires shifting from considering each treatment step separately to considering the full treatment process as a connected system. This study evaluated how treatment configuration and arrangement influence microbial community dynamics, organic carbon removal, and biological stability in a full-scale drinking water treatment plant. A Dutch treatment plant was monitored, operating two parallel lines: one conventional (coagulation, sedimentation, and rapid sand filtration) and one advanced (ion exchange, ceramic microfiltration, and advanced oxidation), both converging into granular activated carbon (GAC) filtration. Microbial and chemical water quality was assessed across treatment stages and seasons. This plant experiences periods of discoloration, taste, and odor issues, and an exceedance of Aeromonas counts in the distribution network. Advanced oxidation achieved a high bacterial cell inactivation (~90%); however, it significantly increased assimilable organic carbon (AOC) (300–900% increase), challenging biological stability. GAC filtration partially reduced AOC levels (from 70 μg Ac-C/L to 12 μg Ac-C/L) but also supported dense (10⁵ cells/mL) and diverse microbial communities (Shannon diversity index 5.83). Moreover, Gammaproteobacteria, which harbor opportunistic pathogens such as Aeromonas, persisted during the treatment. Archaea were highly sensitive to oxidative and physical stress, leading to reduced diversity downstream. Beta diversity analysis revealed that treatment configuration, rather than seasonality, governed the community composition. The findings highlight that treatment arrangement, oxidation, GAC operation, and organic and microbial loads critically influence biological stability. This study proposes integrated strategies to achieve resilient and biologically stable drinking water production when utilizing complex water sources such as eutrophic lakes. Full article

Thermal stability is a key factor in determining the phenomena of deep chlorophyll maxima (DCM) in stratified lakes, as it mediates the vertical balance between light and nutrients required by phytoplankton. While it is well established that lake stratification is sensitive to latitude gradients, the ways in which thermal stability modulates DCM characteristics (i.e., depth, thickness, and concentration) and nutrient–chlorophyll relationships across different latitude classifications remain unclear. In this study, data on thermocline depth, DCM feature, and water quality parameters were collected from 88 globally distributed stratified lakes. Our findings indicate that (1) higher-latitude lakes exhibit strong thermoclines, with light and nitrogen serving as the primary drivers of thermal stratification; (2) in high-latitude lakes, surface chlorophyll a concentrations are more tightly linked to total phosphorus than that at DCM depth in low-latitude lakes; and (3) structural equation modeling (SEM) results demonstrate that higher-latitude lakes form shallower and thinner DCM structures, where low light levels contribute to reduced peaks in algal biomass. These findings provide valuable insights for the management of stratified lakes facing the dual pressures of climate change and eutrophication. Full article

East Africa’s March–April–May (MAM) rainfall exhibits pronounced variability that strongly influences agriculture, water security, and livelihoods. This study analyzes consecutive wet day (CWD) events using CHIRPS precipitation, GridSat infrared cold-cloud brightness temperature, and ERA5 reanalysis for 1982–2023 to examine rainfall variability and its relationship with atmospheric circulation and convection. CWDs are classified into short (3–5 days), medium (6–10 days), and long (>10 days) events. Results reveal three regional activity centers: the Eastern Congo Basin, Lake Victoria, and Southwest Ethiopia. The Congo Basin emerges as the most convectively active region, sustaining frequent events across all categories and supporting long-duration rainfall through persistent moisture flow and mesoscale convection. On average, CWDs contribute 43% of total MAM rainfall across East Africa, ranging from negligible amounts in arid areas to over 90% in equatorial regions. Short-duration events dominate the seasonal total, while long-duration events, though spatially restricted, contribute up to 52% locally. Composite convection analysis shows a transition from widespread moderate activity during short events to highly localized, intense convection in long events, particularly over the equatorial Congo and Lake Victoria regions. These findings highlight the critical contribution of organized synoptic-scale systems to East Africa’s hydrological cycle, which will have implications for improving sub-seasonal rainfall forecasts. Full article

This analysis examines long-term changes in water levels of the Mead and Glen Canyon reservoirs on the Colorado River. Both reservoirs display clear declining trends in water levels, particularly after 2003. The causes include a combination of climate change, megadrought, increased water consumption, and alterations in the hydrological regime. Lake Mead exhibits a stronger and more concerning decline than Lake Powell, including extreme drought conditions over the past three years. The Rescaled Adjusted Partial Sums (RAPS) analysis identifies three statistically distinct subperiods, with an unambiguous decline in the most recent period. The day-to-day (DTD) method indicates reduced day-to-day water level variability in Lake Mead following the commissioning of the Powell reservoir, confirming its regulating influence. The Standardized Hydrological Index (SHI) indicates an accelerating intensification of drought conditions over the past 20 years. Regression analysis confirms a strong relationship between the water levels of the two reservoirs, along with significantly increased water losses in the more recent period. The literature suggests that climate projections are highly unfavorable, with further reductions in Colorado River discharge expected. The study underscores the urgent need to adapt water-management policies and align consumption with the new hydrological realities. Full article