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Mitigating the impacts of agricultural nutrients (nitrogen and phosphorus) on water quality requires a clear understanding of their transport pathways and transformation processes from land to receiving waters. For nitrate, which is subject to subsurface denitrification, it is therefore important to assess the spatial variability and temporal stability of groundwater redox conditions, as nitrate reduction typically occurs in reducing conditions. This paper presents a robust assessment of a large groundwater quality data set collected across New Zealand landscapes, develops methods to impute missing groundwater redox-sensitive variables and characterises the spatial variability and temporal stability of groundwater redox conditions against relevant landscape hydrogeochemical characteristics. Random forest and extreme gradient boosting (XGBoost) outperformed linear regression in predicting missing Mn 2+ values, achieving higher accuracy (R 2  > 0.8) and lower error (RMSE < 0.2 mg/L). Analysis of groundwater redox conditions highlights considerable spatial variability, particularly influenced by subsurface geology (rock types) and soil characteristics such as soil carbon and drainage across various hydrogeological settings. Our findings also reveal a higher prevalence of oxidised redox status in shallower groundwater and greater temporal stability in oxidised conditions across New Zealand landscapes. These insights have significant implications for targeted management strategies to reduce nitrate losses from farming activities, particularly in oxidised, shallow groundwater across different hydrogeological land units., Competing Interests: Declarations. Ethical approval: All authors have read, understood, and have complied as applicable with the statement on ‘Ethical responsibilities of Authors’ as found in the Instructions for Authors. Competing interests: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The US Geological Survey (USGS) is selecting and prioritizing basins, known as Integrated Water Science basins, for monitoring and intensive study. Previous efforts to aid in this selection process include a scientifically defensible and quantitative assessment of basins facing human-caused water resource challenges (Van Metre et al. in Environmental Monitoring and Assessment, 192(7), 458 2020). In the present work, we explore this ranking process based on water quality considerations, specifically salinity and salinization. We selected top candidate basins to study salinity and salinization issues in 18 hydrologic regions that include 163 candidate basins. Our prioritization is based on quantitative assessment of sources of salinity, drivers of change, and receptors that must respond to those sources and drivers. Source terms represented in the prioritization include geology, depth to brackish groundwater, stream conductivity, chloride in precipitation, urban and agricultural land use, application of road salt as a deicer, and irrigation. Drivers represented in prioritization include changes in chemical weathering as a result of changes in rainwater chemistry. Receptors include measures of water stress, measurements of stream ecological health, and socioeconomic factors. In addition, we present research activities for the USGS on salinity and salinization that can be pursued in these basins including assessment of sources, pathways, and loadings; predicting and understanding changes in sources, peaks, and trends; understanding the components of salinity and mobilization of contaminants; understanding the relationship between salinization and changing ecosystems; and developing knowledge on the causes and distribution of groundwater salinity, brackish water resources, and challenges related to desalination., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

The main focus of this study is to explore the complex interactions between aquatic ecosystem health (AEH) and time-varying hydro-environmental factors. We measure AEH in the Namhan River of South Korea using stream health index (SHI) scores for the trophic diatom index (TDI), benthic macroinvertebrate index (BMI), and fish assessment index (FAI) for 2008 to 2022. Key hydro-environmental variables associated with AEH, including their time-lagged responses, are identified. Water quality parameters such as chemical oxygen demand (COD) are significantly and negatively correlated with TDI (r=-0.68), BMI (r=-0.87), and FAI (r=-0.70), highlighting the critical role of water quality in the sensitivities of diatoms, macroinvertebrates, and fish health. The apparent response lag of aquatic ecosystems to hydrological parameters, such as a one-year-lagged correlation of BMI with mean flow (r=0.74) and annual flow anomalies (r=0.73), suggests their potential use as predictors in AEH models. A longitudinal analysis of SHIs over a decade showed consistent changes in AEH from upstream to downstream, with notable trends in the deterioration and improvement of SHIs in different areas. The upstream TDI and BMI deteriorated, while the upstream FAI improved. A multiple-linear-regression-based predictive model demonstrated efficacy in predicting AEH under various hydro-environmental conditions, achieving R 2 values up to 0.85 for BMI and also has the potential to simulate the impacts of anticipated climatic and hydrological changes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

This study investigated the occurrence of Legionella spp. in a chlorinated drinking water distribution system (DWDS), focusing on their community compositions and association with physicochemical water quality. Water samples were collected throughout the DWDS, covering from the treated water reservoir to distal ends. Although Legionella spp. genes were not detected at the reservoir, their abundance dramatically increased along the distribution network, reaching up to 4.4 log copies/L at distal sites. The Legionella communities were further characterized by high-throughput amplicon sequencing targeting the genus-specific 16S rRNA gene. The results revealed a diverse Legionella community, including amplicon sequence variants with high similarity (> 99 %) to potentially pathogenic species such as L. drozanskii and L. pneumophila, albeit at low levels. Moreover, Legionella community diversity increased significantly along the distribution system, leading to distinct community compositions at distal sites. Importantly, decay of residual chlorine concentration was identified as a key factor both in increasing the Legionella gene levels and shaping the community structure. Overall, this study underscores the importance of preventing pipe corrosion and maintaining adequate disinfectant residuals to minimize Legionella regrowth in DWDS., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Gravel-bed rivers draining mountainous forested headwater regions are critically important for drinking water supply and ecological integrity. These rivers, however, have been increasingly impacted by intensifying anthropogenic and natural (especially climate change exacerbated) landscape disturbances that commonly increase hillslope/channel connectivity and the delivery of cohesive sediment (<63 μm) and associated pollutants. Despite the known deleterious threats of excess cohesive sediments, there is still limited understanding of their transport and intra-gravel storage due to the complexities of such processes. Accordingly, the objectives of this study were to: i) calibrate and validate a semi-empirical cohesive sediment transport model (RIVFLOC) using the observations from flume experiments; ii) estimate the intra-gravel storage capacity for cohesive sediment with the calibrated model based on the field dataset (collected in two field campaigns between 2019 and 2021), and; iii) investigate mechanisms of cohesive sediment transport dynamics in this gravel-bed river, identifying knowledge gaps and areas for future research. Our results showed that despite the increased floc settling velocity, deposition was hindered by turbulent flow fields. The model predicted that ∼60 % of upstream cohesive sediment would ingress within the 10 km study reach due to the flow interaction with the gravel-bed. Despite the agreement between flume and field observations on ingress rates and preferential ingress of coarser (∼100 μm) flocs, notable differences were observed between modelled and field datasets, highlighting unknowns regarding cohesive sediment exfiltration without framework mobilization. This study uniquely integrates field measurements, flume experiments, and modelling strategies to evaluate the transport and fate of cohesive sediment in a gravel-bed river. Accordingly, our findings advance current knowledge on the mechanistic understanding of cohesive sediment transport and highlight future research directions., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Mike Stone reports financial support was provided by Natural Sciences and Engineering Research Council of Canada. Adrian L. Collins reports financial support was provided by UK Research and Innovation-Biotechnology and Biological Sciences Research Council. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Karst water resources, traditionally used worldwide for drinking purposes, are highly vulnerable to contamination. Scientific-technical efforts must therefore be done to ensure sufficient water quality for human consumption. Early-Warning-Systems emerge as an effective spring scale protection strategy for real-time identification of contamination episodes at drinking water capture points. With this ambition, the proposed stepwise procedure for the implementation of site-specific Early-Warning-Systems (EWS), focuses on three critical features: identification of groundwater contamination proxy parameters, warning dissemination and system validation. It was tested at three karst springs affected by temporary faecal contamination and intended for supplying drinking water to populations in Spain (Ubrique) and France (Montpellier). The applied statistical techniques, coupled to the analysis of individual flood events at karst springs, allowed to identify the optimal combination of groundwater and contamination proxy parameters at each study site according to the main contaminants and recharge mechanisms. The decision tree-like workflow, used to evaluate groundwater quality at hourly time step and set up the EWS, was then constructed considering a specific combination of hydroclimatic, hydrodynamic and physical variables together with national regulations for drinking water. Hence, warning thresholds were adapted to the behaviour of each karst system, and used to trigger the alarm when specific parameters and proxies exceeded the defined limits. The performance of the EWS was assessed by implementing 4 specific Key Performance Indicators (KPIs) dedicated to appreciate the effectiveness of the workflows in identifying contamination events and verifying estimated warning thresholds. The performed analysis demonstrated an overall successful functioning of the EWS for the three case studies, with mean anticipation times ranging between 12 and 45 h and <3 % of failure rate., Competing Interests: Declaration of competing interest The authors declare that they have no conflict of interest or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Aquatic ecosystems face significant impacts from human-related stressors, demanding a deep understanding of their dynamics and interactions for effective management and restoration. The Albufera Lake (Valencia, Spain) presents a complex scenario of multiple interacting stressors affecting its eutrophic status. In this study, we compiled a 50-year dataset and used Generalized Additive Models (GAMs) to analyse the dynamics of the main stressors affecting the ecological status of the Albufera Lake. Then, we assessed their individual and combined effects on eutrophication using chlorophyll-a concentration as a proxy and provided recommendations to enhance water quality. Overall, we found a decrease in annual water inflow and a clear effect of rice cultivation on the seasonal patterns of the Lake's residence time. Our analysis also shows an increase of average water temperature of 2 °C for the last 50 years, and an increase in the frequency and severity of heat waves. In contrast, we found a slightly negative long-term trend in conductivity, despite the occurrence of seasonal peaks in summer. Regarding nutrients, we identified a clear reduction of total phosphorus (from 1.08 mg/L in 1987 to 0.20 mg/L in 2022), while nitrate concentrations have been rather stable. Our results also point at an increase of toxic pressure exerted by organic and inorganic contaminants during the last years, with seasonal toxicity peaks occurring during rice field drainage periods. The main stressors affecting the chlorophyll-a levels were found to be temperature, water scarcity, and nitrate concentration as well as the interactions between temperature and conductivity, conductivity and nitrate, conductivity and water scarcity, and nitrate and total phosphorus. We found that stressor interactions are highly dynamic and result in synergistic and antagonistic effects that vary according to different stressor levels. Finally, our GAM framework points to two potential scenarios: increasing freshwater inflows or deregulating hydrology to allow seawater exchange, which are key for improving the ecological status of the Albufera Lake in the short-term., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Globally pesticide use has been associated with negative impacts on riverine invertebrate communities, but chronic exposure effects to most specific groups of pesticides are not well understood. In this paper, we sought to identify invertebrate species most vulnerable to effects of AChE-acting pesticides in UK rivers for potential application in environmental monitoring. We did this using a combination of the conservation of molecular target for AChE-acting pesticides (identified using the SeqAPass tool), laboratory-based toxicity data, and both biological traits and life history information. We then applied this information to assess for evidence of impacts on these riverine invertebrate communities in the Anglian region of England where there is high pesticide use. Sensitive genera to AChE-acting pesticides included Aedes, Anopheles, Cloeon, Ischnura, and the tolerant genera were Culex, Daphnia, Lymnaea. Using the UK Environment Agency's biota monitoring data spanning over period of 28 years (1984-2011) we evidence absence of the taxa most sensitive to AChE-acting pesticides (Ischnura, Aedes and Anopheles) but presence of AChE pesticide tolerant taxa (Lymnaea) at riverine sites in the Anglian region with high AChE pesticide use., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Imogen Poyntz-Wright reports financial support was provided by Natural Environment Research Council. Imogen Poyntz-Wright reports financial support was provided by United Kingdom Department for Environment Food and Rural Affairs., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The water chemical effects of copper have been a focus in the study of water quality criteria (WQC). Currently, multiple regression models are commonly used to quantitatively describe the impact of environmental factors on Cu toxicity in WQC studies. However, the influence of species-specific effects may consequently lead to poor prediction results of the regression models in practical application. For this issue, a backpropagation neural network (BPNN) model optimized using a genetic algorithm was developed in this study. The results showed when pooled data of given taxonomic groups were used, the BPNN mixed models had higher Adj.R 2 for five out of seven groups in the predicted toxicity values compared to the MNLR mixed models. When using species-specific models, the BPNN model still showed higher predictive performance. Further comparison of the two models for the species M. galloprovincialis revealed that, in addition to the good predictive performance of the BPNN models, the pre-set species codes of different species in the taxonomic group for the BPNN mixed model also reduced the impact of species-specific effects among species. Finally, the WQCs under different water quality parameter ranges were obtained using predicted toxicity values from mixed BPNN and MNLR models. The short-term WQC range for common water quality parameters (salinity: 25-30 ppt, DOC: 0.5-2.5 mg/L) obtained from the BPNN mixed model in natural marine environments was 1.6-4.41 μg/L, which aligns with guidance values provided by major global institutions, demonstrating the feasibility of applying the BPNN mixed model to WQC derivation. This study aims to provide valuable references for future research on WQC., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

In line with sustainable development goals (SDGs), precise quantification of water pollution and analysis of environmental interactions are crucial for effectively safeguarding water resources. In this study, Nemerow's pollution index was used to evaluate water quality, three receptor models were used to identify pollution sources, and Geodetector analysis was applied to explore environmental interactions in the North Shangyu Plain, Southeast China. Using 5207 surface water samples from September 2023 with 11 physicochemical parameters, the results showed that surface rivers in the North Shangyu Plain exhibited varying degrees of pollution: slight pollution upstream, moderate pollution in midstream and downstream, and concentrated high pollution in certain areas, with TN, COD Cr , and TP as the primary pollutants. Multimethod source apportionment significantly improved the accuracy of pollution source attribution and identified five main sources: domestic sewage (1.42%-3.54%) characterized by NO 3 -N, phytoplankton source (38.43%-50.05%) indicated by chl and PC, agricultural cultivation (16.1%-17.63%) marked by TP and COD Mn , industrial wastewater (17.64%-25.1%) primarily associated with TN, and natural source (10.32%-13.26%) characterized by DO, NH 3 -N, and COD Cr . Influencing factor analysis validated the source identification. Natural factors had minor impacts on water parameters, while pollution control from agricultural activities was suggested to diversify fertilizer types rather than merely reduce quantities. The combined effects of industrial and aquaculture activities intensified pollution from TN, chl, and PC, underscoring the need for targeted management practices. This study showed the objectivity and reliability of using a combined approach of multiple receptor models and Geodetector to evaluate the river water quality status, which helps assist decision-makers in formulating more effective water resource protection strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

The freshwater surface microlayer film (SMF) is a dynamically evolving micro-ecosystem closely related to water quality and microbial growth in water. However, the mechanisms of dynamic regeneration of SMF after their destruction and their impacts on the aquatic environment are still largely unknown. Herein, we modeled the dynamic processes of SMF destruction and recovery in the natural environment by constructing a water-SMF ecosystem. Chemical and biological changes in the dynamic regeneration of SMF were investigated. The results showed that the dynamic regeneration of SMF was very fast, with a regeneration thickness of up to 300 ± 50 μm in two days, and at the same time, it would rapidly enrich organic matter and Fe ions. In addition, the cyclic dynamic regeneration process of SMF is significantly correlated with the surge metabolic growth of microorganisms associated with organic matter metabolism (e.g., Methylophilus, Nevskia) and iron-redox-associated (e.g., Curvibacter). The experimental results suggest that the microbial-mediated process of iron-organic matter coupled oxidation-reduction in SMF may be another important mechanism driving water quality changes. Overall, our study provides valuable theoretical guidance for predicting changes in water quality in slow-flowing water bodies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

The proliferation of harmful algal blooms results in adverse impacts on aquatic ecosystems and public health. Early warning system monitors algal bloom occurrences and provides management strategies for promptly addressing high-concentration algal blooms following their occurrence. In this study, we aimed to develop a proactive prediction model for cyanobacterial alert levels to enable efficient decision-making in management practices. We utilized 11 years of water quality, hydrodynamic, and meteorological data from a reservoir that experiences frequent harmful cyanobacterial blooms in summer. We used these data to construct a deep-learning model, specifically a 1D convolution neural network (1D-CNN) model, to predict cyanobacterial alert levels one week in advance. However, the collected distribution of algal alert levels was imbalanced, leading to the biased training of data-driven models and performance degradation in model predictions. Therefore, an adaptive synthetic sampling method was applied to address the imbalance in the minority class data and improve the predictive performance of the 1D-CNN. The adaptive synthetic sampling method resolved the imbalance in the data during the training phase by incorporating an additional 156 and 196 data points for the caution and warning levels, respectively. The selected optimal 1D-CNN model with a filter size of 5 and comprising 16 filters achieved training and testing prediction accuracies of 97.3% and 85.0%, respectively. During the test phase, the prediction accuracies for each algal alert level (L-0, L-1, and L-2) were 89.9%, 79.2%, and 71.4%, respectively, indicating reasonably consistent predictive results for all three alert levels. Therefore, the use of synthetic data addressed data imbalances and enhanced the predictive performance of the data-driven model. The reliable forecasts produced by the improved model can support the development of management strategies to mitigate harmful algal blooms in reservoirs and can aid in building an early warning system to facilitate effective responses., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Kidney cancer rates are increasing in the US and worldwide. Arsenic, a known human carcinogen, is a suspected contributor to this rise, particularly in areas with arsenic-rich groundwater. However, research on the connection between low-level arsenic in drinking water and kidney cancer is limited. In our ecological study, we assessed the association between county-level drinking water arsenic levels and kidney cancer incidences using data from 240 counties in Texas. The analysis included 28,896 cancer cases among adults aged ≥20 years and 101,776,294 person-years during the period 2016-2020. Spatial Poisson regression models estimated the risk ratio (RR) for incident kidney cancer based on drinking water arsenic levels, adjusting for demographic, socioeconomic, and other risk factors, as well as spatial factors. Population-weighted drinking water arsenic levels were calculated using data from water testing for both public water systems and private wells, adjusted for populations served from each source. After adjusting for spatial factors and covariates, we observed 6% and 22% higher incidence of cancer in the medium (1-5 ppb) (RR 1.06, 95% CI 1.01, 1.11) and high arsenic (>5 ppb) group counties (RR 1.22, 95% CI 1.12, 1.34) compared to the low arsenic level ones (<1 ppb), showing a dose-response relationship (p-trend <0.001). Additionally, when arsenic was treated as a continuous variable, the incidence increased by 4% for each doubling of drinking water arsenic level (RR 1.04, 95% CI 1.02, 1.07) when considering drinking water arsenic level as a continuous variable. Our study suggests that exposure to low-level drinking water arsenic may be associated with an increased risk of kidney cancer. Further prospective studies are required to confirm our findings., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Monitoring water quality and river ecosystems is vital for maintaining public health and environmental sustainability. Over the past decade, data-driven methods have been extensively used for river water quality modeling, including dissolved oxygen (DO) concentrations. Despite advancements, challenges persist regarding accuracy, scalability, and adaptability of data-driven models to diverse environmental conditions. Previous studies primarily employed singular models or basic combinations of machine learning techniques, lacking advanced integration of adaptive mechanisms to process complex and evolving datasets. The current study introduces innovative hybrid models that integrate temporal pattern attention (TPA) mechanisms with advanced neural networks, including feed-forward neural networks (FFNNs) and long short-term memory networks (LSTMs). This approach leverages the synergistic strengths of individual models, significantly enhancing the accuracy of DO predictions. The models were rigorously tested against water quality data obtained from two distinct riverine environments, the Illinois River (ILL) and Des Plaines River (DP). Daily measured water quality data, including DO, chlorophyll-a, nitrate plus nitrite, water temperature, specific conductance, and pH, from 2017 to 2024 provided a robust foundation for comprehensive analysis of DO dynamics in these rivers. We conducted 10 scenarios with different model inputs, wherein the hybrid TPACWRNN-LSTM-10 model particularly excelled, achieving coefficient of determination values of 0.993 and 0.965, and root mean squared errors of 0.241 mg/L and 0.450 mg/L for DO predictions at the ILL and DP stations, respectively. The model's reliability was further confirmed by Willmott's index values of 0.998 and 0.992 and Nash-Sutcliffe efficiency values of 0.990 and 0.961 at the ILL and DP stations, respectively. Additionally, Shapley additive explanations (SHAP) values were utilized to interpret each predictor's contribution, revealing key drivers of DO predictions. We believe the novel hybrid modeling approach presented in this study could benefit utilities and water resource management systems for predicting water quality in complex systems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Waterborne contaminants pose a significant risk to water quality and plant health in agricultural systems. This is particularly the case for relatively small-scale but intensive agricultural operations such as plant production nurseries that often rely on recycled irrigation water. The increasing global demand for plants requires improved water quality and more certainty around water availability, which may be difficult to predict and deliver due to variable and changing climate regimes. Production nurseries are moving to adopt best management practices that recycle water; however, the risks associated with waterborne contaminants of various types, including nutrients, pesticides, plant pathogens, micro-plastics, and toxic metals, are not well understood. We review and synthesise the physical and biogeochemical factors that contribute to waterborne contaminant risk, and the main types of contaminants that are likely to require management, at plant production nurseries. Catchment characteristics (i.e., topography, land use), hydroclimatic factors (i.e., storms, floods, droughts), and landscape hydrological and sediment connectivity influence surface runoff, sediment transport, and associated contaminant transfer and storage. High hydrological connectivity can increase the risk of contaminant transport from the surrounding landscape to nurseries, with potential negative impacts to water quality in reservoirs and in turn plant health. High connectivity may also increase the risk of contaminants (e.g., sediment, pesticides, and phytopathogens) being transferred from nursery farms into downstream waterways, with consequences for aquatic ecosystems. Like all intensive agricultural operations, nurseries need to consider sources of irrigation water, water treatment and management strategies, and catchment and hydroclimatic factors, to mitigate the spread of contaminants and reduce their impacts on both plant production and the surrounding environment. Further research is needed to quantify contaminant loads and transfer pathways in these agricultural systems, and to better understand the threshold levels of contaminants that adversely affect plant health and which may result in devastating economic losses., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

The current work was conducted to investigate fisheries dynamics, rate of growth, and mortality, along with demographic features of Schizothorax niger using length-frequency data collected monthly from Manasbal Lake from August 2020 and July 2022. The length data for estimation was categorized into 13 bins, and population parameters were explored utilizing various options in ELEFAN I, with the best fit (Rn = 0.282) calculated by means of the FiSAT-II application. TW = 1.94 TL 2.94 , with a =  - 1.94, b = 2.94, and an attuned r 2  = 0.77 were derived for the weight and length association. The growing performance metric (ϕ) was calculated as 2.80. S. niger harvested stock in Manasbal Lake was prevalent in length categories of 20.5 to 25.4 and 25.5 to 30.4 cm. Different growth attributes were valued utilizing length frequency statistics as L ∞  = 46.05 cm, k = 0.30/year, and t 0  =  - 0.493 years. Over all mortality (Z), natural mortality (M), and fishing mortality (F) coefficients were evaluated as 1.43 year -1 , 0.56 year -1 , and 0.87 year -1 , respectively. The fish's average length was assessed at the culmination of the 1st, 2nd, 3rd, 4th, 5th, and 6th year as 15.42 cm, 22.78 cm, 28.09 cm, 32.61 cm, 36.03 cm, and 38.53 cm, respectively. Recruitment patterns in S. niger from Manasbal Lake indicate a singular annual recruitment occurrence, exclusively observed during the month of June. The current value of the exploitation (fish harvest) ratio (E) was 0.61 by the size-transformed catch curvature method, found to be marginally lower than the maximum value (E max ) of 0.699 depicting that the species is on the brink of overexploitation, and caution is required to maintain sustainability. The seasonal analysis of water quality parameters revealed that except for pH and free carbon dioxide, the other parameters showed pronounced temporal variations. Total alkalinity values were reflective of hard water type of the lake, and dissolved oxygen and free carbon dioxide values were reported to be suitable for S. niger., Competing Interests: Declarations. Ethical approval: All authors have read, understood, and have complied as applicable with the statement on “Ethical responsibilities of Authors” as found in the Instructions for Authors. Competing interest: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Eukaryotic plankton are important parts of the aquatic ecosystem and their community composition and spatiotemporal distribution patterns are affected by environmental factors. The Liujiaxia Reservoir is located at the northeastern edge of the Tibetan Plateau and is a vital resource for communities and agriculture in the region. Revealing the plankton diversity and their correlation with environmental factors is essential for understanding the ecological processes and mechanisms by which plankton contribute to, and maintain the ecosystem function of, the Liujiaxia Reservoir and beyond. This study investigated the detailed spatiotemporal distribution patterns and assembly mechanisms of eukaryotic plankton communities in Liujiaxia Reservoir for three periods during 2021. Significant spatial and temporal variations of abundance and community distribution of eukaryotic plankton were demonstrated. In addition, environmental factors such as water transparency, total phosphorus, total nitrogen, ammonia nitrogen, and pH were confirmed to have the most significant impact on the distribution of these communities in the reservoir. The dominant eukaryotic plankton group was Pyrrophyta, and the species interactions were predominantly cooperative. The trophic level index indicated excellent overall water quality in the reservoir. Deterministic processes were demonstrated as the predominant factors governing the assembly of eukaryotic plankton communities. This study provides valuable insight into the eukaryotic plankton community structure in the Liujiaxia Reservoir and reveals the complex relationships between plankton communities, environmental factors, and water quality.IMPORTANCEBased on 18S rDNA high-throughput sequencing, the spatiotemporal distribution patterns and assembly mechanisms of eukaryotic plankton communities were investigated. This study provides valuable insight into the eukaryotic plankton community structure in the Liujiaxia Reservoir in the northeastern edge of the Tibetan Plateau, and the relationships between eukaryotic plankton communities, environmental factors, and water quality. Through the dynamic changes of these communities, the water quality of the reservoir was assessed to provide basic data for the protection of its biodiversity. The findings of the present study will help to improve knowledge and understanding of the ecological processes and mechanisms by which plankton contribute to ecosystem function in the Liujiaxia Reservoir and beyond.

Maintaining good surface water quality is essential for protecting ecosystems and human health. Henan Province has long faced challenges related to water scarcity and severe water pollution. To support effective management of water pollution in Henan Province and provide insights for regional water pollution management, we collected extensive water quality monitoring data and applied spatial autocorrelation along with random forest to analyze the sources of heavily polluted areas. Results indicate that the spatial pollution pattern of surface water quality in Henan Province can be generally classified as insignificant pollution in the north, heavy pollution in the central regions, and light pollution in the south. Heavily polluted areas are mainly located in Zhengzhou, Luoyang, and Kaifeng. Key indicators affecting water quality in these regions are chemical oxygen demand (COD Mn ), dissolved oxygen (DO), ammonia nitrogen (NH 3 -N), and total phosphorus (TP), with urban sewage and industrial wastewater identified as the main causes of deterioration. These results not only provide a scientific basis for the systematic management of surface water quality pollution in Henan Province but also provide a reference for regional water pollution management., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

The index of biotic integrity (IBI) is an effective multi-metric tool for assessing biological integrity of aquatic ecosystems and regulating water quality based on fish community surveys. Percentages of individuals with deformity, eroded fin, lesion, and tumor (DELT) anomalies are used in IBIs as a measure of fish health, while the percentage of hybrids reflects changes in reproductive isolation. When rare, these are combined into a joint '% DELT + hybrids' metric. We investigated the distribution and effects of this metric on overall fish IBI scores and biological condition ratings by analyzing data from 646 fish surveys from across Alabama. Following exploratory data analyses, we assessed the impacts of % DELT + hybrids by comparing IBI scores for sites before and after setting this metric to zero to simulate systematic error (no detection). While DELTs and other anomalies were infrequent (~ 11% of sites), the two most commonly diseased fish species were Campostoma oligolepis (Leuciscidae) and Lepomis cyanellus (Centrarchidae). Hybrids were less frequent (~ 7% of sites) than anomalies and were scored only for Lepomis sunfishes. Overall, we found no statistically significant differences in final IBI scores or biological condition ratings before and after anomaly and hybrid removal; however, removal led to increased IBI scores and biological condition ratings in 13.2% and ~ 6% of surveys, respectively. These findings demonstrate that, while IBI outcomes appear relatively robust to systematic error in % DELT + hybrids, anomaly and hybrid observations can alter IBI outcomes, with important implications for fish-based bioassessments and water quality management., Competing Interests: Declarations: All the authors have read, understood, and complied as applicable with the statement on “Ethical responsibilities of Authors” as found in the Instructions for Authors. Competing interests: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

In-channel water treatment systems remove excess nutrients through biological, chemical, and physical processes associated with the hyporheic zone. However, the impact of surface and groundwater interactions on these treatment processes is poorly understood. This research aims to assess the influence of varying groundwater conditions (neutral, drainage water, and groundwater seepage) and different bed sediment hydraulic conductivities on nitrogen and phosphorus dynamics in in-channel treatment systems. A flume containing bed sediment was used to study changes in surface water quality under different groundwater and bed sediment conditions. Compared to inlet and outlet concentrations, dissolved reactive phosphorus (DRP) and ammoniacal nitrogen (NH 4 -N) levels in the surface water increased by 11-65% and 10-51%, respectively, while nitrate (NO 3 -N) concentrations decreased by 11% under groundwater seepage conditions. The increase in NH 4 -N was due to ammonification, while the decrease in NO 3 -N was due to denitrification and mixing and dilution with the groundwater. The upward groundwater flux through the bed sediment transported both DRP and NH 4 -N into the surface water. Low hydraulic (LH) conductivity sediment led to greater changes in nutrient concentration than high hydraulic (HH) conductivity sediment (DRP increased by 65% and NH 4 -N by 51% for LH, compared to 11% and 10% for HH, respectively). However, HH conductivity sediment led to greater variations in pH and Eh values. The findings could assist the design and monitoring of in-channel treatment systems where groundwater and surface water interact., Competing Interests: Declarations. Competing interests: The authors have no relevant financial or non-financial interests to disclose. The data supporting the findings of this study are available within the paper and its Supplementary Information files. Additional data, if needed, are available from the corresponding author upon reasonable request. The authors declare no competing interests., (© 2024. The Author(s).)

Phosphorus is one of the essential nutrients required for plants; however, loss of phosphorus from agricultural areas results in water quality impairment. This research aims to investigate the transport and deposition of phosphate at different solutions chemistries and phosphate-biochar dosages under (a) individual phosphate flow, (b) phosphate transport followed by biochar, and (c) co-transport of biochar-phosphate in saturated porous media. Breakthrough curves (BTCs) for phosphate were generated to understand the effect of pine raw biochar (BC) and iron-modified biochar (Fe-BC) on phosphate transport and deposition under varying solutions, pH (5.5-10.5), ionic strength (0-10 mM), phosphate (10-20 mg/L), and biochar dosages (100-200 mg/L) in saturated porous media. Results revealed increased deposition of BC and Fe-BC at high ionic strength (IS), i.e., 10 mM compared to 0 mM. The BTCs of phosphate (10-20 mg/L) transport at increasing IS showed delayed elute and long tailing curves compared to BTCs of tracer. Further, phosphate transport using BTCs in biochar-mediated saturated porous media was investigated at 10-20 mg/L phosphate, where maximum retardation (37%) was observed at pH 6.7±0.1 and 0 mM IS due to the availability of active sites for 10 mg/L phosphate using Fe-BC than BC. The BTCs of phosphate transport at pH 6.7±0.1 and 0-10 mM IS showed 37% and 40% phosphate deposition in Fe-BC-mediated columns for 0 mM and 10 mM, respectively, than BC-mediated columns. For BC, maximum phosphate adsorption was observed at pH 5.5±0.1, whereas for Fe-BC, it was observed at pH 6.7±0.1 at 10 mM IS. The least adsorption was observed at pH of 10.5±0.1 for both BC and Fe-BC. Similar phosphate retardation BTCs for BC and Fe-BC at 10 mM were observed with adsorption of 40% phosphate for 100-200 mg/L biochar dose. Besides, co-transport and deposition of biochar and phosphate, considering with and without ripening effect, reported high phosphate retardation using Fe-BC than BC at pH 6.7±0.1 and 10 mM IS due to chemical nonequilibrium and mass transfer. Taken together, iron-modified biochar showed significant adsorptive potential for phosphate management in saturated porous media. Overall, modeling of transport and deposition of phosphate and biochar are significant to understanding fate, biochar-phosphate interactions, and remediation designs in saturated porous media., Competing Interests: Declaration of Competing Interest ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Age and growth patterns of fish provide important information about the effects of environmental disturbances, which can be used as comparative tools in subsequent studies that attempt to assess freshwater quality. The main goal of our study was to provide information on relevant biological aspects of a native fish species used as a bioindicator in an extensive area of South America. In particular, we evaluated the age and growth patterns of Cnesterodon decemmaculatus (Poeciliidae) to establish reference species values and to compare them in different sites along an environmental quality gradient in a South American freshwater system. Water quality assessments indicated increasing environmental degradation downstream, reflecting anthropogenic impacts. The estimated ages of C. decemmaculatus along this quality gradient varied across sampling sites. The longest-lived individuals were those from the reference site, also presenting the highest average age value (almost 2 years). The best model to describe the growth in length of the individuals was the Logistic model. According to the parameters estimated from the growth curves, individuals from the most disturbed site showed slower growth although they reached greater maximum lengths than fish from the other sites. These results suggest that fish would tolerate the adverse conditions of the most altered sites, allocating their energy differentially. Our study provides valuable information on the age and growth patterns of C. decemmaculatus, a species endemic to the Neotropical region and a useful bioindicator in ecotoxicological studies., (© 2024 Fisheries Society of the British Isles.)

Harmful algal blooms (HABs) problem in Lake Erie has become critical recently-primarily triggered by phosphorus losses from cropland in the Maumee River watershed (major crops of corn/soybeans/wheat). Implementing agricultural best management practices (BMPs) is crucial to reduce excess nutrient loadings. Nutrient management is the management of nutrient applications for crop production that maximizes nutrient use efficiencies and minimizes nutrient losses. However, an integrated watershed-scale tool is needed for cost-effectively applying nutrient management practices for corn/soybeans/wheat considering the 4Rs (Right nutrient source, Right rate, Right time, and Right place of nutrient applications). In this study, by combining an improved Soil and Water Assessment Tool (SWAT) for nutrient management (SWAT-NM) and an improved BMP Cost Evaluation Tool (BMP-COST) for economic evaluations of nutrient management (BMP-COST-NM) considering the 4Rs for corn/soybeans/wheat, an integrated tool SWAT-COST-NM was created. SWAT-COST-NM was demonstrated in the AXL watershed (a typical agricultural area in the Maumee River watershed). The impacts of single nutrient management practices (single-NM, which separately changed the rate, place, time, or nutrient source of fertilizer applications) and combined-NM practices (multiple single-NM practices combined as one nutrient management practice) for corn/soybeans/wheat were evaluated. Tradeoffs in yearly net costs, crop yields, and March-July/yearly nutrient losses (Total Phosphorus-TP, Dissolved Reactive Phosphorus-DRP, and Total Nitrogen-TN) existed. Nutrient management did not necessarily lead to sufficient increases in crop yields to generate extra revenues that match or exceed the additional costs of the activities (compared to existing practices). One of the combined-NM practices could simultaneously reduce March-July TP, DRP, and TN losses by 5.89%, 8.19%, and 8.23%, respectively, while increasing crop yields with additional income (0.50 $/ha/yr of cropped area). SWAT-COST-NM, which can quantify various factors and tradeoffs when evaluating the impacts of nutrient management practices for corn/soybeans/wheat, can assist decision-makers in cost-effectively applying nutrient management practices considering the 4Rs., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Yaoze Liu reports financial support was provided by US Department of Agriculture. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Biscayne Bay (South Florida) is a subtropical estuary that requires freshwater inputs to maintain its ecological balance. Over the past 50+ years, the bay has been disrupted by contaminated freshwater released from tributaries and canals, negatively affecting its water quality. Specific areas of the bay have been recognized as impaired with respect to nutrients, chlorophyll and bacterial contamination. High human population densities in cities and municipalities within Miami-Dade County significantly influence urban water discharges with large amounts of pollutants released to relatively small areas. In August of 2020, 2021, and 2022, the negative consequences of continued pollution inputs triggered nutrient pulses resulting in significant fish kills followed by atypical algae blooms. To understand these events, we deployed water quality research buoys to monitor the complex system of environmental nutrient contamination in the freshwater canals and saltwater marine environments of Biscayne Bay. The system was designed to produce real-time continuous data for a variety of water quality parameters including chlorophyll a (Chl-a), conductivity, dissolved oxygen (DO), fluorescent dissolved organic matter (FDOM), pH, salinity, temperature, and turbidity. The buoys were strategically positioned in segments of the bay and major outfalls of tributaries and canals. The water quality data collected from the buoys gave a deeper understanding of normal baseline conditions of the tributaries and bay. Seasonal fluctuations of these parameters are significantly different in the dry and wet seasons with tidal influence evident in the managed tributaries. This paper elucidates the utility of a buoy network system for characterizing baseline conditions of various parameters in aquatic environments with varying degrees of environmental degradation. Furthermore, it underscores how a water quality network, comprised of stationary buoys, can serve as an early warning mechanism for stochastic events and provide invaluable data to help guide long-term restoration activities in the Greater Biscayne Bay Watershed., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Gehu Lake, as a key upstream reservoir of Taihu Lake, China, plays a crucial role in improving the water quality, and eutrophication control of the Taihu Lake Basin. Although the microbial communities are significantly important in maintaining the ecological health of lake, the microbial response to water quality, especially for eutrophication has been rarely reported in Gehu Lake. In this study, the water quality parameters and the corresponding effects on the structure and function of microbial communities were determined seasonally. It was found that the poorest water quality in summer (Water Quality Index = 116.52) with severe eutrophication (Trophic Level Index >70), was primarily driven by agricultural non-point sources (33.4%) and seasonal pollution (23.8%). The chemical oxygen demand (COD) was the most important indicator of water quality that affected the concentration of Chlorophyll-a (Chla) according to Pearson correlation analysis (p < 0.001), random forest modeling (p < 0.01), and structural equation modeling (path coefficient = 0.926). Redundancy analysis revealed that total nitrogen, total phosphorus, Chla, and COD significantly influenced the microbial community (p < 0.05). Microbial co-occurrence networks demonstrated significantly seasonal variations, and winter exhibited a more complex structure under lower temperature and limited nutrients compared to the other seasons. In addition, the Chla-sensitive microbial species that involved in nitrogen and phosphorus metabolism were identified as the biological indicators of eutrophication in response to the changes of seasonal water quality. These findings have taken insights into the interactions between water quality and microbial communities, and might provide the basis for improvement of the ecological and environmental management of Gehu Lake, as well as the control of eutrophication in Taihu Lake., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Water quality guidelines are an important tool for managing environmental pressures on freshwater streams. Currently, there is a lack of guideline values for fine sediment deposition in South Australian and, more broadly, Australian and overseas streams despite the potentially profound impacts of sediment deposition on aquatic communities. We used an outdoor recirculating stream mesocosm to assess the responses of freshwater diatoms and macroinvertebrates to fine sediment burial after six weeks following a pulsed event. Communities were exposed to five treatments of fine sediment deposition (inert sand) with an average depth between 1 and 20 mm, added on top of, and compared to, representative background sediments from a high-quality stream dominated by hard-bottom sediments and detritus. The most pronounced change was between the control and treatment one (1 mm sediment depth). Sediment deposition negatively affected diatom composition, with a decrease in functional diversity but a concurrent increase in taxonomic diversity arising from increased abundances of motile species. For macroinvertebrates, there was a clear negative response in the richness and abundance of the sensitive Ephemeroptera, Plecoptera and Trichoptera insect orders to fine sediment burial, and an associated higher macroinvertebrate drift propensity. This study highlights the importance of incorporating functional and behavioural responses in addition to taxonomic metrics when assessing biotic responses to stressors. This study recommends a new guideline which restricts additional fine sediment deposition to <1 mm in temperate South Australian freshwater streams, particularly those dominated by hard-bottom substrates and, or containing sensitive aquatic taxa. This threshold could act as an interim guideline for these stream types elsewhere in the absence of comparable studies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Groundwater is consumed by over 2 billion people globally, though it can be impacted by microbial and chemical contamination in both rural and (peri-)urban areas. This issue is particularly pertinent in regions like East Africa, where rapid urbanisation has strained local infrastructure, including water and sanitation systems. We use selected tracers of human and animal waste to assess the quality of community drinking sources with regards to surface-derived groundwater inputs and to compare urban versus rural water quality, under the rapidly developing urban area of Gulu, Northern Uganda. Specifically, we examine bulk and fluorescent dissolved organic matter (DOM), microorganisms (total coliforms, E. coli) and inorganic tracers of anthropogenic waste (NO 3 - , SO 4 2- , Cl/Br) from various sources: boreholes (12-76 m depth; n = 90), protected springs (n = 11) and municipal taps (n = 4). Our results show that NO 3 - and SO 4 2- were elevated in groundwater sources in the Gulu city urban area and the Cl/Br ratio was elevated in springs, compared to concentrations in the more rural Aswa and Omoro County area (p < 0.05). Interestingly, human and animal waste indicators E. coli and Tryp:FA (the ratio of tryptophan-like to fulvic-like fluorescence) displayed no significant difference between rural and urban settings (p > 0.05), though total coliforms were significantly higher in rural boreholes (p < 0.05). The presence of a pollution source, pollution carrier and a breakdown of a sanitary barrier at the borehole, as spot-checked by a visual sanitary risk assessment, was significantly associated with groundwater E. coli abundances. Evidence suggests monitoring and mitigation should be improved for all water types in Gulu District to meet WHO and Uganda Standard guidelines for potable water. This study offers valuable insights for water management planning and risk assessment of community water sources particularly in the context of East Africa and similar settings., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

The expansion of fish farming globally, driven by rising demand for fish as a food source, has raised substantial environmental concerns due to its impact on aquatic ecosystems. This study investigates the effects of fish farming effluents on taxonomic and functional diversity of macroinvertebrate community and test how taxonomic resolution impacts their effectiveness as pollution indicators. Macroinvertebrate samples were collected from seven trout farms, with sampling sites categorized based on proximity to farm effluents. Results indicate that fish farming effluents significantly alter macroinvertebrate communities, with observable changes in both taxonomic and functional metrics. Although traditional taxonomic metrics revealed differences along the pollution gradient, functional diversity measures provided more sensitive indicators of ecological changes. Functional traits, even at coarse taxonomic resolutions, better reflected shifts in ecological processes than taxonomic diversity alone. The study supports integrating both taxonomic and functional diversity measures in river restoration and management practices to optimize pollution detection and ecological assessment. Combining taxonomic and functional approaches in bioassessment is recommended for better evaluation of water quality and ecosystem health. Functional attributes can simplify routine monitoring, especially for poorly known macroinvertebrate taxa. Nevertheless, metrics related to chironomids showed significant changes along the pollution gradient and were useful for detecting fish farm effluents. Chironomid data at both fine and coarse taxonomic levels revealed the impact of pollution effectively., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Because of negative tap water quality perception, people often prefer bottled water over tap water despite the higher energy consumption and production of plastic waste. Taste and odour (T&O) deviations in tap water are an important aspect of this issue and should be avoided. However, T&O compounds typically occur at low concentrations (≤ ng.L -1 ) and are numerous, originating from various sources, ranging from source water to kitchen taps. Consequently, unravelling T&O events is challenging and causing compounds may remain unknown. Therefore, a multi-compound method (SBSE-TD-GC-MS) was developed, optimised and validated for the simultaneous trace analysis of 45 T&O compounds in drinking water. It covers key compounds of different odour categories with a wide range of physical-chemical properties and originating from the different steps of production and distribution. The intra- and interday precision of the method was shown by relative standard deviations (RSD) lower than 15 % and 23 %, respectively, for 75 % of the measured concentrations. For most of the compounds (>75 %), the detection capability (CCβ) was below 1/3rd of their lowest reported odour threshold concentration (OTC), while for the other 6 compounds, the CCβ was within the reported OTC range. Additionally, the CCβs were comparable to or lower than those in literature. As a proof of concept, the method was used to investigate the occurrence and concentrations of T&O compounds before (surface water) and after drinking water production. The results show a clear removal of compounds related to microbial activity (e.g. geosmin, 2-methylisoborneol, 2,4,6-tribromoanisole) after treatment and an increase of compounds related to disinfection. Although rarely investigated, 3-methylbutanal showed concentrations similar to its OTC in treated drinking water, emphasizing the necessity of a broad ultra-trace analysis to ultimately prevent the occurrence of T&O compounds and guarantee tap water quality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Artificial emergency water source lakes have been built in most cities in the middle and lower reaches of the Yangtze River, China, to ensure water safety for residents. However, these new ecosystems are prone to algal blooms or other degraded water quality conditions. A newly built water supply lake in the lower reaches of the Yangtze River was selected as a model system to test whether the coordinated manipulation of fish and submerged macrophyte communities could enhance ecosystem function and quality. The coordinated manipulations spanned a five-year period, aiming to enhance both top-down and bottom-up control of phytoplankton. As a result of these manipulations, the catch per unit effort of small-bodied zooplanktivorous fishes decreased by >95 % from year two and remained low. The coverage and biomass of submerged macrophytes increased year by year. Water transparency increased from 1.07 to 3.33 m. Total phosphorus and total nitrogen showed a decreasing trend (not significant though). The annual mean biomass of Cyanophyta, Chlorophyta and Bacillariophyta decreased from 2.99 to 0.03 mg/L, 3.90 to 0.16 mg/L, and 3.50 to 0.3 mg/L, respectively. The biomass of phytoplankton in different groups decreased in all four seasons. The annual mean biomass of Cladocera and Copepoda remained low. The biomass of Cladocera and Copepoda decreased in summer, fall, and winter. The Ecosystem Health Index - increased from 15.9 to 32.0. The pros and cons of the various top-down and bottom-up control measures employed are discussed. This research presents a valuable case study on the enhancement of ecosystem structure and function in newly constructed emergency water supply lakes and offers insights into the restoration of other subtropical shallow lakes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

When improving the water quality of natural bodies such as lakes, the explosive growth of filamentous green alga Cladophora can limit the growth of submerged macrophytes and prevent the water from shifting to a clear state. During the decay of Cladophora, it can cause various water quality issues such as reduced dissolved oxygen, increased nutrient levels and water odor. Biomanipulation, involving the introduction of a suitable density of aquatic animals into the water, can reduce the biomass of filamentous algae. We hypothesized that stocking appropriate densities of aquatic animals could reduce filamentous algal biomass and at the same time reduce the concentration of odorants in the water. Our study investigated the impact of stocking swamp shrimp (Macrobrachium nipponense), rosy bitterling (Rhodeus ocellatus), and silver carp (Hypophthalmichthys molitrix) at low (30 g/m 3 ), medium (60 g/m 3 ) and high (120 g/m 3 ) densities on water quality, biomass of primary producers (such as Cladophora, submerged macrophyte and algae) and malodorous volatile organic sulfur compound dimethyl sulfide (DMS) in the water, respectively. It was found that the swamp shrimp treatment groups and the rosy bitterling high-density groups effectively inhibited the growth of filamentous green algae cover, in which the rosy bitterling high-density group reduced the filamentous green algae mat coverage by 29.65 % compared with the control group. Additionally, the high-density swamp shrimp and rosy bitterling groups notably promoted the growth of submerged macrophytes (Vallisneria denseserrulata), and significantly reduced the concentration of the malodorous DMS in the water. Overall, stocking swamp shrimp and rosy bitterling can benefit the restoration of aquatic ecology and the maintenance of clear water. However, it is essential to consider potential changes in water quality resulting from excessive stocking density. Therefore, the appropriate density and proportion of stocking should be determined in conjunction with the specific scale of the aquatic ecological restoration project., Competing Interests: Declaration of competing interest All authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Construction activities can have long-lasting impacts on receiving water bodies, especially when they receive polluted urban runoff. Therefore, it is essential to minimize these impacts on water quality and consider the long-term environmental effects of development activities. This study aims to provide insights into the assessment, temporal variations, and key variables associated with the impact of construction works on streamflow water quality. However, current assessment methods relating to construction works and streamflow water quality may lead to spurious correlations. A spurious correlation refers to a connection between two variables that appears to be causal but is not. This study proposes a novel approach to avoid spurious correlations between construction work signatures and water quality, ensuring causality and correlation between water quality parameters. The approach was applied to a developing urban catchment in Hong Kong. Compared to existing assessment models, the proposed approach advances in ensuring true correlations between construction works and streamflow water quality. It is also the first to develop a new indicator to represent the key variable of construction works. In this study, salinity, turbidity, and suspended solids were used as substitutes for construction activity parameters, such as the number of construction works, to correlate with water quality parameters. Additionally, principal component analysis and the construction work signature index were both adopted to calculate the key variables of water quality on behalf of construction works. Results demonstrate that the new approach has significantly improved causality by 45 % compared to previous assessment methods. However, the method has limitations as it does not consider the impact of rainfall on construction works., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Assessing the macroinvertebrate assemblage in relation to physicochemical parameters can provide insight into the ecological state of aquatic environments. Therefore, this study aimed to assess macroinvertebrate assemblage of hydrogeologically connected wetlands in relation to physicochemical water quality parameters. Data were collected between June 2022 and April 2023 from twelve purposively selected sampling sites following established procedures. A total of 1,211 macroinvertebrates were collected from 18 orders and 44 families. The majority (72.83%) are generally pollution-tolerant families of the order Hemiptera, Odonata, Coleoptera and Diptera. There was significant spatio-temporal variation (P < 0.05, One-way ANOVA) in total macroinvertebrate abundance and bioindices. There were more individual macroinvertebrates collected during the dry season. The CCA and correlation analysis indicated that the physicochemical parameters had an effect on the distribution and abundance of macroinvertebrates. The size of the wetlands andthe intensity of anthropogenic interventionmight also result difference in macroinvertebrate abundance across the wetlands. The higher nutrient concentrations, the low DO level, the higher abundance of tolerant taxa and the medium Shannon&#95;Hvalue (range: 2.13 to 2.68) all indicate the wetlands' poor ecological status. Therefore, regular water quality monitoring, identification of the macroinvertebrate at the lower taxonomic level and the development of macroinvertebratebased multimetric indices are recommended for their sustainable management., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Fentaw et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Aquaculture plays a critical role in global seafood production. Probiotics in aquaculture have gained popularity for enhancing fish health, growth, and water quality. This study aimed to evaluate the effects of probiotic supplementation through different methods-feed and/or water-on Nile tilapia's growth, health, and resistance to Aeromonas hydrophila. A total of 270 Nile tilapia fingerlings (initial weight 10 ± 05 g) were randomly divided into four experimental groups: (1) control group (basal diet with no probiotics), (2) feed additive group (basal diet + probiotics in feed), (3) water additive group (basal diet + probiotics in water), and (4) combined feed and water additive group (basal diet + probiotics in both feed and water). The trial lasted for 12 weeks. The study assessed water quality, growth performance, feed efficiency, digestive enzyme activities, intestinal morphometry, biochemical and immunological parameters, oxidative status, and resistance to A. hydrophila. The results revealed significant improvements in water quality (reduction in TAN and NH3), growth performance, feed utilization, digestive enzyme activity (amylase, lipase), and immune responses in all probiotic-treated groups compared to the control. The group receiving probiotics in both feed and water showed the highest growth, survival rate, and immune function improvements. Additionally, gene expression analysis revealed upregulation of immune-related cytokines (IL-1β, TGF-β, TNF-α) in this group. In conclusion, administering probiotics via both feed and water significantly enhances Nile tilapia's health, growth, and resistance to bacterial infections, with the combined approach yielding the best results. This study highlights the importance of optimizing probiotic administration methods to maximize benefits in aquaculture systems., Competing Interests: Declarations. Consent to Participate: All authors consent to participate in the study and agree to have their information published in an academic article. Consent for Publication: Before submitting their manuscript to a journal, the authors obtained consent from all individuals involved to publish their data. Conflict of Interest: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

To explore the influence of storm runoff on bacterial metabolic activity and water quality in Jinpen Reservoir, three-dimensional fluorescence spectroscopy parallel factor analysis, high-throughput DNA sequencing technology, and Biolog technology were used to analyze variations in the components of dissolved organic matter, bacterial community composition, and microbial metabolic activity during three periods （before, during, and one month after runoff）. The results showed that after storm runoff into the reservoir, the water temperature decreased, and dissolved oxygen in the middle of the water column increased significantly. Finally, the aerobic and low-temperature state in the middle water and anaerobic and low-temperature state in the bottom water was formed. Simultaneously, the concentration of total nitrogen, total phosphorus, organic matter, and turbidity increased significantly. After one month of runoff, the concentration of pollutant decreased, however, was still higher than that before runoff. Further, during the runoff period, the proportion of Proteobacteria and Bacteroidetes increased significantly and the sum of their relative abundance accounted for 63.6% of the bacterial community. The bacterial metabolic activity was also higher than that before. One month after runoff, the bacterial population structure did not recover and the bacterial metabolic activity still remained at a high level.

The accumulation of excessive nitrogen, phosphorus, and other nutrients in rivers, lakes, and reservoirs has greatly accelerated eutrophication, which has led to the frequent outbreaks of algal blooms and brought great ecological risks to the related aquatic ecosystems. Evaluations on the eutrophic status of water bodies and estimations of water environment capacity are not only crucial for comprehensive assessment of eutrophic status but also indispensable references for comprehensive management of the aquatic ecosystems. In this study, major environmental variables （chemical oxygen demand, total nitrogen, and total phosphorus） of Yankou Reservoir watershed were monitored monthly from May 2020 to March 2022 and based upon the determined results, the comprehensive eutrophic conditions and water environment capacity were evaluated and estimated. The results showed that the water quality of Yankou Reservoir and upstream rivers exhibited an obvious seasonal variation pattern and during summer, the water qualities of the surface, mesosphere, and understratum of Yankou Reservoir showed significant differences. Estimations on the water environment capacity indicated that nutrients of nitrogen and phosphorus were currently the management focus for the Yankou Reservoir watershed. Integrated evaluation of eutrophic conditions exhibited that the upstream rivers were fundamentally improved to a mesotrophic or oligotrophic state, whilst the surface water of Yankou Reservoir was down to a mild eutrophication state in spring and summer. Based on this study, future treatment and management focuses on controlling water pollution and eutrophication in Yankou Reservoir were proposed. This study provided supportive reference for scientific evaluation and protection of water qualities, control and prevention of water pollutants, and sustainable development of the aquatic environment in Yankou Reservoir.

Sustainability of bivalve shellfish farming relies on clean coastal waters, however, high levels of faecal indicator organisms (FIOs, e.g. Escherichia coli) in shellfish results in temporary closure of shellfish harvesting beds to protect human health, but with economic consequences for the shellfish industry. Active Management Systems which can predict FIO contamination may help reduce shellfishery closures. This study evaluated predictors of E. coli concentrations in two shellfish species, the blue mussel (Mytilus edulis) and the Pacific oyster (Crassostrea gigas), at different spatial and temporal scales, within 12 estuaries in England and Wales. We aimed to: (i) identify consistent catchment-scale or within-estuary predictors of elevated E. coli levels in shellfish, (ii) evaluate whether high river flows associated with rainfall events were a significant predictor of shellfish E. coli concentrations, and the time lag between these events and E. coli accumulation, and (iii) whether operation of Combined Sewer Overflows (CSO) is associated with higher E. coli concentrations in shellfish. A cross-catchment analysis gave a good predictive model for contamination management (R 2  = 0.514), with positive relationships between E. coli concentrations and river flow (p = 0.001), turbidity (p = 0.002) and nitrate (p = 0.042). No effect was observed for catchment area, the number of point source discharges, or agricultural land use type. 64% of all shellfish beds showed a significant relationship between E. coli and river flow, with typical lag-times of 1-3 days. Detailed analysis of the Conwy estuary indicated that E. coli counts were consistently higher when the CSO had been active the previous week. In conclusion, we demonstrate that real-time river flow and water quality data may be used to predict potential risk of E. coli contamination in shellfish at the catchment level, however, further refinement (coupling to fine-scale hydrodynamic models) is needed to make accurate predictions for individual shellfish beds within estuaries., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Reuse of treated wastewater is necessary to address water shortages in a changing climate. Sustainability of wastewater reuse requires reducing the environmental impacts of contaminants of emerging concern (CECs), but it is being questioned as CECs are not regulated in the assessment of effluent water quality for reuse both nationally in Sweden and at the broader European Union level. There is also a lack of details in this topic on which CECs to be addressed and methodologies to be used for assessing their environmental impacts. A better understanding of the ecological risks and health hazards of CECs associated with wastewater reuse will assist in the development of effective regulations on water reuse, (inter)nationally, as well as related treatment/monitoring guidelines. This review provides a list of specific chemical CECs that hinder sustainable wastewater reuse, and also demonstrates a holistic quantitative methodology for assessing, scoring and prioritizing their associated ecological risks and health hazards posed to the environment and humans. To achieve this, we compile information and concentrations of a wide range of CECs (∼15 000 data entries) identified in Swedish effluent wastewater from domestic (blackwater, greywater, mixture of both) and municipal settings, and further perform a meta-analysis of their potentials for 14 risk and hazard features, consisting of ecological risk, environmental hazard, and human health hazard. The features are then scored against defined criteria including guideline values, followed by score ranking for prioritization. This finally produces a unique list of chemical CECs from high to low priority based on risk- and hazard-evaluations. Out of the priority chemicals, 30, mainly pharmaceuticals, had risk quotient ≥ 1, indicating ecological risk, 16 had environmental hazard being persistent and mobile, and around 60 resulted in positive predictions for at least four human health hazards (particularly skin sensitization, developmental toxicity, hepatoxicity, and carcinogenicity). The 10 highest-priority chemicals (final score 2.3-3.0 out of 4.0) were venlafaxine, bicalutamide, desvenlafaxine, diclofenac, amoxicillin, clarithromycin, diethyltoluamide, genistein, azithromycin, and fexofenadine. Potential crop exposure to selected chemicals following one year of wastewater reuse for agricultural irrigation was also estimated, resulting in a range of 0.04 ng/kg (fluoxetine) to 1160 ng/kg (carbamazepine). Overall, our work will help focus efforts and costs on the critical chemicals in future (waste)water-related studies, such as, to evaluate removal efficiency of advanced treatment technologies and to study upstream source tracing (polluter-pays principle), and also in supporting policymakers to better regulate CECs for sustainable wastewater reuse in the future., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Water sources near mining regions are often susceptible to contamination from toxic elements. This study employs machine learning (ML) techniques to evaluate drinking water quality and identify pollution sources near a chromite mine in Iran. Human health risks were assessed using both deterministic and probabilistic approaches. Findings revealed that concentrations of calcium (Ca), chromium (Cr), lithium (Li), magnesium (Mg), and sodium (Na) in the water samples exceeded international safety standards. The Unweighted Root Mean Square water quality index (RMS-WQI) and Weighted Quadratic Mean (WQM-WQI) categorized all water samples as 'Fair', with average scores of 67.95 and 67.19, respectively. Of the ML models tested, the Extra Trees (ET) algorithm emerged as the top predictor of WQI, with Mg and strontium (Sr) as key variables influencing the scores. Principal component analysis (PCA) identified three distinct clusters of water quality parameters, highlighting influences from both local geology and anthropogenic activities. The highest average hazard quotient (HQ) for Cr was 1.71 for children, 1.27 for adolescents, and 1.05 for adults. Monte Carlo simulation for health risk assessment indicated median hazard index (HI) of 4.48 for children, 3.58 for teenagers, and 2.98 for adults, all exceeding the acceptable threshold of 1. Total carcinogenic risk (TCR) exceeded the EPA's acceptable level for 99.38 % of children, 98.24 % of teenagers, and 100 % of adults, with arsenic (As) and Cr identified as the main contributors. The study highlights the need for urgent mitigation measures, recommending a 99 % reduction in concentrations of key contaminants to lower both carcinogenic and non-carcinogenic risks to acceptable levels., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Air-cooled blast furnace slag (ACBFS) is often used as road construction aggregate. Several incidences of adverse environmental effects have been reported in Indiana where unbound slag has been used. The aggregates that caused issues in the field had been previously approved for use by passing State of Indiana standard slag leaching procedures. The study goal was to test several hypotheses posed to the Indiana Department of Transportation and authors by the industry about slag leaching, and to better understand water quality impacts. Ten slags from two suppliers underwent leaching procedures adopted by two U.S. states, but additional test procedures and material and leachate chemical characterization were also conducted to better interpret results. Aggregates varied in size and age (24 h to 2 years old). Like prior literature reports, the chemical composition among the slag samples was similar. However, water quality impacts observed at the bench-scale in this study differed substantially across the slags. Results were consistent with those previously reported at Indiana field sites, but not with literature reported results from standardized leaching tests (i.e., TCLP, percolation, etc.). In the present study, no relationship was found between slag age and leachate composition. Leachate pH, conductivity, and color levels exceeded thresholds of regulatory and aquatic toxicity significance. For one slag, leachate pH reached 12.9, but the effluent was colorless. During both stagnation and rinsing tests, aqueous chloride, sulfate, and zinc concentrations sometimes exceeded regulatory water quality and aquatic toxicity levels. Repeated rinsing of the slag resulted in water conductivity and sulfate concentration differences. To better understand and predict the impacts of unbound ACBFS, additional fundamental studies and field investigations are recommended. Unbound ACBFS is not recommended for use near environmentally sensitive areas, drinking water sources, habituated areas, and where it may have water contact (i.e., waterways, wetlands, reservoirs, and groundwater)., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Andrew Whelton reports financial support was provided by Indiana Department of Transportation. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Surface water contaminants, including both conventional contaminants (e.g., nutrients, trace elements) and emerging contaminants (e.g., pesticides, pharmaceuticals) are heavily influenced by urban and rural land use practices. The goal of the study was to characterize the influence of watershed land use practices on surface water quality. Specific objectives were to (1) identify and quantify the type and concentration of nutrients, trace elements, pesticides, pharmaceuticals and personal care products in four watersheds and (2) understand potential sources of contamination based on the watershed's land cover and land use characteristics (i.e., oil and gas, urban, mining, agriculture). Monthly polar organic chemical integrative samples and water grab samples were collected from March-October 2022. The results showed that surface water quality varied by location, season, and flood condition Specifically, aluminum (mean = 758 μg L -1 ) and iron (mean = 1130 μg L -1 ) exceeded chronic aquatic life water quality criteria in the agricultural watershed, while imidacloprid exceeded the chronic criteria limit for freshwater invertebrates in both the urban (mean = 5.96 ng L -1 ) and agricultural (mean = 4.72 ng L -1 ) watersheds. Sulfate concentrations (mean = 666 mg L -1 ) also exceeded ambient water quality criteria in the watershed with a high activity of mining. This study provides important steps for developing a comprehensive understanding of land use impacts on contaminant presence and concentration in surface waters, improved understanding of the implications to non-target species, and necessary water treatment processes to ensure a safe water supply., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Tiffany L Messer reports financial support was provided by National Science Foundation. Tiffany L Messer reports financial support was provided by University of Kentucky Center for Appalachian Research in Environmental Sciences. Emily Nottingham Byers reports financial support was provided by National Science Foundation. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Groundwater quality is assessed by conducting water sampling and laboratory analysis. Field-based measurements are costly and time-consuming. This study introduces a machine learning (ML)-based framework and innovative application of stacking ensemble learning model, for predicting groundwater quality in an unconfined aquifer located in northern Iran. The groundwater quality index (GWQI) from 250 wells was evaluated and classified. We considered various influential factors such as proximity to residential areas, evaporation, aquifer transmissivity, precipitation values, population density, distance to industrial centers, distance to water resources, and topography. Three different ML classifiers were employed to establish relationships between GWQI and the aforementioned factors: the AdaBoost classifier (ADA), quadratic discriminant analysis (QDA), and stacking ensemble learning (SEL). A novel model was introduced dubbed quadratic-ada-stacking ensemble learning (QA-SEL) to predict GWQI. The performance of these algorithms was evaluated through the receiver-operating characteristic (ROC) and multiple statistical efficiency indicators, including overall accuracy, precision, recall, and the F-1 score. All three ML algorithms displayed a high degree of accuracy in their GWQI predictions. Nonetheless, the QA-SEL method was identified as the most effective model due to its superior accuracy (overall accuracy, precision, recall = 0.95, 0.95, 0.96, ROC = 0.96, respectively). Following model optimization and testing, the QA-SEL model and a GIS were employed to map GWQI classes across the entire area. The produced GWQI map was validated by comparing the measured and predicted GWQI on the map. This study offers an economically efficient model for groundwater quality prediction, which can be replicated in other plains., Competing Interests: Declarations. Ethical approval: Not applicable. Consent to participate: All authors consent to participate in this manuscript. Consent for publication: All authors consent to publish this manuscript. Conflict of interest: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

This study assessed the surface water quality in Dong Thap province during 2013-2023 using multivariate statistical techniques. Water quality index (WQI), Pearson correlation, principal component analysis (PCA), and cluster analysis (CA) were determined based on monitoring data for parameters. The findings showed that only some water samples had pH values below the permissible standard, while 95.5% of samples exceeded the standard of Escherichia coli in surface water. In some years, 100% samples having BOD 5 , TSS, NH 4 , and E. coli exceeded the permissible limits. The PCA identified four, five, and seven major potential sources during 2013-2015, 2016-2020, and 2021-2023, respectively, explaining 75.9%, 63.0%, and 63.0% of variation in the corresponding duration times. For heavy metals, the number of water samples containing As, Cu, and Pb exceeding the water permissible limits were 15.5%, 21.4%, and 2.8% samples in 2021, respectively, but no heavy metal was above standard in 2022 and 2023. The evaluation of average water quality based on WQI showed that 79.31% and 76.19% of the sample sites were classified to be average during 2016-2020 and 2021-2023, respectively, and others were bad water quality. However, the water quality showed an improving trend with 70% of monitoring positions considered as good water quality in 2023. The results showed that anthropogenic activities and hydrological regime were the main source of pollution. This study provides guidance to policymakers in developing water management strategies to have proper actions to prevent water pollution.+ , and E. coli exceeded the permissible limits. The PCA identified four, five, and seven major potential sources during 2013-2015, 2016-2020, and 2021-2023, respectively, explaining 75.9%, 63.0%, and 63.0% of variation in the corresponding duration times. For heavy metals, the number of water samples containing As, Cu, and Pb exceeding the water permissible limits were 15.5%, 21.4%, and 2.8% samples in 2021, respectively, but no heavy metal was above standard in 2022 and 2023. The evaluation of average water quality based on WQI showed that 79.31% and 76.19% of the sample sites were classified to be average during 2016-2020 and 2021-2023, respectively, and others were bad water quality. However, the water quality showed an improving trend with 70% of monitoring positions considered as good water quality in 2023. The results showed that anthropogenic activities and hydrological regime were the main source of pollution. This study provides guidance to policymakers in developing water management strategies to have proper actions to prevent water pollution., Competing Interests: Declarations. Ethical approval: This research did not involve the use of animals. Competing interests: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Forecasting potential water pollution areas (PWPA) is essential for effective watershed management. However, there remains a limited understanding of the spatial-temporal features that influence water quality (WQ), and advanced technical methods for WQ forecasting. This study developed an integrated framework utilizing spatial-temporal graph convolution networks (STGCN) to enhance comprehension of the spatial-temporal features influencing WQ and to develop a practical module for integrating features into the WQ prediction. The Pearson correlation method and seasonal decomposition analysis described the WQ features. Subsequently, the spatial-temporal distribution of PWPA was assessed using both the comprehensive pollution index method and Cressman space interpolation technique. Data from 403 monitoring stations was collected from the Yangtze River basin (YZR), encompassing pollutants such as COD, TP and NH₄⁺-N. The finding revealed that maximum concentrations of COD (36.4 mg/L), TP (4.078 mg/L) and NH₄⁺-N (13.58 mg/L) exceeded the standard thresholds necessitating early warnings. A significant correlation among pollutants was observed with coefficients ranging from 0.356 to 0.475 (P < 0.001), indicating their potential utility in predicting PWPA. Seasonality components exhibited strong correlations with the original WQ (correlation coefficients ranging from 0.62 to 0.89), followed by residuals (from 0.37 to 0.61) and trend components (from 0.25 to 0.53). The geographic layout of WQ monitoring stations along river lines resembled a graph network structure, suggesting that watershed WQ prediction can be classified as a spatial-temporal prediction task. The STGCN model achieved R 2 values ranging from 0.607 to 0.844 for each pollutant on the test datasets, surpassing traditional models such as RNN, LSTM, and GRU in predictive accuracy. PWPA occurrences were predominantly identified in the southwestern regions as well as within the middle and lower reaches of the YZR. These results validated that the developed framework is capable of forecasting PWPA in large-scale watersheds while supporting effective watershed management., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Many compounds and inorganic elements released from natural and anthropogenic origins contaminate the environment and are implicated in catastrophes involving most biologically driven ecological processes and public health. One such element is Mercury. Mercury exists in both inorganic elemental form and the more metabolically active molecular form e.g. methyl mercury. They enjoy wide applications in medicine and form key components of numerous electrical and electronic devices. Unfortunately, severe health and adverse physiological conditions have developed from the impacts of mercury on the flora and fauna of both aquatic and terrestrial organisms. Despite being present in tiny amounts in water bodies, mercury undergoes a process of trophic amplification where its concentration increases significantly as it moves up the food chain through processes like biomethylation, bioaccumulation, and biomagnification. Most current methods for removing mercury through physical and chemical means have significant drawbacks, including high costs, complex technical requirements, and harmful secondary effects on the environment. Therefore, only environmentally friendly and sustainable approaches are acceptable to mitigate the risks to public health and ecosystem damage. Bioremediation involves the use of biological systems, i.e., plants and microbes, to recover mercury from the environment. The application of microorganisms in remediation is the hallmark of all mitigation strategies targeted at mercury pollution in the soil and aquatic matrices. The present paper provides a comprehensive overview of the current knowledge on mercury pollution in the environment (i.e., atmosphere, soil, water, and sediments). Many symptoms of mercury poisoning in fish, birds, and other animals, including man, were extensively treated. Information on the existing physico-chemical treatment methods, as well as the more ecologically friendly bioremediation measures available, was summarized. The importance of strengthening existing international policies, commitments, protocols, and alignments on the control of anthropogenic generation, treatment, and reduction of mercury discharges to the environment was highlighted., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The Kumamoto Earthquake is named after the Kumamoto Prefecture where the series of earthquakes occurred in the city located on the island of Kyushu, in southwest Japan. In this area, 100 % of the population depends on groundwater for drinking water; hence, groundwater is an extremely important lifeline for people. The effect of earthquakes on the water quality of groundwater has been suggested based on monitoring data measured by public agencies once or twice a year. Frequent water quality monitoring of the groundwater in the Kumamoto area has continued once a month for six years since 2014. In this study, we aimed to statistically evaluate the changes in groundwater quality caused by the 2016 earthquake and provide further insights into its mechanisms. The Stiff diagrams using major ionic components showed no apparent overall water quality change before and after the earthquake for 14 groundwater samples in the area. However, statistically significant changes were indicated for 11 samples by k-medoids clustering (non-hierarchical cluster analysis), divided into two clusters before and after the earthquake. In addition, the samples showing water quality changes did not vary even over the four years after the earthquake, indicating that the change was not temporal. The magnitude and trend of the change in individual water quality parameters depended on the sampling sites, while some parameters, such as nitrate, showed seasonal fluctuations due to precipitation conditions more than the effect of the earthquake. No particular relationship was found between the distance from the sampling sites to the epicenters or active faults and the degree of water quality changes. Finally, it was considered that the aquifer breaching/fluid mixing model (AB/FM model), through the change in the bleeding channel of water due to seismic shaking, most likely explains the main mechanism of water quality change in groundwater in the Kumamoto area., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Water and food security in Israel and the Palestinian Authority are deeply interconnected due to the region's arid climate and water scarcity, shared water resources, and interrelated agricultural sectors. Therefore, jointly addressing water reuse is vital to supporting sustainable agricultural production and ensuring food safety., Objectives: This paper examines the food safety implications of the cross-border trade of fresh fruits and vegetables between the Palestinian Authority and Israel, with an emphasis on the influence of, water technologies, agricultural practices, and environmental health., Methods: This paper provides a comprehensive review of existing data to assess water irrigation quality, food safety, and water reuse regulations in the Palestinian Authority and Israel., Results: Significant discrepancies in food safety, food quality, and exposure to contaminants from fresh produce result from different water reuse regulations, practices, and socioeconomic conditions. Given the volume of trade, consumer mobility, and environmental sustainability, coupled with geopolitical limitations between the Palestinian Authority and Israel, there is an urgent need for a unified regulatory strategy for wastewater reuse ensuring food safety and security. We propose a single, coordinated approach to overseeing wastewater reuse to enhance public health and address contaminants of emerging concern that are not currently regulated. Navigating the political and legislative complexities in a proactive stance requires both Israeli and Palestinian decision-makers to address the matter conscientiously. Existing data and the precautionary principle are sufficient to propose an interim prohibition on treated wastewater irrigation for leafy vegetables to mitigate pollution risks and act as a catalyst for improving irrigation water quality., Conclusions: Our proposed strategy for a unified water reuse regulation emphasizes the necessary steps for its implementation and addresses potential obstacles. This strategy underscores the importance of responsible wastewater management in advancing common goals of environmental sustainability, food safety, and human health., Short Synopsis: We propose a coordinated Israeli-Palestinian approach to wastewater reuse to ensure food safety based on shared environmental and health concerns, economic considerations, and the precautionary principle., A Call for Joint Israeli-Palestinian Guidelines for Water Recycling to Improve Food Security and Safety., Competing Interests: Declaration of Conflicting InterestsThe author declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Groundwater underpins water supply for most of the world's regions, yet its sustainable utilization has been markedly compromised by inappropriate exploitation and a multitude of pollution sources. Water quality evaluation has emerged as an essential strategy to guarantee the optimized utilization and vigilant conservation of water resources. In this study, principal component analysis (PCA), entropy weight method (EWM), coefficient of variation method (CVM), and Water Quality Index (WQI) were used to construct an integrated WQI groundwater quality assessment model that integrates PCA-CVM-EWM for dimensionality reduction and weight optimization. Taking a village in Shandong Province, China, as an example, PCA identified seven evaluation indicators. The CVM-EWM were coupled to calculate comprehensive weights through the principle of minimum information entropy, followed by a comprehensive assessment of groundwater quality based on WQI values. The results indicated that Class III groundwater predominated in the study area, accounting for 74%, with localized pollution present. The hydrochemical type of the groundwater was primarily SO 4 ·HCO 3 -Ca, significantly influenced by human activities. The coefficients of variation for Fe, Mn, and NH 4 -N all exceeded 1. Compared to other methods, the optimized WQI model demonstrated superior performance in the selection of evaluative indicators, weight distribution, and comprehensive water quality assessment, showing a distinct advantage for water quality data with numerous hydrochemical indicators and substantial coefficients of variation. The findings provided a scientific reference for diagnosing groundwater quality issues and formulating preventive and control measures. PRACTITIONER POINTS: A comprehensive water quality index evaluation model was constructed. Optimized steps for selecting indicators and assigning weights for the water quality index model. Selection of evaluation indicators based on indicator correlation analysis. The variability of hydrochemical data is considered., (© 2024 Water Environment Federation.)

Reactive Transport Models (RTMs) are essential tools for understanding and predicting intertwined ecohydrological and biogeochemical processes on land and in rivers. While traditional RTMs have focused primarily on subsurface processes, recent watershed-scale RTMs have integrated ecohydrological and biogeochemical interactions between surface and subsurface. These emergent, watershed-scale RTMs are often spatially explicit and require extensive data, computational power, and computational expertise. There is however a pressing need to create parsimonious models that require minimal data and are accessible to scientists with limited computational background. To that end, we have developed BioRT-HBV 1.0, a watershed-scale, hydro-biogeochemical RTM that builds upon the widely used, bucket-type HBV model known for its simplicity and minimal data requirements. BioRT-HBV uses the conceptual structure and hydrology output of HBV to simulate processes including advective solute transport and biogeochemical reactions that depend on reaction thermodynamics and kinetics. These reactions include, for example, chemical weathering, soil respiration, and nutrient transformation. The model uses time series of weather (air temperature, precipitation, and potential evapotranspiration) and initial biogeochemical conditions of subsurface water, soils, and rocks as input, and output times series of reaction rates and solute concentrations in subsurface waters and rivers. This paper presents the model structure and governing equations and demonstrates its utility with examples simulating carbon and nitrogen processes in a headwater catchment. As shown in the examples, BioRT-HBV can be used to illuminate the dynamics of biogeochemical reactions in the invisible, arduous-to-measure subsurface, and their influence on the observed stream or river chemistry and solute export. With its parsimonious structure and easy-to-use graphical user interface, BioRT-HBV can be a useful research tool for users without in-depth computational training. It can additionally serve as an educational tool that promotes pollination of ideas across disciplines and foster a diverse, equal, and inclusive user community., (© 2024 The Author(s). Journal of Advances in Modeling Earth Systems published by Wiley Periodicals LLC on behalf of American Geophysical Union.)

The Ouislane sub-watershed is currently experiencing severe water shortages and is highly dependent on its water supply. The sub-watershed spans two communes: Meknes to the north and El Hajeb to the south. It serves as the primary water source for irrigation and drinking purposes for the local population. Consequently, it is crucial to assess the spatio-temporal variations of water quality to identify and address potential gaps; these focused on effective monitoring systems to detect contaminants, pollutants and health risks. This research project aims on the application of self-organizing map (SOM) techniques combined with cluster analysis to classify water quality in springs for drinking and irrigation purposes. The present study evaluates the water quality variations using physicochemical parameters of twelve water springs, collected during the wet and dry seasons of 2022. For this purpose, the water quality index (WQI), self-organizing map (SOM), hierarchical cluster analysis (HCA), and principal component analysis (PCA) are used as evaluation and classification methods. As a result, the SOM algorithm with a size of 5 × 5 units identified as the most suitable, based on the minimum quantization error (QE) and topographic error (TE), yielding a QE of 0.379 and a TE of 0.000. It grouped the water quality data into five distinct clusters, Cluster I represented 37.5% of the total samples, while cluster II represented 25%. Cluster III and IV each accounted for 8.33% of the samples, while 20.83% of the sampling water are classified in cluster V. Clusters I, II, and IV indicate good water suitable for drinking. However, cluster V had the highest WQI, suggesting very high contamination due to increased levels of the 10 studied physicochemical parameters. The water quality in this region (cluster V) is influenced by natural processes, such as precipitation intensity, weathering and vegetation cover, as well as anthropogenic factors like agriculture and urban concentration. PCA confirmed the clustering results obtained by SOM. However, SOM provides a more detailed classification and additional insights into the dominant variables influencing the classification processes. The results of this study suggest that SOM was an effective tool for gaining a better understanding of the patterns and processes driving water quality in the Ouislane sub-watershed and provides valuable avenues for further research to establish and monitor water quality for effective management of water resources., Competing Interests: Declarations. Ethics approval: Not applicable. Consent to participate: Not applicable. Consent for publication: Not applicable. Conflict of interest: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)