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Enhancing movement options for confined dairy cows, like in tie-stall housing, may boost natural behaviour and welfare. Yet, limited data exists on the environmental impact of both indoor and outdoor exercise areas. This study investigates the impact of exercise pen type on effluent properties and gas emissions during winter and/or summer conditions in a northern country such as Canada. Forty-five Holstein dairy cows were randomly assigned to three treatments: (1) no exercise [cows kept indoors with tie-stalls (TSs)]; (2) indoor exercise [access to a 28 m2 cow−1 indoor pen (IP) for 1.5 h d−1] and (3) outdoor exercise [access to a 28 m2 cow−1 outside nonaerated (OnAP) or aerated stand-off pad (OAP) for 1.5 h d−1]. The effluent composition of OnAP and OAP varied notably between seasons. In winter, OAP leachates showed higher biological oxygen demand (+89 %), pH (+1.2 units), ammonium (+96 %) and total solids (+50 %), lower faecal but higher total coliforms (−120 % and +20 %, respectively) than OnAP during summer. In addition, OAP presented higher biological and chemical oxygen demand (+80 %) than OnAP in both seasons. Both OAP and OnAP showed higher carbon dioxide emissions (+150 %) and lower methane emissions during summer (−200 %) than IP and TS. Nitrous oxide emissions were higher for OnAP (+600 %) than in OAP, IP and TS, with no changes in ammonia emissions across treatments. Outdoor exercise for dairy cows using a filtering pen didn't meet environmental limits for removing leached contaminants. Exercise pens raised carbon dioxide and nitrous oxide emissions but decreased methane emissions. • Non-aerated, aerated pads served as seasonal exercise areas for tie-stall cows. • Efficient woodchip matrix filters pad leachates by removing contaminants. • Aeration failed to enhance leachate contaminant removal in the stand-off pad. • Outside exercise pens reduce greenhouse gas emissions from dairy housing surfaces. [ABSTRACT FROM AUTHOR]

Health care facilities represent a significant source of pollution, contributing to the growing problems associated with global warming. The resulting climate change impacts our health through worsening air and water quality, diminished access to nutritious food, and safe shelter. We outline here the not only the role of the surgeon in contributing to climate change, but also ways in which to minimize one's carbon footprint. Surgeons are leaders within healthcare systems. Adopting environmentally conscious practices can reduce solid waste, energy usage, and carbon emissions. Practices outside of the clinical setting can also incorporate sustainability, including the use of virtual recruitment and educational programs, as well as thoughtful and conscientious travel practices. Academic surgery combines clinical practice with an element of leadership, at all levels. Our recognition and action to reduce wasteful practices can help leave a better earth for generations to come. [ABSTRACT FROM AUTHOR]

In order to solve a series of problems in the current feeding process, such as inaccuracy, unevenness and high labour costs, a precision feeding system for largemouth bass was developed by integrating feeding management model, water quality monitoring system, fish feeding activity sensor, automatic feeding machine and software platform. Based on the analysis of the growth data of largemouth bass and the bioenergetics principle, the feeding management model for predicting the growth, feed requirements and waste output of largemouth bass was constructed and validated under different culture modes. The real-time DO parameters were used to fine-tune the feed requirements predicted by the model. The feed requirements were then further precisely adjusted by combining the intensity of fish feeding activities. The web platform client used supported the access of any browser and provided a visual interface for software users. The experimental results showed that the feeding management model provides reliable estimates of growth, feed requirements and waste output for largemouth bass. The function of dynamically adjusting the model and feeding parameters through feedback and production data provided by cloud serves or users improved the application effectiveness and scope of the system. The system comprehensively considered multiple factors such as fish biological characteristics, physiological stages, feed nutrients composition, environmental factors and fish appetite, and incorporated relevant technologies or equipment to provide an effective tool for users to shift from experience-driven to knowledge-driven approaches to better optimise production and feeding, thereby improving the economic benefits and environmental sustainability of aquaculture. • Nutritional model provides reliable estimates of fish growth, feed requirement and N, P waste output. • Feedback from real-time water quality monitor improves accuracy of feeding requirement. • Fish feeding activity sensor precisely adjusts feed requirement. • Combination of model, water quality and feeding behaviour precisely determines fish feeding amount. [ABSTRACT FROM AUTHOR]

Acute ammonia toxicity suppresses the immune function and enhances the inflammatory pathways in Nile tilapia. The aim of this study was to compare the effect of Bacillus strains probiotic mixture (BS) or Yucca shidigera liquid extract (YSE) alone or their combination in water treatment and in reliving toxicity of an acute ammonia exposure in Nile tilapia through the assessment of fish immune response, inflammatory pathway, oxidative stress response with respect to the histopathological changes, gene expression, enzymes levels and phagocytosis. Five groups were used; the 1st and 2nd groups fed the basal diet; the 3rd group fed basal diet with BS in water, 4th group fed basal diet and supplemented with YSE in water and 5th group received a combination of BS and YSE. After two weeks of treatments, the 2nd, 3rd, 4th, and the 5th groups were exposed to acute ammonia challenge for 72 h. Fish exposed to ammonia displayed significant decreases in RBCs, Hb, PCV, WBCs, phagocytic activity (PA) and index (PI), lysozyme activities and serum antioxidant enzymes (glutathione peroxidase (GPX) and catalase (CAT)). Also, a significant increase in Malondialdehyde (MDA), degenerative changes in the gills, hepatopancrease and spleen associated with an elevated un-ionized ammonia level. A significant restoration of the hematological parameters was observed with the use of BS, YSE or their combination. Additionally, they improved the innate immunity, antioxidant responses, and histopathological changes. At transcriptomic level, ammonia toxicity significantly lowered the mRNA transcription levels of Nuclear erythroid 2-related factor 2 (Nrf2) , quinone oxidoreductase 1 (NQO-1) , Heme oxygenase 1 (HO-1) and Heat shock proteins (HSP70). While nuclear factor kappa β (NFкβ), Tumor necrosis factor α (TNF-α) , Interleukin 1β (IL-1β), and Interleukin 8 (IL8), transcription levels were increased. Interestingly, BS and YSE and their combination significantly increased the expression of these genes with the highest levels reported with BS and YSE combination. We observed that, the most pronounced restoration of some important inflammatory and immune related genes close to the control level was observed when BS-YSE mix was used. Furthermore, a restored water pH, and a maintained ammonia level to the control level were observed in this group. Otherwise, equal effects for the three treatments were observed on the assessed parameters. We recommend the used of BS-YSE mix for water ammonia treatment and relieving ammonia toxicity in fish. • Acute ammonia toxicity suppresses the immune function and enhances the inflammatory pathways in Nile tilapia. • Bacillus strains, Yucca shidigera (YSE) or their mix are used for reliving acute ammonia toxicity. • A restored level of some important inflammatory and immune related genes was observed with BS-YSE mix. • A restored water pH, and a maintained ammonia level to the control level were observed with BS-YSE mix. • We recommend the used of BS-YSE mix for water ammonia treatment and relieving ammonia toxicity in fish. [ABSTRACT FROM AUTHOR]

This study discussed the effects of two types of lactic acid bacteria, Lactobacillus reuteri (L. reuteri) and Pediococcus acidilactici (P. acidilactici), on the growth and nonspecific immunity of Penaeus vannamei (P. vannamei) and developed probiotic applications for shrimp cultivation. This study incorporated two types of lactic acid bacteria in shrimp feed through spraying. The shrimps were grouped according to the type and concentration of effective bacteria incorporated into their feed. This research was separated into 3 individual feeding treatment as control, L. reuteri (Lr groups) and P. acidilactici (Pa groups). The shrimp was feeding with 103, 105, and 107 cfu/feed (g) L. reuteri namely as Lr3, Lr5, and Lr7. The shrimp was feeding with 103, 105, and 107 cfu/feed (g) P. acidilactici were named Pa3, Pa5, and Pa7, respectively. Through 8 weeks of feeding, the results revealed that the use of shrimp feed incorporated with lactic acid bacteria did not cause negative effects on water quality. The testing items include ammonia-nitrogen concentration, nitrite-nitrogen concentration, and total vibrio count in the water. In addition, the lactic acid bacteria concentration in the water were in the range of 1.33 ± 0.58 × 101 to 9.77 ± 1.34 × 102 cfu/mL. Observations of the growth performance of the white shrimps after 8 weeks of feeding revealed that both bacteria were beneficial to shrimp growth. In particular, group Lr7 had the highest percentage weight gain (107.99 ± 3.92%), special growth rate (1.93 ± 0.07%), feed conversion ratio (3.34 ± 0.05), and survival rate (97.22 ± 4.81%). Furthermore, observations of the nonspecific immunity reactions of the white shrimps after 4 weeks of feeding indicated that on day 4, the total number of haemocyte in shrimps in groups Lr5, Lr7, Pa3, and Pa5 significantly increased. On days 1 and 4, the phenoloxidase activity and superoxide axion production rates of the Lr group and Ls group increased. This phenomenon was the most significant in group Lr7, and the effect continued until day 28. After day 7, the phagocytic rate of groups Lr5 and Lr7 significantly increased. In addition, Lr and Pa groups exhibited significant increases in the phagocytic index after days 4 and 14, respectively. This phenomenon was also the most significant in group Lr7. • Lactobacillus reuteri and Pediococcus acidilactici significantly improved white shrimp growth effect. • Higher concentrations of Lactobacillus reuteri and Pediococcus acidilactici significantly improved nonspecific immunity. • Lactobacillus reuteri and Pediococcus acidilactici can serve as a feed additive with development potential. [ABSTRACT FROM AUTHOR]

Source and raw water quality may deteriorate due to rainfall and river flow events that occur in watersheds. The effects on raw water quality are normally detected in drinking water treatment plants (DWTPs) with a time-lag after these events in the watersheds. Early warning systems (EWSs) in DWTPs require models with high accuracy in order to anticipate changes in raw water quality parameters. Ensemble machine learning (EML) techniques have recently been used for water quality modeling to improve accuracy and decrease variance in the outcomes. We used three decision-tree-based EML models (random forest [RF], gradient boosting [GB], and eXtreme Gradient Boosting [XGB]) to predict two critical parameters for DWTPs, raw water Turbidity and UV absorbance (UV254), using rainfall and river flow time series as predictors. When modeling raw water turbidity, the three EML models (r RF − Tu 2 = 0.87 , r GB − Tu 2 = 0.80 and r XGB − Tu 2 = 0.81) showed very good performance metrics. For raw water UV254, the three models (r RF − UV 2 = 0.89 , r GB − UV 2 = 0.85 and r XGB − UV 2 = 0.88) again showed very good performance metrics. Results from this study suggest that EML approaches could be used in EWSs to anticipate changes in the quality parameters of raw water and enhance decision-making in DWTPs. [Display omitted] • Decision-tree-based ensemble machine learning models were tested to predict quality parameters of raw water supplying DWTP. • Random forest and eXtreme Gradient Boosting techniques yielded the highest metrics for predicting raw water quality. • Decision-tree-based ensemble machine learning techniques may be used in the modelling component early warning systems. [ABSTRACT FROM AUTHOR]

Rural areas lacking essential sewage treatment facilities and collection systems often experience eutrophication due to elevated nutrient loads. Understanding nitrogen (N) sources and transport mechanisms in rural catchments is crucial for improving water quality and mitigating downstream export loads, particularly during storm events. To further elucidate the sources, pathways, and transport mechanisms of N from a rural catchment with intensive agricultural activities during storm events, we conducted an analysis of 21 events through continuous sampling over two rainy seasons in a small rural catchment from the lower reaches of the Yangtze River. The results revealed that ammonia-N (NH 4 +-N) and nitrate-N (NO 3 −-N) exhibited distinct behaviors during rainstorm events, with NO 3 −-N accounting for the primary nitrogen loss, its load being approximately forty times greater than that of NH 4 +-N. Through examinations of the concentration-discharge (c-Q) relationships, the findings revealed that, particularly in prolonged rainstorms, NH 4 +-N exhibited source limited pattern (b = −0.13, P < 0.01), while NO 3 −-N displayed transport limited pattern (b = −0.21, P < 0.01). The figure-eight hysteresis pattern was prevalent for both NH 4 +-N and NO 3 −-N (38.1% and 52.0%, respectively), arising from intricate interactions among diverse sources and pathways. For NO 3 −-N, the hysteresis pattern shifted from clockwise under short-duration rainstorms to counter-clockwise under long-duration rainstorms, whereas hysteresis remained consistently clockwise for NH 4 +-N. The hysteresis analysis further suggests that the duration of rainstorms modifies hydrological connectivity, thereby influencing the transport processes of N. These insights provide valuable information for the development of targeted management strategies to reduce storm nutrient export in rural catchments. [Display omitted] • High-frequency data reveal distinct NH 4 +-N and NO 3 −-N transport in rural areas. • NH 4 +-N is source limited while NO 3 −-N is transport limited under prolonged storms. • Most events had Fig. 8 hysteresis highlighting diverse sources and pathways. • NO 3 −-N hysteresis shift from clockwise to counterclockwise with storm duration. [ABSTRACT FROM AUTHOR]

Land use/land cover (LULC) can have significant impacts on water quality and the health of aquatic ecosystems. Consequently, understanding and quantifying the nature of these impacts is essential for the development of effective catchment management strategies. This article provides a critical review of the literature in which the use of statistical methods to model the impacts of LULC on water quality is demonstrated. A survey of these publications, which included hundreds of original research and review articles, revealed several common themes and findings. However, there are also several persistent knowledge gaps, areas of methodological uncertainty, and questions of application that require further study and clarification. These relate primarily to appropriate analytical scales, the significance of landscape configuration, the estimation and application of thresholds, as well as the potentially confounding influence of extraneous variables. Moreover, geographical bias in the published literature means that there is a need for further research in ecologically and climatically disparate regions, including in less developed countries of the Global South. The focus of this article is not to provide a technical review of statistical techniques themselves, but to examine important practical and methodological considerations in their application in modelling the impacts of LULC on water quality. [Display omitted] • Statistical methods are effective in modelling relationships between land use and water quality. • The results of reviewed studies have been remarkably consistent in several respects. • However, there remain several persistent knowledge gaps which require further research. • These relate to scale, landscape configuration, land use thresholds, and confounding variables. • There is a need for additional context-specific research, especially in developing countries. [ABSTRACT FROM AUTHOR]

Cyanobacteria are the dominating microorganisms in aquatic environments, posing significant risks to public health due to toxin production in drinking water reservoirs. Traditional water quality assessments for abundance of the toxigenic genera in water samples are both time-consuming and error-prone, highlighting the urgent need for a fast and accurate automated approach. This study addresses this gap by introducing a novel public dataset, TCB-DS (Toxigenic Cyanobacteria Dataset), comprising 2593 microscopic images of 10 toxigenic cyanobacterial genera and subsequently, an automated system to identify these genera which can be divided into two parts. Initially, a feature extractor Convolutional Neural Network (CNN) model was employed, with MobileNet emerging as the optimal choice after comparing it with various other popular architectures such as MobileNetV2, VGG, etc. Secondly, to perform classification algorithms on the extracted features of the first section, multiple approaches were tested and the experimental results indicate that a Fully Connected Neural Network (FCNN) had the optimal performance with weighted accuracy and f1-score of 94.79% and 94.91%, respectively. The highest macro accuracy and f1-score were 90.17% and 87.64% which were acquired using MobileNetV2 as the feature extractor and FCNN as the classifier. These results demonstrate that the proposed approach can be employed as an automated screening tool for identifying toxigenic Cyanobacteria with practical implications for water quality control replacing the traditional estimation given by the lab operator following microscopic observations. The dataset and code of this paper are publicly available at https://github.com/iman2693/CTCB. • Implementing ML for cyanobacteria classification. • Introduction of a dataset of 10 toxicogenic cyanobacterial genera. • Proposing the MobileNet for classification of Cyanobacteria. • Utilization of FCNN as the optimal classifier for cyanobacterial cell images. • Reaching to the accuracy and f1-score of 94.79% and 94.91%, respectively. [ABSTRACT FROM AUTHOR]

Monitoring and assessing groundwater quality and quantity lays the basis for sustainable management. Therefore, this research aims to investigate various factors that affect groundwater quality, emphasizing its distance to the primary source of recharge, the Nile River. To this end, two separate study areas have been considered, including the West and West-West of Minia, Egypt, located around 30 and 80 km from the Nile River. The chosen areas rely on the same aquifer as groundwater source (Eocene aquifer). Groundwater quality has been assessed in the two studied regions to investigate the difference in quality parameters due to the river's distance. The power of machine learning to associate different variables and generate beneficial relationships has been utilized to mitigate the cost consumed in chemical analysis and alleviate the calculation complexity. Two adaptive neuro-fuzzy inference system (ANFIS) models were developed to predict the water quality index (WQI) and the irrigation water quality index (IWQI) using EC and the distance to the river. The findings of the assessment of groundwater quality revealed that the groundwater in the west of Minia exhibits suitability for agricultural utilization and partially meets the criteria for potable drinking water. Conversely, the findings strongly recommend the implementation of treatment processes for groundwater sourced from the West-West of Minia before its usage for various purposes. These outcomes underscore the significant influence of surface water recharge on the overall quality of groundwater. Also, the results revealed the uncertainty of using sodium adsorption ratio (SAR), Sodium Percentage (Na%), and Permeability Index (PI) techniques in assessing groundwater for irrigation and recommended using IWQI. The developed ANFIS models depicted perfect accuracy during the training and validation stages, reporting a coefficient of correlation (R) equal to 0.97 and 0.99 in the case of WQI and 0.96 and 0.98 in the case of IWQI. The research findings could incentivize decision-makers to monitor, manage, and sustain groundwater. • Data was collected from two areas that were different from the river. • Physiochemical analysis for 296 samples has been performed. • Hydrogeochemical facies and dynamics have been investigated. • Groundwater appropriateness for various purposes has been evaluated. • ANFIS Model has been developed to predict WQI and IWQI. [ABSTRACT FROM AUTHOR]

Machine learning methodology has recently been considered a smart and reliable way to monitor water quality parameters in aquatic environments like reservoirs and lakes. This study employs both individual and hybrid-based techniques to boost the accuracy of dissolved oxygen (DO) and chlorophyll-a (Chl-a) predictions in the Wadi Dayqah Dam located in Oman. At first, an AAQ-RINKO device (CTD+ sensor) was used to collect water quality parameters from different locations and varying depths in the reservoir. Second, the dataset is segmented into homogeneous clusters based on DO and Chl-a parameters by leveraging an optimized K-means algorithm, facilitating precise estimations. Third, ten sophisticated variational-individual data-driven models, namely generalized regression neural network (GRNN), random forest (RF), gaussian process regression (GPR), decision tree (DT), least-squares boosting (LSB), bayesian ridge (BR), support vector regression (SVR), K-nearest neighbors (KNN), multilayer perceptron (MLP), and group method of data handling (GMDH) are employed to estimate DO and Chl-a concentrations. Fourth, to improve prediction accuracy, bayesian model averaging (BMA), entropy weighted (EW), and a new enhanced clustering-based hybrid technique called Entropy-ORNESS are employed to combine model outputs. The Entropy-ORNESS method incorporates a Genetic Algorithm (GA) to determine optimal weights and then combine them with EW weights. Finally, the inclusion of bootstrapping techniques introduces a stochastic assessment of model uncertainty, resulting in a robust estimator model. In the validation phase, the Entropy-ORNESS technique outperforms the independent models among the three fusion-based methods, yielding R2 values of 0.92 and 0.89 for DO and Chl-a clusters, respectively. The proposed hybrid-based methodology demonstrates reduced uncertainty compared to single data-driven models and two combination frameworks, with uncertainty levels of 0.24% and 1.16% for cluster 1 of DO and cluster 2 of Chl-a parameters. As a highlight point, the spatial analysis of DO and Chl-a concentrations exhibit similar pattern variations across varying depths of the dam according to the comparison of field measurements with the best hybrid technique, in which DO concentration values notably decrease during warmer seasons. These findings collectively underscore the potential of the upgraded weighted-based hybrid approach to provide more accurate estimations of DO and Chl-a concentrations in dynamic aquatic environments. [Display omitted] • Optimized K-means algorithm was used to categorize field measurement points. • Advanced variational AI models were applied to estimate DO and Chl-a indices. • Three hybrid-based methods were established to fuse the outputs of single models. • GA was utilized to assign the optimal weights of the ORNESS weighting method. • The bootstrapping stochastic method was used to evaluate the uncertainty of models. [ABSTRACT FROM AUTHOR]

Within the Huaihe River Basin, Guohe River, as its second-largest tributary, serves as a critical water supply source. Recent industrial and agricultural advancements have led to increased trace element contamination, adversely impacting the water quality within Guohe River Basin. Therefore, this study aimed to investigate the distribution characteristics, sources, water quality and risk assessment of trace elements in the surface water, groundwater, and sediments across the basin. The results showed that the spatial distribution of trace elements in the surface water and groundwater of Guohe River Basin was that most of the high concentrations appeared in Qiaocheng District of Bozhou City, the mean concentration of Fe in Guohe River sediments was the highest, the mean concentration of Sb was the lowest. The PMF source analysis results showed that the main source of trace elements in Guohe River Basin was natural geological processes, followed by human activities. The sodium adsorption ratio (SAR) indicated that the surface water samples of Guohe River in two seasons had high sodium and salinity hazards. The water quality index (WQI) showed that surface water and groundwater samples in the northwestern of Guohe River Basin had poor water quality. The results of the risk assessment showed that As and Mn posed great ecological risks to surface water and groundwater, respectively, and that F− was the pollutant with the most potential health risk hazard in the basin. The Geo-accumulation index (I geo) results showed that Cd, Se and As should be taken seriously as the main contaminants of the sediments in Guohe River Basin. Trace elements; Source analysis; Sodium adsorption ratio; Water quality index; Risk assessment; Geo-accumulation index. • The primary source of trace elements pollution in Guohe River Basin was natural geological processes. • The surface water samples were usually unsuitable for irrigation. • The quality of the surface water and groundwater samples in the northwest of the basin were poor. • F− was the pollutant with the most potential health risk hazard in the basin. • The river sediments were seriously contaminated by Cd, Se and As. [ABSTRACT FROM AUTHOR]

Build-up/wash-off models were originally developed for small-scale laboratory facilities with uniform properties. The effective translation of these models to catchment scale necessitates the meticulous calibration of model parameters. The present study combines the Mat-SWMM tool with a genetic algorithm (GA) to improve the calibration of build-up and wash-off parameters. For this purpose, Mat-SWMM was modified to equip it with the capacity to provide comprehensive water quality analysis outcomes. Additionally, this research also conducts a comparative examination of two distinct types of objective functions in the optimization. Rather than depending on previous literature, this study undertook a numerical campaign to ascertain an appropriate range for the relevant parameters within the case study, thereby ensuring the optimization algorithm's efficient functionality. This research also implements an integrated event calibration approach, i.e., a novel method that calibrates all rainfall events collectively, thus improving systemic interaction representation and model robustness. The findings indicate that employing this methodology significantly enhances the reliability of the outcomes, thereby establishing a more robust procedure. The first objective function (TSS instantaneous less squared difference function, OF 1), which is widely employed in the literature, was designed to minimize the difference between observed and predicted instantaneous Total Suspended Solids (TSS) concentrations. In contrast, the second function (mass and mass peak consistency function, OF 2) considers integral model outputs, i.e., the overall mass balance, the time of the peak mass flow rate, and its intensity. The analysis of the outputs revealed that both objective functions demonstrated sufficient performance. OF 1 provided slightly better performance in predicting the TSS concentrations, whereas OF 2 demonstrated superior ability in capturing global event characteristics. Notably, the optimal parameter set identified through OF 2 aligned with the physically plausible ranges traditionally recommended in technical manuals for urban catchments. In contrast, OF 1's optimal set necessitated an expansion in the acceptable parameter ranges. Finally, from a computational burden viewpoint, OF 1 demanded a significantly higher number of function evaluations, thus implying an escalating computational cost as the range expands. Conversely, OF 2 necessitated fewer evaluations to converge toward the optimal solution. • Enhanced the calibration of build-up/wash-off parameters through integrated event calibration. • Delineated the impact of parameter range size on model performance. • Scrutinized and compared two distinct objective functions. [ABSTRACT FROM AUTHOR]

To study the distribution of trace elements in natural water of the Du River Source National Nature Reserve and to assess the water quality and health risks, Zhushan County in Hubei Province was selected as the study area. Element content in 361 natural water samples collected from Zhushan County were measured by ICP-MS, ICP-OES, and HG-AFS. The main anions and cations present in water samples from Zhushan County are Ca2+ and HCO 3 −. The water chemistry is predominantly influenced by the weathering of carbonate rocks. The water samples with high content of selenium (Se) (0∼82.9 μg/L, mean 4.6 μg/L) in natural water in Zhushan County are mainly distributed in the northern part of Zhushan. The strontium (Sr) content of 49.6% of the water samples (0.001–2.177 mg/L, mean 0.234 mg/L) reached the criteria of natural mineral water for drinking in China (Sr ≥ 0.2 mg/L), which is distributed throughout the county. The high content of metasilicic acid (H 2 SiO 3) (0.026–35.910 mg/L, mean 12.598 mg/L) and zinc (Zn) (0∼407.218 μg/L, mean 12.406 μg/L) are concentrated in northern Zhushan County. 99.7% water samples were freshwater and 98.9% meet the criteria of "good" water quality. All of the natural water samples have low health risk and low heavy metal pollution. 6.1% water samples meet the criteria of Se-type mineral water, while 45.4% meet the criteria of Sr-type mineral water, and 4.4% water samples meet the criteria of "low sodium, high Se, and high Sr" mineral water. Zhushan County has the potential for Se-type mineral water and Sr-type mineral water development. The findings of this study hold immense significance for the public health implications of drinking water in Du River Source, thereby offering valuable insights for effective water resources management. [Display omitted] • Natural water from the Du River Source meets drinking standards. • Light health risk of natural water from Du River Source. • Light heavy metal pollution of natural water from Du River Source. • The Du River Source has the potential to develop Se-rich and Sr-rich water. [ABSTRACT FROM AUTHOR]

[Display omitted] • Establishing a health baseline to assist with investigations into mass bivalve die-offs. • Higher bacterial loads isolated from mortality samples. • Lower gene copy number of Endozoicomonas spp. detected in mortality samples. • Changes in infection prevalence and intensity can be more easily measured. Disease is a major threat to the economic, ecological and cultural services provided by wild bivalve populations. Over the past decade anecdotal reports on declining health of native bivalve populations around Aotearoa New Zealand have been supported by increasing observations of mass die-offs. Causes of declining health and mass die-offs of wild bivalves are not clear and could be due to a number of interactive and cumulative factors, including declining water quality, climate change, or disease. Pipi/kōkota (Paphies australis) within the Whangārei area (northern New Zealand) have suffered repeated die-offs and declining health since at least 2009. Baseline health data for wild native bivalve populations are scarce making it difficult to identify changes in pathogen infection prevalence and intensity and infer their importance to host health. This research aimed to examine and document the health of pipi in Whangārei with the objective of identifying factors that may contribute to their ill health and lack of population recovery. We sampled pipi from four sites within Whangārei, eight times across two years (total n = 640) to establish a health baseline using histopathology, general bacteriology, and qPCR for the intracellular bacteria Endozoicomonas spp. Three pipi mass die-offs occurred during the sampling window that were opportunistically sampled to compare against the health baseline established using healthy pipi. An increase in bacterial growth and a decrease in the abundance of Endozoicomonas spp. in mortality pipi was observed compared with the health baseline. Establishing a health baseline for pipi from Whangārei provided a benchmark to assess changes in a pipi population experiencing high mortality. Such data can help identify factors contributing to die-offs and to help inform what mitigation, if any, is possible in wild shellfish populations. [ABSTRACT FROM AUTHOR]

Ongoing climate change and anthropogenic impacts will continue to worsen the problem of water crisis. In order to explore practical solutions for drought and climate change adaptation, this work uses a set of different methodologies to evaluate an operational fog collection project and discuss solutions for some emerging challenges. This study uses fog collection rate, Water Quality Index (WQI) and interviews with the community as indicators for the assessment. Results indicate that the project continues to deliver improved drinking water access to the community. Fog harvesting rate yielded an annual average from 1.6 to 6 L/m2/d. Interviews confirm the social commitment of the local community. However, challenging points emerge: (1) ongoing groundwater pollution due to the lack of sanitation; (2) if fog water is the only source, inconsistent fog yields may negatively impact water availability; (3) poor solid waste management. The findings represent a baseline for assessing and benchmarking other similar projects or project proposals in the Atlantic coast of North Africa. Therefore, the proposed methodology can also be used in other fog collection projects around the world. [Display omitted] • Sidi Ifni project, Morocco, is the largest fog collection project in the world. • A pilot multi-aspect assessment procedure is proposed. • The fog harvesting rate yielded an annual average of 1.6–6 L/m2/d. • Interviews confirm the technology appropriation by the local community. • Environmental pollution and fog yield variability represent the main challenge. [ABSTRACT FROM AUTHOR]

This study explores the application of a tyrosinase cantilever nanobiosensor for detecting 17β-estradiol and estrone in typical water systems. The physical-chemical parameters of water were evaluated within the Tigre River micro-basin in Erechim, RS, to determine water potability for urban populations. Water clarity, conductivity, and pH levels were essential markers, adhering to recognized standards for water quality and human consumption. The cantilever nanobiosensor demonstrated strong sensitivity and a broad linear range, with a limit of detection (<0.00051 ppb) surpassing other enzymatic biosensors and covering a range of 0.0001–100 ppb. The real water sample quality investigated in relation to contamination with 17β-estradiol and estrone by nanobiosensor showed values below the LOD for both compounds. Recovery studies demonstrated the reliability of the nanobiosensor. Selectivity tests indicated minimal interference from structurally similar substances. This study validates the nanobiosensor's potential for environmental monitoring and hormone detection, aligning with standard practices. [Display omitted] • Tyrosinase can be used in a cantilever nanobiosensor for hormone detection in water systems. • 17β-estradiol and estrone were detected using nanobiosensor in river water. • The nanobiosensor developed present practical application for environmental monitoring. [ABSTRACT FROM AUTHOR]

Dual-source drinking water distribution systems (DWDS) over single-source water supply systems are becoming more practical in providing water for megacities. However, the more complex water supply problems are also generated, especially at the hydraulic junction. Herein, we have sampled for a one-year and analyzed the water quality at the hydraulic junction of a dual-source DWDS. The results show that visible changes in drinking water quality, including turbidity, pH, UV 254 , DOC, residual chlorine, and trihalomethanes (TMHs), are observed at the sample point between 10 and 12 km to one drinking water plant. The average concentration of residual chlorine decreases from 0.74 ± 0.05 mg/L to 0.31 ± 0.11 mg/L during the water supplied from 0 to 10 km and then increases to 0.75 ± 0.05 mg/L at the end of 22 km. Whereas the THMs shows an opposite trend, the concentration reaches to a peak level at hydraulic junction area (10–12 km). According to parallel factor (PARAFAC) and high-performance size-exclusion chromatography (HPSEC) analysis, organic matters vary significantly during water distribution, and tryptophan-like substances and amino acids are closely related to the level of THMs. The hydraulic junction area is confirmed to be located at 10–12 km based on the water quality variation. Furthermore, data-driven models are established by machine learning (ML) with test R 2 higher than 0.8 for THMs prediction. And the SHAP analysis explains the model results and identifies the positive (water temperature and water supply distance) and negative (residual chlorine and pH) key factors influencing the THMs formation. This study conducts a deep understanding of water quality at the hydraulic junction areas and establishes predictive models for THMs formation in dual-sources DWDS. • The hydraulic junction area of dual-source DWDS was located. • Quantitative analysis of organic characterization is conducted by PARAFAC and HPSEC analysis. • Date-driven models for THMs prediction is established by ML. • The key factors that influencing THMs formation is identified by SHAP analysis. • The risks and advantages of dual-source DWDS are summarized. [ABSTRACT FROM AUTHOR]

Forest fertilization with municipal biosolids has been shown to increase tree growth and enhance forest soils. However, there are concerns that nitrogen from the biosolids could impact surface waters through movement from subsurface flow. Here we analyzed data on soil and surface water nitrogen from a working tree plantation that has used biosolids for over three decades to see if there was evidence of N movement through the soil to surface waters. GIS (Geographic Information System) was used to map application units over time and LiDAR (Light Detection and Ranging) was used to delineate watersheds. The program is located in King County Washington with biosolids provided by the King County Wastewater Treatment program. We assembled records to determine if there is any evidence of movement of NO 3 − through soils or any enrichment in surface waters. While soils show evidence of NO 3 − enrichment following biosolids application with cumulative loading rates up to 26 Mg ha−1, this is generally limited to the 'A' soil horizon and does not increase linearly with increased biosolids loading rates. There was no indication of increased surface water NO 3 − concentration relative to biosolids application rates, with a small trend of decreasing water NO 3 − over time. Surface water NO 3 − concentration was not correlated with the fraction of the watershed area that had been amended with biosolids, and there was no observable increase in surface water NO 3 − with increased frequency of biosolids applications to the tree plantations. These results suggest that the current biosolids program is sufficiently protective of ground and surface waters. These observations suggest that biosolids application can be conducted on a large scale with multiple benefits and no discernible impact to surface waters. [Display omitted] • Municipal biosolids enhance tree growth and improve soil quality on tree farms. • Nitrate leaching concerns can limit application frequency and rates. • Long-term data from commercial applications was used evaluate nitrogen movement. • Biosolids increased surface soil NO 3 - but no changes in water N were observed. [ABSTRACT FROM AUTHOR]

Drawing upon an extensive body of valuation literature focused on water quality, this paper performs a meta-analysis benefit transfer exercise aimed at quantifying willingness to pay (WTP) for an enhancement in drinking water quality for households that have been directly exposed to Perfluoroalkyl Substances (PFAS) over recent decades in Italy. The analysis compiles metadata of 72 WTP estimates extracted from 40 previous valuation studies conducted in advanced economies. The benefit transfer is realized estimating a meta regression model (MRM) which includes both study design and socio-economic explanatory variables, according to the Weak Structural Utility Theoretic approach. To determine the most suitable MRM specification, a comparative evaluation of various model configurations is developed exploiting the Least Absolute Shrinkage and Selection Operator (LASSO) selection criterion, and assessing their predictive performances in terms of transfer error and explanatory power. The mean transfer error (MTE) and the adjusted R-squared of the preferred MRM are in line with past published meta-analyses (0.665 and 0.607, respectively). The parameters estimated in the model align with both economic theory and intuition. The benefit transfer process results in an estimated annual WTP of € 250.80 per household for improved drinking water quality in the PFAS-affected area and an aggregated value of social benefits from PFAS decontamination of around € 12 million. • First meta-analysis focused on drinking water quality valuation in developed economies. • WTP for PFAS decontamination of drinking water via benefit transfer. • LASSO selection criteria applied for the selection of variables in the meta-regression model. • New dataset for drinking water quality valuation around the world. [ABSTRACT FROM AUTHOR]

Harvesting of plantation conifers on peatlands is carried out as part of restoration and forestry operations. In particular, in the UK and Ireland, conifer plantations on drained ombrotrophic blanket and raised bogs are increasingly being removed (by harvesting), along with blocking of drainage ditches to help raise water tables to reinitiate and restore bog vegetation and function. However, both tree harvesting and peatland restoration operations can have significant impacts on water quality at local and catchment scales. Previous research has suggested that leaching from leftover decomposing brash (tree tops and branches, including wood and needles) is the primary cause, while other work has suggested that release from rewetted peat also contributes to water quality changes. This research investigates the relative importance of peat rewetting, needles and branches on water quality using mesocosm experiments, to help elucidate the mechanisms behind water quality changes following restoration and harvesting operations. Peat and brash were collected from a drained afforested blanket bog in the Flow Country, Scotland. Short-term mesocosm experiments were conducted by incubating peat, peat + needles and peat + needles + branches with rainwater in quadruplicate. Brash from Sitka spruce (Picea sitchensis) and lodgepole pine (Pinus contorta) was investigated separately, while we also conducted experiments with fresh and aged (∼18 months) brash. Peat, needles and branches all significantly impacted water quality in the order of branches > needles > peat, while concentrations of DOC, PO 4 3−, NH 4 +, K and Mn were most impacted. Water quality impacts of spruce brash appeared generally greater than pine, while fresh brash had larger effects than aged brash. In our mesocosms, relative contributions to water quality changes were estimated by elemental yields. On average, peat contributed 25.4% (range 0.6–72.3%), while needles and brash contributed 19.7% (range 3.0–37.0%) and 54.9% (range 22.1–70.2%) to yields, respectively. We further estimate that 267 kg C ha−1 (255.8 kg as DOC, 10.7 kg as DIC), 27.4 kg K ha−1, 5.8 kg P ha−1 (as PO 4 3−) and 0.5 kg N ha−1 (as NH 4 +) could be released from brash, over nine days. [Display omitted] • Relative contributions of peat, needles and branches to water quality were assessed. • DOC, PO 4 3−, NH 4 +, K and Mn were collectively the variables most impacted. • Contributions to leaching were peat (25.4%), needles (19.7%) and branches (54.0%). • Removal of needles and branches could help mitigate water pollution. [ABSTRACT FROM AUTHOR]

Surface water nutrient pollution, the primary cause of eutrophication, remains a major environmental concern in Western Lake Erie despite intergovernmental efforts to regulate nutrient sources. The Maumee River Basin has been the largest nutrient contributor. The two primary nutrient sources are inorganic fertilizer and livestock manure applied to croplands, which are later carried to the streams via runoff and soil erosion. Prior studies of nutrient source attribution have focused on large watersheds or counties at annual time scales. Source attribution at finer spatiotemporal scales, which enables more effective nutrient management, remains a substantial challenge. This study aims to address this challenge by developing a generalizable Bayesian network model for phosphorus source attribution at the subwatershed scale (12-digit Hydrologic Unit Code). Since phosphorus release is uncertain, we combine excess phosphorus derived from manure and fertilizer application and crop uptake data, flow information simulated by the SWAT model, and in-stream water quality measurements using Approximate Bayesian Computation to derive a posterior that attributes phosphorus contributions to subwatersheds. Our results show significant variability in subwatershed-scale phosphorus release that is lost in coarse-scale attribution. Phosphorus contributions attributed to the subwatersheds are on average lower than the excess phosphorus estimated by the nutrient balance approach currently adopted by environmental agencies. Fertilizer contributes more soluble reactive phosphorus than manure, while manure contributes most of the unreactive phosphorus. While developed for the specific context of Maumee River Basin, our lightweight and generalizable model framework could be adapted to other regions and pollutants and could help inform targeted environmental regulation and enforcement. • Our model traces phosphorus sources by combining its excess, flow, and water quality. • Phosphorus release shows significant spatial variations and peaks in spring planting. • Fertilizer contributes more soluble reactive phosphorus than manure. • Manure contributes most of the unreactive phosphorus. • The lightweight and generalizable framework can improve targeted pollution management. [ABSTRACT FROM AUTHOR]

The ecological health of freshwater rivers is deteriorating globally due to careless human activities, for instance, the emission of plastic garbage into the river. The current research was the first assessment of microplastics (MPs) pollution in water, sediment, and representative organisms (fish, crustacean, and bivalve) from the Surma River. Water, sediment, and organisms were sampled from six river sites (Site 1: Charkhai; Site 2: Golapganj; Site 3: Alampur; Site 4: Kazir Bazar; Site 5: Kanishail and Site 6: Lamakazi), and major water quality parameters were recorded during sampling. Thereafter, MPs in water, sediment, and organism samples were extracted, and then microscopically examined to categorize selected MPs types. The abundance of MPs, as well as size, and color distribution, were estimated. Polymer types were analyzed by ATR-FTIR, the color loss of MPs was recorded, the Pollution Load Index (PLI) was calculated, and the relationship between MPs and water quality parameters was analyzed. Sites 4 and 5 had comparatively poorer water quality than other sites. Microplastic fibers, fragments, and microbeads were consistently observed in water, sediment, and organisms. A substantial range of MPs in water, sediment, and organisms (37.33–686.67 items/L, 0.89–15.12 items/g, and 0.66–48.93 items/g, respectively) was recorded. There was a diverse color range, and MPs of <200 μm were prevalent in sampling areas. Six polymer types were identified by ATR-FTIR, namely Polyethylene (PE), Polyamide (PA), Polypropylene (PP), Cellulose acetate (CA), Polyethylene terephthalate (PET), and Polystyrene (PS), where PE (41%) was recognized as highly abundant. The highest PLI was documented in Site 4 followed by Site 5 both in water and sediment. Likewise, Sites 4 and 5 were substantially different from other study areas according to PCA. Overall, the pervasiveness of MPs was evident in the Surma River, which requires further attention and prompt actions. [Display omitted] • The Surma River's water, sediment, and organisms contain a large extent of MPs. • The water purity in the river sites might be degraded due to MPs. • ATR-FTIR detected six polymers including polyethylene as highly abundant. • The PLI ranked the Surma River as category I in the case of MP pollution. • The pervasiveness of MPs was evident in upstream water and its life. [ABSTRACT FROM AUTHOR]

Excess nitrogen (N) discharged into streams and rivers degrades freshwater quality and threatens ecosystems worldwide. Land use patterns may influence riverine N export, yet the effect of location on N export and removal is not fully understood. We proposed a hybrid model to analyze N export and removal within the watersheds. The proposed model is satisfied for the riverine N modelling. The KGE and R2 are 0.75 and 0.72 in the calibration period which are 0.76 and 0.61 in the validation period. Human-impacted land use may modify the N yield in the watershed, and the net N export from built-up to the in-stream system was highest in the urbanized sub-watersheds (0.81), followed by the agricultural sub-watersheds (0.88), and forested sub-watersheds (0.96). Agricultural activities make a large contribution to the N exports in the watersheds, and the mean N input from the agricultural land use to in-stream were 2069–4353 kg km−2 yr−1. Besides, the excess inputs of N by overapplication of fertilizer and manure during the agricultural activities may increase legacy N in soil and groundwater. Biological processes for the riverine N removal may be controlled by the available substrate in the freshwater system, and temperature sensitivity of denitrification is highest in the flood seasons, especially for the human-impacted sub-watersheds. The riverine biological processes may be limited by other competitions. Our model results provide evidence that quantity and location of specific land use may control biogeochemistry within watersheds. We demonstrate the need to understand nutrient export and removal within watersheds by improving the representation of spatial patterns in existing watershed models, and we consider this study to be a new effort for the spatially explicit modeling to support land-use based N management in watersheds. [Display omitted] • A hybrid model was proposed to quantify the watershed nitrogen export and removal. • Human-impacted land use may modify the N yield in the watershed. • Agricultural activities contribute largely to the legacy N. • The riverine biological N uptake may be limited by competition with dissimilatory nitrate reduction to ammonium. [ABSTRACT FROM AUTHOR]

Information on long-term trends in total suspended solids (TSS) is critical for assessing aquatic ecosystems. However, the long-term patterns of TSS concentration (C TSS) and its latent drivers have not been well investigated. In this study, we developed and validated three semi-analysis algorithms for deriving C TSS using Landsat images. Subsequently, the long-term trends in C TSS in the Pearl River Estuary (PRE) from 1987 to 2022 and the driving factors were clarified. The developed algorithms yielded excellent performance in estimating C TSS , with mean absolute percentage errors <25% and root mean square errors of <13 mg/L. Long-term Landsat observations showed an overall decreasing trend and significant spatiotemporal dynamics of the C TSS in the PRE from 1987 to 2022. The analysis of driving factors suggested that industrial sewage, cropland, forests and grasslands, and built-up land were the four potential driving forces that explained 87.81% of the long-term variation in C TSS. This study not only provides 36-year recorded datasets of C TSS in estuary water, but also offers new insights into the complex mechanisms that regulate C TSS spatiotemporal dynamics for water resource management. • Three novel algorithms allow remote-sensing monitoring of total suspended solids concentration (C TSS) in Pearl River Estuary (PRE). • 36-year Landsat observations unveiled significant spatiotemporal patterns and overall increasing trend of C TSS in PRE. • Driver analysis revealed that the cropland, industrial sewage, forests and grassland, build-up land can collectively explain 87.81% of the long-term changes in C TSS. • Our study has implications for future precise eutrophication control and efficient water resources management. [ABSTRACT FROM AUTHOR]

The food web is a cycle of matter and energy within river ecosystems. River environmental changes resulting from human activities are increasingly threatening the composition and diversity of global aquatic organisms and the multi-trophic networks. How multiple environmental factors influence food web patterns among multi-trophic microbial communities in rivers remains largely unknown. Using water quality evaluation and meta-omics techniques, we investigated the composition, structure and interaction characteristics, and drivers of food webs of microorganisms (archaea, bacteria, fungi, protists, metazoa, viridiplantae and viruses) at multiple trophic levels in different water quality environments (Classes II, III, and IV). First, water quality deterioration led to significant changes in the composition of the microbial community at multiple trophic levels, which were represented by the enrichment of Euryarchaeota in the archaeal community, the increase of r-strategists in the bacterial community, and the increase of the proportion of predators in the protist community. Second, deteriorating water quality resulted in a significant reduction in the dissimilarity of community structure (homogenization of community structure in Class III and IV waters). Of the symbiotic, parasitic, and predatory networks, the community networks in Class II water all showed the most stable symbiotic, parasitic, and predatory correlations (higher levels of modularity in the networks). In Class III and IV waters, nutrient inputs have led to increased reciprocal symbiosis and decreased competition between communities, which may have the risk of a positive feedback loop driving a system collapse. Finally, inputs of phosphorus and organic matter could be the main drivers of changes in the planktonic microbial food web in the Fen River. Overall, the results indicated the potential ecological risks of exogenous nutrient inputs, which were important for aquatic ecosystem conservation. [Display omitted] • Water quality deterioration drove shift in bacterial community to r-strategists. • Water quality degradation increased the proportion of heterotrophic protists. • Trophic transfer efficiency of bacteria, fungi, and metazoa was greatly affected. • Positive feedback loops and associated ecological destabilization risk increased. • TP and CODcr are the main factors driving the microbial food web in the Fen River. [ABSTRACT FROM AUTHOR]

The increasing concern over pesticide pollution in water bodies underscores the need for effective mitigation strategies to support the transition towards sustainable agriculture. This study assesses the effectiveness of landscape mitigation strategies, specifically vegetative buffer strips, in reducing glyphosate loads at the catchment scale under realistic conditions. Conducted over six years (2014–2019) in a small agricultural region in Belgium, our research involved the analysis of 732 water samples from two monitoring stations, differentiated by baseflow and event-driven sampling, and before (baseline) and after the implementation of mitigation measures. The results indicated a decline in both the number and intensity of point source losses over the years. Additionally, there was a general decrease in load intensity; however, the confluence of varying weather conditions (notably dry years during the mitigation period) and management practices (the introduction of buffer strips) posed challenges for a statistically robust evaluation of each contributing factor. A reduction of loads was measured when comparing mitigation with baseline, although this reduction is not statistically significant. Glyphosate loads during rainfall events correlated with a rainfall index and runoff ratio. Overall, focusing the mitigation strategy on runoff and erosion was a valid approach. Nevertheless, challenges remain, as evidenced by the continuous presence of glyphosate in baseflow conditions, highlighting the complex dynamics of pesticide transport. The study concludes that while progress has been made towards reducing pesticide pollution, the complexity of interacting factors necessitates further research. Future directions should focus on enhancing farmer engagement in mitigation programs and developing experiments with more intense data collection that help to assess underlying dynamics of pesticide pollution and the impact of mitigation strategies in more detail, contributing towards the goal of reducing pesticide pollution in water bodies. [Display omitted] • A 6-year monitoring study was conducted in an agricultural catchment in Belgium. • The study evaluated in-field vegetated strips for glyphosate mitigation. • A decrease in glyphosate point losses was observed. • Glyphosate event load reduction in the river was linked to weather and mitigation. [ABSTRACT FROM AUTHOR]

Managing surface water quality is a global challenge, and understanding spatial and temporal patterns of water quality is a key component to effective management. However, analysis of spatiotemporal patterns of impaired waters over broad areas is sparse due to disparate water quality data and variable water quality standards. Thus, here we leverage the Alabama 303(d) List of impaired waters to present a new perspective for investigating spatiotemporal water quality patterns. Every two years, each state in the United States is required to assess its surface water quality and compile a list of impaired waterbodies, meaning waters that do not meet water quality standards for their designated usage – referred to as the 303(d) List. The purpose of the 303(d) List is to identify impaired waters so that corrective action can be taken to reduce pollutant loads and, ultimately, improve water quality. Using GIS, a space time cube was created to analyze and visualize spatiotemporal patterns of the impaired rivers added to the Alabama 303(d) Lists from 1996 to 2022. For this analysis, the percentage of river length impaired out of the total river length, and number of times each impairment cause was listed, were summarized within Alabama sub-basins (Hydrologic Unit Code 8) (n = 51). Trend and hot spot analyses were conducted on the river impairment and causes. There was an up trend in river impairment for eight sub-basins across the state and a downtrend in one sub-basin. Over half of the sub-basins with an up trend in impairment also had an up trend in the number of times pathogens was listed as a cause of impairment. Additionally, coastal sub-basins were found to be a hot spot for river impairment. Interestingly, there was a down trend in the number of times nutrients, ammonia, and siltation were listed as a cause of impairment at the state and sub-basin scales of analysis. Altogether, these findings show the use of spatiotemporal pattern analysis of impaired waters and can indicate where, both spatially and by pollutant, management should prioritize water quality improvement efforts. [Display omitted] • Spatiotemporal analysis of impaired waters provides new insight on water quality. • Trends in river impairment change with the scale of analysis. • At the state scale, there is no trend in river impairment but trends in sub-basins. • Coastal sub-basins are hot spots of river impairment. • At the sub-basin scale, pathogens are the only impairment cause with an up trend. [ABSTRACT FROM AUTHOR]

One of the methods of increasing the availability of drinking water is to reduce water losses in existing water supply systems (WSS). The need to manage water losses in WSS is highlighted in the new Directive (EU) 2020/2184 of the European Parliament and of the Council of 16 December 2020 on the Quality of Water Intended for Human Consumption. It was indicated that the main cause of water losses is underinvestment in the maintenance and renovation of network infrastructure. The new legal provisions require a risk assessment to be carried out in the water supply system, taking into account the risk of leaks. The paper presents the concept of estimating the risk of water losses in the water supply network using the three-parameter risk assessment method and risk maps. The framework of the water balance proposed by International Water Association (IWA) were also presented, including the Infrastructure Leakage Index (ILI) for assessment of the water supply system Leakage Performance Category (LPC). The analysis was carried out for a water supply system used by 200,000 inhabitants. The LPC of the system was determined based on the ILI index. Then the water supply network pipes that could potentially be a source of leaks were identified. The analysis of the risk of water losses for the examined pipes allowed to determine which pipes should be first chosen to reduce the risk of water losses, i.e. active search for leaks. • A new method for assessing the risk of water leaks in the water supply network was proposed (three-parameters risk matrix). • The pipe: diameter, material, age, pressure and failure index was identified as a parameters influencing the risk of leakage. • The results of the analysis were presented on the risk maps. • The presented risk-based approach is consistent with the new legal provisions for EU Member States. [ABSTRACT FROM AUTHOR]

Water renewal and flushing in small, intermittently open or closed estuaries is receiving increasing attention particularly in light of the climate change induced alterations in run-off, wave and sediment transport conditions along coasts. The challenges of predicting the stratification-circulation state and the balance between tidal or freshwater flushing in response to the mouth dynamics of small, wave-dominated estuaries is the focus of the paper. Such predictions are required for determining estuary freshwater requirements or establishing an estuary's capacity to maintain sound water quality under pollutant discharges. Advances in simulating changes in stratification-circulation over long time scales are limited. Instead attention has focused on generating indices of stratification or water quality state using heuristic methods. In this paper, systems dynamics modelling is applied to simulate the non-linear response of the estuary to changes in river and marine water fluxes. The estuary is modelled as a basin with a specified water volume to water level relationship, connected to the sea by a channel with variable sill height, but fixed width. The direction and magnitude of the flow through the mouth determines whether the sill height erodes or accretes and hence the mouth dynamics (see Slinger, 2017). The tidal flux through the mouth co-determines the volumetric exchange of salt, influencing both the stratification state of the estuary and the degree of tidal or freshwater flushing. This is also influenced by run-off. The resulting dynamic balance is captured in two bulk indices, the Estuarine Richardson number and the bulk densimetric Froude number. Using measured data from the Great Brak Estuary, South Africa, the model is calibrated. Model simulations demonstrate the importance of tidal flushing and concomitant mouth breaching for water renewal as freshwater flushing declines under scenarios of increased water abstraction. Although the estuary remains partially mixed, there is increased average salinity and a more uniform the water column. Water releases and mouth breaching bring about a more natural stratification-circulation state, but these effects are short-lived. • Parametric simulation of water renewal in wave-dominated, intermittent estuaries. • A stratification index analogous to the Estuarine Richardson number is modelled. • A circulation index analogous to the bulk densimetric Froude number is simulated. • Stratification-circulation simulations indicate increased water column uniformity. • Mouth breaching & floods temporarily allow more natural stratification-circulation. [ABSTRACT FROM AUTHOR]

Since 2015, green tides have recurred annually in Jinmeng Bay (JMB), China. Reclamation projects have been considered an important anthropogenic perturbation in JMB for green tides. A coupled hydrodynamic and water quality model was used to simulate hydrodynamic and transport processes for different artificial structure scenarios. Numerical results prove that reclamation projects exert a significant impact on the water environment in JMB, and nutrient distributions are mainly influenced by Conch Island, which decreases pollutant dilution and diffusion in coastal waters. Moreover, the average residence time increases by about 35% after the construction of the two artificial islands. Areas with long residence time coincide with the major sources of the green tide blooms, which declares that the weak water exchange capacity affected by artificial islands is responsible for the water quality degradation. The increased nutrient levels and hydraulic residence time also suggest the high possibility of green algal blooms in JMB. • Reclamation projects effect on the water environment in Jinmeng Bay was assessed. • Residence time increases by 35% after the construction of artificial islands. • The artificial islands result in the deterioration of water quality in Jinmeng Bay. • Heavy river input combined with artificial islands is a key factor in green tides. [ABSTRACT FROM AUTHOR]

Understanding saltwater intrusion processes is crucial for both ecosystem health and water resource management in river estuaries. With the development of the global coastal economy, many estuaries worldwide have undergone shipping engineering constructions. Channel deepening in coastal areas adversely impacts the quality of freshwater required for ecological purposes, human consumption, and agricultural and industrial activities. Many studies have focused on saltwater intrusion processes in artificial canals capable of high and medium runoff characteristics; however, little is known about seawater intrusions in canals with low runoff and ship locks located far away from the estuary. This study focuses on the saltwater intrusion process in such a canal, using the Pinglu Canal of Qinjiang River Estuary in China as a prototype example. A three-dimensional (3D) numerical saltwater intrusion model using the standard k–ε turbulence closure was developed to simulate the saltwater intrusion process pre- and post-canal construction. The verification was conducted by comparing the simulated time series of the tidal level, velocity magnitude, and salinity with observations, and the impact of channel deepening on the saltwater intrusion in the Qinjiang River was analysed based on various numerical experiments. After channel deepening, mixing decreased following the decrease in flow velocity, the saltwater intrusion extent could reach the Youth Ship Lock after an increase of 5 km compared to the extent under natural conditions during high tide, and seawater remained in the channel during ebb tide, with freshwater discharge being Q < 20 m3/s. Furthermore, during the dry season, salinity in the approach channel downstream the Youth Ship Lock exhibited a trend of cumulative increase toward a stable value, and the correlation with the tide range cycle decreased from 0.62 under natural conditions to 0.09, whereas the correlation with the upstream inflow increased from 0.10 under natural conditions to 0.51. Results further indicated that the sensitivity of the saltwater intrusion to the flow rate was at a maximum, and its sensitivity to the tidal range was of minor significance after canal construction. Accordingly, a dimensionless function was constructed to quantify freshwater discharge from the Youth Hydro-hub to reduce the saltwater intrusion under variations in the tidal range and salinity during the low-water discharge period. This study can aid water resource management and suggest methods for mitigating saltwater intrusions in this type of artificial canal. • Salt intrusion process is investigated in an artificial canal with low runoff. • Saltwater intrusion extent can reach the ship lock far away from the estuary. • The sensitivity to water discharge is the strongest downstream the ship lock. • The sensitivity to tidal range decreased as increasing of the distance from estuary. • An empirical function is developed to quantify salinity reduction freshwater. [ABSTRACT FROM AUTHOR]

Dissolved organic matter (DOM) is important in determining the drinking water treatment and the supplied water quality. However, a comprehensive DOM study for the whole water supply system is lacking and the potential effects of secondary water supply are largely unknown. This was studied using dissolved organic carbon (DOC), absorption spectroscopy, and fluorescence excitation-emission matrices-parallel factor analysis (EEM-PARAFAC). Four fluorescent components were identified, including humic-like C1–C2, tryptophan-like C3, and tyrosine-like C4. In the drinking water treatment plants, the advanced treatment using ozone and biological activated carbon (O 3 -BAC) was more effective in removing DOC than the conventional process, with the removals of C1 and C3 improved by 17.7%–25.1% and 19.2%–27.0%. The absorption coefficient and C1–C4 correlated significantly with DOC in water treatments, suggesting that absorption and fluorescence could effectively track the changes in bulk DOM. DOM generally remained stable in each drinking water distribution system, suggesting the importance of the treated water quality in determining that of the corresponding network. The optical indices changed notably between distribution networks of different treatment plants, which enabled the identification of changing water sources. A comparison of DOM in the direct and secondary water supplies suggested limited impacts of secondary water supply, although the changes in organic carbon and absorption indices were detected in some locations. These results have implications for better understanding the changes of DOM in the whole water supply system to help ensure the supplied water quality. [Display omitted] • DOM was characterized throughout the whole city water supply system. • The advanced O 3 -BAC treatments improved the removals of DOM. • Humic and protein-like components showed selective removals by different treatments. • Optical indices can be used to detect water quality changes in water supply systems. • First study to examine the effects of secondary water supply on DOM. [ABSTRACT FROM AUTHOR]

The reasonable utilization of water resources and real-time monitoring of water pollution are the core tasks of current world hydrological and water conservancy work. Novel technologies and methods for monitoring water pollution are important means to ensure water health. However, the absence of intuitive and simple analysis methods for the assessment of regional pollution in large-scale water bodies has prevented scientists from quickly grasping the overall situation of water pollution. In this study, we propose a strategy based on the unique combination of fluorescence technology and simple kriging (SK) interpolation (FL-SK) for the first time. This strategy could present the relative magnitude and distribution of the physicochemical indicators of a whole natural lake intuitively and accurately. The unique FL-SK model firstly offers a simple and effective water quality method that provides the pollution index of different sampling points in lakes. The macroscopic evaluation of large-scale water bodies by the FL-SK model primarily relies on the fluorescence response of the RDM-TPE to the comprehensive indicators of the water body, as experimental results have revealed a good correlation between fluorescent responses and six normalized physicochemical indicators. Multiple linear regression and fluorescence response experiments on RDM-TPE indicate that to some extent, the fluorescence signals of the FL-SK model may originate from a certain type of sulfide in the water body. Pattern discovery could enable the analysis of pollution levels in other ecosystems and promote early pollution assessment in the future. [Display omitted] • We developed a unique combination mode FL–SK for the first time. • The FL-SK mode could present pollution levels in natural water intuitively and accurately. • The evaluation of water bodies by FL-SK mainly relies on the fluorescence data of RDM-TPE. • Pattern discovery could enable the analysis of pollution levels in other ecosystems. [ABSTRACT FROM AUTHOR]

Hydrogen sulfide (H 2 S) is one of the sewer gases commonly found in wastewater collection systems. This anaerobic degradation product causes issues, ranging from odor nuisances and health hazards to pipe corrosion. Several studies have provided an understanding of H 2 S formation mechanism, including simulations of H 2 S emissions in sewers, especially in pressurized systems. However, the present models necessitate a large amount of data due to the complexity of the H 2 S processes and common routine-monitoring water quality parameters may not fit the requirements. This study aims to simulate the fate and transport of H 2 S in both air and water phases in combined sewers, with a realization of practicableness of the application. The study case is centered around a fresh market in Bangkok, where the sewers are commonly plagued with garbage-related issues. These challenges pose difficulties for site monitoring across various aspects, necessitating the application of unconventional methods. On-site hydrodynamics, wastewater quality, and H 2 S gas concentration data were monitored on hourly and daily bases. It was found that the sulfides in the combined sewerage were correlated with sewage quality, e.g., COD, sulfate (SO 4 2−), and pH concentrations in particular. The model results were in an acceptable range of accuracy (R2 = 0.63; NSE = 0.52; RMSE = 1.18) after being calibrated with the measured hydrogen sulfide gas concentration. The results lead to the conclusion that the simplified model is practical and remains effective even in sewers with untraditional conditions. This could hold promise as a fundamental tool in shaping effective H 2 S mitigation strategies. • Hydrogen sulfide notably persists in combined sewers despite stormwater dilution. • Tracer moment analysis effectively depicts hydrodynamics in obstructed sewers. • Thoughtful simplification enhances model implementability with minor trade-offs. • Original field monitoring of hydrogen sulfide enables insightful model calibration. • Resembling substrate attributes in domestic sewages suggest common fraction values. [ABSTRACT FROM AUTHOR]

Nowadays, biomarkers are recognized as valuable tools to complement chemical and ecological assessments in biomonitoring programs. They provide insights into the effects of contaminant exposures on individuals and establish connections between environmental pressure and biological response at higher levels. In the last decade, strong improvements in the design of experimental protocols and the result interpretation facilitated the use of biomarker across wide geographical areas, including aquatic continua. Notably, the statistical establishment of reference values and thresholds enabled the discrimination of contamination effects in environmental conditions, allowed interspecies comparisons, and eliminated the need of a reference site. The aim of this work was to study freshwater-estuarine-coastal water continua by applying biomarker measurements in multi-species caged organisms. During two campaigns, eight sentinel species, encompassing fish, mollusks, and crustaceans, were deployed to cover 25 sites from rivers to the sea. As much as possible, a common methodology was employed for biomarker measurements (DNA damage and phagocytosis efficiency) and data interpretation based on guidelines established using reference values and induction/inhibition thresholds (establishment of three effect levels). The methodology was successfully implemented and allowed us to assess the environmental quality. Employing multiple species per site enhances confidence in observed trends. The results highlight the feasibility of integrating biomarker-based environmental monitoring programs across a continuum scale. Biomarker results align with Water Framework Directive indicators in cases of poor site quality. Additionally, when discrepancies arise between chemical and ecological statuses, biomarker findings offer a comprehensive perspective to elucidate the disparities. Presented as a pilot project, this work contributes to gain insights into current biomonitoring needs, providing new questions and perspectives. • A novel strategy to monitor aquatic continua using biomarkers is proposed. • A common analysis method was applied in multi-species caged organisms. • Biomarkers provide clear and easily useable assessment of the environmental quality. • Reference values and thresholds are recommended to interpret biomarker responses. • Biomarker-based monitoring on a wide scale complements the WFD evaluation. [ABSTRACT FROM AUTHOR]

Water quality indicators (WQIs), such as chlorophyll-a (Chl-a) and dissolved oxygen (DO), are crucial for understanding and assessing the health of aquatic ecosystems. Precise prediction of these indicators is fundamental for the efficient administration of rivers, lakes, and reservoirs. This research utilized two unique DL algorithms—namely, convolutional neural network (CNNs) and gated recurrent units (GRUs)—alongside their amalgamation, CNN-GRU, to precisely gauge the concentration of these indicators within a reservoir. Moreover, to optimize the outcomes of the developed hybrid model, we considered the impact of a decomposition technique, specifically the wavelet transform (WT). In addition to these efforts, we created two distinct machine learning (ML) algorithms—namely, random forest (RF) and support vector regression (SVR)—to demonstrate the superior performance of deep learning algorithms over individual ML ones. We initially gathered WQIs from diverse locations and varying depths within the reservoir using an AAQ-RINKO device in the study area to achieve this. It is important to highlight that, despite utilizing diverse data-driven models in water quality estimation, a significant gap persists in the existing literature regarding implementing a comprehensive hybrid algorithm. This algorithm integrates the wavelet transform, convolutional neural network (CNN), and gated recurrent unit (GRU) methodologies to estimate WQIs accurately within a spatiotemporal framework. Subsequently, the effectiveness of the models that were developed was assessed utilizing various statistical metrics, encompassing the correlation coefficient (r), root mean square error (RMSE), mean absolute error (MAE), and Nash-Sutcliffe efficiency (NSE) throughout both the training and testing phases. The findings demonstrated that the WT–CNN–GRU model exhibited better performance in comparison with the other algorithms by 13% (SVR), 13% (RF), 9% (CNN), and 8% (GRU) when R-squared and DO were considered as evaluation indices and WQIs, respectively. [Display omitted] • Developing singular DL algorithms, CNN and GRU, to estimate DO and Chl-a concentration. • Integrating the singular developed DL algorithms based on CNN-GRU. • Implementing the Wavelet Transform (WT) to enhance the results of the hybrid models. • Comparing the results of individual DL algorithms with that of the hybrid models. • WT improved the accuracy of water quality estimation for the training/testing phases. [ABSTRACT FROM AUTHOR]

Globally, agriculture is a significant pressure on water quality. While nutrient and sediment loss from agricultural land to water can be scientifically complex, mitigation measures primarily focus on reducing farm nutrient stocks or blocking loss pathways. The appropriateness of mitigation measures is dependent on the identification of specific context-related risks on individual farms. However, advisers also need to consider the likelihood of uptake of measures by farmers. Past research has looked at uptake of particular mitigation measures or a small range of measures. This research expands the literature with an analysis of uptake of a broad and diverse range of measures. Farm characteristics, farmer norms, knowledge required and costs (direct and indirect) associated with individual mitigation measures are investigated to identify factors that could influence greater adoption. Results show that alignment to farmer norms and lower specific costs were associated with high adoption rates. These results have implications for advisers in relation to the selection of measures most likely to be adopted by farmers, and also for policy-makers in relation to the need to incentivise the adoption of high-cost measures. • Understanding farmers' uptake of mitigation measures in bespoke plans by advisors is key for water quality improvements. • Implementation costs and alignment to farmer norms influence farmers adoption decisions. • Implementing improvement plans with consideration of these traits will focus resource use by advisors and policymakers. [ABSTRACT FROM AUTHOR]

Small watercourses are essential contributors to catchment water quality, but they continue to suffer degradation across Europe. A results-based agri-environment scheme, aimed at improving watercourse quality in Ireland, developed a rapid drainage assessment to identify point source risks. The assessment uses a scoring system based on visual indicators of nutrient and sediment risk, linking the outcomes to farmer payments. To understand how this novel drainage risk assessment relates to instream watercourse quality, we used three macroinvertebrate-based biotic indices (Q-value, Small Stream Impact Score and Proportion of Sediment Sensitive Invertebrates). Macroinvertebrate kick-sampling and physiochemical analysis were completed in May and July 2021 for 12 'At Risk' and 12 'Not at Risk' small watercourses as identified by the results-based scheme. Results show that the scheme's drainage risk assessment can identify point source risks but we found it does not directly reflect local instream quality as assessed by the biotic indices. Unexpectedly, the biotic indices showed watercourse degradation in 58% of the upstream (control) sampling points, indicating impacts not captured by the drainage risk assessment. Small watercourses displayed high heterogeneity, with significant species turnover between the sampling months. The Small Stream Impact Score was less influenced by temporal change than the Q-value index. There was a significant relationship between instream watercourse quality and sedimentation, as quantified by the Proportion of Sediment Sensitive Invertebrates. Including a measurement of instream sedimentation in the drainage assessments would improve the identification of risks and management. These results show that by linking farmer payments to the drainage risk assessments results-based payment schemes could positively contribute to improving catchment scale watercourse quality, but further work is required to capture wider sources of freshwater impacts. • Small watercourses are important for catchment water quality. • We tested links between rapid risk indicators and biotic indices. • Small watercourses are complex with high heterogeneity and species turnover. • Catchments had extensive levels of degradation linked to multiple stressors. • Biotic indices show significant link between watercourse quality and sedimentation. [ABSTRACT FROM AUTHOR]

Bottled drinking water (BDW) has emerged as the preferred and perceived healthier option for water consumption in the past two decades, even in developing nations. This study aims to assess the baseline levels of dissolved ions in BDW, compares them to drinking water standards, and proposes the optimal minimum ion concentrations. About 30 random BDW samples from densely populated cities in India were collected and analysed for pH, total dissolved solids (TDS), major cations and anions. The maximum and average concentrations of TDS and other dissolved major ions in BDW do not exceed the BIS, WHO, USEPA, and EU standards. Through adherence to food-related norms and human health requirements, this research establishes the minimum optimal concentration of major ions in BDW. In this study, the emphasis on importance of water quality shifts from pesticides and emerging contaminants to a focus on the necessary ion concentrations required in drinking water. • Critical analyses on people perception about BDW were illustrated. • Drinking water standards confirms the scant of minerals in BDW. • Potential health consequences of consuming BDW were represented. • Established the optimal requirements of minerals in BDW. • Importance of ensuring the essential ions in BDW were stressed. [ABSTRACT FROM AUTHOR]

Water scarcity has threatened the sustainability of human life, ecosystem evolution, and socio-economic development. However, previous studies have often lacked a comprehensive consideration of the impact of water quality and existing solutions, such as inter-basin water transfer and unconventional water resources, on water scarcity. In this paper, an improved approach was proposed to quantify water scarcity levels by comprehensively considering surface water quality and multiple solutions. China's water scarcity was first assessed at a high spatial resolution on a monthly basis over the 5-year period from 2014 to 2018. Then, the driving factors including water quality and solutions were identified by a geographic detector model. Finally, an in-depth investigation was conducted to unravel the effects of water quantity solutions (i.e., inter-basin water transfer and unconventional water use), and water quality solutions (i.e., improving surface water quality) on alleviating water scarcity. Based on monthly assessments considering water quality and multiple existing solutions, the results showed that over half of the national population (∼777 million) faced water scarcity for at least one month of the year. Agricultural water use and inadequate water quality were the main driving factors responsible for China's water scarcity. Over four-fifths of the national population (∼1.10 billion) could benefit from alleviated water scarcity through a combination of water quantity and quality solutions. However, the existing solutions considered were insufficient to completely resolve water scarcity in China, especially in Northern China, persisting as a challenging issue. The results obtained from this study provided a better understanding of China's water scarcity, which could contribute to guiding future efforts aimed at alleviating water scarcity and ensuring water security in China. • Water scarcity assessment incorporated water quality and multiple existing solutions. • China's water scarcity was assessed at a high spatial resolution on a monthly basis. • Over half of the national population faced water scarcity for at least one month of the year. • Agricultural water use and inadequate water quality were the main driving factors. • Over four-fifths of the national population could benefit from alleviated water scarcity by the combined water quantity and quality solutions. [ABSTRACT FROM AUTHOR]

The detachment of biofilm caused by changes in hydraulic conditions is an essential reason for the pollution of water in the drinking water distribution system (DWDS). In this research, the effect of flow fluctuation on bulk water quality was studied. The turbidity, iron concentration, manganese concentration, the total number of bacteria, biodegradable dissolved organic carbon (BDOC), bacterial community structure, and pathogenic genes in bacteria of bulk water were analyzed. The results indicate that the detachment of biofilm caused by fluctuant flow and reverse flow (especially instant reverse flow) can lead to the pollution of water. Throughout the entire experimental period, the turbidity under fluctuant flow velocity is 4.92%∼49.44% higher than that under other flow velocities. BDOC concentration is 5.68%∼53.99% higher than that under low and high flow velocities. The flow fluctuation increases bacterial regrowth potential (BRP) and reduces the biological stability of the bulk water. Low flow velocity is more conducive to the expression of pathogenic functional genes. In the short term, the water quality under low flow velocity is the best. Nevertheless, in a long-term operation (about seven days later), the water quality under high flow velocity is better than that under other flow velocities. This research brings new knowledge about the fluctuant hydraulic conditions on the bulk water quality within the DWDS and provides data support for stable drinking water distribution. [Display omitted] • Fluctuant flow velocities have the greatest impact on water quality deterioration. • The water quality is better under high flow velocity during the long-term operation. • The detachment of biofilm caused by hydraulic change increases the BRP. • Biofilm detachment reduces the biological stability of bulk water. [ABSTRACT FROM AUTHOR]

Dongping Lake is one of the most important regulation and storage lakes along the eastern route of the South-to-North Water Diversion Project in China, the water quality condition of which directly influences the safety of water diverting, because it serves as a Yangtze River water redistribution control point. However, the changes in algae, and in environmental factors affecting their community structures, before and after the water diversion project are rarely reported. In this study, the temporal variations of phytoplankton abundance were examined based on monthly samples collected at three stations from May 2010 to April 2022. The total abundance of algae greatly decreased after the water diversion project was implemented, with a relatively stable biodiversity and evenness before and after the water translocation. Multiple statistical methods were used together with the water quality indices (WQIs) and the nutrient status index (TSI M) to evaluate overall water condition and analyse relationships among environmental factors. The WQIs demonstrated a general "Good" water quality with a seasonal differentiation, and that water conditions during water transfer periods were better than during non-water transfer periods, which may be ascribed to the improved hydraulic conditions and purified water environment during water transfer periods. Redundancy analysis showed that water temperature, ammonia nitrogen, water transparency, and total phosphorus were the most important environmental factors, with relatively decreased contribution rates towards phytoplankton communities after the water translocation. Importantly, some dominant phytoplankton genera of Chlorophyta, Bacillariophyceae, and Cyanophyceae were similarly affected by water transparency, and nitrogen and phosphorus nutrients in summer after the water translocation. These research findings helped us gain a comprehensive understanding of the changing patterns of water quality and microalgae and their relationships before and after the water diversion project, providing a guidance for future lake management in regulating hydraulic conditions and improving water quality of Dongping Lake. [Display omitted] • Phytoplankton abundance in Dongping Lake significantly decreased after SNWDP. • Phytoplankton diversity and evenness remained stable before and after SNWDP. • WQI indicated better water quality during the water transfer period. • Environmental factors contributed less towards phytoplankton communities after SNWDP. • More attention to lake water management is recommended after SNWDP. [ABSTRACT FROM AUTHOR]

Stormwater Control Measures (SCMs) contribute to reducing micropollutant emissions from separate sewer systems. SCM planning and design are often performed by looking at the hydrological performance. Assessment of pollutant removal and the ability to comply with discharge concentration limits is often simplified due to a lack of data and limited monitoring resources. This study analyses the impact of using different time resolutions of input stormwater concentrations when assessing the compliance of SCMs against water quality standards. The behaviour of three indicator micropollutants (MP - Copper, Diuron, Benzo[a]pyrene) was assessed in four SCM archetypes, which were defined to represent typical SCM removal processes. High resolution MP data were extrapolated by using high resolution (2 min) measurements of TSS over a long period (343 events). The compliance assessment showed that high resolution input concentrations can result in a different level of compliance with water quality standards, especially when discharged concentrations are close to the limit values. This study underlines the importance of considering the high temporal variability of stormwater micropollutants when planning and designing SCMs to identify the most effective solutions for stormwater pollution management and to ensure a thorough consideration of all the environmental implications. • Temporal resolution of pollutant input concentrations matters when planning SCMs. • Removal of three indicator micropollutants (MP) in four SCMs assessed. • High resolution MP concentrations were extrapolated by using TSS measurements. • Input resolution is sensitive when discharge levels are close to quality standards. • Input resolution should match the quality standard used for performance assessment. [ABSTRACT FROM AUTHOR]

Thermal stratification often occurs in deep-water bodies, including oceans, lakes, and reservoirs. Dissolved organic matter (DOM) plays a critical role in regulating the dynamics of aquatic food webs and water quality in aquatic ecosystems. In the past, thermal stratification boundaries have been sometimes used exclusively to analyze the vertical distribution of DOM in thermally stratified water bodies. However, the validity of this practice has been challenged. Currently, there is limited understanding of the formation mechanism and stratification of the vertical distribution of DOM in thermally stratified water bodies, which hinders the analysis of the interactions between DOM and vertical aquatic ecological factors. To address this gap, we conducted a comprehensive study to extensively collect the vertical distribution of DOM in thermally stratified water bodies and identify the primary factors influencing this distribution. We found that DOM was independently stratified in thermally stratified water bodies (including two cases in unstratified water bodies), and that the formation mechanisms and statuses of DOM stratification were different from those of thermal stratification. The boundaries and numbers of DOM stratification were generally inconsistent with those of thermal stratification. Therefore, it is more accurate to divide DOM into different layers according to its own vertical profile, and analyze DOM characteristics of each layer based on its own stratification instead of thermal stratification. This study sheds light on the relationship between DOM and thermal stratification and provides a novel approach for analyzing DOM vertical distribution characteristics and their impact on aquatic ecosystems. This finding also holds significant implications for the design and implementation of environmental management programs aimed at preserving the health and functionality of aquatic ecosystems. [Display omitted] • Analyzing DOM vertical distribution based on thermal stratification may be arguable. • DOM was found to be stratified independently in thermally stratified water bodies. • Some conformity existed between DOM and thermal stratification due to interaction. • DOM vertical distribution was primarily influenced by its sources and sinks. • DOM stratification's boundaries/numbers were different from thermal stratification. [ABSTRACT FROM AUTHOR]

Lakes in taiga and tundra regions may be silently undergoing changes due to global warming. One of those changes is browning in lake color. The browning interacts with the carbon cycle, ecosystem dynamics, and water quality in freshwater systems. However, spatiotemporal variabilities of browning in these regions have not been well documented. Using MODIS remote sensing reflectance at near ultraviolet wavelengths from 2002 to 2021 on the Google Earth Engine platform, we quantified long-term browning trends across 7616 lakes (larger than 10 km2) in taiga and tundra biomes. These lakes showed an overall decreased trend in browning (Theil-Sen Slope = 0.00015), with ∼36% of these lakes showing browning trends, and ∼1% of these lakes showing statistically significant (p-value <0.05) browning trends. The browning trends more likely occurred in small lakes in high latitude, low ground ice content regions, where air temperature increased and precipitation decreased. While temperature is projected to increase in response to climate change, our results provide one means to understand how biogeochemical cycles and ecological dynamics respond to climate change. • Lakes in taiga and tundra overall showed a decreased trend in browning from 2002 to 2021. • The browning trend of the study lakes varies significantly among ecoregions, temperature, precipitation, and lake area. • The results support the theory that climate change may cause increased DOC in lakes in pan-Arctic regions. [ABSTRACT FROM AUTHOR]

Ambitious to fulfill the European Water Framework Directive obligations, the European governments support projects to rehabilitate lakes with poor water quality. However, most lake restorations having relied on biomanipulation by fish thinning have failed to improve or even maintain water quality. Previous attempts removed all target fish species simultaneously, thus making it impossible to assess the specific impact of each feeding group on water chemistry. Lake Bromme was selected for extensive, time-selective fish biomanipulation to improve water clarity and promote submerged macrophytes and piscivorous fish stocks over a three-year monitoring period. Thinning of adult benthivorous bream (Abramis brama) and tench (Tinca tinca) was conducted throughout year one while thinning in years two and three targeted planktivorous roach (Rutilus rutilus), juvenile bream, and small perch (Perca fluviatilis). Yearly fish surveys assessed changes in fish population structure and biomass. Water quality parameters were monitored continually, and the cover of submerged macrophytes was surveyed annually via sonar. We found no improvement in water clarity or reductions of nutrients, organic particles, chlorophyll concentrations, or watercolor, despite a 6-fold thinning of total estimated fish biomass, from 112 to 19 kg ha−1. Over the period, the macrophyte cover increased from 0.8 to 13.5 %, but no recruitment of large piscivorous fish (perch and pike (Esox lucius) > 10 cm) was detected. We found higher correlations of particle concentration and water clarity to water temperature than to wind speed, which indicates sediment particle resuspension by the remaining fish community (mostly carp Cyprinus carpio) that forage on benthos in shallow lakes. Further system-ecological research in Lake Bromme should evaluate whether thinning the stock of carp and increasing plant cover may improve water quality and test which optical properties sustain high water turbidity and prevent shallow, eutrophic lakes like Lake Bromme from responding to intense fish thinning. [Display omitted] • Water clarity and nutrients did not improve despite a six-fold fish reduction. • A novel methodology for quantifying levels of suspended particulate organic carbon. • Submerged macrophyte cover increased from thinning of cyprinids. • Sustained particle resuspension from few benthic fish may hinder lake improvement. • Water turbidity may be indifferent to manipulations in fish community structure. [ABSTRACT FROM AUTHOR]

Urban stormwater runoff is a significant source of nutrient pollution that is very costly to treat. Water quality trading (WQT) is a market-based strategy that can be used to lower the costs associated with meeting stormwater quality regulations. While many WQT programs have experienced low participation, Virginia's program has seen high participation due to the inclusion of land developers and other regulated stormwater dischargers. However, the extent to which WQT is used as a compliance option by regulated stormwater dischargers is not well understood, particularly when compared with the adoption of traditional compliance options. To address this knowledge gap, we collated a novel dataset comprising site characteristics and stormwater compliance methods for all development projects in the City of Roanoke, Virginia from December 2015 to March 2022. We analyzed this dataset to characterize the adoption of nutrient offset credits and other compliance methods being used, including best management practices (BMPs) and improved land covers associated with reduced nutrient export. Results show that credits are the preferred compliance option in Roanoke and were used as the only treatment compliance method for 59% of projects with treatment requirements. Projects using credits corresponded with a lower median disturbed area (1.36 acres) and lower median nutrient load reduction requirement (0.69 pounds of total phosphorus per year) compared with other compliance methods. Furthermore, we found that 58% of the projects that used credits achieved stormwater quantity compliance using methods other than implementing stormwater control devices. By mapping buyers and sellers of credits, we found that all credit sellers are downstream of the development projects. We discuss how this downstream trading could be a cause for concern, as part of a larger discussion of the advantages of tracking stormwater compliance methods, drawing on Roanoke as a case study. • We compare the use of water quality trading with alternative stormwater quality compliance options in Roanoke, Virginia, USA. • We find that water quality credits are the preferred stormwater quality compliance method for land development projects. • The majority of the credit offsets are associated with small development impacts. • Twice as much nutrient load is being offset using credits compared with loads treated using onsite best management practices. • Considerations for water quality trading and stormwater management programs are discussed. [ABSTRACT FROM AUTHOR]

In aquatic animals, dietary protein plays a crucial role in their growth and immunity. A feeding trial was conducted on soft-shelled turtles (Pelodiscus sinensis) to assess the effects of various levels of protein on the specific growth rate (SGR), ambient water quality (total ammonia nitrogen (TAN), total nitrogen (TN) and total phosphorus (TP)), hematological parameters (respiratory burst (RB), red blood cell count (RBC), albumin content (Alb), hemoglobin level (Hb) and osmolality), plasma immunoglobulin M (IgM) levels and lysozyme activity. Soft-shelled turtles weighing about 4.02 g were fed fish meal-based diets with 14.38%, 20.41%, 26.19%, 32.23%, 37.63% and 45.23% protein for 8 weeks. SGR, RBC, Hb, Alb, RB, IgM and lysozyme activity were enhanced as the dietary protein was increased from 14.38% to 26.19%, then reached a plateau. For identical feeding times, TAN and TN were increased with elevating dietary protein levels. While, no statistically significant differences were observed among the 26.19%, 32.23% and 37.63% groups. When the turtles were cultivated for 56 days and fed with 45.23% protein, the TP in the culturing water was higher than that in the other groups. An increase in dietary protein level up to 26.19% increased the RNA/DNA ratio, which subsequently plateaued at a steady level. The levels of dietary protein had no impact on osmolality or alkaline phosphatase (AKP) activity. On the basis of broken-line analyses derived from SGR, the optimum dietary protein level for soft-shelled turtles was found to be 27.11% protein. • Optimum dietary protein level for soft-shell turtles was 27.11% protein, based on broken-line analyses derived from SGR. • Optimum protein level improved the specific growth rate. • Optimum protein level enhanced hematological indicators (respiratory burst, red blood cells, albumin, and hemoglobin). • Optimum protein level increased Ig M, lysozyme activity, and the RNA/DNA ratio. • Total ammonia nitrogen and total nitrogen were elevated with increasing dietary protein levels. [ABSTRACT FROM AUTHOR]