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To meet the Sustainable Development Goal (SDG) target 6.1, China has undertaken significant initiatives to address the uneven distribution of water resources and to enhance water quality. Since 2000, China has invested heavily in the water infrastructure of numerous reservoirs, with a total storage capacity increase of 4.704 × 10 11 m 3 (an increase of 90.8%). These reservoirs have significantly enhanced the available freshwater resources for drinking water. Concurrently, efforts to improve water quality in lakes and reservoirs, facilitated by nationwide water quality monitoring, have been successful. As a result, an increasing lakes and reservoirs are designated as centralized drinking water sources (CDWSs) in China. Among the 3441 CDWSs across all provinces, 40.8% are sourced from lakes and reservoirs, 32.6% from rivers, and 26.6% from groundwater in 2023. Notably, from 2016 to 2023, the percentage of lakes and reservoirs categorized as CDWSs has increased consistently across all 29 provinces. This progress has enabled 561.4 million urban residents to access improved drinking water sources in 2022, compared to 303.4 million in 2004. Our findings underscore the pivotal role of water infrastructure construction and water quality improvement jointly promoting lakes and reservoirs as vital drinking water sources. Nevertheless, the nationwide occurrence of algal blooms has surged by 113.7% from the 2000s to the 2010s , which is a considerable challenge to drinking water safety. Fortunately, algal blooms have been markedly alleviated in past four years. However, it is still crucial to acknowledge that lakes and reservoirs face the challenges of algal blooms, and associated toxic microcystin and odor compounds., (Copyright © 2024 Science China Press. Published by Elsevier B.V. All rights reserved.)

The loss of phosphorous (P) from the land to aquatic systems has polluted waters and threatened food production worldwide. Systematic trend analysis of P, a nonrenewable resource, has been challenging, primarily due to sparse and inconsistent historical data. Here, we leveraged intensive hydrometeorological data and the recent renaissance of deep learning approaches to fill data gaps and reconstruct temporal trends. We trained a multitask long short-term memory model for total P (TP) using data from 430 rivers across the contiguous United States (CONUS). Trend analysis of reconstructed daily records (1980-2019) shows widespread decline in concentrations, with declining, increasing, and insignificantly changing trends in 60%, 28%, and 12% of the rivers, respectively. Concentrations in urban rivers have declined the most despite rising urban population in the past decades; concentrations in agricultural rivers however have mostly increased, suggesting not-as-effective controls of nonpoint sources in agriculture lands compared to point sources in cities. TP loss, calculated as fluxes by multiplying concentration and discharge, however exhibited an overall increasing rate of 6.5% per decade at the CONUS scale over the past 40 y, largely due to increasing river discharge. Results highlight the challenge of reducing TP loss that is complicated by changing river discharge in a warming climate., Competing Interests: Competing interests statement:The authors declare no competing interest.

In this study, we compared a wide range of cell-based bioassays to the use of chemical analysis followed by exposure-activity ratio (EAR) and Toxicological Prioritization index (ToxPi) for prioritizing chemicals, sites, and hazard concerns in water samples. Surface water samples were collected from nine sites in three Central Pennsylvania streams and analyzed for a forty-six contaminants of emerging concern (CECs), including pesticides, personal care products, and pharmaceuticals. Cell-based reporter assays evaluated human and zebrafish molecular initiating events (MIEs) in endocrine and metabolic disruption, altered lipid metabolism, and oxidative stress. Bioassays showed that 12 out of 40 assays had at least one site with activity over the effect-based trigger (EBT) values. The receptors that exhibited the highest number of samples above the EBT that would be expected to cause toxicity were Aryl hydrocarbon receptor (AhR, human and zebrafish), Pregnane X Receptor (PXR), Estrogen Receptor-beta (ERB), and Androgen Receptor (AR). Characterizing the collection sites by their bioactivity aligned closely with the stream in which samples were collected. The sum of all EARs for each chemical indicated that the pharmaceutical Carbamazepine and the pesticides Carbaryl and Atrazine posed the greatest concern. However, predicted activity and site prioritization based on individual chemical analysis and calculated EAR were different than those measured by bioassay, indicating that biologically active chemicals are present in the samples that were not included in the targeted analytes. Taken together, these data show that chemical analysis and EAR analysis are beneficial for prioritization of chemicals, whereas mechanism-based bioassays are more inclusive of known as well as unknown chemical contaminants and thus of more use for overall water quality analysis and site prioritization., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: John P. Vanden Heuvel reports financial support was provided by INDIGO Biosciences Inc. J.P. Vanden Heuvel is a Founder and Chief Scientific Officer of INDIGO Biosciences, Inc. For other authors there are no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Extreme precipitation can significantly influence the water quality of surface waters. However, the total amount of bacteria carried by rainfall runoff is poorly understood. Here, thirty rainfall scenarios were simulated by artificial rainfall simulators, with designed rainfall intensity ranging from 19.3 to 250 mm/h. The instantaneous concentration ranges of R2A, nutrient agar (NA) culturable bacteria, and viable bacteria in runoff depended on the types of underlying surfaces. The instantaneous bacterial concentrations in runoff generated by forest lands, grasslands and bare soil were: R2A culturable bacteria = 10 4.5-6.3 , 10 4.5-6.1 , 10 4.0-5.3 colony-forming units (CFU)/mL, NA culturable bacteria = 10 4.0-6.0 , 10 3.9-5.8 , 10 3.2-4.9 CFU/mL, and viable bacteria = 10 6.4-8.0 , 10 7.0-8.9 , 10 6.4-7.6 cells/mL. Based on the measured bacterial instantaneous concentration in runoff, cumulative dynamic models were established, and the maximum amount of culturable bacteria and viable bacteria entering water sources were estimated to be 10 9.38-11.31 CFU/m 2 and 10 11.84-13.25 cells/m 2 , respectively. The model fitting and the bacterial accumulation dynamics were influenced by the rainfall types (p < 0.01). Surface runoff from the underlying surface of forest lands and grasslands had a high microbial risk that persisted even during the "Drought-to-Deluge Transition". Bacterial accumulation models provide valuable insight for predicting microbial risks in catchments during precipitation and can serve as theoretical support for further ensuring the safety of drinking water under the challenge of climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

In the US, private well users are responsible for their own water quality testing, but local health officials are often uncertain what tests to recommend, particularly for regulated organic chemical contaminants. This study evaluated the utility of suspect and non-target screening (NTS) high resolution mass spectrometry (HRMS) as a tool to identify a wide range of organic chemicals of emerging concern in private well water and to inform well water management decisions. Qualitative NTS, which detects chemicals without providing concentrations, was used to analyze 25 private well water samples from Wake County, North Carolina. Using the NIST 20 mass spectral database (M 1 ), NTS tentatively identified 106 unique organic chemicals across the 25 samples and an average of 11 organic chemicals per sample. At least one USEPA ToxCast chemical was identified in each private well water sample. Private well water users were interviewed prior to and after their sample's NTS results were reported back; four county groundwater managers were interviewed after aggregated results for all 25 water samples were reported back. All but one well user participant chose to participate in the reporting-back post-interview. The 24 private well users found NTS results useful and valued the contextualization of their results using NTS results for other well users and a local municipal water sample. Most private well users (67%) were surprised by their well water results, especially regarding the number of tentatively identified organic chemicals detected. All the groundwater managers believed the NTS results were useful and could help improve their testing recommendations to private well users. Even with qualitative limitations, NTS results can be an effective and valuable tool to inform the public and governance stakeholders in decisions around groundwater quality management., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Hayden Rudd reports financial support was provided by NC Water Resources Research Institute. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

In degraded urban habitats, nature-based solutions aim to enhance ecosystem functioning and service provision. Bivalves are increasingly reintroduced to urban environments to enhance water quality through biofiltration, yet their long-term sustainability remains uncertain. Following the restoration of the disused South Docks in Liverpool in the 1980s, natural colonization of mussels rapidly improved dock-basin water quality and supported diverse taxa, including other filter feeders. While the initial colonization phase has been well documented, there has been limited published research since the mid-1990s, despite ongoing routine water quality monitoring. Here, we assessed the long-term persistence of mussel populations, their associated biodiversity, and physico-chemical parameters of the water in Queens and Albert Docks by comparing historical (1980s to 1990s) and contemporary data from follow-up surveys (2012,2022). Following an initial period of poor water quality (high contamination and turbidity, low oxygen), the natural colonization of mussels from Albert Dock in 1988 extended throughout the South Docks. By the mid-1990s, the environment of the South Docks and its mussel populations had stabilized. The dock walls were dominated by mussels which provided important complex secondary substrate for invertebrates and macroalgae. Surveys conducted in 2012 and 2022 confirmed the continued dominance of mussels and estimates of mussel biofiltration rates confirm that mussels are continuing to contribute to maintaining water quality. A decline in salinity was observed in both docks in 2022, with evidence of recovery. While these ecosystems appear relatively stable, careful management of the hydrological regime is crucial to ensuring the persistence of mussels and resilient ecosystem service provision through biofiltration., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Groundwater pollution has attracted widespread attention as a threat to human health and aquatic ecosystems. However, the mechanisms of pollutant enrichment and migration are unclear, and the spatiotemporal distributions of human health risks are poorly understood, indicating insufficient groundwater management and monitoring. This study assessed groundwater quality, human health risks, and pollutant sources in the Fen River Basin(FRB). Groundwater quality in the FRB is good, with approximately 87 % of groundwater samples rated as "excellent" or "good" in both the dry and rainy seasons. Significant precipitation elevates groundwater levels, making it more susceptible to human activities during the rainy season, slightly deteriorating water quality. Some sampling points in the southern of Taiyuan Basin are severely contaminated by mine drainage, with water quality index values up to 533.80, over twice the limit. Human health risks are mainly from As, F, NO 3 - , and Cr. Drinking water is the primary pathway of risk. From 2019 to 2020, the average non-carcinogenic risk of As, F, and NO 3 - increased by approximately 28 %, 170 % and 8.5 %, respectively. The average carcinogenic risk of As and Cr increased by 28 % and 786 %, the overall trend of human health risks is increasing. Source tracing indicates As and F mainly originate from geological factors, while NO 3 - and Cr are significantly influenced by human activities. Various natural factors, such as hydrogeochemical conditions and aquifer environments, and processes like evaporation, cation exchange, and nitrification/denitrification, affect pollutant concentrations. A multi-tracer approach, integrating hydrochemical and isotopic tracers, was employed to identify the groundwater pollution in the FRB, and the response of groundwater environment to pollutant enrichment. This study provides a scientific basis for the effective control of groundwater pollution at the watershed scale, which is very important in the Loess Plateau., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Water temperature and feeding frequency are critical abiotic factors regulating the growth and immune function of aquatic organisms. This study investigated the effects of water temperature and feeding frequency on growth and immune function in Nile tilapia (Oreochromis niloticus) over two months. A total of 360 juvenile fish (average weight: 20.00 ± 1.26 g) were divided into six groups, each with three replicates, based on a combination of three water temperatures (26, 28, and 30 °C) and two feeding frequencies (either 1 or 2 meals per day)., Results: At 30 ºC and 28 ºC, water electrical conductivity and total dissolved salts increased, while total ammonia nitrogen and dissolved oxygen rose slightly in groups fed twice daily, with a significant interaction between temperature and feeding frequency. The group at 30 ºC with two meals per day showed the highest final body weight (FBW). The interaction between temperature and feeding frequency significantly influenced FBW, total feed intake, and body thickness. Fish at 30 ºC exhibited upregulated hepatic growth hormone receptor 1 and insulin-like growth factor 1, while those at 28 ºC with one meal per day, as well as those at 30 ºC regardless of meal frequency, also showed increased expression of hepatic fatty acid binding protein and intestinal cluster of differentiation 36. Fish at 30 ºC had upregulated leptin levels and downregulated cholecystokinin, while those at 26 ºC displayed the opposite trend, particularly with one meal daily. Higher temperatures significantly boosted serum IgM, superoxide dismutase (SOD), and lysozyme (LYZ) levels, with meal frequency also affecting malondialdehyde, IgM, and SOD levels. Additionally, 30 ºC enhanced the hepatic expression of mucin-like protein (muc), oligo-peptide transporter 1 (pept1), interleukin 1, nf-κB, complement C3, lyz, sod, catalase, and glutathione peroxidase, with twice-daily meals having a more pronounced effect. Conversely, 28 ºC with one meal per day upregulated some of these genes, such as muc, pept1, and sod., Conclusions: Overall, 30 ºC with two meals per day significantly improved the growth and health of juvenile Nile tilapia, while 28 ºC with two meals maintained satisfactory performance., Competing Interests: Declarations Ethics approval The study was conducted at the Department of Aquaculture, Faculty of Aquatic and Fisheries Sciences, Kafrelsheikh University, Egypt. It was reviewed and approved by Kafrelsheikh University’s Ethical Committee under approval number KFS-IACUC/176/2024. The study adhered to the regulations and ethical guidelines outlined in ARRIVE (https://arriveguidelines.org/). Consent for publication Not applicable. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Accurate estimation of coastal and in-land water quality parameters is important for managing water resources and meeting the demand of sustainable development goals. The water quality monitoring based on discrete water sample analysis is limited to specific locations and becomes less effective to offer a synoptic view of the water quality variability at different spatial and temporal scales. The optical remote sensing techniques have proved their ability to provide a comprehensive and synoptic view of water quality parameters. In conjugation with other products, the optical remote sensing data products can be utilized for the effective management of water bodies while addressing the socio-economic issues faced by local governments and states. In recent years, multiple machine-learning (ML) models have been reported on the estimation of water quality using remote sensing data, but their performance is limited when extended to diverse water types within coastal and inland water environments. In this study, we present an ensemble machine-learning model for estimating the primary water quality parameters in coastal and inland waters, such as Chlorophyll-a (Chl-a) concentration, colored dissolved organic matter (a CDOM 440), and Turbidity. It utilizes the in-situ measurements to train and optimize the ensemble machine-learning models for the spectral measurements data (400-700 nm) provided by MODIS-Aqua, Sentinel-2 Multi Spectral Instrument (MSI), and PlanetScope (Planet). To develop the prediction models, these in-situ measurements data were split into two parts: a training dataset (70 %) and a testing dataset (30 %). The ensemble machine-learning models were validated using the 5-fold cross-validation method. These models were trained and tested against distinct datasets encompassing a broad range of variations in water quality parameters collected from open ocean, coastal and inland waters. The validation results demonstrated a superior performance of the present ensemble ML models compared to other ML models (Chl-a: R 2  = 0.96, RMSE = 4.93, MAE = 2.89; a CDOM 440: R 2  = 0.93, RMSE = 0.057, MAE = 0.025; Turbidity: R 2  = 0.95, RMSE = 4.52, MAE = 1.009). To realize the importance of this study, the ensemble ML models were applied to MODIS-Aqua monthly composite measurements from 2003 to 2022 and captured pronounced seasonal variations in water quality parameters (WQP) and Water Quality Index (WQI). For instance, in the Gulf of Khambhat, turbidity decreased at an annual average rate of ∼0.08 NTU and Chl-a increased at an annual average rate of ∼0.004 mg m -3 for the past 20 years. Furthermore, we investigated the occurrences of Noctiluca scintillans (here after N. scintillans) bloom between 2019 and 2021 near the fin fish cage culture sites in Mandapam, on the southeast coast of Tamil Nadu, within the Gulf of Mannar, India which serves as a documentation of the Harmful Algal Bloom (HAB) incidents. The performance of ensemble model is further demonstrated using Planet images from inland turbid waters of the Muthupet lagoon (Brackish water) and Adyar river (Urban River) and MSI image from Chilika lagoon. The proposed ensemble ML models proved as an effective method for accurately estimating the WQP and WQI products and capturing their spatial and temporal variations in regional and global waters, which forms an important tool for sustainable development and management of coastal and inland water environments., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Palanisamy Shanmugam reports financial support was provided by Department of Science and Technology, Ministry of Science and Technology, India. Gurunathan Saravana Kumar and Palanisamy Shanmugam reports a relationship with India Ministry of Science & Technology Department of Science and Technology that includes: funding grants. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The 2020 mass mortality of 350 African elephants (Loxodonta africana) in Botswana sparked global concern, with cyanotoxins in watering holes (pans) being a suspected cause, though evidence remains inconclusive. Combining remote sensing and spatial analysis, we examined the relationship between the ecohydrology of ∼3000 pans and the locations of deceased elephants. Our analysis revealed a significant difference in the spatial distribution of fresh versus decayed carcasses (p < 0.001), indicating that the die-off deviated from typical regional elephant mortality patterns. We identified 20 pans near fresh carcasses that experienced increased cyanobacteria bloom events in 2020 (n = 123) compared to the previous 3 years combined (n = 23), exhibiting the highest average phytoplankton biomass of the period 2015-2023 (Normalised Difference Chlorophyll Index >0.2). These findings suggest a heightened risk and likelihood of cyanotoxin presence in these pans. Elephants were estimated to have walked 16.5 km (± 6.2 km) and died within 88 h (± 33 h) of exposure. Our study provides evidence that cyanobacterial toxicity could be a contributing factor to the 2020 die-off, while also considering other potential causes, and offers a general framework for investigation of future mortality events. We underscore the need to integrate spatial analysis and regional ecohydrological assessments to monitor and mitigate animal mortality events and inform conservation strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Road construction significantly affects water resources by introducing contaminants, fragmenting habitats, and degrading water quality. This study examines the use of Remote Sensing (RS) data of Sentinel-1 (S1) and Senitnel-2 (S2) in Google Earth Engine (GEE) to do spatio-temporal analysis of turbidity in adjacent water bodies during the construction and operation of the E18 Arendal-Tvedestrand highway in southeastern Norway from 2017 to 2021. S1 radiometric data helped delineate water extents, while S2-Top of Atmosphere (TOA) multispectral data, corrected using the Modified Atmospheric correction for INland waters (MAIN), used to estimate turbidity levels. To ensure a comprehensive time series of RS data, we utilized S2-TOA data corrected with the MAIN algorithm rather than S2-Bottom Of Atmosphere (BOA) data. We validated the MAIN algorithm's accuracy against GLORIA (Global Observatory of Lake Responses to Interventions and Drivers) observations of surface water reflectance in lakes, globally. Subsequently, the corrected S2 data is used to calculate turbidity using the Novoa and Nechad retrieval algorithms and compared with GLORIA turbidity observations. Findings indicate that the MAIN algorithm adequately estimates water-leaving surface reflectance (Pearson correlation > 0.7 for wavelengths between 490 and 705 nm) and turbidity (Pearson correlation > 0.6 for both algorithms), determining Nechad as the more effective algorithm. In this regard, we used S2 corrected images with MIAN to estimate turbidity in the study area and evaluated with local gauge data and observational reports. Results indicate that the proposed framework effectively captures trends and patterns of turbidity variation in the study area. Findings verify that road construction can increase turbidity in adjacent water bodies and emphasis the employing RS data in cloud platforms like GEE can provide insights for effective long-term water quality management strategies during construction and operation phases., (Copyright © 2024. Published by Elsevier B.V.)

The integration of somatic coliphage analysis into water quality regulations has driven the development of more streamlined, easier, and faster detection methods. These include the Bluephage method, initially designed for the qualitative assessment of coliphages in 100 mL water samples. In the present study this technique was adapted for quantitative analysis using the most probable number method, enabling quantification of somatic coliphages in 100 mL water samples within 6.5 h of incubation. Early readings were optimised using an algorithm developed from an extensive dataset of over 400 environmental samples. This new quantitative method has been refined and commercialised as the Enumera® Rapid kit (BPF-SE, Bluephage S.L.), which includes a new reference somatic coliphage, strain GR8. After sequencing and further characterisation, it was confirmed that the new strain belongs to the same species as the reference somatic coliphage of the ISO 10705-2 method. The Enumera® Rapid kit was then validated by assessing its efficacy across 151 samples from various water matrices. The method provided a mean recovery rate of 103 %, ranging from 95 % for drinking water to 116 % for wastewater, at concentrations from 0 to 300 PFU/100 mL. In comparison, ISO 10705-2 applied after membrane filtration yielded a mean recovery rate of 63.8 %, with the highest rate observed for wastewater (88.9 %). The results obtained with the Enumera® Rapid kit did not differ significantly compared to the reference method after adjusting for potential losses during the concentration stage outlined in ISO 10705-3. The new method also demonstrated a robust accuracy of 0.16 logs, good linearity, and achieved a limit of detection and quantification of 1 MPN/100 mL. The Enumera® Rapid kit enables rapid and straightforward quantification of somatic coliphages in 100 mL water samples within a single working day. Its streamlined workflow serves as a useful tool for microbial water quality monitoring., (Copyright © 2024. Published by Elsevier B.V.)

The interconnected systems of lakes of Bengaluru, India, experience tremendous stress due to unsustainable urbanisation. Traditional lake-centric research approach struggles to capture and address this issue due to the cascaded nature of impacts in interconnected lake systems. Hence, this study assesses the impact of urbanisation on a lake series scale, focusing on the Yele Mallappa Shetty Lake series (YMSLS). Land use land cover change analysis (1993-2023) showed that in 1993, the YMSLS catchment area was dominated by open spaces (53.4%) and agriculture land and vegetation (35%), with built-up areas covering only 7.2%. By 2023, the built-up area has expanded to 34.6% and became the dominant land use. This rapid urbanisation has led to increased water surface area from wastewater influx, causing significant weed growth and water pollution in the lakes. Lake water quality assessment showed that faecal coliform, total coliform, dissolved oxygen, and biochemical oxygen demand levels exceeded standard limits with spatio-temporal variations driven by interconnectivity. Pollutant flushing during monsoon reduced pollution load in upstream lakes, but high wastewater inflow made downstream lakes, particularly the end lake, highly polluted but perennial. Increased water availability expanded the user base of the end lake, but traditional uses have declined and coping strategies of users, such as wastewater lift irrigation from the lake, became unsustainable. The study indicates that spatial interdependence and cascading effects necessitate a lake series approach for assessing the impacts of urbanisation on interconnected lake system, which is crucial for enhancing water security and preparedness for future extreme events., Competing Interests: Declarations Ethical Approval and Consent to Participate Not applicable. Consent for Publication Not applicable Competing Interests The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Triclosan, a widely used antimicrobial agent, is frequently detected in aquatic environments, prompting concerns about its toxic effects on aquatic species. Understanding its occurrence and ecological risks is crucial for mitigating triclosan contamination, formulating water quality criteria, and protecting aquatic organisms. This study systematically analyzed triclosan occurrence and ecological risks in surface water across China using the Risk Quotient methodology. A total of 139 and 134 data points were collected for triclosan concentrations and toxicities of aquatic organisms, respectively. Triclosan concentrations in surface water across China ranged from 0.06 to 612 ng/L. Higher triclosan levels were observed in Eastern China compared to Central and Western China, with the average concentration being 4.21- and 7.25-fold higher, respectively. Specifically, the Southeast Rivers Basin (132.98 ng/L) and Pearl River Basin (86.64 ng/L) exhibited maximum triclosan levels, 2.57-19.58 times higher than the other river basins. Further analysis revealed elevated triclosan concentrations in small rivers and surface water within residential areas, with values of 246.1 ng/L in Zhejiang, 86.64 ng/L in Guangdong, 67.58 ng/L in Jiangsu, and 127.99 ng/L in Beijing. Additionally, species sensitivity distribution curves indicated that algae was the most sensitive species to triclosan exposure, followed by invertebrates, while fish exhibited the highest tolerance. The Predicted No-Effect Concentration for the algae, invertebrates, fish, and combined aquatic species were determined to be 0.09, 2.95, 4.44, and 1.51 μg/L, respectively. The occurrence of triclosan in surface water across China did not pose widespread ecological risks. However, targeted monitoring and mitigation efforts are needed, especially in highly developed regions. This study provides crucial insights into the status of triclosan contaminations and risks in China and contributes valuable knowledge to global efforts aimed at safeguarding aquatic ecosystems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Despite widespread deployment and investigation of ultrafiltration (UF) for secondary effluent purification, the challenge of membrane fouling due to effluent organic matter (EfOM) remains formidable. This study introduced a novel pretreatment method utilizing Co nanoparticles-encapsulated carbon nanotubes activated peroxymonosulfate (Co@CNT/PMS) to degrade EfOM and mitigate membrane fouling. Characterization of Co@CNT revealed the efficient encapsulation of Co nanoparticles within nanotubes, which notably enhanced the catalytic degradation of bisphenol A and typical organics. The tube-encapsulated structure increased the concentration of reactive species within the confined nanoscopic space, thereby improving the probability of collisions with pollutants and promoting their degradation. The Co@CNT/PMS pretreatment led to substantial reductions in aromatic compounds, fluorescent components, and both high and middle molecular weight substances. These changes proved crucial in diminishing the fouling potential in subsequent UF processes, where reversible and irreversible fouling resistances decreased by 97.1 % and 72.8 %, respectively. The transition volume from pore blocking to cake filtration markedly increased, prolonging the formation of a dense fouling layer. Surface properties analysis indicated a significant reduction of pollutants on membrane surfaces after the Co@CNT/PMS pretreatment. This study underscored the efficacy of confinement-based advanced oxidization pretreatment in enhancing UF performance, presenting a viable resolution to membrane fouling., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Ultraviolet light-emitting diodes (UV-LEDs) have demonstrated the ability to inactivate microorganisms in water, offering an environmentally safer alternative to the conventional mercury lamp, in UV applications. While several studies have explored the microbiological effect of UVC-LEDs (200nm-280nm), limited information exists regarding their effects on waters with critical qualities. These critical qualities encompass bacteria, viruses, and protozoa - drinking water quality indicators defined by the World Health Organization for small water systems. For the first time, this work reports on the Escherichia coli, PhiX-174, MS2, and Cryptosporidium oocysts inactivation using a bench-scale UVC-LED (280 nm) water disinfection system. UV doses at a wavelength of 280 nm (UV 280 ) of up to 143.4 mJ/cm 2 were delivered under two quality-critical water conditions: filtered water (UV transmittance at 280 nm - UVT 280 90.2 %) and WHO challenge water (UVT 15.7 %). Results revealed microbiological reductions dependent on exposure time and UVT. For UV 280 dose of 16.1 mJ/cm 2 , 2.93-3.70 log E. coli reductions were observed in UVT 90.2 % and 15.7 %, 3.49-4.21 log for PhiX-174, 0.63-0.78 log for MS2, and 0.02-0.04 log for Cryptosporidium oocysts. Significantly higher UV 280 doses of 143.4 mJ/cm 2 led to reductions of 3.94-5.35 log for MS2 and 0.42-0.46 log for Cryptosporidium oocysts. Statistical analysis revealed that the sensitivity among the organisms to UV 280 exposure was E. coli = PhiX-174 > MS2 >> Cryptosporidium oocysts. Although experiments with WHO challenge water posed greater challenges for achieving 1 log reduction compared to filtered water, this difference only proved statistically significant for PhiX-174 and MS2 reductions. Overall, UVC-LED technology demonstrated notable efficacy in microbiological inactivation, achieving significant reductions based on WHO scheme of evaluation for POU technologies in both bacteria and viruses even in critical-quality waters. The findings emphasize the potential for extending the application of UVC-LED as a viable solution for household water treatment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

To reduce the harm of water contamination incidents in drinking water source areas (DWSAs) and explore feasible approaches, the research developed a hydrodynamic water quality model for DWSAs based on two dimensional water quality and quantity equations, Geographic Information System (GIS), and Digital Elevation Model (DEM). The Heshangshan Drinking Water Source Area (HDWSA) in the Three Gorges Reservoir Area (TGRA) was selected as the research area, with total phosphorus (TP) as the representative pollutant in the water. The research investigated the changes in TP content during various hydrological phase under pollution incident, compared the duration and trends of TP concentration exceeding standard value before and after joint reservoir group dispatch. The results showed that the migration speed of TP pollutants varied from slowest to fastest in the following order: dry phase, recession phase, storage phase, and flood phase. Under pollution incident condition, the time demanded for TP content to meet standard value in each water phase was 36 min (dry phase), 33 min (recession phase), 30 min (storage phase), and 27 min (flood phase). The joint dispatch group 1-3 shortened the time required to meet standard value by 6-13 min (dry phase), 5-11 min (recession phase), 4-9 min (storage phase), and 3-7 min (flood phase). The trend of TP concentration before and after joint dispatch showed four stages: significant increase, sharp decrease, rapid decrease, and slow decrease. Joint dispatch of reservoir group can effectively reduced the TP concentration in DWSA under pollution incident., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Grass-type architectural waterscapes (GAWs) utilize submerged plants to enhance self-purification ability and maintain a clear-water state. However, knowledge about their long-term water quality and microbial community dynamics remains limited. This study monitored the water quality, microbial community composition, and networks in two GAWs. GAW1 consisted solely Hydrilla verticillata with a water depth of 0.70 m, while GAW2 primarily contained Vallisneria natans, Microsorum pteropus, and Aquarius grisebachii with a water depth of 0.30 m. Results show that both water depth and submerged plant species play crucial roles in GAW establishment. The water depth of 0.7 m enabled Hydrilla verticillata to thrive underwater despite temperature variations, which demonstrated excellent nutrient uptake capacity. Thus, GAW1 exhibited superior self-purification ability, consistently meeting Class III standard for surface water in China. In contrast, GAW2 had a shallow water depth and contained ornamental plants, only meeting Class V standard. Furthermore, microbial communities were shaped by water quality, with distinct enriched genera serving as potential "microbial indicators". Enrichment of the hgcI clade and Sporichthyaceae&#95;unclassified indicated superior water quality in GAW1, while prevalence of Comamonadaceae&#95;unclassified, Flavobacterium, Rhodoluna, and Pseudarcicella suggested poor water quality in GAW2. Additionally, highly complex and connected microbial networks suggested elevated pollutant levels in GAWs. This study emphasized the significance of submerged plant species and water depth in GAWs construction and highlighted microbial communities and networks as potential indicators of water quality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Rivers are well-known sources of the greenhouse gasses (GHG) carbon dioxide (CO 2 ), methane (CH 4 ) and nitrous oxide (N 2 O). These emissions from rivers can increase because of anthropogenic activities, such as agricultural fertilizer input or the discharge of treated wastewater, as these often contain elevated nutrient concentrations. Yet, the specific effects of wastewater effluent discharge on river GHG emissions remain poorly understood. Here, we studied two lowland rivers which both receive municipal wastewater effluent: river Linge and river Kromme Rijn. Dissolved concentrations and fluxes of CH 4 , N 2 O and CO 2 were measured upstream, downstream and at discharge locations, alongside water column properties and sediment composition. Microbial communities in the sediment and water column were analysed using 16S rRNA gene sequencing. In general, observed GHG emissions from Linge and Kromme Rijn were comparable to eutrophic rivers in urban and agricultural environments. CO 2 emissions peaked at most discharge locations, likely resulting from dissolved CO 2 present in the effluent. CH 4 emission was highest 2 km downstream, suggesting biological production by methanogenic activity stimulated by the effluents' carbon and nutrient supply. Dissolved N 2 O concentrations were strongly related to NO 3 - content of the water column which points towards incomplete riverine denitrification. Notably, methanogenic archaea were more abundant downstream of effluent discharge locations. However, overall microbial community composition remained relatively unaffected in both rivers. In conclusion, we demonstrate a clear link between wastewater effluent discharge and enhanced downstream GHG emission of two rivers. Mitigating the impact of wastewater effluent on receiving rivers will be crucial to reduce riverine GHG contributions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Environmental offsetting has been developed as a mechanism to facilitate the benefits from economic development while avoiding or minimizing environmental harm. This is achieved by compensating for environmental impacts at one location by generating equivalent environmental improvements elsewhere. However, experience with biodiversity and carbon offsetting indicates it can be difficult to ensure the integrity of offsets. Under recent legislation in the catchments of the Great Barrier Reef (GBR), Australia, it is mandatory for water quality emissions from new or expanded point source development to be offset by reducing pollution elsewhere, frequently through reducing non-point source pollution (NPSP). Therefore, informed by experience with biodiversity and carbon offsetting, we summarised sources of uncertainty in NPSP reduction that would influence water quality offset integrity; estimated the maximum potential demand for water quality offsets from sewage treatment plants, the largest point source emitter of total nitrogen (TN) in the GBR catchments, between 2018 and 2050; and discussed the implications of both on the ability of offsetting to counterbalance the impact of economic development in catchments where nitrogen loads have a large influence on the health of important GBR ecosystems. The catchments surrounding the population centres of Cairns and Mackay had both a potentially high future demand for nitrogen water quality offsets and nitrogen loads with a strong influence on the health of the GBR. Consequently, any low integrity water quality offsets in these catchments could jeopardise progress toward the water quality improvements needed to ensure the continued health of the GBR. Water quality offsetting has numerous strengths as a policy instrument however substantial uncertainties remain related to environmental outcomes. Until further research can reduce these uncertainties, water quality offsets that are implemented near increased point source emissions and have a high certainty of effectiveness may provide a balance between scientific rigour and policy workability., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The potential for machine learning to answer questions of environmental science, monitoring, and regulatory enforcement is evident, but there is cause for concern regarding potential embedded bias: algorithms can codify discrimination and exacerbate systematic gaps. This paper, organized into two halves, underscores the importance of vetting algorithms for bias when used for questions of environmental science and justice. In the first half, we present a case study of using machine learning for environmental justice-motivated research: prediction of drinking water quality. While performance varied across models and contaminants, some performed well. Multiple models had overall accuracy rates at or above 90 % and F2 scores above 0.60 on their respective test sets. In the second half, we dissect this algorithmic approach to examine how modeling decisions affect modeling outcomes - and not only how these decisions change whether the model is correct or incorrect, but for whom. We find that multiple decision points in the modeling process can lead to different predictive outcomes. More importantly, we find that these choices can result in significant differences in demographic characteristics of false negatives. We conclude by proposing a set of practices for researchers and policy makers to follow (and improve upon) when applying machine learning to questions of environmental science, management, and justice., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Urban wastewater treatment plants (WWTPs) and drinking water treatment plants (DWTPs) play vital roles in the urban water cycle, ensuring access to safe drinking water and maintaining aquatic ecosystems. This study comprehensively assessed the occurrence and risks of pharmaceuticals and personal care products (PPCPs) in urban WWTPs and DWTPs. Our findings revealed widespread PPCPs presence, with concentrations ranging from <1 ng/L to several thousand ng/L. Significant regional disparities in occurrence and composition were observed linked to population types and economic structures. Furthermore, strong correlations were observed between DWTPs and WWTPs indicating consistent transport and transformation patterns of PPCPs within the urban water cycle. Approximately two-thirds of PPCPs were degraded post-WWTP treatment, with about one-tenth persisting in drinking water following surface water dilution and purification processes. Thus, we suggested that controlling the total concentration of the five priority PPCPs in the effluent from the WWTP to <1100 ng/L have potential to reduce the environmental and health risk of PPCPs. Additionally, this research identified influential water quality parameters, such as pH, dissolved oxygen, and temperature, through redundancy analysis. This research underscores the importance of establishing emission standards to mitigate PPCP-related risks and supports sustainable urban water system advancement., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The environmental changes from climatic, terrestrial and anthropogenic drivers can significantly influence the groundwater quality that may pose a threat to human health. However, the driving mechanism of groundwater quality and potential health risk still remains to be studied. In this paper, 165 groundwater samples were analyzed to evaluate the groundwater quality, driving mechanism, and probabilistic health risk in the central Yinchuan Plain by applying fuzzy comprehensive evaluation method (FCEM), redundance analysis (RDA) and Monte Carlo simulation. The results showed that hydrochemical evolution of groundwater were strongly influenced by water-rock interaction, evaporation and human activities. While 55.2% of groundwater samples reached the drinking water quality standard (Class I, II and III), 44.8% of samples exceeded the standard limits of Class III water quality (Class IV and V), indicating a high pollution level of groundwater. Mn, TDS, NH 4 + , NO 3 - , Fe, F - , NO 2 - , As were among major indicators that influence the groundwater quality due to the natural and anthropogenic processes. The RDA analysis revealed that climatic factors (PE: 10.9%, PRE: 1.1%), GE chemical properties (ORP: 20.7%, DO: 2.4%), hydrogeological factors (BD: 16.5%, K: 4.1%), and terrestrial factors (elevation: 1.2%; distance d : 5.6%, distance rl : 1.5%, NDVI: 1.2%) were identified as major driving factors influencing the groundwater quality in the study area. The HHRA suggested that TCR values of arsenic in infants, children and teens greatly exceeded the acceptable risk threshold of 1E-4, indicating a high cancer risk with a basic trend: infants > children > teens, while TCR values of adults were within the acceptable risk level. THI values of four age groups in the RME scenario were nearly ten times higher than those in the CTE scenario, displaying a great health effect on all age groups (HQ > 1). The present study provides novel insights into the driving mechanism of groundwater quality and potential health hazard in arid and semi-arid regions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Storm events result in nutrient fluctuations and deterioration of reservoir water supply quality. Understanding of nutrient dynamics (e.g., concentration, composition, loads and transport pathways) and adoption of effective management strategies are critical for safeguarding water quality. A comprehensive monitoring was conducted for three storm events during the rainy season in 2023. Results showed nitrogen (N) and phosphorus (P) dynamics demonstrate a significant response to hydrological process. Rainfall resulted in the highest event mean concentrations (EMCs) of total nitrogen (TN), nitrate nitrogen (NO 3 - -N), ammonia nitrogen (NH 4 + -N), total phosphorus (TP), and particulate phosphorus (PP) in the runoff being 1.97, 2.15, 2.30, 44.17, and 62.38 times higher than those observed in baseflow. On average, NO 3 -N were primarily delivered by subsurface runoff. Additionally, nutrient concentrations were significantly higher in the intrusive layer in reservoir compared to the pre-storm period, which gradually decreased from the tail to the head as particulate sedimentation and water column mixing occurred. Water-lifting-aerators (WLAs) were employed to alter the reservoir thermal stratification regime via artificial mixing to affect the intrusive layer of storm runoff. Comparison of the intrusive layer for three storms reveals that WLAs triggers the storm runoff to form an underflow via increasing the reservoir bottom water temperature above that the runoff, ensuring that water quality at the intake position remains unaffected by inflows. These findings serve as a reference for the response of reservoir eutrophication levels to storm events and present practical engineering experience for enhancing water quality safety during the rainy season.- -N/PP accounted for 82 %/96 % of N/P exports. Hysteresis analyses reveal that NH 4 + -N and PP were mainly transported by surface runoff from over-land sources, whereas TN and NO 3 - -N were primarily delivered by subsurface runoff. Additionally, nutrient concentrations were significantly higher in the intrusive layer in reservoir compared to the pre-storm period, which gradually decreased from the tail to the head as particulate sedimentation and water column mixing occurred. Water-lifting-aerators (WLAs) were employed to alter the reservoir thermal stratification regime via artificial mixing to affect the intrusive layer of storm runoff. Comparison of the intrusive layer for three storms reveals that WLAs triggers the storm runoff to form an underflow via increasing the reservoir bottom water temperature above that the runoff, ensuring that water quality at the intake position remains unaffected by inflows. These findings serve as a reference for the response of reservoir eutrophication levels to storm events and present practical engineering experience for enhancing water quality safety during the rainy season., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Climate change is expected to significantly deteriorate water quality in heavily managed agricultural landscapes, however, the exact mechanisms of these impacts are unknown. In this study we adopted a modelling approach to predict the multiple effects of climate change on hydrological and biogeochemical responses for dominant solutes and particulates in two agriculture-dominated temperate headwater catchments. We used climatic projections from three climatic models to simulate future flows, mobilisation and delivery of solutes and particulates. This allowed an examination of potential drivers by identifying changes in flow pathway distribution and key environmental variables. We found that future climate conditions will lead to a general increase in stream discharge as well as higher concentrations and loads of solutes and particulates. However, unlike previous studies, we observed a higher magnitude of change during the warmer part of the year. These changes will reduce the relative importance of winter flows on solute and particulate transport, leading to both higher and more evenly distributed concentrations and loads between seasons. We linked these changes to the higher importance of superficial flow pathways of tile and surface runoff driven by more rapid transition from extremely wet to dry conditions. Overall, the observed increase in solute and particulate mobilisation and delivery will lead to widespread water quality deterioration. Mitigation of this deterioration would require adequate management efforts to address the direct and indirect negative effects on stream biota and water scarcity., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Stream water quality can be impacted by a myriad of fecal pollution sources and waste management practices. Identifying origins of fecal contamination can be challenging, especially in high order streams where water samples are influenced by pollution from large drainage areas. Strategic monitoring of tributaries can be an effective strategy to identify conditions that influence local water quality. Water quality is assessed using fecal indicator bacteria (FIB); however, FIB cannot differentiate sources of fecal contamination nor indicate the presence of disease-causing viruses. Under different land use scenarios, three small stream catchments were investigated under 'wet' and 'dry' conditions (Scenario 1: heavy residential; Scenario 2: rural residential; and Scenario 3: undeveloped/agricultural). To identify fecal pollution trends, host-associated genetic targets HF183/BacR287 (human), Rum2Bac (ruminant), GFD (avian), and DG3 (canine) were analyzed along with FIB (Escherichia coli and enterococci), viral indicators (somatic and F+ coliphage), six general water quality parameters, and local rainfall. Levels of E. coli exceeded single sample maximum limits (235 CFU/100 mL) in 70.7 % of samples, enterococci (70 CFU/100 mL) in 100 % of samples, and somatic coliphage exceeded advisory thresholds (600 PFU/L) in 34.1 % of samples. The detection frequency for the human-associated genetic marker was highest in Scenario 3 (50 % of samples) followed by Scenario 2 (46 %), while the ruminant-associated marker was most prevalent in Scenario 1 (64 %). Due to the high proportion of qPCR-based measurements below the limit of quantification, a Bayesian data analysis approach was applied to investigate links between host-associated genetic marker occurrence with that of rainfall and fecal indicator levels. Multiple trends associated with small stream monitoring were revealed, emphasizing the role of rainfall, the utility of fecal source information to improve water quality management. And furthermore, water quality monitoring with bacterial or viral methodologies can alter the interpretation of fecal pollution sources in impaired waters., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier B.V.)

Due to decades of persistent anthropogenic pressures, lowland rivers represent one of the most severely impaired habitats in Europe. Despite improved water quality, novel stressors, particularly climate change, are emerging with most lowland rivers suffering from past hydromorphological degradation. We aim to elucidate how such degradation alters the biological response in multiple-stressor environments, as this has rarely been considered in studies documenting long-term development of anthropogenically impacted rivers. Here, benthic macroinvertebrates, water quality and hydroclimatic variables were monitored over a period of two decades in nine of the largest Czech rivers. Detailed data on hydromorphological degradation allowed us to track distinct patterns in rivers with high and low levels of degradation. Temporal changes in environmental variables showed similar patterns in both site groups, characterised by reduced organic and nutrient pollution but increased hydroclimatic and salinity stress. 150 % increase in total abundance, especially in abundance and richness of sediment-dwelling and non-native taxa was found in both site groups. While the increase in abundance was due to improved water quality and rising water temperature, the longer duration of minimal flows had a negative effect on species richness, hampering species gain particularly at highly degraded sites. Our results provide novel evidence that degree of hydromorphological degradation modifies long-term macroinvertebrate responses to anthropogenic pressures. Less degraded sites displayed several favourable changes, such as 27 % increase in total and 23 % increase in potamal indicator richness, and stabilisation of the assemblages with few functional changes. In contrast, highly degraded sites experienced 9 % reduction in evenness, 235 % increase in proportion of non-native taxa and functional reorganisation, changes congruent with continuous deterioration. While overall water quality at studied sites has improved, consequences of climate change and high degree of hydromorphological degradation limit biotic recovery in multiple-stressor lowland rivers., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Selma de Donnová, Jindřiška Bojková, Světlana Zahrádková reports financial support was provided by Czech Science Foundation. Libuše Barešová reports financial support was provided by Technology Agency of the Czech Republic. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Understanding and quantifying the influences and contributions of air pollution emissions on water quality variations is critically important for surface water quality protection and management. To address this, we created a five-year daily data matrix of six water quality indicators-permanganate index (COD Mn ), NH 3 -N, pH, turbidity, conductivity, and dissolved organic matter (DOM)-and six air pollution indicators-O 3 , CO, NO 2 , SO 2 , 2.5 μm particulate matter (PM 2.5 ), and inhalable particles (PM 10 )-using data from seven national monitoring stations along the world's longest water-diversion project, the Middle Route of the South-to-North Water Diversion Project in China (MR-SNWD). Multivariate techniques (Mann-Kendall, Spearman's correlation, lag correlation, and Generalized Additive Models [GAMs]) were applied to examine the nonlinear relationships and lag effects of air pollution on water quality. Air pollution and water quality exhibited marked spatial heterogeneity along the MR-SNWD, with all water quality parameters meeting Class I or II national standards and the air pollution indicators exceeding those thresholds. Except for COD Mn and DOM, the other water quality and air pollution indicators exhibited significant seasonal differences. Air pollution exhibited significant lag effects on water quality at the northern stations, with NO 2 , SO 2 , PM 2.5 , and PM 10 being highly correlated with changes in pH, with an average lag of 17 d. Based on the GAMs, lag effects enhanced the significant nonlinear relationships between air pollution and water quality, increasing the average deviance explained for COD Mn , NH 3 -N, and pH by 93%, 24%, and 41%, respectively. These findings provide a scientific basis for protecting water quality along the long-distance inter-basin water-diversion project under anthropogenic air pollution., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

This study addresses the urgent need to understand the impacts of climate change on coastal ecosystems by demonstrating how to use the SWAT+ model to assess the effects of sea level rise (SLR) on agricultural nitrate export in a coastal watershed. Our framework for incorporating SLR in the SWAT+ model includes: (1) reclassifying current land uses to water for areas with elevations below 0.3 m based on SLR projections for mid-century; (2) creating new SLR-influenced land uses, SLR-influenced crop database, and hydrological response units for areas with elevations below 2.4 m; and (3) adjusting SWAT+ parameters for the SLR-influenced areas to simulate the effects of saltwater intrusion on processes such as plant yield and denitrification. We demonstrate this approach in the Tar-Pamlico River basin, a coastal watershed in eastern North Carolina, USA. We calibrated the model for monthly nitrate load at Washington, NC, achieving a Nash-Sutcliffe Efficiency (NSE) of 0.61. Our findings show that SLR substantially alters nitrate delivery to the estuary, with increased nitrate loads observed in all seasons. Higher load increases were noted in winter and spring due to elevated flows, while higher percentage increases occurred in summer and fall, attributed to reduced plant uptake and disrupted nitrogen cycle transformations. Overall, we observed an increase in mean annual nitrate loads from 155,000 kg NO 3 -N under baseline conditions to 157,000 kg NO 3 -N under SLR scenarios, confirmed by a statistically significant paired t-test (p = 2.16 × 10 -10 ). This pioneering framework sets the stage for more sophisticated and accurate modeling of SLR impacts in diverse hydrological scenarios, offering a vital tool for hydrological modelers., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Benthivorous fish disturbance and density-dependent competition from adjacent macrophytes are two important biotic factors that significantly impact the growth of submerged macrophyte pioneer species, which is crucial for the success of eutrophication lake restoration. We conducted an outdoor mesocosm experiment to explore the individual and combined effects of these two factors on water quality and the growth of Vallisneria natans. The experiment involved two levels of fish (Misgurnus anguillicaudatus) disturbance crossed with two levels of Hydrilla verticillata vegetative propagule (shoot) intensity. The results showed that fish disturbance significantly increased the water column total nitrogen (TN), ammonia nitrogen (N-NH 4 ), total phosphorus (TP), and phosphate‑phosphorus (P-PO 4 ). V. natans exhibited restricted plant height elongation and decreased soluble carbohydrate (SC) and starch concentration in fish treatments. Fish disturbance inhibited the growth advantage of V. natans by increasing the extinction coefficient of the water column. There was no statistical significance in total biomass between the two macrophytes in increased vegetative propagule and fish treatments. H. verticillata exhibited a higher relative growth rate (RGR) and summed dominance ratio (SDR 3 ) than V. natans in four treatments and the treatment with three shoots of H. verticillata and one M anguillicaudatus, respectively. Fish disturbance and vegetative propagules showed cumulative effects that negatively affected the RGR&#95;V.H (V. natans relative to H. verticillata). Our findings indicated that benthivorous fish disturbance and vegetative propagules could individually and cumulatively reduce the growth advantage of the pioneer species, V. natans. Our study sheds light on the accumulated effects of multiple disturbances that simultaneously occur in lakes, which holds theoretical and practical importance for lake restoration efforts., Competing Interests: Declaration of competing interest The authors declare that there are no conflicts of interest., (Copyright © 2024. Published by Elsevier B.V.)

Chlorine is a common disinfectant used in water treatment. However, its reaction with organic matter can lead to the formation of harmful byproducts, such as trihalomethanes (THMs), which are potentially carcinogenic. To address this issue, the aim of this work was to enhance a colorimetric method capable of quantifying THMs in drinking water through UV/Vis Spectrophotometry, using cost-effective equipment, and validate this methodology for the first time according to established validation protocols. The method's innovation involved replacing the solvent pentane with the more common hexane, along with adjusting the heating ramp, elucidating the mechanisms involved in the process. This method involves the reaction between THMs, pyridine, and NaOH to produce a colored compound, which is then monitored through molecular absorption spectroscopy in the visible region. The method was thoroughly validated, achieving a limit of detection of 13.41 μg L -1 and a limit of quantification of 40.65 μg L -1 . Recovery assays ranged from 86.1 % to 90.7 %, demonstrating high accuracy. The quality of the linear fit for the analytical curve exceeded R 2  > 0.98. The method was applied to real samples, revealing concentrations ranging from 13.58 to 55.46 μg L -1 , all way below the legal limit in Brazil (Maximum Contaminant Levels (MCL) = 100 μg L -1 ). This cost-effective and straightforward method is suitable for integration into water treatment plant laboratories., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The ecological recharge of urban landscapes with reclaimed water plays a crucial role in alleviating urban water shortage. In Yinchuan, we examined the effects of recharging urban rivers with either Yellow River or reclaimed water on the abundance and diversity of microbial communities. This study aimed to support the effective utilization of reclaimed water. We monitored six sites: three in the reclaimed water recharge area (Lucaowa inlet (ZLJ), Lucaowa channel (ZLH), and Lucaowa outlet (ZLC)) and three in the Yellow River water recharge area (Ningcheng lock (FNCZ), Qingfengjie (FQFJ), and Laifosi (FLFS)). Various indicators (pH, turbidity, temperature (T), dissolved oxygen (DO), electrical conductivity (EC), chemical oxygen demand (COD), total phosphorus (TP), total nitrogen (TN), ammonia nitrogen (NH 3 -N), and nitrate nitrogen (NO 3 -N)) were used to assess the water quality. The microbial community abundance and diversity were evaluated using 16S rRNA high-throughput sequencing. The results indicated that throughout the monitoring period, the reclaimed water recharge area exhibited increased water transparency and greater microbial community abundance and diversity than the Yellow River water recharge area. However, the reclaimed water recharge area also showed significantly higher levels of nitrogen, phosphorus, organic matter, and electrical conductivity, along with an increase in Firmicutes. Seasonal changes significantly influenced water quality factors, significantly affecting Cyanobacteria and Campylobacter populations, as demonstrated by RDA analysis, which showed a close relationship between microbial communities and environmental factors. Further comparative analysis revealed that erythrocytic bacteria were predominant in the reclaimed water recharge area, whereas Actinobacteria, Planktonia, and Aspergillus spp. were more significant in the Yellow River water recharge area. Predictive analysis of microbial functions suggested that carbon and nitrogen cycle-related functions were more abundant in the reclaimed water recharge area, indicating that reclaimed water recharge could improve the self-purification capacity of the water body., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Mineral water is a natural water that originated from an underground water table, a well, or a natural spring which is considered microbiologically intact. The revenue from the bottled mineral water industry will be USD 342.40 billion in 2023, and it is expected to grow at a compound annual growth rate (CAGR) of 5.24 %. Consequently, the discrimination of original bottled mineral water from tap water is an important issue that requires designing sensors for simple and portable identification of these two types of water. In this work, we have developed a Dip-Type colorimetric paper-based sensor array with three organic dyes (Bromothymol Blue, Bromophenol Blue, and Methyl Red) followed by chemometrics' pattern recognition methods (PCA and LDA) for discrimination of original bottled mineral waters from tap waters based on differences in ion variety and ion quantity. Forty brands of mineral water and twenty-six Tap water samples from different regions of Shiraz and other Iranian cities were analyzed by this sensor array. Moreover, these experiments were performed in two consecutive years to check the versatility of the sensor with seasonal changes in waters. This sensor array was able to discriminate these two water types from each other with an accuracy of > 95 % based on the analysis of 85 water samples., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Efficient management of wastewater treatment plants (WWTPs) necessitates accurate forecasting of influent water quality parameters (WQPs) and flow rate (Q) to reduce energy consumption and mitigate carbon emissions. The time series of WQPs and Q are highly non-linear and influenced by various factors such as temperature (T) and precipitation (Precip). Conventional models often struggle to account for long-term temporal patterns and overlook the complex interactions of parameters within the data, leading to inaccuracies in detecting WQPs and Q. This work introduced the Pre-training enhanced Spatio-Temporal Graph Neural Network (PT-STGNN), a novel methodology for accurately forecasting of influent COD, ammonia nitrogen (NH 3 -N), total phosphorus (TP), total nitrogen (TN), pH and Q in WWTPs. PT-STGNN utilizes influent data of the WWTP, air quality data and meteorological data from the service area as inputs to enhance prediction accuracy. The model employs unsupervised Transformer blocks for pre-training, with efficient masking strategies to effectively capture long-term historical patterns and contextual information, thereby significantly boosting forecasting accuracy. Furthermore, PT-STGNN integrates a unique graph structure learning mechanism to identify dependencies between parameters, further improving the model's forecasting accuracy and interpretability. Compared with the state-of-the-art models, PT-STGNN demonstrated superior predictive performance, particularly for a longer-term prediction (i.e., 12 h), with MAE, RMSE and MAPE at 12-h prediction horizon of 2.737 ± 0.040, 4.209 ± 0.060 and 13.648 ± 0.151 %, respectively, for the algebraic mean of each parameter. From the results of graph structure learning, it is observed that there are strong dependencies between NH 3 -N and TN, TP and Q, as well as Precip, etc. This study innovatively applies STGNN, not only offering a novel approach for predicting influent WQPs and Q in WWTPs, but also advances our understanding of the interrelationships among various parameters, significantly enhancing the model's interpretability., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The Water Quality Surveillance Information System for Human Consumption (SISÁGUA) is designed to manage the risks of water contamination for human consumption. This short communication focuses on data from the 2022 Report regarding pesticide analysis. The data centers on 27 active pesticide ingredients found in drinking water samples exceeding the maximum residual limits (MRLs) established by Brazilian legislation. Results indicate that 1609 municipalities (60 %) found at least one pesticide in their water. Two hundred ten municipalities detected all 27 pesticides tested, with 11 of these pesticides reported to have some carcinogenic potential. Nearly one and a half million people were exposed to levels above the Brazilian MRL, with the sum of maximum detected residues exceeding 80,000 ppb. Additionally, the report highlights that 53 % of Brazilian municipalities did not submit water monitoring data for human consumption. Thus, improving and expanding the scope of water analysis within the SISÁGUA framework is essential., Competing Interests: Declaration of competing interest The authors have no conflict of interest to declare., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Determining the occurrence of disinfection byproducts (DBPs) in drinking water distribution system (DWDS) remains challenging. Predicting DBPs using readily available water quality parameters can help to understand DBPs associated risks and capture the complex interrelationships between water quality and DBP occurrence. In this study, we collected drinking water samples from a distribution network throughout a year and measured the related water quality parameters (WQPs) and haloacetic acids (HAAs). 12 machine learning (ML) algorithms were evaluated. Random Forest (RF) achieved the best performance (i.e., R 2 of 0.78 and RMSE of 7.74) for predicting HAAs concentration. Instead of using cytotoxicity or genotoxicity separately as the surrogate for evaluating toxicity associated with HAAs, we created a health risk index (HRI) that was calculated as the sum of cytotoxicity and genotoxicity of HAAs following the widely used Tic-Tox approach. Similarly, ML models were developed to predict the HRI, and RF model was found to perform the best, obtaining R 2 of 0.69 and RMSE of 0.38. To further explore advanced ML approaches, we developed 3 models using uncertainty-based active learning. Our findings revealed that Categorical Boosting Regression (CAT) model developed through active learning substantially outperformed other models, achieving R 2 of 0.87 and 0.82 for predicting concentration and the HRI, respectively. Feature importance analysis with the CAT model revealed that temperature, ions (e.g., chloride and nitrate), and DOC concentration in the distribution network had a significant impact on the occurrence of HAAs. Meanwhile, chloride ion, pH, ORP, and free chlorine were found as the most important features for HRI prediction. This study demonstrates that ML has the potential in the prediction of HAA occurrence and toxicity. By identifying key WQPs impacting HAA occurrence and toxicity, this research offers valuable insights for targeted DBP mitigation strategies., Competing Interests: Declaration of competing interest The authors declare that we have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Although river water is vital for drinking, irrigation and domestic needs, it faces threats from natural processes and human activities. Small and medium-sized rivers, especially in Nepal, remain understudied despite their vital importance in providing water to densely populated areas. This study evaluated the suitability for drinking and irrigation and the hydro-chemical characteristics of the Biring and Tangting rivers in Koshi province, Nepal. The results showed that turbidity, pH, EC, TDS, TH, NH 4 + , K + , Ca 2+ , Mg 2+ , Na + , Cl - , SO 4 2- values of all sampling sites in the Biring and Tangting rivers, except for the turbidity value of 10.39 NTU recorded in the PT9 site of the Tangting River, did not exceed maximum limit values set for drinking water. However, according to Water Quality Index results, the water of both rivers was in poor condition for drinking due to domestic wastewater discharges and cremation activities which caused high NH 3 - and NO 3 - values of all sampling sites in the Biring and Tangting rivers, except for the turbidity value of 10.39 NTU recorded in the PT9 site of the Tangting River, did not exceed maximum limit values set for drinking water. However, according to Water Quality Index results, the water of both rivers was in poor condition for drinking due to domestic wastewater discharges and cremation activities which caused high NH 4 + levels. The major cations in both rivers were listed as Ca 2 ⁺ > Na⁺ > K⁺ > Mg 2 ⁺, while the major anions were listed as HCO₃⁻ > Cl⁻ > SO₄ 2 ⁻ > NO₃⁻. Gibbs and Piper diagrams showed that geogenic weathering of carbonate rocks prevailing in the region affected the hydrochemistry in both rivers. Evaluation based on seven different irrigation indices and US salinity laboratory diagram revealed that the water of both rivers was suitable for irrigation despite some magnesium-related limitations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Farm dams, also known as 'agricultural ponds', are ubiquitous features of agricultural landscapes globally. Those accessed by livestock have high methane (CH 4 ) emissions per unit area relative to other freshwater systems. Fencing dams and installing water troughs to prevent livestock from entering the dams are promising strategies to improve water quality and substantially reduce their carbon footprints. However, previous studies only measured the effects of fencing on methane diffusive emissions without considering ebullitive fluxes (i.e., methane bubbles), which is often the dominant emission pathway in smaller water bodies. Also, data is lacking on how the benefits of fencing farm dams vary across seasons. Using Australia as a test case, this study investigates the benefit of fencing off farm dams by monitoring total CH 4 (diffusion + ebullition) and carbon dioxide (CO 2 ) in summer and winter. Fenced dams had 72 % lower CH 4 emissions in summer and 92 % lower in winter than unfenced dams. Similarly, CO 2 -equivalent (CO 2  + CH 4 ) fluxes were lower in fenced dams by 59 % in summer and 73 % in winter. Fenced dams had higher water quality, with 51 % less total dissolved nitrogen, 57 % less phosphorous, and 23-49 % more dissolved oxygen. Average daily air temperature was a key predictor of CH 4 emissions from farm dams, underscoring the importance of considering temporal dynamics for estimating yearly farm dam emissions. We confirmed that excluding livestock from entering farm dams using fences significantly mitigates CH 4 emissions and enhances water quality, and these benefits are maintained seasonally., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Substantial inequalities in the overall prevalence and patterns of multimorbidity have been widely reported, but the causal mechanisms are complex and not well understood. This study aimed to identify common patterns of multimorbidity in Serbia and assess their relationship with air pollutant concentrations and water quality indicators., Methods: This ecological study was conducted on a nationally representative sample of the Serbian population. Data were obtained from the European Health Interview (EHIS) Survey, a periodic study designed to assess population health using widely recognized standardized instruments. The study included 13,069 participants aged 15 and older, randomly selected through a multistage stratified sampling design. Multimorbidity was defined as having two or more self-reported diagnoses of chronic non-communicable diseases. Latent class analysis (LCA) was performed to identify clusters of multimorbidity. Concentrations of particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3), as well as water quality indicators, were obtained from the Serbian Environmental Protection Agency., Results: The overall prevalence of multimorbidity was 33.4% [32.6%-34.2%]. Six latent classes of multimorbidity were identified: Healthy, Multicondition, Cardiovascular, Metabolic syndrome, Respiratory, and Musculoskeletal. Annual increases in PM10 and SO2 concentrations, as well as daily increases in O3 concentrations, significantly raised the odds of having multimorbidity (OR = 1.02, 95% CI 1.02-1.03; OR = 1.01, 95% CI 1.00-1.02 and OR = 1.03, 95% CI 1.02-1.03, respectively). A pattern of increased risk was observed with rising levels of water contamination. Exposure to physico-chemical, microbiological and combined contamination was associated with a 3.92%, 5.17% and 5.54% higher probability, respectively, of having multiple chronic conditions. There was strong evidence that air pollutants, as well as chemical and microbial water contamination, were significantly associated with higher odds of the most common clusters of multimorbidity identified by LCA., Conclusion: There is compelling evidence of an association between multimorbidity and environmental pollution, suggesting that exposure to air pollutants and water contaminants may contribute to disease accumulation and help explain geographically and socioeconomically patterned inequalities. These findings underscore the need for extensive studies that simultaneously measure both multimorbidity and pollution to explore their complex interrelationships., Competing Interests: Declarations Ethics approval and consent to participate This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of the Institute of Public Health of Serbia (date: 10.06.2021; n˚ 3607/1). Informed consent was obtained from all individual participants included in the study. Consent for publication Not applicable. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

The relationship between landscape patterns and water quality has been extensively studied, yet the understanding of how human activity modulates the spatial scale effects of landscape patterns on water quality remains limited. Here, we investigated the water quality and landscape patterns of three rivers in the Poyang Lake Basin, China, subjected to different intensities of human activity, and analyzed the extent to which water quality parameters were influenced by human activity to unravel the spatial scale effects and identify critical landscape metrics that significantly influence water quality. The results showed that the influence of riparian zone landscape patterns on water quality progressively exceeded that of sub-basin landscape patterns as the intensity of human activity increased. For water quality parameters that were minimally affected by human activity, the influence of sub-basin landscape patterns slightly exceeded that of riparian zone landscape patterns at different intensities of human activity (differences were 0.63 %, 4.25 % and 7.65 %, respectively). Conversely, for water quality parameters significantly affected by human activity, the landscape patterns of the riparian zone had a significantly greater influence than the sub-basin landscape patterns (differences were 5.90 %, 13.00 % and 17.86 %, respectively). Furthermore, the discrepancy between the influence of riparian zone and sub-basin landscape patterns on water quality increased with increasing intensity of human activity, while the overall influence of landscape patterns on water quality showed a decreasing trend (decreasing from 60.35 % to 39.10 %). In addition, the proportions of construction land, farmland, and forestland, and the fragmentation of grassland, were identified as critical landscape metrics that significantly influenced water quality at different intensities of human activity. This study revealed that different intensities of human activity were key factors influencing the spatial scale effects of landscape patterns on water quality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Onsite wastewater systems (OWSs) can be significant sources of nutrients and E. coli to water resources, potentially resulting in water quality degradation especially during times of malfunction. An OWS is considered malfunctioning when septic tank effluent is discharged into drainfield trenches during periods when there is insufficient separation to groundwater (<30 cm), when wastewater upwells to the surface, or when backup of wastewater into the tank or home occurs. Few studies have quantified groundwater and surface water quality downgradient from malfunctioning OWSs. Thus, the goal of this study was to quantify nutrients and Escherichia coli in shallow groundwater and adjacent streams downgradient from malfunctioning OWSs. Three residences served by conventional-style OWSs were instrumented with piezometers near the drainfields for groundwater sample collection. Streams near two of the OWS were also monitored. Sites were sampled 10 times between Feb 2022 and Apr 2023. Samples were analyzed for nutrients, E. coli, and other water quality parameters. Results indicated that groundwater was typically within 30 cm of the trench bottom at 2 sites (Sites 100 and 200), thus these OWSs were malfunctioning for insufficient vertical separation distance. Groundwater beneath the 2 malfunctioning drainfields contained median concentrations of TDN (17.98 mg L -1 ), TDP (0.34 mg L -1 ), and E. coli (2419.6 MPN 100 mL -1 ) that were approximately 19, 34, and 576 times greater than concentrations in background groundwater. Groundwater near a functioning OWS (Site 300) had lower median concentrations of TDN (1.26 mg L -1 ), TDP (0.10 mg L -1 ), and E. coli (248.1 MPN 100 mL -1 ) compared to the malfunctioning sites. Drainfield groundwater regardless of functionality contained elevated pollutant concentrations relative to background groundwater, which had median concentrations of 0.95 mg-N L -1 , 0.01 mg-P L -1 , 4.2 MPN 100 mL -1 for TDN, TDP, and E. coli, respectively. Streams adjacent to the malfunctioning OWSs also contained elevated concentrations and exports of nutrients and E. coli relative to background. Thus, OWS malfunctions inhibited soil treatment processes contributing to elevated nutrient and E. coli pollution in receiving waters., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier Ltd.)

Urbanization development often leads to significant changes in the extent in area and fragmentation of built-up land landscape pattern (BLLP) in river basins, which greatly impact the processes of rainfall runoff and pollutant migration. Understanding the spatial scale effects and driving mechanisms of BLLP changes on water quality in large river basins is a challenging research topic and an international frontier in the interdisciplinary fields of geography and environment. This study analyzes the spatial variations of BLLP and water quality throughout the Yellow River Basin (YRB) during the rainy seasons from 2019 to 2021 (4 h scale). Utilized the random forest model to quantitatively separates the contributions of rainfall processes to surface runoff and water pollution, revealing the scale effects and non-linear driving mechanisms of BLLP impacts on water environment changes. The results indicate that: 1) The YRB exhibits great spatial heterogeneity in terms of both BLLP and water quality, with places with lower water quality displaying bigger areas and higher degrees of BLLP fragmentation. 2) The patch density and built-up land area (PD.B and CA.B) have a major impact on changes in water quality in the YRB, with notable impacts noted in circular buffer zones with radii of 20 km and 5 km, respectively. 3) PD.B is sensitive to water quality in the YRB, explaining 39.1%-49.5% of the variance under different rainfall conditions, and exhibits a significant non-linear relationship, with an impact threshold of 0.38 (n/100 ha). The study suggests that for large-scale regions like the YRB, the degree of BLLP fragmentation is more likely to lead to degradation of water environmental quality compared to its area. BLLP fragmentation due to higher PD.B and CA.B disrupts the original ecosystem and hydrological connectivity, resulting in poorer retention and filtration of pollutants carried by rainfall runoff, while increasing the export of other pollutants. However, once urbanization surpasses a certain threshold, the BLLP fragmentation can enhance water quality by reducing the impermeable surface connectivity, as they are no longer impacted by expanding areas. To achieve ecologically sustainable development, it is necessary to apply rational landscape management and water resource management policies that consider the dual process of how BLLP fragmentation affects the water environment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

This study addresses the critical public health issue of fecal coliform contamination in the four major rivers in South Korea (Han, Nakdong, Geum, and Yeongsan rivers) by applying advanced machine learning (ML) algorithms combined with Explainable Artificial Intelligence to enhance both prediction accuracy and interpretability. Both traditional and machine learning models often face challenges in accurately estimating fecal coliform levels due to the complexity of environmental variables and data limitations. To address this limitation, we employed two tree-based models (i.e., random forest [RF] and extreme gradient boost [XGBoost]), and two neural network models (i.e., deep neural network and convolutional neural network [CNN]). we employed the use of Shapley Additive Explanations (SHAP) to facilitate a more comprehensive understanding of the influence exerted by each variable on the model's predictions. Based on a comprehensive dataset collected from the National Institute of Environmental Research covering 16 water quality parameters and meteorological data from 2014 to 2022, our study improved the accuracy of fecal coliform estimation using XGBoost and CNN models. The optimal result was obtained using XGBoost, which had a validation Nash-Sutcliffe efficiency of 0.597 in the Han River. In addition, this study provides insights into the significant factors influencing fecal coliform concentrations across different river environments using the SHAP model. The results indicated that the XGBoost model provided superior estimation accuracy and explanations for the contributions of variables. The SHAP results provided the precise contribution of each water quality variable that affected the fecal estimation results using the XGBoost model. The study facilitates an improved understanding of the relationship between water quality variables and fecal coliform contamination mechanisms in the four major rivers in South Korea., (Copyright © 2024. Published by Elsevier B.V.)

The dipper (Cinclus cinclus) is a species strongly linked to the riparian ecosystem, known to feed on aquatic macroinvertebrates, which are sensitive to water pollution. For this, dippers have been proposed as useful bioindicators of water quality. While the distribution and ecology of the dipper are well known in Northern European rivers, few studies focus on this in Central Italy, lacking data for dipper conservation. Here, we aimed to (i) assess the dipper occurrence related to water quality using biotic indices based on diatom and macroinvertebrate communities, and (ii) evaluate the river ecosystem's overall state, through the River Functionality Index and land-use analysis in buffer areas. Overall, water quality alone does not explain the dipper occurrence, as the species was not found in many potentially suitable sites with good or high-water quality. Moreover, the diversity of the diatom and macroinvertebrate communities was not a sufficient constraint either. Conversely, the dipper occurrence significantly correlated with the River Functionality Index, which integrates several riparian ecosystem factors, indicating that well-preserved ecosystems with high functionality levels are important for dipper occurrence. Land use analyses in the areas surrounding the presence sites have shown, although not significantly, a fair level of naturalness, potentially favouring the riparian zone maintenance. As the dipper was considered in decline and threatened in Central Italy, further research on its auto-ecology and conservation threats is urgently needed. Finally, given the link between the species and the riparian ecosystem, a charismatic species such as the dipper could be used as an umbrella species in protection and conservation projects for the benefit of the entire riparian belt, which represents a buffer area of fundamental importance between terrestrial and aquatic ecosystems, although often resulted severely reduced and fragmented., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Rapid urbanization and industrial growth have led to water quantity and quality problems. Most current water allocation models focus solely on physical water and neglect the optimization of the water quantity and quality considering the water footprint. Therefore, this study aimed to establish an optimal water resource allocation model for industrial sectors based on the water footprint to identify the most effective strategies for determining the water quantity and quality distribution in river basins. First, we constructed an improved water footprint accounting system using input‒output tables to quantify the total water footprint, grey water footprint, and virtual water trade. Second, we constructed a multiobjective optimal water resource allocation model by considering the water footprint as a decision variable and combining regional economic development and productivity differences. Finally, we compared the water allocation results obtained for the Yellow River Basin, a typical "water-quantity water-scarce region" in China, with those of the Yangtze River Basin, a "water-quality water-scarce region." The results indicate that the total water footprints of the Yellow and Yangtze River Basins were 211.37 and 317.83 billion m³, respectively, prior to optimization. After optimization, the footprints were 199.54 and 306.03 billion m³, respectively. Water resources have been reallocated through virtual water trade strategies to effectively alleviate both water quantity and quality problems. Virtual water trade strategies have emerged as policy tools capable of mitigating mismatches between industrial systems and regional water resource allocation and providing a solution to physical-virtual water system challenges within river basins., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The continuous impact of COVID-19 on aquatic environments has attracted considerable attention, primarily focusing on short-term water quality effects during lockdown, while studies on changes following the lifting of restrictions are relatively limited. Following adjustments to China's pandemic public policy in December 2022, the effects on water quality and nutrient status in lakes and reservoirs remain unclear. In this study, we collected national environmental monitoring data comprising 15 indicators of water quality, meteorology, soil, and economic factors, from 86 lakes and reservoirs across China between March 2021 and December 2023. Total nitrogen (TN), total phosphorus (TP), the mass TN/TP ratio (TN/TP), and ammonia-nitrogen (NH 3 -N) were selected as representative nutrient indicators. The water quality index (WQI) and multivariate statistical techniques were employed to comprehensively assess national water quality and identify the drivers of nutrient variations in sub-regions. The results show that during the monitoring period from 2021 to 2023, Chinese national water quality consistently fell within the 'good (61-80)' or 'excellent (81-100)' categories, with the lowest water quality observed in the summer of each year. The summer of 2021 recorded the lowest WQI value among all seasons at 75.01. Following the elimination of the COVID-19 epidemic public lockdown policy, concentrations of TN, TP, and NH 3 -N declined. These findings indicate a general improvement in the water quality of lakes and reservoirs nationwide. Mantel test and multiple stepwise linear regression models revealed significant correlations between nutrients and human activity indicators in central, eastern, and northern China. In northern China, TP showed a significant positive correlation with GDP (0.2 < Mantel's r < 0.5, P < 0.05), with the beta value increasing from 0.27 to 0.38 after the elimination of the COVID-19 epidemic public lockdown policy. In these regions, the influence of rainfall, wind speed, NDVI, surface soil moisture, and water temperature on nutrients shifted from significant to insignificant effects after the elimination of the COVID-19 epidemic public lockdown policy, indicating that human activities have overshadowed natural factors. This study examines the water quality and nutrient status of lakes and reservoirs in China after the elimination of the COVID-19 epidemic public lockdown policy, highlighting the long-term impacts and spatial variations of the pandemic. These findings will inform environmental governance and promote sustainable water resource management in the post-pandemic era., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

This study presents the process of design and development of a low-cost turbidimeter for monitoring water quality, facilitating rigorous spatial-temporal variability analysis within large-scale hydrological systems. We propose a low-cost optical turbidimeter, modifying the existent SEN0189 turbidity sensor, Arduino boards, and additional sensors for temperature compensation. We compared a low-cost system with high-tech sensors, modifying the original low-cost SEN0189 probe for enhanced environmental performance. The three-step methodological framework involved prototype development, compensation for environmental factors, and preparation for future field deployment. Calibration equations with a high coefficient of determination and a temperature correction equation were established. We made adaptations to overcome field deployment challenges, including a 3-D printed sensor case, defining the relationship between measurement uncertainty and energy consumption, and specifying field installation guidelines. In summary, this study presents a comprehensive approach to a low-cost optical turbidity system, demonstrating its potential for accurate and affordable field deployment. We aim to address the critical need for sustainable inland water management tools, making this system a valuable contribution to environmental monitoring practices. We also aim to inspire similar development of open-source monitoring systems within our community., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Aquatic ecosystems serve as crucial reservoirs for pathogens and antimicrobial resistance genes, thus presenting a significant global health risk. Here, we investigated the phylogenomics of Aeromonas veronii from Lake Wilcox in Ontario. Among the 11 bacterial isolates, nine were identified as A. veronii . Notably, 67% of A. veronii isolates were potential human pathogens. Considerable genetic diversity was noted among the A. veronii isolates, suggesting the lake as a reservoir for multiple human pathogenic strains. Comparison of the A. veronii sequenced with global A. veronii genomes highlighted significant genetic diversity and suggests widespread dissemination of strains. All the isolates carried chromosomal genes encoding resistance to β-lactams. Although virulence gene content differed between human and non-human pathogenic strains, type III secretion systems was associated with human pathogenic isolates. The assessment of AMR genes in global isolates showed that β-lactam and tetracycline resistance genes were predominant. Although the machine learning-based pangenome-wide association approach performed did not yield any source-based genes, some genes were enriched in a few isolates from different sources. The mrkABCDF operon that mediates biofilm formation and genes encoding resistance to colistin, chloramphenicol, trimethoprim, and tetracycline were enriched in animal products, whereas macrolide resistance genes and Inc plasmid-types were linked to the aquatic environment. Novel biosynthetic gene clusters were identified, suggesting that A. veronii with varying pathogenic potential could produce unique secondary metabolites. There is a need for continuous tracking of pathogens in aquatic ecosystems to contribute to our understanding of their evolutionary dynamics and the ecological roles of their genetic elements., Importance: Lakes and other aquatic ecosystems can harbor harmful bacteria that can make people sick and resist antibiotics, posing a significant global health risk. In this study, we investigated Aeromonas veronii , a Gram-negative bacteria found in Lake Wilcox in Ontario. We used various techniques, including whole-genome sequencing (WGS), to analyze the bacteria and found that many of the isolates had the potential to cause human disease. We also discovered significant genetic diversity among the isolates, indicating that the lake may be a reservoir for multiple human pathogenic strains. All isolates carried genes that confer resistance to antibiotics, and some virulence genes were associated with human pathogenic isolates. This study highlights the importance of monitoring aquatic ecosystems for harmful bacteria to better understand their evolution, potential for human pathogenicity, and the ecological roles of their genetic elements. This knowledge can inform strategies for preventing the spread of antibiotic-resistant bacteria and protecting public health.

Swales are a low-cost, conveyance and treatment system to manage roadway runoff, but available design guidance is limited. Eight grass swales were constructed in Raleigh, North Carolina, USA, to systematically evaluate the effects of design factors: length, shape, and longitudinal slope under two different storm sizes. Water from an onsite reservoir was used to generate synthetic runoff and simulate flow through the swales. Inflow volume, total suspended sediment (TSS), nitrogen, phosphorus, and four total metals (copper, lead, zinc, and cadmium) were tested with simulated levels representing highway runoff. Efficiency ratios were used to estimate the reductions in inflow volume, pollutant concentrations, and mass loads. Swale length, shape, longitudinal slope, and storm size significantly influenced runoff volume reduction. The longer (30 m) trapezoidal swale constructed on the flatter (1%) longitudinal slope provided maximum reductions in sediment and heavy metal concentrations during small-medium storms. Larger storms had modestly reduced pollutant and volume mitigation. Effluent nutrient concentrations generally exceeded the influent exporting nitrogen and phosphorus from all swale configurations. Significantly better pollutant load reductions were provided by the longer swales for all pollutants, except dissolved phosphorus. Therefore, to optimize swale function, designers could maximize the swale length to the greatest extent practicable, particularly when swales receive inflow from end-of-pipe systems draining roadway surfaces. The trapezoidal cross-section was superior to the triangular cross-section for stormwater treatment. Proper vegetation establishment and maintaining optimal grass height are key to proper swale functioning., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Freshwater and groundwater are important resources for the drinking water supporting agricultural and livestock activities in the Córdoba province, Argentina. The aim of this study was to assess the physicochemical and microbiological quality of surface water (n = 14) and groundwater (n = 17) sites in the middle-lower basin of the Ctalamochita River (Córdoba, Argentina) for human and animal consumption. A total of 18 physicochemical and five microbiological parameters were evaluated to determine the hydrogeological characteristics of both water resources and their suitability for human and animal consumption using the Water Quality Index (WQI). The results indicated that Na + and HCO 3 - were the dominant cation and anion, respectively, in both water resources. Physicochemical and microbiological parameters values were compared with national and international guidelines. The WQI showed that groundwater samples exhibited poorer quality when compared to surface waters for human consumption, primarily due to elevated concentrations of major ions and the presence of total coliforms and Pseudomonas aeruginosa. Meanwhile, the WQI for animal consumption indicated that both surface and groundwater samples were suitable for this purpose. The Piper diagram showed that most of the surface water samples were classified as Na + -Cl - -HCO 3 - , while groundwater samples were classified as Na + -HCO 3 - . This classification highlights the hydrogeochemical differences between the two water resources. The Gibbs diagram indicates that the chemical composition of both surface and groundwater sources is primarily controlled by processes of rock-water interaction and evaporation. The findings of this study will facilitate the development of a proactive plan to safeguard and sustain water resources in the middle-lower basin of the Ctalamochita River. This can be achieved through the implementation of preventive strategies and the introduction of innovative policies., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)