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

Urban areas often struggle with deteriorated water quality because of complex interactions between landscape factors and climatic variables. However, few studies have considered the effects of landscape variables on water quality at a sub-500-m scale. We conducted a spatial statistical analysis of six pollutants for 128 water quality stations in four watersheds around Portland, Oregon, using data from 2015 to 2021 for the wet season at two microscales (100 m and 250 m buffers). E. coli was associated with land cover, soil type, topography, and pipe length, while lead variations were best explained by topographic variables. Developed land cover and impervious surface explained variations in nitrate, while orthophosphate was associated with mean elevation. Models for zinc included land cover and topographic variables in addition to pipe length. Spatial regression models better explain variations in water quality than ordinary least squares models, indicating strong spatial autocorrelation for some variables. Our findings provide valuable insights to city planners and researchers seeking to improve water quality in metropolitan areas by manipulating city landscapes., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Water quality monitoring is very important in agricultural catchments. UV-Vis spectrometry is widely used in place of traditional analytical methods because it is cost effective and fast and there is no chemical waste. In recent years, artificial neural networks have been extensively studied and used in various areas. In this study, we plan to simplify water quality monitoring with UV-Vis spectrometry and artificial neural networks. Samples were collected and immediately taken back to a laboratory for analysis. The absorption spectra of the water sample were acquired within a wavelength range from 200 to 800 nm. Convolutional neural network (CNN) and partial least squares (PLS) methods are used to calculate water parameters and obtain accurate results. The experimental results of this study show that both PLS and CNN methods may obtain an accurate result: linear correlation coefficient (R 2 ) between predicted value and true values of TOC concentrations is 0.927 with PLS model and 0.953 with CNN model, R 2 between predicted value and true values of TSS concentrations is 0.827 with PLS model and 0.915 with CNN model. CNN method may obtain a better linear correlation coefficient (R 2 ) even with small number of samples and can be used for online water quality monitoring combined with UV-Vis spectrometry in agricultural catchment., (© 2022. The Author(s).)

Forestry best management practices (BMPs) have proven to be very effective in protecting adjacent stream water quality at the plot scale. However, our knowledge is incomplete about the effectiveness of forestry BMPs in large watersheds where industrial forests are intensively managed. In this study, we compared long-term concentrations and loadings of total suspended solids (TSS), nitrate/nitrite nitrogen (NO 3 NO 2 -N), total Kjeldahl nitrogen (TKN), and total phosphorus (TP) before (1978-1988) and after extensive implementation of forestry BMPs (1994-2008) at the outlet of a 5000-km 2 river basin that is predominately covered by intensively managed pine forests in Central Louisiana, USA. Our study shows that after extensive BMP implementation, both concentrations and loads of TSS in the basin outlet decreased significantly from 34 to 25 mg L -1 and from 55,000 to 36,700 t year -1 , respectively. However, no significant difference was found in NO 3 NO 2 -N, TKN, and TP concentrations between the two periods. The results of nutrient loadings varied, whereby the annual nitrogen loading declined without significant differences (from 1790 to 1600 t year -1 for TKN and from 176 to 158 t year -1 for NO 3 NO 2 -N, respectively) but the annual TP loading increased significantly (from 152 to 192 t year -1 ) after BMP implementation. The increase in TP loading is likely due to an increased application of phosphorus fertilizer, which offset BMPs' effects especially during high-flow conditions. These results strongly suggest that current forestry BMPs in this region are effective in reducing sediment loading, but current BMP guidelines for fertilization and nutrient management need to be reviewed and improved.

The Cache River Watershed (CRW) in Arkansas is part of one of the largest remaining bottomland hardwood forests in the US. Although wetlands are known to improve water quality, the Cache River is listed as impaired due to sedimentation and turbidity. This study measured turbidity and total suspended solids (TSS) in seven sites of the lower CRW; six sites were located on the Bayou DeView tributary of the Cache River. Turbidity and TSS levels ranged from 1.21 to 896 NTU, and 0.17 to 386.33 mg/L respectively and had an increasing trend over the 3-year study. However, a decreasing trend from upstream to downstream in the Bayou DeView tributary was noted. Sediment loading calculated from high precipitation events and mean TSS values indicate that contributions from the Cache River main channel was approximately 6.6 times greater than contributions from Bayou DeView. Land use surrounding this river channel affects water quality as wetlands provide a filter for sediments in the Bayou DeView channel.

Roadside ditches are ubiquitous, yet their role in water pollution conveyance has largely been ignored, especially for bacteria and sediment. The goal of this study was to determine if roadside ditches are conduits for fecal indicator organisms and sediment, and if land use, specifically manure amendment, affects the concentrations and loadings. Seven roadside ditches in central New York, adjacent to either manure amended fields or predominately forested land, were monitored for one year for Escherichia coli (E. coli), total suspended solids (TSS) and flow. E. coli concentrations in water samples following storms averaged 4616 MPN of E. coli/100 mL. Concentrations reached as high as >241,960 MPN of E. coli/100 mL and frequently exceeded New York State and US EPA recommendations. Concentrations peaked in both summers following manure spreading, with declining levels thereafter. However, viable organisms were detected throughout the year. The concentrations were also high in the forested sites, with possible sources including wildlife, pets, septic wastes and livestock. E. coli concentrations and loadings were related to TSS concentrations and loadings, whether manure had been spread in the last 30 days and for concentrations only, antecedent rainfall. Viable E. coli were also present in ditch sediment between storm events and were available for resuspension and transport. Total suspended solids concentrations averaged 0.51 g/L and reached as high as 52.2 g/L. Loads were similarly high, at an average of 631.6 kg/day. Both concentrations and loads tended to be associated with discharge and rainfall parameters. The cumulative pollutant contribution from the ditch network was estimated to be large enough to produce detectable and sometimes high concentrations in a receiving stream in a small, rural watershed. Roadside drainage networks need to be actively managed for water quality improvements, because they capture and rapidly shunt stormwater and associated contaminants to streams., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

The biofloc technology (BFT) in sea cucumber (Apostichopus japonicus) farming utilizes nutrient cycling, driven by heterotrophic microorganisms, to improve water quality and promote sustainable aquaculture. This study explored the potential of sodium bicarbonate and sodium acetate as novel carbon sources, which may offer advantages in maintaining water stability and enhancing microbial diversity compared to traditional carbon sources. Juvenile sea cucumbers were cultured in a 64‐day trial and assigned to five treatment groups: S (sucrose), SSa (S + sodium acetate), SSb (S + sodium bicarbonate), Nc (no carbon source), and Cg (control group), each treatment group was repeated three times (n = 3). The inclusion of sodium bicarbonate and sodium acetate significantly improved water quality parameters. The group SSb exhibited a higher pH (8.28), and significantly lower ammonia nitrogen (0.501 mg L−1), and nitrite levels (0.031 mg L−1) compared to other groups. Additionally, the biofloc volume (BFV; 17 mL L−1), total suspended solids (TSSs; 238 mg L−1), and protein content (13.9%) in the group SSb were all within the tolerance range for sea cucumbers. Group SSb also showed the significantly highest weight gain rate (WGR; 78.5%) and specific growth rate (SGR; 0.91%), alongside increased enzyme activities, including superoxide dismutase (SOD; 179 U mL−1) and peroxidase (POD; 1.59 U mL−1), which were significantly higher than those in other groups. Furthermore, the group SSb demonstrated enhanced gut microbiota diversity, characterized by a higher abundance of beneficial Bacillus and lower levels of harmful Vibrio and Pseudomonas. The addition of SSb significantly improved water quality by maintaining optimal pH and reducing harmful nitrogen compounds, which in turn supported enhanced physiological growth and increased gut microbiota diversity, indicating its potential as a superior carbon source in biofloc systems. [ABSTRACT FROM AUTHOR]

Exurban expansion can degrade significantly stream water quality. This study was conducted on Rock Creek of the Clark's Fork of the Yellowstone River in southcentral Montana, USA. The impact from recent exurban expansion was evaluated by a baseline study measuring total suspended solids (TSS), total phosphorus (TP), total nitrogen (TN) and nitrites (NO2) and nitrates (NO3) together. This was part of a larger study by Montana Department of Environmental Quality to assess water quality, identify sources of pollution and develop total maximum daily loads (TMDL). Water samples were measured for these analytes at nine (2022) and 11 (2023) locations with different land-uses over seven periods (both years). Seasonal spikes, corresponding to runoff (2022, late May), occurred in TSS, TP and TN. Data from 2023 showed similar but reduced levels occurring in June for TSS and TP. Total suspended solids, TP, NO2 and NO3 concentrations increased by location year over year, 2022 to 2023. The high relative concentrations of NO2 and NO3 in Rock Creek are primarily associated with exurban expansion, a significant threat to stream quality and wildlife habitat in Montana. The results will assist county planners in land use decisions. KEY POLICY HIGHLIGHTS: Nitrite and nitrate levels were significantly higher in Rock Creek near exurban areas. Nitrite and nitrate and total phosphorus levels increased 23% and 27%, respectively, from 2022 to 2023. Exurban expansion has accounted for 78% of homes built in our study area, with an accompanied 31,840 acres of habitat loss. Two sites are within the Greater Yellowstone Ecosystem and all sites are within the historic home range for the grizzly bear (Ursus arctos) and wolverine (Gulo gulo). [ABSTRACT FROM AUTHOR]

The article "Unleashing the power of remote sensing data in aquatic research: Guidelines for optimal utilization" published in Limnology & Oceanography Letters discusses the importance of remote sensing data in lake studies, focusing on the estimation of chlorophyll a as a water quality indicator. It highlights the complexities of utilizing remote sensing data in limnological studies, emphasizing the need for careful product selection, atmospheric correction, and validation processes. The article provides recommendations for optimal utilization of remote sensing data in aquatic research, including choosing the right products, processes, and strategies for improving data quality and collaboration between aquatic sciences and remote sensing communities. [Extracted from the article]

This study investigates the performance of published bio-optical remote sensing indices/algorithms for monitoring water quality changes in Lake Karla, Greece, caused by Storm Daniel after the September 2023 flooding event. Commonly applied indices were utilised to estimate chlorophyll-a (Chl-a) and total suspended solids (TSS) using Sentinel-2 high-resolution optical imagery. In situ measurements were undertaken and water samples were collected during the pre-flooding period, post-flooding, and one-year post-flood, providing a basis for validating the remote sensing models. Monitoring results showed that most physicochemical parameters changed considerably. Chl-a and TSS were estimated by testing five and seven indices, respectively. Regarding the Chl-a estimation, the NDCI and 2-BDA indices outperformed other models, having high correlations with in situ Chl-a measurements and effectively following the in situ Chl-a temporal trends. Among the TSS indices, NDWI and TUR-IND demonstrated better performances, effectively capturing the variations in suspended solids. Overall, this study highlights the potential of Sentinel-2 imagery in assessing water quality changes, particularly in response to flooding events. It is an exploratory approach to assess the feasibility of utilising optical satellite data for evaluating the environmental impacts of natural disasters on lake water quality and supports decision-making in environmental management. Additionally, it identifies potential challenges and considerations that must be addressed to ensure effective application. [ABSTRACT FROM AUTHOR]

The study examined the core, buffer, and transition zones within the Cat Ba Biosphere Reserve in Vietnam to assess changes in five land cover categories (water surface, cropland, vacant land, residential land, and forestland) between 2018 and 2022. Additionally, we aimed to evaluate water quality using three indicators (normalized difference turbidity index, normalized difference chlorophyll index, total suspended solids) and air quality using four indicators (nitrogen dioxide, sulfur dioxide, carbon monoxide, ozone) for the 2022 data. Land cover change analysis and monitoring of water and air quality indicators were conducted using the Google Earth Engine platform, employing Sentinel-2 imagery for land cover and water quality assessment and Sentinel-5P images for air quality assessment. The findings revealed correlations between changes in land cover and water and air quality indicators within the Cat Ba Biosphere Reserve. While occasional instances of values surpassing permissible limits were noted, the average values over the 12-month period in 2022 indicated that water and air quality indicators remained within acceptable thresholds. These results suggest effective preservation efforts in the Cat Ba Biosphere Reserve, indicating no significant signs of degradation. [ABSTRACT FROM AUTHOR]

This study interrogates the state of social-ecological landscapes (SEL) in West Africa, focusing on two case studies: the Mankran SEL in Ghana (case study 1) and the Doma–Rutu SEL in Nigeria (case study 2). Using a mix of methods, the assessment was framed by the Drivers Pressure State Impact Response (DPSIR) model tailored for SEL evaluation (DPSIR-SEL). In the Mankran landscape, land use patterns shifted significantly from 2008 to 2018, with cash crop cultivation peaking at 30% in 2015 before declining to 14.5% by 2018. Water quality assessments in the Mankran micro-watershed indicated that several parameters, including Total Suspended Solids (TSS) at 914.41 ± 1974 mg/L, lead at 18.73 ± 17.26 µg/L, and arsenic at 53.41 ± 86.66 µg/L, exceeded World Health Organization (WHO) standards, raising concerns about potential contamination. In contrast, the Doma–Rutu landscape in Nigeria experienced land use and land cover (LULC) changes from 2000 to 2022, characterized by the expansion of residential and agricultural areas alongside modifications to natural water bodies and vegetation. Water quality issues have emerged, with elevated levels of electrical conductivity, total dissolved solids, and salinity. Furthermore, Focus Group Discussions (FGDs) revealed persistent herder-farmer conflicts in Nigeria, which have historically constrained crop production due to various environmental and social factors. The intertwined challenges faced by both the Mankran and Doma–Rutu landscapes underscore the urgent need for sustainable and inclusive resource management, adaptive land-use strategies, and proactive measures to safeguard water quality. [ABSTRACT FROM AUTHOR]

Simple Summary: This study considered using insect families as bioindicators to establish the health status of an ecosystem's lentic bodies. The water quality in urban lentic bodies in the Metropolitan Region, Chile, was evaluated using aquatic insect family assemblages and physicochemical variables for conserving aquatic life. The eudominant insect families were Corixidae (associated with very bad water quality), Chironomidae (very bad), and Baetidae (good). The TSS (total suspended solids), P (phosphorus), and EC (electrical conductivity) were strongly positively correlated and negatively associated with DO (dissolved oxygen) levels. The TSS level was the most significant influential factor. Based on the nitrogen and phosphorus levels in the three water bodies, all of them were eutrophic. Given the diversity and complexity of ecosystems, studies should delve deeper into wetlands to establish methods that contribute to determining water quality, using insects as bioindicators and physicochemical variables. Considering the diversity of these water bodies, it is possible to determine not only the water quality but also the conservation state of the whole environment. This study considered using insect families as bioindicators to establish the health status of an ecosystem of lentic bodies. The water quality in urban lentic bodies in the Metropolitan Region, Chile, was evaluated from aquatic insect family assemblages and physicochemical variables for conserving aquatic life. Evaluations were carried out in parallel at four sampling stations of three water bodies (Batuco Wetland, Carén Lagoon, and Chada Reservoir) in a 2–3-year series, spring (2015, 2017, and 2018) and fall (2016 and 2018), with three replicates. Families were randomly sampled and aquatic insects were identified; abundance and richness differences were compared with non-parametric tests. Physicochemical variables were measured using portable multiparametric and laboratory chemical analyses to determine the water quality. A Canonical Correspondence Analysis was applied for insect families and the physical–chemical variable. In order to categorize the health of these water bodies based on aquatic insect composition and abundance, the Family Biotic Index (FBI), British Biological Monitoring Work Party (BMWP), and Stream Invertebrate Grade Number—Average Level (SIGNAL), adapted for Chile by Figueroa et al. (2007), were calculated. The eudominant insect families were Corixidae and Chironomidae in Batuco, Chironomidae and Corixidae in Carén, and Corixidae in Chada. Baetidae was dominant in Carén and Chada. The water bodies were classified in descending order of water quality by Chilean physicochemical standards: Chada > Carén > Batuco. The TSS (total suspended solids), phosphorus, and electrical conductivity were strongly positively correlated and negatively associated with dissolved oxygen. The TSS level was the most significant influential factor. The BMWP value and the SIGNAL differed from the FBI, but the first was more restrictive, contributing to the conservation of these ecosystems. Based on the nitrogen and phosphorus levels in the water bodies, all of them were eutrophic. Given the ecosystem diversity and complexity, studies should delve deeper into wetlands to establish methods that contribute to determining water quality, using insect families as bioindicators and physicochemical variables. [ABSTRACT FROM AUTHOR]

Chilika Lake, a RAMSAR site, is an environmentally and ecologically pivotal coastal lagoon in India facing significant emerging environmental challenges due to anthropogenic activities and natural processes. Traditional in situ water quality monitoring methods are often labor intensive and time consuming. This study presents a novel approach for ex situ water quality monitoring in Chilika Lake, located on the east coast of India, utilizing Google Earth Engine (GEE) and spectral indices, such as the Normalized Difference Turbidity Index (NDTI), Normalized Difference Chlorophyll Index (NDCI), and total suspended solids (TSS). The methodology involves the integration of multi-temporal satellite imagery and advanced spectral indices to assess key water quality parameters, such as turbidity, chlorophyll-a concentration, and suspended sediments. The NDTI value in Chilika Lake increased from 2019 to 2021, and the Automatic Water Extraction Index (AWEI) method estimated the TSS concentration. The results demonstrate the effectiveness of this approach in providing accurate and comprehensive water quality assessments, which are crucial for the sustainable management of Chilika Lake. Maps and visualization are presented using GIS software. This study can effectively detect floating algal blooms, identify pollution sources, and determine environmental changes over time. Developing intuitive dashboards and visualization tools can help stakeholders engage with data-driven insights, increase community participation in conservation, and identify pollution sources. [ABSTRACT FROM AUTHOR]

Fast urbanization can result in significant stormwater runoff pollution due to changes in land use. A 3-year study on the distribution and temporal variations of urban water pollutants in stormwater runoff was conducted, with a specific focus on the influence of land-use patterns in the recharge zone of a regional karst aquifer in Texas (Edwards Aquifer). The presence and concentration of various water pollutants including total suspended solids (TSS), total dissolved solids (TDS), nutrients (nitrite, nitrate, ammonia and phosphate), total carbon (TC) and total organic carbon (TOC), oil and grease (O&G), and eight heavy metals (Fe, Mg, Cu, Pb, Zn, Ni, Cr, Cd) were measured in stormwater samples collected from three bioswales. Results show that average TSS in site S1 (598.87 mg/L) and S2 (628.69 mg/L), COD in site S1 (103.97 mg/L), phosphate in sites S1 (1.44 mg/L) and S3 (0.65 mg/L), and O&G (ranging from 50.63 to 84.32 mg/L) in all three sites surpassed the national average (NSQD). While residential areas were identified as the main sources of nutrients, roads and parking lots were associated with heavy metals. Temporal variations indicated the effect of antecedent dry days on the concentrations of TSS and phosphate. Growing seasons as well as pet feces were associated with elevated nitrate concentrations in residential areas. Organic carbon was found overall higher during warmer months, while heavy metals during cooler months. The study also identified specific land-use practices that can be enhanced to mitigate stormwater pollution, such as the implementation of permeable pavements, rain gardens, and stricter waste disposal regulations. The results of this study offer valuable insights for enhancing stormwater management strategies to better mitigate stormwater pollution in urban regions. [ABSTRACT FROM AUTHOR]

Advancements in smart sensing and control technologies enable urban drainage engineers to retrofit stormwater storage facilities with real-time control devices for mitigating stormwater in-site overflow, downstream flooding, and overloaded total suspended solids (TSS) in drainage pipes. While the smart technology can improve the performance of the static drainage systems, coordinatively controlling multiple valve and gate operations poses a significant challenge, especially at a large-scale watershed. Using a benchmark stormwater model located at Ann Arbor, Michigan, USA, we assessed the impact of different real-time control strategies (local individual downstream control and system-level multiple control) on balancing flooding mitigation at downstream outlets and TSS reduction at upstream storage units, such as detention ponds. We examined changes in peak water depth, outflow, and TSS as indicators to assess changes in water quantity and quality. The results indicate that system-level control can reduce peak water depth by up to 7.3%, reduce flood duration by up to 34%, and remove up to 67% of total suspended solids compared with a baseline uncontrolled system, with the outflow from upstream detention ponds being the most important hydraulic indicator for control strategy rule set-up. We find that system-level control does not always outperform the individual downstream controls, particularly in alleviating flooding duration at some downstream outlets. With urban growth and a changing climate, this research provides a foundation for quantifying the benefits of real-time control methods as an adaptive stormwater management solution that addresses both water quantity and quality challenges. [ABSTRACT FROM AUTHOR]

Monitoring and analyzing reservoir water quality are crucial for ecological and environmental strategies. This study examines the differences between the water quality index (WQI) of Indonesia (WQI-INA), Malaysia (DOE-Malaysia), Oregon (WQI-Oregon), and Italy (PI-Prati), considering the tropical climate of Indonesia and Malaysia, and contrasting with the temperate climate of Oregon and the Mediterranean climate of Italy. Using data from the Sutami Reservoir in Indonesia from 2015 to 2021, the study assesses water quality parameters such as BOD, COD, DO, NH3, NO3, total suspended solids, total phosphorus (TP), and pH at various depths (0.3, 5, and 10 meters) across three sites (upstream, midstream, down-stream). The results show varied classifications: WQI-INA rated the reservoir as "pretty good," WQI-Oregon as "poor," and both DOE-Malaysia and PI-Prati as "slightly polluted." Spatial analysis of vertical distribution revealed "slightly polluted" (WQI-INA), "moderately polluted" (WQI-Oregon and PI-Prati), and "heavily polluted" (DOE-Malaysia). These discrepancies arise from differences in local environmental standards, regulatory requirements, and specific water quality concerns included in each index. The Sutami Reservoir water quality status was declared using WQI-INA, however, other methods were employed to simulate the worst-case scenarios and inform preventive actions. The Sutami Reservoir hyper-eutrophic conditions indicate a pollution load capacity of 65.22 tons per year. Critical parameters such as pH and TP highlight significant water quality and pollution issues. Recommendations for water quality treatment under heavy pollution conditions include applying 12.09-120.87 tons of lime, using 78.75-393.75 kg of chemical buffers, oxygen diffusion, controlling riparian vegetation over 2.37-23.7 hectares, dredging 37,100 m3 of sediment per year, and reducing nutrient sources through community involvement. [ABSTRACT FROM AUTHOR]

Hydrological modeling is a very relevant tool for planning and managing water resources because it considers the spatial and temporal distribution of hydrological processes and can be used for various purposes, such as estimating water availability, predicting flows, and analyzing the hydrological response of the basin as a result of changes in land use. The objective of this work was to calibrate and validate the Soil and Water Assessment Tool (SWAT) model for the Corumbataí River Basin, Brazil, and analyze the impacts of changing land use and land cover on the quality and quantity of water in the basin. Data on flow, total suspended solids, total phosphorus, and total nitrogen were calibrated and validated. The model's performance was better in simulating flow on a monthly scale when compared with a daily scale, with Nash–Sutcliffe efficiency coefficient (NS) and R2 equal to 0.79 and PBIAS equal to 3.8% in the calibration and NS and R2 equal to 0.58 and PBIAS equal to 1.7% in the validation period. The PBIAS measures the average tendency of simulated values to be higher or lower than those observed and was the statistical index that best classified the model's performance in nutrient simulation, thus indicating that nutrient values can be used when accumulated over time. Among the four alternative land use and land cover scenarios, Scenario 2 (pessimistic) resulted in greater sediment production and surface runoff in the basin. The results presented showed that the SWAT model was able to accurately simulate the variables involved in the calibration and validation process, proving to be a viable tool to support managers in the planning, management, and conservation of the Corumbataí River Basin, through scenario simulation alternative land use options, which highlighted the impacts that could be generated. [ABSTRACT FROM AUTHOR]

Marine pollution poses significant risks to both human and marine health. This investigation explores the limnological status of the Odisha and West Bengal coasts during the annual cruise program, focusing on the influence of riverine inputs on coastal marine waters. To assess this impact, physicochemical parameters such as pH, salinity, total suspended solids (TSS), dissolved oxygen (DO), biochemical oxygen demand (BOD), and dissolved nutrients (NO2-N, NO3-N, NH4-N, PO4-P, SiO4-Si, total-N, and total-P) were analyzed from samples collected along 11 transects. Multivariate statistics and principal component analysis (PCA) were applied to the datasets, revealing four key factors that account for over 70.09% of the total variance in water quality parameters, specifically 25.01% for PC1, 21.94% for PC2, 13.13% for PC3, and 9.99% for PC4. The results indicate that the increase in nutrient and suspended solid concentrations in coastal waters primarily arises from weathering and riverine transport from natural sources, with nitrate sources linked to the decomposition of organic materials. Coastal Odisha was found to be rich in phosphorus-based nutrients, particularly from industrial effluents in Paradip and the Mahanadi, while ammonia levels were attributed to municipal waste in Puri. In contrast, the West Bengal coast exhibited higher levels of nitrogenous nutrients alongside elevated pH and DO values. These findings provide a comprehensive understanding of the seasonal dynamics and anthropogenic influences on coastal water quality in Odisha and West Bengal, highlighting the need for targeted conservation and management efforts. [ABSTRACT FROM AUTHOR]

Antimicrobial resistance (AMR) is a significant global issue impacting human, animal, and environmental health, as well as economic security. Water bodies, especially, are now recognized for their role in the spread of antimicrobial-resistant pathogens, though standardized monitoring methods are lacking. This study investigates the presence of extended-spectrum beta-lactamase (ESBL) producing Escherichia coli in the Sungai Terengganu River in Malaysia, focusing on water quality and ESBL E. coli monitoring. Sampling was conducted twice in 2023 at 13 locations along the river. Overall, the water quality index (WQI) classified the river as Class II (WQI = 81), with upstream regions rated as Class I, indicating minimal anthropogenic impact. Higher Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), and Total Suspended Solids (TSS) in downstream areas suggested organic pollution from anthropogenic activities. Four metal elements exceeded the National Water Quality Standards (NWQS): Al (0.88 mg/L), Fe (3.45 mg/L), Cu (0.102 mg/L), and Hg (2.525 mg/L). No Pb, Cr, Se, Sn, or As were detected. Statistical analysis showed better water quality correlates with lower microbial contamination. ESBL E. coli was found in 8 of 13 sampling sites (61.5%), with the highest concentration at 800 CFU/100 mL. From 40 presumptive ESBL isolates tested, 87.5% (35 isolates) were positive for ESBL and carried additional drug resistance genes, including mcr-1, tetW, sul-1, and sul-2. These findings indicate a concerning presence of multidrug-resistant E. coli in the river, representing a potential public health risk. [ABSTRACT FROM AUTHOR]

The Zandvlei Estuary is the only functioning estuary along the False Bay coastline of Cape Town and is therefore of extreme local ecological importance. The most significant problems are eutrophication and siltation caused by the increased total inorganic nitrogen (TIN) and soluble ready phosphorus (SRP) levels due to urban development and the associated increased impervious surface area in the catchment that drains into it. In South Africa, stormwater drainage systems conventionally channel everything they collect into receiving water bodies without significant treatment. Sustainable drainage systems (SuDS) provide an alternative approach to managing stormwater runoff. They are designed to manage both stormwater quality and quantity while potentially improving biodiversity and amenity. This project modelled the potential improvement in the quality of the water entering Zandvlei Estuary resulting from the implementation of selected SuDS control measures in Zandvlei’s Diep River catchment using the software program, PCSWMM. SRP, TIN, total phosphorus (TP) and total suspended solids (TSS) were selected as pollutant indicators. Treatment trains that included a large, constructed wetland at the bottom of the catchment will likely provide the greatest improvements to the water quality entering Zandvlei – potentially reducing SRP, TIN, TP and TSS by approximately 59%, 53%, 53%, and 66%, respectively – as well as potentially reducing the runoff by 48%. [ABSTRACT FROM AUTHOR]

This study evaluated the biological and physicochemical parameters of the Oda River, including the detection of heavy metals. To achieve this purpose, a quantitative experimental research design was employed. Twenty-four water samples were taken along the Oda River from Obeng ne Obeng, Abuakwaa, and Odaso communities. The samples were analysed in a laboratory, and the results were compared to the irrigation water quality standards from the Food and Agricultural Organization (FAO). The study found that the concentration of turbidity and total suspended solids exceeded the recommended standards of FAO, while the river’s pH, electrical conductivity, and total dissolved solids concentrations were within permissible boundaries. Lead, cadmium, mercury, arsenic, and fluoride were present at concentrations lower than the recommended guidelines, whereas copper and cyanide were not discovered. However, iron concentrations exceeded the FAO guidelines. Escherichia coli concentrations in the Obeng ne Obeng were lower than the FAO irrigation standards but were higher in the Abuakwaa and Odaso. The Pearson correlation coefficient highlighted significant correlations between the physicochemical parameters. This paper concludes that unregulated mining activities may endanger vital water resources for irrigation, public health, food safety, ecosystems, and livelihoods. [ABSTRACT FROM AUTHOR]

This study evaluated the performance of a pre-treatment facility for SuDS water quality improvement designed to handle the stormwater runoff of a 200 m2 parking lot, using synthetic runoff and a statistical model of two levels of operation and four variables. The prototype consisted of an inlet ramp, sedimentation and filtration tank, and a recirculation system. The results showed that the removal efficiency of total suspended solids (TSS) and fats and oils concentration in the effluent are not affected by influent variations in flow rate, pH, temperature, TSS, fats and oils, and lead concentration. For the 32 measurements taken, an average of 82.9% (SD 3.6%) was obtained regarding total suspended solids removal. Lead retention possibilities were also observed. The TSS removal efficiencies were above 90.6% for precipitation events, generating peak flows of up to 5 L/s and a duration of 21 minutes, controlling the diffuse pollution peak. [ABSTRACT FROM AUTHOR]

Water quality of wetland ecosystems is a critical concern due to its implications on human health and aquatic life. This study was conducted to assess the spatial and temporal variation of water quality in Kotagala wetland to understand its impact on water safety for domestic uses and ecosystem health. Water samples were collected (n = 70) from six inlets and the wetland outlet from November 2021 to August 2022, and analyzed for pH, electrical conductivity (EC), salinity, total dissolved solids (TDS), total suspended solids (TSS), nitrate, and phosphate. The pH, EC, and nitrate showed significant correlations. Spatial clustering divided the monitoring sites into two clusters, as areas of higher and lower pollution levels. Discriminant analysis highlighted the significance of EC, pH, and nitrate concentrations in differentiating these clusters. Principal According to principal component analysis (PCA) 88.8% of the total variance of spatial variation in water quality was explained by the first two components. Temporal clustering following seasonal variations revealed the influence of rainfall pattern on water quality. EC, TDS, TSS, and nitrate concentrations emerged as the most important factors in this temporal categorization. In PCA, 76.8% of the total variance of temporal variation in water quality was explained by the first two components. Findings highlight the urgent need for sustainable strategies and policies to mitigate the impacts of human activities on wetland water quality, since water quality variations in the wetland was significantly impacted by direct human activities, and variations in rainfall trends in the area. [ABSTRACT FROM AUTHOR]

Reservoirs fulfil several societal needs, including water storage, energy production, flood control and recreation. However, the interruption of the river continuum may cause water quality declines that compromise water use. The surrounding landscape is a key driver of water quality variation in space and time, both across and within catchments. Therefore, understanding how landscape composition, structure and functioning influence reservoir water quality can help address management challenges. Here, we aim to investigate the current use and predictive capacity of landscape functioning indicators for reservoir water quality prediction. First, we carried out a literature review to investigate which landscape factors are most frequently studied as drivers of water quality in lentic systems. Then, we tested the predictive capacity of landscape functioning indicators in four reservoirs in Portugal using linear mixed models and multi‐model inference. The literature review shows that most studies assess the effects of landscape composition while landscape functioning is rarely included. Our test using four reservoirs suggests that landscape functioning indicators, namely greenness and brightness, can complement landscape composition and structure indicators, improving the capacity to predict total suspended solids, chlorophyll‐a, and total phosphorous. Landscape functioning indicators portrayed temporal variability in ecosystem dynamics that was not encompassed by landscape composition or structure indicators and may be relevant to predict specific water quality parameters. Our results show landscape functioning indicators can improve modelling of landscape contributions to water quality and thus have great potential to contribute to monitoring, modelling and forecast systems for water quality and ecological status. [ABSTRACT FROM AUTHOR]

This study highlights the importance of managing fishpond effluent to minimize its impact on aquatic environments. Fish effluents are a major concern worldwide in aquatic environments. It also provides information on the impacts of effluents on the water quality index of streams when released into aquatic environments. Streams and fishponds were sampled bimonthly for two annual cycles, covering different sampling stations both upstream and downstream of the fishpond effluents at 50-m intervals. Water quality parameters associated with in situ conditions were determined in the field. In the laboratory, other physicochemical parameters were determined via proper standard protocols. The results of the study revealed that water quality parameters such as turbidity, total suspended solids, total solids, conductivity, total dissolved solids, dissolved oxygen, biological oxygen demand and organic matter recorded in water samples collected from 50 m upstream at the point of effluent discharge were significantly (p < 0.05) different from those recorded at other sampling stations. The WQI value of the discharge point was higher than the WQI recorded in both the upstream and downstream sections of the stream. The findings of this study showed that the point of discharge of fishpond effluents is particularly concerning for the receiving stream compared with other sampling points. This localized area has experienced marked deterioration in water quality, posing significant threats to the health and biodiversity of aquatic ecosystems. The effluent's impact, though slight when dispersed in the receiving waterbody, underscores the necessity for adequate management practices to mitigate its adverse effects. Effective strategies, including regular monitoring, effluent treatment, and sustainable pond management, are imperative to ensure the long-term health and resilience of the aquatic environment. [ABSTRACT FROM AUTHOR]

The application of remote sensing technology for water quality monitoring has attracted much attention recently. Remote sensing inversion in coastal waters with complex hydrodynamics for non-optically active parameters such as total nitrogen (TN) and total phosphorus (TP) remains a challenge. Existing studies build the relationships between remote sensing spectral data and TN/TP directly or indirectly via the mediation of optically active parameters (e.g., total suspended solids). Such models are often prone to overfitting, performing well with the training set but underperforming with the testing set, even though both datasets are from the same region. Using the Hong Kong coastal region as a case study, we address this issue by incorporating spatial covariates such as hydrometeorological and locational variables as additional input features for machine learning-based inversion models. The proposed model effectively alleviates overfitting while maintaining a decent level of accuracy (R2 exceeding 0.7) during the training, validation and testing steps. The gap between model R2 values in training and testing sets is controlled within 7%. A bootstrap uncertainty analysis shows significantly improved model performance as compared to the model with only remote sensing inputs. We further employ the Shapely Additive Explanations (SHAP) analysis to explore each input's contribution to the model prediction, verifying the important role of hydrometeorological and locational variables. Our results provide a new perspective for the development of remote sensing inversion models for TN and TP in similar coastal waters. [ABSTRACT FROM AUTHOR]

Improved freshwater resource management requires the implementation of widespread, effective, and timely water quality monitoring. Conventional monitoring methods are often inhibited by financial, infrastructural, and human capacity limitations, especially in developing regions. This study aimed to validate the citizen‐scientist‐operated transparency or clarity tube (hereafter "clarity tube") for measuring water clarity as a proxy for total suspended solids (TSS) concentration, a critical quality metric in river systems and wastewater treatment works (WWTW) effluent in Southern Africa. Clarity tubes provided a relatively accurate and precise proxy for TSS in riverine lotic systems and WWTW effluent, revealing significant inverse log‐linear relationships between clarity and TSS with r2 = 0.715 and 0.503, respectively. We demonstrate that clarity‐derived estimates of TSS concentration (TSScde) can be used to estimate WWTW compliance with WWTW effluent TSS concentration regulations. The measurements can then be used to engage with WWTW management, potentially affecting WWTW performance. Overall, these findings demonstrate the usefulness of clarity tubes as low‐cost, accessible, and easy‐to‐use citizen science tools for high spatial and temporal resolution water quality monitoring, not only in rivers in Southern Africa but also in WWTW effluent for estimating compliance, with strong global relevance to the sustainable development goals (SDGs). Integr Environ Assess Manag 2024;20:1463–1472. © 2024 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). Key Points: Clarity tubes provide a relatively accurate and precise proxy for total suspended solids (TSS) in riverine lotic systems and wastewater treatment works (WWTW) effluent, revealing significant inverse log‐linear relationships between clarity and TSS.Clarity‐derived estimates of TSS concentration (TSScde) can be used to estimate WWTW compliance with WWTW effluent TSS concentration regulations, which can then be used to engage with WWTW management, potentially affecting WWTW performance.These findings demonstrate the usefulness of clarity tubes as low‐cost, accessible, and easy‐to‐use citizen science tools for high spatial and temporal resolution water quality monitoring in rivers in Southern Africa and in WWTW effluent for estimating compliance.Using clarity tubes for river and WWTW monitoring is a decisive step toward achieving significant progress in meeting sustainable development goal (SDG) 6 for ensuring safe access to water and sanitation for all, specifically SDG 6.3.2 and SDG 6b, by involving communities in water and sanitation monitoring and management. [ABSTRACT FROM AUTHOR]

East African lakes support the food and water security of millions of people. Yet, a lack of continuous long-term water quality data for these waterbodies impedes their sustainable management. While satellite-based water quality retrieval methods have been developed for lakes globally, African lakes are typically underrepresented in training data, limiting the applicability of existing methods to the region. Hence, this study aimed to (1) assess the accuracy of existing and newly developed water quality band algorithms for East African lakes and (2) make satellite-derived water quality information easily accessible through a Google Earth Engine application (app), named LAndsat water QUality retrieval tool for east African lakes (LAQUA). We collated a dataset of existing and newly collected in situ surface water quality samples from seven lakes to develop and test Landsat water quality retrieval models. Twenty-one published algorithms were evaluated and compared with newly developed linear and quadratic regression models, to determine the most suitable Landsat band algorithms for chlorophyll-a, total suspended solids (TSS), and Secchi disk depth (SDD) for East African lakes. The three-band algorithm, parameterised using data for East African lakes, proved the most suitable for chlorophyll-a retrieval (R2 = 0.717, p < 0.001, RMSE = 22.917 μg/L), a novel index developed in this study, the Modified Suspended Matter Index (MSMI), was the most accurate for TSS retrieval (R2 = 0.822, p < 0.001, RMSE = 9.006 mg/L), and an existing global model was the most accurate for SDD estimation (R2 = 0.933, p < 0.001, RMSE = 0.073 m). The LAQUA app we developed provides easy access to the best performing retrieval models, facilitating the use of water quality information for management and evidence-informed policy making for East African lakes. [ABSTRACT FROM AUTHOR]

Dams and artificial reservoirs can significantly alter the dynamics of sediment transport in a watercourse. Therefore, the main objective of this study is to assess the influence of the Pandeiros Small Hydroelectric Plant reservoir on sediment transport in the Pandeiros River. The study also aims to characterize the sediment composition and assess the correlation between total and suspended solids with turbidity, flow, and precipitation variables. The study was carried out in the Pandeiros River basin, Brazil, between May 2019 and January 2023. The following variables were analyzed: flow, turbidity, precipitation, total solids (fixed and volatile), and suspended solids (fixed and volatile). The results showed that, under the conditions observed during the study, the reservoir did not affect the concentration and composition of the sediments. It was found that the solids transported by the Pandeiros River are mostly composed of inorganic material. A positive correlation was observed between the variables, which was stronger when correlated with suspended solids. The correlation analysis indicated that precipitation is one of the main factors related to sediment transport in the Pandeiros River. In conclusion, the reservoir did not significantly affect the sediment concentration in the Pandeiros River. Highlights: The Pandeiros Small Hydroelectric Plant Reservoir did not affect sediment transport. Solids are mostly composed of inorganic material. The reservoir did not significantly influence the sediment concentration and composition. Precipitation was one of the main factors associated with sediment transport. [ABSTRACT FROM AUTHOR]

The Kereh River in Penang, Malaysia, has faced severe pollution for over 40 years due to untreated wastewater from swine farms in Kampung Selamat, discharged via stormwater drains. Despite official claims that all 77 swine farms treat their wastewater to meet regulatory standards, local non‐governmental organizations and villagers have challenged this, though their concerns lack scientific backing. This study evaluates the river's water quality by analyzing samples from upstream (US), midstream (MS), and downstream (DS), and from Parit Cina‐Parit Besar, a conduit for untreated swine wastewater. Fourteen parameters were measured against Malaysia's National Water Quality Standards (NWQS). Significant differences were found in six parameters: ammonium nitrogen (AN), biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), total suspended solids (TSS), and oil and grease (OG). While Dunn's post hoc pairwise comparison showed no significant differences among river segments, mean values indicated increased pollution downstream, particularly after the convergence with untreated swine wastewater. River classification worsened, with water quality index dropping from 69.88 ± 11.37 score (Class III) US to 38.49 ± 12.74 and 50.44 ± 3.14 scores (Class IV) MS and downstream, respectively. A significant positive correlation between E. coli and AN (r = 0.71, p < 0.01) suggests a common point source pollutant, particularly the untreated swine wastewater. The river exhibits low oxygen levels and high organic matter and nutrient concentrations, especially MS and downstream, highlighting substantial ecological and public health risks. Effective enforcement of waste treatment regulations and enhanced monitoring are crucial for mitigating pollution and restoring the river's ecosystem. Collaboration between authorities and pig farmers is essential to improve water quality and maintain the river's ecological balance. Practitioner points: Severe Kereh River pollution: Untreated swine wastewater from Kampung Selamat pig farms, primarily via Parit Cina‐Parit Besar, has degraded the river for over 40 years.Regulatory non‐compliance: Despite official claims, untreated swine wastewater continues to pollute the river, challenging regulatory standards.Significant pollution indicators: Elevated levels of AN, BOD, COD, DO, TSS, OG, and E. coli signal severe pollution midstream and downstream.Water quality index drop: WQI scores classify midstream and downstream sections as polluted, indicating worsening conditions downstream.Urgent need for action: Enforcing regulations, improving wastewater treatment, and relocating pig farms are crucial for restoring the Kereh River. [ABSTRACT FROM AUTHOR]

River ecosystems in Central Asia face significant stress from environmental changes and pollution. This study assesses temporal and spatial variations in water quality parameters within the Zarafshan River Basin using retrospective data and field measurements. Water quality indicators, including electrical conductivity (EC), total suspended solids (TSS), ammonium nitrogen (N‐NH4), nitrite nitrogen (N‐NO2), nitrate nitrogen (N‐NO3), temperature (T), chemical oxygen demand (COD), dissolved oxygen (DO), and discharge, were analyzed using the Pearson's correlation coefficient and ANOVA, with the Mann–Kendall (MK) test detecting trends over time. Obtained results indicate significant seasonal effects with elevated TSS during summer, increasing sediment load and changing aquatic habitats. The strong inverse correlation (–0.89) between DO and N‐NH4 signifies ecological challenges particularly in low DO concentrations during summer (3.25 mg L–1). Long‐term analysis identifies Navoiazot chemical factory as a major pollution hotspot. Spatial analyses based on extended sampling have revealed the Siab and Dargom canals and Samarkand City as major pollution sources of elevated N‐NO2 and COD, respectively. Trends at various gauging stations (MK‐test) show increasing EC (τ = 0.72) and N‐NH4 (τ = 0.46) levels, with decreasing TSS, N‐NO3, T, and COD levels over time. Recommendations include targeted measures to reduce pollution at the Navoiazot factory and downstream, introducing sustainable agriculture practices, increasing public awareness for environmental conservation, and improving urban wastewater treatment to meet water quality requirements for different users. [ABSTRACT FROM AUTHOR]

Given the use of machine learning-based tools for monitoring the Water Quality Indicators (WQIs) over lakes and coastal waters, understanding the properties of such models, including the uncertainties inherent in their predictions is essential. This has led to the development of two probabilistic NN-algorithms: Mixture Density Network (MDN) and Bayesian Neural Network via Monte Carlo Dropout (BNN-MCD). These NNs are complex, featuring thousands of trainable parameters and modifiable hyper-parameters, and have been independently trained and tested. The model uncertainty metric captures the uncertainty present in each prediction based on the properties of the model--namely, the model architecture and the training data distribution. We conduct an analysis of MDN and BNN-MCD under near-identical conditions of model architecture, training, and test sets, etc., to retrieve the concentration of chlorophyll-a pigments (Chl a), total suspended solids (TSS), and the absorption by colored dissolved organic matter at 440 nm (acdom (440)). The spectral resolutions considered correspond to the Hyperspectral Imager for the Coastal Ocean (HICO), PRecursore IperSpettrale della Missione Applicativa (PRISMA), Ocean Colour and Land Imager (OLCI), and MultiSpectral Instrument (MSI). The model performances are tested in terms of both predictive residuals and predictive uncertainty metric quality. We also compared the simultaneous WQI retrievals against a single-parameter retrieval framework (for Chla). Ultimately, the models' real-world applicability was investigated using a MSI satellite-matchup dataset (N - 3, 053) of Chla and TSS. Experiments show that both models exhibit comparable estimation performance. Specifically, the median symmetric accuracy (MdSA) on the test set for the different parameters in both algorithms range from 30% to 60%. The uncertainty estimates, on the other hand, differ strongly. MDN's uncertainty estimate is ~50%, encompassing estimation residuals for 75% of test samples, whereas BNN-MCD's average uncertainty estimate is ~25%, encompassing the residuals for 50% of samples. Our analysis also revealed that simultaneous estimation results in improvements in both predictive performance and uncertainty metric quality. Interestingly, the trends mentioned above hold across different sensor resolutions, as well as experimental regimes. This disparity calls for additional research to determine whether such trends in model uncertainty are inherent to specific models or can be more broadly generalized across different algorithms and sensor setups. [ABSTRACT FROM AUTHOR]

This study aimed to derive major pollutants for standard watersheds with relatively high pollution levels and identify their trends. Hence, the water quality index (WQI) and multivariate statistical techniques were used to analyze the water quality evaluation of standard watershed during the total maximum daily load (TMDL) policy period implemented since 2004. The WQI was calculated for 41 standard watersheds, divided into 14 main streams and 27 tributaries. Consequently, in the main stream, WQI decreased as it moved downstream after the MS5 site. In the tributary, WQI values were found to be low at TS11, TS15, TS16, and TS17 sites. However, the Mann–Kendall test results indicated that the overall WQI value was increasing, suggesting that the water quality of the study basin was improving as the TMDL policy phase progressed. Principal component analysis of the group with relatively low WQI among the standard watersheds revealed that water temperature, dissolved oxygen, total phosphorus, chemical oxygen demand, biochemical oxygen demand, and electrical conductivity were the main variables in the main stream cluster. In the tributary stream cluster, total phosphorus, dissolved oxygen, total suspended solids, total nitrogen, and electrical conductivity showed high loading values. This study proposed a series of methods to provide the basic data required for watershed management through detailed water quality assessment methods, statistical techniques for deriving major pollutants, and trend analysis of water quality evaluation. [ABSTRACT FROM AUTHOR]

The growing processes of urban expansion have led to changes in the biochemical and physical properties of the hydrological systems in watersheds, not only by altering the hydrological conditions of the territory, but also by introducing pollutants into water bodies. Thus, diffuse pollution from stormwater runoff is considered one of the main causes of water quality degradation in receiving waters in urban areas, especially in rainy regions such as the South American tropics, where urban development and management processes are generally poorly planned. This article presents the results of an evaluation of the relationship between land use and runoff water quality, taking into account different rainfall characteristics. Sampling was carried out in Medellín, Colombia, in areas with different land uses. Basic water quality parameters and some sources of urban pollution were studied. The results showed that parameters such as total suspended solids have a high variability, especially in the residential area, which makes it difficult to control the activities carried out there. The highest levels of pollution were found in the industrial area, where the presence of covers with very low or no permeability and the increase in anthropic activity cause a strong alteration in the quality of runoff water. These results open the door to question the impact of land use on the chemical composition of rainwater and promote a better understanding of surface runoff water pollution processes, thus providing a complete vision of the interactions in an urban ecosystem, establishing a key tool for water management in urban watersheds. [ABSTRACT FROM AUTHOR]

Industries generate hazardous dye wastewater, posing significant threats to public health and the environment. Removing dyes before discharge is crucial. The ongoing study primarily focused on synthesizing, applying, and understanding the mechanism of green nano-biochar composites. These composites, including zinc oxide/biochar, copper oxide/biochar, magnesium oxide/biochar, and manganese oxide/biochar, are designed to effectively remove Actas Pink-2B (Direct Red-31) in conjunction with constructed wetlands. Constructed wetland maintained pH 6.0–7.9. At the 10th week, the copper oxide/biochar treatment demonstrated the highest removal efficiency of total suspended solids (72%), dissolved oxygen (7.2 mg/L), and total dissolved solids (79.90%), followed by other biochar composites. The maximum removal efficiency for chemical oxygen demand (COD) and color was observed at a retention time of 60 days. The electrical conductivity also followed the same order, with a decrease observed up to the 8th week before becoming constant. A comprehensive statistical analysis was conducted, encompassing various techniques including variance analysis, regression analysis, correlation analysis, and principal component analysis. The rate of color and COD removal followed a second-order and first-order kinetics, respectively. A significant negative relationship was observed between dissolved oxygen and COD. The study indicates that employing biochar composites in constructed wetlands improves textile dye removal efficiency. The novelty of this study is the selection of Cymbopogon as a proper plant for phytoremediation of dye along with green metal oxide coated biochar. These were selected due to their good ability to remove organic pollutant. This study demonstrates the uptake and degradation processes of persistent dye in constructed wetland. [ABSTRACT FROM AUTHOR]

The study investigated the impacts of dietary supplementation with two probiotics, PondToss® and LactéolFort®, on the growth performance and biochemical indices of the whiteleg shrimp (Litopenaeus vannamei) in clear water (CW) and biofloc technology (BFT) systems. Six different treatments were applied: T1 (CW without probiotics, control), T2 (BFT without probiotics), T3 (BFT with PondToss® at 0.5g g-1), T4 (BFT with PondToss® at 1g kg-1), T5 (BFT with LactéolFort® at 0.5gkg-1), and T6 (BFT with LactéolFort® at 1g kg-1). Over 90 days, shrimps with initial average weights of 3.9 to 4.10g were fed the experimental diets to satiety twice daily. The study found that neither rearing system nor probiotic treatment affected water temperature or dissolved oxygen (DO) levels. However, the treatments significantly influenced water pH, dissolved nitrogen forms (ammonia, nitrite, and nitrate), total suspended solids (TSS), total alkalinity (as CaCO3), and floc volume (VF). Biofloc and probiotic-enriched diets stimulated growth in terms of weight gain, specific growth rate (SGR), and survival rate. In biofloc conditions, shrimps fed with probiotics showed an increased feed intake and a better feed and protein utilization. Biochemical indices such as albumin, total protein, and globulin levels varied significantly among the groups, with the control group (T1) recording the lowest survival rate (66.89%), while the BFT and probiotic-enriched groups had higher survival rates, ranging from 87.35 (T6) to 90.21% (T2). The findings suggest that probioticsupplemented diets in BFT systems improve water quality, boost shrimp growth, enhance nutrient utilization, and positively affect biochemical characteristics. Thus, combining probiotics with biofloc technology appears to be a promising strategy for enhancing shrimp performance. [ABSTRACT FROM AUTHOR]

The quantity and quality of surface water are inherently connected yet are overwhelmingly studied separately in the field of remote sensing. Remotely observable water quantity (e.g., water extent, water elevation, lake/reservoir volume, and river discharge) and water quality (e.g., color, turbidity, total suspended solids, chlorophyll a, colored dissolved organic matter, and temperature) parameters of inland waterbodies interact through a series of hydrological and biogeochemical processes. In this review, we analyzed trends in remote sensing publications to understand the prevalence of studies on the quantity versus quality of open‐surface inland waterbodies (rivers, streams, lakes, and reservoirs) as well as identified opportunities for integrating both water quality and quantity sensing in future work. Our bibliometric analysis found that despite the increasing number of publications using remote sensing for inland waterbodies, few studies to date have used remote sensing tools or approaches to simultaneously study water quantity and quality. Ultimately, by providing insights into potential integration of the water quality and quantity studies, we aim to identify a pathway to advance the understanding of inland water dynamics and freshwater resources through remote sensing. This article is categorized under:Water and Life > MethodsScience of Water > Water QualityWater and Life > Nature of Freshwater EcosystemsScience of Water > Methods [ABSTRACT FROM AUTHOR]

Rudrasagar Lake, a vital habitat for diverse flora and fauna, supports over 2000 households to sustain their daily livelihoods. The current study attempts to examine the impact of human activities on spatio-temporal variation in the water quality of the study area. The study integrates extensive field surveys, sample processing, and statistical analysis to assess the recent status of wetland health. Latin Square Matrix (LSM) was employed to select the sampling sites while the Inverse Distance Weighting (IDW) interpolation technique was used for spatial variation mapping. Modified Weighted Arithmetic Water Quality Index (MWAWQI) and Comprehensive Pollution Index (CPI) were utilized for assessing seasonal variation water quality and pollution loads, respectively. The results showed that dissolved oxygen (DO) was strongly influenced by the tributaries, and recreational activities have substantially influenced the highest concentrations of biochemical oxygen demand (BOD), and total suspended solids (TSS). The central portion of the lake is particularly susceptible to pollution from extensive fishing and recreational activities while peripheral sites are strongly influenced by agricultural run-offs, seepages from brick industries, and municipal wastes characterized by high concentrations of pH, total hardness (TH), oxidation–reduction potential (ORP). The findings reveal remarkable spatio-temporal fluctuations and highlight the areas within the lake susceptible to anthropogenic activities. The study proposed a sustainable management model to ameliorate anthropogenic threats. Moreover, the study contributes to the scientific understanding of the challenges and ensures the long-term viability of wetland health as a vital ecological and socio-economic resource. [ABSTRACT FROM AUTHOR]

Extensive hydrologic and water quality modeling within a watershed benefits from long-term flow and nutrient data sets for appropriate model calibration and validation. However, due to a lack of local water quality data, simpler water quality modeling techniques are generally adopted. In this study, the monitoring sites were established at two different locations to collect hydraulic data for the hydraulic calibration and validation of the model. In addition, water quality samples were collected at eight monitoring sites and analyzed in the lab for various parameters for calibration. This includes total suspended solids (TSS), soluble phosphorus, five-day biochemical oxygen demand (BOD5), and dissolved oxygen (DO). The Personal Computer Storm Water Management Model (PCSWMM) 7.6 software was used to simulate all the pollutant loads using event mean concentrations (EMCs). The performance of the model for streamflow calibration at the two USGS gauging stations was satisfactory, with Nash–Sutcliffe Efficiency (NSE) values ranging from 0.51 to 0.54 and coefficients of determination (R2) ranging from 0.71 to 0.72. The model was also validated with the help of historical flow data with NSE values ranging from 0.5 to 0.79, and R2 values ranging from 0.6 to 0.95. The hydraulic calibration also showed acceptable results with reasonable NSE and R2 values. The water quality data recorded at the monitoring stations were then compared with the simulated water quality modeling results. The model reasonably simulated the water quality, which was evaluated through visual inspection using a scatter plot. Our analysis showed that the upstream tributaries, particularly from agricultural areas, were contributing more pollutants than the downstream tributaries. Overall, this study demonstrates that the PCSWMM, which was typically used for modeling urban watersheds, could also be used for modeling larger mixed land use watersheds with reasonable accuracy. [ABSTRACT FROM AUTHOR]

The climate changes impact the surface water quality fed by the glaciers of high altitude throughout the world. Consistent increase in water pollution is observed mainly by rapid industrialization, extreme use of fertilizers to fulfill the ever-growing food demand, urbanization, and other anthropogenic activities. River Mandakini in Kedarnath Valley has not been scientifically studied till date in a composite manner. Hence, we collected water samples from Chandrapuri, Agastyamuni, and Tilwara in seasons such as summer, rainy, and winter. Various water quality parameters like temperature, pH, DO (dissolved oxygen), BOD (biochemical oxygen demand), COD (chemical oxygen demand), TDS (total dissolved solids) and TSS (total suspended solids) of all the samples collected were studied. The results of all these physicochemical parameters of river water have shown a considerable decrease compared with the standard values of BIS. The deteriorated water quality of the river poses potential health hazards to people using this water for drinking purposes and aquatic beings residing in the Ganga River. The findings of the present study reflect an overall decline in the water quality of the river and warn of its uses to human beings and the biotic community of the Ganga River. [ABSTRACT FROM AUTHOR]

Predicting river water quality in the Special Region of Yogyakarta (DIY) is crucial. In this research, we modeled a river water quality prediction system using the artificial neural network (ANN) backpropagation method. Backpropagation is one of the developments of the multilayer perceptron (MLP) network, which can reduce the level of prediction error by adjusting the weights based on the difference in output and the desired target. Water quality parameters included biochemical oxygen demand (BOD), chemical oxygen demand (COD), total suspended solids (TSS), dissolved oxygen (DO), total phosphate, fecal coliforms, and total coliforms. The research object was the upstream, downstream, and middle parts of the Oya River. The data source was secondary data from the DIY Environment and Forestry Service. Data were in the form of time series data for 2013-2023. Descriptive data results showed that the water quality of the Oya River in 2020-2023 was better than in previous years. However, increasing community and industrial activities can reduce water quality. This was concluded based on the prediction results of the ANN backpropagation method with a hidden layer number of 4. The prediction results for period 3 in 2023 and period 1 in 2024 are that 1) the concentrations of BOD, fecal coli, and total coli will increase and exceed quality standards, 2) COD and TSS concentrations will increase but will still be below quality standards, 3) DO and total phosphate concentrations will remain constant and still on the threshold of quality standards. The possibility of several water quality parameters increasing above the quality standards remains, so the potential for contamination of the Oya River is still high. Therefore, early prevention of river water pollution is necessary. [ABSTRACT FROM AUTHOR]

The present study was conducted to evaluate the bioflocculant chitosan and its nano-conjugated form in biofloc production and to evaluate the growth performance of genetically improved farmed tilapia (GIFT) in an insitu biofloc system. A completely randomised design (CRD) was used to evaluate the growth performance of GIFT in insitu biofloc over a 75-day period. The trial was conducted with biofloc control (T1), 30 ppm chitosan (T2) and 30 ppm nano-chitosan (T3) in triplicate. The water quality parameters were maintained in the optimum range for biofloc production. The highest value for flocculation activity, total suspended solids, total dissolved solids and total solids other than floc volume was observed in T3 followed by T2 and T1. The result of this study showed that there was a significant difference (p < 0.05) between treatments in terms of specific growth rate (SGR), weight gain (%WG), feed conversion ratio (FCR), feed efficiency ratio (FER) and daily increment (DI). Good growth performance of fish was observed in biofloc produced with nano-chitosan in terms of average body weight (g) (24.74 ± 2.58), SGR (%/day) (3.56 ± 0.094), PWG (%) (1546.27 ± 143.42), lowest FCR (1.421 ± 0.029), FER (0.62 ± 0.011), PER (1.68 ± 0.03) and DI (g day−1) (0.21 ± 0.014). The highest levels of amylase, lipase and protease activity and increased activity of antioxidant enzymes (SOD and CAT) were found in the T3 treatment compared to T2 and T1 treatments. This study demonstrated that biofloc developed with 30 ppm nano-chitosan could shorten the production time of biofloc, maintain the water quality of the biofloc system and improve the growth of GIFT tilapia reared in an insitu biofloc system with inland saline groundwater. [ABSTRACT FROM AUTHOR]

This study was conducted to evaluate surface water quality using pollution indices including the organic pollution index (OPI), comprehensive pollution index (CPI), and water quality index (WQI), cluster analysis (CA), with the support of one-way analysis of variance (One-way ANOVA), and principal component analysis (PCA). Water quality data at 42 locations, with 22 water quality parameters including temperature, pH, turbidity, salinity, chloride, total dissolved solids, electrical conductivity, sulfate, dissolved oxygen, total suspended solids, biological oxygen demand, chemical oxygen demand, nitrite, nitrate, ammonium, orthophosphate, coliform, E. coli, arsenic, cadmium, lead, and copper, were used for the evaluation. The results showed that all the pollution indices fluctuated spatially and temporally. The OPI index ranged from slight organic pollution to heavy organic pollution, and the OPI values in February and April were higher than those in other months. OPI values were classified as moderate with 54.76% of the locations and heavily polluted with 45.24%. Assessment based on the CPI revealed that 16.7% and 83.3% of locations were classified as moderately contaminated and heavily contaminated, respectively. The WQI classified 45% of the locations as poor and 55% of the locations as having average water quality. In particular, the water quality in August, October, and December was better than that in other months. PCA results showed that eight polluting sources were responsible for 77.1% of the water quality variation. The main surface water polluting sources could be natural sources (riverbank erosion, rainwater runoff), wastewater (domestic, agricultural, and industrial), water discharge from the national park, and livestock areas. Local environmental management agencies need to have appropriate solutions to improve water quality. Future research should focus on the contribution sources to surface water degradation. [ABSTRACT FROM AUTHOR]

Rainwater runoff samples from a range of roofing materials were temporally collected from 19 small-scale roof structures and two commercial buildings through simulated and actual storm events, and the concentrations of polycyclic aromatic hydrocarbons (PAHs), phosphorus flame retardants (PFLs), and pyrethroid insecticides and other water quality parameters were analyzed. In Part I of this research, the concentrations of these contaminants in roof runoff and soils receiving runoff from a range of roofing materials were evaluated. In Part II, recommendations have been developed for a first-flush exclusion to improve the quality of water harvesting for nonpotable uses. Recommendations focus on a first-flush diversion based on mass removals of total suspended solids (TSS) and PAHs linked to conductivity measurements throughout a storm event. Additionally, an upper-confidence limit (UCL) was constructed to determine the minimum diversion required to obtain 50, 75, 90, and 95% mass removal of TSS and PAH contaminants. The majority of TSS were produced during the initial 1.2 mm of runoff. Likewise, the majority of PAHs were removed during the initial 1.2 mm of runoff, except for the asphalt shingle roofs, where high PAHs were observed after 6 mm of runoff. The Texas Water Development Board (TWDB)-recommended first-flush diversion of one gallon for every 100 square feet of rooftop was not always adequate for removing 50% of TSS and PAHs from the roofs. Rainwater runoff conductivity decreased drastically between 1.2 to 2.4 mm of rainwater runoff. Diverting the first flush based on conductivity has the potential to also divert the majority of TSS and PAHs in roof runoff. [ABSTRACT FROM AUTHOR]

Rainfall runoff may be captured and stored for later use, but the quality of this water can be detrimental in some uses without the use of appropriately designed first-flush diverters. The rainfall runoff water quality was measured on nineteen new small-scale and two aged commercial roofs located near high traffic highways. Roof coverings included asphalt shingles, sheet metal, clay tiles, and tar and gravel. Runoff samples were evaluated for polycyclic aromatic hydrocarbons (PAHs), phosphorus flame retardants (PFRs), and pyrethroid insecticides. Eighteen small-scale roofs were subjected to a range of simulated rainfall events, while natural runoff was sampled on the commercial roofs and one small-scale roof. Runoff was analyzed for pH, conductivity, turbidity, total suspended solids, boron, iron, copper, zinc, manganese, sodium adsorption ratio, nitrate-nitrogen, seventeen PAHs, tris(2-chloroethyl) phosphate, tris(1,3-dichloro-2-propyl)phosphate, bifenthrin, cypermethrin, and lambda-cyhalothrin. Samples from four natural storm events were also analyzed for total coliforms and Escherichia coli. In addition, soils below seventeen existing gutter downspouts were sampled to determine long-term pollutant accumulation. Atmospheric deposition was the main contributor of pollutants in the roof runoff. A majority of samples fell within the U.S. EPA guidelines for non-potable urban and agricultural water reuse. Trace levels of PAHs, PFRs, and insecticides were detected, but all detections were three orders of magnitude below the USGS health-based screening level benchmark concentrations. Results indicate that diverting the first flush, based on turbidity, total suspended solids, or conductivity, can improve the overall water quality and reduce the concentrations of PAHs in harvested rainwater. Downspout soil sampling showed potential for the long-term accumulation of PAHs at concentrations exceeding the minimum human-health risk-based screening levels at these high runoff-loading locations. [ABSTRACT FROM AUTHOR]

Exposed soils associated with active construction sites provide opportunities for erosion and sediment transport during storm events, introducing risks associated with excess sediment to downstream infrastructure and aquatic biota. A better understanding of the drivers of sediment transport in construction site runoff is needed to improve the design and performance of erosion and sediment control measures (ESCMs). Eleven monitoring locations on 3 active road construction sites in central Ohio were established to characterize runoff quality from points of concentrated flow during storm events. Grab samples were analyzed for total suspended solids (TSS), turbidity, and particle size distribution (PSD). Median TSS concentrations and turbidity levels across all samples were 626 mg/L (range 25–28,600 mg/L) and 759 NTU (range 22–33,000 NTU), respectively. The median PSD corresponded to a silty clay loam, mirroring the soil texture of much of Ohio's subsoils. TSS concentrations and turbidity were significantly positively correlated with the rainfall intensity 10 min prior to sample collection, suggesting that higher flow rates created greater shear stress on bare soil which resulted in more erosion. Conversely, rainfall duration was negatively correlated with particle size, indicating that prolonged moisture from rainfall promoted the dispersion of soil aggregates which mobilized smaller particles. Multivariable linear regression models revealed that higher rainfall intensities corresponded to higher turbidity values, while higher TSS concentrations were associated with higher rainfall intensities, depths, and durations. Results from this study highlight the importance of reducing raindrop impact and subsequent shear stress applied by concentrated flows through the use of ESCMs to limit sediment export from construction sites. [ABSTRACT FROM AUTHOR]

Dams are regarded as crucial pieces of structure that store water for irrigation and municipal uses. Given their vital role, the dam's water quality assessment is considered to be an important criterion and requires constant monitoring. In this research, we attempted to use two water quality indices (WQIs) methods to assess the water quality of the Keddara Dam, which is located on the Boudouaou River, Algeria, using eleven water quality parameters (temperature, pH, conductivity, turbidity, total suspended solids (TSS), full alkalimetric title (TAC), hydrometric title (TH), nitrite ions (NO2−), nitrate ions (NO3−), ammonium ions (NH4+), and phosphate ions (PO43−)) for data recorded from 29 December 2018 to 3 June 2021. Application of The Canadian Council of Ministers of the Environment (CCME) WQIs and the Weighted Arithmetic Method (WAM) indicated that the Keddara Dam's water quality parameters were within the WHO's permissible level, except for the conductivity and turbidity values. The results of the CCME WQI ranged from acceptable (81.92) to excellent (95.08) quality, whereas the WAM WQI ranged from 9.52 to 17.77, indicating excellent quality. This demonstrates that the Keddara Dam is appropriate for agriculture and municipal use. The water quality indices (WQIs) methods are recommended as valuable tools that allow both the public and decision-makers to comprehend and manage the water quality of any aquatic environment by providing flexibility in choosing variables. [ABSTRACT FROM AUTHOR]