In the present investigation, coagulation-flocculation and fenton process in conjunction with phytoremediation by water hyacinth (Eicchornia crassipes) were applied to treat the most frequently occurred contaminants in textile wastewater. The mean values of EC, TDS, turbidity, pH, DO, BOD, COD and TOC in the raw effluents were 2300 μSCm-1, 1260 mgL-1, 48.28 FTU, 10.5, 1.2 mgL-1, 265 mgL-1, 522 mgL-1 and 12.8 mgL-1, respectively whereas the average concentration of Cr, Pb, Mg, Cu, Ni and Zn was 0.86, 1.21, 10.97, 0.47, 2.85 and 0.52 mg/L, correspondingly which evidently indicated that the effluents were highly contaminated compared to Bangladeshi standard. The results demonstrated that the values of EC, TDS, turbidity, pH, BOD, COD and TOC reduced significantly compared to raw effluents by both coagulation-flocculation and fenton processes and meet the standards set by BDS-ECR except BOD and DO. After being treated the COD value reduced to 70 mg/L (86.56%) and 188 mg/L (63.985%) from its initial concentration by coagulation-flocculation and fenton process, respectively on the other hand TOC removal efficiency by coagulation- flocculation process was 97.8125%, significantly greater than fenton methods where removal efficiency was 63.9%. However, the BOD removal efficiency by both treatment processes was ~50% which was not satisfactory compared to local standard. Interestingly, the concentration of DO increased substantially by both coagulation-flocculation (1.2 to 4.4 mg/L) and fenton process (1.2 to 3.85 mg/L). In case of trace elements removal, the combination of coagulation-flocculation-water hyacinth and fenton-water hyacinth show promising results where the removal efficiency of coagulation-flocculation-water hyacinth and fenton-water hyacinth was 24%-76% and 17%-76.36%, respectively. Therefore, it can be concluded that coagulation-flocculation-water hyacinth combination is better than fenton-water hyacinth combination in terms of trace metals removal. Textile effluents treatment and management is considered as one of the most significant issues in Bangladesh herein based on the this study, combination of chemical and phytoremediation technologies could be a promising sustainable low cost alternative for Bangladesh’s textile industrial sector.

This work aims to assess the Water Quality Index (WQI) of the groundwater-based public drinking water supply system of Kamrup District (Rural) of Assam, India. For assessing WQI, water samples have been collected, both raw water and treated water, from seventy-eight public drinking water supply projects over the district for comprehensive physicochemical analysis. The WQI was calculated based on the weightage derived from the literature survey and based on the doctors’ weightage. The derived WQI showed that the water quality falls from poor to very poor quality. However, the concentration of the water quality parameters except Iron, Fluoride, and Manganese are within the permissible limit in all the water supply projects. It shows that the WQI calculated based on the weightage derived, as stated above, is not displaying the actual water quality of the supplied water. As such, a modified method is proposed to calculate the WQI of the supplied water considering the permissible limit of the parameters in deriving the weightage for the parameters. The WQI values calculated using the modified method falls in the range of good water quality to poor water quality and shows the true water quality of the supplied water. The statistical analysis of the water quality parameters and WQI shows that the WQI has a very high correlation with Manganese with a coefficient of correlation value of 0.86, followed by 0.4 with Chloride and 0.34 with Fluoride.

The Phromhot Canal is the only natural water source for consumption and agriculture the Sa Kaeo special economic zone, Thailand. At present, the Phromhot Canal is facing a serious problem with water quality. Our study carried out to analyze and assess the pollution carrying capacity of the natural water resource. The sampling sites were examined 7 stations cut across the downstream areas. All these stations were served as the control station to represent the actual condition of the Phromhot Canal. The results indicated that the water quality of the Phromhot Canal after flowing through the Aranyaprathet Municipality's wastewater treatment plant (AM's-WWTP) was severely contaminated. Effluents from the AM's-WWTP does not meet the effluent quality standard of the Ministry of Natural Resources and Environment, Thailand. In addition, it can flow into the water body up to 6,439.55 m3/day. The maximum amount of a pollutant (in terms of BOD loading) allowed to enter a water body of the Phromhot Canal should be ≤ 0.08 kgBOD/day (dry period) and 16.52 kgBOD/day (wet period). While the Phromhot Canal has to carry BOD loading up to 51.12 kgBOD/day. For this reason, the Phromhot Canal at after flowing through the WWTP was unable to the pollution carrying capacity. From the field survey, the AM's-WWTP is not suitable for wastewater treatment, which has a capacity of 923.93 m3/day. Therefore, it is necessary to strictly control the drainage of the wastewater from the Aranyaprathet Municipality's wastewater treatment system, both quantitative and geographic.

Numerous genetic markers for microbial source tracking (MST) have been evaluated by testing a panel of target and nontarget faecal samples. However, the performance of MST markers may vary between faecal and water samples, thereby resulting in inaccurate water quality assessment. In this study, a 30-day sampling study was conducted in an urban river impacted by human- and sewage-associated pollution to evaluate the performance of different human-associated markers in environmental water. Additionally, marker decay was assessed via a microcosms approach. Overall, Bacteroidales 16sRNA and crAssphage markers exhibited higher prevalence in the study area, and their detection frequencies exceeded 90%. In contrast, Bacteroidales protein markers exhibited poor detection frequencies compared to other markers, with the prevalence of Hum2 and Hum163 reaching only 63% and 84%, respectively. Regarding marker abundance, there was no significant difference in the detection concentrations between Bacteroidales 16sRNA and crAssphage markers (p > 0.05); however, the concentrations of Bacteroidales protein markers were nearly 1 order of magnitude lower than those of other MST markers. The microcosm experiments indicated that the decay rate of crAssphage markers was significantly lower than that of other bacterial target markers, which may improve their detectability when the pollution source is located far from the sampling site. Due to the observed differences in performance and decay patterns among Bacteroidales 16sRNA, crAssphage, and Bacteroidales protein markers, we recommend the simultaneous use of multiple markers from different target microorganisms to obtain a more comprehensive understanding of the pollution sources. This approach would also provide an accurate assessment of pollution levels and health risks.

Nitrogen in urban stormwater has been widely studied, and effective management of nitrogen pollution is critical for improving urban stormwater and receiving water quality. This requires an in-depth understanding of the transport process and source contribution to both dissolved and particulate nitrogen in stormwater from urban catchments. In this study, 123 stormwater runoff samples were collected from an urban catchment during different rainfall events. Dissolved and particulate nitrogen concentrations in roof runoff, road runoff, and sewer flow were analyzed. The concentration of dissolved nitrogen was higher in roof runoff than in road runoff and sewer flow. However, the concentration of particulate nitrogen was lower in roof runoff than in road runoff and sewer flow. Isotopic analysis and Bayesian mixing models showed that road runoff was the largest source contributor of both nitrate and particulate organic nitrogen (PON) in sewer flow discharged from the study catchment. In addition, road runoff contributed the majority of PON associated with coarse particles (>105 μm), whereas PON associated with fine particles (<105 μm) was primarily washed-off of sewer sediments. The results provided several suggestions for the management of nitrogen pollution in urban catchments. This study could help to fully understand the transport and sources of nitrogen pollution in urban stormwater and provide recommendations to the government for implementing appropriate stormwater management strategies to minimize stormwater pollution.

Excessive nutrient discharges have resulted in pervasive water pollution and aquatic eutrophication. China has made massive efforts to improve water quality since 2000. However, how long-term policy interventions govern external and internal fluxes as well as nitrogen (N) concentrations is not well known. Here we examined the historical N concentration change and its key drivers in eutrophic Lake Dianchi (southwest China) over the period 2002–2018, based on monthly observations of water quality and external N fluxes, local surveys of mitigation measures, and process-based model simulations of internal N fluxes. Our data indicated that N concentrations peaked at 3.0 mg L⁻¹ in 2007–2010 but afterwards declined down to 1.2 mg L⁻¹ in 2018. Compared with 2010, the decline in lake N concentrations was attributed to reduced riverine N inflow decreasing by 0.20 g N m⁻³ month⁻¹ and the water-sediment exchange flux decreasing by 0.07 g N m⁻³ month⁻¹ from 2010 to 2018. Adoptions of wastewater treatment, pollution interception, and transboundary water transfer dominated the changes in external and internal fluxes of N and thereby the decline of lake N concentrations. These findings underscore the priority of reducing external discharge for historical lake water quality improvement and the need of enhancing internal N removal for future lake ecosystem restoration.

Pollution of riverine ecosystems through the multidimensional impact of human footprints around the world poses a serious challenge. Research studies that communicate potential repercussions of landscape structure metrics on snowmelt riverine water quality particularly, in climatically fragile Himalayan watersheds are very scarce. Though, worldwide, grasping the influence of land-use practices on water quality (WQ) has received renewed attention yet, the relevance of spatial scale linked to landscape pattern is still elusive due to its heterogenic nature across diverse geomorphic regions. In this work, therefore, we tried to capture the insights on landscape-aquascape interface by juxtapositioning the impacts of landscape structure pattern on snowmelt stream WQ of the whole Jhelum River Basin (JRB) under three varying spatial scales viz., watershed scale, riparian corridor (1000 m wide) and reach buffer (500 m wide). The percentage of landscape pattern composition and configuration metrics in the JRB were computed in GIS utilizing Landsat-8 OLI/TIRS satellite image having 30 m resolution. To better explicate the influence of land-use metrics on riverine WQ with space and time, we used Redundancy analysis (RDA) and multilinear regression (MLR) modeling. MLR selected land-use structure metrics revealed the varied response of WQ parameters to multi-scale factors except for total faecal coliform bacteria (TC) which showed perpetual presence. The reach-scale explained slightly better (76%) variations in WQ than riparian (75%) and watershed (70%) scales. Likewise, across seasonal scale, autumn (75%), winter (83%), and summer (77%) captured the most WQ variation at catchment, riparian, and reach scales respectively. We observed impairing WQ linkages with agriculture, built-up and barren rocky areas across watersheds, besides, pastures in riparian buffer areas, and fragmentation of landscape patches at the reach scale. Due to little appearance of spatial scale differences, a multi scale perspective landscape planning is emphasized to ensure future sustainability of Kashmir Himalayan water resources.

Management of water-quality in a river ecosystem needs to be focused on susceptible regions to eutrophication based on proper measurements. The stress–response relationships between nutrients and primary productivity of phytoplankton allow the derivation of ecologically acceptable thresholds of stressors under field conditions. However, spatio-temporal variations in heterogeneous environmental conditions have hindered the development of locally applicable criteria. To address these issues, we utilized a combination of a geographically specialized artificial neural network (Geo-SOM, geo-self-organizing map) and linear mixed-effect models (LMMs). The model was applied to a 24-month dataset of 54 stations that spanned a wide spatial gradient in the Nakdong River basin. The Geo-SOM classified 1286 observations in the basin into 13 clusters that were regionally and seasonally distinct. Inclusion of the random effects of Geo-SOM clustering improved the performance of each LMM, which suggests that there were significant spatio-temporal variations in the Chla–stressor relationships. These variations arise owing to differences in background seasonality and the effects of local pollutant variables and land-use patterns. Among the 16 environmental variables, the major stressors for Chla were total phosphate (TP) as a nutrient and biological oxygen demand (BOD) as a non-nutrient according to the results of both Geo-SOM and LMM analyses. Based on LMMs with the random effect of the Geo-SOM clusters on the intercept and the slope, we can propose recommended thresholds for TP (18.5 μg L⁻¹) and BOD (1.6 mg L⁻¹) in the Nakdong River. The combined method of LMM and Geo-SOM will be useful in guiding appropriate local water-quality-management strategies and in the global development of large-scale nutrient criteria.

Agricultural activities often lead to nutrient enrichment and habitat modification in rivers, possibly altering macroinvertebrate assemblages and hence ecosystem functioning. For the sake of environmental management and conservation, therefore, assessing the impacts of agricultural activities becomes indispensable, especially when these activities are predicted to be intensified in the future. In this study, the plain river network in the Lake Chaohu Basin was chosen to examine how agricultural activities influence the functioning of rivers by assessing land use, water quality, habitat condition and macroinvertebrate assemblages, followed by calculating the macroinvertebrate-based multimetric index (MMI) to indicate overall ecosystem health of the rivers. We found that agricultural activities lowered the diversity of macroinvertebrates (e.g. total number of taxa and Simpson index) primarily due to elevated ammonium concentrations in water and reduced microhabitat types, thereby impairing the habitat integrity and nutrient cycling of rivers. The macroinvertebrate-based MMI was positively correlated with increasing habitat quality but negatively with increasing nutrient concentrations, suggesting its high reliability for indicating the impacts of agricultural activities, which was further substantiated by classification and regression tree (CART) analysis. We recommend analyzing macroinvertebrate assemblages using both multivariate and multimetric approaches to offer a more comprehensive evaluation of the impacts of agricultural activities on ecosystem health. Some environmental (CODMₙ, NH₄⁺-N and PO₄³⁻-P) and biological parameters (total number of taxa), however, can be used as good proxies for MMI, when time and resources for gathering information to develop MMI are limited.

The occurrence of veterinary antibiotics and hydro-chemical parameters in eleven natural springs in a livestock production area is evaluated, jointly with the characterization of their DOM fingerprint by Orbitrap HRMS. Tetracycline and sulfonamide antibiotics were ubiquitous in all sites, and they were detected at low ng L⁻¹ concentrations, except for doxycycline, that was present at μg L⁻¹ in one location. DOM analysis revealed that most molecular formulas were CHO compounds (49 %–68 %), with a remarkable percentage containing nitrogen and sulphur (16 %–23 % and 11 %–24 %, respectively). Major DOM components were phenolic and highly unsaturated compounds (~90 %), typical for soil-derived organic matter, while approximately 11 % were unsaturated aliphatic, suggesting that springs may be susceptible to anthropogenic contamination sources. Comparing the DOM fingerprint among sites, the spring showing the most different profile was the one with surface water interaction and characterized by having lower CHO and higher CHOS formulas and aliphatic compounds. Correlations between antibiotics and DOM showed that tetracyclines positively correlate with unsaturated oxygen-rich substances, while sulfonamides relate with aliphatic and unsaturated oxygen-poor compounds. This indicates that the fate of different antibiotics will be controlled by the type of DOM present in groundwater.