Machine-learning-based models are used to predict dissolved oxygen (DO); however, acquiring continuous water quality data for input variables in harsh environments remains challenging. Herein, redox potential (ORP) determined by a thermo-treated flexible carbon fiber electrode was introduced as a single or preferential input variable for machine-learning-based DO prediction in a year-round eutrophic estuary. The novel ORP sensor was operated for 4 months, and DO was predicted from ORP and six water quality data sources using a long short-term memory (LSTM) neural network. ORP and DO concentration showed a linear correlation, but the first-order correlation slopes varied seasonally. The optimal LSTM hyperparameters were proposed, which depended on the prediction time step and predictor case. Simulation results showed higher seasonal DO dynamics reproduced using ORP alone (RMSE = 1.09) than that predicted using six other water quality parameters (RMSE = 1.32). In addition, ORP played a key role in DO prediction when combined with all water quality parameters (RMSE = 1.08). The feature importance of ORP as a predictor was evaluated from a random forest model. Overall, the highly selective redox sensor has a distinct response to DO concentration and offers a novel and cost-effective approach for monitoring or predicting DO in eutrophic waters. Full article

This paper presents results of an aquatic vegetation resource potential assessment. The study is aimed at assessing the perspective of biotechnological approaches to reducing the biogenic pollution of water bodies by the removal of aquatic vegetation. The article analyzes the dominant species of aquatic vegetation in the Curonian Lagoon, and their productivity and resource potential. It was established that the concentrations of protein and fat in the biomass of four dominant plants are extremely low, making it impossible to speak of their values in terms of biomass processing. Based on elemental composition, we can conclude that the biomass of Phragmites australis should have a high calorie content because it has a high carbon and hydrogen content (49.6% and 7.1%, respectively), resulting in a high energy value. Synchronous thermal analysis revealed that the maximum energy values of biomasses of Phragmites australis and Scirpus lacustris have a net calorific value of 12.62 and 12.55 MJ/kg, respectively. At the same time, the biomass of these plants has a low ash content (around 6.6–7.6%) and a low sulfur content (less than 0.41%). An analysis of the composition of aquatic vegetation biomass samples allowed us to establish that, given the permissible collection time (no earlier than September), the search for directions in the utilization of aquatic vegetation should focus on processing cellulose with the production of crystalline cellulose, biochar, or biofuel via anaerobic digestion. The removal of the excess biomass of aquatic vegetation (Phragmites australis) will allow the reduction of the nitrogen and phosphorus load in the water body by 140 kg/ha and 14 kg/ha, respectively. Full article

Identification of sources and transport pathways of heavy metals and major ions is crucial for effective water quality monitoring, particularly in large river systems. The Ganges river basin, the largest and the most populous river basin in India, remains poorly studied in this regard. We conducted a basin-level analysis of major ions, heavy metals, and stable isotopes of nitrate in the Ganges during the pre-monsoon season to constrain the sources and quantify the inorganic chemical composition of the river during its lean flow. Bedrock weathering, anthropogenic interferences, water contribution through tributaries, and surface water-groundwater interaction were identified as the major driver of metal and ion variability in the river. Heavy metals showed the highest concentrations in the upper section of the river, whereas ionic loads were the most variable in the middle. We find a significant impact of tributaries on the metal and ion concentrations of the Ganges in its lower reaches. Isotopic analysis of dissolved nitrate suggested synthetic fertilizers and industrial wastes as the main sources. We find that the otherwise clean waters of the Ganges can show high ionic/metallic concentrations at isolated stretches (As: up to 36 µg/L), suggesting frequent monitoring in the source region to maintain water quality. Except for water collected from the Yamuna and Kannauj in the middle stretch and the Alaknanda and Rishikesh in the upper stretch, the WQI showed acceptable water quality for the sampled stations. These findings provide an insight into the modifications of dissolved inorganic chemical loads and their sources in different sections of the basin, needed for mitigating site-specific pollution in the river, and a roadmap for evaluating chemical loads in other rivers of the world. Full article

(1) Background: Aquatic systems are important to the community and the environment, requiring careful assessment, including the monitoring of their waters. Cities are usually built close to aquatic systems, which serve as a source of water for the entire population. With the uncontrolled increase in cities, aquatic environments receive a great pollutant load. (2) Methods: In this context, the present study aimed to evaluate water contamination, evaluating multi-indicators, cytotoxicity and mutagenicity and conducting a multivariate analysis on the João Leite stream in central Brazil. (3) Results: It was demonstrated, by means of multi-indicators of water quality, that according to the CONAMA classification, current Brazilian legislation and the purpose of the João Leite stream, the water quality met some parameters (i.e., turbidity, dissolved oxygen, and bacteriological); however, in some samples, the quality was poor or very poor. Samples collected in the rainy season indicated cytotoxicity, probably due to pollutants dragged by the rain into the stream. Based on multivariate and association analysis, we suggest that the João Leite stream presents anthropogenic pollution. (4) Conclusions: This study provides data for the development of prevention, control and environmental management policies. In addition, we demonstrate that the use of multivariate statistical analyses can provide data on water pollution, its source of pollution and the association between pollutants. Full article

The research was carried out on the flow-through Lake Mielenko (7.8 ha; 1.9 m), which also acts as a stormwater receiver. In 2015, a disposal for road salts was created in the lake’s catchment area. As a result of the inflow of salt-contaminated stormwater, there was a significant increase in the concentration of calcium (57 mg Ca/L), chloride (220 mg Cl/L) and electrolytic conductivity (790 µS/cm). Increased calcium concentrations in lake waters changed their hardness from low to medium-hard. The ecological effect of the change in hydrochemical conditions in Lake Mielenko is the Potamogeton crispus that grows abundantly in this reservoir, which prefer calcium-rich water. The overall aesthetics of the lake have deteriorated significantly, and the availability of water for recreation has also been limited. Full article

Many measurements, tools, and approaches are used to identify and track the influence of human activities on the physicochemical status of streams. Commonly, chemical concentrations are utilized, but in some areas, such as downstream of coal mines, capacity indices such as specific conductivity have also been used to estimate exposure and risk. However, straightforward tools such as conductivity may not identify human influences in areas with saline groundwater inputs, diffuse exposure pathways, and few discharges of industrial wastewater. Researchers have further suggested in conductivity relative to alkalinity may also reveal human influences, but little has been done to evaluate the utility and necessity of this approach. Using data from 16 example sites in the Peace, Athabasca, and Slave Rivers in northern Alberta (but focusing on tributaries in Canada’s oil sands region) available from multiple regional, provincial, and national monitoring programs, we calculated residual conductivity and determined if it could identify the potential influence of human activity on streams in northern Alberta. To account for unequal sampling intervals within the compiled datasets, but also to include multiple covariates, we calculated residual conductivity using the Generalized Estimating Equation (GEE). The Pearson residuals of the GEEs were then plotted over time along with three smoothers (two locally weighted regressions and one General Additive Model) and a linear model to estimate temporal patterns remaining relative to known changes in human activity in the region or adjacent to the study locations. Although there are some inconsistencies in the results and large gaps in the data at some sites, many increases in residual conductivity correspond with known events in northern Alberta, including the potential influence of site preparation at oil sands mines, reductions in particulate emissions, mining, spills, petroleum coke combustion at one oil sands plant, and hydroelectric development in the Peace basin. Some differences in raw conductivity measurements over time were also indicated. Overall, these analyses suggest residual conductivity may identify broad influences of human activity and be a suitable tool for augmenting broad surveillance monitoring of water bodies alongside current approaches. However, some anomalous increases without apparent explanations were also observed suggesting changes in residual conductivity may also be well-suited for prompting additional and more detailed studies or analyses of existing data. Full article

The shutdown of drinking water treatment plants (DWTPs) at the Langat River Basin, Malaysia, which provides drinking water to almost one-third population in the basin, is very frequent, especially due to chemical pollution in the river. This study explored the pollution sources in the Langat River based on eight specific water intake points of the respective DWTPs to suggest an integrated river basin management (IRBM). Analysis of Al (250.26 ± 189.24 µg/L), As (1.65 ± 0.93 µg/L), Cd (1.22 ± 0.88 µg/L), Cr (0.47 ± 0.27 µg/L), and Pb (9.99 ± 5.38 µg/L) by ICP-MS following the Chelex^® 100 column resin ion exchange method found that the mean concentrations except Al were within the water quality standard of the Ministry of Health (MOH) as well as the Dept. of Environment (DOE) Malaysia. However, the determined water quality index based on physicochemical parameters (2005–2015) at the midstream of Langat River was Class III, which needs substantial treatment before drinking. The linear regression model of Al, As, Cd, and Pb suggests that water quality parameters are significantly influencing the increase or decrease in these metal concentrations. Moreover, the principal component analysis (PCA) and the hierarchical cluster analysis (HCA) also support the regression models that the sources of pollution are both natural and man-made activities, and these pollution sources can be clustered into two categories, i.e., upstream (category 1) and mid to downstream (category 2) in the Langat River. The degraded water quality in the midstream compared to up and downstream of the river is mainly due to human activities apart from the natural weathering of minerals. Therefore, the implementation of policies should be effective at the local level for pollution management, especially via the proactive leadership roles of local government for this transboundary Langat River to benefit from IRBM. Full article