Seasonal variation in water quality of Anchar Lake was evaluated using multivariate statistical techniques- principal component analysis (PCA) and cluster analysis (CA). Water quality data collected during 4 seasons was analyzed for 13 parameters. ANOVA showed significant variation in pH (F3 = 10.86, P < 0.05), temperature (F3 = 65, P <0.05), Electrical conductivity (F3 = 32.72, P <0.05), Calcium (F3 = 36.84, P <0.05), Magnesium (F3 = 16.52, P <0.05), nitrate-nitrogenSeasonal variation in water quality of Anchar Lake has been evaluated, using two multivariate statistical techniques, namely Principal Component Analysis (PCA) and Cluster Analysis (CA). Water quality data, collected during four seasons, have been analyzed for 13 parameters and ANOVA has shown that pH (F3= 10.86, P < 0.05), temperature (F3 = 65, P < 0.05), electrical conductivity (F3= 32.72, P < 0.05), Calcium (F3= 36.84, P < 0.05), Magnesium (F3= 16.52, P < 0.05), nitrate-nitrogen (F3= 48.06, P < 0.05), ammonical nitrogen (F3 =198.75, P < 0.05), and dissolved oxygen (F3= 4.96, P < 0.05) varied by season, whereas the substantial variations of sodium (F2= 7.18, P <0.05), phosphate-phosphorous (F2= 25.31, P < 0.05), biological oxygen demand (F2= 11.02, P < 0.05), and chemical oxygen demand (F2=37.73, P < 0.05) were based on different sites. CA has grouped the three sampling sites throughout the four seasons into three clusters of similar water quality as relatively Less-Polluted (LP), Medium-Polluted (MP), and Highly-Polluted (HP). In addition, PCA has been applied on the extract to recognize the factors, responsible for water quality variations in four seasons of the year, resulting in four principal components for winter, summer, and autumn, five ones for spring, accounting for 79.58%, 89.07%, 83.34%, and 93.13% of total variance respectively. Thus the factors, responsible for water quality variation, are mainly related to domestic wastewaters, seasonal variation, agricultural runoff, and catchment geology. These results will help decision-makers better understand the influence of various factors on water quality and manage pollution/eutrophication adaptively in Anchar Lake.

The present study has been conducted to assess the surface water quality of Halda River from September 2015 to March 2016. DO, BOD5, COD, pH, EC, Chloride, Alkalinity, and Hardness concentrations in water samples have been found to range within 0.93-5.15 mg/L, 30-545 mg/L, 43-983 mg/L, 6.3-7.3, 110-524 uS/cm, 12-56 mg/L, 35-67 mg/L, and 38-121 mg/L, respectively. Multivariate statistical analyses, such as Principal Component Analysis (PCA) as well as Correlation Matrix (CM) have revealed significant anthropogenic pollutant intrusions in water. Cluster Analysis (CA) has indicated decent results of rendering three different groups of resemblance between the two sampling sites, reflecting the different water quality indicators of the river system. A very strong positive linear relation has been found between COD and BOD (1.000), hardness and EC (0.993), pH and DO (0.979), hardness and COD (0.929), hardness and BOD (0.924), EC and COD (0.922), and EC and BOD (0.916) at a significance level of 0.01, proving their common origin entirely from industrial effluents, municipal wastes, and agricultural activities. River Pollution Index (RPI) has indicated that the water from rivers at Kalurghat and Modhunaghat varied from low to high pollution, which is due to the former area's being mostly industrial zone with some domestic sewage, while the latter underwent less industrial activities. On the contrary, lots of agricultural activities have been found in Modhunaghat. Use of river water can pose serious problems to human health and aquatic ecosystem via biological food chain. The present research suggests special preference for proper management of the river with eco-friendly automation along with development of the country's sustainable economic.

One of the main aims of water resource planners and managers is to estimate and predict the parameters of groundwater quality so that they can make managerial decisions. In this regard, there have many models developed, proposing better management in order to maintain water quality. Most of these models require input parameters that are either hardly available or time-consuming and expensive to measure. Among them, the Artificial Neural Network (ANN) Models, inspired from human brain, are a better choice. The present study has simulated the groundwater quality parameters of Ramhormoz Plain, including Sodium Adsorption Ratio (SAR), Electrical Conductivity (EC), and Total Dissolved Solids (TDS), via ANN and ANN+ Particle Swarm Optimization (PSO) Models and at the end has compared their results with the measured data. The input data for TDS quality parameter is consisted of EC, SAR, pH, SO4, Ca, Mg, and Na, while for SAR, it includes TDS, pH, Na, and Hco3, and as for EC, it involves So4, Ca, Mg, SAR, and pH; all of them, gathered from 2009 to 2015. Results indicate that the highest prediction accuracy for SAR, EC, and TDS is related to the ANN + PSO model with the tangent sigmoid activation function so that both MAE and RMSE statistics have the minimum and R2 the maximum value for the model. Also the highest prediction accuracy is respectively related to EC, TDS, and SAR parameters. Considering the high efficiency of artificial neural network model, by training the PSO algorithm, it can be used in order to make managerial decisions and ensure monitoring and cost reduction results.

Intermittent, fluctuating and pulsed contaminant discharges may result in organisms receiving highly variable contaminant exposures. This study investigated the effects of dissolved copper pulse concentration and exposure duration on the toxicity to two freshwater green algae species. The effects of single copper pulses of between 1 and 48 h duration and continuous exposures (72 h) on growth rate inhibition of Pseudokirchneriella subcapitata and Chlorella sp. were compared on a time-averaged concentration (TAC) basis. Relationships were then derived between the exposure concentration and duration required to elicit different levels of toxicity expressed as inhibition concentration (IC). Continuous exposure IC50's of 3.0 and 1.9 μg/L were measured on a TAC basis for P. subcapitata and Chlorella sp., respectively. Algal growth rates generally recovered to control levels within 24–48 h of the copper pulse removal, with some treatments exhibiting significantly (p < 0.05) higher rates of cell division than controls in this recovery period. For both algae, when exposed to treatments with equivalent TACs, the continuous exposure elicited similar or slightly greater growth rate inhibition than the pulsed exposures. To elicit equivalent inhibition, the exposure concentration increased as the exposure duration decreased, and power models fitted this relationship reasonably well for both species. Water quality guideline values (WQGVs) are predominantly derived using data from continuous exposure toxicity bioassays, despite intermittent contaminant exposures often occurring in aquatic systems. The results indicate the WQGV for copper may be relaxed for pulsed exposures by a factor less than or equivalent to the TAC and still achieve a protection to these sensitive algae species.

Understanding the sources, occurrence and sinks of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in the urban water cycle is important to protect and utilize local water resources. Concentrations of 22 target PFASs and general water quality parameters were determined monthly for a year in filtered water samples from five tributaries and three sampling stations of an urban water body. Of the 22 target PFASs, 17 PFASs were detected with a frequency >93% including PFCAs: C4-C12 perfluoroalkyl carboxylates, C4, C6, C8, and C10 perfluoroalkane sulfonates, perfluorooctane sulfonamides and perfluorooctane sulfonamide substances (FOSAMs), C10 perfluoroalkyl phosphonic acid (C10 PFPA), 6:2 fluorotelomer sulfonic acid (6:2 FTSA) and C8/C8 perfluoroalkyl phosphinic acid (C8/C8-PFPIA). The most abundant PFASs in water were PFBS (1.4–55 ng/L), PFBA (1.0–23 ng/L), PFOS (1.5–24 ng/L) and PFOA (2.0–21 ng/L). In the tributaries, PFNA concentrations ranged from 1.2 to 87.1 ng/L except in the May 2013 samples of two tributaries, which reached 520 and 260 ng/L. Total PFAS concentrations in the sediment samples ranged from 1.6 to 15 ng/g d.w. with EtFOSAA, PFDoA, PFOS and PFDA being the dominant species. Based on water and sediment data, two types of sources were inferred: one-time or intermittent point sources and continuous non-point sources. FOSAMs and PFOS released continually from non-point sources, C8/C8 PFPIA, PFDoA and PFUnA was released from point sources. The highly water soluble short-chain PFASs including PFBA, PFPeA and PFBS remained predominantly in the water column. The factors governing solution phase concentrations appear to be compound hydrophobicity and sorption to suspended particles. Correlation of the dissolved phase concentrations with precipitation data suggested stormwater was a significant source of PFBA, PFBS, PFUnA and PFDoA. Negative correlations with precipitation indicated sources feeding FOSAA and FOSA directly into the tributaries.

Advances in drilling techniques have facilitated a rapid increase in hydrocarbon extraction from energy shales, including the Williston Basin in central North America. This area overlaps with the Prairie Pothole Region, a region densely populated with wetlands that provide numerous ecosystem services. Historical (legacy) disposal practices often released saline co-produced waters (brines) with high chloride concentrations, affecting wetland water quality directly or persisting in sediments. Despite the potential threat of brine contamination to aquatic habitats, there has been little research into its ecological effects. We capitalized on a gradient of legacy brine-contaminated wetlands in northeast Montana to conduct laboratory experiments to assess variation in survival of larval Boreal Chorus Frogs (Pseudacris maculata) reared on sediments from 3 local wetlands and a control source. To help provide environmental context for the experiment, we also measured chloride concentrations in 6 brine-contaminated wetlands in our study area, including the 2 contaminated sites used for sediment exposures. Survival of frog larvae during 46- and 55-day experiments differed by up to 88% among sediment sources (Site Model) and was negatively correlated with potential chloride exposure (Chloride Model). Five of the 6 contaminated wetlands exceeded the U.S. EPA acute benchmark for chloride in freshwater (860 mg/L) and all exceeded the chronic benchmark (230 mg/L). However, the Wetland Site model explained more variation in survival than the Chloride Model, suggesting that chloride concentration alone does not fully reflect the threat of contamination to aquatic species. Because the profiles of brine-contaminated sediments are complex, further surveys and experiments are needed across a broad range of conditions, especially where restoration or remediation actions have reduced brine-contamination. Information provided by this study can help quantify potential ecological threats and help land managers prioritize conservation strategies as part of responsible and sustainable energy development.

In Ireland, the land application of biosolids is the preferred option of disposing of municipal sewage waste. Biosolids provide nutrients in the form of nitrogen, phosphorus, potassium and increases organic matter. It is also an economic way for a country to dispose of its municipal waste. However, biosolids may potentially contain a wide range of pathogens, and following rainfall events, may be transported in surface runoff and pose a potential risk to human health. Thus, a quantitative risk assessment model was developed to estimate potential pathogens in surface water and the environmental fate of the pathogens following dilution, residence time in a stream, die-off rate, drinking water treatment and human exposure. Surface runoff water quality data was provided by project partners. Three types of biosolids, anaerobically digested (AD), lime stabilised (LS), and thermally dried (TD)) were applied on micro plots. Rainfall was simulated at three time intervals (24, 48 and 360 h) following land application. It was assumed that this water entered a nearby stream and was directly abstracted for drinking water. Consumption data for drinking water and body weight was obtained from an Irish study and assigned distributions. Two dose response models for probability of illness were considered for total and faecal coliform exposure incorporating two different exposure scenarios (healthy populations and immuno-compromised populations). The simulated annual risk of illness for healthy populations was below the US EPA and World Health Organisation tolerable level of risk (10⁻⁴ and 10⁻⁶, respectively). However, immuno-compromised populations may still be at risk as levels were greater than the tolerable level of risk for that subpopulation. The sensitivity analysis highlighted the importance of residence time in a stream on the bacterial die-off rate.

Solomon Islands is rapidly developing its natural resource exploitation sector, but data needed to assess consequent environmental impacts are scarce. We assessed catchments surrounding the Gold Ridge gold mine (Guadalcanal, Solomon Islands) and found that extensive changes in river course, and water and sediment quality have occurred downstream of the gold mine since its development. Sediment run-off from exposed areas associated with the mine pit has increased, elevating turbidity (up to 2450 NTU) and metal and arsenic levels, with levels of the latter being up to 0.141 mg/L in surface waters and 265 mg/kg in sediments. An overfull, inoperative tailings storage facility associated with the currently inactive gold mine with fluctuating arsenic levels (up to 0.087 mg/L in the water; 377 mg/kg in the sediment) presents an ongoing threat to the environment. Arsenic, due to its toxicity, appears to be the greatest threat, with sediment and water guideline levels in rivers exceeded 10-fold and exceeded nearly 20-fold in the tailings dam sediments. Despite elevated metal and arsenic content in the area, no toxic inorganic arsenic was found to have bioaccumulated in locally harvested food. In summary, the natural environment surrounding the Gold Ridge mine has been modified substantially and requires an ongoing monitoring program to ensure the ecosystem services of food and water for the local communities continue to be safe. This study informs not only the local area but also provides a microcosm of the broader global challenges facing the regulation of extractive industries in proximity to subsistence communities.

Studies have yet to evaluate the effects of water improvement on fluoride concentrations in drinking water and the corresponding health risks to Chinese residents in endemic fluorosis areas (EFAs) at a national level. This paper summarized available data in the published literature (2008–2016) on water fluoride from the EFAs in China before and after water quality was improved. Based on these obtained data, health risk assessment of Chinese residents' exposure to fluoride in improved drinking water was performed by means of a probabilistic approach. The uncertainties in the risk estimates were quantified using Monte Carlo simulation and sensitivity analysis. Our results showed that in general, the average fluoride levels (0.10–2.24 mg/L) in the improved drinking water in the EFAs of China were lower than the pre-intervention levels (0.30–15.24 mg/L). The highest fluoride levels were detected in North and Southwest China. The mean non-carcinogenic risks associated with consumption of the improved drinking water for Chinese residents were mostly accepted (hazard quotient < 1), but the non-carcinogenic risk of children in most of the EFAs at the 95th percentile exceeded the safe level of 1, indicating the potential non-cancer-causing health effects on this fluoride-exposed population. Sensitivity analyses indicated that fluoride concentration in drinking water, ingestion rate of water, and the exposure time in the shower were the most relevant variables in the model, therefore, efforts should focus mainly on the definition of their probability distributions for a more accurate risk assessment.

Dissolved organic matter (DOM) in surface waters used for drinking purposes can vary markedly in character depending on its source within catchments and the timing and intensity of rainfall events. Here we report the findings of a study on the character and concentration of DOM in waters collected during different seasons from Myponga River and Reservoir, South Australia. The character of DOM was assessed in terms of its treatability by enhanced coagulation and potential for disinfection by-product i.e. trihalomethane (THM) formation. During the wet seasons (winter and spring), water samples from the river had higher DOC concentrations (X¯: 21 mg/L) and DOM of higher average molecular weight (AMW: 1526 Da) than waters collected during the dry seasons (summer and autumn: DOC: 13 mg/L; AMW: 1385 Da). Even though these features led to an increase in the percentage removal of organics by coagulation with alum (64% for wet compared with 53% for dry season samples) and a lower alum dose rate (10 versus 15 mg alum/mg DOC removal), there was a higher THM formation potential (THMFP) from wet season waters (treated waters: 217 μg/L vs 172 μg/L). For reservoir waters, samples collected during the wet seasons had an average DOC concentration (X¯: 15 mg/L), percentage removal of organics by alum (54%), alum dose rates (13 mg/mg DOC) and THMFP (treated waters: 207 μg/L) that were similar to samples collected during the dry seasons (mean DOC: 15 mg/L; removal of organics: 52%; alum dose rate: 13 mg/mg DOC; THMFP: 212 μg/L for treated waters). These results show that DOM present in river waters and treatability by alum are highly impacted by seasonal environmental variations. However these in reservoir waters exhibit less seasonal variability. Storage of large volumes of water in the reservoir enables mixing of influent waters and stabilization of water quality.