Understanding seasonal variations in water quality is crucial for effective management of freshwater rivers amidst changing environmental conditions. This study employed water quality index (WQI), metal index (MI), and pollution indices (PI) to comprehensively assess water quality and pollution levels in Nyabarongo River of Rwanda. A dynamic driver-pressure-state-impact-response model was used to identify factors influencing quality management. Over 4 years (2018-2021), 69 samples were collected on a monthly basis from each of the six monitoring stations across the Nyabarongo River throughout the four different seasons. Maximum WQI values were observed during dry long (52.90), dry short (21.478), long rain (93.66), and short rain (37.4) seasons, classified according to CCME 2001 guidelines. Ion concentrations exceeded WHO standards, with dominant ions being HCO 3 - and Mg 2 + . Variations in water quality were influenced by factors such as calcium bicarbonate dominance in dry seasons and sodium sulfate dominance in rainy seasons. Evaporation and precipitation processes primarily influenced ionic composition. Metal indices (MI) exhibited wide ranges: long dry (0.2-433.0), short dry (0.1-174.3), long rain (0.1-223.7), and short rain (0.3-252.5). The hazard index values for Cu2+, Mn4+, Zn2+, and Cr3+ were below 1, ranging from 8.89E - 08 to 7.68E - 07 for adults and 2.30E - 07 to 5.02E - 06 for children through oral ingestion, and from 6.68E - 10 to 5.07E - 07 for adults and 6.61E - 09 to 2.54E - 06 for children through dermal contact. With a total carcinogenic risk of less than 1 for both ingestion and dermal contact, indicating no significant health risks yet send strong signals to Governmental management of the Nyabarongo River. Overall water quality was classified as marginal in long dry, poor in short dry, good in long rain, and poor again in short rain seasons.

Many urban water bodies grapple with low flow flux and weak hydrodynamics. To address these issues, projects have been implemented to form integrated urban water bodies via interconnecting artificial lake or ponds with rivers, but causing pollution accumulation downstream and eutrophication. Despite it is crucial to assess eutrophication, research on this topic in urban interconnected water bodies is limited, particularly regarding variability and feasible strategies for remediation. This study focused on the Loucun river in Shenzhen, comprising an pond, river and artificial lake, evaluating water quality changes pre-(post-)ecological remediation and establishing a new method for evaluating the water quality index (WQI). The underwater forest project, involving basement improvement, vegetation restoration, and aquatic augmentation, in the artificial lake significantly reduced total nitrogen (by 43.58%), total phosphorus (by 79.17%) and algae density (by 36.90%) compared to pre-remediation, effectively controlling algal bloom. Rainfall, acting as a variable factor, exacerbated downstream nutrient accumulation, increasing total phosphorus by 4.56 times and ammonia nitrogen by 1.30 times compared to the dry season, and leading to algal blooms in the non-restoration pond. The improved WQI method effectively assesses water quality status. The interconnected water body exhibits obvious nutrient accumulation in downstream regions. A combined strategy that reducing nutrient and augmenting flux was verified to alleviate accumulation of nutrients downstream. This study provides valuable insights into pollution management strategies for interconnected pond-river-lake water bodies, offering significant reference for nutrient mitigation in such urban water bodies.

The aim of the present study was to assess the drinking water quality in the selected urban areas of Lahore and to comprehend the public health status by addressing the basic drinking water quality parameters. Total 50 tap water samples were collected from groundwater in the two selected areas of district Lahore i.e., Gulshan-e-Ravi (site 1) and Samanabad (site 2). Water samples were analyzed in the laboratory to elucidate physico-chemical parameters including pH, turbidity, temperature, total dissolved solids (TDS), electrical conductivity (EC), dissolved oxygen (DO), total hardness, magnesium hardness, and calcium hardness. These physico-chemical parameters were used to examine the Water Quality Index (WQI) and Synthetic Pollution Index (SPI) in order to characterize the water quality. Results of th selected physico-chemical parameters were compared with World Health Organization (WHO) guidelines to determine the quality of drinking water. A GIS-based approach was used for mapping water quality, WQI, and SPI. Results of the present study revealed that the average value of temperature, pH, and DO of both study sites were within the WHO guidelines of 23.5 °C, 7.7, and 6.9 mg/L, respectively. The TDS level of site 1 was 192.56 mg/L (within WHO guidelines) and whereas, in site 2 it was found 612.84 mg/L (higher than WHO guidelines), respectively. Calcium hardness of site 1 and site 2 was observed within the range from 25.04 to 65.732 mg/L but, magnesium hardness values were higher than WHO guidelines. The major reason for poor water quality is old, worn-out water supply pipelines and improper waste disposal in the selected areas. The average WQI was found as 59.66 for site 1 and 77.30 for site 2. Results showed that the quality of the water was classified as \"poor\" for site 1 and \"very poor \" for site 2. There is a need to address the problem of poor water quality and also raise the public awareness about the quality of drinking water and its associated health impacts.

The water crisis may be solved by utilizing reclaimed water. Three reclaimed water sources have restored the lower sections of the Licun River, forming a landscaped river. In this paper, the river\'s water quality was monitored for a year, and the ecological concerns were analyzed using luminescent bacteria, chlorella, and zebrafish. The results indicated that although basic water quality indicators like COD and ammonia fluctuated along the river, the classification of water quality was primarily affected by factors such as flow rate and water depth. Under experimental conditions, the toxic inhibitory effect of river water on luminescent bacteria, chlorella, and zebrafish was related to the treatment process of reclaimed water. It was found that the reclaimed water produced by the MBR, along with the UV disinfection process, showed no detectable toxicity. In contrast, the MBBR process, when combined with coagulation, sedimentation, filtration, ozonation, and chlorination, seemed to be the source of this toxicity. Along the river, the results of water quality assessments and ecological risk assessments were different, indicating that both should be conducted to evaluate rivers replenished with reclaimed water.

Water quality, increasingly recognized for its significant impact on health, is garnering heightened attention. Previous studies were limited by the number of water quality indicators and the duration of analysis. This study assessed the drinking water quality and its associated health risk in suburban areas of Wuhan, a city in central China, from 2016 to 2021. We collected 368 finished water samples and 1090 tap water samples and tested these for 37 different indicators. The water quality was evaluated using the water quality index, with trends over time analyzed via the Mann-Kendall test. Furthermore, an artificial neural network model was employed for future water quality prediction. Our findings indicated that the water quality in rural Wuhan was generally good and had an improvement from 2016 to 2021. The qualification and excellent rates were 98.91% and 86.81% for finished water, and 97.89% and 78.07% for tap water, respectively. The drinking water quality was predicted to maintain satisfactory in 2022 and 2023. Additionally, principal component analysis revealed that the primary sanitary issues in the water were poor sensory properties, elevated metal contents, high levels of dissolved solids, and microbial contamination. These issues were likely attributable to domestic and industrial waste discharge and aging water pipelines. The health risks associated with the long-term consumption of this water have been steadily decreasing over the years, underscoring the effectiveness of Wuhan\'s ongoing water management efforts.

To explore the changes in nitrite nitrogen, ammoniacal nitrogen, nitrate nitrogen, phosphates, pH, dissolved oxygen, salinity, and water temperature over time and the correlations and mutual influences between these indexes in the traditional farming of largemouth bass, this study selected three ponds in Lizigu Farm in Baodi District of Tianjin, China as research objects. From May to October 2021, nutrient salts and other water quality indexes in the ponds were measured, and water samples were collected at different depths for repetition, Water is collected from the ponds using Plexiglas samplers and sent back to the lab for determination of water quality indexes using our national laboratory standards. According to the analysis of the measurement results, in traditional farming, nitrite nitrogen, ammoniacal nitrogen, nitrate nitrogen, phosphates, pH, dissolved oxygen, salinity, and water temperature in the ponds for largemouth bass all change significantly over time, with different changing trends and certain correlations with each other. In particular, nutrient salts indexes in ponds are influenced by other water quality indexes, human activities, and phytoplankton. During the breeding process, strengthening the dynamic monitoring of nutrient salts and other water quality indexes in the ponds and adjusting the nitrogen, phosphorus, and ammonia levels in the ponds artificially play an important role in preventing eutrophication in the water and promoting the green and sustainable production of pond ecosystems, in particular, allowing better quality growth of the largemouth bass, as well as ensuring the production and economic efficiency. This study provides a theoretical basis and data support for further optimization of traditional pond aquaculture in similar regions, in order to provide aquatic products with better quality and achieve higher economic benefits.

The degradation of water quality induced by the construction of large-scale hydraulic projects is one of the primary public concerns; however, it is rarely addressed with long-term field observation data. Here, we reported the long-term (2003-2021) trends, seasonal patterns, and overall condition of water quality of the Three Gorges Reservoir (TGR) with an enhanced water quality index (WQI). Specifically, to emphasize the importance of the biological role in water quality assessment, chlorophyll-a (Chla) was incorporated into WQI, and then a novel workflow using machine learning approach based on Random Forest (RF) model was constructed to develop a minimal water quality index (WQImin). The enhanced WQI indicated an overall \"good\" water quality condition, exhibiting a gradually improving trend subsequent to the reservoir impoundment in 2003. Meanwhile, the assessment revealed that the water quality has discernible seasonal patterns, characterized by poorer conditions in the spring and summer seasons. Furthermore, the RF model identified Chla, dissolved oxygen (DO), ammonium nitrogen (NH4-N), water temperature (WT), pH, and total nitrogen (TN) as key parameters for the WQImin, with Chla emerging as the most important factor in determining WQImin in our study. Moreover, weighted WQImin models exhibited improved performance in estimating WQI. Our study emphasizes the importance of biological parameters in water quality assessment, and introduces a systematic workflow to facilitate the development of WQImin for accurate and cost-efficient water quality assessment. Furthermore, our study makes a substantial contribution to the advancement of knowledge regarding long-term trends and seasonal patterns in water quality of large reservoirs, which provides a foundational basis for guiding water quality management practices for reservoirs worldwide.

Rapid urbanization accelerates the release of anthropogenic heavy metals from local to wider water systems, posing a serious threat to aquatic ecosystems and public health. The characteristics of trace elements were investigated to evaluate the environmental status of surface water in 40 cities of China. The concentrations of 22 elements in surface water ranged from 7.00 × 10-4 to 4.37 × 105 μg/L. The water quality can be classified as \"excellent\" except Songhuajiang. The levels of As, Cd, Cr, Pb, and Hg are all within the limits permitted by national drinking water quality standards. An obvious regional distribution characteristic was observed, with concentrations of Zn, Mn, Ni, Cu, Co, U, and Cr higher in surface water collected in the north than in the south, while the trends for Cd, Tl, and As are opposite. Notably, Tl shows significant geographical divergences, with the level of surface water collected from the south nine times higher than that from the north. The regional distribution of the mineral, industrial, or agricultural activity might be responsible for the south-to-north difference of these elements. The hazard index (HI) and total cancer risk (TCR) through oral or dermal contact with water-related heavy metals were further calculated. The average HI was 0.54 in the north and 0.29 in the south for adults, while HI for children was relatively higher. The value was 1.01 and 0.55 in the north and south, respectively. TCR in the north is 2.58 × 10-4 and mainly contributed by Cr (88.1 %), while TCR in the south is 4.48 × 10-5 and mainly contributed by As (98.4 %). The research results can provide essential data for effective water resources management and human health protection in China.

Arsenic contamination in the groundwater occurs in various parts of the world due to anthropogenic and natural sources, adversely affecting human health and ecosystems. The current study intends to examine the groundwater hydrogeochemistry containing elevated arsenic (As), predict As levels in groundwater, and determine the aptness of groundwater for drinking in the Vehari district, Pakistan. Four hundred groundwater samples from the study region were collected for physiochemical analysis. As levels in groundwater samples ranged from 0.1 to 52 μg/L, with an average of 11.64 μg/L, (43.5%), groundwater samples exceeded the WHO 2022 recommended limit of 10 μg/L for drinking purposes. Ion-exchange processes and the adsorption of ions significantly impacted the concentration of As. The HCO3- and Na+ are the dominant ions in the study area, and the water types of samples were CaHCO3, mixed CaMgCl, and CaCl, demonstrating that rock-water contact significantly impacts hydrochemical behavior. The geochemical modeling indicated negative saturation indices with calcium carbonate and other salt minerals, encompassing aragonite, calcite, dolomite, and halite. The dissolution mechanism suggested that these minerals might have implications for the mobilization of As in groundwater. A combination of human-induced and natural sources of contamination was unveiled through principal component analysis (PCA). Artificial neural networks (ANN), random forest (RF), and logistic regression (LR) were used to predict As in the groundwater. The data have been divided into two parts for statistical analysis: 20% for testing and 80% for training. The most significant input variables for As prediction was determined using Chi-squared analysis. The receiver operating characteristic area under the curve and confusion matrix were used to evaluate the models; the RF, ANN, and LR accuracies were 0.89, 0.85, and 0.76. The permutation feature and mean decrease in impurity determine ten parameters that influence groundwater arsenic in the study region, including F-, Fe2+, K+, Mg2+, Ca2+, Cl-, SO42-, NO3-, HCO3-, and Na+. The present study shows RF is the best model for predicting groundwater As contamination in the research area. The water quality index showed that 161 samples represent poor water, and 121 samples are unsuitable for drinking. Establishing effective strategies and regulatory measures is imperative in Vehari to ensure the sustainability of groundwater resources.

Taking the Tugeligaole sub-basin of the Jilantai Salt Lake Basin in Inner Mongolia as the typical study area, the groundwater samples of 22 points were collected, and their main characteristic indexes were tested during the wet season and the dry season separately in 2021. Mathematical statistics, Piper triangular diagrams, a Gibbs plot, ionic relations, and factor analysis were used to analyze and discuss the hydrochemical characteristics and formation mechanism of groundwater in different periods. Based on the evaluation of the groundwater quality using the water quality index(WQI) method, the potential risks of groundwater Cr6+ and F- were evaluated using the health risk evaluation model. The results showed that the groundwater was overall weakly alkaline; the dominant anions and cations during the different periods were Cl- and Na+, and the water chemistry type was mainly Cl--Na+; the groundwater quality was generally good, and the difference in water quality between the wet season and the dry season was not significant; adults and children had higher carcinogenic health risks in the dry season than that in the wet season, and the health risks of children were significantly higher than those in adults. The maximum carcinogenic health risk of drinking water exposure to Cr6+ in adults and children was higher than the maximum acceptable risk level(5×10-5). The chemical evolution of groundwater was mainly affected by evaporative concentration, evaporative salt rock dissolution, and cation exchange, and the main control factors were evaporative concentration(contribution rate of 54.19%), native geological environment factors(contribution rate of 12.99%), and carbonate rock dissolution(contribution rate of 11.66%). The study results have significance to some degree to the sustainable exploitation and utilization of groundwater resources and environmental protection of the salt lake basin.