Spatial and seasonal groundwater quality assessment for drinking suitability using index and machine learning approach.

Spatial and seasonal evaluation and monitoring of groundwater (GW) quality is essential for the sustainable management of this priceless resource and the provision of safe drinking water. Nevertheless, GW quality appraisal was not given due attention in the current study area (flat terrain part of the Tana sub-basin). This study sought to assess the seasonal and regional physicochemical GW quality parameters for drinking appropriateness using the drinking water quality index (DWQI) and support vector machine (SVM). The main cations in both the dry and wet study seasons were, in decreasing order, Na+, Ca2+, Mg2+, K+, and Fe2+, according to the results. Conversely, the main anions were HCO3-, CO32-, Cl- or NO3-, SO42- and PO43-, ordered from higher to lower. During the two research seasons, Ca-HCO3 and Na-HCO3 were the predominant water types based on Piper diagram results. Reverse ion exchange and evaporation were the principal hydrogeochemical processes that control the hydrogeochemistry identified by Durov and Gibbs diagrams, respectively. Excellent GW quality class for drinking was demonstrated by the majority of geographical and seasonal DWQI readings over the two seasons. Nevertheless, during the rainy season, there was a noticeable decline in the GW quality condition around the northern shores of Lake Tana. Therefore, it is advised to implement comprehensive GW quality protection measures and improve system management to mitigate pollution to reduce health hazards in the examined region.

Health impact assessment of the surface water pollution in China.

China suffers from severe surface water pollution. Health impact assessment could provide a novel and quantifiable metric for the health burden attributed to surface water pollution. This study establishes a health impact assessment method for surface water pollution based on classic frameworks, integrating the multi-pollutant city water quality index (CWQI), informative epidemiological findings, and benchmark public health information. A relative risk level assignment approach is proposed based on the CWQI, innovatively addressing the challenge in surface water-human exposure risk assessment. A case study assesses the surface water pollution-related health impact in 336 Chinese cities. The results show (1) between 2015 and 2022, total health impact decreased from 3980.42 thousand disability-adjusted life years (DALYs) (95 % Confidence Interval: 3242.67-4339.29) to 3260.10 thousand DALYs (95 % CI: 2475.88-3641.35), measured by total cancer. (2) The annual average health impacts of oesophageal, stomach, colorectal, gallbladder, and pancreatic cancers added up to 2621.20 thousand DALYs (95 % CI: 2095.58-3091.10), revealing the significant health impact of surface water pollution on digestive cancer. (3) In 2022, health impacts in the Beijing-Tianjin-Hebei and surroundings, the Yangtze River Delta, and the middle reaches of the Yangtze River added up to 1893.06 thousand DALYs (95 % CI: 1471.82-2097.88), showing a regional aggregating trend. (4) Surface water pollution control has been the primary driving factor to health impact improvement, contributing -3.49 % to the health impact change from 2015 to 2022. It is the first city-level health impact map for China's surface water pollution. The methods and findings will support the water management policymaking in China and other countries suffering from water pollution.

A critical analysis of parameter choices in water quality assessment.

The determination of water quality heavily depends on the selection of parameters recorded from water samples for the water quality index (WQI). Data-driven methods, including machine learning models and statistical approaches, are frequently used to refine the parameter set for four main reasons: reducing cost and uncertainty, addressing the eclipsing problem, and enhancing the performance of models predicting the WQI. Despite their widespread use, there is a noticeable gap in comprehensive reviews that systematically examine previous studies in this area. Such reviews are essential to assess the validity of these objectives and to demonstrate the effectiveness of data-driven methods in achieving these goals. This paper sets out with two primary aims: first, to provide a review of the existing literature on methods for selecting parameters. Second, it seeks to delineate and evaluate the four principal motivations for parameter selection identified in the literature. This manuscript categorizes existing studies into two methodological groups for refining parameters: one focuses on preserving information within the dataset, and another ensures consistent prediction using the full set of parameters. It characterizes each group and evaluates how effectively each approach meets the four predefined objectives. The study presents that the minimal WQI approach, common to both categories, is the only approach that has successfully reduced recording costs. Nonetheless, it notes that simply reducing the number of parameters does not guarantee cost savings. Furthermore, the group of studies classified as preserving information within the dataset has demonstrated potential to decrease the eclipsing problem, whereas studies in the consistent prediction group have not been able to mitigate this issue. Additionally, since data-driven approaches still rely on the initial parameters chosen by experts, they do not eliminate the need for expert judgment. The study further points out that the WQI formula is a straightforward and expedient tool for assessing water quality. Consequently, the paper argues that employing machine learning solely to reduce the number of parameters to enhance WQI prediction is not a standalone solution. Rather, this objective should be integrated with a more comprehensive set of research goals. The critical analysis of research objectives and the characterization of previous studies lay the groundwork for future research. This groundwork will enable subsequent studies to evaluate how their proposed methods can effectively achieve these objectives.

Water quality characteristics and ecological risk evaluation of a landscaped river replenished by three reclaimed water sources in Qingdao, China.

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.

Hydrogeochemical characteristics of groundwater contamination in Guwahati city, Assam, India: Tracing the elemental Threads.

Groundwater serves as an important resource for drinking and agriculture in many countries, including India. Assessing the quality of groundwater is essential for understanding its chemical characteristics and suitability for consumption. This study aims to explore the factors affecting the hydrogeochemical changes in groundwater within Guwahati City, Assam, India. Groundwater samples were collected and analyzed for major and trace elements, as well as anion concentrations. Concentrations of As, Al, Ba, Cu, F-, Fe, Mn, and Pb exceeded the permissible limits set by both World Health Organization (WHO) and Bureau of Indian Standards (BIS), indicating serious health concerns for the local inhabitants. The distribution pattern of trace elements exceeding the guideline values is intricate, suggesting widespread contamination of groundwater throughout the study area. The Heavy Metal Pollution Index (HPI) and Water Quality Index (WQI) revealed that, except for the central zone, groundwater across the entire study area requires intervention. Piper plot illustrated that the groundwater is predominantly of Ca-HCO3 type, indicating the dominance of alkaline earth and weak acids. Groundwater hydrogeochemistry is mainly controlled by rock-water interaction and evolves through silicate weathering, carbonate weathering, and cation exchange processes. Multivariate statistical analysis identified distinct groups of groundwater based on chemical characteristics, emphasizing the role of both natural processes and anthropogenic activities in influencing groundwater quality. Regular monitoring, management, and intervention of groundwater sources throughout the study area are crucial for long-term use. The findings of this study will assist stakeholders, regulators, and policymakers in formulating strategies for the sustainable use of groundwater.

Heavy metal contamination and environmental risk assessment: a case study of surface water in the Bahr Mouse stream, East Nile Delta, Egypt.

Water, as an indispensable constituent of life, serves as the primary source of sustenance for all living things on Earth. The contamination of surface water with heavy metals poses a significant global health risk to humans, animals, and plants. Sharkiya Governorate, situated in the East Nile Delta region of Egypt, is particularly susceptible to surface water pollution due to various industrial, agricultural, and urban activities. The Bahr Mouse Stream, crucial for providing potable water and supporting irrigation activities in Sharkiya Governorate, caters to a population of approximately 7.7 million inhabitants. Unfortunately, this vital water source is exposed to many illegal encroachments that may cause pollution and deteriorate the water resource quality. In a comprehensive study conducted over two consecutive seasons (2019-2020), a total of 38 surface water samples were taken to assess the quantity of heavy metals in surface water destined for human consumption and other applications, supported by indices and statistics. The assessment utilized flame atomic absorption spectrophotometry to determine the concentration of key heavy metals including iron (Fe), manganese (Mn), cadmium (Cd), copper (Cu), lead (Pb), zinc (Zn), nickel (Ni), cobalt (Co), and chromium (Cr). The calculated mean value of the Water Quality Index (WQI) was found to be 39.1 during the winter season and 28.05 during the summer season. This value suggests that the surface water maintains good quality and is suitable for drinking purposes. Furthermore, the analysis indicated that the concentrations of heavy metals in the study area were below the recommended limits set by the World Health Organization and fell within the safe threshold prescribed by Egyptian legislation. Despite the identification of localized instances of illegal activities in certain areas, such as unauthorized discharges, the findings affirm that the Bahr Mouse stream is devoid of heavy metal pollution. This underscores the importance of continued vigilance and regulatory enforcement to preserve the integrity of these vital water resources.

Evaluation of irrigation, drinking, and risk indices for water quality parameters of alpine lakes.

Alpine lakes are aquatic ecosystems that maintain and regulate water supply for the downstream streams, rivers, and other reservoirs. This study examined the water characteristics of various alpine lakes in Gilgit-Baltistan, Northern Pakistan. For this purpose, water was sampled and investigated for basic parameters, anions, and cations using the multi-parameter analyzers and atomic absorption spectrophotometer. Physicochemical parameters of alpine lakes were noted under the World Health Organization water guidelines, except for fluoride (F-) and turbidity in 4.3% and 36% of samples, respectively. Water quality index (WQI) classified samples (93%) as excellent and good quality (7%). Results showed maximum chronic daily intake values (0.14 ± 0.01 mg/kg-day) for nitrate (NO3-) and hazard quotient (0.80 ± 0.24) for F- in children via water intake from Upper Kachura and Shausar Lakes, respectively. Statistical analyses of Piper and Gibbs's plots revealed that the water quality is mainly characterized by bedrock geology.

Spatial distribution and hydrogeochemical evaluations of groundwater and its suitability for drinking and irrigation purposes in kaligonj upazila of satkhira district of Bangladesh.

Groundwater is a significant water resource for drinking and irrigation in Satkhira district, Bangladesh. The depletion of groundwater resources and deterioration in its quality are the results of the confluence of factors such as industrialization, intensive irrigation, and rapid population growth. For this reason, this study focused on the evaluation of tubewell water of six unions of Kaligonj upazila in Satkhira district, which is situated in the coastal southwest part of Bangladesh. Major and trace elemental concentrations were assimilated into positive matrix factorization (PMF) to identify potential sources and their respective contributions. Principal component analysis (PCA) revealed that groundwater salinization and manmade activities were the primary causes of heavy metals in the coastal groundwater. Its average pH value was found to be 7.5, while Dissolved oxygen, Total dissolved solids, salinity, and conductivity, with values ranging from 1.18 to 7.38 mg/L, 0.5-4.88 g/L, 0.4-5%, and 0.95 to 8.56 mS/cm, respectively. The total hardness average value was 561.7 mg/L, classified into the very hard water categories, which is why 90% of the tubewell water samples were unfit for household purposes. All samples had an excessive level of arsenic present. The iron concentration of fifteen (15) samples crossed the standard limit according to WHO 2011 value. Around 63% of the samples were of the Na+-K+-Cl--SO42- type, and about 72% were sodium-potassium and alkali types. 98% of samples were covered in chloride and bicarbonate. The findings showed that 45.83% of the groundwater samples had negative Chloroalkaline index (CAIs), while 54.16% had positive. The permeability index (PI) was an average of 73%, and residual sodium carbonate (RSC) averaged 260.2 mg/L, and the findings clearly showed that 80% of the samples weren't appropriate for irrigation. According to the sodium adsorption ratio (SAR) value, 65% of the samples fell into the unsuitable category. These calculations indicated a high overall salinity hazard in the study area, which may be caused by the intrusion of sea water given that the study area is close to the coastal region. Findings compared to standards revealed that the majority of the samples were deemed unfit for drinking and irrigation purposes. Hence, additional attention must be paid to this area to ensure the availability of drinkable water and to preserve sustainable farming practices.

Groundwater quality and potential analysis using geospatial techniques: The case of Ashanti Region in Ghana.

The ecosystem and economy's reliance on clean water is influenced by various factors such as geology, topography, soil types, activities, and the presence of plants and animals. The Ghana Water Company is encountering difficulties in delivering water to consumers in the Ashanti Region due to the shortage of surface water resources, leading to water rationing in the area. Furthermore, poor waste disposal practices, illegal mining, use of fertilizers, and industrial activities have resulted in surface and groundwater source damage. Therefore, there is a need to implement a reliable, simple, and timely method to assess groundwater quality. This study aims to employ GIS and RS techniques to evaluate groundwater quality and potential in the Ashanti Region, Ghana. The Water Quality Index (WQI) was estimated using pH, Total Dissolve Solid (TDS), Chloride, Total Hardness (TH), Nitrate, Temperature, Turbidity, Iron, and Electrical Conductivity (EC). The study then used the WQI distribution to conduct a groundwater potential analysis to identify suitable areas for borehole placement. Digital thematic layers and maps were developed to expose the spatial distribution of water quality parameters, enabling the identification of groundwater pollution control and remedial measures. The study estimated the region's groundwater potential using an integrated GIS and Analytical Hierarchical Process (AHP) technique, grouping under excellent, good, fair, and poor potential. The WQI in the Ashanti Region ranged from 5.208 to 134.232, with 32.252% of the study area having an excellent WQI and 60.168% of the study area having a good WQI. Poor water quality covered 7.550% of the study area. The results showed that the GIS-based AHP approach accurately mapped the spatial distribution of WQI and Groundwater Potential Zones (GWPZ). This information is helpful to planners in water resource management in groundwater exploration and future planning. Policymakers and stakeholders must ensure that groundwater sources are protected from pollution.

Hydrogeochemical evolution processes, groundwater quality, and non-carcinogenic risk assessment of nitrate-enriched groundwater to human health in different seasons in the Hawler (Erbil) and Bnaslawa Urbans, Iraq.

The main objectives of this research are to assess groundwater, a primary source of drinking water in the urban areas of Hawler (Erbil) and Bnaslawa in northern Iraq, and the non-carcinogenic human health risks of nitrate contamination associated with drinking water quality. For this purpose, twenty-seven groundwater samples were collected from wells to assess the hydrogeochemical characteristics and groundwater quality for both natural and anthropogenic purposes during the wet (May 2020) and dry (September 2020) seasons. During the wet and dry seasons, NO3- in groundwater ranged from 14.00 to 61.00 mg/L and 12.00 to 60.00 mg/L, with an average value of 35.70 and 29.00 mg/L, respectively. Approximately 25.92% of the samples exceeded the permissible limit of the WHO (2011) drinking water standard. The ratios of NO3-/Na+ vs. Cl-/Na+ and SO42-/Na+ vs. NO3-/Na+ indicate the effect of agricultural activities and wastewater leaking from cesspools or septic tanks on the quality of groundwater during the wet and dry seasons. The entropy weighted water quality index method ranked 62.5% and 75% of the urban groundwater as not recommended for drinking, and the remaining samples are moderately suitable in both wet and dry seasons. The non-carcinogenic human health risk assessment displayed that during the wet and dry seasons, 29.6% and 25.9% of adults, 48% and 30% of children, and 48.1% and 29.6% of infants were exposed to increased concentrations of nitrate in groundwater. Due to high nitrate in drinking water, non-carcinogenic human health risk levels vary as infant > child > adults. The main findings obtained from this study can assist policymakers in better understanding the hydrogeochemical properties of groundwater in terms of drinking water safety, thereby facilitating the management of water resources to take the necessary measures.

Groundwater quality assessment using water quality index and principal component analysis in the Achnera block, Agra district, Uttar Pradesh, Northern India.

The qualitative and quantitative assessment of groundwater is one of the important aspects for determining the suitability of potable water. Therefore, the present study has been performed to evaluate the groundwater quality for Achhnera block in the city of Taj, Agra, India, where groundwater is an important water resource. The groundwater samples, 50 in number were collected and analyzed for major ions along with some important trace element. This study has further investigated for the applicability of groundwater quality index (GWQI), and the principal component analysis (PCA) to mark out the major geochemical solutes responsible for origin and release of geochemical solutes into the groundwater. The results confirm that, majority of the collected groundwater samples were alkaline in nature. The variation of concentration of anions in collected groundwater samples were varied in the sequence as, HCO3- > Cl- > SO42- > F- while in contrast the sequence of cations in the groundwater as Na > Ca > Mg > K. The Piper diagram demonstrated the major hydro chemical facies which were found in groundwater (sodium bicarbonate or calcium chloride type). The plot of Schoellar diagram reconfirmed that the major cations were Na+ and Ca2+ ions, while in contrast; major anions were bicarbonates and chloride. The results showed water quality index mostly ranged between 105 and 185, hence, the study area fell in the category of unsuitable for drinking purpose category. The PCA showed pH, Na+, Ca2+, HCO3- and fluoride with strong loading, which pointed out geogenic source of fluoride contamination. Therefore, it was inferred that the groundwater of the contaminated areas must be treated and made potable before consumption. The outcomes of the present study will be helpful for the regulatory boards and policymaker for defining the actual impact and remediation goal.

The impact of the COVID-19 pandemic on the seawater quality of Ha Long Bay, Vietnam.

Ha Long Bay is a UNESCO World Heritage Site in Vietnam with unique natural scenery. Development and socio-economic activity impact its water quality. In the context of the Vietnam National Standards, historical follow-up data taken over a five-year period (2016 to 2020), for twenty-eight widely dispersed sampling sites, has been used to carry out a temporal assessment of seawater quality utilizing a Water Quality Index (WQI) method. The analysis shows that the seawater quality is generally acceptable over this period. However, the calculated WQI values for the "pandemic year" of 2020 compared to the data for 2016 to 2019, demonstrate a significantly lesser impact for the bay overall and, more specifically, for seventeen individual sites. Ten sites remain unaffected, and one site shows a significantly higher impact. This study demonstrates how the occurrence of the pandemic in 2020 may be exploited for the interrogation of anthropogenic impacts around the bay.

Assessment of drinking water quality and health risk using water quality index and multiple computational models: a case study of Yangtze River in suburban areas of Wuhan, central China, from 2016 to 2021.

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.

Prediction of weighted arithmetic water quality index for urban water quality using ensemble machine learning model.

Urban water quality index (WQI) is an important factor for assessment quality of groundwater in the urban and rural area. In this research, the Weighted Arithmetic Water Quality Index (WA-WQI) was estimated for understanding the groundwater quality. Four machine learning (ML) models were developed including artificial neural network (ANN), support vector machine (SVM), random forest (RF), and extreme gradient boosting (XG-Boost) in addition to multiple linear regression (MLR) for WA-WQI prediction at the Ujjain city of Madhya Pradesh in India. Groundwater quality samples were collected from 54 wards under the urban area, the main eight different physiochemical parameters were selected for WA-WQI prediction. The different input parameters data were analysed and calculated for the relationships of their ability to predict the results of WA-WQI. The ML models performance were calculated using three statistical metrics such as determination coefficient (R2), mean absolute error (MAE), and root mean square error (RMSE). In this research shown the XG-Boost model is better results other than other ML models. The best modelling results over the training phase revealed R2 = 0.969, RMSE = 2.169, MAE = 2.013 and over the testing phase R2 = 0.987, RMSE = 3.273, MAE = 2.727). All the ML models results were validated using receiver operating characteristic (ROC) curve for the best models selection. The results of best model area under curve (AUC) was 0.9048. Hence, XG-Boost model was given the accurate prediction of WA-WQI in the urban area. Based on the graphical presentation evaluation, XG-Boost model showed similar results of superiority. The obtained modelling results emphasis the utility of computer aid models for better planning and essential information for decision-makers, and water experts. The implement agency can adopt the procedures of water quality to decrease pollution and safe and healthy water provide to entire Ujjain city.

Identification of hydrochemical fingerprints, quality and formation dynamics of groundwater in western high Himalayas.

Identifying hydrochemical fingerprints of groundwater is a challenge in areas with complex geological settings. This study takes the Gilgit-Baltistan, a complex geological area in west high Himalayas, Pakistan, as the study area to get insights into the hydrochemcial genesis and quality of groundwater in complex geological mountainous regions. A total of 53 samples were collected across the area to determine the hydrochemical characteristics and formation of groundwater. Results revealed groundwater there is characterized by slightly alkaline and soft fresh feature. Groundwater is dominated by the hydrochemical facies of HCO3·SO4-Ca·Mg type. The factor method yields three components (PCs) of principal component analysis, which together explain 75.71% of the total variances. The positive correlation of EC, TDS, Ca2+, SO42-, K+ in PC1, and NO3-, Cl- in PC2 indicate that a combination of natural and anthropogenic activities influences groundwater hydrochemistry. Water-rock interaction is the main mechanism governing the natural hydrochemistry of groundwater. The negative correlation of Cl-, SO42-, Ca2+, and Na+ with NDVI attributes to inorganic salt uptake by plant roots. Groundwater chemical composition is also affected by the type of land use. Groundwater is characterized as excellent and good water quality based on the entropy-weighted water quality index assessment, and is suitable for drinking purposes except for very few samples, while aqueous fluoride would pose potential health threats to water consumers in western high Himalayas, and infants are most at risk compared to other populations. This study will help to deepen the hydrochemial formation mechanism and exploitation suitability of groundwater resources in the mountainous areas that undergone the combined actions of nature and human activities, and provide insights into the characteristics of water environmental quality in western Himalayas area.

Evaluation of Surface Water Quality in the Betwa River Basin through the Water Quality Index Model and Multivariate Statistical Techniques.

The Betwa River Basin (BRB), a sub-basin of the River Yamuna, is the oldest flowing water system in Central India. The water quality of the rivers are under stress, hence regular monitoring and appraisal is required to know the health of the rivers. Factor analysis and principal component analysis (FA/PCA) multivariate statistical techniques were used to extract three and four varimax factors that explained 96.408 and 100.00 percent of the total variance in water quality, respectively. Cluster analysis (CA) categorizes observed items into distinct quality categories based on correlations between stations and years. Point industrial/sewage effluents, diffuse pollution as runoff from arable land, erosion, and natural source pollution contribute to the pollution of the BRB. As a result, water quality is threatened or impaired, and conditions often departed from natural or desirable levels at Rajghat, Garrauli, Mohana, and Shahijina stations. According to the Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI), the surface water quality at the Rajghat and Mohana stations corresponds to fair ecological status. However, the surface water quality of the Garrauli and Shahijina stations has a marginal water quality as per CCME-WQI. From 1985 to 2018, the Shahijina had the most considerable load of nutrients and organic matter, as determined by the CCME-WQI and by comparing the water quality data. A thorough examination had revealed a fluctuating trend in the BRB pollution, particularly at all stations. Results indicate that between 1985 and 2018, the only defense mechanism of the river was the auto purification mechanism, which is strongly influenced by the drought, point pollution source, and extreme meteorological events that probably cause these fluctuations.

Heavy metal geochemistry and toxicity assessment of water environment from Ib valley coalfield, India: Implications to contaminant source apportionment and human health risks.

The present study aims to investigate the hydrogeochemical evolution of heavy metals and assesses impacts of mining activities on the groundwater resources and potential human health risks in the coal mining areas of Ib valley coalfield. In this perspective, a total of one hundred and two mine water and groundwater samples were collected from different locations. The water samples were analysed for some selected heavy metals i.e. Mn, Cu, Pb, Zn, Ni, Co, As, Se, Al, Sr, Ba, Cd, Cr, V and Fe using ICP-MS. In addition, pH and SO42- concentration were also measured following APHA procedure. The water pH in the Ib valley coalfields ranged from 3.26 to 8.18 for mine water and 5.23 to 8.52 for groundwater, indicating acidic to alkaline nature of water. Mn in mine water and Zn in groundwater environment were observed as the most dominant metals. The water hazard index (WHI) reflects that around 80% of mine water are non-toxic (WHI<5), 5% slightly toxic (510) and 15% extremely toxic (WHI>15). Relatively high pH and low concentration of dissolved metals and SO42- in groundwater as compared to mine water indicate lesser impact of mining activities. The calculated drinking water quality index (DWQI) suggests that Mn, Al, Ni and Fe in mine water and Mn, Fe, Ni and Pb in groundwater were the major objectionable metals which caused the water quality deterioration for drinking uses. Further, the non-carcinogenic health risk assessment for adult male, female and child populations identifies Co, Mn, Ni as the key elements making the water hazardous for human health. Comparatively higher ratio of ingestion rate and body weight in child population might be causing higher health risks in child population as compared to adult male and adult female population.

Analysis of changes in nutrient salts and other water quality indexes in the pond water for largemouth bass (micropterus salmoides) farming.

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.

Identifying susceptible groundwater contamination zones in western Odisha of India using hydro-geochemical and geospatial approaches.

Nuapada is one of the most drought-affected and fluoride-contaminated districts in Odisha, India. The presence of various dissolved substances, evapotranspiration, and lowering water table during pre- and post-monsoon (PRM and POM) seasons are responsible for declining groundwater (GW) quality over the Nuapada region. To comprehend the contaminated GW zones over the Nuapada and Komna blocks of the northern Nuapada district during the seasons, integration of hydrogeochemistry and statistical approaches using GW sample data on a geospatial platform have been done. The analysis exhibits that the major source of groundwater contamination is mostly geogenic with little anthropogenic impact. The cumulative impact of fluoride (F-), iron (Fe2+), and nitrate (NO3-) contents are noticed in great-depth zones of the water table in the north and south parts of Nuapada and Komna blocks, respectively. The dominant hydro facies, such as Na-Cl (41.77%) and Ca-Cl (25.31%) types exist over both blocks during PRM and POM seasons, respectively. Demarcation of contaminant and susceptible zones over the study area using geospatial analysis and groundwater quality indices (GWQI) were done. About 3% of the total area, in the north and middle parts of the Nuapada and Komna blocks, falls under contamination zones and is unfit for drinking purposes, and about 35% of the region is susceptible to future contamination. The outcome of the result analysis will enhance the scope for researchers, policymakers, and water managers to regulate emerging health, agricultural, and industrial issues in the stressed aquifer system in India and the world.

Assessment of human health risk from potentially toxic elements and predicting groundwater contamination using machine learning approaches.

The Rooppur Nuclear Power Plant (RNPP) at Ishwardi, Bangladesh is planning to go into operation within 2024 and therefore, adjacent areas of RNPP is gaining adequate attention from the scientific community for environmental monitoring purposes especially for water resources management. However, there is a substantial lack of literature as well as environmental datasets for earlier years since very little was done at the beginning of the RNPP's construction phase. Therefore, this study was conducted to assess the potential toxic elements (PTEs) contamination in the groundwater and its associated health risk for residents at the adjacent part of the RNPP during the year of 2014-2015. For the purposes of achieving the aim of the study, groundwater samples were collected seasonally (dry and wet season) from nine sampling sites and afterwards analyzed for water quality indicators such as temperature (Temp.), pH, electrical conductivity (EC), total dissolved solid (TDS), total hardness (TH) and for PTEs including Iron (Fe), Manganese (Mn), Copper (Cu), Lead (Pb), Chromium (Cr), Cadmium (Cd) and Arsenic (As). This study adopted the newly developed Root Mean Square water quality index (RMS-WQI) model to assess the scenario of contamination from PTEs in groundwater whereas the human health risk assessment model was utilized to quantify the risk of toxicity from PTEs. In most of the sampling sites, PTEs concentration was found higher during the wet season than the dry season and Fe, Mn, Cd and As exceeded the guideline limit for drinking water. The RMS score mostly classified the groundwater in terms of PTEs contamination into "Fair" condition. The non-carcinogenic risks (expressed as Hazard Index-HI) revealed that around 44% and 89% of samples for adults and 67% and 100% of samples for children exceeded the threshold limit set by USEPA (HI > 1) and possessed risks through the oral pathway during dry and wet season, respectively. Furthermore, the calculated cumulative HI score was found higher for children than the adults throughout the study period. In terms of carcinogenic risk (CR) from PTEs, the magnitude of risk decreased following the pattern of Cr > As > Cd. Although the current study is based on old dataset, the findings might serve as a baseline for monitoring purposes to reduce future hazardous impact from the power plant.