Search

The study was carried out in the Phewa Lake of Pokhara Metropolitan City, Gandaki Province, Nepal, for geochemical assessment and characterization of the lake water quality. A total of 28 water samples were collected in each season from the different zones of the lake in March 2022 (pre-monsoon) and November 2022 (post-monsoon). The lake exhibited elevated levels of PO43−, NO3−, and NH3, indicating that anthropogenic activities are interfering the lake water. The significant differences in many monitored physicochemical parameters between the pre- and post-monsoon visualize dilution effect in the lake during post-monsoon. Piper diagram illustrates that the majority of water samples in the lake are of Ca–HCO3 type. Additionally, Piper diagram, Gibbs diagram, and Mixing plot illustrate that carbonate weathering is dominant in both seasons. Principal component analysis (PCA) reveals significant correlations among NO3−, SO42−, Na+, and Cl−, demonstrating that pollution in the lake water is attributed to agricultural activities and domestic effluents. In the majority of samples, water quality index (WQI) depicts that the lake water quality is very poor to poor in the pre-monsoon and poor to good in the post-monsoon. Sodium absorption ratio (SAR), % Na (percent sodium), electrical conductivity (EC), cation ratio of soil structural stability (CROSS), and United States Salinity Laboratory (USSL) diagram illustrate that the lake water is suitable for irrigation. [ABSTRACT FROM AUTHOR]

Monitoring water quality is a helpful tool for assessing the effects of pollution sources, ensuring effective management of water resources, and preserving aquatic life in surface water bodies. Hence, the present study focussed on evaluating the water quality of thirty-four selected lakes in Chikkaballapura taluk by characterizing physico-chemical parameters, Dissolved oxygen levels, organic loads (viz., BOD and COD) and WQI. The TDS level in the study area was well within the tolerance limit of 1500 mg/L, illustrating medium salinity (viz., electrical conductivity) in lake water. None of the lakes in the study area recorded nitrate concentrations above the tolerance limit of 50 mg/L during either season. Kolavanahalli and Varamallenahalli lakes witnessed nitrate levels of over 40 mg/L, while the pooled mean phosphate concentration was 0.40 mg/L during the study periods. High organic load in terms of COD was witnessed in selected lakes, as revealed by their ranges 64.0-144.0 mg/L (mean: 98.6 mg/L) and 60.8-136.0 mg/L (mean: 91.7 mg/L), respectively, during the pre- and post-monsoon seasons. Despite organic load, dissolved oxygen concentration ranged from 4.45-6.10 mg/L and 4.25-5.88 mg/L during these seasons, well above the desirable 4.0 mg/L limit. The present study also demonstrated the contribution of phosphate and nitrates towards organic loadings (viz., BOD and COD), illustrating increased anthropogenic contribution like entry of raw sewage, agricultural runoff, and others. Irrigation suitability was observed for most lakes, as revealed by their SAR, percent sodium and RSC values. [ABSTRACT FROM AUTHOR]

Due to water shortages and the potential impact of Ethiopia’s new dam on the Nile River, Egypt is seeking new water resources. This study assesses the drinking water quality and associated risks from potentially toxic elements (PTEs) in the Quaternary aquifer (QA) in Beni-Suef, Egypt. Using a comprehensive approach, including PHREEQC geochemical modeling, ionic ratios, multivariate statistical analyses, and the integrated weight water quality index (WQI), the study evaluated the sources of ion contamination and the mixing of Nile water with QA. Various indices, such as the Heavy Metal Pollution Index (HPI), ecological Risk Index (RI), Hazard Quotient (HQ), and Hazard Index (HI), were used to assess ecological and health risks. Monte Carlo simulations provided probabilistic assessments of non-carcinogenic risks for adults and children. GIS tools were used to map risk indices, identifying the most deteriorated locations for sustainable management. The hydrochemical analysis revealed water facies including Na–Cl, Ca–Mg–HCO3, and mixed types, influenced by carbonate dissolution, ion exchange, and silicate weathering. Contamination sources, particularly in the north and south, were linked to agricultural activities, irrigation return flow, municipal waste, and evaporation. The WQI indicated that 10.14% of samples were extremely poor, 21.7% were poor, 26% were medium, and 42% were good to excellent. PTE contamination varied, with HPI values indicating good water quality in the central area in 53.6% of the collected samples (HPI < 30), but contamination in the north and south is high (HPI > 51). Ecological Risk Index values were below the threshold in 100% of samples (RI < 30), confirming water safety regarding PTEs. In comparison, for hazard index (HI) through oral/ingestion, adults exhibited HI values ranging from 0.012 to 2.16, while children showed higher values, ranging from 0.045 to 8.25. However, the hazard index for oral/ingestion exceeded safe limits in the north and south (HI oral > 1), posing non-carcinogenic risks. Monte Carlo simulations revealed significant risks from oral exposure to manganese (HQ oral > 1), particularly in El-Wasta and El-Fashn, necessitating further treatment and management. [ABSTRACT FROM AUTHOR]

The majority of spring water from the limestone layers near the surface is suitable for various domestic, agricultural, and industrial uses and typically requires minimal purification. The springs from the highland areas of Zawitah, Baidol, Belkev, Atrush, and Khans converge to form the Komel River, the largest tributary of the Al-Khazer River. The Komel River flows along the right side of Mount Bardrash. The rainfall and snow accumulation in the Komel River basin, particularly in the hilly areas, contribute to its spring water sources. The physical and chemical characteristics of the water were assessed using the water quality index (WQI), in accordance with the WHO standard values. Generally, the water is suitable for irrigation, as indicated by the sodium adsorption ratio (SAR) values, which suggest that the water is low in sodic content and classified as Class S1. Additionally, the sodium percentage (SSP) is less than 75%, the magnesium adsorption ratio (MAR) is below 50%, and the residual sodium carbonate (RSBC) values are less than 1.25. These indicators reflect low calcium and magnesium bicarbonate sedimentation from irrigation water and minimal sodium concentration increases, reducing the risk of soil damage. The permeability index (PI) classifies the water as suitable for irrigation (Class II), and the Kelly's ratio (KR) values are below 1.0. The study concludes that the water quality of the Komel River is comparable to spring water, making it suitable for both domestic and agricultural use. This supports the establishment of water harvesting operations in the secondary valleys of the Komel River basin, particularly in the hilly regions. Additionally, irrigation projects can be developed in the downstream plain areas due to the favorable topographic slope. [ABSTRACT FROM AUTHOR]

The Water Quality Index (WQI) is a tool designed to provide a singular figure representing the overall water quality status of a water body. This study applies Malaysia WQI, National Sanitation Foundation WQI (NSFWQI) and statistical analysis to investigate the impact of diverse pollution sources on the Brunei River's water quality, a critical aquatic ecosystem affected by the rapid escalation of urbanization, industrial activities, and agricultural runoff. Principal component analysis (PCA), expert judgement, and correlation analysis were used to propose parameters for developing Brunei River's WQI. Eight monitoring stations were selected to analyze 16 water quality parameters (pH, water temperature (T), dissolved oxygen (DO), oxidation-reduction potential (ORP), chemical oxygen demand (COD), the five-day biochemical oxygen demand (BOD5), salinity, electrical conductivity (EC), total dissolved solids (TDS), turbidity, total suspended solids (TSS), ammoniacal-nitrogen (NH3-N), fecal coliform (FC), total coliform (TC), phosphate and nitrate (NO3−) in this study. The results showed that NSFWQI classified the Brunei River as moderately polluted, while Malaysia (WQI) status was classified as slightly polluted except for Station Q around the quarry area. Statistical analysis revealed that the primary pollution sources are anthropogenic activities such as quarrying, domestic waste, and agricultural and urban runoff. Other specific areas of concern with low WQI and significant pollution levels are situated at Kampong Ayer Stations (N and J) due to proximal anthropogenic activities. The proposed water quality parameters for developing Brunei River's WQI are pH, DO, EC, FC, NO3−, BOD5, T, TSS, turbidity and phosphate. This study addresses the current pollution status of the Brunei River and sets a precedent for future research emphasizing collaborative data-driven strategies for water quality management. [ABSTRACT FROM AUTHOR]

Copyright of Environmental Quality Management is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A field study was conducted to evaluate groundwater pollution and determine its suitability for drinking and irrigation purposes in the districts of Shawan , Alton Kopre and Dibs district in Kirkuk Governorate(Fig1). Samples were collected from fifty-two wells during the September 2023. The chemical concentration of groundwater ( pH, EC, TDS, T.H,Ca+2, Mg+2, K+, Na+ SO4-2, CO3-2, HCO3-, NO3-, PO4-3, Cl-) were analyzed, also mathematical model WQI was measured to evaluate Water quality for irrigation and drinking. ArcGIS 10.4.1 software was used for figping spatial distribution of parameters.The results showed that the chemical characteristics of the well waters are within the permissible limits except of total hardness (T.H.) and electrical conductivity (EC), as 50.02% and 2.13% of the water in the study wells exceeded the permissible limits for drinking and irrigation in terms of hardness and electrical conductivity, respectively.As for dissolved cations, 13.67% of the total area exceeded the permissible limits for drinking only for calcium ions, and 25.71% exceeded the permissible limits for drinking and irrigation to magnesium ions, as for potassium ions, 4.35% of the study wells exceeded the permissible limits for irrigation. While the dissolved (negative) ions for all well water were within the permissible limits, with the exception of sulphate, phosphate, and nitrate ions, as 99.89% of the study well water was within the permissible limits for drinking, with the exception of wells W3 and W31, but all of them are suitable for irrigation with regard to sulphate ions. As for phosphate ions, 99.96% of the study well water exceeded the permissible limits for drinking only, while 46.82% was not suitable for irrigation regarding to nitrates.

Abstract Crop productivity relies on the quantity and quality of irrigation water, with groundwater quality playing a major role. Exploitation of groundwater for irrigation is slowly increasing in central districts of Odisha. A study was carried out in these areas to assess the groundwater quality for irrigation for sustainable use of the groundwater resources. This was done by developing a Water Quality Index (WQI) for eight parameters. The groundwater quality was assessed using a framework that utilised the entropy weight approach and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). This framework was employed to determine the relative proximity of each solution to the ideal solution. The TOPSIS range is divided into three categories: low quality (less than 0.1), medium quality (0.1–0.5), and good quality (0.5–0.9). The low-quality category has a percentage of 6.45%, categorized as poor quality and unfit for drinking and irrigation uses; the medium-quality category has 52.07%, and the good quality category has 41.47% of the area falls under the very good category. These parameters are essential when considering water usage for agriculture, especially in regions where farmers use fertilizers and pesticides extensively to enhance crop production.

In 2022, 23 piped water samples from Liaquatabad town were examined study for pH, TDS, turbidity, chloride, hardness, nitrate, and sulphate. Majority of these indicators, with the exception of TDS, hardness, and sulphate, complied with the standards given by WHO and NSDWQ. Ca > Mg > Pb > Fe > Ni > Cr > As were metals that were found in that order. E. coli was found in about 74% of the samples while MPN Technique's microbial assessment, which found that more than 70% of the samples were contaminated with faecal matter. Despite having adequate physico-chemical properties in 95.6% samples, the Water Quality Index (WQI) showed that they were unsafe for drinking due to metal contamination. The samples' microbiological quality was good in just 26% of them. Untreated sewage discharge, cross-contamination and presence of faeces were all blamed for the pollution in the samples and responsible for serious health dangers.

Groundwater is the main water source that is most widely used in the world, one of which is in Indonesia. One of the uses of groundwater is for consumption needs. Therefore, the groundwater used should have good water quality. For this reason, this study aimed to determine groundwater quality in Indonesia during the dry season and make recommendations for groundwater management policies. A total of 211 groundwater samples taken from springs, drilled wells, and dug wells spread across volcanic areas on the islands of Sumatra, Java, Bali, and Sulawesi were collected to test their quality in this research. The method used in this research consisted of 4 analyses: WHO threshold analysis, Piper Diagram, Water Quality Index (WQI), and statistical correlation and regression. Based on the analysis, it was discovered that 47 K+ samples, 1 Na+ sample, 5 Ca2+ samples, 1 Cl- sample, 115 HCO3- samples, 3 TDS samples, and 3 pH samples exceeded WHO standards. The results of the Piper triangle diagram analysis showed that the majority of groundwater in Indonesia falls into the Unpolluted Groundwater classification (categories D and G), and the results of the WQI analysis also showed that 98% of the groundwater in Indonesia analyzed falls into the excellent and good water categories. The results of statistical analysis of the parameters K+, Na+, Mg2+, Ca2+, SO42-, Cl-, HCO3-, TDS, and pH showed that all these parameters are strongly and positively correlated with the WQI value.

Around the world, groundwater supply is critical for vital needs such as drinking and irrigation. This work investigates groundwater in the carbonate aquifer of the Middle Miocene in the east El Minia area, Egypt. In this regard, thirty-two groundwater samples were collected. The water samples were analyzed for Ca2+, Mg2+, Na+, K+, Cl−, SO42−, NO3−, CO2−, HCO3−, Fe, Mn, Cd, As, Cr, Cu, and Pb. Groundwater has been evaluated using two methods, which are water quality index (WQI) and health risk assessment (HRA). The predominant groundwater is soft water, and the samples range in salinity from fresh to slightly salty. The groundwater mostly falls into the alkaline water type. All the groundwater samples under study are deemed low quality for human consumption due to water contamination. Fe, Mn, Cd, Cu, and Pb have high HQnc values, which can result in non-carcinogenic health issues in adults, while Mn, Cu, and Pb can give rise to non-carcinogenic health issues in children. [ABSTRACT FROM AUTHOR]

Despite high pollution levels in Indian rivers, a comprehensive study on the water quality index (WQI) remains elusive. WQI values were computed, and their classes were determined using six water quality parameters from an available decennial dataset (n = 3595) on Indian Rivers. This study aims to assess the spatial distribution of WQI values and their classes across Indian River systems while exploring the application of machine learning (ML) based models in predicting WQI classes using a reduced number of input parameters. Modeling experiments were designed on five models- Decision Tree (DT), Random Forest (RF), Gradient Boosted Trees (GBT), Artificial Neural Network (ANN), and Support Vector Machine (SVM) for predicting WQI classes. Each model was trained with input parameters and WQI classes with 2990 datasets. Testing of WQI classes by each model was made on 605 datasets under different framework sets. Models' performance metrics were evaluated by accuracy, weighted mean recall and precision, and F-score. Our study demonstrates that the two largest systems, Ganga and Brahmaputra, lie on the extremes of the WQI (mean) spectrum, reflecting the impact of contrasting population density, industrial activities, change in land-use-land-cover pattern, and agricultural use on the riverine WQI. Our modeling experiments underscore that with only three input parameters, GBT can predict WQI classes with > 80% of performance metrics. With only two input parameters, GBT, RF, and ANN, all can provide reliable estimates. Our study highlights that ML models can serve as decision-supporting tools for water resource policymakers and managers in making effective pollution control and water resource management decisions. [ABSTRACT FROM AUTHOR]

The Middle Western Cheliff plain hosts an important alluvial aquifer that is exploited for various uses including drinking water supply, irrigation and industry. This study aims to provide a hydrogeochemical characterisation of groundwater by using statistical methods and binary diagrams, as well as to evaluate the physico-chemical quality of groundwater by using the water quality index (WQI). Moreover, parametric indices such as SAR and %Na were used to evaluate the suitability of groundwater for irrigation. The hydrochemical approach based on results of 45 analyses of groundwater samples for the dry period 2019 enabled the determination of the most dominant chemical facies, which was chloride, sulphate, calcic and magnesium. The binary diagrams used indicated that the water-rock interaction and the evaporitic phenomenon are major geochemical processes that control the mineralisation of groundwater. The evaluation of groundwater quality for drinking water supply using WQI provided results with values ranging from 45.95 to 194.78, and above 60% of samples were classified into the category of excellent to good quality (WQI < 100), while the remaining 40% of water samples were classified in the category of poor quality for drinking (WQI > 100). However, the quality of groundwater is mostly acceptable for irrigation, mostly for plants with salinity-tolerant in drained soils. [ABSTRACT FROM AUTHOR]

Vamsadhara is a prominent river in north-western Andhra Pradesh. Without enough and reliable knowledge on the quality of the water, people utilize it for home and agricultural purposes quite a lot. This study aims to evaluate the quality of river water for agricultural and domestic consumption. Water samples from 10 sampling stations were collected during the pre and post-monsoon seasons of 2021, and the water quality index and agricultural indices were computed. The Water Quality Index was found to be satisfactory in both the seasons. Correlation and regression analyses are performed to understand the relationship between various hydrochemical parameters. The pre-season and post-season principal components were found to explain 81.3% and 78.9% of the total variance, respectively. The variables in both seasons are solely hydro-chemical and are believed to result from geological processes, suggesting geogenic sources. Water quality parameters for irrigation are within the limits. In irrigated soils, a higher growth of exchangeable Na is typically encouraged by elevated Mg levels. Water with a magnesium hazard level below fifty is considered suitable for irrigation. The Mg hazard was slightly excessive in most of the examined locations of the Vamsadhara River. The river water quality for irrigation is good to excellent, with exemptions from MH. Prioritizing effective sewage water treatment facilities before release into rivers. [ABSTRACT FROM AUTHOR]

The article focuses on assessing groundwater quality for drinking purposes in Malda District, India, using Water Quality Index (WQI) and Geographic Information Systems (GIS) techniques. Topics include the physicochemical characteristics of groundwater, the identification of hazardous elements and their impact on water quality, and the use of GIS to enhance spatial understanding and management of groundwater resources.

The article presents a study on groundwater quality assessment and the interrelationship between various physico-chemical parameters and potentially toxic element sin low-hills of Himachal Pradesh, India. Topics discussed include sampling of groundwater and analysis, seasonal groundwater quality parameters in district Sirmaur, and groundwater quality parameters in district Una.

Groundwater is the main water source that is most widely used in the world, one of which is in Indonesia. One of the uses of groundwater is for consumption needs. Therefore, the groundwater used should have good water quality. For this reason, this study aimed to determine groundwater quality in Indonesia during the dry season and make recommendations for groundwater management policies. A total of 211 groundwater samples taken from springs, drilled wells, and dug wells spread across volcanic areas on the islands of Sumatra, Java, Bali, and Sulawesi were collected to test their quality in this research. The method used in this research consisted of 4 analyses: WHO threshold analysis, Piper Diagram, Water Quality Index (WQI), and statistical correlation and regression. Based on the analysis, it was discovered that 47 K+ samples, 1 Na+ sample, 5 Ca2+ samples, 1 Cl-sample, 115 HCO3 - samples, 3 TDS samples, and 3 pH samples exceeded WHO standards. The results of the Piper triangle diagram analysis showed that the majority of groundwater in Indonesia falls into the Unpolluted Groundwater classification (categories D and G), and the results of the WQI analysis also showed that 98% of the groundwater in Indonesia analyzed falls into the excellent and good water categories. The results of statistical analysis of the parameters K+, Na+, Mg2+, Ca2+, SO4 2-, Cl-, TDS, and pH showed that all these parameters are strongly and positively correlated with the WQI value. [ABSTRACT FROM AUTHOR]3-, TDS, and pH showed that all these parameters are strongly and positively correlated with the WQI value. [ABSTRACT FROM AUTHOR]

The main purpose of this study is to assess the urban lake water quality along the coastal region of Miri City, Sarawak, East Malaysia. This study concentrates on the hydrochemical characteristics and the mechanisms controlling the suitability of the lakes for domestic, irrigation, and industrial purposes. A total of 15 lake water samples were collected and analysed for physical parameters, major ions, nutrients, BOD, COD, and heavy metals. The results show that Lakes 6, 7, and 8 commonly exceeded the National Drinking Water Quality Standards (NDWQS) limits, particularly in physical parameters and major ions. The cation dominance was Na+ > Mg2+ > K+ > Ca2+, while the anion dominance was Cl− > HCO3− > SO42−. It is inferred that lake 8 was affected by the seawater intrusion through the inlet flow, resulting in an excess concentration of ions present in that lake. The concentrations of heavy metals in these lakes were considerably low, indicating that most of them were from the geogenic source. Most of the lakes were NaCl water type and the main controlling mechanism were weathering and ionic exchange processes, with anthropogenic impacts. Based on the calculated Water Quality Index (WQI) according to the National Water Quality Standards (NWQS), all lakes were suitable for irrigation use (class IV), while most of these lakes fell under the "polluted" index. Apart from that, based on the National Lake Water Quality Standards (NLWQS), all lakes were classified under category D, indicating that the lakes must be kept in good condition. According to the irrigation quality indices, lakes 1, 2, 3, 4, and 5 were the most suitable for irrigation purposes. As for metal pollution indices (HPI and HEI), lakes 1, 2, 3, 4, 5, and 15 were considered safe with low pollution status. From the multivariate statistical analysis, it is deduced that both anthropogenic and geogenic impacts mostly influenced the quality of these lake waters. The outcome of this study will help the policymakers under the national water department in sustainable management of water resources in this region. [ABSTRACT FROM AUTHOR]

As industrial development and population growth continue, water pollution has become increasingly severe, particularly in rapidly industrializing regions like the area surrounding the Yopurga landfill. Ensuring water resource safety and environmental protection necessitates effective water quality monitoring and assessment. This paper explores the application of advanced machine learning technologies and the Water Quality Index (WQI) model as a comprehensive method for accurately assessing groundwater quality near the Yopurga landfill. The methodology involves selecting water quality indicators based on available data and the hydrochemical characteristics of the study area, comparing the performance of Decision Trees, Random Forest, and Xgboost algorithms in predicting water quality, and identifying the optimal algorithm to determine indicator weights. Indicators are scored using appropriate sub-index (SI) functions, and six different aggregation functions are compared to find the most suitable one. The study reveals that the Xgboost model surpasses Decision Trees and Random Forest models in water quality prediction. The top three indicator weights identified are pH, Manganese (Mn), and Nickel (Ni). The SWM model, with a 0% overestimation eclipsing rate and a 34% underestimation eclipsing rate, is chosen as the most appropriate WQI model for evaluating groundwater quality at the Yopurga landfill. According to the WQI results from the SWM aggregation function, the overall water quality in the area ranges from moderately polluted to slightly polluted. These assessment results provide a scientific basis for regional water environment protection. [ABSTRACT FROM AUTHOR]

The aim of this research are to assess the feasibility of water and soil quality in silvofishery cultivation areas and to determine the environmental carrying capacity of the cultivation. The methods employed include Water Quality Index (WQI), Soil Quality Index (SQI), carrying capacity, and correlation analysis of parameters. The concentration of COD in the silvofishery pond water ranges from 705.34-749.50 mg.L-1, and the total nitrogen content in the soil ranges from 7-8 mg.L-1. The COD parameter in water shows a strong correlation with dissolved oxygen. The soil type parameter silt is correlated with redox potential, while the clay soil type is correlated with sand soil. The variance in data for water and soil quality variables is considered significant as per cluster analysis. The WQI values range from 0.47-0.85, categorized as poor, good, and excellent. The SQI values range from 0.52-0.77, falling into the good and excellent categories. The carrying capacity of dissolved oxygen ranges from 0.7-1.99 kg.ha-1, indicating that if the DO concentration is below this range, oxygen depletion may occur in the silvofishery pond. The research results indicate that the water and soil quality in the silvofishery pond is still sufficiently suitable for silvofishery activities. The carrying capacity of dissolved oxygen in the silvofishery pond is deemed adequate for operational silvofishery activities, ranging from 14.26-15.87 kg.ha-1. This implies that the silvofishery cultivation system is capable of enhancing aquaculture productivity while minimizing environmental pollution in the surrounding aquatic areas resulting from the waste generated during aquaculture operations. [ABSTRACT FROM AUTHOR]

In Büyük Akgöl, one of the most important lakes of Sakarya province in the Marmara region of Turkey, water and benthic sampling was carried out from five stations representing the lake seasonally between 2009 and 2010. As a result of the study, a total of 8736 individuals were collected from lake and that was a total of 24 species belonging to 36 taxa were identified. The benthic fauna community structure of the lake was classified with Turkish Biological Monitoring Working Party, Average Score Per-Taxon and Pielou's Evenness, Shannon–Wiener. According to the TR-BMWP scores were in the IV and the III class while the ASPT analysis was classified as moderate, and was as very poor. J' values ranged between 0.62 and 0.73, and H' values ranged from 1.74 to 2.14. The water quality parameters of the lake were classified as "unsuitable" by WQI and as "very polluted" according to HEI whereas the SAR, Na, and NPI were classified as 'excellent, good and no pollution.' According to the classification of water pollution control regulation it was showed 1st, 2nd and 3rd quality water characteristic. Pb, Hg, Al, Se, Cd concentrations and turbidity were exceeded the limit values set by WHO. [ABSTRACT FROM AUTHOR]

Present study deals with water quality (WQ) assessment season-wise ionic concentration in the Mewat district of Haryana, India. A total of 36 groundwater samples were collected, 12 each for the pre-monsoon, monsoon, and post-monsoon seasons of 2016, to know the status of WQ for drinking and irrigation purposes. Piper, Durov, and Gibbs plots were used to find out the water type and the factors controlling the chemistry of groundwater, respectively. Piper diagram reveals that Ca-Cl and mixed Ca–Mg-C1 typed water during the pre-monsoon, monsoon, and post monsoon season's where- Na-Cl water type indicates salinity problem. Gibb's plot depicted that the weathering of rocks is the major reason behind the ionic chemistry of the groundwater. Water Quality Index (WQI) has been calculated to know the overall WQ based on physico-chemical parameters estimated for this study. It was found that Na+ concentration was dominant among cations and Cl- among anions. Moreover, irrigation indices (KR, RSC, P.I, Cl–/HCO3–,SAR, and Na%) represent that majority of the groundwater samples during pre-monsoon (PRM) season were suitable for agricultural purposes but in monsoon (MON) and post monsoon (POM) season majority of samples lie in an unsuitable zone. The groundwater in the study region presents a high risk of salinization. Using the baseline data generated through this work, there is an immediate need for carrying out a detailed study to address the groundwater issues, understand salinity mechanisms, expansion of salinization in the fresh water aquifers and to suggest suitable management and remedial measures. Extension of this work is being carried out in the form of a purpose driven study under the National Hydrology Project aided by the World Bank. [ABSTRACT FROM AUTHOR]

One of the key landscapes on earth are the wetland ecosystems which are extremely crucial for the sustenance of various ecological realms as they provide immense ecosystem services to them. From serving impressive hosts to many organisms, particularly migratory birds, and successfully aiding in useful interactions between various biotic and abiotic components, wetlands have a remarkable repute. It has been a matter of only few decades that interaction of man with wetlands has resulted in severe degradation of these ecological repositories. Similar is the case of Pargwal wetland of lower Shivalik, located about 5 km from the international border in Akhnoor tehsil of Jammu and Kashmir division. Continuous interference from the human habitation, encroachment of wetland area, conversion into agricultural area, illegal sand mining, construction of cemented pillars for bridge, are just to name a few leading causes of its dwindling status. The present study is a data generated for seasonally for one year and assessment of the degrading parameters were made. Based on the water quality parameters, the wetland turned out moderately alkaline in nature and WQI showed poor water quality at all the study stations, depicting its deteriorating state. Also, aquatic insects that serve as important bioindicators were implemented for assessing the water quality using various biotic indices. Thus, a pioneer attempt has been made to decipher the causes of the continuing deterioration status of this immensely important wetland by analyzing its hydrobiology, which if not paid heed, will result in total territorialization of this intermediate water resource. [ABSTRACT FROM AUTHOR]

The seasonal water quality of the Surajpur wetland was analysed using 13 physicochemical parameters, including pH, TDS, EC, temperature, total hardness, total alkalinity, DO, BOD, phosphate, fluoride, nitrate, sulphate, and chloride employing standardized procedures. Fifteen samples were collected in triplicate from five distinct locations within the wetland. These samples were then compared to the BIS and WHO standards (2012). The analysis used titrimetric techniques to determine DO, BOD, total hardness, total alkalinity, and chlorides. Moreover, phosphate, sulphate, and nitrate were determined through UV-spectrophotometry. The wetland has an alkaline nature, the hydrogeochemical facies that dominate the surface water are Ca2+, Mg2+, HCO3, and Cl−. The results indicate that TDS, total alkalinity, phosphates, and fluorides exceeded the permissible limits. The evaluation of water quality in the study area was conducted through the implementation of the standard Water Quality Index (WQI), the Canadian Council of Ministers of the Environment Water Quality Index-(CCME-WQI) and the Comprehensive Pollution Index (CPI) and their associated parameters.. The CCME-WQI ranges from 46 to 53, indicating very poor/marginal water quality, the WQI value ranges from 82.80 to 96.18, indicating good water quality, while the CPI ranges from 0.9 to 1.15, indicating very poor/marginal water quality. The pH-EC and pH-TA, TDS-CPI, Cl-TH and the WQI-PO43− are negatively correlated at a significance level p < 0.01. The TA-EC, BOD-DO and TA-PO43− are negatively correlated at a significance level p < 0.05 as per the correlation matrix result. Using hierarchical cluster analysis, 5 sampling sites were divided into two clusters based on the similarity of water quality characteristics: comparatively less polluted and more polluted sites. The four principal components were identified using PCA, principal components contribute to 46.02%, 223.48%, 19.38% and 11.11%, of the total variance of the dataset respectively. The PCA indicate that the variation in water quality is due to anthropogenic activities around the vicinity of the wetland. In order to preserve the wetland's aesthetic value and ecological health, preventive measures such as de-weeding, preventing the infiltration of untreated sewage, and desilting are advised. Incorporating these measures can prevent potential damage to the wetland and ensure the survival of its ecology and aesthetic value. [ABSTRACT FROM AUTHOR]

The Tafna river serves as a model for assessing surface water and environmental quality by combining water quality and pollution indices using multivariate statistical methods. Thirty-six surface water samples were analyzed to assess 13 indicators. The results indicate contamination of the surface waters of the Tafna river by organic matter and the influence of lithology (presence of calcite), leading to an enrichment in Cl−, SO42−, and Ca2+ by dissolution (9.6–4.8 and 4.06 mg.l−1, respectively). During the summer and autumn, pH, electrical conductivity (EC), biochemical oxygen demand (BOD) reaching 57 mg.l−1, chemical oxygen demand (COD) at 90.9 mg.l−1, N-NH4+, and N-NO3− showed significant increases. In addition, the pollution index revealed the absence of pollution during winter and early summer but moderate levels of pollution in autumn. In addition, the spatial distribution of the water quality index (WQI) indicates good water quality in the estuary upstream to 54.94, but progressive deterioration upstream. However, analysis of the correlation matrix highlighted the influence of various sources, both natural and human, on surface water quality. In particular, a significant correlation (R2 = 0.9) was observed between Ca2+ and HCO3− concentrations, indicating a close relationship between these two elements. Organic pollution of the waters of the Tafna river has been strongly influenced by wastewater discharge and agricultural activities, which could lead to potential health risks if consumed. The results of this study provide a sound scientific basis to support decision-making and the implementation of measures to preserve and sustainably manage the Tafna river. [ABSTRACT FROM AUTHOR]

The present study was carried out to assess the water quality of Lakhota Lake. Objective water samples from five different sites were collected and analyzed from January 2023 to December 2024. Furthermore, the data obtained were processed to calculate the water quality index (WQI). The values obtained were compared with the guidelines for drinking purposes suggested by the World Health Organization and Bureau of Indian Standard. The results revealed that all the studied parameters were within the permissible limits except turbidity, TDS and EC, which exceeded the permissible limits. Among all the sites, site 5 was more heavily polluted than all the other sites. Among the heavy metals, iron was found above the permissible limits at Site 3, Site 4 and Site 5. Eight water quality parameters were used in the WQI approach to estimate the integrated groundwater quality. The WQI values ranged from 63.8 to 81.9, indicating that the Lakhota Lake water is not suitable for drinking water, including water from both humans and animals. At sites 1-4, the WQI falls in the poor category, while at site 5, it falls under the very poor category. There is a need for proper wastewater management in and around Lakhota Lake to protect the water quality and aesthetic properties of the lake. It is finally suggested that vegetation should also be planted at the boundaries of the lake, which will work as a natural purifier for the water of the lake. [ABSTRACT FROM AUTHOR]

The Water Quality Index (WQI) is an essential tool for monitoring trends, conducting scientific research, and making informed decisions. It offers a comprehensive view of the spatiotemporal variation in water quality in a watershed. Water quality data from various environmental assessment sources are often scattered and contain valuable information that researchers do not use. This study addresses the challenge of analyzing temporally and spatially dispersed monitoring data to assess water quality in riverine ecosystems over time. Our objective was to investigate fluctuations in water quality by constructing an aggregate water quality index, combining data from multiple public monitoring initiatives over 40 years in the Mediterranean region of central Chile, specifically in the Mataquito River Basin. Hydrochemical data were obtained from the measurement records available through the National Water Quality Monitoring Network of the Dirección General de Aguas of the Ministry of Public Works, integrating additional information from the water quality output station in the basin, which included sources from the Ministry of the Environment. Outliers for each parameter were removed and a data availability criterion was defined in relation to the total number of campaigns. Missing data were imputed to complete the matrix of water quality parameters. A total of 550 sampling campaigns provided 6624 water quality data points distributed across 10 chemical parameters and two chemical indicators, which were used to calculate the water quality index. The aggregation WQI water quality function was calculated using a modified additive method. Our research revealed that supplemented data offer valuable insights into evaluating water quality in the river ecosystems of the Andean watershed. In the lower zone, the water quality was determined to be good, while in the middle of the basin near the Andean Cordillera, it was considered acceptable. The analysis of the WQI over a decade indicated changes in water quality, irrespective of the station location in the watershed and the level of human intervention. The WQI values suggest a decrease in the water quality over the past 40 years. This study demonstrates that integrating information from diverse environmental monitoring sources into a WQI can be used to assess water quality trends and patterns in the Andean watersheds of Central Chile over time and space. These findings have significant implications for water management and decision making, providing a solid foundation for implementing appropriate strategies aimed at preserving water quality and ensuring water security in central Chile.

This study aims to create complete surface water quality maps for the Oum Er Rabia watershed by predicting nitrates (NO3-) and water quality index (WQI) values at unsampled locations. Utilizing a combination of NO3-, IQE data, and ArcGIS Pro software. Water samples were collected from 40 stations across the basin during twelve campaigns conducted in the winter and summer of 2021 and 2022. The database contains the analysis results of 12 parameters measured in 480 samples. The method used to model water quality is interpolation with ArcGIS Pro. The distribution map of Nitrate (NO3-) values for all samples shows concentrations ranging from 0.26 to 38.89 mg/L. These values are lower than the admissible level recommended by the Moroccan standard for drinking water (50 mg/L). The resulting map of the modeling shows higher NO3- concentrations in summur than in winter. The resulting map of the WQI modeling shows that water quality is excellent in most of the Oum Er-Rbia watershed, with the majority of the area falling into the "good" and "excellent" categories. The water quality deterio-rates in certain parts, especially at stations SS3, SS4, SS5, SS8, and PS9, where the water is of poor quality. In the central and eastern parts, the presence of excessively high ammonium concentrations has significantly compromised the water quality, leading to heavy pollution. Exceeding Moroccan drinking water standards, these observed levels likely stem from human activities. Accurate water quality predictions with ArcGIS Pro require considering data quality, historical trends, and spatiotemporal variations. Understanding these limitations ensures responsible and effective tool use. The study concluded that water pollution could be due to proximity to industrial and urban areas. This study's uniqueness lies in integrating the WQI, NO3-, and ArcGIS-Pro into maps. This approach makes information accessible to the public and useful for decision-makers to take action at all watershed points.

Groundwater is the most important natural resource, and many people throughout the world rely on it for drinking, particularly in rural areas. The present study was carried out to assess the status of groundwater quality and to check its suitability for domestic purposes in urban centres of Bahir Dar City, Ethiopia. Twelve shallow wells were selected for sampling. The sampled water was taken during the dry and summer seasons of the year 2019/2020. pH, turbidity, EC, TDS, chloride (Cl−), nitrate (NO3−), phosphate (PO4−3), total hardness, and Escherichia coli were measured for the suitability analysis. Comparison of measured results with those of WHO and Ethiopian drinking water quality standards was done. Moreover, Geographic Information System (GIS) and Water Quality Index (WQI) data analysis techniques were applied in order to investigate the groundwater quality. The spatial distribution map showed that the city's core area had the poorest groundwater quality status. The WQI result obtained from the analysis showed that 41.67, 33.33, and 25% of the sampled groundwater has low, extremely poor, and unsafe quality for drinking purposes, respectively. The present study revealed that anthropogenic activities have a great impact on the quality of groundwater in the area, necessitating immediate mitigating actions. HIGHLIGHTS Anthropogenic activities influence the quality of groundwater.; The groundwater quality is fully contaminated with fecal coliforms.; The WQI and GIS techniques show a majority of the city groundwater is unfit for drinking purposes.; The highest concentration occurred in the central and mid-southern regions of the surveyed field.;

The traditional wastewater treatment process is laborious and demanding in terms of time, energy, and space. With rapid advancements, there's a quest for more efficient techniques that can achieve comparable treatment outcomes while minimizing these demands. This study proposes a solution by employing ozone as an Advanced Oxidation Process (AOP) to expedite the treatment while enhancing the water quality. The Water Quality Index (WQI) offers a consolidated representation of overall water quality by considering multiple quality parameters. Although typically used for assessing surface water quality, this study utilizes WQI to gauge the enhancement in parameters post-treatment. The research investigates the impact of varied ozone doses on raw sewage samples collected from four different sites in Mumbai, focusing on parameters such as dissolved oxygen, turbidity, hardness, chemical oxygen demand (COD), and WQI. The results demonstrate a notable percentage enhancement in WQI, ranging from 30 to 60% across various sites within a short 25-minute timeframe, attributed to the application of ozone. HIGHLIGHTS Conventional wastewater treatment methods are time-consuming and resource-intensive.; AOP is proposed as a solution to expedite treatment and improve water quality.; Normally used for surface water assessment, WQI is employed here to measure improvements post-treatment.; Study examines varied ozone doses on sewage samples from Mumbai, analyzing parameters like DO, turbidity, hardness, COD, and WQI.; Significant enhancements in WQI (30–60%) within 25 minutes demonstrate ozone's promise in reducing treatment time and space requirements, with simplified installation and maintenance compared to traditional methods.;

This study aimed to assess spatiotemporal water quality variation and its suitability for irrigation and domestic purposes in Lah River using the irrigation water quality index (IWQI) and the weighted arithmetic water quality index (WAWQI). The IWQI analysis result showed that the sodium absorption ratio, residual sodium carbonate, potential salinity, Kelly index, magnesium ratio, sodium percentage, and permeability index were found to be 1.07 mEq/L, −0.43 mEq/L, 0.8 mEq/L, 0.78 mEq/L, 43.01%, 42.95%, and 63.46%, respectively. The IWQIs revealed that the water quality of the river was appropriate for agricultural use during the dry season. Furthermore, the calculated WAWQI of the river water ranged from 123.13 to 394.72 during the wet season, indicating the high pollution levels in the Lah River and incompatibility for drinking purposes. On the other hand, the principal component analysis identified two pollution sources during the wet season and three during the dry season. In addition, the positive matrix prioritization model predicted the pollution source's contribution quite well with a signal-to-noise ratio of >2 and a residual error between −3 and 3 for both seasons. This study suggests that water quality of Lah River is degrading periodically necessitating proper pollution management. HIGHLIGHTS In this study, water quality and its suitability were assessed using multivariate statistical techniques and receptor models conjunctively.; The middle segment of the Lah River is more polluted than the upstream and downstream sections necessitating coordinated intervention measures.; During the dry season, the Lah River is suitable for irrigation.; Integrated water quality index and multivariate statistical techniques can be used for preliminary pollution management in Lah River.;

Abstract The groundwater quality of the Gopalganj district in Bangladesh was not well documented. Therefore, this research was done to determine the groundwater quality in the study area. The water quality index and the human health risk for heavy metal ingestion were used to describe the water quality. The water quality was performed through the estimation of turbidity, pH, electrical conductivity, total dissolved solids, and concentration of sodium, potassium, ammonium, nitrate, iron, manganese, zinc, copper, and arsenic. The mean turbidity, pH, and total dissolved solids in the two upazila were within the permissible limit. However, the electrical conductivity in both the upazila was higher than the WHO-prescribed value in which the higher concentration was in Kotalipara. Excess concentrations of iron and arsenic were found in the Kashiani upazila, but these were below the detection limit in Kotalipara upazila. The water quality index revealed that roughly 61.0% of samples of Kashiani upazila were of poor quality. However, about 96.0% of samples of Kotalipara upazila were of excellent quality. Chronic health risks due to the revelation of drinking have also been determined by assessing the hazard quotient and hazard index. In Kashiani, almost 85.0% of samples were elevated chronic risks for adults and 100.0% of the samples were very high chronic risks for children. In Kotalipara, all the samples (almost 100%) were suggested to have a lower chronic risk for adults and children. The results suggested that the carcinogenic risk of arsenic via oral exposure was very high for both adults and children in Kashiani upazila.

Assessing the quality of water resources and having accurate information about their quantity and quality is a prerequisite for water resources management. Considering the importance of the Chahnimeh reservoirs of the main source of drinking and agricultural water supply in Sistan, it seems necessary to evaluate the water quality of the No.1 Chahnimeh, which is the most important and the largest lake among the triple Chahnimeh reservoirs. Today, one of the most important methods to determine the quality of water in simple terms is the use of water quality indicators. This research was conducted during one year based on seasonal sampling from September 2020 to September 2021. The factors of nitrate, nitrite, dissolved oxygen, electrical conductivity, hardness, and pH were measured in eight sampling stations and the WQI index was calculated using them. In general, according to the numbers of the water quality index, the water quality in all stations, and sampling periods has not gone out of the range of good quality waters (50-100), and the range of changes is such that the water quality is favorable for human use. The highest numerical value of the quality index was recorded in the winter. The middle points of the lake have better quality compared to the peripheral parts and the inlet and outlet of the reservoir. It is worth noting that due to the increasing importance of Chahnimeh reservoirs and the trend of changes in the type of water consumption of these valuable resources, it seems necessary to carry out more detailed investigations, continuously evaluate and monitor the water quality, and design a water quality monitoring model for these sources.

The present study aimed to assess the impact of anthropogenic stressors on the physico-chemical characteristics and water quality of the River Ganga employing a GIS-based approach in the middle Gangetic Plain at Patna, India. After the survey, sand mining, bridge construction, and disposal of untreated domestic and sewage wastes were selected as major anthropogenic stressors. A total of 48 samples were collected in pre-monsoon and post-monsoon seasons of 2022 and were analyzed for 16 physico-chemical parameters, namely water temperature (WT), pH, electrical conductivity (EC), total dissolved solids (TDS), turbidity, dissolved oxygen (DO), biological oxygen demand (BOD), total hardness (TH), Ca2+, Mg2+, Na+, K+, Cl- and SO42− ions, following standard protocols. The WQI was calculated using the Weighted Arithmetic Water Quality Index (WAQWI) method and spatial maps were created using ArcGIS software. The result revealed significant seasonal variation in several physico- chemical parameters except for Ca2+, K+ and TA (p > 0.05). ANOVA revealed significant variation for BOD and COD at Ghagha and Triveni, whereas for nitrate at Gai Ghat reference and impact sites, respectively. The Water Quality Index (WQI) revealed a deterioration in water quality by 60% in post-monsoon season. HCA revealed that the WQI was mostly governed by TDS, TH, TA, and EC. HIGHLIGHTS The study highlights the impact of anthropogenic stressors on the River Ganga water quality in Patna India.; Sand mining, sewage disposal and bridge construction activities were selected as major anthropogenic stressors.; Significant seasonal variation was observed for several physico-chemical parameters.; Water quality deteriorated from pre-monsoon to post-monsoon season.; WQI of the River Ganga is primarily governed by TDS, TH, TA and EC.;

The water quality index (WQI) is an important tool for evaluating the water quality status of lakes. In this study, we used the WQI to evaluate the spatial water quality characteristics of Dianchi Lake. However, the WQI calculation is time-consuming, and machine learning models exhibit significant advantages in terms of timeliness and nonlinear data fitting. We used a machine learning model with optimized parameters to predict the WQI, and the light gradient boosting machine achieved good predictive performance. The machine learning model trained based on the entire Dianchi Lake water quality data achieved coefficient of determination (R2), mean square error, and mean absolute error values of 0.989, 0.228, and 0.298, respectively. In addition, we used the Shapley additive explanations (SHAP) method to interpret and analyse the machine learning model and identified the main water quality parameter that affects the WQI of Dianchi Lake as NH4+-N. Within the entire range of Dianchi Lake, the SHAP values of NH4+-N varied from −9 to 3. Thus, in future water environmental governance, it is necessary to focus on NH4+-N changes. These results can provide a reference for the treatment of lake water environments. HIGHLIGHTS The water quality of Dianchi Lake at the entry point is better than that at the exit point.; An interpretable machine learning model for predicting water quality index has been proposed.; NH4+-N is the main parameter affecting the water quality of Dianchi Lake.;

Groundwater, an invaluable resource crucial for irrigation and drinking purposes, significantly impacts human health and societal advancement. This study aims to evaluate the groundwater quality in the Mnasra region of the Gharb Plain, employing a comprehensive analysis of thirty samples collected from various locations, based on thirty-three physicochemical parameters. Utilizing tools like the Pollution Index of Groundwater (PIG), Nitrate Pollution Index (NPI), Water Quality Index (WQI), Irrigation Water Quality Index (IWQI), as well as Multivariate Statistical Approaches (MSA), and the Geographic Information System (GIS), this research identifies the sources of groundwater pollution. The results revealed Ca2+ dominance among cations and Cl− as the primary anion. The Piper and Gibbs diagrams illustrated the prevalent Ca2+-Cl− water type and the significance of water–rock interactions, respectively. The PIG values indicated that 86.66% of samples exhibited "Insignificant pollution". NPI showed notable nitrate pollution (1.48 to 7.06), with 83.33% of samples rated "Good" for drinking based on the WQI. The IWQI revealed that 80% of samples were classified as "Excellent" and 16.66% as "Good". Spatial analysis identified the eastern and southern sections as highly contaminated due to agricultural activities. These findings provide valuable insights for decision-makers to manage groundwater resources and promote sustainable water management in the Gharb region. [ABSTRACT FROM AUTHOR]

The groundwater quality of the Gopalganj district in Bangladesh was not well documented. Therefore, this research was done to determine the groundwater quality in the study area. The water quality index and the human health risk for heavy metal ingestion were used to describe the water quality. The water quality was performed through the estimation of turbidity, pH, electrical conductivity, total dissolved solids, and concentration of sodium, potassium, ammonium, nitrate, iron, manganese, zinc, copper, and arsenic. The mean turbidity, pH, and total dissolved solids in the two upazila were within the permissible limit. However, the electrical conductivity in both the upazila was higher than the WHO-prescribed value in which the higher concentration was in Kotalipara. Excess concentrations of iron and arsenic were found in the Kashiani upazila, but these were below the detection limit in Kotalipara upazila. The water quality index revealed that roughly 61.0% of samples of Kashiani upazila were of poor quality. However, about 96.0% of samples of Kotalipara upazila were of excellent quality. Chronic health risks due to the revelation of drinking have also been determined by assessing the hazard quotient and hazard index. In Kashiani, almost 85.0% of samples were elevated chronic risks for adults and 100.0% of the samples were very high chronic risks for children. In Kotalipara, all the samples (almost 100%) were suggested to have a lower chronic risk for adults and children. The results suggested that the carcinogenic risk of arsenic via oral exposure was very high for both adults and children in Kashiani upazila. [ABSTRACT FROM AUTHOR]

The issue of water contamination in reservoirs and watersheds due to the irregular use of fertilizers and uncontrolled occupation by riverside populations has worried managers operating hydroelectric plants. The increase in the levels of certain physical–chemical parameters causes problems of accelerated deterioration of equipment and clogging of water pipes. Within this context, here we estimate a specific water quality index (WQI) for hydroelectric plants. The novelty of this article is to use expert consultation to select the most critical parameters that cause damage to the dam structures and mechanical equipment. We propose a method carried out in three steps: selection of specific parameters for hydropower plants and fuzzy MCDA estimation of their weights; fuzzification of sub-indices; and estimation and classification of the WQI. In this last step, the sub-indices are defuzzified and weighted for classification according to the degree of membership in a fuzzified scale. Fuzzy logic deals with variables that do not allow objective classification, given that the limits between classes are imprecise or non-statistical, such as the parameters analyzed in this study. These thresholds are fuzzy numbers, so the treatment of the sub-indices must follow this logic. We obtained a specific classification for the water quality upstream of the Corumbá IV Hydroelectric Plant, located in the central region of Brazil. Observing the individual ratings of each parameter obtained before aggregation, although producing results for drinking water set by Brazil's National Environmental Council, presents concentrations of some parameters that, if not controlled, could harm the hydroelectric plant. [ABSTRACT FROM AUTHOR]

The Ganges Riverine System is a vital ecological hotspot that supports diverse habitats and sustains numerous species, including zooplankton communities crucial for the ecosystem's functioning. However, rapid urbanization, industrialization, and agricultural activities have led to substantial anthropogenic impacts on this ecosystem, raising concerns about its ecological integrity and biodiversity. Preliminary findings indicate significant alterations in habitat ecology, including changes in water quality parameters such as dissolved oxygen levels, pH and nutrient concentrations, attributable to anthropogenic activities. Total eight sampling zones were selected to assess water quality and zooplankton diversity in the upper Ganga River and its major tributaries between September, 2021 and September, 2023. There were four major groups of zooplankton recorded in the selected sampling zones: Cladocera (5 genera), Copepoda (4 genera), Protozoa (3 genera) and Rotifera (3 genera). Despite the fact that Cladocera was dominating in sampling zone 7 and 8, Copepoda was leading in the rest of the sampling zones 4, 5, 6, 7 and 8, as well as Rotifera was leading in sampling zone 2 and 4, while Protozoa was leading in sampling zones 4, 6 and 7. Moreover, habitat degradation, fragmentation and loss were observed, primarily associated with land-use changes, urban expansion and agricultural intensification. Furthermore, continued monitoring and research efforts are essential to better understand the complex interactions between anthropogenic stressors and ecological dynamics, facilitating informed decision-making for ecosystem conservation and restoration in the Himalayan region. The present study also demonstrated that the water quality was acceptable for sustaining aquatic biodiversity in the upper Ganga basin. [ABSTRACT FROM AUTHOR]

The crux of groundwater protection lies in a profound understanding of the sources of pollutants and their impacts on human health. This study selected 47 groundwater samples from the Fengshui mining area in central Shandong Province, China, employing advanced hydrogeochemical techniques, positive matrix factorization (PMF), and Monte Carlo analysis methods, aimed at unveiling the characteristics, origins, and health risks of water pollutants. The results indicated that the majority of samples exhibited a slightly alkaline nature. Notably, the concentrations of fluoride (F−) and nitrate (NO3−) exceeded China's safety standards in 40.43% and 23.40% of the samples, respectively. Moreover, a water quality index (WQI) below 50 was observed in approximately 68.09% of the sites, suggesting that the water quality in these areas generally met acceptable levels. However, regions with higher WQI values were predominantly located in the northern and southern parts of the mining area. PMF analysis revealed that regional geological and industrial activities were the primary factors affecting water quality, followed by mining discharges, fundamental geological and agricultural processes, and leachate enrichment activities. The health risk assessment highlighted the heightened sensitivity of the youth demographic to fluoride, with a more pronounced non-carcinogenic risk compared to nitrate, affecting about 31.89% of the youth population. Hence, it is imperative for local authorities and relevant departments to take prompt actions to remediate groundwater contamination to minimize public health risks. [ABSTRACT FROM AUTHOR]

The water quality index (WQI) is a globally accepted guideline to indicate the water quality standard of any groundwater resource. Water levels in existing groundwater sources are declining in several coastal zones. Therefore, for monitoring water quality and improving water management, the prediction and identification of groundwater status by an effective technique with higher accuracy is urgently needed. Therefore, this research aims to find an effective model for WQI prediction by comparing entropy and critic weight-based WQI (ENW-WQI and CRITIC-WQI) with multi-layer perceptron artificial neural network (MLP-ANN) technique and also to identify contaminated zones using GIS. Initially, 1000 water sampling datasets with concentrations of several water quality parameters of different coastal blocks of eastern India during 2018 to 2022 are considered for the estimation of ENW-WQI and CRITIC-WQI. It shows 65% and 67% of the samples are excellent to good for drinking. ENW-WQI and CRITIC-WQI-based MLP-ANN models have been established considering different data portioning and hidden neuron numbers. Input variables and appropriate dataset partitioning with hidden neurons for models obtained from correlation and trial–error analysis. Spatial distribution maps are also produced for calculated WQIs using inverse distance weighted interpolation approaches. Three fitting models are obtained: ENW-WQI-MLP-ANN, CRITIC-WQI-MLP-ANN-I and CRITIC-WQI-MLP-ANN-II. CRITIC-WQI-MLP-ANN-II model (data ratio 85:15, network structure 6–12-1, R2 = 0.986, NSE = 0.98, and error rate 0.49%) provides the best accuracy in WQI prediction. The GIS-based WQI maps record several areas related to drinking water quality. The results of this research can help in planning the provision of safe drinking water in the future. [ABSTRACT FROM AUTHOR]

In developing countries, such as Brazil, public policies for monitoring surface water quality are precarious. Although the country has legal norms that establish water quality parameters, and the Water Quality Index (WQI) is used as an assessment tool, the management of surface water is neglected in cities such as Manaus. The objective of this study was to evaluate the water quality of the São Raimundo basin in Manaus during the years 2020 and 2021. The following parameters were evaluated: dissolved oxygen (DO), thermotolerant coliforms (Colif), biochemical oxygen demand (BOD), pH, temperature (Temp), total nitrogen (Ntotal), total phosphorus (Ptotal), turbidity (Turb), and total solids (Sol.T). ANOVA showed that the water quality is constantly low, and in no period of either year did it present acceptable levels for use. The Colif result having a mean value of 96.7 × 103 NMP 100 mL−1 in the month of February 2020. October 2020 and 2021 presented the worst results for the WQI with values of 27.7 and 28.2, respectively. Multiple regression showed DO, Turb, BOD, and Ntotal as being the most significant parameters, which indicates that the pollution probably originates from sewers and industrial effluents. This is the first study to monitor the waters of the São Raimundo basin using this approach. The results show the need for urgent treatment of the water in the basin via environmental preservation and recovery measures. This type of study could thus result in changes in the management of the water in this basin as well as in similar ones present in the Amazon region. [ABSTRACT FROM AUTHOR]

- In Ghana, mining of minerals at small-scale and large-scale is widespread across many districts, leading to significant heavy metal pollution in the environment. In this study, the concentrations of iron (Fe), manganese (Mn), arsenic (As), and mercury (Hg) in the different drinking water samples collected from households, institutions, water points and surface water in two mining districts namely the Wassa East and Asutifi North were analyzed. The water types collected included boreholes, wells, piped water into yards, public standpipes, rainwater, sachet water, and surface water. The results indicated that the levels of Fe and Mn were higher than As and Hg in all the drinking water samples. The levels of As and Hg in drinking water from households and institutions were higher in the Wassa East district compared to the Asutifi North district. However, the metal levels at water points were similar in both districts. In surface water, Fe levels were higher in the Wassa East district compared to the Asutifi North district with median values of 1243 μg/L and 860 μg/L for the Wassa East and Asutifi North districts, respectively. In contrast, the Mn levels were higher in the Asutifi North district than the Wassa East district with median values of 9.5 μg/L and 90 μg/L for Wassa East and Asutifi North districts, respectively. All the metals (Mn, As, and Hg) studied except Fe were within the recommended WHO level. The Heavy Metal Pollution Index (HPI) values for the different water types in households, institutions and water points were all below the critical limit of 100. The Water Quality Index (WQI) indicates that the boreholes, piped water into yards, and public standpipes in both districts were classified as excellent or good, making them suitable for drinking. However, the wells and surface water in both districts were classified as very poor and unfit for drinking, respectively.

In Bangladesh, groundwater is the most widely used source of drinking water for rural communities. However, the groundwater quality is degraded by natural contaminants and anthropogenic pollution. Groundwater is a reliable and sustainable source of safe water for irrigation and domestic purposes, especially during the dry season. The water quality assessment data for the study area was not found in the literature. This study aims to assess groundwater quality and seasonal variation in a rural area of five unions of Bagatipara Upazila, Natore, and its suitability for drinking purposes by measuring the Water Quality Index (WQI). The groundwater of five unions, namely Dayarampur, Bagatipara, Faguardiar, Jamnagar, and Pacca, has been selected for investigation. The electrical conductivity (EC), color, and turbidity exceeded the ECR guidelines. EC showed a positive correlation with total dissolved solids (TDS), total solids (TS), and turbidity. On the other hand, dissolved oxygen (DO), hardness, chloride, carbon-di-oxide (CO2), and iron (Fe) concentrations varied based on the location of the sampling points. The bacteriological parameters TC and E. coli were found in most of the samples, which indicate the potential sources of contaminants such as septic tank leakage and inadequate waste disposal systems. The groundwater quality was found not to be influenced by seasonal variation except by pH, DO, and CO2. The Water Quality Index (WQI) spatial mapping demonstrated that during the post-monsoon period, the water quality of the central part of Bagatipara upazila was in ‘good’ condition, which was in Bagatipara, Fagurdiar, and Pacca unions, whereas during the pre-monsoon season, the ‘good’ condition was found very limited to Fagurdiar union only. The study revealed that the groundwater of Bagtipara Upazila is not suitable for drinking water due to the presence of TC and E. Coli as well as ‘poor’ to ‘unsuitable’ conditions in most of the areas based on WQI.

Water is essential for life, as it supports bodily functions, nourishes crops, and maintains ecosystems. Drinking water is crucial for maintaining good health and can also contribute to economic development by reducing healthcare costs and improving productivity. In this study, we employed five different machine learning algorithms – logistic regression (LR), decision tree classifier (DTC), extreme gradient boosting (XGB), random forest (RF), and K-nearest neighbors (KNN) – to analyze the dataset, and their prediction performance were evaluated using four metrics: accuracy, precision, recall, and F1 score. Physiochemical parameters of 30 groundwater samples were analyzed to determine the Water Quality Index (WQI) of Pano Aqil city, Pakistan. The samples were categorized into the following four classes based on their WQI values: excellent water, good water, poor water, and unfit for drinking. The WQI scores showed that only 43.33% of the samples were deemed acceptable for drinking, indicating that the majority (56.67%) were unsuitable. The findings suggest that the DTC and XGB algorithms outperform all other algorithms, achieving overall accuracies of 100% each. In contrast, RF, KNN, and LR exhibit overall accuracies of 88, 75, and 50%, respectively. Researchers seeking to enhance water quality using machine learning can benefit from the models described in this study for water quality prediction. HIGHLIGHTS Groundwater quality is evaluated using the Water Quality Index method.; Machine learning algorithms are used for forecasting groundwater quality.; The predictive capabilities of decision tree classifier, extreme gradient boosting, logistic regression, random forest, and K-nearest neighbors models have been evaluated and compared.;

This study, conducted in the Nanton District of Northern Ghana, assesses groundwater quality for drinking purposes and examines hydrochemical processes. We collected and analyzed 30 groundwater samples, evaluating their physicochemical properties, microbial content, microbial and physicochemical relationship, and hydrochemistry. Utilizing methods such as the weighted arithmetic water quality index (WQI), Gibbs and Piper diagrams, Stiff plots, scatter plots, and correlation matrices, we aimed to comprehensively understand groundwater quality in the district. Physicochemically, our findings indicate that approximately 83.3% of the groundwater is safe for direct consumption without treatment. However, microbial contamination was prevalent in all samples, rendering them unsafe. Parameters such as iron, manganese, color, turbidity, nitrates, sulfate, and pH were identified as potential influencers of microbial survival in the groundwater. Regarding major ions, sodium (Na+) dominated among cations, while bicarbonate (HCO3-) was the primary anion. Water types were categorized as Na-K-HCO3−, Na-K-Cl-SO42−, Ca-Mg-HCO3−, and mixed water, reflecting the hydrochemical composition. Our analysis revealed that rock weathering, evaporation, ion exchange, and human activities influence groundwater chemistry. We recommend further research to assess groundwater availability for sustainable development in the district. Additionally, continued research is encouraged to enhance our understanding of the correlation between coliform bacteria and physicochemical water parameters. HIGHLIGHTS Comprehensive groundwater assessment in the Nanton District of Ghana was studied.; Multi-faceted analytical approaches were done.; Identification of dominant contaminants and water types.; Insights into microbial and physicochemical parameters relationship in water.; Insights into factors affecting groundwater chemistry.;

Groundwater quality degradation is a pressing concern in semi-arid coastal regions, exemplified by the Ghiss-Nekor aquifer in northeastern Morocco, spanning 100 km². This study adopts a comprehensive approach, utilizing Chloro-Alkaline Indices, hydrochemical facies diagrams, the Water Quality Index (WQI), and the Synthetic Pollution Index (SPI) to assess groundwater quality and its evolution. Key findings reveal that Ghiss-Nekor groundwater is brackish, primarily suitable for irrigation due to high Total Dissolved Solids (TDS). Salinization stems from reverse cation exchange, as indicated by hydrochemical analyses. WQI assessments highlight the inadequacy of this groundwater for drinking purposes, with SPI classifying 54% of wells as moderately polluted. Fine particles mitigate marine intrusion in the northwest. Overlaying land-use and electrical conductivity maps identify areas with poor-quality groundwater, notably near an unregulated landfill, a coastal tourist site, and a wastewater treatment facility. Ionic analysis identifies multiple saline sources, with nitrate and sulfate contributions standing out. While the study offers valuable insights, limitations include the need for ongoing data collection and source identification challenges. Nonetheless, the research underscores the urgency of effective water management, particularly around the landfill site situated above permeable deposits, offering an innovative approach with global applicability for addressing groundwater quality issues in semi-arid coastal areas.

The water quality of Himalayan rivers has declined due to human activities, untreated effluent discharge, and poor sewage and drainage systems. The current study aimed to assess the water quality of these rivers using multivariate statistical analysis throughout four seasons. The analyses of 44 surface water samples taken during the monsoon, winter, spring, and summer seasons are well within the ranges acceptable for drinking and domestic use after the sedimentation. The suspended soils and turbidity are highly correlated and affect the water quality index (WQI). The WQI of headwater streams is good during low water flow seasons and poor during high water flow seasons. This is due to the number of melting glaciers and suspended solids/turbidity. Principal component analysis shows that in all the seasons, human activities such as road-cutting projects across the river and natural causes such as intense rainfall and melting of moraine-filled glaciers both impact the WQI. The findings of this study provide important information for future research and policy decisions aimed at improving the water quality of the Himalayan rivers. HIGHLIGHTS Water quality indices were calculated from physicochemical parameters across 15 sampling locations and four seasons (monsoon, winter, spring, and summer).; A strong positive correlation was observed between TSS-Turbidity, TA-TH, TSS-TA, and TSS-TH during different seasons.; Winter and spring showed WQI values ranging from good to poor, with pH, EC, TA, TH, and DO having less impact on WQI compared to turbidity and TSS.; PCA was used to identify latent variables affecting water quality parameters across different seasons.; The findings of this study provide important information for future research and policy decisions aimed at improving the water quality of the Himalayan rivers.;