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End-point evaluation of stream health is essential for the quantification of water quality. To this end, many Multi-Metric Indices (MMIs) have been developed to quantify water quality. The most extensive work has occurred in North America and Europe, while other areas of the world are in development. In this study, we compared the use of relevant physical, chemical and biological parameters in MMIs to various other stream health indicators to assess water quality throughout a three-river corridor along the north central Pacific slope of Costa Rica. Analysis of the data suggested MMIs were the best indicators of water quality and, more specifically, insect MMIs were the most predicative. MMIs were also best at pinpointing anthropomorphic impact throughout the corridor. Further, less complex insect MMIs such as compilations of family diversity using Ephemeroptera, Plecoptera and Trichoptera (EPT) orders were equally as predictive as the more complex models. With a need to better understand and use citizen monitors to predict water quality in these tropical environments, less complex insect MMIs show promise as a solution.

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.

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.

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.

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.

Groundwater pollution is considered a major concern in today’s world. Most industries in Pakistan produce untreated wastewater, extracting from and contaminating a nearby water source and the soil. This study was conducted in the Nithar Ke area of Chiniot District to assess the impact of the flow of wastewater over the area on groundwater quality. It aimed to: (1) investigate the conditions of industrial wastewater; (2) study the spatial variability of different parameters in groundwater using a GIS map; and (3) check the appropriateness of groundwater for drinking purposes using the water quality index (WQI). Physical and chemical characteristics, including pH, electrical conductivity, total dissolved solids, TSS, CO3, HCO3, chlorides, alkalinity, total hardness, Ca, Mg, arsenic, copper, chromium, nickel, iron, manganese, and sulfate, were tested using groundwater samples, and variance in groundwater was analyzed using a GIS (geographic information system). The water quality index (WQI) was developed for the Nithar Ke area to determine the appropriateness of the groundwater for drinking purposes. WQI values were determined within the range of 41 to 89.5, which showed a poor to good water quality. It was discovered that parameters such as BOD, COD, iron, and TDS had average concentrations of 192 mg/L, 264 mg/L, 2.62 mg/L, and 6039 mg/L, respectively, in the polluted water, which exceeded the permissible limit. Iron and manganese were the most common contaminants found in that area. The biplot and correlation circle showed that iron and turbidity had a positive relationship. Further study on soil stratification and soil characteristics is recommended in this area for a detailed analysis of the causes of metal contamination.

One of the aims of The European Water Framework Directive (WFD) is that the Member States monitor and assess the ecological and chemical status of all surface water bodies (rivers, lakes, transitional and coastal waters) and to ensure that they achieve a good status by 2027, with an interim deadline of 2021 [...]

Hydrogeochemical properties and groundwater quality assessment are very important for the effective management of water resources in arid and semiarid regions. The present investigation is a spatiotemporal analysis of groundwater quality using both chemical analysis and water quality indices (WQIs) in the Mornag Basin in northeastern Tunisia. The results exhibit that the Mornag shallow aquifer is dominated by chloride–sodium–potassium water facies, which progress over time toward chloride–sulfate–calcium and magnesium water facies. This may highlight that the mineralization of groundwater, which increases in the direction of groundwater flow, is primarily controlled by a natural process resulting from the dissolution of evaporative minerals and cation exchange with clay minerals relatively abundant in the study area. The anthropogenic activities represented by the return flow of irrigation water, the recharge by wastewater, and climate change also have a key role in groundwater contamination. The temporal evolution in %Na and SAR over the last three years in the Mornag aquifer shows an increasing trend that makes them unsuitable for irrigation. These findings highlight the need for assessing water quality in mapping local water resource vulnerability to pollution and developing sustainable water resources management.

Groundwater is vital to local human life and agricultural irrigation, and the quality of the water is critical to human health. As a result, it is critical to investigate the hydrochemical evolution and water quality of groundwater in the Sanjiang Plain. There were 259 samples obtained. Furthermore, hydrogeochemical simulation was performed to highlight groundwater’s hydrochemical features, evolution process, and water quality. The analytical results show that the groundwater in the study area is somewhat alkaline with a mean TDS of 285.94 mgL−1 and the primary contributing ions being Ca2+ and HCO3−. The closer the concentration of TDS and NO3− is to the city, the higher the concentration, indicating that the chemical composition of the water body has been affected by certain human activities. The Piper diagram, Gibbs diagram, and correlation analysis results demonstrate that the chemical type of groundwater is mostly HCO3-Ca and the hydrochemistry is primarily regulated by weathering and carbonate and silicate dissolution. According to the entropy-weighted water quality index, the groundwater quality in this location is pretty acceptable. This study could help strengthen groundwater quality monitoring based on local conditions, identify the source of nitrate, provide data support for the safe use of local water resources, and serve as a reference for global water chemical evolution and water quality evaluation in cold regions.

The water quality of urban rivers in China has undergone significant improvement since the 13th Five-Year Plan period (2016–2020). Among these, urban rivers in Shenzhen are the most representative. Assessing historical trends and analyzing the driving forces of river water quality improvement is of great importance and provides valuable insights. This study selects two typical watersheds, Maozhou River and Longgang River, to explore how water quality trends link with water control projects in Shenzhen from 2003 to 2020. The historical trends were evaluated using a recently developed index called WQI-DET, which considers DO, COD, NH3-N, TP, and anionic surfactants. Results showed that both rivers were seriously polluted before 2010 and gradually improved during the 12th Five-Year Plan period. After 2010, the water quality improved rapidly thanks to the environmental remediation of the mainstream, especially the interception project of Longgang River around 2010, and the Maozhou River interception project in 2015. The rainwater and sewage diversion renovation project mainly contributed to meeting the standards for Class IV water bodies during the 13th Five-Year Plan period. This study reveals the semi-quantitative link between comprehensive water quality improvement and pollution control engineering measures. It is a helpful review for Shenzhen and provides a useful reference for other cities.

The water quality assessment of the surface water bodies (SWBs) is one of the major tasks of environmental authorities dealing with water management. The present study proposes a water quality assessment scheme for the investigation of the surface waters’ physicochemical status changes and the identification of significant anthropogenic pressures. It is designed to extract valuable knowledge from the Water Frame Directive (WFD) mandatory monitoring datasets. The water quality assessment scheme is based on the Canadian Council of Ministers of the Environment water quality index (CCME-WQI), trend analysis of estimated WQI values, and Principal Component Analysis (PCA) using calculated excursions during the determination of WQI values. The combination of the abovementioned techniques preserves their benefits and additionally provides important information for water management by revealing the latent factors controlling water quality, taking into account the type of the SWB. The results enable the identification of the anthropogenic impact on SWBs and the type of the corresponding anthropogenic pressure, prioritization and monitoring restoration measures, and optimization of conducted monitoring programs to reflect significant anthropogenic pressures. The proposed simple and reliable assessment scheme is flexible to introducing additional water quality indicators (hydrological, biological, specific pollutants, etc.), which could lead to a more comprehensive surface water quality assessment.

Groundwater has been the main resource used for drinking, domestic and agricultural activities in West central Senegal for the past few decades. Thus, this study investigates the quality of groundwater and assesses its suitability for drinking and irrigation purposes. To this end, 42 samples were collected and analyzed for various chemical parameters (major ions, fluoride, pH, total dissolved solids (TDS)). Chemical data were interpreted using water quality indexes, Wilcox and USSL salinity diagrams, bivariate plots, ionic ratios and by comparing with the WHO standards. Results indicated that the groundwater is neutral to slightly alkaline with pH values between 7.1 and 8.2. Piper diagram shows that mixte-Ca-Na-Mg-HCO3 is the dominant hydrochemical facies. TDS and water quality index (WQI) values indicated respectively that 69% and 64.3% of samples were suitable for drinking. Moreover, major ions concentrations were found below the desirable limits in most of groundwater samples. However, for fluoride, 69% of samples exceed the WHO guideline, limiting their use for drinking. The computed index of irrigation water quality and Wilcox diagram reveal that 87% and 78% of samples belong, respectively, to excellent to good category and excellent to good and good to permissible. Similarly, according to the US salinity classification, the majority of samples were acceptable for irrigation. Gibbs plots illustrate that water-rocks interaction with some extent evaporation is the main hydrochemical process controlling groundwater chemistry while bivariate plots and ionic ratios indicate that mineral dissolution and ion exchange play important role in groundwater chemistry.

Because of anthropogenic activity and seawater intrusion, coastal aquifers worldwide frequently face a threat to their water supply due to salinization. This paper investigates the assessment of the groundwater quality in coastal aquifers of the Hauturivien aquifer in the Essaouira basin. In this study, 56 groundwater samples collected from the Hauturivian aquifer across four campaigns in 2017, 2018, 2019, and 2020 were subjected to multivariate analyses involving principal component analysis (PCA) and cluster analysis (CA) using SPSS software. Among the three main water types, the mixed Ca-Mg-Cl classification was predominant in the investigated aquifer. In addition to the natural processes (such as the water–rock interaction, ion exchange, dissolution/precipitation dynamics, and evaporation) that govern groundwater quality, current land use practices have increased salinization in this poorly drained semi-arid area. Based on assessments using Water Quality Index (WQI) and Irrigation Water Quality Index (IWQI), the water quality is suitable for human consumption, but its use for irrigation is limited to crops that can tolerate high salt levels. The stable isotopes (δ2H and δ18O) of groundwater demonstrated that local precipitation is the primary recharge source. Nonetheless, the evaporation process, influenced by various geological conditions, affects groundwater recharge, regardless of the topographical differences in the study area.

The Yangtze River Basin, one of China’s five major watersheds and a primary source of drinking water for the country, is experiencing serious environmental pollution as heavy metals are discharged into its rivers. To evaluate the water quality of the river, determined water quality parameters were compared with the maximum permissible limit values recommended by the World Health Organization and Chinese drinking water standards. Physical and chemical analyses were conducted on water samples taken from 19 locations along the river’s path. The study quantified the contents of sodium (Na), magnesium (Mg), calcium (Ca), strontium (Sr), barium (Ba), lithium (Li), cobalt (Co), copper (Cu), iron (Fe), manganese (Mn), scandium (Sc) and mercury (Hg). The results show that the average values of Mg, Sr, Co, Cu, Fe, Mn and Sc are higher than the historical background values. Moreover, through a correlation analysis it was concluded that these nutrients and trace metals have high values due to anthropogenic pollution in the study area. The computed WQI values range between 9.59 and 20.26, indicating excellent water quality in the river basin. Finally, hazard quotient (HQ) values show that exposure to the detected pollutants will have no adverse effects on human health and does not pose a potential non-carcinogenic risk.

The time required for diatom assemblages to integrate the abiotic variables of the aquatic environment has been subject of discussion for many years, with contrasting opinions as shown by field observations and experiments. Numerous diatom-based water quality indices are being used in the bioassessment of freshwaters; one of the most widely used (Specific Polluosensitivity Index or SPI) is compared in this study with water quality status as measured by the Water Quality Index (WQI) obtained from limnological parameters measured at 37 fluvial stations belonging to the Duero Basin (NW Spain). The correlation existing between both metrics was determined using different time lags between water and diatom sample collection. Results show that the correlation coefficient increases as the time gap decreases, but is maximal when comparing WQI scores measured one month before diatom sampling. We thus confirm the initial hypothesis that diatom indices actually indicate past (1 month ago) and not current water conditions in rivers. The practical consequences of this finding are briefly discussed.

Surface water is used for a variety of purposes, including agriculture, drinking water, and other services. Therefore, its quality is crucial for irrigation, human welfare, and health. Thus, the main objective is to improve surface water quality assessment and geochemical analysis to evaluate anthropogenic activities’ impact on surface water quality in the Oued Laou watershed, Northern Morocco. Thirteen surface water samples were characterized for 26 physicochemical and biological parameters. In this aspect, emerging techniques such as multivariate statistical approaches (MSA), water quality indices (WQI), irrigation water quality (IWQI), and Geographic Information System (GIS) were employed to identify the sources of surface water pollution, their suitability for consumption, and the distribution of surface water quality. The results showed that the major ion concentrations were reported in the following order: Ca2+, Na+, Mg2+, and K+; and HCO3− > CO32− > Cl− > SO42− > NO3− > F− > PO43− > NO2−. It was also demonstrated that almost all parameters had concentrations lower than World Health Organization (WHO) limits, except for bicarbonate ions (HCO3−) and the biochemical oxygen demand for five days (BOD5), which exceeded the WHO limits at 120 mg/L and 3 mg/L, respectively. Furthermore, the types of Ca2+-HCO3− (Calcium-Bicarbonate) and Ca2+-Mg2+-HCO3− (Calcium-Magnesium-Bicarbonate) predominated in surface water. The Principal Component Analysis (PCA) indicates that the Oued Laou river was exposed to two forms of contamination, the first being attributed to anthropogenic activities such as agriculture, while the second reflects the water-sediment interaction. The Hierarchical Cluster Analysis (HCA), reflecting the mineralization in the study area, has classified the samples into four clusters. The Inverse Distance Weighting (IDW) of the WQI indicates that 7.69% and 38.46% of the surface water represent, respectively, excellent and good quality for drinking. At the same time, the IWQI revealed that 92.30% of the water surface is good for irrigation. As a result, the combination of WQIs, PCA, IWQI, and GIS techniques is effective in providing clear information for assessing the suitability of surface water for drinking and its controlling factors and can also support decision-making in susceptible locations such as the Oued Laou river in northern Morocco.

Continuous monitoring of drinking water quality is essential in terms of the levels of heavy metals and toxic substances, especially in developing countries like Pakistan. Therefore, this study aimed to investigate groundwater quality in residential areas of the Rajanpur District, Pakistan. Groundwater samples (n = 200) were collected from various sites in the study area and analyzed by in situ tests (pH, EC, TDS, temperature, and turbidity), and the concentration of 32 dissolved elements and ions was also analyzed. The results showed that higher concentrations of dissolved elements are the primary reason for poor drinking water quality. A few measured parameters (TDS~992 mg L−1 and EC~1921.15 µS/cm) exceeded the permissible limits of the World Health Organization (WHO, Geneva, Switzerland) in most of the samples. Elements that had higher values than the allowable limits in most of the samples were calcium (Ca), sodium (Na), bicarbonates (HCO3), sulfate (SO4), chlorides (Cl), manganese (Mn), and strontium (Sr), with average values of 113 mg L−1, 223 mg L−1, 282 mg L−1, 367 mg L−1, 175 mg L−1, 69 mg L−1, and 1291 mg L−1, respectively. The measured parameters that had no significant issues in terms of drinking water quality were aluminum (Al), nitrite (NO2), phosphate (PO4), pH, and turbidity. The levels of potentially toxic elements such as arsenic (As), lead (Pb), chromium (Cr), and copper (Cu) (average ~2.179 mg L−1, 1.659 mg L−1, 0.092 mg L−1, and 1.032 mg L−1, respectively) were found to be lower than the drinking water guideline values of the WHO. The statistical analysis revealed weak correlations possibly due to multiple sources and localized variations. The physicochemical analysis-based WQI values for all groundwater samples were much lower at the residential sampling locations and in industrial settings, indicating poor water quality. The elevation model indicated that as water moves in the aquifer in the general direction of west to southeast, it gets concentrated by mineral dissolution, with geogenic sources having a major impact on the hydrochemistry. Hence, regular monitoring of water quality is required through advanced technology to overcome groundwater deterioration issues. The quality of water is poor for drinking purposes and the health of the residents of the Rajanpur District may be at risk.

Globally, water quality indices (WQIs) are beneficial for evaluating groundwater and surface water quality. The Canadian Council of Ministers of Environment Water Quality Index (CCME WQI) was combined with the parametric values given by Directive 98/83/EC to investigate the possible suitability of groundwater resources for human consumption on Rhodes Island. Chloride (Cl−), pH, calcium (Ca2+), electrical conductivity (CND), carbonate (CO32−), bicarbonate (HCO3−), potassium (K+), magnesium (Mg2+), sulfate (SO42−), sodium (Na+),nitrate (NO3−), nitrite (NO2−), ammonium (NH4+), and phosphate (PO43−) were included in the dataset applied in this study. Statistical analysis, GIS database, and WQI estimation were successfully used to evaluate the groundwater resources of the study area. All studied groundwater parameters have mean and median values lower than the corresponding parametric values established by Directive 98/83/EC. The high CND values (up to 2730 μs cm−1) in groundwater collected from Rhodes’ coastal aquifers indicate a direct relationship with seawater intrusion. CCME-WQI classifies the groundwater samples for most monitoring stations on Rhodes aquifers as “excellent”, Class 5, for 2019 and 2020. The findings of this study may be helpful for scientists and stakeholders monitoring the study area and applying measures to protect the groundwater resources.

Groundwater risks driven by population growth and industrialization in metropolitan cities have become a worldwide problem. Faisalabad is Pakistan’s third largest city with a population of more than 2 million and is renowned for its diverse industries. Many factories in the area dump their untreated effluent into nearby drainage systems, having a direct negative effect on the marine ecosystem. This research focuses on the Madhuana drain and Khurrianwala industrial region of Faisalabad to investigate groundwater quality status. Sixty water samples from groundwater bore wells and open wells were obtained, and all these samples were subjected to lab experiments for physical and chemical analysis. Sixteen physiochemical parameters, namely, electrical conductivity (EC), pH, total dissolved solids (TDS), total suspended solids (TSS), turbidity, carbonate, Ca2+, Fe, HCO3−, Cl−, Mg2+, SO24−, As, Cr, Cu, and Mn, were examined. To provide a comprehensive picture of water quality from a human perspective, we calculated the water quality index (WQI) by integrating 16 physiochemical criteria. The results revealed that a larger proportion had poor drinking quality due to direct releases of toxins by industries. It was observed that 87% of the water samples showed an unsuitable status of groundwater for drinking purposes in terms of pH, EC, Fe, Mn, Cu, and Cr. The results of this study could be used to build and construct wastewater treatment plant facilities for the Madhuana drain, reducing pollution loads on the drain and river, as well as contaminant seepage rates into groundwater. The research’s resulting maps will help policymakers to manage groundwater supplies more efficiently for sustainable development.

Baia Mare area represents one of the most important mining areas of Romania. Although the mining activities carried out here are currently inactive (since 2012), they generated residual pollution that negatively influences all the environmental factors. The aim of the study is to evaluation of the quality of surface water from the vicinity of the city of Baia Mare, Romania. The surface water samples, collected in two distinct years (2021 and 2022), were analyzed to determine the concentration of heavy metals (Cd, Cr, Cu, Ni, Zn, Pb, Fe, Mn, and As) in order to establish the degree of contamination and the water quality through heavy metal evaluation index (HEI), heavy metal pollution index (HPI), and water quality index (WQI). The pH and the content of cations (Ca, Mg, Na, K) and anions (HCO3−, SO42−, Cl−) were also determined for complex characterization. The results showed that the water in the area had a high degree of pollution with high concentrations of Cr: 0.165–1.57 mgL−1, Ni: 0.01–0.718 mgL−1, and Cu: 0.036–0.195 mgL−1. The pollution indices showed an average level of heavy metal pollution for the collected surface water samples. The quality index demonstrated that all surface water samples in the study area were unfit for irrigation and drinking due to poor and very poor water quality.

Groundwater is one of the important determinants of human health in many regions of Morocco. Indeed, it is one of the government’s top concerns. However, slow and wrong decisions are hindering the advancement of the quality of groundwater in Morocco. The traditional monitoring methods are costly, time-consuming, and human-resource-intensive, especially in such a developing country. An exploratory study was conducted in the Jouamaa Hakama region in Morocco to test and compare groundwater quality using in situ measurements, water quality indices (WQIs), and a fuzzy logic (FL) method. The methodology followed in this study involves using and comparing four WQIs and FL based on in situ measurements at nine different wells along the Ouljat Echatt River downstream of the Chrafate wastewater treatment station. Twelve physical–chemical and bacteriological parameters: potential of hydrogen (pH), temperature (T°), turbidity (TURB), chemical oxygen demand (COD), biochemical oxygen demand in five days (BOD5), suspended matter (SM), phosphate (PO43−), nitrite (NO2−), nitrate (NO3−), ammonium (NH4+), dissolved oxygen (DO), electrical conductivity (EC), and fecal coliforms (FC) were measured in 2016 and 2017. The results show that all wells are of poor quality according to FL and WQIs; the Weighted Geometric WQI and Oregon WQI indicate that the groundwater is below the acceptable standard for human consumption, while the Weighted Arithmetic WQI and Logarithmic WQI indicate that the majority of wells are of good quality. These tested indices represent an excellent tool to support decision making and can be highly helpful in monitoring groundwater quality in vulnerable areas such as the Jouamaa Hakama region in the north of Morocco.

We surveyed and selectively sampled the major water sources in Bamyan city and the surrounding area to assess the water quality. Water quality measurements were taken in situ and more samples were collected for laboratory analysis from canals, rivers, springs, wells, and water supply systems. In urban areas, water supply systems provide 36% of the drinking water, but in rural areas, this source accounts for only 7% of drinking water supplies. Wells comprise 33% and 15% of urban and rural water supplies, respectively, while canals and rivers are modest water sources for Bamyan communities. Basic water quality parameters, such as pH, EC, and TDS, were variable with high values in some areas. Most of the samples fall in the range of potable water, but some had a high TDS and EC indicating that there is the potential of contamination. Values of pH were mostly were mostly in the range of drinking water (6.5–9.5). A Drinking Water Quality Index (DWQI) was calculated to better understand the water quality issues for the potable water supplies. Subsets of representative samples were analyzed for 17 selected chemical elements and other constituents. Barium (Ba) was detected in almost all of the water samples, while arsenic (As) was detected in about 9% of the analyzed samples, and this was mostly associated with thermal springs. Concentrations of Mn and Cu in some samples exceeded that of the water quality standards, while Zn concentrations were below tolerable limits in all of the samples. Most of the analyzed water samples were hard, and several samples showed evidence of microbial pollution in urban areas. Rivers originating from snow and glacier melting had excellent quality for drinking.

Scaling models is one of the challenges for water resource planning and management, with the aim of bringing the developed models into practice by applying them to predict water quality and quantity for catchments that lack sufficient data. For this study, we evaluated artificial neural network (ANN) training algorithms to predict the water quality index in a source catchment. Then, multiple linear regression (MLR) models were developed, using the predicted water quality index of the ANN training algorithms and water quality variables, as dependent and independent variables, respectively. The most appropriate MLR model has been selected on the basis of the Akaike information criterion, sensitivity and uncertainty analyses. The performance of the MLR model was then evaluated by a variable aggregation and disaggregation approach, for upscaling and downscaling proposes, using the data from four very large- and three large-sized catchments and from eight medium-, three small- and seven very small-sized catchments, where they are located in the southern basin of the Caspian Sea. The performance of seven artificial neural network training algorithms, including Quick Propagation, Conjugate Gradient Descent, Quasi-Newton, Limited Memory Quasi-Newton, Levenberg–Marquardt, Online Back Propagation, and Batch Back Propagation, has been evaluated to predict the water quality index. The results show that the highest mean absolute error was observed in the WQI, as predicted by the ANN LM training algorithm; the lowest error values were for the ANN LMQN and CGD training algorithms. Our findings also indicate that for upscaling, the aggregated MLR model could provide reliable performance to predict the water quality index, since the r2 coefficient of the models varies from 0.73 ± 0.2 for large catchments, to 0.85 ± 0.15 for very large catchments, and for downscaling, the r2 coefficient of the disaggregated MLR model ranges from 0.93 ± 0.05 for very large catchments, to 0.97 ± 0.02 for medium catchments. Therefore, scaled models could be applied to catchments that lack sufficient data to perform a rapid assessment of the water quality index in the study area.

The provision of webGIS-based water quality data services has become a priority area for both the public and administrative sectors in the context of the pandemic emergency associated with the global spread of COVID-19. Current geographic, monitoring and decision supporting systems, typically based on web-based geospatial information, greatly facilitate the sharing of spatial and temporal data from environmental databases and real-time analyses. In the present study, different water quality indices are determined, compared and geovisualized, during which the changes in the quality of the shallow groundwater resources of a settlement are examined in the period (2011–2019) in an eastern Hungarian settlement. Another objective of the research is to determine three water quality indices (Water Quality Index, CCME Water Quality Index, Contamination degree) and categorize water samples based on the same input spatial and temporal data using self-developed freely available geovisualization tools. Groundwater quality was assessed by using different water quality indices. Significant pollution of the groundwater in the time period before the installation of a sewage network was shown. Regarding water quality, significant positive changes were shown based on all three water quality indices in the years after installing a sewage network (2015–2019). The presence of pollution apart from the positive changes suggests that the purification processes will last for a long time.

Groundwater constitutes a significant component of freshwater resources in India being vital for its economy and domestic water security. The quantity, quality and accessibility of water resources forms the basis of balanced socio-economic development and its optimum utilization cannot be sustained unless its quality is assessed. The current study tries to access the quality and suitability of groundwater for drinking purposes in western drier parts of India in the state of Rajasthan. Based on collected data, selected hydro-geochemical parameters, the quality of water has been determined and Water Quality Index (WQI) have been prepared using GIS applications. Applying the Inverse Distance Weighting method, WQI values for 89 villages in the area have been computed, which ranged between 71.23 and 447.39. While 68% of the region had “poor water quality”, only 32% is sustained as ‘good water’ for consumption. The fluoride content ranging between 1.66 and 8.60 mg/L and TDS > 1000 mg/L with average pH levels > 7 (8–9 pH) were found to be very high amongst all the 12 water quality parameters taken for the study. The northeastern region with a WQI value of >250 had the worst water quality. Furthermore, the existing water quality is also examined for influencing two water borne diseases, i.e., gastroenteritis and fluorosis in the region. The study thus establishes that the majority of groundwater in the region is beyond the permissible safer consumption limits, and a large population of the region, which is directly dependent on groundwater sources, is prone to water borne health hazards. A significantly high correlation was observed between Specific Water Quality Parameters in the region and prevalence of gastroenteritis (and fluorosis diseases with R2 = 0.530 and R2 = 0.813, respectively).

Subtropical rivers in developing countries often lack adequate monitoring, which makes it difficult to comprehensively determine their water quality when faced with different anthropic impacts. There are no proper protocols in the regulations to incorporate indicators and adapt them to different biogeographic regions, limiting the potential success of conservation and restoration of river ecosystems. This study proposes implementing macroinvertebrates as bioindicators of water quality in river ecosystems, and modifying the calibration of the widely used Biomonitoring Working Party (BMWP) index for its adaptation in a subtropical river. The Duero River, Mexico, was used as an example in this study. Data were explored with multivariate statistics, and the water quality and habitat values were averaged to obtain the families’ bioindication values and the index categories. The BMWP adequately described a deterioration gradient from the origin to the river mouth (from fair to extremely polluted), with some intermediate recovery points related to the presence of springs. Its performance was compared with other biological indices and exhibited a positive relationship with all of them. In addition, how BMWP changed over time was analyzed by examining previous samples, and highlighted increased river deterioration over time. A calibrated BMWP will allow for long-term monitoring at a low cost.

This research aims to assess the hydrogeochemical evolution of the groundwater in Oued souf valley for drinking and irrigation purposes. To achieve this, 49 groundwater samples from the complex terminal were examined and treated concurrently with multivariate statistical methods, geostatistical modeling and the WQI (water quality index). Focusing on the physico-chemical parameters, Q mode clustering analysis detected four major water groups, where the mineralization augmented from group 1 to group 4. The hydro-chemical type was the same, Ca-Mg-Cl-SO4 for all the groups. Calcite, dolomite, anhydrite, and gypsum would be the dominant reactions with the undersaturation of evaporates minerals, based on geochemical modeling, while the carbonate minerals are precipitating. Geostatistical analysis using ordinary Kriging demonstrated the exponential semi-variogram model fitted for EC (electrical conductivity), Ca2+ (calcium), Mg2+ (magnesium), K+ (potassium), HCO3− (bicarbonate), Cl− (chloride), and SO42− (sulfate). At the same time, the rational quadratic model was the best-fitted semi-variogram model for Na+ (sodium) and NO3− (nitrate). EC, SO42−, and NO3− have a strong spatial structure, while Ca2+, Na+, K+, and HCO3− have a moderate spatial structure. Moreover, there was a weak spatial structure for Mg2+ and Cl−. The WQI shows that CT (complex terminal groundwater aquifers) are not suitable for drinking and their quality for irrigation fluctuates from excellent to moderate quality.

The achievement of sustainable development goals in groundwater resources related to water quality issues is a critical question in many regions. This study aims to combine powerful tools for helping stakeholders and policymakers achieve sustainable development goals in groundwater resources of agricultural areas. The DPSIR (Driver–Pressure–State–Impact–Response) model in combination with the Canadian Council of Ministers of Environment Water Quality Index and Groundwater Directive 2006/118/European Community—Threshold Values was applied using a hydrogeochemical dataset derived from the analysis of groundwater samples collected from 31 monitoring sites in an unconfined alluvial aquifer. Elevated Cl− (up to 423.2 mg L−1), NO3− (up to 180.1 mg L−1) concentration and electrical conductivity (up to 2037 μS cm−1) value are observed for groundwater samples of the study area. The outcome of the “One Out-All Out” procedure revealed that the groundwater in 42% of the monitored sites is unsuitable for drinking according to the health-based guideline values established by Directive 98/83/European Community. A difficulty to achieve targets under Sustainable Development Goals 3 and 6 in the study area is revealed. The proposed response actions are reported.

Freshwater quality and quantity are some of the fundamental requirements for sustaining human life and civilization. The Water Quality Index is the most extensively used parameter for determining water quality worldwide. However, the traditional approach for the calculation of the WQI is often complex and time consuming since it requires handling large data sets and involves the calculation of several subindices. We investigated the performance of artificial intelligence techniques, including particle swarm optimization (PSO), a naive Bayes classifier (NBC), and a support vector machine (SVM), for predicting the water quality index. We used an SVM and NBC for prediction, in conjunction with PSO for optimization. To validate the obtained results, groundwater water quality parameters and their corresponding water quality indices were found for water collected from the Pindrawan tank area in Chhattisgarh, India. Our results show that PSO–NBC provided a 92.8% prediction accuracy of the WQI indices, whereas the PSO–SVM accuracy was 77.60%. The study’s outcomes further suggest that ensemble machine learning (ML) algorithms can be used to estimate and predict the Water Quality Index with significant accuracy. Thus, the proposed framework can be directly used for the prediction of the WQI using the measured field parameters while saving significant time and effort.

Groundwater and artificial reservoirs are in a continuous dynamic interaction that can affect not only water quantity but the quality. In this paper, taking the DR (Doumen Reservoir) as an example, the level dynamic changes between the DRTS (Doumen Reservoir Test Section) and groundwater were discussed, and the water quality used by SFE (single-factor evaluation) and WQI (water quality index) method were analyzed. A coupling model is presented to quantify the leakage impact range and groundwater budget and regionalize the impact of surface water on regional groundwater quality. The results show that the level dynamics of the reservoir and groundwater are highly consistent, with a cross-correlation coefficient of 0.85 and a lag time of about 7 days. The reservoir recharges the groundwater with an increase-decrease-stationary wave dynamic potential. After 3 years of operation of the DR, the groundwater still is recharged, the groundwater level will rise obviously, with a maximum of 8.5 m. The amount of surface water recharged is always 0. NH3-N, and COD will have varying degrees of impact, both of which are mainly the pollution halo around North Lake. The results can provide support for water resources management and environmental protection of urban plain reservoirs.

Considering the well-documented impacts of land-use change on water resources and the rapid land-use conversions occurring throughout Africa, in this study, we conducted a spatiotemporal analysis of surface water quality and its relation with the land use and land cover (LULC) pattern in Mokopane, Limpopo province of South Africa. Various physico-chemical parameters were analyzed for surface water samples collected from five sampling locations from 2016 to 2020. Time-series analysis of key surface water quality parameters was performed to identify the essential hydrological processes governing water quality. The analyzed water quality data were also used to calculate the heavy metal pollution index (HPI), heavy metal evaluation index (HEI) and weighted water quality index (WQI). Also, the spatial trend of water quality is compared with LULC changes from 2015 to 2020. Results revealed that the concentration of most of the physico-chemical parameters in the water samples was beyond the World Health Organization (WHO) adopted permissible limit, except for a few parameters in some locations. Based on the calculated values of HPI and HEI, water quality samples were categorized as low to moderately polluted water bodies, whereas all water samples fell under the poor category (>100) and beyond based on the calculated WQI. Looking precisely at the water quality’s temporal trend, it is found that most of the sampling shows a deteriorating trend from 2016 to 2019. However, the year 2020 shows a slightly improving trend on water quality, which can be justified by lowering human activities during the lockdown period imposed by COVID-19. Land use has a significant relationship with surface water quality, and it was evident that built-up land had a more significant negative impact on water quality than the other land use classes. Both natural processes (rock weathering) and anthropogenic activities (wastewater discharge, industrial activities etc.) were found to be playing a vital role in water quality evolution. This study suggests that continuous assessment and monitoring of the spatial and temporal variability of water quality in Limpopo is important to control pollution and health safety in the future.

Primary school children in the developing world often lack potable water, which may result in a high burden of water-related diseases and poor school performance. The present study aimed to characterize the drinking water quality in primary schools of Pakistan. We used a multistage random-sampling method to select 425 primary schools from selected districts of Sindh province. Standard methods were used to characterize water quality. The results were compared with maximum acceptable values recommended by the Pakistani National Environmental Quality Standards (Pak NEQS) and the World Health Organization (WHO) drinking water quality standards. Groundwater (62%) and surface water (38%) were identified as two major drinking water sources in the selected schools with varying levels of water quality. Among all parameters, dissolved oxygen (DO), pH, and nitrate remained within WHO and Pak NEQS water quality standard limit, while total dissolved solids (TDS) (33%), electrical conductivity (EC) (46%), chloride (34%), turbidity (27%), and hardness (11%) samples exceeded standard limits. All dissolved salts had moderate to strong positive correlations with TDS and EC values. Based on a water quality index (WQI), 74% of primary schools had access to excellent or good quality drinking water compared to 26% of schools that had access to either poor, very poor or unsuitable drinking water. Among all three regions, more schools from South Sindh had either poor, very poor or unsuitable drinking water (33%) compared to the Central (25%) and North zones (15%). Hence, water from these locations is unfit for human consumption and these schools need better water quality management plans to stop the spread of water-related diseases in primary school children.

Until now, there was no simple procedure to test the performance of water quality indices (WQIs) or, in other words, to perform their meta-evaluation. The purpose of this study is to provide a meta-evaluation approach of two widely used WQIs and suggestions for selecting one or both of them for application in groundwater quality assessment as proposed by the European Union. The meta-evaluation concept is based on testing the performance of two widely known WQIs by applying classification of Water Framework Directive (WFD; 2000/60/EC) and Groundwater Directive (GWD; 2006/118/EC) which was used as a reference. The Canadian Council of Ministers of Environment (CCME) and National Sanitation Foundation (NSF-WQI) have been selected for evaluation. These WQIs were applied in an agricultural area of the Mediterranean region where six sub-datasets for an entire hydrological year were available. This study uses all the available water quality data (52 monitoring stations × 2 sampling periods × 15 parameters) which is systematically collected at the area studied. The CCME-WQI is a rather strict index since it estimates statistically significantly lower values than the NSF-WQI. Based on the performance of the examined indices, it is shown that, mostly, the CCME-WQI classification findings are close to those of the GWD.

The aim of the present paper is to quantify water quality in the Lower Danube Region by using a series of multivariate techniques and the Water Quality Index (WQI). In this paper were measured 18 parameters upstream and downstream the city of Galati along the Danube River, namely: pH, Dissolved Oxygen (DO), Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD), N-NH4+, N-NO2−, N-NO3−, N total, P-PO43−, SO42−, Cl−, Fe-total, Cr-total, Pb2+, Ni2+, Mn2+, Zn2+, As2+, in the interval winter 2013−winter 2016. The samples were either analyzed on the field, or sent for testing to the laboratory. The physicochemical parameters mentioned above were analyzed in accordance with the Romanian and International standards in force. The WQI was calculated according to Weighted Arithmetic Water Quality Index Method. The interdependencies between the selected physicochemical parameters were used for determining potential sources of pollution. Monitoring water quality dynamics in the period mentioned above favoured a series of relevant conclusions about the anthropic influence on water quality. Water quality was assessed by processing the measurements results, by calculating the water quality index (WQI), and by using the principal component analyses (PCA) and the response surface method (RSM) with the aim of correlating the indices for the physico-chemical parameters.

Worldwide, it is acknowledged that changes of land use influence water quality; however, in tropical forests, the relationship between land use and water quality is still poorly understood. This study assessed spatial and seasonal variations in water quality, and the relationship between water quality and changes of land use in the Bobos-Nautla River, whose upper course runs across a patch of a tropical cloud forest. Spatial and seasonal variations in water quality and land use were assessed with multivariate tools. A cluster analysis, as well as a Principal Component Analysis (PCA-3D), identified three groups of sites: (1) an upper portion, which showed the best water quality and the broadest natural vegetation coverage; (2) a middle course, with high nitrogen and phosphorus concentrations associated with extensive agricultural uses; and (3) a lower course, characterized by the highest levels of total and fecal coliforms, as well as ammonia nitrogen, associated with the highest percentage of urbanization and human settlements. Our findings demonstrate the impact of changes of land use on water quality of rivers running through cloud forests in tropical zones, which are currently endangered ecosystems.