Interpreting optimised data-driven solution with explainable artificial intelligence (XAI) for water quality assessment for better decision-making in pollution management.

In Saudi Arabia, water pollution and drinking water scarcity pose a major challenge and jeopardise the achievement of sustainable development goals. The urgent need for rapid and accurate monitoring and assessment of water quality requires sophisticated, data-driven solutions for better decision-making in water management. This study aims to develop optimised data-driven models for comprehensive water quality assessment to enable informed decisions that are critical for sustainable water resources management. We used an entropy-weighted arithmetic technique to calculate the Water Quality Index (WQI), which integrates the World Health Organization (WHO) standards for various water quality parameters. Our methodology incorporated advanced machine learning (ML) models, including decision trees, random forests (RF) and correlation analyses to select features essential for identifying critical water quality parameters. We developed and optimised data-driven models such as gradient boosting machines (GBM), deep neural networks (DNN) and RF within the H2O API framework to ensure efficient data processing and handling. Interpretation of these models was achieved through a three-pronged explainable artificial intelligence (XAI) approach: model diagnosis with residual analysis, model parts with permutation-based feature importance and model profiling with partial dependence plots (PDP), accumulated local effects (ALE) plots and individual conditional expectation (ICE) plots. The quantitative results revealed insightful findings: fluoride and residual chlorine had the highest and lowest entropy weights, respectively, indicating their differential effects on water quality. Over 35% of the water samples were categorised as 'unsuitable' for consumption, highlighting the urgency of taking action to improve water quality. Amongst the optimised models, the Random Forest (model 79) and the Deep Neural Network (model 81) proved to be the most effective and showed robust predictive abilities with R2 values of 0.96 and 0.97 respectively for testing dataset. Model profiling as XAI highlighted the significant influence of key parameters such as nitrate, total hardness and pH on WQI predictions. These findings enable targeted water quality improvement measures that are in line with sustainable water management goals. Therefore, our study demonstrates the potential of advanced, data-driven methods to revolutionise water quality assessment in Saudi Arabia. By providing a more nuanced understanding of water quality dynamics and enabling effective decision-making, these models contribute significantly to the sustainable management of valuable water resources.

Water quality assessment of Bheemasandra Lake, South India: A blend of water quality indices, multivariate data mining techniques, and GIS.

An integrated approach combining water quality indices (WQIs), multivariate data mining, and geographic information system (GIS) was employed to examine the water quality of Bheemasandra Lake, located adjacent to a sewage treatment plant (STP) in Tumakuru city, India. The analysis of 22 lake water samples, examined before and after the monsoons, revealed that the physicochemical parameters namely - electrical conductivity, biochemical oxygen demand, turbidity, total dissolved solids, ammoniacal nitrogen, nitrates, phosphates, magnesium, total hardness, total alkalinity, and calcium - exceeded the acceptable limits stipulated by national and international standards. The Canadian Council of Ministers of the Environment WQI (pre-monsoon: 25.3; post-monsoon: 33.9) and weighted arithmetic WQI (pre-monsoon: 3398; post-monsoon: 2093) designated the water as unsafe for drinking. Irrigation WQIs (sodium adsorption ratio, sodium percentage, residual sodium carbonate, magnesium hazard, permeability index, and potential salinity) implied water's suitability for irrigation. However, electrical conductivity indicated otherwise. Industrial WQIs (Larson-Skold Index, Langelier Index, Aggressive Index, and Puckorius Scaling Index) illustrated scaling propensity and the chloride sulfate mass ratio alluded galvanic corrosion potential. Hierarchical cluster analysis gathered 22 sampling points into two clusters (cluster 1: relatively lower polluted regions; cluster 2: highly polluted regions) for each season based on similarities in water features. Principal component analysis extracted four (79.07% cumulative variance) and six (87.14% cumulative variance) principal components before and after the monsoons, respectively. These components identified the primary pollution sources as urban sewage and natural lithological processes. WQI maps, created using the inverse distance weighted interpolation technique, enhanced the visualization of spatial-temporal variations. This study highlights the dire consequences of urbanization, STP pollution, and sewage management failures, necessitating that concerned authorities should implement policies and measures to curb the negative impacts on the environment and public health.

Tracing the land use specific impacts on groundwater quality: a chemometric, information entropy WQI and health risk assessment study.

Understanding the nexus of land use and water quality can potentially underline the influences within the groundwater management. The study envisages land use-specific qualitative assessment of the groundwater resources in Ghaziabad district, in western Uttar Pradesh, India. For encountering the relative impacts of land use on the groundwater quality, chemometric analysis has been employed to apportion the pollution sources. The integration of quality parameters, in the information entropy index modeling, has segregated the quality classes and visualized the seasonal suitability trends as per potability standards along with non-carcinogenic health hazard risk assessment (HHRA). The qualitative assessment of the groundwater resources, along with spatial distribution, has deciphered a polluting impact, specifically in western and south western parts of district, and observed the linkages with direct and indirect discharges/seepages from densely populated residential and industrial land use types localized in urbanized areas. Statistically significant annual and seasonal variations have been found exclusively for EC, Mg2+, F-, Cd, Cr(total), Ni, and Pb which inferred variable concentrations, whereas land use types showed a non-significant variation within groundwater quality. Chemometric-based source apportioning and hierarchical cluster analysis (HCA) have derived salinization and enrichment of dissolved salts, arising from mixed sources and contributes to metal pollution, i.e., mainly from anthropogenic sources. Information EWQI derived poor to extremely poor category represented degraded potability specifically for fewer sites located within western and southern parts on the Yamuna-Hindon flood plains for limited sites of residential, industrial, and agricultural in an urbanized region. However, majority of the samples fall under excellent to good groundwater quality, recommendable in the north and north-eastern (peri-urban) regions. Non-carcinogenic HHRA has shown that majority of the samples categorized under unsafe value for hazard index (HI > 1), for females and children and thus, presumed probable health hazard risk from metal groundwater pollution in south-western part, eastern, and northern regions.

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

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

Pollution sources apportionment and suitability assessment of Lah River, Ethiopia: Conjunctive application of multivariate statistical analysis and water quality index.

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.

Identification of groundwater pollution sources and health risk assessment in the Fengshui mining area of Central Shandong, China.

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.

Water quality assessment of Elgo river in Ethiopia using CCME, WQI and IWQI for domestic and agricultural usage.

The increasing demand for water due to the escalation in population and aggressive agricultural activities for drinking and irrigation purposes in the rural areas of Ethiopia has put tremendous stress on water requirements. The Elgo River in southern Ethiopia is deteriorating due to sedimentation, soil erosion, stormwater runoff, and anthropogenic activities. Elgo village faces water shortages and a lack of safe drinking water. The purpose of this research was to identify the extent of pollution in Elgo River water using the Canadian Council of Ministers of the Environment (CCME), Water Quality Index (WQI), and Irrigation Water Quality Index (IWQI). A total of 12 water samples were collected from 3 river sampling sites for the dry and wet seasons to test the physicochemical and biological parameters. Results obtained were: turbidity (46.5-156) NTU, colour (103.65-606.5) TCU, EC (182-268) µS/cm, TDS (192.5-275.5) mg/l, TSS (680-2774) mg/l, Ca2+ (22-45) mg/l, Mg2+ (19.5-23.5) mg/l, Cl- (10.5-16.65) mg/l, and SO42- (17.18-47) mg/l for both the dry and wet seasons, respectively. The CCME WQI revealed that the overall results were 38.38 for the dry season and 36.6 for the wet season for drinking water parameters. The CCME WQI categorization indicates that the Elgo River water is classified as poor, with results ranging from 0 to 44. For irrigation purposes 10, parameters such as SAR, PS, PI, MAR, KI, RSC, EC, SSP, TH, and %Na were examined to compute indices using the IWQI model. The overall result of water quality indicated that IWQIs of 81.4 and 62.14 are good for the dry season and poor for the wet season, respectively. This research provides a thorough analysis through modelling to determine the suitability of water for different purposes for the tribal and backward communities of the area.

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

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

Assessment of seasonal water quality and land use land cover change in Subarnarekha watershed of Ranchi stretch in Jharkhand.

In this paper, the assessment of seasonal water quality and land use land cover change in the Subarnarekha watershed in Ranchi stretch was analysed. Agricultural runoff along with climate change adds to the pollution risk to the Subarnarekha River of Ranchi stretch in Jharkhand. Water quality indicators, like acidity alkalinity (ALK), total dissolved solids (TDS), hardness (H), dissolved oxygen (DO), biochemical oxygen demand (BOD), chlorides (CL-), electrical conductivity (EC), salinity (SAL), resistivity (RES) and pH, were assessed as per the standard method. During monsoon season, acidity, alkalinity, hardness, chlorides, salinity, pH and DO decreased, whereas EC, TDS, BOD and resistivity increased in comparison to pre-monsoon season. In post-monsoon, chloride problem was observed very high. Hardness was least in monsoon and maximum in post-monsoon season. EC and BOD increased in monsoon season in comparison to other seasons. Statistical analysis like HCA (hierarchical cluster analysis) and PCA (principal component analysis) also confirmed the problem of TDS, EC, chloride and hardness in the area. WQI (water quality index) analysis showed that the water quality was poor to unsuitable on all the sampling points throughout the study area in all seasons. LULC (land use land cover) and NDWI (normalized difference water index) analysis had also concluded that due to high rate of urbanization, the area has undergone a massive change in terms of forest cover and water bodies. The need for afforestation, forest protection and wetland protection can be clearly seen from the result of this study.

Hydrochemistry, quality, and integrated health risk assessments of groundwater in the Huaibei Plain, China.

Groundwater is an essential freshwater resource utilized in industry, agriculture, and daily life. In the Huaibei Plain (HBP), where groundwater significantly influences socio-economic development, information about its quality, hydrochemistry, and related health risks remains limited. We conducted a comprehensive groundwater sampling in the HBP and examined its rock characteristics, water quality index (WQI), and potential health risks. The results revealed that the primary factors shaping groundwater hydrochemistry were rock dissolution and weathering, cation exchange, and anthropogenic activities. WQI assessment indicated that only 73% of the groundwaters is potable, as Fe2+, Mn2+, NO3-, and F- contents in the water could pose non-carcinogenic hazards to humans. Children were more susceptible to these health risks through oral ingestion than adults. Uncertainty analysis indicated that the probabilities of non-carcinogenic risk were approximately 57% and 31% for children and adults, respectively. Sensitivity analysis further identified fluoride as the primary factor influencing non-carcinogenic risks, indicating that reducing fluoride contamination should be prioritized in future groundwater management in the HBP.

Mapping and assessment of river water quality under varying hydro-climatic and pollution scenarios by integrating QUAL2K, GEFC, and GIS.

Water quality modelling has proved to be effective method for managing river water quality. But the most effective and comprehensive approach involving integration of river water quality simulation and pollution visualization with the objective of pollution reduction and maintenance of environmental flow strategies has gained less attention. Thus, the objective of this study was to employ an integrated approach for mapping and analysing river water quality under various hydro-climatic and pollution scenarios. Specifically, this approach involved the integration of a river water quality simulation model, QUAL2K, Global Environmental Flow Calculator (GEFC), and Geographical Information System (GIS) to develop water quality index (WQI) based map charts of water quality. The calibrated QUAL2K model was utilized to simulate WQI parameters including water temperature, pH, electrical conductivity, dissolved oxygen (DO), biological oxygen demand (BOD), nitrates (NO3), ammonia (NH4), and alkalinity. To analyse the WQI, the Weighted Arithmetic-Water Quality Index (WA-WQI) method was employed for various individual and combined pollution scenarios, environmental flow (Eflow), and climate change scenarios. The developed integrated approach was applied to the Bhadravati segment of Bhadra River, India. The findings revealed that the prevailing WQI status of the study stretch ranged from poor to unsuitable for drinking purposes. This deterioration can be attributed to the impact of both industrial and municipal effluents. By maintaining the effective Environmental Management Class (EMC) flow rates (class C flowrate of EMC (40.32 m3/s)) in conjunction with appropriate Pollution Reduction (PR) level (10% PR) at headwater and incoming drains, the stream self-purification capacity was enhanced resulting in the Bhadravati River stretch water quality transitioning to favourable water quality condition.

Assessment of spring water quality of Khandbari Municipality in Sankhuwasabha District, Eastern Nepal.

The study was carried out in the Khandbari Municipality, Sankhuwasabha District, Eastern Nepal to document the spring location and assess the water quality of the spring water for drinking and irrigation purposes. A total of 85 springs were mapped, which are located from 274 to 2176 m in altitude. Spring water samples were collected from 33 springs in the pre-monsoon (November, 2021) and 31 springs in the post-monsoon (March, 2022). Correlation matrices, t-test, principal component analysis (PCA), Piper diagram, Gibbs diagram, water quality index (WQI), United States Salinity Laboratory (USSL) diagram, and Wilcox diagram were applied for evaluating the spring water. All the physicochemical parameters were within the Nepalese National Drinking Water Quality Standard (NDWQS) and drinking water quality guidelines of the World Health Organization (WHO) except for pH in the pre-monsoon and iron in the post-monsoon season. The main contributors to the groundwater are Na+, Ca2+, Cl-, total dissolved solids (TDS), and total hardness, which exhibit significant correlations with electrical conductivity (EC) similar to TDS, suggesting their common source of origin. Based on the WQI, spring water is excellent in the post-monsoon and excellent and good in the pre-monsoon season. Furthermore, the spring water is excellent for irrigation purposes except for the percent sodium in the post-monsoon and the magnesium ratio in the pre-monsoon season. Gibbs diagram illustrates that spring water is mainly governed by rock and precipitation dominance in some springs. The PCA indicates that anthropogenic activities (mixing of human waste and agricultural run-off in the spring water) are the main causes of contamination. Piper trilinear diagram demonstrates carbonate dissolution and silicate weathering as major processes for controlling the spring water chemistry. The study reveals that 62.5% of spring water was contaminated with microbes. For benthic macroinvertebrates, 18 springs were sampled, where nine orders and 17 families were recorded in the pre-monsoon and six orders and ten families in the post-monsoon season. The main influencing variables for macroinvertebrate assemblages are elevation, discharge, NO3-, and NH3.

Spatio-temporal evolution of groundwater quality and its health risk assessment in Punjab (India) during 2000-2020.

The state known as the bread basket of India has now been defamed as the cancer capital of the country. The toxicity of groundwater associated with the declining water level is reported in recent years. However, an extensive temporal and spatial analysis is required to identify hotspots. In this study, spatial tools are utilized to understand the evolution of groundwater in Punjab (> 315 sites) for the last two decades (2000-2020) for drinking purposes using the water quality index (WQI). The data for pH, electric conductivity (EC), bicarbonate (HCO3¯), chloride (Cl¯), sulfate (SO42¯), nitrate (NO3¯), fluoride (F¯), calcium (Ca2+), magnesium (Mg2+), sodium (Na+), and potassium (K+) collected from the Central Groundwater Board (CGWB) were analyzed. The results show that the average cation abundance is in declining order of Na > Mg > Ca > K, and anion abundance is in order of HCO3¯ > SO42¯ > Cl¯ > NO3 > F. The ions are compared with water quality standards defined by BIS and WHO. The study shows that in the year 2000, 69.52% of locations are above the acceptable limit for EC, 68.89% for Mg2, 84.76% for Na+, 51.75% for HCO3¯, 38.41% for NO3¯, and 17.20% for F¯. While in the year 2020, 48.89% exceed the acceptable limit for EC, 57.78% for Mg2+, 68.25% for Na+, 34.92% for HCO3¯, 27.30% for NO3¯, and 8.88% for F¯. WQI shows that in the year 2000, 13.01% of sampling locations are categorized as very poor and 20% as unsuitable for drinking. Meanwhile, in 2020, 6.35% of locations are categorized as very poor and 12.38% as unsuitable for drinking in the study area. In addition to the effect on plant growth, consumption of contaminated water can adversely affect human health. The health hazards for F¯ (HQF) and NO3¯ (HQN) and their total health index (THI) are also evaluated that depicts 244 groundwater sampling sites in the year 2000, and 152 sampling sites in the year 2020 show high non-carcinogenic effects on adults, children, and infants. Southwestern Punjab is found to be the worst affected, while north-eastern regions drained by the Himalayan rivers show better quality water. Shifting in agricultural practices in the last two decades and declining water levels due to excess pumping of water from deeper water tables deteriorated the quality of water in the Southern region as observed from the geospatial analysis.

Water quality assessment of Remeți watercourse, Maramureș, Romania, located in a NATURA 2000 protected area subjected to anthropic pressure.

The study assessed the evolution of water indicators of Remeți water body that is located in the Remeți locality in the Upper Tisa, a Natura 2000 protected area. Thus, electric conductivity, dissolved oxygen, oxygen saturation, temperature, pH, turbidity, ammonium concentration (NH4+), nitrates (NO3-), nitrites (NO2-), orthophosphate (PO43-), dissolved Fe, Mn, water hardness, alkalinity (A) and chloride were measured over the January (I)-October (X) 2021 period. This water course was subjected to anthropic pressure, being polluted with nutrients such as ammonium and orthophosphate ions, iron and manganese. The concentrations of other metals were either low (Al, Ba, Li, Ga, Rb, Ni, Sr, Zn, Cu, Ti) or below the detection limit (Pb, Cd). The study was performed over a period of 8 months, namely January 2021-October 2021, covering the 4 seasons, in order to establish their influence on the level of water quality indicators. Exceeded turbidity values and high concentrations of ammonium, orthophosphate and dissolved iron were found, these being generally higher in the summer-autumn months. Dissolved oxygen concentrations were low in the summer-autumn months. Based on the values of the physico-chemical indicators, two types of water quality indices WA-WQI (weighted arithmetic water quality indices) and CCME-WQI (Canadian Council of Ministers of the Environment water quality indices) were calculated to evaluate the global water quality and its evolution over the seasons with a single value. WA-WQI values varied in the range of 78.56-761.63, with a tendency to increase in autumn, showing an intensified tendency of global water quality deterioration due to an increase in ammonium, turbidity, iron and orthophosphates in autumn months while CCME-WQI values were between 39.6 and 68.9, being fair in winter-spring months and marginal / bad in summer and autumn months. The results of this study are advantageous in identifying the level of pollution of Remeți water course, being a signal for local authorities in taking the necessary measures to reduce the pollution around it, for a better human health and conservation of the ecosystems hosted in the protected area.

Marine waters assessment using improved water quality model incorporating machine learning approaches.

In marine ecosystems, both living and non-living organisms depend on "good" water quality. It depends on a number of factors, and one of the most important is the quality of the water. The water quality index (WQI) model is widely used to assess water quality, but existing models have uncertainty issues. To address this, the authors introduced two new WQI models: the weight based weighted quadratic mean (WQM) and unweighted based root mean squared (RMS) models. These models were used to assess water quality in the Bay of Bengal, using seven water quality indicators including salinity (SAL), temperature (TEMP), pH, transparency (TRAN), dissolved oxygen (DOX), total oxidized nitrogen (TON), and molybdate reactive phosphorus (MRP). Both models ranked water quality between "good" and "fair" categories, with no significant difference between the weighted and unweighted models' results. The models showed considerable variation in the computed WQI scores, ranging from 68 to 88 with an average of 75 for WQM and 70 to 76 with an average of 72 for RMS. The models did not have any issues with sub-index or aggregation functions, and both had a high level of sensitivity (R2 = 1) in terms of the spatio-temporal resolution of waterbodies. The study demonstrated that both WQI approaches effectively assessed marine waters, reducing uncertainty and improving the accuracy of the WQI score.

Groundwater quality assessment using SPSS based on multivariate statistics and water quality index of Gaya, Bihar (India).

Groundwater is a valuable resource for developmental activities, and its demand is growing as surface water becoming scarce. Groundwater demand is increasing, resulting in reduction in water level and deterioration in water quality. A total of 156 groundwater samples were taken from Gaya, a district in Bihar (India), to check the safety of drinking water. The quality of groundwater was assessed using a water quality index (WQI). Analysed samples were assessed using a variety of physicochemical characteristics, and statistical methods principal component analysis (PCA) and cluster analysis (CA) were used as they are effective and efficient. As per the Gibbs, plot majority of the sample falls in the rock-water interaction and some evaporation dominance field. The domination of major cation in the order of Ca2+ > Mg2+ > Na+ and the major anions followed the order of HCO3- > [Formula: see text]>[Formula: see text]>[Formula: see text]>[Formula: see text]. The KMO's sample adequacy value of 0.703 and the significance level of Bartlett's test of sphericity (0.0001) were indicating that PCA may be implemented. Using the PCA, the three components recovered explained 69.58% of the total variation. Cluster analysis classified the groundwater sample into three cluster based on the similarities among chemical parameters involved in groundwater quality. HCA exhibit less, intermediate, and heavily mineralized groundwater characteristics of groups I, II, and III, respectively. The major parameters affecting the water quality in the study region are TDS, Ca2+, Mg2+, HCO3-, [Formula: see text]. WQI indicates 17% of the sample were found to be of very poor quality and not consumable. The study's findings offer insights and understanding into groundwater pollution regimes. These results used for water quality assessment leading to improved environmental management and planning and in decision-making for water quality management.

Spatial-temporal distribution, source identification, risk assessment and water quality assessment of trace elements in the surface water of typical tributary in Yangtze River delta, China.

As China's first cross-province ecological compensation mechanism pilot area in the hinterland of the Yangtze River Delta, Xin'an River has been hotspot in the study of rational utilization of ecological resources, and the functional value of its ecosystem services has been widely concerned. As an important tributary of the upper reaches of Xin'an River, Fengle River may affect the whole basin. The spatial-temporal distributions, occurrence, water quality and risk assessment of trace elements were studied in Fengle River in three seasons. High element concentrations were found in the downstream. Traceability models results showed that the major sources of trace elements were related to different human activities. The water quality was worse downstream in the wet season, and was more suitable for irrigation in the dry season. Risk assessment results showed that Zn, Cu, Mn, Co, and As were able to pose the risk to the ecological environment and human.

Water security and health risk assessment of an urban household-level drinking water and sanitation system, Punjab, India.

The water scarcity and deteriorating water quality are major issues of concern to the agrarian state of Punjab, India. The focus of the study is to assess the status of drinking water and sanitation systems of Punjab using an exhaustive dataset of 1575 drinking water samples from 433 sampling locations in 63 urban local bodies of Punjab. Water security index (WSI) indicate that out of 63 urban local bodies, 13 are categorized into good class, 31 fall under fair class, and 19 fall under poor class. The access indicator under sanitation dimension shows that Bathinda region has maximum sewerage network coverage relative to other regions, whereas ca. 50% of the ULBs in Amritsar region do not have sewerage facility. It is clearly depicted that the variation in WSI is mainly attributable to sanitation dimension (10-22.5) as variation in water supply dimension (29-35) is relatively less. Hence, emphasis on indicators and variables of sanitation dimension is required for the improvement of overall WSI. The assessment of qualitative aspects of drinking water and health risk depicts that the drinking water quality of southwest part of the state (i.e. Malwa region) is under good quality class contrary to its poor groundwater quality. Kapurthala district shows high health risk due to the presence of trace metals despite being classified into good class within water security index. The drinking water quality is better and health risks are minimal in regions where drinking water is supplied via treated surface water sources (e.g. Bathinda region). Furthermore, the results of health risk assessment correlate with M[Formula: see text]-Water Quality Index outcome owing to presence of trace metals in groundwater above permissible limits. These results will help in identification of shortcomings in water supply and sanitation infrastructure and its management in urban areas.

Assessment of the correlation between the nutrient load from migratory bird excrement and water quality by principal component analysis in a freshwater habitat.

Waterbirds depend on a dispersed network of wetlands for their annual life cycle during migration. Climate and land use changes raise new concerns about the sustainability of these habitat networks, as water scarcity triggers ecological and socioeconomic impacts threatening wetland availability and quality. During the migration period, birds can be present in large enough numbers to influence water quality themselves linking them and water management in efforts to conserve habitats for endangered populations. Despite this, the guidelines within laws do not properly account for the annual change of water quality due to natural factors such as the migration periods of birds. Principal component analysis and principal component regression was used to analyze the correlations between the presence of a multitude of migratory waterbird communities and water quality metrics based on a dataset collected over four years in the Dumbravița section of the Homoród stream in Transylvania. The results reveal a correlation between the presence and numbers of various bird species and the seasonal changes in water quality. Piscivorous birds tended to increase the phosphorus load, herbivorous waterbirds the nitrogen load, while benthivorous duck species influenced a variety of parameters. The established PCR water quality prediction model showed accurate prediction capabilities for the water quality index of the observed region. For the tested data set, the method provided an R2 value of 0.81 and a mean squared prediction error of 0.17.

Assessment of the water quality of Bartin Kisla (Kozcagiz) Dam by using geographical information system (GIS) and water quality indices (WQI).

This study was conducted to evaluate the water quality of the Kisla (Kozcagiz) Dam located in the province of Bartin in the Western Black Sea Region of Turkey. Water samples were collected monthly from 5 stations for a year and analyses were conducted using 27 water quality parameters. The quality of the dam and the water quality parameters were evaluated using different indices in comparison to the limits determined according to the standards set by the World Health Organization (WHO) and Turkey Surface Water Quality Regulation (SWQR). Water quality index (WQI), organic pollution index (OPI), sodium adsorption ratio (SAR), magnesium adsorption ratio (MAR), permeability index (PI), and metal pollution index (MPI) were calculated and spatial assessment of pollution was made seasonally by making use of the geographic information system (GIS). A piper diagram was used in determining the facies of the water. The types of Ca2+-Mg2+-HCO3- predominated in the dam water. Moreover, statistical analyses were used in order to determine if there was a significant difference between the parameters. WQI results generally indicate that the water quality was good in all seasons; however, only in the autumn, sampling points S1 (101.58), S2 (100.59), S4 (102.31), and S5 (102.12) showed poor water characteristics. According to the OPI results, while winter and spring yielded good water quality, summer samples were lightly polluted and autumn samples were moderately polluted. Given SAR results, it can be stated that the water of Kisla Dam could be used as irrigation water. Considering the standards specified by WHO and SWQR, the parameters generally exceeded the threshold values, but the water hardness value was much higher than 100 mg L-1 specified in SWQR as very hard water. The principal component analysis (PCA) results showed that the pollution sources were anthropogenic. Thus, for the dam water to not be affected by the increasing pollutant factors, it should be continuously monitored, and attention should be paid to the irrigation methods used in agricultural activities.