Calculation Of Water Quality Index Research Articles

Developing an ensembled machine learning model for predicting water quality index in Johor River Basin

Currently, the Water Quality Index (WQI) model becomes a widely used tool to evaluate surface water quality for agriculture, domestic and industrial. WQI is one of the simplest mathematical tools that can assist water operator in decision making in assessing the quality of water and it is widely used in the last years. The water quality analysis and prediction is conducted for Johor River Basin incorporating the upstream to downstream water quality monitoring station data of the river. In this research, the numerical method is first used to calculate the WQI and identify the classes for validating the prediction results. Then, two ensemble and optimized machine learning models including gradient boosting regression (GB) and random forest regression (RF) are employed to predict the WQI. The study area selected is the Johor River basin located in Johor, Peninsular Malaysia. The initial phase of this study involves analyzing all available data on parameters concerning the river, aiming to gain a comprehensive understanding of the overall water quality within the river basin. Through temporal analysis, it was determined that Mg, E. coli, SS, and DS emerge as critical factors affecting water quality in this river basin. Then, in terms of WQI calculation, feature importance method is used to identify the most important parameters that can be used to predict the WQI. Finally, an ensemble-based machine learning model is designed to predict the WQI using three parameters. Two ensemble ML approaches are chosen to predict the WQI in the study area and achieved a R2 of 0.86 for RF-based regression and 0.85 for GB-based ML technique. Finally, this research proves that using only the biochemical oxygen demand (BOD), the chemical oxygen demand (COD) and percentage of dissolved oxygen (DO%), the WQI can be predicted accurately and almost 96 times out of 100 sample, the water class can be predicted using GB ensembled ML algorithm. Moving forward, stakeholders may opt to integrate this research into their analyses, potentially yielding economic reliability and time savings.

Groundwater quality and hydrochemical characteristics in the upper Seybouse sub-basin, Northeast Algeria.

The present study aims to evaluate the groundwater quality in an area characterized by significant human anthropic activities within the upper Seybouse. In order to assess the quality, a total of 20 samples were analyzed to identify the chemical and bacteriological composition of the water, its variations, and their potential impacts on the environment and human health. The results revealed concentrations of the chemical and bacteriological elements exceeding the WHO standards, with high levels of electrical conductivity (EC) (peak = 4210 μS/cm), Ca2+ (peak = 340.68mg/L), Na+ (peak = 360mg/L), HCO3- (peak = 287mg/L), Cl- (peak = 542mg/L), SO42- (peak = 687mg/L), NO3- (pek = 65.91mg/L), fecal coliforms (FC) (peak = 160 UFC/mL), fecal Streptococcus (FS) (peak = 43 UFC/mL), and Clostridium perfringens (CP) (peak = 29 UFC/mL). Within the basin, two different facies have been identified: Cl-SO4-Na type and Cl-SO4-Ca type. The calculated Water Quality Index (WQI) indicates that none of the groundwater samples are suitable for drinking or human consumption. The detection of pathogenic microorganisms through diverse molecular methods has revealed the existence of eight distinct species, encompassing pathogenic strains that can affect human health. Moreover, the dissolution of geologic formations can influence the water's chemistry. In this region, groundwater pollution seems to be influenced by anthropogenic and agricultural factors such as fertilizer application, irrigation practices, and the release of domestic sewage.

Estimating the water quality index based on interpretable machine learning models.

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

Seasonal variation of surface water quality and streamflow in Rispana: A tributary of Ganges river, India

AbstractTo evaluate the seasonal changes in quality and quantity of river Rispana (a tributary of river Ganges—Dehradun region of India) water quality index (WQI) was calculated at four major locations by using the weighted arithmetic method. Sixteen samples in all were taken throughout the pre‐monsoon (April 2022), monsoon (July 2022), post‐monsoon (November 2022), and the Winter season (January 2023). The major parameters, namely, temperature, dissolved oxygen (DO), pH, electrical conductivity (EC), and total dissolved solids (TDS), E‐coliform, sulphate, total alkalinity (TA), total hardness (TH), and biochemical oxygen demand (BOD) were considered for calculation of WQI. The WQI varied from minimum 44.53 (good) at site 1 – Kairwaan Gaon during monsoon season to maximum 302.69 (unfit for drinking) at site 4 – Mothrowala during the pre‐monsoon period. In 75% samples quality of water was unfit for domestic purpose and the contributing factors are DO, BOD, and Coliform which exceeds permissible limit in all samples. The major factors attributed for decline in the Rispana water quality are discharge of sewage, commercial sites effluent, and urban runoff. Pre‐monsoon, monsoon, post‐monsoon, and winter had average total coliform levels of 1849.6, 2419.6, 2419.6, and 1546.25, respectively, in MPN units. The average value of E‐coli for the four season vary from 1306.8 to 1888.1 MPN. The pollution load (physico‐chemical parameters and bacteriological factors) increases as the river Rispana flows to downstream in urban locations. Streamflow was observed as very lean except monsoon season (~1500 cfs) due to more extraction of Rispana's fresh water in upstream and unplanned changes in its catchment basin; thus establishes an extensive decline in availability of fresh water sources (Domestic use) in downstream Dehradun city area. In monsoon season, more streamflow (rain water influx) maintains the WQI also in good‐moderate category. The land use/land cover – LULC analysis in Rispana basin area, depicted 71% enhancement in urbanization (24.16%–41.55%) takes place in 15 years’ span (2003–2017). The study establishes the potential causes (natural and anthropogenic) for Rispana deterioration and provides a baseline (quality index) for aquatic and ecological rejuvenation of its watershed by executing a proper management strategy with people participation. This work contributes discernments for effective water resource management to address the smart city objectives and sustainable development goal‐SDG:6, urban and municipal authorities must take cognizance for revival of this domestic water resource.

Selecting effluent outfall location in small rivers using proper water quality models based on effluent and local characteristics

ABSTRACT This study presents a methodology to determine the appropriate location for effluent disposal in a low-flow river using numerical modelling, via a case study of a river located in Southern Brazil, considering disposal of landfill leachate with known characteristics. There are four key steps: 1) a principal component analysis (PCA) for a set of representative parameters; 2) a decision flowchart for proper water quality models; 3) a modified Water Quality Index (WQI) using the resulting concentrations and 4) simulation on 1D and 2D models and WQI calculation and evaluation. The PCA highlights eight relevant parameters: ammonia (NH3), chloride (Cl−), biochemical oxygen demand (BOD), total phosp horus, nitrite (NO2 −), nitrate (NO3 −), dissolved oxygen (DO) and total dissolved solids. Two models were considered suitable: HEC-RAS (1D) and SisBaHiA (2DH). After simulating the parameters in both models, a WQI was calculated for each location. Both HEC-RAS and SisBaHiA lead to the same effluent outfall location, showing that spatial discretisation does not affect the results.

Contaminant transport from solid waste dumps: Implications for environmental degradation with a focus on capital territory regions

Open dumping of Municipal solid waste is the main method of solid waste management in Pakistan. To investigate the impacts of leachate transportation from these waste dumps on groundwater quality, two sites were selected (I-12 in Islamabad and Lohsar in Rawalpindi), water samples were collected from existing wells during summer, winter, and rainy seasons and were analyzed for physiochemical parameters using standard methods. Most groundwater samples showed contamination and values of various parameters exceeded the desired limits set by the World Health Organization (WHO) and the National Standard for Drinking Water Quality (NSDWQ), especially during the rainy season, whereas the least contamination in groundwater samples was observed during the winter season. The results obtained were, pH: 5.75–7.87, Electrical Conductivity (EC): 103–3460 μS cm−1, Total Dissolved Solids (TDS): 436–4425 mg L−1, Total Alkalinity (TA): 190–1330 mg L−1, Total Hardness (TH): 128–676 mg L−1, Chlorides (Cl⁻): 56.7–893.3 mg L−1, Nitrates (NO₃⁻): 7.8–19.9 mg L−1, Dissolved Oxygen (DO): 6.1–20.8 mg L−1, Biological Oxygen Demand (BOD): 1.0–44.0 mg L−1 and Chemical Oxygen Demand (COD): 56–272 mg L−1. The findings suggest that the magnitude of groundwater contamination from leachate transportation is intricately influenced by factors such as leachate composition, seasonal variations and distance from the dumpsite. The contamination level reduced along the distance from the dumps. Except Copper (Cu) and Zinc (Zn), the concentration of all other heavy metals including, Iron (Fe), Chromium (Cr), Nickel (Ni), Lead (Pb), Cadmium (Cd) was found above standard appreciable limits. The t-test showed a significant difference in parameter concentrations for all seasons except for Cd and Zn. The calculation of water quality index through CCME (Canadian Council of Ministers of Environment) model revealed that all the groundwater samples around both the dump sites were of poor and marginal quality. In general, the groundwater quality of both study areas is not suitable for the drinking purpose. The study suggests regular testing and treating groundwater before use, use of engineered landfills, covering landfills with clay and vegetation and use of alternative strategies like composting and recycling for waste management.

Assessment of drinking water quality based on trace elements concentrations in the semi-arid region, Morocco

Human health and sustainable socio-economic growth are closely linked to water quality. Due to increasingly intense human activity, pollutants, and in particular trace elements, are entering the aquatic system and harming humans. The main objective of this study is to analyse and compare the impact of the trace elements on the water quality of natural springs. The concentrations of ten trace elements in 12 spring water samples collected in 2022 were analyzed using ICP-MS to determine the spatial variability of natural water quality in the Ouislane watershed. Nine major trace elements (boron, cobalt, chromium, copper, manganese, nickel, lead, zinc, and vanadium) were measured using the inductively coupled plasma mass spectrometry (ICP-MS) technique. The average values of these elements followed the descending trend: B > Ni > Cr > Co > Zn > Mn > V > Cu > Pb in spring water samples. Some trace elements measured in certain water samples exceed the upper limits set by Moroccan drinking water quality standards (NM) and the World Health Organization (WHO). From the principal components analysis (PCA), 83% of the variation is explained by the first three main components. B, Co, Cr and Ni have a strongly impact on water quality explain by their strong correlation with CP1 (R2 > 0.70). The calculated water quality index (WQI) values ranged from 61.18 to 95.11, with an average of 78.47. Approximately 17% of the water samples were categorized as excellent quality water (WQI < 50), with the remaining 83% classified as good quality water (50 < WQI < 100). According to the WQI index, all the natural spring waters investigated are deemed suitable for human consumption.

Integrated Assessment and Geostatistical Evaluation of Groundwater Quality through Water Quality Indices

This study undertook an assessment of 24 physiochemical parameters at over 1094 sites to compute the water quality index (WQI) across the upper and central Punjab regions of Pakistan. Prior to the WQI calculation, an analytical hierarchy process (AHP) was employed to assign specific weights to each water quality parameter. The categorization of WQI into distinct classes was achieved by constructing a pairwise matrix based on their relative importance utilizing Saaty’s scale. Additionally, the groundwater quality status for irrigation and drinking purposes across various zones in the study area was delineated through the integration of WQI and geostatistical methodologies. The findings revealed discernible heavy metal issues in the Lahore division, with emerging microbiological contamination across the entire study region, potentially attributed to untreated industrial effluent discharge and inadequately managed sewerage systems. The computed indices for the Lahore, Sargodha, and Rawalpindi divisions fell within the marginal to unfit categories, indicating water quality concerns. In contrast, the indices for other divisions were in the medium class, suggesting suitability for drinking purposes. Scenario analysis for developing mitigation strategies indicated that primary treatment before wastewater disposal could rehabilitate 9% of the study area, followed by secondary (35%) and tertiary (41%) treatments. Microbiological contamination (27%) emerged as the predominant challenge for water supply agencies. Given the current trajectory of water quality deterioration, access to potable water is poised to become a significant public concern. Consequently, government agencies are urged to implement appropriate measures to enhance overall groundwater quality for sustainable development.

Calculation of Water Quality Index and Its Use for Water Quality Assessment in Lake Sevan

Calculation of Water Quality Index and Its Use for Water Quality Assessment in Lake Sevan

Interpretation of Ground Water Quality Parameters with correlation matrix of different sampling sites of Jaipur (Rajasthan)

Water is one of the utmost important constituents on earth. This study is based on physicochemical water quality parameters (pH, EC, TDS, TH, Ca2+ Mg2+, Na+, K+, F-, Cl- NO3-SO42-) biological Parameters (BOD, COD, DO) and calculation of water quality index to assess the water quality of a four sampling sites like Muhana (S1), Vatika (S2), Shivdaspura (S3) and Tiwadi (S4) of Jaipur (Rajasthan, India). Statistical analysis had been used to calculate the correlation coefficient of different parameters with WQI and determine the Irrigational nature of ground water. Among these parameters, EC has the highest positive correlation with Na+, Cl-, F- ion concentration whereas as TDS show strong negative correlation with Ca2+.

Status of River Water in India: A Review

Water means life which is a cyclic, inexhaustible, renewable prime natural resource. It is both a basic human need and a valued asset possessed by all living creatures. Hydrosphere, cryosphere, atmosphere, lithosphere and biosphere are all sources of water around the world. Water covers 71 % of the earth’s surface but only 1% of water is potable. Rivers like the Ganga, Yamuna and Sabarmati are revered throughout India. River water is critical for commercial and industrial development, hydroelectric power generation, agriculture, new multipurpose dams and tourism attractions. However, the presence of different contaminants such as pesticides, heavy metals, organic waste, chemical waste and direct sewage discharge has harmed the river's water quality. In India, river water pollution is a major issue that has harmed not only human and animal health, but also the economy of the country. In this review, a substantial number of studies on river water pollution in India are examined. Data on various physical, chemical, and biological characteristics are carefully analysed and interpreted, and it is discovered that river water in India is severely polluted. Furthermore, after careful interpretation of data and discussions published in research articles, this review explains the interrelationships among distinct physical and chemical parameters. EC and TDS are complementary to each other and temperature has a direct impact on pH and DO levels. Also, BOD and DO are reciprocally related with each other. This review provides a concise set of guidelines for assessing river water pollution and calculation of water quality index.

Study on Water Quality of Some Tributaries in Palembang City

The results of monitoring the water quality of Sekanak, Bendung, and Ogan river at some point have exceeded the quality standards referring Class II Water Quality Standards in accordance with Government Regulation of Indonesian Republic Number 22 of 2021. To find out the level of water pollution and water quality in the river, it is necessary to calculate the water status and water quality indeks. The purpose of study was to evaluate the water quality status and water quality index of the Sekanak, Bendung and Ogan Rivers. Calculation of water quality status used the Nemerow and Sumitomo Pollution Index method with parameters pH, DO, BOD, COD, TSS, Nitrate, Phosphate, and Fecal Coli and calculation of water quality index in accordance with the Regulation of the Ministry of Environment and Forestry of the Indonesian Republic Number 27 of 2021. The highest concentration of BOD and COD were in Sekanak river at low tide with a value of 9.51 mg/l and 41.36 mg/l. The pollution index was in the range of 0.75 to 2.47 with a meeting quality standars status up to mildly pollutants. Water quality indexs at Sekanak, Bendung and Ogan river in 2020 - 2022 were in the moderate category, except at Ogan river in 2021 was in a good category. From statistical analysis there were correlation between BOD and COD at the Sekanak, Bendung and Ogan River and the most significant parameters on the pollution index for Sekanak and Bendung River were Phosphate and for Ogan River was BOD.

ASSESSMENT OF THE QUALITY OF DOMESTIC WATER RESOURCES: CASE OF THE SAN-PEDRO RIVER AT THE FAYE HYDROELECTRIC DAM (SOUTHWEST COTE DIVOIRE)

Surface waters are the most vulnerable to pollution and variations in the hydrological cycle. These waters are polluted by anthropogenic pollutants such as pesticides from agricultural activities and heavy metals from agro-industrial activities. The waters of the San-Pedro River reservoir at the Faye dam are expected to be used for the drinking water supply of the population of the city of San-Pedro. The objective of this study is to assess the chemical quality of the water in the San-Pedro River at the Faye dam based on the calculation method of the Water Quality Index (WQI). Thirteen (13) stations were sampled during the four (4) climatic seasons in 2021 and 2022. These seasons are: the large dry season (LDS), large rainy season (LRS), small dry season (SDS), and small rainy season (SRS). Chemical analyses were conducted on 27 physico-chemical and chemical parameters. The results of the Water Quality Index calculation indicate water unsuitable for drinking in all seasons. The quality of these waters is influenced by trace metal elements (TME) with average WQIavg, TME values of 1079.6 864.5 3007.6 and 3645.2 in LDS, LRS, SDS, and SRS, respectively. On the other hand, organic parameters have a less significant influence on the quality of this water, as evidenced by WQI values of 35.7 in LDS 53.9 in LRS 80.1 in SDS and 33.5 in SRS. Therefore, this water requires appropriate treatment before any use.

Assessment of groundwater vulnerability for seawater intrusion using DRASTIC model in coastal area at Patuakhali District, Bangladesh.

Seawater intrusion is a growing concern for coastal regions in Bangladesh. Overexploitation of groundwater, low rainfall, a high rate of evaporation, rising sea level, cyclones, storm surges, and shrimp cultivation are the causes of seawater intrusion that polluted the groundwater near the coastal area. High values of EC, TDS, Na+, and Cl- ions in groundwater indicate the seawater intrusion. Piper's Trilinear and Durov diagrams of groundwater indicated that most gathered groundwater show predominantly Na-Cl-type of water. Based on the USSL diagram, it is observed that the salinity of the study area is medium to high and the alkalinity is medium to very high. Also, in view of the Wilcox outline, most of the samples in the area of interest are permissible to doubtful, and doubtful to unsuitable. Chloride is moderately correlated with Na+ (R2 = 0.590) and poorly correlated with (HCO3- + CO32-) (R2 = 0.128), which indicates seawater intrusion. According to a comparison of the levels of Fe and Mn in the groundwater of the study area with those recommended by the World Health Organization (WHO) and Department of the Environment (DOE), twenty-two out of thirty-one samples exceed the acceptable limit for Fe and thirty out of thirty-one samples fall within the acceptable limit for Mn. The calculated water quality index reveals that most samples are of low drinking water quality. The research area's poor water type is found in the north-central and southern parts. The WQI geographic variation map reveals that the study's water has a WQI of more than 100, making it unsuitable for consumption. The final seawater intrusion vulnerability map clearly identifies the moderate to highly vulnerable zone of the study area using DRASTIC index parameters. DRASTIC index parameters revealed that some portions of the northwestern part of the sample area show a moderately vulnerable zone. And the rest of the sampling area indicates the highly vulnerable zone.

Hydrogeochemistry and Mercury Contamination of Surface Water in the Lom Gold Basin (East Cameroon): Water Quality Index, Multivariate Statistical Analysis and Spatial Interpolation

Artisanal and small-scale gold mining activities have an impact on natural resources and human health. This study addresses the assessment of surface water quality in the Lom gold basin. A combined approach of water quality index calculation, multivariate statistical analysis and spatial interpolation was used. Sampling was performed at 15 stations during low- and high-water periods in 2021 for classical physicochemical parameters and total mercury measurements. The results show that the physicochemical parameters were below drinking water standards for both periods, except for pH, total suspended solids and total mercury. These waters show a large cation deficit as well as an anion deficit. The water chemistry is controlled by precipitations and silicate dissolutions in rock that convert the water into the Ca-HCO3 and Ca-Mg-HCO3 types. The level of mercury contamination varied from acceptable to high due to high flow rates during high water that cause a dilution effect for the mercury concentration upstream and its accumulation downstream. The water quality varied from excellent to very poor with better quality during the high-water period. The Lom watershed is locally affected by physical and chemical pollution due to the abundance of suspended solids and mercury resulting from the different gold mining activities.

Integrating WQI and GIS to assess water quality in Shatt Al-Hillah River, Iraq using physicochemical and heavy metal elements

This study assessed the quality of water in the Shatt Al-Hillah River by adopting some variables of physical, chemical, and heavy metal elements. The samples have been taken at six sites along the river in 2020 (from January to December). The water quality index has been determined by using the weighted-arithmetic method which is including a series of equations. Also, the model of Inverse-Distance-Weighting in the Geographic information system was applied to create a map of the water quality in the study area. Eleven physicochemical variables and five elements of heavy metals were comprised of calcium, magnesium, dissolved oxygen, Hydrogen Ions, chloride, sulfate, total hardness, total dissolved solids, turbidity, alkalinity, electric conductivity, cadmium, copper, iron, lead, and zinc. The results showed the values of the water quality index ranged from 245 to 253 (with a category of 200–300). The water quality index was rated as very poor for the selected locations along the Shatt Al-Hillah River. The GIS result illustrated the distributing map of water quality for the Shatt Al-Hillah River for household uses. The combination of the water quality index calculations with GIS in the current study might be used as a guide for future studies.

Сезонная динамика содержания тяжелых металлов и оценка загрязнения воды в реке Северная Двина (Архангельск)

The article presents the research results on the identification of seasonal variability in the values of physicochemical parameters and the metal content in the water of the Northern Dvina River. Sampling was carried out daily from January 23, 2020 to January 23, 2021 at low tide. In general, the researchers have revealed that the values of the studied parameters largely depend on the volume of seasonal river water runoff, on the underlying rocks of the river water basin, and also on anthropogenic influence. Thus, the values of pH, mineralization and a number of metals (Mg, Sr and Ba) are minimal during the flood period, which is explained by the large amount of melt water. Increased concentrations during the flood period are observed for Al, Mn, Cr, Zn, V, and Pb, which is associated with the dissolution of the underlying rocks and the runoff of winter precipitation in the form of melted snow. The researchers have determined elevated average content of natural elements Fe, Sr and Al, as well as anthropogenic metals Ni, Zn and Cr in the Northern Dvina relative to the average world concentration values. The calculation of water quality indices (HMEI, HMPL and HMTL) and public health risk indices (HI and CR) has revealed that the water in the Northern Dvina River has different levels of pollution, from mild to severe. However, the scientists have proved that permanent consumption of water as a drink can cause carcinogenic and non-carcinogenic effects. The main metals that contribute most to the index values are Fe, Ni, Al, Cr, Mn, Ba, and As. The study of the uranium content and its isotopes has revealed a large number of extremes, which does not allow drawing a conclusion about its seasonal dynamics, but the average value of the uranium content is similar to the global value for rivers.

Assessment of Physico-chemical Parameters of Manchippa Lake, Nizamabad District, Telangana

In the present work Manchippa lake water samples are collected from three different seasons, four different stations and water quality assessment was carried out from January 2020 to December 2020 on seasonal basis in order to assess the environmental impact of disposal of domestic, waste into the lake. The study was carried out to assess the water quality, analyzed for the various physico-chemical factors by following standard methods, the study area were calculated, pH, total alkalinity, chlorides, total hardness, calcium, magnesium, nitrates, sulphates, total dissolved solids and dissolved oxygen were the parameters considered for the calculation of Water quality index. The water quality index levels of the lake and all the 4 stations were clearly showing that, the status of the water body was oligotrophic and it is suitable for the human consumption. Based on the results all the selected physico-chemical parameters are within the permissible limits of standard methods of (APHA 2017)[1].

Method for screening water physicochemical parameters to calculate water quality index based on these parameters’ correlation with water microbiota

Water quality index (WQI) plays a crucial role in guiding water resource management. However, WQI calculation methods are not uniform, especially the selection of water parameters and the weighting given to each water parameter (Pi). To optimize WQI calculation, 132 water samples from seven rivers and from Chaohu Lake (33 sampling sites in Chaohu Lake Basin) in four seasons were collected, and the water parameters and microbiota composition were analyzed using high-throughput sequencing of 16 S rDNA. The correlation coefficient R2 between water parameters and microbiota composition using redundancy analysis with the Monte Carlo method were calculated, and the water parameters that significantly correlated with the microbiota composition were selected to calculate WQImin. The results showed that TP, COD, DO, and Chl a correlated significantly with water microbiota composition. WQIb calculated by substituting R2 for Pi was more consistent with the similarity between the microbiota compositions. WQIminb calculated using TP, COD, and DO was consistent with WQIb. The results of WQIb and WQIminb were more consistent than those of WQI and WQImin. These results imply that using R2 instead of Pi could help obtain a more stable WQIb that could better reflect the biological characteristics of the Chaohu Lake Basin.

Hydrogeochemical characterization of groundwater with a focus on Hofmeister ions and water quality status in CKDu endemic and CKDu non‒endemic areas, Sri Lanka

Hydro-geochemistry of drinking water was characterized in chronic kidney disease of unknown etiology (CKDu) endemic areas in Girandurukotte (GK) and Dehiattakandiya (DH) and non-endemic areas in GK, DH, and Sewanagala (SW) in Sri Lanka to comprehend any potential risk factors for CKDu. Groundwater (n = 142) and surface water (n = 08) were sampled during wet and dry seasons and analyzed for major anions, cations and stable isotopes of hydrogen and oxygen (δ2H and δ18O). Besides the typical water quality analysis, the water quality status was determined using the weighted arithmetic water quality index (WQI) and Hofmeister ion exposure levels. The measured average groundwater F− level was higher than the permissible level assigned by regulatory agencies for tropical countries at CKDu locations in GK, DH and non-CKDu locations in DH and SW. Significant differences in the content of total hardness (p = 0.017) and total dissolved solids (p = 0.003) were observed between CKDu and non-CKDu locations whereas the differences were insignificant for F− (p = 0.985) and alkalinity (p = 0.203). Weathering of silicate and carbonate minerals was found to be the main governing factor of groundwater compositions in both CKDu and non-CKDu areas, while recharging of groundwater is mainly determined by the rainfall than the surface water inputs. Higher ionic strength of groundwater in non-CKDu areas suggested that the potential environmental CKDu risk factors might be suppressed from dissolution into groundwater. The WQI calculations revealed that the both CKDu and non-CKDu locations were frequently presented with poor water quality. This study highlights the water quality status of the CKDu and non-CKDu locations and signifies the potential health risks that could arise even in non-CKDu areas due to the consumption of poor quality water. Accordingly, regular monitoring of water quality and assessment of Hofmeister ions exposure from food and beverages are highly warranted.