Water Quality Index Assessment Research Articles

Hydro-Geochemistry and Water Quality Index Assessment in the Dakhla Oasis, Egypt

Water quality is crucial to the environmental system and thus its chemistry is important, and can be directly related to the water’s source, the climate, and the geology of the region. This study focuses on analyzing the hydrochemistry of specific locations within the Dakhla Oasis in Egypt. A total of thirty-nine groundwater samples representing the Nubian Sandstone Aquifer (NSSA) and seven surface water samples from wastewater lakes and canals were collected for analysis. Key parameters such as pH, electrical conductivity (EC), and total dissolved solids (TDS) were measured on-site, while major ions and trace elements (Fe+2 and Mn+2) were analyzed in the laboratory. The water quality index (WQI) method was employed to assess the overall water quality. Hydro-chemical facies were investigated using Piper’s, Scholler’s, and Stiff diagrams, revealing sodium as the dominant cation and chloride, followed by bicarbonate as the dominant anion. The hydro-chemical composition indicates that Na–Cl constitutes the primary water type in this study. This points to the dissolution of evaporates and salt enrichment due to intense evaporation resulting from the region’s hyper-aridity. In groundwater samples, the order of hydro-chemical facies is HCO3− > Cl− > SO4−2 > Na+ > Ca+2 > K+ > Mg+2, while in wastewater samples, it is Cl− > Na+ > SO4−2 > HCO3− > Ca+2 > Mg+2 > K+. When considering iron and manganese parameters, the water quality index (WQI) values suggest that most groundwater samples exhibit excellent to good quality but become poor or very poor when these elements are included. This study could prove valuable for water resource management in the Dakhla Oasis.

GIS-based groundwater potential zonation and assessment of groundwater quality and suitability for drinking and irrigation purposes in the Shanmughanadhi river basin, south India

To develop a specific watershed scenario, the quantity and quality of groundwater resources must be assessed and monitored locally. In the present study, an attempt has been made to identify possible groundwater potential zones, determine the quality of groundwater resources in this region, and evaluate their suitability for drinking and irrigation purposes. This goal has been achieved with the combined use of the weighted index overlay analysis (WIOA), groundwater quality index (GWQI), Remote Sensing (RS), and Geographic Information System (GIS) techniques. The proposed study area, Shanmuganadhi, is marked with superior rainfall, oscillating temperature, and runoff with litho-units encompassing charnockite (CHK) and hornblende biotite gneiss (HBG). Over-abstraction of groundwater and intensive agricultural practices have resulted in declining and degrading water quantity and quality in this area. The resulting integrated thematic map has been classified into five groundwater potential zones, namely poor, low, moderate, high, and very high, covering 3.2, 45.49, 15.3, 27.9, and 8.1% area, respectively. Sixty groundwater samples were collected during the pre-monsoon (PRM) and analyzed for major Physico-chemical parameters. From the water quality index assessment, over 28.0% of the samples fall within the “excellent,” 8.0% “good” and 4.0% “poor” in CHK, followed by 5.71% “excellent,” 48.57% “good,” 37.14% “poor,” 5.71% “very poor” and 2.87% “unsuitable” for drinking purposes in HBG terrain of this region. Irrigation indices also demonstrated that most of the groundwater samples in the CHK and HBG exposed zones exhibited good classes for irrigation purposes, as evidenced by the SAR and %Na+. The outcome, which shows the research area's groundwater potential zones, is beneficial for improved groundwater resource planning and management. It is concluded that for larger-scale groundwater-quality investigation and assessment, the groundwater quality index-making approach (GWQI) is more practical and dependable. Water planners and decision-makers may find it helpful in effectively controlling and monitoring groundwater quality at the basin or watershed scale. Reducing urban land use and natural runoff from farms can help prevent water contamination in some regions. To ensure the safe use of groundwater, long-term monitoring of these groundwater was suggested.

Monitoring the Industrial waste polluted stream - Integrated analytics and machine learning for water quality index assessment

The Water Quality Index (WQI) is a primary metric used to evaluate and categorize surface water quality which plays a crucial role in the management of fresh water resources. Machine Learning (ML) modeling offers potential insights into water quality index prediction. This study employed advanced ML models to get potential insights into the prediction of water quality index for the Aik-Stream, an industrially polluted natural water resource in Pakistan with 19 input water quality variables aligning them with surrounding land use and anthropogenic activities. Six machine learning algorithms, i.e. Adaptive Boosting (AdaBoost), K-Nearest Neighbors (K-NN), Gradient Boosting (GB), Random Forests (RF), Support Vector Regression (SVR), and Bayesian Regression (BR) were employed as benchmark models to predict the Water Quality Index (WQI) values of the polluted stream to achieve our objectives. For model calibration, 80% of the dataset was reserved for training, while 20% was set aside for testing. In our comparative analyses of predictive models for water quality index, the Gradient Boost (GB) model stood out the fittest for its precision, utilizing a combination of just seven parameters (chemical oxygen demand, total organic carbon, oil & grease, Ammonia- nitrogen, arsenic, nickel and zinc), surpassing other models by achieving better results in both training (R2 = 0.88, RMSE = 7.24) and testing (R2 = 0.85, RMSE = 8.67). Analyzing feature importance showed that all the selected variables, except for NO3 N, TDS and temperature had an impact on the accuracy of the models predictions. It is concluded that the application of machine learning to assess water quality in polluted environments enhances accuracy and facilitates real-time tracking, enabling proactive risk mitigations.

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

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

Geothermal Water Quality Index Assessment for Irrigation Purpose with Multicomputing Modeling Coupled with GIS: Case of El Hamma, Southeastern Tunisia

Geothermal Water Quality Index Assessment for Irrigation Purpose with Multicomputing Modeling Coupled with GIS: Case of El Hamma, Southeastern Tunisia

Impact of Dumpsite Leachate Contamination on Surface Water at Beris Lalang Dumpsite, Kelantan

Leachate from dumpsites poses a significant threat due to its potential to contaminate surface water, damage local biodiversity, and negatively impact human health. This research focuses on assessing the environmental risks associated with leachate from the Beris Lalang Dumpsite. The aim of the study is to analyze the physical and chemical properties of leachate contamination in nearby surface water. Water samples were collected from four different locations, and the physical and chemical characteristics were evaluated. The Water Quality Index (WQI) and Leachate Pollution Index (LPI) were also calculated. The findings reveal the levels of pollutants were high at surface water samples close to the landfill. According to the WQI assessment, all locations fall under Class III. The LPI assessment indicates that the locations have a low pollution level. Although heavy metals such as zinc, arsenic, and iron were detected, the Heavy Metal Pollution Index (HPI) shows that all locations are considered safe and not highly contaminated. The study highlights the environmental impact of leachate and its potential effects on surface water near the Beris Lalang dumpsite. Additionally, it offers important insights into preventing pollution and safeguarding water resources.

Optimisation and interpretation of machine and deep learning models for improved water quality management in Lake Loktak

Loktak Lake, one of the largest freshwater lakes in Manipur, India, is critical for the eco-hydrology and economy of the region, but faces deteriorating water quality due to urbanisation, anthropogenic activities, and domestic sewage. Addressing the urgent need for effective pollution management, this study aims to assess the lake's water quality status using the water quality index (WQI) and develop advanced machine learning (ML) tools for WQI assessment and ML model interpretation to improve pollution management decision making. The WQI was assessed using entropy-based weighting arithmetic and three ML models — Gradient Boosting Machine (GBM), Random Forest (RF) and Deep Neural Network (DNN) — were optimised using a grid search algorithm in the H2O Application Programming Interface (API). These models were validated by various metrics and interpreted globally and locally via Partial Dependency Plot (PDP), Accumulated Local Effect (ALE) and SHapley Additive exPlanations (SHAP). The results show a WQI range of 72.38–100, with 52.7% of samples categorised as very poor. The RF model outperformed GBM and DNN and showed the highest accuracy and generalisation ability, which is reflected in the superior R2 values (0.97 in training, 0.9 in test) and the lower root mean square error (RMSE). RF's minimal margin of error and reliable feature interpretation contrasted with DNN's larger margin of error and inconsistency, which affected its usefulness for decision making. Turbidity was found to be a critical predictive feature in all models, significantly influencing WQI, with other variables such as pH and temperature also playing an important role. SHAP dependency plots illustrated the direct relationship between key water quality parameters such as turbidity and WQI predictions. The novelty of this study lies in its comprehensive approach to the evaluation and interpretation of ML models for WQI estimation, which provides a nuanced understanding of water quality dynamics in Loktak Lake. By identifying the most effective ML models and key predictive functions, this study provides invaluable insights for water quality management and paves the way for targeted strategies to monitor and improve water quality in this vital freshwater ecosystem.

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.

Water Quality Index Assessment of River Ganga at Haridwar Stretch Using Multivariate Statistical Technique.

The Ganges (Ganga) river contributes significant water resources for the ecology and economy, but it frequently encounters severe deterioration due to cumulative impact from upstream natural and anthropogenic variables. Knowledge and understanding ofthe dynamic behavior of such networks remain a significant challenge, particularly in the context of rising environmental pressures, such as climate change and industrialization, as well as constraints in both process and data understanding across geographies. An interdisciplinary approach is required to be developed to investigate the hydrogeochemical dynamics and anthropogenic sources influencing water quality in major river systems. The present study has been carried out to evaluate the characterization of river water quality in terms of the physico-chemical & bacteriological parameters. Also, the development of a water quality index (WQI) for Domestic (drinking) and Spiritual (bathing) usage is a part of the study. The water quality index has been developed using the Canadian Council of Ministers of the Environmental Water Quality Index (CCME WQI). The river's water quality index score in the present study lies in the range of 38.32 to 79.82, indicating the quality of water from fair to poor for drinking purposes. The highest water quality index value of 79.82 has been observed at Guru Kashnik Ghat, while the lowest WQI value of 38.32 has been observed at Har ki Pauri for drinking purposes. However, the water quality score for bathing purposes ranged from 71.04 to 91.22 thus signifying the quality of the water from fair to good for bathing purposes. The highest water quality index value of 91.22 has been assessed at Guru Kashnik Ghat, while the lowest WQI value of 71.04 has been assessed at Bhimgoda Barrage. The developed water indices assessment in the present study will be beneficial for society to provide a benchmark for the control of water pollution in River Ganga. These findings will support policymakers and stakeholders in addressing water quality issues in a more efficient and effective manner. The study also emphasizesthe requirement for ongoing water quality monitoring and evaluation in order to guarantee the long-term well-being of the river and its ecosystems.

Multiple Evaluations of the Spatial and Temporal Characteristics of Surface Water Quality in the Typical Area of the Yangtze River Delta of China Using the Water Quality Index and Multivariate Statistical Analysis: A Case Study in Shengzhou City.

Surface water assessments are of critical importance for balancing economic development with the ecological environment in rapidly developing regions. In this research, Shengzhou City, a typical town in the Yangtze River Delta region of China, was chosen to conduct a surface water quality study. As a region with a well-developed water system, monthly water quality monitoring data from eight sampling sites on the major tributaries and the mainstream were selected for six consecutive years from 2013 to 2018, containing seven important water quality indicators (pH, DO, CODMn, CODCr, BOD, NH4+-N, and TP). The comprehensive evaluation method based on the water quality index (WQI) and multivariate statistical analysis methods of cluster analysis (CA) and principal component analysis (PCA) were applied to explore the spatial and temporal changes of water quality in Shengzhou City. The main findings are as follows: (1) spatially, for three main tributaries, Xinchang River had the worst water quality, followed by Changle River, while Huangze River had the best. The water quality of the tributaries had higher volatility than the mainstream. (2) The sampling sites with similar locations had similar water quality characteristics. (3) Seasonally, for the four indicators of DO, CODMn, CODCr, and BOD, the water quality was better in the dry season while, for NH4+-N and TP, water quality was better in the wet season. The low WQI points were more likely to appear in the wet season. (4) The results of WQI assessment showed an improving trend in water quality. (5) Nitrogenous substances and organic matter were the key pollutants in this area. The research results prove that water quality evaluation methods and multivariate statistical methods are effective for the study of regional surface water quality.

Water quality Index Assessment of the Groundwater of Industrial area and absorption by Polymer Composites

Introduction: Water play a pivtol role in the existence in the human life. water quality index is assessing the overall quality of water based on location, time and some parameters of water. water quality index is important tool for assessing the quality water on the surface. Water quality index assessing is the important parameter helps in improving the quality of drinking and ground water. Due to anthropogenic activites the quality of ground and drinking water is decreased. Objective: The main objective of research is to find the water quality index of the ground water and bore water in selected industrial area of the Kakinada and analyse the water quality index of it and absorption of ions by polymer composites for desalination and water treatment. Methodology: the water quality inex is calculated based on icmr standards. Results: The research results revealed that the sampling sites S-1,S-2 and S-3 is water quality index is less than 100 which is treated the poor quality of drinking water. The S-4,S-5,-6,S-7S-8,S-9,S-10,S-11,S-12 the water quality index is greater than 100 which is not suitable for drinking water. Conclusion: The water quality index observed at various stations shows that some places are not fits for drinking S-1,S-2 and S-3 are below 100 are very poor and S4-S12 sites are more polluted and unfit for drinking. The ground water is need to protected from pollution and govt need to take necessary measures to improve the quality of ground water and cyclodextrin polymer composites effective composite for removal of hardness and desalination.

Water Quality Index Assessment of Bada Talab, Chhatarpur, (M.P.) India

This study focuses on assessing the water quality of “Bada Talab” at five different sampling sites over the course of one year, from January 2022 to December 2022.In this study, various physico-chemical parameters were used to assess the water quality. The parameters tested are Nitrate, DO,Temperature, pH, EC, Turbidity, TS,TDS, TSS, Fluoride, Total Hardness, BOD and Iron on Pre-monsoon, Monsoon and post-Monsoon basis. The Water Quality Index (WQI) is a composite index that takes into account several water quality parameters to provide an overall assessment of water quality. In this study, the calculated WQI values indicate that the lake is moderately and slightly polluted. As a result, the water may not be suitable for direct domestic use without treatment. However, it is considered acceptable for irrigation and other non-potable purposes.

Characterization and assessment of groundwater from Obafemi Awolowo University campus, southwestern Nigeria

This study deduced groundwater contaminant sources and the processes controlling groundwater chemistry using Principal Component Analysis (PCA), rock source deduction and Water Quality Index (WQI), all with a view to characterize and assess the groundwater. Groundwater sampling was performed at Obafemi Awolowo University (OAU), Ile-Ife, Southwestern Nigeria. A total of 41 groundwater samples were collected in dry season (November) and subjected to physicochemical analyses. Twelve (12) parameters (pH, TDS, electrical conductivity, temperature, Calcium, Magnesium, Sodium and Potassium, Bicarbonate, Chloride, Sulphate and Nitrate) were analysed. PCA analysis highlighted five principle components (PC–I, PC-II, PC-III, PC-IV and PC-V), which explained 82% of the total variance in the hydrogeochemical data. PC-I to PC-V had loading for Ca2+ and SO42−; Na+ and K+; EC and TDS; Mg2+ and HCO3−; and pH and temperature, respectively. The PCA and source rock deductions revealed that the groundwater chemistry is influenced by geogenic effects of weathering and rock-water interaction, and non-geogenic effects of precipitation and organic processes. Based on the WQI assessment, the groundwater quality was adjudged good to excellent.

Sobol sensitivity analysis for non-carcinogenic health risk assessment and water quality index for Kohgiluyeh and Boyer-Ahmad Province, Western Iran

Human activities and climate may have an impact on the water quality of reservoirs. Therefore, the present research aims to use the entropy water quality index assessment technique to analyze the water quality features of the main water supply reservoirs as well as to investigate the effect of water parameters on the water quality of the reservoirs. In this study, the total non-carcinogenic health risks from various exposure paths were estimated for adults and children. The water quality of the major water supply reservoirs in Kohgiluyeh and Boyer-Ahmad province was typically poor and unfit for human consumption. Besides, the non-carcinogenic risk was higher in males (0.958–1.497) and children (1.065–1.664) than in females (0.879–1.374) according to health risk assessments. Among the factors under study, magnesium and nitrate had the highest influence on the non-carcinogenic risk. Finally, the sensitivity of each of the parameters affecting the non-carcinogenic risk was assessed using Sobel sensitivity analysis. The results indicated that the nitrate concentration (Cw) and Ingestion Rate (IR) were the most sensitive in the oral state, while Cw and fraction of skin’s surface area (F) were more sensitive in the dermal state.

The impact of anthropogenic and environmental factors on the variability of Escherichia coli in rivers in southwest Bangladesh

Faecal contamination of surface water sources is an important water quality issue worldwide. Although quite a few studies exist on surface water faecal contamination and variability of indicator bacteria, most of the studies have been based on larger river basins and in temperate region. The variability is relatively unknown in local scale and in tropical developing countries. In this study, we assess how anthropogenic and environmental factors affect faecal contamination and physicochemical parameters in Rupsha and Bhairab rivers around Khulna city, Bangladesh. Water samples were collected from six locations of the rivers during a wet and dry period in 2018 to measure Escherichia coli (E. coli) concentrations applying membrane filtration method. Of the physicochemical parameters examined, turbidity, biochemical oxygen demand, and chemical oxygen demand showed higher levels of spatial variability (variation over 30%). Higher concentrations of E. coli were found in the sampling sites located near the densely populated urban area compared to the downstream site, which receives fewer amounts of discharges from sewer drains. After rainfall events E. coli concentrations were increased by about one order of magnitude compared to dry weather conditions, this is in line with expectations that runoff from urban and agricultural areas brings pathogens into the rivers. All the E. coli samples violated bathing water quality standards. E. coli concentrations were found to be correlated positively with precipitation and turbidity. A linear regression model was applied, that explains large part of the variation in E. coli concentration (R2 = 0.42). Water quality index assessment also ranked the water quality as ‘poor’ category indicating high health risks involved with the water use. Therefore, the river water should not be used for domestic, recreational or bathing purposes. The study findings highlight the problem of untreated sewage discharge into the rivers. Implementation of sewage treatment plant with adequate capacity is highly recommended.

Water quality index for assessment of drinking groundwater purpose case study: area surrounding Ismailia Canal, Egypt

The dramatic increase of different human activities around and along Ismailia Canal threats the groundwater system. The assessment of groundwater suitability for drinking purpose is needed for groundwater sustainability as a main second source for drinking. The Water Quality Index (WQI) is an approach to identify and assess the drinking groundwater quality suitability.The analyses are based on Pearson correlation to build the relationship matrix between 20 variables (electrical conductivity (Ec), pH, total dissolved solids (TDS), sodium (Na), potassium (K), calcium (Ca), magnesium (Mg), chloride (Cl), carbonate (CO3), sulphate (SO4), bicarbonate (HCO3), iron (Fe), manganese (Mn), zinc (Zn), copper (Cu), lead (Pb), cobalt (Co), chromium (Cr), cadmium (Cd), and aluminium (Al). Very strong correlation is found at [Ec with Na, SO4] and [Mg with Cl]; strong correlation is found at [TDS with Na, Cl], [Na with Cl, SO4], [K with SO4], [Mg with SO4] and [Cl with SO4], [Fe with Al], [Pb with Al]. The water type is Na–Cl in the southern area due to salinity of the Miocene aquifer and Mg–HCO3 water type in the northern area due to seepage from Ismailia Canal and excess of irrigation water.The WQI classification for drinking water quality is assigned with excellent and good groundwater classes between km 10 to km 60, km 80 to km 95 and the adjacent areas around Ismailia Canal. While the rest of WQI classification for drinking water quality is assigned with poor, very poor, undesirable and unfit limits which are assigned between km 67 to km 73 and from km 95 to km 128 along Ismailia Canal.

Performance Evaluation and Water Quality Index Analysis for Qandil Water Treatment Plant

Water treatment plant (WTP) is essential for supplying water with the accepted quality to the consumer. There is a necessity to evaluate the performance of WTP for proper treatment of raw water. The present study aimed to evaluate the performance of Qandil WTP units, Erbil City, Iraq. For assessment the WTP units, water samples were collected from raw water, after clarification, after filtration, and storage tank. Removal efficiencies for the clarifiers, filtration unit, storage tank, and the whole WTP were calculated and presented. Obtained removal efficiencies for the sedimentation unit, filtration unit, after disinfection, and the entire Qandil WTP were 85.13 %, 90.50 %, 31.9, and 99.178 %, respectively. In addition, water quality index (WQI) for the WTP was studied. WQI assessment was made by testing 13 physicochemical water quality such as turbidity, pH, electrical conductivity (EC), total dissolved salts etc... It has been found that turbidity, electrical conductivity, total alkalinity, and total hardness have more influence on drinking water quality. WQI for Qandil WTP was 41.59 and it regarded as excellent level.

Water quality index assessment methods for surface water: A case study of the Citarum River in Indonesia

Water quality index (WQI) can express overall water quality status in a single term. As such, the application of daily WQI assessment should help the general public be more aware of the condition of the surface water around them. As the longest and biggest river in the West Java Province, the Citarum River plays an important role in the life of the community and ecosystem around it. Therefore, this research evaluated which WQI assessment method was best suited for determining the Citarum River's water quality. We utilized West Java Province monitoring data collected from four monitoring stations along the Upstream Citarum. The WQI was calculated using the National Sanitation Foundation WQI (NSF WQI), Canadian Council of Ministers of the Environment WQI (CCME WQI), and Oregon Water Quality Index (OWQI) assessment methods. Nine years of monitoring data were grouped and analyzed according to wet vs. dry months, wet vs. dry years, monitoring station, and year. Using the NSF WQI assessment method, the Citarum River obtained a ‘Fair’ and ‘Bad’ water quality grade with WQI ranging between 38.212 and 60.903 during dry months, 49.089 and 62.348 during wet months, 42.935 and 65.696 during dry years, and 39.002 and 58.898 during wet years. The data ranged from 41.458 and 61.206 from each monitoring station, and between 35.920 and 58.713 for the data from each monitoring year. The CCME WQI assessment method showed that the Citarum River had ‘Fair’, ‘Marginal’, and ‘Bad’ water quality with WQI ranging between 12.683 and 31.503 during dry months, 21.231 and 33.127 during wet months, 12.683 and 31.503 during dry years, 12.134 and 28.748 during wet years, 13.621 and 30.569 for the data from each monitoring station, and 13.219 and 68.808 for the data from each monitoring year. The OWQI assessment method gave the Citarum River a ‘Very Bad’ water quality rating with WQI ranging between 11.528 and 18.827 during dry months, 13.898 and 24.563 during wet months, 11.528 and 25.782 during dry years, 11.528 and 15.997 during wet years, 11.528 and 18.842 for each monitoring station, and 11.523 and 16.528 for the data from each monitoring year. Based on these results and the collated advantages and disadvantages of each method, the NSF WQI assessment method was deemed to be the best for determining the Citarum River's water quality.

Physicochemical, bacteriological and water quality index assessment of hand dug well (HDW) water suitability for drinking

ABSTRACT Underground water were abstracted from HDWs to determine their suitability for drinking. Physical, chemical and bacteriological parameters were carried out following standard guidelines. Total coliform count was done using the membrane filtration method. Heavy metal was determined using an Atomic Absorption Spectrophotometer (AAS BULK SCIENTIFIC MODEL 210 VGP). Samples were subjected to statistical and multivariate analysis. Results of physicochemical parameters show that they were all within the WHO standard for drinking. Cation concentrations follow the order: Na+ > Ca2+ > Mg2+ > K+, while anions are: HCO3 − > SO4 2-> Cl−> NO3 − > PO4 2-. As, Cd and Pb were not detected in the sampled water, but other heavy metals Cr, Cu, Fe, Mn and Zn were detected. They were, however, within the WHO’s recommended range. Based on E. coli analysed, all of the water samples were free from faecal contamination since none was discovered in the water samples. Based on the water quality index, only sample G hand-dug well is of poor quality (though it could be treated) for human consumption; all other samples are good for human consumption. Deductions from Pipers’ and the Durov diagram, as well as principal component analysis, revealed that there was little geological and human activity within the hand-dug wells. Based on the physicochemical, microbiological, heavy metal and water quality indexes, this study indicates that all of the water samples examined are free of pollution, but that continual monitoring of the hand-dug wells should be prioritised.

Water quality index assessment for drinking and irrigation purpose for Wardha district

It is always said that groundwater is safe for consumption i.e. free from micro-organisms. But in many places, the groundwater is subjected to contamination due to human and industrial activities. The unsafe disposal of domestic and industrial wastes is found to be the main source for contamination of groundwater with micro-organisms, nitrates, etc. Therefore, it is inevitable to assess the quality of groundwater in terms of the Water Quality Index (WQI) before it is supplied to the end-user. Water Quality Index (WQI) is an index that converts complex data about water quality into the simplest form. This manuscript discusses the level of contamination of groundwater in the villages situated in the vicinity of Wardha River in Wardha District. Groundwater samples were collected during ninety days starting from 1st May 2021 to 30th July 2021. Analysis was carried out for the assessment of 12 parameters and their WQI. The results reveal that 40% of the 12 parameters assessed are higher values whereas, 60% of the 12 parameters assessed are reported safe values as per Indian Standards for Drinking Water. On the other hand, WQI for all the groundwater samples (barring very few) has shown bad quality.