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Numerous indicator models have been developed and utilized for the assessment of pollution levels in water resources. In the present study, modified water quality index (MWQI), integrated water quality index (IWQI), and entropy-weighted water quality index (EWQI) were integrated with statistical analysis for the assessment of drinking water quality in Umunya suburban district, Nigeria. There is no known study that has simultaneously compared their performances in water quality research. Overall, the results of this study showed that the water supplies are threatened by heavy metal pollution. The parametric quality rating analysis observed that Pb contamination has the most significant impact on the water supplies. Hierarchical cluster analysis was proved very efficient in the allotment of the possible sources of pollution in the study area. MWQI results classified the water supplies as “marginal”, signifying that they are frequently threatened. Based on the IWQI, 26.67% of the samples are suitable for drinking, 13.33% are acceptable for domestic uses, and 60% are unfit for drinking purposes. Similarly, the EWQI results showed that 60% of the samples are unfit for human consumption, whereas 40% are suitable. Investigation into the performance and sensitivity of the MWQI, IWQI and EWQI models in water quality assessment was analyzed and the results showed that they are all sensitive, efficient and effective tools. This study has indicated that the integration of the three models gives a better understanding of water quality. The excessive concentration of some potentially toxic heavy metals in the water supplies suggests that the contaminated water supplies should be treated before use.

In many parts of the world, groundwater is considered to be a key source of fresh water for both the domestic and non-domestic sectors. Where groundwater extraction is implemented, systems to monitor water quality must ensure a safe and sustainable supply. Over the years, Iraq has suffered from surface water quality and supply problems, necessitating groundwater extraction in many regions. This study investigates groundwater quality in a region of central Iraq around Babylon city, covering an area of 5119 km 2 . The data gathered for this study included maps, well locations and water quality data and was sourced from the relevant governmental departments. A base map of the focussed region was initially prepared following data collection. The analysed water quality parameters were used as an attribute database to produce thematic maps using a geographical information system (GIS) environment. In this paper, the water quality index (WQI) and the irrigation water quality index (IWQI) were calculated for different groundwater samples using various parameters including the Electrical Conductivity (EC), Cl − , HCO3 − , Na + and pH. Moreover, the groundwater suitability for irrigation purposes has been assessed using indices such as Kelly’s ratio (KR), sodium absorption ratio (SAR), residual sodium carbonate (RSC), soluble sodium percentage (SSP) and permeability index (PI). Water quality index maps have been developed using the GIS environment. The obtained results reveal that the groundwater in the study location requires specific treatments to be usable.

In this study, water supplies for the two distinct climatic seasons, wet and dry seasons, were evaluated. This was carried out to determine the degree of contamination and whether the water supplies were safe for human consumption. In light of this, four water quality indices; the vector modulus of Pollution Index (PIvector), Entropy-weighted Water Quality Index (EWQI), Integrated Water Quality Index (IWQI), and Modified Water Quality Index (MWQI) were integrated. Based on the results, the pH of the analyzed water samples varied from 6.02 to 7.92 with a mean value of 7.2 during the wet season and from 5.25 to 8.25 with a mean value of 6.82 during the dry season. A generic quality assessment study revealed that Pb, As, during the wet season and Pb, As, and Mn during the dry season has the greatest effects on the region's water supplies. According to the indices, PIvector classified approximately 71.43% of the water during the wet season as unpolluted and 28.57% as polluted, and 37.14% of the water during the dry season as unpolluted and 62.86% as polluted. Similarly, the EWQI classified 65.71% as safe water and 34.28% as unfit for human consumption during the wet season, whereas, 34.28% and 65.72% as safe and unfit, respectively for the dry season. According to IWQI, during the wet season, 25.7% of the water is considered acceptable for drinking, while 74.3% is unsafe, and during the dry season, 14.85% is acceptable and 85.15% is unsafe. The MWQI results indicated that the water samples for the wet season were classed as \"fair\" water suggesting they are occasionally threatened while, for the dry season as “marginal” water indicating they are frequently threatened. Summarily, the results show that the water resources are safer and less contaminated in the wet season than in the dry season, which is attributed to the impact of rainfall, which reduces the mobility of contaminants, as well as the influence of vegetation cover.

The assessment of water quality has turned to be an ultimate goal for most water resource and environmental stakeholders, with ever-increasing global consideration. Against this backdrop, various tools and water quality guidelines have been adopted worldwide to govern water quality deterioration and institute the sustainable use of water resources. Water quality impairment is mainly associated with a sudden increase in population and related proceedings, which include urbanization, industrialization and agricultural production, among others. Such socio-economic activities accelerate water contamination and cause pollution stress to the aquatic environment. Scientifically based water quality index (WQI) models are then essentially important to measure the degree of contamination and advise whether specific water resources require restoration and to what extent. Such comprehensive evaluations reflect the integrated impact of adverse parameter concentrations and assist in the prioritization of remedial actions. WQI is a simple, yet intelligible and systematically structured, indexing scale beneficial for communicating water quality data to non-technical individuals, policymakers and, more importantly, water scientists. The index number is normally presented as a relative scale ranging from zero (worst quality) to one hundred (best quality). WQIs simplify and streamline what would otherwise be impractical assignments, thus justifying the efforts of developing water quality indices (WQIs). Generally, WQIs are not designed for broad applications; they are customarily developed for specific watersheds and/or regions, unless different basins share similar attributes and test a comparable range of water quality parameters. Their design and formation are governed by their intended use together with the degree of accuracy required, and such technicalities ultimately define the application boundaries of WQIs. This is perhaps the most demanding scientific need—that is, to establish a universal water quality index (UWQI) that can function in most, if not all, the catchments in South Africa. In cognizance of such a need, this study attempts to provide an index that is not limited to certain application boundaries, with a contribution that is significant not only to the authors, but also to the nation at large. The proposed WQI is based on the weighted arithmetic sum method, with parameters, weight coefficients and sub-index rating curves established through expert opinion in the form of the participation-based Rand Corporation’s Delphi Technique and extracts from the literature. UWQI functions with thirteen explanatory variables, which are NH3, Ca, Cl, Chl-a, EC, F, CaCO3, Mg, Mn, NO3, pH, SO4 and turbidity (NTU). Based on the model validation analysis, UWQI is considered robust and technically stable, with negligible variation from the ideal values. Moreover, the prediction pattern corresponds to the ideal graph with comparable index scores and identical classification grades, which signifies the readiness of the model to appraise water quality status across South African watersheds. The research article intends to substantiate the methods used and document the results achieved.

The study was conducted to evaluate the physicochemical parameters of water and assess the public perception of the water quality status in the Tasik Chini watershed based on a community survey. The water sample was analyzed based on standard methods and categorized according to WQI (Water Quality Index). Multivariate statistical analysis was adopted to find spatial variations in water quality, determining the pollution level and sources of contamination. The study results were compared with NWQS (National Water Quality Standard for Malaysia). The results showed that the value of dissolved oxygen (DO) was low (4.68 mg.L-1), while the level of biological oxygen demand (BOD), chemical oxygen demand (COD), and total dissolved solids (TDS) was found to be high, 2.92 mg.L-1, 26.10 mg.L-1 and 22.93 mg.L-1 respectively. High turbidity was recorded in a mining area in the rainy season (35.76 NTU). The DOE-WQI value categorized the lake under class II and class III. The Principal Component Analysis (PCA) revealed that the major sources of contamination were due to anthropogenic activities, especially settlement, mining, agriculture, and illegal activities. Overall, Tasik Chini’s water quality status was classified as slightly polluted to highly polluted based on hierarchical cluster analysis (CA) results. The survey showed that 55% of the local community reported that the water quality was poor. The knowledge and attitude level of the local people was medium category, while community practice was low. The Pearson correlation coefficient test showed a strong significant relationship at 0.01 level between knowledge and attitude and knowledge and practices. The scientific findings with public perceptions might be useful for policymakers and the general public to improve the management system for a desirable future.

Background: Water quality is usually measured using various indicators based on physical, chemical and biological parameters. By using the biological index that is based on the identification of the arthropod families, it is possible to make a logical judgment about the ecosystem condition. The aim of this study was measuring correlation coefficients between qualitative and biological Indices. Methods: Water samples were collected 27 samples in northwest of Iran and aquatic insects’ samples 54 in 2019. The NSFWQI and IRWQISC as the most important indices of physical and chemical quality of water ranged from 54.45–76.21 and from 41.32 to 77.40, respectively. Results: A total of 2,953 aquatic insects were collected, and biological Index ranged from 6.26 to 3.38. It can be stated that increasing in the concentration of pollutants in the source and end of the river could lead to a sharp decrease in bio­logical index. IRWQISC index, the effluent stations of fish farms can fit into ‘fairly bad quality’ and ‘moderate quality’ categories. Conclusion: The linear regression analysis revealed a significant relationship between the Hilsenhoff biological Index and the physiochemical parameters of pH, DO (Dissolved Oxygen) and total dissolved solids. The activity of fish farms and discharging their effluents into water sources, can change the physical, chemical and biological parameters of re­ceiving waters, therefore it is recommended that the location of these units be reviewed and also the appropriate treat­ment for such effluents should be considered, so that the health risks caused by them can be effectively reduced.

The expansion of urbanization and the amplification of anthropic activities in the Rif region require the establishment of wells. However, the irrational exploitation of water and natural conditions have generated the rise of the water table and the increase in pollution. Thus, the assessment of water quality has emerged as a significant concern. This study’s goal is to assess the adequacy of groundwater quality in two aquifers in the vicinity of the Mediterranean Zone - Drouich Province and Oriental Region, Morocco, for drinking water needs by taking 62 water samples of the Kert aquifer for 2019. The Water Quality Index (WQI) classifies water quality: as excellent, good, poor, very poor, etc. That is essential for conveying information about water quality to people and decision-makers in the affected area. The WQI in the Kert aquifer varies from 62.3 to 392.3. The calculation of the water quality index (WQI) of the Kert aquifer view is based that 45.16% of groundwater samples are of poor quality, making them acceptable for drinking. The study’s analysis is established with a geographic information system (GIS) setting. The index map provides decision-makers with a complete and interpretable picture for better water resource planning and management. SVM models are shown to account for 87.71% of the varying water quality score. Different statistical and intelligence models may make the index more predictable. These forecasts assist us in better managing the aquifer’s water quality.

The study investigated poultry waste effect on water quality of shallow wells in Asa and Ilorin, south local government areas of Kwara State. The factors considered are the number of birds (N), years of existence of the farm (Y), and the distance between the shallow wells and the poultry dump sites (D). Physicochemical parameters of the water collected were analyzed. The data obtained were analyzed using SPSS Software (Version 16.0). For the number of birds, the result shows that the mean turbidity, Chemical Oxygen Demand COD, and fecal coliform were between 23.25 -101.92 NTU, 85.22-111.56 mg.L-1, and 0.00-0.34 cfu.mL-1 respectively. For the year of existence of the farm, the mean turbidity, phosphate, COD were between 14.10-56.6 NTU, 1.07-2.30 mg.mL-1, 88.00-95.43 mg.mL-1 respectively. The mean turbidity was found to be between 11.81 NTU and 58.85 NTU, phosphate 1.09-2.06 mg.mL-1, COD 86.73-94.57 mg.mL-1, and fecal coliform 0.00-0.24 cfu.mL-1 for the distance between dumpsites and water source. The number of birds has a significant effect on turbidity, BOD, COD and fecal coliform at p ≤ 0.05 compared to the measured control 400 m away from the dumpsites. As a result, there is evidence of pollution risks from poultry wastes. Proper treatment and the placement of farms far away from dumpsites will assist maintain the water’s suitability and sustainability.

The rising concerns surrounding water scarcity have prompted a closer examination of water sources to determine their suitability for various purposes based on their quality. Multivariate Statistical Analysis (MSA) is often used for grouping pollution sources based on their shared characteristics. Techniques such as Pearson's correlation coefficient analysis, Principal Component Analysis (PCA), and Hierarchical Cluster Analysis (HCA) are employed for in-depth parametric analysis. Additionally, the quantification of these parameters is carried out using both traditional Water Quality Index (WQI) methods and the newer Modified Water Quality Index (MWQI). For the present study, the MSA revealed elevated levels of electrical conductivity (EC), biochemical oxygen demand (BOD), and chemical oxygen demand (COD), primarily due to sediment influx from watershed areas and increased agricultural activities around the lakes. HCA indicated moderate pollution levels, further corroborated by the three selected WQI techniques. Overall, the water quality in both lakes was deemed ‘good’ across their entire expanse, suggesting they can be used directly for activities such as bathing, boating, and irrigation. However, for drinking purposes, some degree of treatment was still necessary.

The objective of the research was to determine the water quality index of Lake Chinchaycocha, which has faced pollution problems for several years. To do this, we worked with data from ten water quality monitoring points collected by the National Water Authority (ANA) during the period 2019-2023, after which the water quality index (ICA-PE) was calculated by analyzing a total of 12 parameters, using the Water Quality Standard (ECA) for water category 4 E1 (lagoons and lakes). The results of the physicochemical parameters indicated that the values of total nitrogen exceed the limits established in the ECA in 82% of the data obtained, pH in 13%, and phosphorus in 1%. In the evaluation of inorganic parameters, data from the LChin1S monitoring point showed that lead and zinc levels exceeded the values established in the ECA by 8% and 3%, respectively. Regarding the ICA-PE of the dry and wet seasons, it was determined that both present a good quality according to their averages and with the results obtained from the ICA-PE in a general way, it is concluded that Lake Chinchaycocha has a good water quality having total nitrogen as the main pollutant.