Evaluation of water quality using water quality index (WQI) method and GIS in Aksu River (SW-Turkey)

Water Quality Index (WQI) as a Potential Proxy for Remote Sensing Evaluation of Water Quality in Arid Areas

Water Resource Sustainability Management plays a vitally important role in ensuring sustainable development, especially in water-stressed arid regions throughout the world. In order to achieve sustainable development, it is necessary to study and monitor the water quality in the arid region of Central Asia, an area that is increasingly affected by climate change. In recent decades, the rapid deterioration of water quality in the Ebinur Lake basin in Xinjiang (China) has severely threatened sustainable economic development. This study selected the Ebinur Lake basin as the study target, with the purpose of revealing the response between the water quality index and water body reflectivity, and to describe the relationship between the water quality index and water reflectivity. The methodology employed remote sensing techniques that establish a water quality index monitoring model to monitor water quality. The results of our study include: (1) the Water Quality Index (WQI) that was used to evaluate the water environment in Ebinur Lake indicates a lower water quality of Ebinur Lake, with a WQI value as high as 4000; (2) an introduction of the spectral derivative method that realizes the extraction of spectral information from a water body to better mine the information of spectral data through remote sensing, and the results also prove that the spectral derivative method can improve the relationship between the water body spectral and WQI, whereby R2 is 0.6 at the most sensitive wavelengths; (3) the correlation between the spectral sensitivity index and WQI was greater than 0.6 at the significance level of 0.01 when multi-source spectral data were integrated with the spectral index (DI, RI and NDI) and fluorescence baseline; and (4) the distribution map of WQI in Ebinur Lake was obtained by the optimal model, which was constructed based on the third derivative data of Sentinel 2 data. We concluded that the water quality in the northwest of Ebinur Lake was the lowest in the region. In conclusion, we found that remote sensing techniques were highly effective and laid a foundation for water quality detection in arid areas.

Water quality assessment, multivariate analysis and human health risks of heavy metals in eight major lakes in Kenya

This study evaluates water quality, concentrations and health risks of heavy metals (HMs) in eight major lakes in Kenya namely Naivasha, Elementaita, Nakuru, Baringo, Bogoria, Turkana, Victoria and Magadi. Water quality was assessed using water quality index (WQI) and pollution evaluation index (PEI), while human health risk associated with ingestion and dermal contact of HMs was assessed using hazard quotients (HQ) and hazard index (HI). Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used to deduce the probable sources of the HMs. The average concentration of aluminium (Al), molybdenum (Mo), manganese (Mn), nickel (Ni), arsenic (As), zinc (Zn), selenium (Se), lead (Pb), chromium (Cr), mercury (Hg), cobalt (Co) and cadmium (Cd) in the eight lakes was 824.6, 66.1, 58.9, 16.2, 8.40, 7.84, 6.91, 4.65, 2.66, 0.86, 0.78 and 0.46, respectively, all in μg/L. Al, Mn, As, and Mo were relatively high in Rift Valley lakes and exceeded the maximum permissible levels for drinking water. Notably, high HM concentrations were recorded at the entry points of rivers and areas with high human activities. Lake Magadi had the highest average WQI of 158.8 followed by lake Elementaita (128.4), Bogoria (79.5), Nakuru (73.3), Turkana (57.6), Victoria (52.3), Baringo (42.6) and Naivasha (25.5). Lake Magadi also had the highest average PEI of 40.0 followed by Elementaita (30.1), Bogoria (16.2), Nakuru (15.7), Victoria (10.8), Baringo (9.57), Turkana (9.53) and Naivasha (5.12). Based on WQI, Lake Naivasha water was excellent for drinking, Lake Victoria, Turkana, Baringo, Nakuru, and Bogoria had good water, but water from Lake Elementaita and Magadi was of poor quality. PEI classified the lakes as minimally polluted except Lake Magadi. Multivariate analysis concluded that Pb, Cr, Ni and Se had anthropogenic sources, mainly agricultural and urban runoff, but other HMs had natural influence. Although the HMs did not pose any health risks through dermal contact, HQingestion was >1 for adults and children consuming water from Lake Elementaita, Nakuru, Bogoria and Magadi due to non-carcinogenic risks associated with As, Zn and Mo. These results are important for formulating the necessary remediation policies to improve water quality in the eight lakes.

The Effect of Urban Land-Use Change on Runoff Water Quality: A Case Study in Hangzhou City

The main functions of this research are to guide the proportion of urban land that is used and the layout of the facilities on it, help understand the changes to surface runoff that are caused by land being used in urban development, and thus solve surface runoff pollution. Hangzhou City, China has been selected for the experiment, and the way in which its land is utilized as well as the grading of urban construction projects in the demonstration area are specifically analyzed. This study systematically distinguishes the definitions of impervious area based on the Sutherland equation and analyzes the impact of different impervious area subtypes on surface runoff water quality. Then, we compare the impact of impervious area subtypes with the impact of other land-use patterns on surface runoff water quality. This study shows the relationship between different land-use types and runoff water bodies: Land-use index can affect runoff water quality; Greening activities, impervious surface, and the water quality index are negatively correlated; the effective impervious area rate is positively correlated with the water quality index. The paper suggests that increasing the proportion of green spaces and permeable roads in build-up land reduces the effective impervious area (EIA) and thus controls land runoff pollution and improves runoff water quality.

Hydrochemical Assessment of the Irrigation Water Quality of the El-Salam Canal, Egypt

The El-Salam canal in Egypt is considered an important stream of fresh water for the agricultural sector that extends from the Nile River to Sinai, while it is subjected to several anthropogenic stresses. In this study, five-georeferenced stations (named from S1 to S5) were monitored along the El-Salam Canal before El-Sahara of the Suez Canal, via the estimation of the WQ index based on major cations and anions analysis including salinity hazard, permeability index, residual sodium carbonate, magnesium hazard, sodium percentage, sodium adsorption ratio, Kelley index, potential salinity, total hardness, and irrigation water quality index (IWQI). The sequence of average concentration of cations in water were Na+ > Ca2+ > Mg2+ > K+. The major cations constitute around 60% of the total dissolved salts. While the sequence of major anions in water were SO42− > HCO3− > Cl− > CO32−. These cations and anions showed an increasing trend from S1 (intake of the canal) to S5 (before El-Sahara) of the El-Salam Canal. Moreover, the order of heavy metals was Zn < Cd < Cr < Ni < Fe < Mn < Co < Cu < Pb. According to the US EPA (1999) guidelines, the levels of Fe and Zn in the El-Salam Canal are within the permissible limits for drinking and irrigation purposes, while Mn, Pb, Cu, Co, Ni, Cr, and Cd were detected at higher concentrations than those recommended. The value of IWQI in water samples varied from 40.26 to 114.82. The samples of S1 showed good water, the samples of region S2 (after mixing with Faraskour drainage) showed poor water quality, samples of regions S3 (after mixing with the El-Serw drain waters) and S5 (before El-Sahara) fell under the very poor water category and samples of region S4 (after mixing with the Hadous drainage) showed unsuitable water. Croplands irrigated with such water will not be exposed to any alkaline risks but will be exposed to the risk of salinity, which is more severe after mixing at the S3 and S4 sites. It is recommended to treat the drainage water before mixing with the irrigation water of El-Salam Canal to raise the suitability of irrigation water for crops, particularly for the Hadous drain.

Evaluation of sustainable groundwater utilization using index methods (WQI and IWQI), multivariate analysis, and GIS: the case of Akşehir District (Konya/Turkey)

Akşehir district is one of the regions where significant agricultural production and industrial activities are carried out. Groundwater is the most important water resource in this region used for different purposes, especially for drinking and irrigation water. In order to ensure sustainable water management in the study area, it is necessary to reveal the drinking and irrigation water quality of groundwater and to take precautions and determine the management plans. In the present study, groundwater quality was evaluated using water quality index methods (WQI and IWQI) and statistical analyses to determine the sustainable and most appropriate usage of groundwater. In addition, spatial distribution maps were prepared using GIS for drinking and irrigation WQI assessments of the groundwater. A total of 31 groundwater samples were collected from wells in October 2018 and physicochemical analysis results were evaluated. According to the results obtained with the WQI method, all groundwater samples in the study area are definitely not suitable for use as drinking water. According to the results obtained by the IWQI method, samples S23, S24, S25, S27, S28, S29, and S31 especially are not suitable for use as irrigation water. Statistical evaluations support the results obtained from WQI and IWQI methods. Also, factor analysis indicates that anthropogenic pollution, especially agricultural applications, is effective on the chemical and quality characteristics of groundwater samples in addition to the geological properties. As seen in the spatial distribution maps for WQI and IWQI results, while the quality of groundwaters around Doğruözü and Erdoğdu is not suitable for drinking water, the groundwater quality in the north-east of the study area is also unusable for irrigation water. Consequently, the use of groundwater in the region as drinking water can be dangerous for human health and alternative drinking water resources should be investigated. In addition, in order to ensure the sustainable use of groundwater, it is necessary to control agricultural activities in the region, to monitor the use of pesticides and fertilizers, and to encourage organic farming practices in the region.

Impact of a small hydropower plant on water quality dynamics in a diversion and natural river channel

This study innovatively evaluates the impact of hydropower plants located in a diversion channel on water quality dynamics. The spatial characteristics of water in the diversion channel above and below a hydropower plant were assessed; specifically, the investigation was conducted in the watercourse undeveloped by the hydropower plant and at reference points. Among the five analyzed points, the strongest statistically significant changes were observed in electrical conductivity, pH, and dissolved oxygen. Statistical analyses showed a similar, statistically significant relationship for most months. The water quality indicators proposed in this study help assess hydropower plants' impact on water quality dynamics because they enable water comparison at different locations. The best water quality, as calculated using designated indices, was recorded below the hydropower plant. Among the physicochemical parameter values, the most noticeable change occurred in dissolved oxygen below the hydropower plant and below the fixed weir; its value was 8.10 and 5.32% higher in the two locations at the reference point below the hydropower facility. Moreover, the NH₄ -N content was higher by 7.06% below the weir than the point below the hydropower plant. In the long term, this research may help plant operators manage water resources on watercourses with hydropower development more efficiently, according to sustainable development principles. This research will contribute to the rational management of such facilities on diversion channels considering sustainable water management principles.

GIS, Multivariate Statistics Analysis and Health Risk Assessment of Water Supply Quality for Human Use in Central Mexico

The spatial assessments of water supply quality from wells, springs, and surface bodies were performed during the dry and rainy seasons in six municipalities in the eastern regions of Michoacán (Central Mexico). Different physicochemical parameters were used to determine the supplies’ Water Quality Index (WQI); all of the communities presented good quality. The analysis indicates that many water quality parameters were within limits set by the international standards, showing levels of “excellent and good quality” according to WQI, mainly during the dry season (except at San Pedro Jácuaro and Irimbo communities in the rainy season). However, some sites showed “poor quality” and “unsuitable drinking water” related to low pH levels (<5) and high levels of turbidity, color, Fe, Al, Mn, and arsenic. Multivariate statistical analysis techniques (Principal Component and Hierarchical Cluster) and geographic information system (GIS) identify potential sources of water pollution and estimate the geographic extension of parameters with negative effects on human health (mainly in communities without sampling). According to multivariate analysis, the Na+/K+ ratio and water temperature (22–42 °C) in various sites suggest that the WQI values were affected by geological and geothermal conditions and physical changes between seasons, but were not from anthropogenic activity. The GIS established predictions about the probable spatial distribution of arsenic levels, pH, temperature, acidity, and hardness in the study area, which provides valuable information on these parameters in the communities where the sampling was not carried out. The health risk assessment for dermal contact and ingestion showed that the noncancer risk level exceeded the recommended criteria (HQ > 1) in the rainy season for three target groups. At the same time, the carcinogenic risk (1 × 10−3) exceeded the acceptability criterion in the rainy season, which suggests that the As mainly represents a threat to the health of adults, children, and infants.

Comparison of characteristics, water quality and health risk assessment of trace elements in surface water and groundwater in China

Water quality is closely associated with human health and socio-economic sustainable development. With the increasingly intensive anthropogenic activities, pollutants especially trace elements, enter water aquatic system and cause harm to humans. This study conducted the first systematic comparison on the pollution status of surface water and groundwater in China. Water quality and health risk assessment of 12 trace elements were evaluated according to the water quality index (WQI), hazard quotient (HQ), hazard index (HI), and carcinogenic risk (CR). The results showed that the average values of trace elements in the majority of surface water were higher than those in groundwater. The WQI values demonstrated that 86.02% of surface water and 83.11% of groundwater were suitable for drinking water. Arsenic served as the predominant pollutant and contributed significantly to cause the non‑carcinogenic risk on human health in both surface water and groundwater, children were more vulnerable to the adverse effects than adults. In surface water, the priority non-carcinogenic risk sites were mainly distributed in Anning River, Taizi River, Middle reaches of Huai River and Jilin section of Songhua River. For groundwater, the high-risk sites were located in Huhhot Basin, Kuitun, Jianghan Plain, Datong Basin and Yucheng County. Arsenic posed potential carcinogenic risk to local resident in some water sites, and it presented higher in groundwater than surface water. More concerns should be paid on Songhua, Yangtze and Huai River Basins, in addition, Pearl, Southeast Coastal, Southwest and Northwest River Basins still need attention. The future work should be carried out more extensive range of the water sites and long-term monitoring in China. In particular, more attention should be dedicated to assess high As water bodies.

Spatial Variation of Water Chemistry in Aries River Catchment, Western Romania

This study aims to investigate the quality and vulnerability of surface water (Aries River catchment) in order to identify the impact of past mining activities. For this purpose, the pollution and water quality indices, Piper and Durov plots, as well vulnerability modeling maps were used. The obtained results indicate that the water samples were contaminated with As, Fe, Mn, Pb and have relatively high concentrations of SO42−, HCO3−, TDS, Ca, K, Mg and high values for the electrical conductivity. Possible sources of the high content of chemicals could be the natural processes or the inputs of the mine drainage. Generally, according to the pollution indices, which were correlated to high concentrations of heavy metals, especially with Pb, Fe and Mn, the water samples were characterized by heavy metals pollution. The water quality index classified the studied water samples into five different classes of quality, namely: unsuitable for drinking, poor, medium, good and excellent quality. Similarly, medium, high and very high vulnerability classes were observed. The Durov and Piper plots classified the waters into Mg-HCO3− and Ca-Cl− types. The past and present mining activities clearly change the water chemistry and alter the quality of the Aries River, with the water requiring specific treatments before use.

Imprints of COVID-19 lockdown on the surface water quality of Bagmati river basin, Nepal

COVID-19 pandemic has caused profound impacts on human life and the environment including freshwater ecosystems globally. Despite the various impacts, the pandemic has improved the quality of the environment and thereby creating an opportunity to restore the degraded ecosystems. This study presents the imprints of COVID-19 lockdown on the surface water quality and chemical characteristics of the urban-based Bagmati River Basin (BRB), Nepal. A total of 50 water samples were collected from 25 sites of BRB during the monsoon season, in 2019 and 2020. The water temperature, pH, electrical conductivity, total dissolved solids, dissolved oxygen (DO), and turbidity were measured in-situ, while the major ions, total hardness, biological oxygen demand (BOD), and chemical oxygen demand (COD) were analyzed in the laboratory. The results revealed neutral to mildly alkaline waters with relatively moderate mineralization and dissolved chemical constituents in the BRB. The average ionic abundance followed the order of Ca²⁺ > Na⁺ > Mg²⁺ > K⁺ > NH₄⁺ for cations and HCO₃^-> Cl^- > SO₄^2- > NO₃^- > PO₄^3- for anions. Comparing to the pre-lockdown, the level of DO was increased by 1.5 times, whereas the BOD and COD were decreased by 1.5 and 1.9 times, respectively during the post-lockdown indicating the improvement of the quality water which was also supported by the results of multivariate statistical analyses. This study confirms that the remarkable recovery of degraded aquatic ecosystems is possible with limiting anthropic activities.

Water quality of streams associated with artisanal gold mining; Suárez, Department of Cauca, Colombia

Gold mining is one of the major problems of contamination of hydric resources in Colombia, this practice generates a high impact on water quality due to the accumulation of waste during its process. In this study water quality was evaluated in five natural stream beds corresponding to four streams with gold mining operations and one in the Cauca River, taking samples before the water inlet and after the outlet in each operation in the streams of Dios Te Dé, Tamboral, Piedra Imán, and Lorenzo affected by artisanal gold mining labor, which drain into the Salvajina Reservoir on the Cauca River in the municipality of Suárez Cauca, Colombia. Characterization of water bodies in the streams was carried out applying contamination indices of Colombia. The IDEAM protocol was used as guide to monitor the water currents. Samples were taken in 15 stations in the natural stream beds with operations and a sampling station on the Cauca River after the reservoir in these lotic ecosystems, during three periods; two from 2018 and one from 2019. The range of the contamination indices according to the environmental variables were considered. Results show that the contaminants associated with TSS, TUR, and Hg are high in the sampling stations in the output of the operations and the sampling stations of the streams with influence on the operations (T3, T4, I2, I3, D2, and D5). The water quality score according to the ICA IDEAM index varied between acceptable and regular in the different sampling stations. However the Hg concentration in sampling station C1 of the Cauca River is due to contributions from the operations in the amalgamation process. This requires strategic interventions by the communities, miners, operation owners, and control organisms as the Regional Autonomous Corporation of Cauca (CRC) and the Ministry of Environment and Sustainable Development (MADS) to minimize the negative impacts on the hydric resource and ecosystemic services associated with this resource.

Development and evaluation of an innovative Enhanced River Pollution Index model for holistic monitoring and management of river water quality

The present study was conceptualized to develop the Enhanced River Pollution Index (ERPI) model. The ERPI model was used to evaluate the river water quality (RWQ) for its beneficial usage, i.e., drinking with (DCD) and without (DD) conventional treatment, outdoor-bathing (OB), wildlife and fisheries (WF), and industrial and irrigation (IIW). The adequacy of multiple linear regression (MLR) and support vector regression (SVR) models was also investigated to predict the ERPI for estimating the RWQ. The accuracy of the MLR and SVR models was tested by using the statistical parameters, i.e., root mean squared error (RMSE), coefficient of determination (R²), and mean absolute error (MAE). The results revealed that the MLR models performed well (RMSE = 0.004 ± 0.0043, R² = 0.998 ± 0.001, and MAE = 0.002 ± 0.003) for the DD, DCD, and OB. However, the SVR models estimated the RWQ more accurately (RMSE = 0.041 ± 0.001, R² = 0.962 ± 0.010, and MAE = 0.026 ± 0.002) than the MLR models for WF and IIW. Moreover, this study disclosed that the RWQ was not excellent for DD, OB, and DCD. However, the RWQ was categorized from excellent to poor classes for WF, while it was suitable for IIW.

Groundwater hydrochemistry, source identification and pollution assessment in intensive industrial areas, eastern Chinese loess plateau

Groundwater is essential for regional ecological-economic system and is an important resource of drinking water, especially in the Chinese Loess Plateau (CLP), where is a typical water-limited ecosystem. Groundwater quality deterioration will affect water security and exacerbate the water shortages. Groundwater hydrochemistry, pollution source apportionment, quality and health risks were evaluated based on analysis of major ions and selected trace elements in seasonal samples of the Fen River Basin (FRB) in the eastern CLP. Groundwaters in the FRB were mainly HCO₃^--Ca²⁺-Na⁺ water type with low dissolved solutes in upstream samples, high values in midstream samples and medium values in downstream samples. Solutes in upstream samples were mainly derived from carbonate weathering, while those in midstream and downstream samples came from silicate weathering, evaporites dissolution and anthropogenic sources. Self-organizing map (SOM) showed the hydrochemistry remained unchanged from dry to wet season for most sampling points. The seasonal variations of Ag, Cd, Ni, Pb, and Tl were significant due to anthropogenic input. High NO₃^- in upstream and downstream samples resulted primarily from sewage discharge, and high SO₄^2- in midstream and downstream samples was from gypsum- and coal-related industries. In addition, anthropogenic input related to coal industries significantly aggravates pollution of As, Ni, Ag, Fe, and Mn. Influenced by evaporites and anthropogenic input, midstream samples had high salinity, total hardness and water quality indices (WQIs) and were unsuitable for irrigation or drinking purposes. Seasonal variation of WQI in the FRB was unsignificant except Jiaokou River sub-basin, where groundwater quality was worse in the wet season than the dry season due to coal mining. Great attention should be paid to the high non-carcinogenic risks of exposure to F, V, Mn, and Cr via dermal absorption, particularly for children. Overall, groundwater quality in the FRB was best in upstream, medium in midstream and worst in midstream based on different index. Groundwater quality is deteriorated by anthropogenic input and the sewage discharge in the FRB should be strictly controlled. Our report provides a reference for groundwater pollution evaluation and source identification in similar areas.

Mobilization mechanisms and toxicity risk of sediment trace metals (Cu, Zn, Ni, and Pb) based on diffusive gradients in thin films: A case study in the Xizhi River basin, South China

Identifying the mobilization mechanisms and predicting the potential toxicity risk of metals in sediment are essential to contamination remediation in river basins. In this study, a sequential extraction procedure and diffusive gradients in thin film (DGT) were employed to investigate the mobilization mechanisms, release characteristics, and potential toxicity of sediment metals (Cu, Zn, Ni, and Pb). Acid-soluble and reducible fractions were the dominant geochemical species of Cu, Zn, Ni, and Pb in sediments, indicating high mobility potentials for these metals under reducing conditions. In summer, the sediment acted as a source of water-column metals due to mineralization of organic matter and reductive dissolution of iron/manganese oxides in surface sediments, and the formation of metal sulfide precipitates markedly lowered DGT-labile metal concentrations with depth, while localized sulfide oxidation was responsible for fluctuating labile metal concentrations. Stable distribution patterns of labile metals resulted from the weak reducing conditions of sediment in winter, when the sediment shifted to a metal sink. The interstitial water criteria toxicity unit (IWCTU), calculated from DGT measurements, indicated no and low-to-moderate toxic risk of sediments in summer and winter seasons, respectively, and Pb was the major contributor to the predicted toxic effects in the soft interstitial water.

Development of fuzzy analytic hierarchy process based water quality model of Upper Ganga river basin, India

The ecological sustainability of rivers is in question due to severe pollution and lack of stringent regulations. Long term (1990-2016) water quality data of five stations namely Haridwar, Bareilly, Kanpur, Prayagraj and Varanasi of Upper Ganga river, India was considered for analysis using fuzzy analytical process (FAHP) based water quality index (WQI) to assess surface water quality. The value of water physical, biological and chemical parameters of temporal resolution (monthly, seasonal and yearly) indicate that value of electrical conductivity (EC), total dissolved solids (TDS), biological oxygen demand (BOD), chemical oxygen demand (COD), total alkalinity (Mg CaCO₃), total hardness (Mg CaCO₃), calcium (Ca), magnesium (Mg), sodium (Na), chlorine (Cl) and bicarbonate (HCO₃) were observed very high compared to recommended value of Bureau of Indian Standards (BIS) and World Health Organization (WHO) at Kanpur, Prayagraj and Varanasi stations. However, low value of parameters is observed at Haridwar and Bareilly stations. Also, the high deviation was observed in water quality parameters during 1990-2010 whereas the deviation of parameters is decreased in 2011-2016. It is observed from the piper diagram that magnesium and bicarbonate at Haridwar, sodium, potassium and bicarbonate in Bareilly, Kanpur, Prayagraj and Varanasi stations are dominant during monthly and seasonal periods. The fuzzy based WQI value indicate that water quality is excellent to poor at Haridwar, while poor to unsuitable in Bareilly, Kanpur, Prayagraj and Varanasi during monthly and seasonal periods. The water quality ranges from poor to unsuitable during the 1990-2010 period and good to very poor during the 2011-2016 period at Bareilly, Kanpur, Prayagraj and Varanasi stations. Whereas very good to good during 1990-2010 and excellent to good during 2011-2016 at Haridwar. It was also determined that water quality parameters (Ca, Na+K, SO₄, Hardness, Cl and Mg) and WQI values were increased with length of the stream. It indicates that drain discharge, urban growth, urban functions, ecological footprints and crop area increment were key sources of pollution.

Surface water quality assessment of Skardu springs using Water Quality Index

Natural springs which originate from hilly areas of Skardu in Pakistan make their route downward and are utilized by the public as they passes from residential areas. Due to weathering processes in mountainous regions, these springs can be the source of various trace elements and pollutants. Keeping in mind the same concept, ten mostly used freshwater springs were selected to evaluate their drinking water quality in the Skardu region. Three samples of water from each spring (start/mouth, 100 m away from the mouth, and 200 m away from mouth) were collected and analyzed for water quality via Water Quality Index (WQI). The main parameters of spring water were recorded in the laboratory as electrical conductivity (EC), total dissolved solids (TDS), residual sodium carbonate (RSC), and sodium adsorption ratio (SAR), and secondary parameters, i.e., Kelley's ratio (KR), permeability index (PI), and WQI, were derived. Besides these parameters, heavy metal pollutants (Cd, Cr, Mn, and Cu) were also determined from the water samples. The results showed that the assessed parameters TDS, SSP, KR, and PI were found within the safer limits of drinking water as prescribed by the Pak-EPA and WHO. However, among trace elements, only Cd (0.03 mg L-1) was found above the permissible limits of 0.01 mg L-1 as given by the GOP-EPA (2008) and WHO (1996) at Shigri Bala spring 200 m away. Similarly, at 2 ft from the mouth of Chumig S1 spring, its concentrations were recorded 0.03 mg L-1, and at Benazir Chowk spring (100 m away), it was found 0.02 mg L-1. In general, the Water WQI demonstrates that springs have good water quality. Our findings are useful for the environmental protection managers and citizens of the Skardu concerned with the water quality of the springs.

Modification of the Water Quality Index (WQI) Process for Simple Calculation Using the Multi-Criteria Decision-Making (MCDM) Method: A Review

Human activities continue to affect our water quality; it remains a major problem worldwide (particularly concerning freshwater and human consumption). A critical water quality index (WQI) method has been used to determine the overall water quality status of surface water and groundwater systems globally since the 1960s. WQI follows four steps: parameter selection, sub-indices, establishing weights, and final index aggregation, which are addressed in this review. However, the WQI method is a prolonged process and applied to specific water quality parameters, i.e., water consumption (particular area and time) and other purposes. Therefore, this review discusses the WQI method in simple steps, for water quality assessment, based on two multi-criteria decision-making (MCDM) methods: (1) analytical hierarchical process (AHP); and (2) measuring attractiveness by a categorically based evaluation technique (MACBETH). MCDM methods can facilitate easy calculations, with less effort and great accuracy. Moreover, the uncertainty and eclipsing problems are also discussed—a challenge at every step of WQI development, particularly for parameter selection and establishing weights. This review will help provide water management authorities with useful knowledge pertaining to water usage or modification of existing indicators globally, and contribute to future WQI planning and studies for drinking, irrigation, domestic, and industrial purposes.

Effects of Physicochemical Variables of Superficial Waters on the Abundance of the North African Freshwater Crab Potamon algeriense (Bott, 1967)

The large number of pollutants discharged into the aquatic environment may influence the physicochemical and biological qualities of the aquatic ecosystem. This study discloses the global quality of the surface waters and the effect of physicochemical variables on the abundance of the African freshwater crab Potamon algeriense inhabiting Zegzel watercourse, a mountain stream in the northeast of Morocco. Physicochemical variables including streamflow, water temperature, pH, dissolved oxygen, suspended matter, chloride, calcium, magnesium, ammonia, nitrite, nitrate, orthophosphate, and organic matter were evaluated monthly for one year (October 2017-September 2018). The evaluation of the physicochemical quality showed that the waters of all the stations studied are between the excellent and good quality classes concerning all the physicochemical variables and highlights also two variations with a tendency towards degradation, one spatial from upstream to downstream and the other seasonal from the wet to the dry period. The abundance of crabs was recorded to exhibit a positive correlation with dissolved oxygen, calcium (N = 44) (p < 0.01), and magnesium. However, a negative correlation has been noticed for streamflow (N = 1) (p < 0.01), water temperature, pH, suspended matter, chloride, ammonia, nitrite, nitrate, orthophosphate, and organic matter. The results obtained reveal that besides the biotic variables, the distribution of P. algeriense also depends on these specific environmental variables.

Parametrization of groundwater quality of the Quaternary aquifer in N'Djamena (Chad), Lake Chad Basin: application of numerical and multivariate analyses

The urban groundwater of the Quaternary aquifer of the Lake Chad basin in N'Djamena has been subject to many hydrochemical studies. However, the results are often not presented in a way that enables water quality managers to make an appropriate decisions, which restrict development and poverty reduction efforts. The objective of the present study was to contribute the improved management of the local groundwater resources. A total of 85 groundwater samples were interpreted using hydrochemical techniques associated with integrated numerical indices and multivariate statistical analysis. The hydrochemical results coupled with the relative residence time of water have shown that the chemical composition of these waters is linked to geogenic and anthropogenic factors and to their proximity to the Chari-Logone rivers. These investigations showed that the groundwater quality in N'Djamena is characterized by a high spatial variability. This study also assessed the suitability of groundwater for user needs and identified areas which are more/less favorable for a specific use. The evaluation of water quality and its suitability for human consumption is also a problem of optimizing data acquisition strategy, and this study used the correlation between water quality index (WQI) and electrical conductivity (EC) to orientate future data acquisition strategies. This parametrization can assist the decision makers and water management professionals in evaluating groundwater availability and setting up a robust water quality management plan in areas with similar hydrogeological and climatic conditions.

Spatiotemporal variations, sources, water quality and health risk assessment of trace elements in the Fen River

As the largest river in Shanxi Province, the Fen River is the main water source for regional economic and ecological development. Water deficiency and industrialization have led to serious water pollution in the Fen River. The major and trace elements of seasonal river waters were measured to determine the spatiotemporal variations and assess the water quality as well as its controlling factors in the Fen River. Trace elements are divided into high abundance elements (B, Ba, Li, and Mn) and low abundance elements (As, Cu, Fe, Ni, Rb, Se, U, and V). The spatial variation of trace elements is obvious, with low values upstream, intermediate values downstream, and very high values midstream. The average values of the trace elements showed different seasonal variations, with high values of As, B, Ba, Mn, and Rb in the wet season, high Cu, V, and Li values in the dry season, and minor seasonal variations of Fe, Ni, Se, and U concentrations. Principal component analysis (PCA) and correlation analysis (CA) showed natural origins of Ba, Mn, Ni, and U, anthropogenic input of As, B, Cu, Li, Rb, Se, and V. According to the results of absolute principal component sore-multivariate linear regression (APCS-MLR), the major pollution sources in the Fen River basin were related to human activities. The land use type significantly influenced the concentrations of trace elements, with high values in the cropland and low values in the forest. The water quality index (WQI) values were higher in the midstream and wet season. In comparison with other rivers in the world, the pollution of the Fen River is at a moderate level. Health risk assessment showed that As, Ba, Mn, Ni, V, and Se were the potential pollutants damaging in the Fen River, especially for children. This study highlights the importance of seasonal sample analysis and can provide vital data for water quality conservation in the Fen River basin.

Groundwater quality for potable and irrigation uses and associated health risk in southern part of Gu'an County, North China Plain

The study area is a part of the North China Plain, where groundwater is heavily abstracted for drinking and irrigation purposes. Groundwater quality is adversely affected due to rapid economic development and urbanization. Therefore, the purposes of this study were to evaluate the suitability of groundwater for drinking and irrigation purposes and to quantify the associated human health risks in the southern part of Gu'an County, North China Plain. The matter-element extension method based on entropy weight was used to evaluate the water quality for drinking, while sodium adsorption ratio, sodium percentage (%Na), residual sodium carbonate and magnesium hazard were used to evaluate the water quality for irrigation. Non-carcinogenic and carcinogenic health risks via different exposure ways were evaluated for different age groups. The study found that the quality of both deep and shallow groundwater in this area was generally suitable for drinking. Deep water quality has better quality than the shallow water. However, 8.70% and 73.92% of water samples pose non-carcinogenic health risks on adults and children, respectively. Children and adults are also at cancer risk due to Cr⁶⁺ and As in drinking groundwater in this area. The main responsible parameters for non-carcinogenic risk are Cr⁶⁺, F^- and Fe, and Cr⁶⁺ is also responsible for carcinogenic risk. These toxic elements are mainly from industries. Therefore, deterioration of groundwater quality can be prevented by strengthening the sewage management of various industries.

Assessment and management of lake eutrophication: A case study in Lake Erhai, China

Some wastewater sources, such as agricultural waste and runoff, and industrial sewage, can degrade water quality. This study summarises the sources and corresponding mechanisms that trigger eutrophication in lakes. Additionally, the trophic status index and water quality index (WQI) which are effective tools for evaluating the degree of eutrophication of lakes, have been discussed. This study also explores the main nutrients (nitrogen and phosphorus) driving transformations in the water body and sediment. Lake Erhai was used as a case study, and it was found to be in a mesotrophic state, with N and P co-limitation before 2006, and only P limitation since 2006. Finally, effective measures to maintain sustainable development in the watershed are proposed, along with a framework for an early warning system adopting the latest technologies (geographic information systems (GIS), remote sensing (RS)) for preventing eutrophication.

Application of neural network and time series modeling to study the suitability of drain water quality for irrigation: a case study from Egypt

Limited water resources are one of the major challenges facing Egypt during the current stage. The agricultural drainage water is an important water resource which can be reused for agriculture. Thus, the current study aims to assess the quality of drainage water for irrigation purpose through monitoring and predicting its suitability for irrigation. The chemical composition of Bahr El-Baqr water drain, especially salinity, as well as ions are mainly involved in calculating indicators of water suitability for irrigation, i.e., Ca²⁺, Mg²⁺, Na⁺, K⁺, HCO^-3, Cl^-, and SO₄^2-. Further analysis was carried out to evaluate the irrigation water quality index (IWQI) through integrated approaches and artificial neural network (ANN) model. Further, ARIMA models were developed to forecast IWQI of Bahr El-Baqr drain in Egypt. The results indicated that the computed IWQI values ranged between 46 and 81. Around 11% of the samples were classified as excellent water, while 89% of the samples were categorized as good water. The results of IWQI showed a standard deviation of 8.59 with a mean of 62.25, indicating that IWQI varied by 13.79% from the average. ANN model showed much higher prediction accuracy in IWQI modeling with R² value greater than 0.98 during training, testing and validation. A relatively good correlation was obtained, between the actual and forecasted IWQI based on the Akaike information criterion (AIC); the best fit models were ARIMA (1,0) (0,0) without seasonality. The determination coefficient (R²) of ARIMA models was 0.23. Accordingly, 23% of IWQI variability could be explained by different model parameters. These findings will support the water resources managers and decision-makers to manage the irrigation water resources that can be implemented in the future.

Seasonal and Spatial Variation of Groundwater Quality Vulnerable Zones of Yellareddygudem Watershed, Nalgonda District, Telangana State, India

Evaluation of seasonal and spatial variations in vulnerable zones for poor groundwater quality is essential for the protection of human health and to maintain the crop yields. With this objective, groundwater samples were collected seasonally (i.e., pre- and post-monsoon) from the Yellareddygudem watershed of Telangana, India. These samples were analysed for major chemical parameters (pH, TDS, Ca²⁺, Mg²⁺, Na⁺, K⁺, [Formula: see text], Cl^-, [Formula: see text], [Formula: see text], and F^-). Geographical information system (GIS) tools were used to delineate the seasonal and spatial variations for vulnerable zones related to the drinking groundwater quality index (DGQI) and irrigation groundwater quality index (IGQI). Geochemical facies and relations, Piper diagrams, and principal component analysis indicated that the weathering, dissolution, leaching, ion exchange, and evaporation were the primary processes controlling the groundwater quality seasonally. Human influences were the secondary factors. The TDS, Na⁺, K⁺, Cl^-, [Formula: see text], and F^- parameters were observed to be within the drinking water quality standard limits in most post-monsoon groundwater samples. However, the DGQI showed an increase in the number of samples with unsuitable quality for drinking in the post-monsoon period compared with the pre-monsoon period. The IGQI demonstrated that the number of samples with unsuitable quality for irrigation increased in the post-monsoon period compared to the pre-monsoon period. The differences in the vulnerable zones between the pre- and post-monsoon periods were due to variations in groundwater recharge, following the topography. Thus, the present study will help decision makers to plan groundwater treatment measures within vulnerable zones.

Appraisal of Groundwater Quality with Human Health Risk Assessment in Parts of Indo-Gangetic Alluvial Plain, North India

Groundwater contamination in the Indo-Gangetic alluvial plain has reportedly been affected by various factors, such as mineral dissolution, overexploitation, precipitation, and ion exchange. This study was designed to interpret the hydrochemical fluctuations in the groundwater sources of a rural area in Raebareli district. Groundwater is slightly alkaline and affected by the issues of fluoride, salinity, hardness, and nitrate. The Pollution Index of Groundwater significantly categorize 57% and 79% of the samples under the "insignificant pollution" category during pre-monsoon and post-monsoon periods. The Health risk assessment indicated the high susceptibility of children toward health risks. It also indicated that fluoride had greater impact than nitrate in the study area. The multivariate statistical analysis indicates that anthropogenic activities, such as agricultural practices, including excessive fertilizer application and improper domestic and cattle waste management, are probable causes of groundwater contamination through NO₃^-, Cl^-, Na⁺, and K⁺. Furthermore, the base exchange index classified 71.43% samples in pre-monsoon and 78.57% in post-monsoon as Na-HCO₃ type. The meteoric genesis index suggested that 78.57% and 85.71% of the samples belong to shallow meteoric water percolation type during pre- and post-monsoon periods, respectively. The Piper plots revealed that HCO₃-Ca·Mg and SO₄·Cl-Na + K type are the prominent facies in the area, with dominance of alkalis and weak acids. According to Gibbs plot, majority of the samples fall under "rock dominance" suggesting that "rock-water" interaction was the dominant natural process controlling the groundwater chemistry.

Bacteriophages in water pollution control: Advantages and limitations

Wastewater is a breeding ground for many pathogens, which may pose a threat to human health through various water transmission pathways. Therefore, a simple and effective method is urgently required to monitor and treat wastewater. As bacterial viruses, bacteriophages (phages) are the most widely distributed and abundant organisms in the biosphere. Owing to their capacity to specifically infect bacterial hosts, they have recently been used as novel tools in water pollution control. The purpose of this review is to summarize and evaluate the roles of phages in monitoring pathogens, tracking pollution sources, treating pathogenic bacteria, infecting bloom-forming cyanobacteria, and controlling bulking sludge and biofilm pollution in wastewater treatment systems. We also discuss the limitations of phage usage in water pollution control, including phage-mediated horizontal gene transfer, the evolution of bacterial resistance, and phage concentration decrease. This review provides an integrated outlook on the use of phages in water pollution control.

Water Quality Estimation and Population’s Attitudes: A Multi-Disciplinary Perspective of Environmental Implications in Tara National Park (Serbia)

The paper analyzes the water quality of hydrological resources in the wider area of Tara National Park (NP Tara) in Serbia and the opinions of the local community and the national park visitors about the grade of the possible damage. The pollution level of the Drina River at the Bajina Bašta hydrological station was analyzed using the Water Pollution Index. The results showed that water quality corresponded to classes II (clean water) or III (moderately polluted water) and revealed the presence of organic pollution. In addition, using a survey combined with field research, the perceptions of local inhabitants and national park visitors related to environmental pollution were analyzed. The community believed that tourism does not cause significant damage to the environment. However, the older and more educated groups of residents and visitors had a more critical perception of the environmental impact of tourism. The results also indicated that the perceptions of visitors were mostly in agreement with measured water quality in the Drina River. The findings of this study have important implications for the management of protected areas and future policies related to national parks.

Chemometrics Applied in the Development of a Water Quality Indicator System for the Brazilian Amazon

The objective of this work was to develop a method to calculate the water quality index (WQI) using chemometric methods. The study was carried out at the Curuá-Una hydroelectric power plant in the state of Pará in the Brazilian Amazon. Eight collection stations in four periods (winter, intermediate I, summer, and intermediate II) and 29 parameters were selected. Multivariate analysis was applied to the results to verify the quality of the data and to select the most sensitive variables to be used as indicators for the WQI calculation. The 10 parameters selected were E _h, dissolved oxygen, total dissolved solids, chlorophyll a, phosphate, Ba, Ca, Fe, Na, and Sn. The WQI proposed herein was effective in the classification of water quality for the periods analyzed.

The Integration of Multivariate Statistical Approaches, Hyperspectral Reflectance, and Data-Driven Modeling for Assessing the Quality and Suitability of Groundwater for Irrigation

Sustainable agriculture in arid regions necessitates that the quality of groundwater be carefully monitored; otherwise, low-quality irrigation water may cause soil degradation and negatively impact crop productivity. This study aimed to evaluate the quality of groundwater samples collected from the wells in the quaternary aquifer, which are located in the Western Desert (WD) and the Central Nile Delta (CND), by integrating a multivariate analysis, proximal remote sensing data, and data-driven modeling (adaptive neuro-fuzzy inference system (ANFIS) and support vector machine regression (SVMR)). Data on the physiochemical parameters were subjected to multivariate analysis to ease the interpretation of groundwater quality. Then, six irrigation water quality indices (IWQIs) were calculated, and the original spectral reflectance (OSR) of groundwater samples were collected in the 302–1148 nm range, with the optimal spectral wavelength intervals corresponding to each of the six IWQIs determined through correlation coefficients (r). Finally, the performance of both the ANFIS and SVMR models for evaluating the IWQIs was investigated based on effective spectral reflectance bands. From the multivariate analysis, it was concluded that the combination of factor analysis and principal component analysis was found to be advantageous to examining and interpreting the behavior of groundwater quality in both regions, as well as predicting the variables that may impact groundwater quality by illuminating the relationship between physiochemical parameters and the factors or components of both analyses. The analysis of the six IWQIs revealed that the majority of groundwater samples from the CND were highly suitable for irrigation purposes, whereas most of the groundwater from the WD can be used with some limitations to avoid salinity and alkalinity issues in the long term. The high r values between the six IWQIs and OSR were located at wavelength intervals of 302–318, 358–900, and 1074–1148 nm, and the peak value of r for these was relatively flat. Finally, the ANFIS and SVMR both obtained satisfactory degrees of model accuracy for evaluating the IWQIs, but the ANFIS model (R2 = 0.74–1.0) was superior to the SVMR (R2 = 0.01–0.88) in both the training and testing series. Finally, the multivariate analysis was able to easily interpret groundwater quality and ground-based remote sensing on the basis of spectral reflectance bands via the ANFIS model, which could be used as a fast and low-cost onsite tool to estimate the IWQIs of groundwater.

Quality and Health Risk Assessment Associated with Water Consumption—A Case Study on Karstic Springs

In rural areas without centralized water supply systems, inhabitants often use groundwater of unknown quality as drinking water, without understanding the possible negative consequences on their health. Karstic spring waters from Dobrogea region in Romania were assessed for their potential to be used as drinking water source, according to their quality and seasonal variation. The physico-chemical parameters of waters were compared with the guideline values for drinking water established by the World Health Organization and the Directive 98/83/EC. The nitrate and Cr concentrations exceeded the guideline value in the springs from Southern Dobrogea, but met the quality criteria in those from Northern Dobrogea, thus, to be used as drinking water, the karstic springs located in Southern Dobrogea require treatment for nitrates removal. Heavy metals pollution indices showed low to medium cumulative heavy metal pollution in all springs, while the human health risk assessment by oral exposure indicated possible noncarcinogenic risks of nitrates, both for adults and children in springs from South Dobrogea. A rigorous monitoring of the water quality before human consumption is recommended for all four studied water sources.

A Review of Current and Emerging Approaches for Water Pollution Monitoring

The aquatic ecosystem is continuously threatened by the infiltration and discharge of anthropogenic wastewaters. This issue requires the unending improvement of monitoring systems to become more comprehensive and specific to targeted pollutants. This review intended to elucidate the overall aspects explored by researchers in developing better water pollution monitoring tools in recent years. The discussion is encircled around three main elements that have been extensively used as the basis for the development of monitoring methods, namely the dissolved compounds, bacterial indicator, and nucleic acids. The latest technologies applied in wastewater and surface water mapped from these key players were reviewed and categorized into physicochemical and compound characterizations, biomonitoring, and molecular approaches in taxonomical and functional analyses. Overall, researchers are continuously rallying to enhance the detection of causal source for water pollution through either conventional or mostly advanced approaches focusing on spectrometry, high-throughput sequencing, and flow cytometry technology among others. From this review’s perspective, each pollution evaluation technology has its own advantages and it would be beneficial for several aspects of pollutants assessments to be combined and established as a complementary package for better aquatic environmental management in the long run.

Assessment of physico-chemical characteristics of river water emphasizing tannery industrial park: a case study of Dhaleshwari River, Bangladesh

Pollution of industry-adjacent surface water bodies become a major environmental concern in Bangladesh recently. Therefore, this study aimed to elaborate assessment of physico-chemical characteristics of the Dhaleshwari River (the adjacent river of newly shifted tannery industrial park) and also the discharged effluent from the central effluent treatment plant (CETP) considering both seasonal and spatial variations. Among the examined 30 water quality parameters (including 11 heavy metals), only TDS, Cl^-, NO₃-N, EC, Cu, Zn, Cd, and Ni met the standards for discharged wastewater from industrial units into inland surface water set by Bangladesh government. This indicated that the CETP is not fully and/or effectively functioning. Out of 19 parameters (excluding heavy metal), 14 parameters exceeded the Bangladesh standard for drinking water quality either spatially or seasonally. The river water quality indicated slowly biodegradable capacity with algal bloom risk. The concentrations of the studied heavy metals in the river water followed a decreasing order of Ca > K > Mg > Na > Fe > Cr > Pb > Ni > Cu > Zn > Cd, and Cr concentration in the winter season exceeded the standard values. The concentrations of other heavy metals met the quality standard that indicated still the river is capable to self-purify. Furthermore, strong (p < 0.01) and significant (p < 0.05) correlation were observed among the quality parameters in river water. This study suggested that the efficiency of the existing CETP needs to be enhanced, and the proper operation and maintenance are required to meet the desired discharge standard quality. Also, all the unauthorized wastewater outfalls from tanneries must be closed to save the Dhaleshwari River.

Drinking Water Quality Mapping Using Water Quality Index and Geospatial Analysis in Primary Schools of Pakistan

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

Application of Irrigation Water Quality Indices and Multivariate Statistical Techniques for Surface Water Quality Assessments in the Northern Nile Delta, Egypt

Under sustainable development conditions, the water quality of irrigation systems is a complex issue which involves the combined effects of several surface water management parameters. Therefore, this work aims to enhance the surface water quality assessment and geochemical controlling mechanisms and to assess the validation of surface water networks for irrigation using six Water Quality Indices (WQIs) supported by multivariate modelling techniques, such as Principal Component Regression (PCR), Support Vector Machine Regression (SVMR) and Stepwise Multiple Linear Regression (SMLR). A total of 110 surface water samples from a network of surface water cannels during the summers of 2018 and 2019 were collected for this research and standard analytical techniques were used to measure 21 physical and chemical parameters. The physicochemical properties revealed that the major ions concentrations were reported in the following order: Ca2+ > Na+ > Mg2+ > K+ and alkalinity > SO42− > Cl− > NO3− > F−. The trace elements concentrations were reported in the following order: Fe > Mn > B > Cr > Pb > Ni > Cu > Zn > Cd. The surface water belongs to the Ca2+-Mg2+-HCO3− and Ca2+-Mg2+-Cl−-SO42− water types, under a stress of silicate weathering and reverse ion exchange process. The computation of WQI values across two years revealed that 82% of samples represent a high class and the remaining 18% constitute a medium class of water quality for irrigation use with respect to the Irrigation Water Quality (IWQ) value, while the Sodium Percentage (Na%) values across two years indicated that 96% of samples fell into in a healthy class and 4% fell into in a permissible class for irrigation. In addition, the Sodium Absorption Ratio (SAR), Permeability Index (PI), Kelley Index (KI) and Residual Sodium Carbonate (RSC) values revealed that all surface water samples were appropriate for irrigation use. The PCR and SVMR indicated accurate and robust models that predict the six WQIs in both datasets of the calibration (Cal.) and validation (Val.), with R2 values varying from 0.48 to 0.99. The SMLR presented estimated the six WQIs well, with an R2 value that ranged from 0.66 to 0.99. In conclusion, WQIs and multivariate statistical analyses are effective and applicable for assessing the surface water quality. The PCR, SVMR and SMLR models provided robust and reliable estimates of the different indices and showed the highest R2 and the highest slopes values close to 1.00, as well as minimum values of RMSE in all models.

Assessing Land-Cover Effects on Stream Water Quality in Metropolitan Areas Using the Water Quality Index

This study evaluated the influence of different land-cover types on the overall water quality of streams in urban areas. To ensure national applicability of the results, this study encompassed ten major metropolitan areas in South Korea. Using cluster analysis, watersheds were classified into three land-cover types: Urban-dominated (URB), agriculture-dominated (AGR), and forest-dominated (FOR). For each land-cover type, factor analysis (FA) was used to ensure simple and feasible parameter selection for developing the minimum water quality index (WQImin). The chemical oxygen demand, fecal coliform (total coliform for FOR), and total nitrogen (nitrate-nitrogen for URB) were selected as key parameters for all land-cover types. Our results suggest that WQImin can minimize bias in water quality assessment by reducing redundancy among correlated parameters, resulting in better differentiation of pollution levels. Furthermore, the dominant land-cover type of watersheds, not only affects the level and causes of pollution, but also influences temporal patterns, including the long-term trends and seasonality, of stream water quality in urban areas in South Korea.

Assessment of spatio-temporal variations in lake water body using indexing method

The study assesses the characteristics of two lakes located in close vicinity to each other in identifying the status of the lakes based on Designated Best Use (DBU) criteria for optimum utilization and use. Further, the study reports the characteristic assessment of the lakes for two seasons with sampling carried out in August and October months of 2019 and samples collected at different depths and locations to present the comprehensive existing water quality conditions of the lake. The study utilized about twenty parameters evaluated experimentally for determination of Water Quality Indices. In this context, different water quality indices including National Sanitation Foundation Method (NSFWQI) and BIS 10500 (BISWQI) were utilized in determining the indices. The WQI were determined depth wise and a weighted average method was utilized in presenting the overall WQI of the lakes which represents the true water quality based on depth wise evaluation. Hence, the study represents both spatial and temporal variations in the lake water quality. The overall classification of water quality for both the lakes using the NSFWQI methodology was good for both the sampling periods. Similarly, the overall water quality was categorized to be excellent for both the sampling periods using the BISWQI. Further, a new approach in determining water quality indexing is presented through introduction of a Modified Water Quality Index (MWQI) which utilizes the maximum number of parameters and thereby provides a means to reduce ambiguity and eclipsing problems of WQI. Using this newly developed MWQI, the water quality was categorized to be excellent and good for samples collected in August and October respectively for both the lakes. However, conservative estimation considering spillover effects may lead to classification of good category using MWQI. The Heavy Metal Pollution Index (HMI) were classified to be good for both the lakes and sampling periods. Spectral characterization of water samples revealed the presence of oxygen (O), tantalum (Ta), sodium (Na) and Zinc (Zn). However, further monitoring studies are being carried out to cover a period of 1 year to observe if there is a change in water quality due or any seasonal variations.

Water quality assessment and pollution source apportionment using multi-statistic and APCS-MLR modeling techniques in Min River Basin, China

Anthropogenic activities pose challenges on security of water quality. Identifying potential sources of pollution and quantifying their corresponding contributions are essential for water management and pollution control. In our study, 2-year (2017-2018) water quality dataset of 15 parameters from eight sampling sites in tributaries and mainstream of the Min River was analyzed with multivariate statistical analysis methods and absolute principal component score-multiple linear regression (APCS-MLR) receptor modeling technique to reveal potential sources of pollution and apportion their contributions. Temporal and spatial cluster analysis (CA) classified 12 months into three periods exactly consistent with dry, wet, and normal seasons, and eight monitoring sites into two regions, lightly polluted (LP) and highly polluted (HP) regions, based on different levels of pollution caused by physicochemical properties and anthropogenic activities. The principal component analysis (PCA) identified five latent factors accounting for 75.84% and 73.46% of the total variance in the LP and HP regions, respectively. The main pollution sources in the two regions included agricultural activities, domestic sewage, and industrial wastewater discharge. APCS-MLR results showed that in the LP region, contribution of five potential pollution sources was ranked as agricultural non-point source pollution (22.13%) > seasonal effect and phytoplankton growth (19.86%) > leakage of septic tanks (15.73%) > physicochemical effect (12.86%) > industrial effluents and domestic sewage (11.59%), while in the HP region ranked as point source pollution from domestic and industrial discharges (20.81%) > municipal sewage (16.66%) > agricultural non-point source pollution (15.23%) > phytoplankton growth (14.82%) > natural and seasonal effects (12.67%). Based on the quantitative assessment of main pollution sources, the study can help policymakers to formulate strategies to improve water quality in different regions.

Use of water quality index and multivariate statistical methods for the evaluation of water quality of a stream affected by multiple stressors: A case study

The Sürgü Stream, located in the Euphrates River basin of Turkey, is used for drinking water source, agricultural irrigation and rainbow trout production. Therefore, water quality of the stream is of great importance. In this study, multivariate statistical techniques (MSTs) and water quality index (WQI) were applied to assess water quality of the stream affected by multiple stressors such as untreated domestic sewage, effluents from fish farms, agricultural runoff and streambank erosion. For this, 16 water quality parameters at five sites along the stream were monitored monthly during one year. Most of parameters showed significant spatial variations, indicating the influence of anthropogenic activities. All parameters except TN (total nitrogen) showed significant seasonal differences due to high seasonality in WT (water temperature) and water flow. The spatial variations in the WQI were significant (p < 0.05) and the mean WQI values ranged from 87.6 to 95.3, indicating "good" to "excellent" water quality in the stream. Cluster analysis classified five sites into three groups, that is, clean region, low polluted region and very clean region. Stepwise temporal discriminant analysis (DA) identified that pH, WT, Cl^-, SO₄^2-, COD (chemical oxygen demand), TSS (total suspended solids) and Ca²⁺ are the parameters responsible for variations between seasons, and stepwise spatial DA identified that DO (dissolved oxygen), EC (electrical conductivity), NH₄-N, TN (total nitrogen) and TSS are the parameters responsible for variations between the regions. Principal component analysis/factor analysis revealed that the parameters responsible for water quality variations were mainly associated with suspended solids (both natural and anthropogenic), soluble salts (natural) and nutrients and organic matter (anthropogenic).

A holistic assessment of water quality condition and spatiotemporal patterns in impounded lakes along the eastern route of China's South-to-North water diversion project

Water quality is one of the key determinants for assessing effectiveness and success of water diversions, but rarely studied at a spatial scale that crosses large river basins. Multiple statistical methods and the water quality index (WQI) were used to assess overall condition and detect spatiotemporal patterns of water quality in a series of impounded lakes along the Eastern Route of China's South-to-North Water Diversion Project. Principal components analysis and analysis of variances identified three groups with distinct water quality characteristics: upstream Gaoyou Lake and Hongze Lake showing relatively higher nutrients, turbidity, and total suspended solids; downstream Dongping lake and Donghu Lake showing higher conductivity, total hardness, and chloride; and Luoma Lake and Nansi Lake intermediate between the two former groups. The WQI indicated overall "Good" water quality with an improving trend from upstream to downstream lakes. The upstream Gaoyou Lake had over 55% of the monitoring sites with "Moderate" water quality in all the seasons. Management should focus on preventing high nitrogen, phosphorus, turbidity, and total suspended solids in upstream lakes, high chloride in downstream lakes, high nitrogen during water diversion seasons, and high phosphorus during non-water diversion seasons. These findings greatly improved our understanding of the spatiotemporal water quality patterns of the impounded lakes, and can be used to develop water quality management strategies. This study exemplifies a methodology for investigating and securing water quality for inter-basin water transfer projects.

A comparative study on the performance of NSFWQIm and IRWQIsc in water quality assessment of Sefidroud River in northern Iran

Local water quality indices (WQIs) are usually developed by modifying internationally recognized indices, which are considered reference index. In previous works on WQIs, the performance of local and reference indices has not been compared with each other. Therefore, the question crosses the mind whether using local or international indicators individually can show all qualitative aspects of a water resource. In this study, it was aimed to make this comparison between NSFWQI_m (National Sanitation Foundation Water Quality Index) as the reference index and IRWQI_sc (Iranian Water Quality Index for Surface Water Resource-Conventional Parameters) as the local one through a case study (Sefidroud River in northern Iran). Based on the results, the indices' performance in representing the seasonal and spatial fluctuations of the river water quality was almost similar. However, the water quality scores obtained by the two indices were somewhat different. Based on NSFWQI_m, the average water quality score of the river was about 49.0, by which the water was categorized in "bad" class, while IRWQI_sc represented an average score of 56.1, which corresponds to "fairly good" class. Therefore, NSFWQI_m identified the water quality with stricter criteria than IRWQI_sc, regarding the public health. On the other hand, according to relative standard deviations (0.17 for NSFWQI_m, 0.21 for IRWQI_sc) of the obtained water qualities, IRWQI_sc better distinguished between high and low water qualities of the river. Accordingly, in order to better interpret the quality conditions of surface water resources in Iran, it is necessary to use both indices since NSFWQI_m (reference index) attracts attention to stricter international standards and requirements, while IRWQI_sc (local index) causes more focus on seasons or locations with the worst water quality.

Spatiotemporal Analysis of Water Quality Using Multivariate Statistical Techniques and the Water Quality Identification Index for the Qinhuai River Basin, East China

Monitoring water quality is indispensable for the identification of threats to water environment and later management of water resources. Accurate monitoring and assessment of water quality have been long-term challenges. In this study, multivariate statistical techniques (MST) and water quality identification index (WQII) were applied to analyze spatiotemporal variation in water quality and determine the major pollution sources in the Qinhuai River, East China. A rotated principal component analysis (PCA) identified three potential pollution sources during the wet season (mixed pollution, physicochemical, and nonpoint sources of nutrients) and the dry season (nutrient, primary environmental, and organic sources) and they explained 81.14% of the total variances in the wet season and 78.42% of total variances in the dry season. The result of redundancy analysis (RDA) showed that population density, urbanization, and wastewater discharge are the main sources of organic pollution, while agricultural fertilizer consumption and industrial wastewater discharge are the main sources of nutrients such as nitrogen and phosphorus. The water quality of the Qinhuai River basin was determined to be mainly Class III (slightly polluted) and Class IV (moderately polluted) based on WQII. Temporally, the change trend of WQII showed that water quality gradually deteriorated between 1990 and 2005, improved between 2006 and 2010, and then deteriorated again. Spatially, the WQII distribution map showed that areas with more developed urbanization were relatively more polluted. Our results show that MST and WQII are useful tools to help the public and decision makers to evaluate the water quality of aquatic environment.

Evaluating surface water quality using water quality index in Beiyun River, China

The Beijing-Tianjin-Hebei urban agglomeration is one of the most water-scarce regions in China, because of the frequent human activities. Water scarcity and pollution have weakened the service functions of water ecosystems and hindered the regional economic development. As the "lifeline" of the economic development of Beijing-Tianjin-Hebei region, the water quality of Beiyun River has been widely concerned. River water quality assessment is one of the most important aspects to enhance water resources management plans. Water quality index (WQI), as one of the most frequently used evaluation tools, was used to comprehensively analyze the water quality in the Beiyun River. Between January 2017 and October 2018, we collected samples from 16 typical sampling sites along the main rivers of the watershed, covering four seasons. Seventeen water quality parameters, including temperature, pH, conductivity, dissolved oxygen (DO), chemical oxygen demand (COD), biochemical oxygen demand (BOD₅), ammonia nitrogen (NH₃-N), total phosphorus (TP), oil, volatile phenol (VP), fluoride, sulfide, surfactant, lead (Pb), copper (Cu), zinc (Zn), and arsenic (As), were used to calculate WQI. The average WQI values of Beiyun River in winter, spring, summer, and autumn were 88.15, 71.70, 78.92, and 90.12, respectively, explaining the water quality was "good" generally. There were significant differences in the spatial distribution of WQI values from Beiyun River, and water quality of upstream and downstream was better than that of midstream. In addition, correlation analysis was applied to explore the correlation between land use types and water quality. Water quality was significant negatively correlated with agriculture land and rural residential land, and a positive relationship between urban land and water quality. Generally, we believe that people's related activities on different land use are major elements impacting the water quality. Water environment improvement ought to increase the wastewater collection rate and sewage treatment capacity in rural areas, especially in the midstream of the Beiyun River. Graphical abstract.

Bacterial eutrophic index for potential water quality evaluation of a freshwater ecosystem

Water quality evaluation of freshwater ecosystems has been widely reported based on the physical and chemical parameters of water (e.g., Carlson's trophic state index (TSI)), while the aquatic microorganisms are actually a more intuitive way to reflect the eutrophic levels. This article was based on 27 global freshwater ecosystems including freshwater rivers, lakes, and reservoirs. Bacterial eutrophic index (BEI) was determined as the function of temperature and abundances of Cyanobacteria and Actinobacteria. BEI and TSI values of the freshwater ecosystems were determined and the correlation analysis of TSI and BEI indicated their positive correlation (ρ = 0.452, p < 0.01). Furthermore, an eutrophication classification based on BEI was proposed. It turned out that BEI was a possible feasible method for water quality evaluation. The aquatic microorganism-based method such as BEI should be considered for water quality evaluation of a freshwater ecosystem. Complicated models combined with physicochemical (e.g., TSI) and microbial (e.g., BEI) method are recommended for water quality evaluation of a freshwater ecosystem in future.

Intelligent System for the Predictive Analysis of an Industrial Wastewater Treatment Process

Considering the exponential growth of today’s industry and the wastewater results of its processes, it needs to have an optimal treatment system for such effluent waters to mitigate the environmental impact generated by its discharges and comply with the environmental regulatory standards that are progressively increasing their demand. This leads to the need to innovate in the control and management information systems of the systems responsible to treat these residual waters in search of improvement. This paper proposes the development of an intelligent system that uses the data from the process and makes a prediction of its behavior to provide support in decision making related to the operation of the wastewater treatment plant (WWTP). To carry out the development of this system, a multilayer perceptron neural network with 2 hidden layers and 22 neurons each is implemented, together with process variable analysis, time-series decomposition, correlation and autocorrelation techniques; it is possible to predict the chemical oxygen demand (COD) at the input of the bioreactor with a one-day window and a mean absolute percentage error (MAPE) of 10.8%, which places this work between the adequate ranges proposed in the literature.

Climatic seasonality and water quality in watersheds: a study case in Limoeiro River watershed in the western region of São Paulo State, Brazil

Applying the climatological water balance (WB) concept to describe the relationship between climatic seasonality and surface water quality according to different forms of land use and land cover (LULC) is an important issue, but little explored in the literature. In this paper, we evaluate the influence of WB on surface water quality and its impacts when interacting with LULC. We monitored 11 sampling points during the four seasons of the year, from which we estimate WQI (water quality index) and TSI (trophic state index). We found an effect of the seasonality factor on both WQI values (F(3,30) = 12.472; p < 0.01) and in TSI values (F(3,30) = 6.967; p < 0.01). We noticed that LULC interferes in the way that the water balance influences the WQI and TSI values since in sampling points closest to higher urban density, with little or no riparian protection, the correlation between water balance and water quality was lower. In the stations that had the lowest water surplus and deficit, there was positive linearity between water balance and WQI. However, in the seasons when the surplus and water deficit recorded were extreme, there was no linearity. We conclude that water deficiency impairs the quality of surface water. In the extreme surplus water season, the homogeneity of WQI samples was lower, suggesting a higher interaction between rainwater and LULC. This study contributes to design management strategies of water resources, considering the climatic seasonality for optimization.

Combining Hydrogeochemical Characterization and a Hyperspectral Reflectance Tool for Assessing Quality and Suitability of Two Groundwater Resources for Irrigation in Egypt

Hyperspectral reflectance sensing provides a rapid and cost-effective technique for assessing the suitability of groundwater for irrigation by monitoring real-time changes in its quality at a large scale. In this study, we assessed the quality of 15 groundwater samples from El Fayoum depression in the Western Desert (WD) and 25 groundwater samples from the Central Nile Delta (CND) in Egypt using a traditional approach of the physiochemical parameters, irrigation water quality indicators (IWQIs), and hydrochemical facies. The spectral reflectance data of the water surface was used to build new simple reflectance indices (SRIs), and the performance of these indices for assessing IWQIs was compared with those by partial least square regression (PLSR) that was based on all SRIs or the full-spectrum ranges. Generally, the groundwater of the CND was fresher and more suitable for irrigation purposes than those of the WD. Based on the six IWQIs, ~6.7–60.0% and 85.0–100.0% of the groundwater samples of the WD and CND, respectively, were categorized as highly suitable for irrigation purposes. Based on hydrochemical facies, Na-Cl and Ca-HCO3 were dominant in the WD and CND, respectively, as well as the alkali earth metals (Na+ + K+), which significantly exceeded the alkaline earth metals (Ca2+ + Mg2+) in the WD, with the reverse for the CND. Most developed SRIs had a moderate, weak, and moderate to strong relationship with physiochemical parameters and IWQIs in the WD, CND, and across both regions, respectively. The PLSR models based on all SRIs provided a more accurate estimation of IWQIs in calibration and validation datasets than those based on full-spectrum ranges, and both PLSR models provided better estimation than the individual SRIs. These findings support the feasibility of using ground reflectance measurements as a fast and low-cost tool for the assessment and management of groundwater for irrigation in arid and semiarid regions.