Assessment of surface water quality using water quality index and multivariate statistical analyses in Saraydüzü Dam Lake, Turkey

A case study of using artificial neural networks to predict heavy metal pollution in Lake Iznik

Artificial neural networks offer a viable route in assessing and understanding the presence and concentration of heavy metals that can cause dangerous complications in the wider context of water quality prediction for the sustainability of the ecosystem. In order to estimate the heavy metal concentrations in Iznik Lake, which is an important water source for the surrounding communities, characterization data were taken from five different water sources flowing into the lake between 2015 and 2021. These characterization results were evaluated with IBM SPSS Statistics 23 software, with the addition of the lake water quality system. For this purpose, seven distinct physicochemical parameters were measured and monitored in Karasu, Kırandere, Olukdere and Sölöz water sources flowing into the lake, to serve as input data. Concentration levels of 15 distinct heavy metals in Karsak Stream originating from the lake were as the output. Specifically, Sn for Karasu (0.999), Sb for Kırandere (1.000), Cr for Olukdere (1.000) and Pb and Se for Sölöz (0.995) indicate parameter estimation R2 coefficients close to 1.000. Sn stands out as the common heavy metal parameter with best estimation prospects. Given the importance of the independent variable in estimating heavy metal pollution, conductivity, COD, COD and temperature stood out as the most effective parameters for Karasu, Olukdere, Kırandere and Sölöz, respectively. The ANN model emerges as a good prediction tool that can be used effectively in determining the heavy metal pollution in the lake as part of the efforts to protect the water budget of Lake Iznik and to eliminate the existing pollution.

Assessment of water quality based on statistical analysis of physical-chemical, biomonitoring and land use data: Manso River supply reservoir

Preserving the quality of surface water has become increasingly difficult due to the intensification of human activities in watersheds. This study assessed the water quality of the Manso River reservoir, which supplies water to Brazil's third largest metropolitan region. The integration of >10,000 secondary data, comprising physico-chemical parameters, metals and microbiological indicators, together with biomonitoring and land use and occupation data, were analyzed by using statistical tools, the Water Quality Index (WQI) and the Trophic State Index (TSI). The results showed higher concentrations for solids and metals (Fe and Mn) characteristic of local geochemistry and also related to the mining activity in the region. Parameters associated with organic pollution, such as total phosphorus and Escherichia coli, were also elevated, probably due to contamination by untreated or insufficiently treated domestic sewage. The water at the tributary watercourses presented worse quality, predominantly medium WQI, compared with the stations inside the reservoir (predominantly good WQI). The TSI indicated a predominance of ultra-oligotrophic conditions for stations located in the lotic environment and mesotrophic conditions for those located in the lentic environment. In general, the same pattern was observed for the occurrence of the phytoplankton and zooplankton classes, indicating the relationship between the degree of trophy and the composition of these groups. In quantitative terms, for phytoplankton, the Euchlorophyceae and Cyanophyceae classes stood out, mainly in the rainy period (summer), whereas for zooplankton, the Crustacea and Monogonta classes were dominant. Regarding land use and occupation in the reservoir sub-basin, the positive impact of the surrounding forest cover was observed. It was also identified the effect of seasonality on the quality of aquatic environments. The integrated evaluation of the results proved to be efficient in assessing the environmental conditions of the reservoir and the tributaries, providing information for better management of these water resources.

Evaluation of some heavy metals and selenium pollution in Karataş Lake (Burdur/Türkiye) using various pollution indices and statistical analysis

Wetland face environmental problems due to some reasons such as drought, rapid population and rapid developments in technology. Karataş Lake is located within the Lakes Region in Türkiye and has also of great economically, ecologically and ornithologically importance. Unfortunately, it completely dried out in 2021 due to sufficient rainfall, groundwater withdrawal and global climate change. In 2022, the lake started to hold water again. This study is important because it is one of the last studies before the lake dries up and first study to evaluate some heavy metals and selenium pollution using some indices. In this study, which was carried out between October 2019-July 2020, some heavy metals and selenium concentrations were determined in water of Karataş Lake seasonally and evaluated pollution degree of lake water using some indices and statistical analysis. Water temperature, pH, electrical conductivity and dissolved oxygen levels were measured in situ using YSI 556 MPS. For heavy metal analysis, water samples were taken, acidified to a pH of <2, stored at 4 °C and analyzed directly using ICP-OES (Agilent 5110). Pb and Se in all seasons were below detection limit. The analyzed metals sorted as; Cd < Mo < Cr < Cu < Mn < Zn < Ni < Fe. Generally, heavy metals were increased in autumn and decreased in spring. According to some water quality standards for drinking water, Fe levels were higher than the permissible levels for drinking water in all seasons (TSE, 2005; EPA, 2018; EU, 2020), Mn in autumn (TSE, 2005; EPA, 2018; EU, 2020), Ni in autumn and summer (TSE, 2005; EU, 2020). Water Quality Index (WQI), Heavy Metal Pollution Index (HPI) and Heavy Metal Evaluation Index (HEI) values were calculated in Karataş Lake to determine pollution degree. Depend on WQI results, lake water was in good category in autumn, winter and spring while poor category in summer. The lake water samples based on HPI and HEI values are in the low contamination category. The lake is still struggling with environmental problems. If necessary precautions are not taken for the future of the lake, the lake may dry out again. The results of this study will help the authorities in terms of preventing re-drying, sustainability of the lake and management of the region. This study will be also a reference for future studies.

The effect of organic pollution on the seasonal dynamics of water quality in a semi-arid zone: case of the Hammam Boughrara Dam, Tlemcen (Algeria)

The present study aims to assess the impact of human activities on the water quality of the Hammam Boughrara dam. It also highlights the crucial importance of sustainable management of water resources in the face of persistent challenges related to various forms of pollution. The study is based on an exhaustive database covering a period spread over 16 years, with monthly measurements of organic pollution indicator parameters, namely BOD5, COD, [Formula: see text],[Formula: see text], [Formula: see text], [Formula: see text], Organic Matter (OM), TDS, Dissolved Oxygen (DO) and pH. The box plots showed an asymmetric distribution of almost all the parameters, with significant seasonal variations in the interquartile (IQR) range. The IQR ranges for [Formula: see text] extends from 0.575 mg/l (summer) to 4.445 mg/l (spring), and for [Formula: see text] from 1.3075 mg/l (autumn) to 1.8625 mg/l (spring). This led to the use of the Spearman method for the analysis of correlations between different parameters. The seasonal study of the five categories of water quality, according to the Organic Pollution Index (OPI), revealed considerable organic pollution. At the 1% significance level, the seasonal correlation between OPI and [Formula: see text] varies between -0.71 and -0.85, while that with [Formula: see text] fluctuates between -0.69 and -0.86. During the period analyzed, the COD/BOD Ratio (CBR) reveals two dominant categories with seasonal variations, i.e. the Moderately Biodegradable Effluents (MBE), with 96 cases, reaching 29 in autumn and 20 in spring. The Difficult to Biodegrade or Non-Biodegradable Effluents (DBE or NBE) category records 94 cases, with a maximum frequency of 26 in winter and minimum of 21 in autumn. These results therefore show the persistence of organic pollution, which had an impact on water quality over the four seasons and throughout the period studied. The results indicate persistent organic pollution affecting water quality. Therefore, prompt actions and sustainable strategies are deemed necessary to mitigate these harmful impacts and to ensure the sustainability of the water resource.

Identification of core carcinogenic elements based on the age-standardized mortality rate of lung cancer in Xuanwei Formation coal in China

In this study, the core carcinogenic elements in Xuanwei Formation coal were identified. Thirty-one samples were collected based on the age-standardized mortality rate (ASMR) of lung cancer; Si, V, Cr, Co, Ni, As, Mo, Cd, Sb, Pb, and rare earth elements and yttrium (REYs) were analyzed and compared; multivariate statistical analyses (CA, PCA, and FDA) were performed; and comprehensive identification was carried out by combining multivariate statistical analyses with toxicology and mineralogy. The final results indicated that (1) the high-concentration Si, Ni, V, Cr, Co, and Cd in coal may have some potential carcinogenic risk. (2) The concentrations of Cr, Ni, As, Mo, Cd, and Pb meet the zoning characteristics of the ASMR, while the Si concentration is not completely consistent. (3) The REY distribution pattern in Longtan Formation coal is lower than that in Xuanwei Formation coal, indicating that the materials of these elements in coal are different. (5) The heatmap divides the sampling sites into two clusters and subtypes in accordance with carcinogenic zoning based on the ASMR. (6) PC1, PC2, and PC3 explain 62.629% of the total variance, identifying Co, Ni, As, Cd, Mo, Cr, and V. (7) Fisher discriminant analysis identifies Ni, Si, Cd, As, and Co based on the discriminant function. (8) Comprehensive identification reveals that Ni is the primary carcinogenic element, followed by Co, Cd, and Si in combination with toxicology. (9) The paragenesis of Si (nanoquartz), Ni, Co, and Cd is an interesting finding. In other words, carcinogenic elements Ni, Co, Cd, and Si and their paragenetic properties should receive more attention.

Microbial and potentially toxic elements risk assessment in high Andean river water based on Monte Carlo simulation, Peru

The study evaluated microbial and Potentially Toxic Elements-PTEs risks in high Andean river water in Peru using Monte Carlo simulation. A total of 144 water samples were collected from four rivers and evaluated for physicochemical parameters, PTEs and bacterial pathogens. The microbial risk analysis for exposure to pathogens present in the water was based on the probability of occurrence of diseases associated with Escherichia coli, Pseudomonas aeruginosa and enterococci. PTEs risk analysis was performed using a Monte Carlo simulation approach. The results showed that the highest microbial risk due to exposure to water contaminated by E. coli, P. aeruginosa and enterococci was recorded in the Miraflores and Chia rivers. Meanwhile, the analysis of carcinogenic and non-carcinogenic risk by PTEs in adults and children revealed that the Chia river presents a high risk of contamination by PTEs, especially the carcinogenic risk for children. The Monte Carlo simulation indicated a 56.16% and 94.85% probability of exceeding the limit value of 0.0001 for carcinogenic risk in adults and children, respectively. It can be concluded that children consuming the waters of the Chia river are potentially at risk of As toxicity.

Spatial distribution and pollution assessment of heavy metals in surface and bottom water along the eastern part of the Egyptian Mediterranean coast

Seawater contamination with heavy metals (HMs) as a result of anthropogenic activities is a global challenge due to its negative impacts on marine environments and coastal communities. This study investigates the distribution of HMs (Fe, Zn, Cu, Mn, Cd, Ni and Co) and assesses the quality of surface and bottom seawater. Samples were collected in winter 2020 and summer 2021 from eleven sectors along the eastern Egyptian Mediterranean Sea coast. The water quality was evaluated using Water Quality Index (WQI), Metal Index (MI), heavy metal pollution index (HMI) and Metal Pollution index (MPI). The results indicated that, Eastern Harbour, Abu-Qir and Port Said sectors were polluted with HMs. Based on Two-Way ANOVA test there was seasonal variation for dissolved HMs (Zn, Ni, Cd and Mn in bottom layer and Cu in surface layer), while, (Cd, Co, Cu, Zn and Mn (in bottom layer)) revealed spatial differences among sectors.

The impacts of human-induced disturbances on spatial and temporal stream water quality variations in mountainous terrain: A case study of Borcka Dam Watershed

Unaltered watersheds with natural vegetation cover (forest, grasslands, etc.) provide several ecological benefits in addition to providing freshwater, controlling water levels, and supporting flourishing streamside ecosystems. However, as in many watersheds in the World, the research area in this study, the Borcka Dam Watershed (BDW), has been affected by many human-induced disturbances affecting a wide area of forest and grassland areas as well as soil and water resources. Therefore, the objective of this study was to assess and evaluate the possible effects of anthropogenic disturbances, particularly on annual changes in water discharge, some water quality parameters, and total suspended sediment (TSS) amounts in the main streams of four sub-watersheds (Fabrika, Godrahav, Hatila, and Murgul) and the reservoir of the dam. In addition, we intend to confirm that land use change and/or transformation play a significant role in influencing stream water quality. The YSI/Professional-Plus, a portable water quality measurement device, was used to determine the amounts of pH, dissolved oxygen (DO), total dissolved substance (TDS), ammonium (NH4-N), nitrate (NO3-N), salinity, electrical conductivity (EC), and temperature besides measuring discharge and total suspended sediments (TSS) from a total of 27 sampling points in the field. Although the results revealed that the annual mean values of all water quality parameters for all four streams were mostly in good condition, for some time and points of the measurements, several parameters were found to be above the official water quality standards due to the intensive aforementioned anthropogenic activities, particularly in the stream waters of Murgul (e.g. pH and TSS being 10,84 and 236 mg/L, respectively) and Fabrika (e.g. EC of 412 μs/cm; DO of 4.44 mg/L; 14 ml of NO3-N) sub-watersheds. These outcomes indicate that these two sub-watersheds have been impacted more severely by the human-induced disturbances compared to Hatila and Godrahav sub-watersheds.

Surface water quality for irrigation and industrial purposes: a comparison between the south and north sides of the Wei River Plain (northwest China)

Surface water is extensively used for irrigation and industrial purposes in the Wei River Plain. However, the surface water shows different characteristics in the southern and northern zones of the Wei River Plain. This study aims to investigate the differences in surface water quality between the southern and northern zones of the Wei River Plain and their influencing factors. To ascertain the hydrochemistry and its governing factors, graphical methods, ion plots, and multivariate statistical analyses were employed. The quality of the irrigation water was assessed using various irrigation water quality indices. In addition, water foaming, corrosion, scaling, and incrustation risks were determined to evaluate water quality for industrial uses. The spatial distribution of water quality was done using GIS models. This research revealed that the concentrations of EC, TH, TDS, HCO₃^-, Na⁺, Mg²⁺, SO₄^2- and Cl^- on the north side of the plain were twice as high as those on the south side. On both sides of the Wei River Plain, water‒rock interactions, ion exchange, and considerable evaporation were observed. Gypsum, halite, calcite, and dolomite all dissolve to produce significant anions and cations in the water, according to ion correlation analysis. However, additional sources of contaminants led to higher concentrations in the surface water on the north side than on the south side. Surface water in the south of the Wei River Plain has superior quality to that in the north, according to the overall findings of irrigation water and industrial water quality assessments. The findings of this study will boost better water resource management policies for the plain.

Implications of land use/land cover dynamics on urban water quality: Case of Addis Ababa city, Ethiopia

Water resources are often at the center of urban development but, as the city expands, the environmental pressure on its water resources increases. Therefore, in this study, we looked into how various land uses and changes in land cover affect the water quality in Addis Ababa, Ethiopia. Land use and land cover change maps were generated from 1991 to 2021 at intervals of five years. On the basis of the weighted arithmetic water quality index approach, the water quality for the same years was likewise divided into five classes. The relationship between land use/land cover dynamics and water quality was then evaluated using correlations, multiple linear regressions, and principal component analysis. According to the computed water quality index, the water quality decreased from 65.34 in 1991 to 246.76 in 2021. The built-up area showed an increase of over 338%, whereas the amount of water decreased by over 61%. While barren land exhibited a negative correlation with nitrates, ammonia loadings, total alkalinity, and total hardness of the water, agriculture and built-up areas positively correlated with water quality parameters such as nutrient loading, turbidity, total alkalinity, and total hardness. A principal component analysis revealed that built up areas and changes in vegetated areas have the biggest impact on water quality. These findings suggest that land use and land cover modifications are involved in the deterioration of water quality around the city. This study will offer information that might help reduce the dangers to aquatic life in urbanized environments.

Assessment of the water quality of Bartın Kışla (Kozcağız) Dam by using geographical information system (GIS) and water quality indices (WQI)

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

Quality and groundwater contamination of Wadi Hanifa, central Saudi Arabia

In arid and semi-arid regions, freshwater is mainly acquired from groundwater. Over the years, human activities have reduced the latter's quality, making it a threat to health. Heavy metal pollution index (HPI), metal index (MI), groundwater quality index (GWQI), sodium absorption ratio (SAR), magnesium ratio (MR), Kelly's ratio (KR), and sodium percentage (Na%) were applied as pollution parameters and indices in assessing the groundwater's suitability for irrigation and drinking purposes in Wadi Hanifa in Saudi Arabia. Samples were collected from 26 sites, and a physicochemical analysis and heavy metal analysis were conducted. The results showed a concentration of SO₄^2-, Cl^-, Ca²⁺, HCO₃^-, Na⁺, Mg²⁺, and K⁺, which is higher than the WHO standards for drinking water. 96.15% of the water samples (n = 25) fell under the Ca-Cl groundwater dominant facies type, and one model fell under the mixed type. According to the GWQI classification, 16.66%, 50%, and 26.92% of the collected samples are categorized as very poor, poor, and generally unsuitable for human consumption, respectively. Parameters such as SAR, KR, and Na% are indicative of irrigation water. The study's primary factors affecting the groundwater chemistry included the natural processes of precipitation or dissolution of the silicates, carbonates, and evaporites alongside anthropogenic activities and soil leaching.

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

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

A 16th century artificial reservoir under human pressure: water quality variability assessment in Laguna de Yuriria, central Mexico

This study assesses the variability of physicochemical and biochemical parameters, identifies principal pollutant sources, and characterizes water quality in Yuriria reservoir using water quality indexes in combination with multivariate statistical techniques. In situ parameters were measured in 55 reservoir sites including surface and deep points and in 7 associated channels. Moreover, major compounds and biochemical data were determined. Yuriria reservoir had alkaline, bicarbonate-mixed waters, with total dissolved solids (TDS) of 393.83 ± 3.43 mg L^-1. Water quality index (WQI) indicated a good class for agricultural irrigation but very poor and poor classes for preservation of aquatic life. The nutrient inputs and the internal nitrogen recycling triggered a hypereutrophic status in the reservoir. The decomposition of residual biomass from aquatic macrophytes contributed to reduce dissolved oxygen (DO) in the hypolimnetic waters (mean DO = 3.86 mg L^-1). Statistical analysis revealed that the study area is highly exposed to anthropogenic stress and in a lesser extent to natural processes. Urban and agriculture runoff enhanced the salinization and the generation of solid particles which deteriorated water quality. Chemical oxygen demand (COD), biochemical oxygen demand (BOD), and NO₃^--N presented a common anthropogenic origin by external (point and diffuse) and internal pollution sources, while a diffuse source (agricultural activities) was reveled for phosphorus. This study is important to be used in systematic monitoring and sustainable co-management programs and for formulating the necessary strategies to remediate the Yuriria reservoir water quality and extrapolate to other reservoirs worldwide.

Evaluation of seasonal dynamics of the surface water hydrochemistry using multivariate statistical techniques and aquatic macrophyte productivity in a mountainous lake, Northeast India

The present work elucidates the effective application of multivariate statistics in understanding the probable relations between surface water hydrochemistry and aquatic macrophyte productivity and their underlying seasonal dynamics in a remote mountainous lake of northeast India. The result of hierarchical cluster analysis revealed three distinct clusters corresponding to the pre-monsoon (35.42%), post-monsoon (52.08%), and monsoon (12.50%) seasons. The factor analysis yielded three principal components suggesting the sediment flux, farming discharge, domestic waste, bacterial oxidation of sulfur compounds, and dissolution of plant matters associated with dissolved feldspar minerals as the influential factors. The lake hydrochemistry also varied significantly, both spatially and temporally implying geogenic weathering processes from rock-soil-water interactions. Overall, sixteen aquatic macrophytes were identified, and their monthly and daily net primary productivity varied considerably in different seasons. Regression analysis highlighted the effect of temperature, total dissolved solids, electrical conductivity, and turbidity on the seasonal fluctuations in macrophyte productivity. Overall, the study provides insights into seasonal variation in the lake water chemistry and highlights the role of statistical tools in understanding the fragile aquatic ecosystems over cost-, labor-, and time-intensive inventory studies.

Improving the measurement of total dissolved sulfide in natural waters: A new on-site flow injection analysis method

Total dissolved sulfide (TDS) plays multiple important roles in the aquatic environments. However, the determination of trace levels of TDS in natural waters is challenging because TDS is vulnerable to oxidation and volatilization. In this study, a fully automated flow injection analysis spectrophotometric system, incorporating a hollow fiber membrane contactor (HFMC) and a long path length liquid waveguide capillary cell, was fabricated to facilitate the on-site measurement of trace TDS in natural waters. The HFMC was used for matrix separation and analyte preconcentration. The measurement was based on the reaction of sulfide and N,N-dimethyl-p-phenylenediamine in the presence of FeCl₃ under acidic conditions to yield methylene blue (MB). The proposed method was highly sensitive, with detection and quantification limits of 0.57 and 1.90 nmol L^-1, respectively. The linear working range was from 1.90 to 150 nmol L^-1, with a correlation coefficient of 0.9995. The repeatability, expressed as the relative standard deviation, was less than 0.86% (n = 15) and the recoveries varied from 76.2 ± 0.1% to 103.9 ± 0.6% (n = 3) for spiked samples. This method was applied to conduct a field analysis of TDS in a reservoir, giving results aligned with those obtained using a standard MB method. This work demonstrates that the new method for determining TDS was effective for both laboratory analysis and on-site measurement.

Combinations of multivariate statistical analysis and analytical hierarchical process for indexing surface water quality under arid conditions

Novel methods for water quality indexing increase insight into the fitness of water bodies for different uses. We hypothesized that integrating multivariate statistical analysis (MSA) with the analytical hierarchical process (AHP) may provide a reliable estimation of water quality status. Hence, twenty water samples from canals and drains in the northern Nile Delta, Egypt were collected during summer, autumn, winter, and spring and analyzed. Data were subjected to MSA, including correlation analysis, principal component analysis (PCA), and hierarchal cluster analysis (HCA). The AHP was applied to derive weights of parameters implied in developing water quality indices for irrigation (IWQI) and fish farming (FFWQI). Human health risks due to exposure to potentially toxic elements (PTEs) via dermal contact were also considered. The average concentrations of water constituents were acceptable for irrigation, except sodium adsorption ratio (SAR) and Cl^-. The dissolved oxygen, total dissolved solids, Cl^-, NO₂-N, NO₃-N, NH₃, and PTEs (except Zn) did not meet standard limits for fish production. The MSA revealed that water contamination resulted from human activities (agriculture, industry, and domestic wastes) and hydrochemical processes. The PCA indicated that SAR, Cu, and pH could adequately represent water quality for irrigation, while temperature, NO₂-N, Cr, and Zn could reflect fish farming requirements. The AHP provided consistent weights for the original and shortlisted parameters. The water quality varied from good to poor for irrigation and from excellent to low for fish farming. The minimum IWQI could adequately represent the IWQI (R² = 0.83) and thus reduce the time, effort, and cost for monitoring water quality. However, the minimum FFWQI showed moderate consistency (R² = 0.51) with FFWQI, implying that increasing the sampling size is essential for better performance. The hazard quotient of all PTEs was below 1.0 for both adults and children, indicating a safe limit. The potential cancer risk was acceptable (1.36E-06) for adults and safe (8.03E-07) for children. Results of this work would be a start point for efficient quality control programs in arid regions.

Data-driven soft computing modeling of groundwater quality parameters in southeast Nigeria: comparing the performances of different algorithms

In recent decades, the simulation and modeling of water quality parameters have been useful for monitoring and assessment of the quality of water resources. Moreover, the use of multiple modeling techniques, rather than a standalone model, tends to provide more robust and reliable insights. In this present paper, several soft computing techniques were integrated and compared for the modeling of groundwater quality parameters (pH, electrical conductivity (EC), total dissolved solids (TDS), total hardness (TH), modified heavy metal index (MHMI), pollution load index (PLI), and synthetic pollution index (SPI)) in Ojoto area, SE Nigeria. Standard methods were employed in the physicochemical analysis of the groundwater resources. It was found that anthropogenic and non-anthropogenic activities influenced the concentrations of the water quality parameters. The PLI, MHMI, and SPI revealed that about 20-25% of the groundwater samples are unsuitable for drinking. Simple linear regression indicated that strong agreements exist between the results of the water quality indices. Principal component and Varimax-rotated factor analyses showed that Pb, Ni, and Zn influenced the judgment of the water quality indices most. Q-mode hierarchical and K-means clustering  algorithms grouped the water samples based on their pH, EC, TDS, TH, MHMI, PLI, and SPI values. Multiple linear regression (MLR) and artificial neural network (ANN) algorithms were used for the simulation and prediction of  the pH, EC, TDS, TH, PLI, MHMI, and SPI. The MLR performed better than the ANN model in predicting EC, TH, and TDS. Nevertheless, the ANN model predicted the pH better than the MLR model. Meanwhile, both MLR and ANN performed equally in the prediction of PLI, MHMI, and SPI.

Assessment of Groundwater Quality Using Water Quality Index from Selected Springs in Manga Subcounty, Nyamira County, Kenya

We present the results of groundwater quality assessment that was done during the rainy season in November 2018 in the Manga region of Nyamira County, Kenya. Water samples were collected from three springs, Kiangoso, Kerongo, and Tetema, for the assessment. Water quality index was calculated based on pH, turbidity, nitrate, phosphate, calcium, magnesium, chloride, sulphates, fluoride, iron, total phosphorous, total hardness, total alkalinity, total dissolved solids, and total coliform. These fifteen parameters were analyzed and characterized according to standard methods and with reference to the World Health Organization and Kenya Bureau of Standards for physiochemical and bacteriological parameters which were then used in the calculation of water quality index. The water quality index was 21.32 for Kiangoso, 29.66 for Kerongo, and 25.64 for Tetema. The water quality index was found to be of excellent quality status at Kiangoso, while of good quality status at Kerongo and Tetema. The water quality index of Manga groundwater represented by the three springs therefore is less than 30 and can be used for drinking, irrigation, and industrial purpose. The present results are crucial for future management of groundwater in the Manga region.

Ecological risks and controlling factors of trace elements in sediments of dam lakes in the Black Sea Region (Turkey)

The evaluation of trace elements (TEs) in sediments of dam lakes is crucial for maintaining ecosystem health. Therefore, it is very important to determine their concentrations, pollution status, sources, controlling factors and ecological risks in these ecosystems. Here, for the first time, we analyzed 14 TEs (Al, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Cd, Sb, Hg and Pb) and sediment properties (organic matter (OM) and pH) in sediments from four dam lakes (Erfelek, Derbent, Suat Uğurlu and Saraydüzü) in the Black Sea Region of Turkey, which are used for different purposes and located on the different rivers or streams with different pollution levels. The results indicated that Al, V, Mn, Fe, Cu, Zn, As, Pb and Sb concentrations were lower in the Erfelek Dam Lake which has been used for drinking water supply, indicating that it is more protected than other dam lakes. However, Al, V, Mn, Fe, Co, Cu and Sb concentrations were higher in the Suat Uğurlu Dam Lake on the Yeşilırmak River which is moderately polluted. According to sediment contamination indices, there was low contamination in the sediments of all dam lakes. Similarly, the assessment of ecological risk posed by TEs indicated low eclogical risk in the dam lakes. Sediment OM and pH were found to be important control factors affecting the distribution of TEs in the dam lakes sediments. Correlation and factor analyses suggested that all TEs in the sediments of dam lakes mainly originated from geogenic sources.

Evaluation of spatio-temporal variation of water quality and source identification of conducive parameters in Damodar River, India

The lower course of the Damodar River in West Bengal is one of the most polluted stretches in the Ganga River basin. There is a lack of research along the whole course of the Damodar, and parameter level analysis receives little attention. Eleven monitoring sites were chosen based on the potential sources of pollution for 6 years (2014-2019). Multivariate statistical techniques (factor analysis (FA), cluster analysis (CA), and discriminate analysis (DA)) evaluate the spatial and temporal variation of Damodar River water quality by considering 24 parameters. Factor analysis extracts the most influential seasonal parameters, and stepwise DA extracts ammonia, DO, potassium, temperature, total coliform, TFS, and turbidity, which are the most responsible parameters for seasonal variation of the water quality. CA classify sampling stations into three groups helping to identify the spatial variation of water quality. Ammonia, BOD, calcium, chloride, conductivity, DO, sodium, sulfate, temperature, Alkalinity, TDS, hardness, TSS, and turbidity are the most influential variables for spatial variation extracted through stepwise DA. Monsoon season shows a higher pollution level due to the contribution from both point and non-point sources. Due to high-density urban areas and large-scale industries, the middle course is more polluted. The Canadian Council of Ministers of the Environment (CCME) water quality index (WQI) accesses the water quality in temporal and spatial scales. The resultant water quality pattern is matched with the derived result from multivariate analysis. Poor water quality is regular at all sample sites in all seasons.

Ganga river water quality assessment using combined approaches: physico-chemical parameters and cyanobacterial toxicity detection with special reference to microcystins and molecular characterization of microcystin synthetase (mcy) genes carrying cyanobacteria

Water quality assessment relies mostly on physico-chemical-based characterization; however, eutrophication and climate change advocate the abundance of toxic microcystins (MCs) producing cyanobacteria as emerging bio-indicator. In the present study, a spatial-temporal analysis was carried out at ten sampling sites of Prayagraj and Varanasi during June 2017 and March 2018 to determine the Ganga River water quality using physico-chemical parameters, cyanobacteria diversity, detection of MCs producing strains and MC-LR equivalence. Coliform bacteria, COD, NO₃-N, and phosphate are the significant contaminated parameters favoring the growth of putative MCs producing cyanobacteria. National Sanitation Foundation WQI (NSFWQI) indicates water quality, either bad or medium category at sampling points. The morphological analysis confirms the occurrence of diverse cyanobacterial genera such as Microcystis, Anabaena, Oscillatoria, and Phormidium. PCR amplification affirmed the presence of toxic microcystin (mcy) genes in uncultured cyanobacteria at all the sampling sites. The concentration of MC-LR equivalence in water samples by protein phosphatase 1 inhibition assay (PPIA) and high-performance liquid chromatography (HPLC) methods was observed in the range of 23.4-172 ng/L and 13.2-97.5 ng/L respectively which is lower than the harmful exposure limit by World Health Organization (WHO). Ganga isolate 1 was identified as Microcystis based on partial 16S rDNA sequence and its toxicity was confirmed due to presence of mcy genes and MCs production potential. These findings suggest the presence of MCs producers as new emerging parameter to monitor water quality index and identification up to species level will be valuable for restoration strategies of river Ganga.

Surface hydrochemical dynamic in an artificial lake with anthropic impact: La Purísima reservoir, Central Mexico

In the present study, the hydrochemical dynamic and the water quality of La Purísima reservoir, Central Mexico, have been determined. The reservoir presents total dissolved solids (TDSs) between 146 and 328 mg L^-1 and water quality neutral to slightly alkaline (pH 7.0 to 8.7) during the dry season, whereas it becomes clearly alkaline (pH 8.1-9.9) in the rainy-warm season. Through its main tributaries, La Purísima reservoir has been receiving water affected by anthropic activities, such as mining, urbanization, and agriculture. La Purísima reservoir indicates water quality suitable for irrigation and aquatic lives, but unsuitable for drinking purposes. A geochemical evolution from the riverine to the lacustrine zone is evidenced by the complexation of several free ions: the higher saturation indexes; the lower toxic metal concentrations; and the lower trophic status, which ameliorate the water quality in the lacustrine zone. Trace elements co-precipitate and are adsorbed onto bottom sediments. During summer, high evaporation rates and atmospheric precipitation are found to decline the water quality. Cluster analyses reflect the geo-setting and different pollution levels: urban impact from the north coast, and agricultural activities from the east coast. The sensitivity of the lake to geochemical behavior can be used to understand the complex dissolved geochemical dynamics in a lake and the potential effects from long-term anthropic impact variability. The information about water quality of La Purísima reservoir may be useful to preserve the ecosystem and its biodiversity.

Assessment of the potentially toxic element contamination in water of Şehriban Stream (Black Sea Region, Turkey) by using statistical and ecological indicators

In the present study, the spatial-temporal variations of iron, lead, copper, cadmium, mercury, nickel, and zinc accumulations in the water of Şehriban Stream (northern Turkey) were investigated. Water Quality Index (WQI), Heavy Metal Evaluation Index (HEI), Pearson Correlation Index (PCI), and Factor Analysis (FA) were used in analyzing the water quality. Sampling was performed in 12 stations on monthly basis between February 2019 and January 2020 (a hydrological year). The data showed that the Şehriban Stream had significantly high water quality characteristics and the investigated toxicants were not found as dangerous for health. Although there was a slight decrease in the water quality from upstream to downstream, the stream was found to have 1st class water quality in general. As a result of WQI and HEI, although it was determined that the water quality decreased slightly in autumn, the stream was found to be "A Grade - Excellent (<50)" and "Low Contamination (<10)," respectively. As a result of PCI, strong positive correlations were found between almost all the toxicants investigated here (p < 0.01). As a result of FA, 2 factors ("Agriculture - Forestry" and "Rock Structure") explained 86% of the total variance.

Evaluation of groundwater quality in central Saudi Arabia using hydrogeochemical characteristics and pollution indices

The groundwater quality and heavy metal (HM) contamination were evaluated in palm farms, central Saudi Arabia, using pollution indices, irrigation quality parameters, and multivariate statistical analyses. Thirty groundwater samples were collected in October 2020 for major anions, cations, and HMs analyses and interpretation. The results showed that the average concentrations of total dissolved solids (TDS), Ca⁺, Na⁺, K⁺, Cl^-, SO₄^2-, and F^- were greater than the permissible limits of the WHO standards for drinking water. The groundwater facies types were Ca-Na-SO₄-Cl (23 samples), Ca-Cl-SO₄, (4 samples), and Ca-SO₄-Cl type (3 samples). The groundwater quality index indicated that 15 groundwater samples were of good quality and 15 were of poor quality, whereas the metal index and heavy metal pollution index indicated that all samples were categorized as slightly affected and with low pollution, respectively. The variation is attributed to the increasing average concentrations of some ions and decreasing HMs. The dissolution/precipitation of silicates, gypsum, and carbonates and soil leaching were the natural factors affecting groundwater chemistry, whereas higher PO₄^3-, NO₃^-, F^-, Pb, and Zn values in some samples may be attributed to human activities from the extensive use of fertilizers and pesticides on the investigated farms.

Integration of Water Quality Indices and Multivariate Modeling for Assessing Surface Water Quality in Qaroun Lake, Egypt

Water quality has deteriorated in recent years as a result of rising population and unplanned development, impacting ecosystem health. The water quality parameters of Qaroun Lake are contaminated to varying degrees, particularly for aquatic life consumption. For that, the objective of this work is to improve the assessments of surface water quality and to determine the different geo-environmental parameters affecting the lake environmental system in Qaroun Lake utilizing the weighted arithmetic water quality index (WAWQI) and four pollution indices (heavy metal pollution index (HPI), metal index (MI), contamination index (Cd), and pollution index (PI), that are enhanced by multivariate analyses as cluster analysis (CA), principal component analysis (PCA), and support vector machine regression (SVMR). Surface water samples were collected at 16 different locations from the lake during years 2018 and 2019. Thirteen physiochemical parameters were measured and used to calculate water quality indices (WQIs). The WQIs of Qaroun Lake such WAWQI, HPI, MI, Cd, PI revealed a different degree of contamination, with respect to aquatic life utilization. The WQIs result revealed that surface water in the lake is unsuitable, high polluted, and seriously affected by pollution for an aquatic environment. The PI findings revealed that surface water samples of Qaroun Lake were significantly impacted by Al, moderately affected by Cd and Cu, and while slightly affected by Zn due to uncontrolled releases of domestic and industrial wastewater. Furthermore, increasing salinity accelerates the deterioration of the lake aquatic environment. Therefore, sewage and drainage wastewater should be treated before discharging into the lake. The SVMR models based on physiochemical parameters presented the highest performance as an alternative method to predict the WQIs. For example, the calibration (Val.) and the validation (Val.) models performed best in assessing the WQIs with R2 (0.99) and with R2 (0.97–0.99), respectively. Finally, a combination of WQIs, CA, PCA, and SVMR approaches could be employed to assess surface water quality in Qaroun Lake.

Assessment of Spatial and Vertical Variability of Water Quality: Case Study of a Polymictic Polish Lake

UE regulations focus on methods of water quality monitoring and their use in rational management practices. This study investigated horizontal and vertical variations of electrical conductivity (EC), pH, dissolved oxygen (DO), and chlorophyll a (Chl-a) in a shallow polymictic lake. Monitoring of short-term variability of physical and chemical lake water parameters is a critical component in lake management, as it influences aquatic life. Based on the field research, maps of spatial distribution of the parameters were drawn. Using two methods: (1) a classical approach to water column measurements, from the top to the bottom (TB), in which the reference point is always a surface layer (SL), and (2) a newly introduced method of lake water quality monitoring based on a nearest neighbor (NN) approach; a comparison of higher and lower layers of the water column. By subtracting partial maps of spatial variability for different depths, final raster images were obtained. The NN method is rather absent in the limnology literature worldwide. Vertical and horizontal variability of the tested parameters in the polymictic, shallow Lake Bikcze (Poland) was presented in the results. In the presented paper, the commonly used TB method emphasized the role of the surface layer in shaping the variability of physicochemical parameters of lake waters. It shows a general trend of parameters’ changes from the top, to the bottom. The newly presented NN method, which has a major advantage in its simplicity and objectivity, emphasized structural differentiation within the range of variability. The nearest neighbor method was more accurate in showing the actual structure of fluctuation of parameters with higher fluctuation in the water column. Its advantage is a detailed recognition of the vertical variability of selected parameters in the water column. The method may be used regardless of the lake depth, its location in climatic zone, and/or region.

Surface water quality management for drinking use in El-Beheira Governorate, Egypt

This research was initiated to assess and manage water quality status of fourteen surface drinking water intakes in El-Beheira Governorate, Egypt. The study was conducted on four main branches of water resources in the governorate. Three water quality indices (WQIs) and two multivariate statistical techniques were applied, based on the Egyptian guidelines for the Nile River. Water quality records were collected for two successive years, 2014 and 2015, and were analyzed by descriptive statistics. The results revealed the critical water quality status of the four branches at the fourteen intakes. The multivariate statistical techniques returned the critical water quality conditions to the agricultural drainage and the domestic wastewater discharges. In addition, a new software application was developed to manage WQIs calculation. An urgent water quality monitoring and assessment system should be initiated for the drinking water resources all over Egypt, based on the developed water quality assessment techniques of this study. PRACTITIONER POINTS: Three different WQIs and two different statistics tools were applied. Critical water quality status for the investigated surface drinking water intakes was reported. Agricultural drainage then domestic effluents are the main pollution sources. A new software application was developed to calculate WQIs to support decision makers.

Assessment of surface and groundwater quality for irrigation purposes in the Danube-Tisa-Danube hydrosystem area (Serbia)

The study evaluates irrigation water quality in the Danube-Tisa-Danube hydrosystem area (Vojvodina, northern Serbia). The area is dominantly a plain with about 75% arable land, suitable for agricultural production and irrigation. Use of water of inadequate quality can have long-term effects on irrigated land and affect the yield of cultivated crops. The analyses included data from 40 surface water and 23 groundwater quality monitoring locations, observed during the period 2013-2018. The average annual values of the concentrations of major cations and anions and of electrical conductivity in surface and groundwater were comparatively analyzed. These values were statistically significantly higher (by p < 0.05) in groundwater bodies with most of the analyzed parameters. Hydrochemical classification of water types shows that 95% of surface and 87% of groundwater locations belong to the Ca·Mg-HCO₃ water type. Water suitability for irrigation was assessed using specific parameters and indices (sodium adsorption ratio, Na%, residual sodium carbonate, magnesium hazard, permeability index, and Kelly's index). The results showed that surface and groundwater resources are generally of good quality and suitable for irrigation, with sporadic deviations at several locations. The principal component analysis (PCA) was used to identify the most important variables affecting the chemical composition of the analyzed waters and group the monitoring locations by their chemical characteristics. The spatial variation of the analyzed water quality indices was shown on thematic maps.

Evaluation of Groundwater Using an Integrated Approach of Entropy Weight and Stochastic Simulation: A Case Study in East Region of Beijing

Groundwater is an important source of water in Beijing. Hydrochemical composition and water quality are the key factors to determine the availability of groundwater. Therefore, an improved integrated weight water quality index approach (IWQI) combining the entropy weight method and the stochastic simulation method is proposed. Through systematic investigation of groundwater chemical composition in different periods, using a hydrogeochemical diagram, multivariate statistics and spatial interpolation analysis, the spatial evolution characteristics and genetic mechanism of groundwater chemistry are discussed. The results show that the groundwater in the study area is weakly alkaline and low mineralized water. The south part of the study area showed higher concentrations of total dissolved solids, total hardness and NO3--N in the dry season and wet season, and the main hydrochemical types are HCO3--Ca and HCO3--Ca-Mg. The natural source mechanism of the groundwater chemical components in Chaoyang District includes rock weathering, dissolution and cation exchange, while the human-made sources are mainly residents and industrial activities. Improved IWQI evaluation results indicate that water quality decreases from southwest to northeast along groundwater flow path. The water quality index (WQI) method cannot reflect the trend of groundwater. Sensitivity analysis indicated that the improved IWQI method could describe the overall water quality reliably, accurately and stably.

Spatio-temporal variations in physicochemical water quality parameters of Lake Bunyonyi, Southwestern Uganda

The current study was carried out to examine the spatial and temporal variations of physicochemical water quality parameters of Lake Bunyonyi. The observations were made on the surface water of Lake Bunyonyi for 1 year to determine the water quality. The basic 12 variables used to determine the quality of water were measured monthly at nine stations. Water temperature, dissolved oxygen (DO), turbidity, electric conductivity (EC), pH and Secchi depth (SD) were measured in the field, while parameters like total nitrogen (TN), total phosphorus (TP), nitrite-nitrogen (NO2-N), nitrate-nitrogen (NO3-N), soluble reactive phosphorus (SRP) were determined following APHA 2017 standard guidelines for physicochemical analysis. Taking into account standard guidelines for drinking water by the Uganda National Bureau of Standards (UNBS) and the World Health Organization (WHO), the water quality index (WQI) was used to determine the water quality. Temperature, DO, pH, turbidity and EC did not differ significantly among the study stations (p > 0.05) but showed significant temporal variations among the study months (p < 0.05). Likewise, TN, TP, NO2-N, NO3-N and SRP did not differ significantly among the study stations (p > 0.05) but showed significant temporal variations among the study months (p < 0.05). The WQI values ranged from 28.36 to 49 across and from 28.2 to 56.2 between study months with an overall mean value of 36.9. The measured water quality variables did not exceed the UNBS and WHO standards for drinking water in all months and at all stations. According to these values, the water quality of Lake Bunyonyi generally belongs to the ‘good’ class in terms of drinking water quality based on the WQI classification. The study findings are fundamentally important for policy makers in setting guidelines for effective lake management.

Groundwater pollution index (GPI) and GIS-based appraisal of groundwater quality for drinking and irrigation in coastal aquifers of Tiruchendur, South India

We assessed groundwater pollution index (GPI) and groundwater quality of coastal aquifers from Tiruchendur in South India for drinking and irrigation by evaluating the physico-chemical parameters of 35 samples of mainly Na-Cl type in an area of 470 km² with respect to the World Health Organization (WHO) standard as well as by estimating different indices such as total hardness (TH), sodium percentage (Na%), magnesium ratio (MR), Kelley's ratio index (KR), potential salinity (PS), Langelier saturation index (LSI), residual sodium carbonate (RSC), sodium adsorption rate (SAR), permeability index (PI), and the irrigation water quality index (IWQI). Minimal influence of aquifer lithology and the dominant influence of evaporation on groundwater chemistry reflected the semi-arid climate of the study area. Electrical conductivity (EC) of about 89% of the samples across 418 km² exceeded the permissible limit and Ca values of 74% of samples, however, remained within the allowable limit for drinking. More chloride was caused by influx of seawater and salt leaching and higher K was due to excessive fertilizer usage for agriculture. The spatial distribution map created using inverse distance weighting (IDW) method shows that the suitable groundwater is present close to the river basin. GPI values between 0.40 and 4.7, with an average of 1.5, classify insignificant pollution in 43% of the study region and the groundwater suitable for drinking purposes. In addition, 17% of the groundwater samples are also marginally suitable for drinking. The irrigation water quality indices provided contradictory assessments. Indices of TH, Na%, MR, PS, and LSI suggested 32-95% of the samples as unsuitable for irrigation, whereas the indices of RSC, SAR, and PI grouped 72-100% samples as permissible for irrigation. The IWQI map, however, indicated that the groundwater from more than half of the study area are not apt for irrigation and the groundwater of about one-third of the area could only be applied to salt-resistant plants.

A multivariate statistical approach for the evaluation of spatial and temporal dynamics of surface water quality from the small reservoir located in the drought-prone area of South-West India: a case study of Tiru reservoir (India)

With the use of different multivariate statistical analysis methods, spatio-temporal fluctuations in the water parameters of Tiru reservoir located at the Marathwada drought-prone area of Maharashtra, India, have been analysed and reported in this case study. Tiru reservoir, situated on the tributary of the Godavari River, was regularly monitored at five different sites from August 2017 to January 2019 for the estimation of 20 water quality parameters. Various multivariate methods such as pattern reorganisation using cluster analysis (CA), factor analysis/principal component analysis (FA/PCA), and discriminant analysis (DA) were used for handling complex datasets. CA extracted three different clusters from five sampling sites with similar water quality characteristics. FA/PCA extracted thirteen factors (65% of 20 measured) required to explain 74% of the data variability and identified the factors accountable for variation in water quality and also evaluated the prevalence of each cluster on the overall dissimilarity at five different sampling sites. Discriminant analysis extracted a total of 16 parameters with 97.7% right assignations. Varifactors (VFs) acquired by factor analysis recommended that the water quality parameters accounted for variation were linked to two groups. The first group included water quality parameters like T, DO, SDD, turbidity, TDS, PA, and MA, whereas the second group covered most of the nutrients Cl-, silicates, PP, TP, NO3-N, NO2-N, and NH3-N; hardness; and CHL-a and mainly entered the reservoir during surface runoff from agriculture fields and the surrounding area containing domestic as well as animal waste. Thus, the present work showed the efficiency of multivariate methods for the assessment of spatial as well as a temporal variation in the water quality of a small reservoir.

Using Remote Sensing and Multivariate Statistics in Analyzing the Relationship between Land Use Pattern and Water Quality in Tien Giang Province, Vietnam

This study was carried out to understand how land use patterns influence surface water quality in Tien Giang Province using remote sensing and statistical approaches. Surface water quality data were collected at 34 locations with the frequency of four times (March, June, September, and November) in 2019. Water quality parameters were used in the analysis, including pH, temperature, electrical conductivity (EC), total suspended solids (TSS), dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), ammonium (N-NH4+), nitrite (N-NO2−), nitrate (N-NO3−), sulfate (SO42−), orthophosphate (P-PO43−), chloride (Cl−), total nitrogen (TN), total phosphorus (TP), and coliform. The relationship between land use patterns and water quality was analyzed using geographic information techniques (GIS), remote sensing (RS), statistical approaches (cluster analysis (CA), principal component analysis (PCA), and Krustal–Wallis), and weighted entropy. The results showed water quality was impaired by total suspended solids, nutrients (N-NH4+, N-NO2−, P-PO43−), organic matters (BOD, COD), and ions (Cl− and SO42−). Kruskal–Wallis analysis results showed that all water quality parameters in the water bodies in Tien Giang Province were seasonally fluctuated, except for BOD and TN. The highest levels of water pollutants were found mostly in the dry season (March and June). The majority of the land in the study area was used for rice cultivation (40.64%) and residential (27.51%). Water quality in the study area was classified into nine groups corresponding to five combined land use patterns comprising residential–aquaculture, residential–rice cultivation, residential–perennials, residential–rice–perennial, and residential–rice–perennial crops–aquacultural. The concentrations of the water pollutants (TSS, DO, BOD, COD, N-NH4+, N-NO2−, Cl−, and coliform) in the locations with aquaculture land use patterns (Clusters 1 and 2) were significantly larger than those of the remaining land use patterns. PCA analysis presented that most of the current water quality monitoring parameters had a great impact on water quality in the water bodies. The entropy weight showed that TSS, N-NO2−, and coliform are the most important water quality parameters due to residential–aquaculture and residential–rice cultivation; EC, DO, N-NH4+, N-NO2−, Cl−, and coliform were the significant variables for the land use type of residential–perennial crops; N-NO2−, P-PO43−, and coliform for the land use pattern of residential–rice cultivation–perennial crops) and N-NH4+, N-NO2−, Cl−, and coliform for the land use pattern of residential–rice cultivation–perennial crops–aquaculture. The current findings showed that that surface water quality has been influenced by the complex land use patterns in which residential and rice cultivation may have major roles in causing water impairment. The results of the water quality assessment and the variation in water properties of the land use patterns found in this study provide scientific evidence for future water quality management.

Comprehensive health evaluation of an urban wetland using quality indices and decision trees

In a world where pristine water is becoming scarcer, the need to reuse water becomes imperative. In this context explaining the water quality, purpose fitness and the parameters or conditions of the water body to adjust so as to improve its quality, are of great relevance. The goal of the present study was the use of water, riverine, and biodiversity quality indices to assess the condition of the studied urban wetland, since no single index can provide a complete health assessment of a water body. Decision trees were also used to elucidate the best water parameters to mend in order to recover the overall health of the urban wetland. The decision trees identified relevant physicochemical parameters as well as their approximate concentration at which a healthy water environment can be sustained for zooplankton and proved to be a powerful and simple alternative to customary approaches. Suspended particles and phosphates proved to be important parameters with concentrations approximately lower than 88 mg L^-1 and 11 mg L^-1, respectively, for a good biodiversity index of zooplankton. Ammonia, total coliforms, BOD, nitrates, and sodium were the main parameters that affected the water quality index. The vegetation coverage and its structure were the driving factors in the riverine quality index of the wetland.

An integrated approach for assessing surface water quality: Case of Beni Haroun dam (Northeast Algeria)

In this paper, we use an integrated approach to carry out a comprehensive evaluation of water quality in the Beni Haroun (BH) dam, the largest surface water resource in Algeria. Several techniques have been employed under the same framework, including the Canadian Council Ministers Environment Water Quality Index (CCME-WQI), principal component analysis and factor analysis (PCA/FA), the K-means clustering, and the ordinary least square (OLS) analysis. A data set of 22 physicochemical parameters has been collected, over a period of 11 years, from three sampling stations: Ain Smara (ST1) and Menia (ST2), both located upstream of "Wadi Rhumel," and BH dam station (ST3), located at the dam site. The PCA/FA enables the identification of seven key factors that influence significantly BH dam water quality. The average values of CCME indices at the BH dam were 17, 40, 42, and 32 for drinking, irrigation, industry, and aquatic life purposes, respectively, which indicate poor water quality, according to the CCME categorization scheme. Besides, the K-means algorithm has been proven to be a very useful machine learning tool to detect that the major source of BH dam pollution is "Wadi Rhumel." Finally, OLS analysis, along with the Mann-Kendall test, highlighted the positive trend of BH dam's water quality.