Assessment of water quality of polluted lake using multivariate statistical techniques: a case study

Hydrogeochemical assessment of aquifer salinization in north-eastern Morocco's Gueroaou coastal plain using statistical methods

The Guerouaou aquifer investigation spanning 280 km2 in Ain Zohra yields promising outcomes, instilling optimism for regional water quality. These analyses were applied to 45 sampling instances from 43 wells, enabling a comprehensive water quality assessment. Groundwater conductivity ranged from medium to high, peaking at 18360 ms/cm2. The conductivity reveals insights about the groundwater's mineralization. Key physiochemical parameters fell within desirable thresholds, bolstering the positive perspective. HCO3- levels spanned 82-420 mg/L, while chloride content ranged from 38 to 5316 mg/L, benefiting water quality. NO3- ions, vital for gauging pollution, ranged from 0 to 260 mg/L, indicating favorable results. Cation concentrations exhibited encouraging variations: Ca2+- 24 to 647 mg/L, Mg2+- 12 to 440 mg/L, Na+- 18 to 2722 mg/L, K+- 1.75 to 28.65 mg/L. These collectively favor water quality. Halite breakdown dominated mineralization, as evidenced by the prevalence of Na-Cl-Na-SO4 facies. Water resource management and local communities need effective management and mitigation strategies to prevent saltwater intrusion.

Evaluation of spatial and temporal dynamics of seawater intrusion in coastal aquifers of southeast India: insights from hydrochemical facies analysis

This study aims to investigate and understand the temporal and spatial movement of seawater intrusion into the coastal aquifers. Groundwater salinity increase has affected the entire eastern part of the study area and is primarily influenced by direct and reverse ion exchange reactions associated with intrusion and freshwater influx phases, which alternate over monsoons. To gain insights into the spatiotemporal dynamics of the seawater intrusion process, hydrochemical facies analysis utilizing the HFE-Diagram was employed. Additionally, the study considered the major ionic changes during both the monsoons. The HFE-Diagram analysis of hydrochemical facies revealed distinctions in the behaviour of each coastal aquifer concerning seawater intrusion-induced salinization. In PRM 2020, the data shows that approximately 65% of the samples fall under the freshening phase, while the remaining 35% were categorized as intrusion phase. Within the freshening phase, seven different hydrochemical facies were identified, including Na-Cl, Na-MixCl, MixNa-MixCl, Na-MixHCO3/MixSO4, MixNa-MixSO4, Na-HCO3, and MixCa-HCO3. In contrast, the intrusion phase had four facies: MixCaMixHCO3, MixNa-Cl, Ca-Cl, and Na-Cl. Especially, the Na-Cl facies (f1) within the freshening phase attributed for the largest percentage, contributing 30% of the samples. In POM 2021, the distribution of samples shifted slightly, with approximately 72.5% belonging to the freshening phase and 27.5% to the intrusion phase. Within the freshening phase of POM 2021, five hydrochemical facies were identified: Na-Cl, Na-MixCl, Na-MixHCO3/MixSO4, MixNa-MixSO4, and Na-HCO3. The intrusion phase of POM 2021 had three facies: MixNa-Cl, Na-Cl, and MixCa-Cl. Similar to PRM 2020, the Na-Cl facies (f1) remained the most predominant in the freshening phase, comprising 30% of the samples. The relation between total dissolved solids (TDS) and various ionic ratios, such as HCO3-/Cl-, Na+/Cl-, Ca2+/Cl-, Mg2+/Cl-, K+/Cl-, and SO42-/Cl-, clearly demonstrates the presence of seawater influence within the coastal aquifers of the study area.

Geostatistical appraisal of water quality, contamination, source distribution of potentially toxic elements (PTEs) in the lower stretches of Subarnarekha River (Odisha), India, and health risk assessment by Monte Carlo simulation approach

In the present study, the status of water quality, environmental contamination in the lower stretch of Subarnarekha River with respect to potentially toxic elements (PTEs), its seasonal distribution, and ecotoxicological health impacts were investigated. For this purpose, a combination of indexing approaches and geospatial methods was used. The estimated water quality index (WQI) has shown that the river water falls under "moderate to very poor" category during the pre-monsoon and "moderate to poor" category in the post-monsoon season. The abundance of PTEs (Pb, Cu, Ni, Cd, Fe, and Cr) was on the higher side during the pre-monsoon in comparison with the post-monsoon season. The results of contamination index (Cd) and heavy metal evaluation index (HEI) explain that Subarnarekha River has low-to-moderate levels of contamination with PTEs in the majority of sampling sites. However, HPI indicated that the river water is moderate-to-highly contaminated with PTEs in both seasons. Principal component analysis (PCA) and cluster analysis (CA) reveal that anthropogenic sources are prime contributors to PTEs contamination in Subarnarekha River. The potential non-cancerous health concerns for child and adults due to Cr and Pb in some sampling stations along the river stretch have been observed. The carcinogenic risk (CR) has been established for Cr, Pb, and Cd in Subarnarekha River with Cr (> 10-4) as the most unsafe element. Monte Carlo simulation (MCS) indicates a high risk of cancer hazards due to Cr (values > 1E-04) in present as well as future for both child and adults.

Characterizing dissolved organic matter and bacterial community interactions in a river network under anthropogenic landcover

Anthropogenic landcover could rise nutrient concentrations and impact the characteristics and bioavailability of dissolved organic matter (DOM) in a river network. Exploring the interactions between DOM and microbials might be conducive to revealing biogeochemistry behaviors of organic matter. In this study, synchronous fluorescence spectra (SFS) with Gaussian band fitting and two-dimensional correlation spectroscopy (2D-COS) were employed to identify DOM fractions and reveal their interactions with bacterial communities. DOM was extracted from a river network under eco-agricultural rural (RUR), eco-residential urban (URB), eco-economical town (TOW), and eco-industrial park (IND) regions in Jiashan Plain of eastern China. The overlapping peaks observed in the SFS were successfully separated into four fractions using Gaussian band fitting, i.e., tyrosine-like fluorescence (TYLF), tryptophan-like fluorescence (TRLF), microbial humic-like fluorescence (MHLF), and fulvic-like fluorescence (FLF) materials. Across all four regions, TRLF (44.79% ± 7.74%) and TYLF (48.09% ± 8.85%) were the dominant components. Based on 2D-COS, variations of TYLF and TRLF were extremely larger than those of FLF in RUR-TOW. However, in URB-IND, the former exhibited lower variations compared to the latter. These suggested that FLF be likely derived continuously from lignin and other residue of terrestrial plant origin along the river network, and TYLF and TRLF be originated discontinuously from domestic wastewater in RUR-TOW. By high-throughput sequenced OTUs, the number of organisms in RUR-TOW could be higher than those in URB-IND, while genes associated with carbohydrate metabolism were lower in former than those in the latter. According to co-occurrence networks, microbes could promote the production of TYLF and TRLF in RUR-TOW. In contrast, microbial communities in URB-IND might contribute to decompose FLF. The obtained results could not only reveal interactions between DOM fractions and bacterial communities in the river network, but this methodology may be applied to other water bodies from different landscapes.

Fluvial responses towards the tannery effluent: Tracing the anthropogenic foot-prints

Tannery-effluent is one of the top-ranked hazardous waste which is generally discharged into the river. To study the fluvial response toward the tannery-effluents and to trace anthropogenic foot-prints in the fluvial-system, a suite of systematically collected sediment and water samples were analyzed for radioactive (226Ra, 232Th, and 40K) and non-radioactive elements (Al, Ti, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Cd, Sb, Hg, and Pb). Neutron activation analysis and atomic absorption spectroscopy were used for elemental analysis, whereas HPGe-gamma-detector was used for measuring the primordial-radionuclides. Ranges of Cr-abundances in sediment and water were 63-4373 μg.g-1 and 15.6-52.2 μg.L-1, respectively which were ∼4-14 times higher than the geological background. Radioactivity concentrations of 226Ra, 232Th, and 40K ranged from 17.7-48.5, 36.1-81.6, and 687-1041 Bq.kg-1, respectively which were significantly depleted in effluent discharge point. Hence, primordial-radionuclides were used as natural tracers for tracing anthropogenic foot-prints which were explained in terms of dilution effect, redox environment and differential geo-environmental events/characteristics. From statistical-approaches and geochemical reasoning, elemental sources and responses in fluvial system were explored. Surprisingly, ecological & radiological risks were reduced while sediment quality guideline-based ecotoxicity & water-mediated health risks were increased by the incorporation of tannery effluents. This study describes the sedimentary response toward the received tannery effluents which is particularly explored by the primordial radionuclides.

Combined Multivariate Statistical Techniques and Water Quality Index (WQI) to Evaluate Spatial Variation in Water Quality

In present study, Water Quality Index (WQI) has been assessed of the Rawal Lake which is a major source of drinking water for people in the Federal Capital, Islamabad, and its adjacent city Rawalpindi in Pakistan. For this, the principal component analysis (PCA) and WQI were applied as an integrated approach to quantitatively explore difference based on spatial variation in 11 water quality parameters of the five major feeding tributaries of the Rawal Lake, Pakistan. The results of temperature in water, total dissolved solids, pH, electrical conductivity, chlorides and sulfates were well within the allowable World Health Organisation's (WHO) limits. However, the heavy metals like cadmium and lead were above permissible limits by the WHO in tributaries of Bari Imam and Rumli. Moreover, this has been proven by the Pearson correlation which suggested strong positive correlation (0.910*) between lead and cadmium. The results of present study were subjected to statistical analysis, i.e., PCA which gave three major factors contributing 96.5% of the total variance. For factor 1, pH, TDS, alkalinity, chlorides, sulfates and zinc have highest factor loading values (>0.60) and presented that these parameters were among the most significant parameters of first factor. As per the WQI results, the water was categorised in two major classes indicating that water of Bari Imam and Rumli is highly contaminated with heavy metals and totally unsuitable for drinking purposes. Based on the results of the present study, it is suggested to make heavy metals consideration as an integrated component in future planning for maintaining water quality of the Rawal Lake and its tributaries.

Spatio-temporal evolution of eutrophication and water quality in the Turawa dam reservoir, Poland

The objectives of the article are: to assess spatio-temporal evolution of eutrophication and water quality of the Turawa dam reservoir, located in south-western Poland on the Mała Panew River; to identify location and relationship between potential sources of physicochemical pollution related to the progressing process of eutrophication; and to determine trophic status and water quality indices of the selected research object. The analysis (Mann-Whitney U test, PCA, HCA, Spearman correlation matrix) showed a high susceptibility of the reservoir to eutrophication processes, especially due to the influence of dangerous loads of compounds emerging from areas with high tourist intensity and pollutants flowing from the Mała Panew River. The parameters deteriorating the ecological status were TP, DO, BOD₅, and COD. Considering the cumulative results of water quality indices for the period 1998-2020, the average water quality was in classes II or III. A noticeable deterioration appeared in water quality for the years 2016-2020, which proves the progressing eutrophication in the Turawa reservoir. In 1998-2020, the reservoir was classified as eutrophic or mesoeutrophic based on the calculated three trophic status indices. This article would help in developing a strategy for dealing with water blooms, a reliable system for monitoring pressures causing eutrophication, and optimal technologies for the reconstruction of multifunctional reservoirs.

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.

Changes in the water environment and its major driving factors in Poyang Lake from 2016 to 2019, China

The hydrological exchange process between Poyang Lake (PYL), the largest freshwater lake in China, and the Yangtze River leads to drastic changes in water area (WA) and water level (WL), as well as apparent fluctuations in lake nutrients, algal organisms, and trophic level index. This study investigated the current status of the PYL water environment and the influence of hydrological changes on the nutrient status of the floodplain of the lake. Based on monthly measured data from six hydrological stations from 2016 to 2019, it was hypothesized that WA and WL were the key regulators of the spatial and temporal distribution patterns of lake water quality and algal growth, including water temperature, water clarity (Secchi depth [SD]), and nutrient levels. The results revealed that (1) the spatial and temporal distribution characteristics of major nutrients in PYL were influenced by dynamic changes in hydrological characteristics (SD, total nitrogen [TN], and total phosphorus [TP]); (2) the eutrophication level in PYL has been in a steady state in recent years, while the central area has been more prone to the risk of eutrophication (e.g., the peak eutrophication index during Period 1 [January to April] in the water near the Duchang station reached 70); and (3) there were significant correlations among environmental variables, nutrients, and algal organisms, with different spatial and temporal distribution characteristics (p < 0.05), while the changes in WA and WL considerably influenced the water environment in the PYL.

Using Canadian Water Quality Index method to evaluate the spatio-variation of water quality and the impacts of quality parameters: a case study of Amasya's surface water (Northern Turkey)

In this study, the spatial variation of water quality in Yeşilırmak River passing through Amasya was investigated using the Canadian Water Quality Index (CWQI). For this aim, the measured 15 parameters in 3-month periods between the years 2008 and 2015 were used at 11 sample points from the Yeşilırmak River and its tributaries. The calculated CWQI scores using parameters of pH, Dissolved Oxygen (DO), Chemical Oxygen Demand (COD), ammonia, ammonium, nitrite, nitrate, phosphate, iron, copper, zinc, potassium, sulfate, sulfite and chlorine range from 33 to 64. These scores indicate that the surface waters in the studied area are poor to marginal in quality. The effect of each parameter on the CWQI scores by excluding each parameter, one by one, considering the water quality of the Yeşilırmak River was investigated using the Hierarchical Cluster Analysis (HCA) method. It was determined that the presence and/or absence of the parameters, which caused an increase or decrease in CWQI scores, were ammonia, phosphate, COD, sulfide, iron, ammonium, nitrite, DO. On the other hand, the parameters having positive effects on CWQI are nitrate, chlorine and potassium. The HCA statistical analysis method is suitable for interpreting complex water quality datasets and understanding time/location dependent changes in water quality. HCA can be used effectively to group parameters in river water quality monitoring programs.

Water quality assessment of Lake Burullus, Egypt, utilizing statistical and GIS modeling as environmental hydrology applications

GIS is a very powerful tool for analyzing huge amount of data and connecting them with the geography; moreover, recently, there is great advancement in the field. The main objective of this study is to assess the water quality (WQ) and trophic status (TS) conditions of Lake Burullus, Egypt, using statistical modeling (PCA/FA and CA), WQ index (L-WQI), and trophic status index (Carlson TSI and TRIX) approaches, in addition to using GIS tools for building models able to automatically calculate the various indices and producing color coded maps for the lake. The results indicated that PCA/FA grouped the twenty-four WQ parameters into nine principal components explaining 72.6% of the total variance, domestic, and agriculture pollution were dominant. CA divided the twelve sampling stations into most and least polluted groups. The lake WQ was classified as a "Very Poor," according to L-WQI. Moreover, the results of the Carlson TSI and TRIX indices were coincided and classified the eutrophication levels in the lake as "Hyper-Eutrophic" and "Elevated Trophic," respectively. Based on the results of this study, Lake Burullus needs urgent plans for recovering its WQ. Pre-treatment for its drains' effluents and implementing of a periodical WQ monitoring program are highly recommended.

Water quality analysis based on phytoplankton and metal indices: a case study in the Sauce Grande River Basin (Argentina)

The increasing landscape alterations due to anthropogenic activities is of global concern since it affects aquatic ecosystems, often resulting in compromise of the ecological integrity and the water quality. In this sense, the evaluation, monitoring, and prediction of the aquatic ecosystem quality becomes an important research subject. This study presents the first integrated water quality assessment of the Sauce Grande River Basin, in Argentina, based on the spatial distribution of the phytoplankton community, the physicochemical parameters, and the metal concentrations (Cd, Cu, Cr, Fe, Mn, Ni, Pb, and Zn) found in the particulate fraction. According to the trophic indices and the phytoplankton abundance, composition, and diversity, the water quality showed significant deterioration in the lower basin after the Sauce Grande lake. The trophic state index indicated that water was oligotrophic in over 75% of the sampling sites, increasing downstream, where two sites were characterized as mesotrophic, and one described as hypertrophic. The phytoplankton community was dominated by diatoms in zones with low anthropogenic impact and conductivity, whereas high densities of Euglenophyta, Chlorophyta, and Cyanobacteria were found in the middle-lower basin, associated with higher organic matter and eutrophication. The conductivity, turbidity, and most metal concentrations also increased towards the downstream area, even exceeding recommended levels for the metals Cu, Cr, Mn, and Pb in the middle and lower reaches of the basin (Cu: 3.5 µg L^-1; Cr: 2.4 µg L^-1; Pb: 1.2 µg L^-1; Mn 170 µg L^-1). This study generates a database for the water quality of the Sauce Grande River Basin and sets an example of how the water quality varies along a basin that crosses different topographic environments, land covers, and anthropogenic influences.

Hydrogeochemical characterization based water resources vulnerability assessment in India's first Ramsar site of Chilka lake

A limnological site is significantly characterized by rich biological, chemical, and physical properties of the environment and is also described as the epitome of a large aquatic ecosystem. During the last few decades, the Chilka lake Ramsar site has experienced substantial degradation of water quality with associated deterioration of aquatic biodiversity. Our study aims to quantify the VWRM of the Chilka lake Ramsar region using the most reliable MLAs, namely ANN and RF, with the help of seventeen hydro-chemical properties of lake water. The produced map is validated through six validating measures (ROC-AUC- 0.89, Sensitivity-0.90, Specificity-0.78, PPV-0.78, NPV-0.88, Taylor diagram (r)-0.94), which depict that ANN is the most reliable ML algorithm in assessing the VWRM of the concerned region followed by RF. The prepared map of our study revealed that the eastern part was remarkably high to very high vulnerable zone covered area with 22.41 % and 7.19 %, respectively.

Combination of water quality, pollution indices, and multivariate statistical techniques for evaluating the surface water quality variation in Can Tho City, Vietnam

This study assessed the surface water quality in Can Tho city, Vietnam, using a combination of water quality, pollution indices, and multivariate statistical methods. Surface water samples were collected at 38 locations with a frequency of 4 times in 2020 (March, June, September, and December) and at the time of high and low tides to analyze for 18 indicators. Results showed that surface water in Can Tho city was contaminated with organic matters and microorganisms. Parameters of pH, turbidity, total suspended solids (TSS), biochemical oxygen demand (BOD), chemical oxygen demand (COD), N-NH₄⁺, and N-NO₃^- are significantly increased with low tide. Comprehensive pollution index indicated mild to moderately polluted water in March, June, and September and moderately to severely polluted water in December. Organic pollution index revealed that surface water quality in all locations was polluted with organic matters during the study period especially in March and December. The water quality index also indicated that water quality in December was mostly classified as moderate and bad. The principal component analysis indicated that surface water quality could be affected by five main sources that explain 64.40% of the total variation. This significantly caused the fluctuation of pH, temperature, turbidity, TSS, DO, BOD, COD, N-NH₄⁺, P-PO₄^3-, Fe, and As, which should all be the focus for future monitoring. Surface water management in Can Tho city should also emphasize on the wastewater from urbanization and agriculture, which has been recognized by the analysis to have highest contribution to organic, nutrient, and microbial pollutants in the water bodies.

Hydrochemical characterization of groundwater quality using chemometric analysis and water quality indices in the foothills of Himalayas

Groundwater pollution of the watershed is mainly influenced by the multifaceted interactions of natural and anthropogenic process. To analyse the spatial-temporal variation and pollution source identification and apportionment, the dataset was subjected to a globally acknowledged coherent technique using water quality indices and chemometric techniques (principal component analysis (PCA) and cluster analysis. The bulk of the samples tested were below the BIS's permissible levels. Groundwater samples from the pre- and post-monsoon seasons mostly contained the anions HCO- 3 > Cl- > SO2- 4 > NO- 3, while the primary cations were Ca2+ > Mg2+ > Na+ > K+. Groundwater was alkaline and hard at most of the sites. According to hydro-geochemical facies and relationships, Piper diagrams, and principal component analysis, weathering, dissolution, leaching, ion exchange, and evaporation were the key mechanisms influencing groundwater quality. The hydrochemical facies classified the groundwater samples into the Ca-Mg-HCO3 type. For all the sampling locations, PIG was determined to be 0.43, 0.52, 0.47, 0.48, 1.00, and 0.70; respectively. The majority of the test locations fell into the low to medium contamination zone, as determined by the groundwater pollution index (PIG) and contamination index. Three principal components, which together account for 93.8% of the total variance, were identified via PCA. The study's findings confirm the value of these statistical techniques in interpreting and understanding large datasets and offering reliable information to reduce the time and expense of programmes for monitoring and evaluating water quality.

Impacts of Land Use on Surface Water Quality Using Self-Organizing Map in Middle Region of the Yellow River Basin, China

The Yellow River is one of the most important water sources in China, and its surrounding land use affected by human activities is an important factor in water quality pollution. To understand the impact of land use types on water quality in the Sanmenxia section of the Yellow River, the water quality index (WQI) was used to evaluate the water quality. A self-organizing map (SOM) was used for clustering analysis of water quality indicators, and the relationship between surface water quality and land use types was further analyzed by redundancy analysis (RDA). The results showed that WQI values ranged from 82.60 to 507.27, and the highest value was the sampling site S3, whose water quality grade was "Likely not suitable for drinking", mainly polluted by agricultural non-point sources ammonia nitrogen pollution. SOM clustered the sampling sites into 4 groups according to the water quality indicators, the main influencing factors for different groups were analyzed and explored in more depth in relation to land use types, suggesting that surface water quality was significantly connected with the proportion of land use types at the watershed scale in the interpretation of water quality change. The negative impact of cropland on surface water quality was greater than that of other land use types, and vegetation showed a greater positive impact on surface water quality than other land uses. The results provide evidence for water environment conservation based on land use in the watershed.

Analysis of Surface Water Quality in Upstream Province of Vietnamese Mekong Delta Using Multivariate Statistics

The study employed different statistical approaches to assess surface water quality in the upstream region of the Vietnamese Mekong Delta. The dataset included seven parameters (i.e., temperature, pH, total suspended solids (TSS), five-day biological oxygen demand (BOD5), chemical oxygen demand (COD), ammonium nitrogen (NH4+-N) and coliform) at seventy-three locations. Cluster analysis (CA) and principal component analysis (PCA) were applied to analyze spatial variations in surface water quality and recognize the important parameters. The findings revealed that surface water quality was deteriorated by organic matters (high BOD5 and COD), nutrients and microorganisms. Particularly, urban areas were found to be more polluted than the other areas. The PCA results indicated that three potential water pollution sources, including industry, urban and tourism, could explain 87.03% of the total variance. Coliform was identified as the leading latent factor that controls surface water quality in the study area. CA grouped the sampling locations into 11 groups, in which the groups of the baseline monitoring sites and large rivers had better water quality. The results indicated a significant impact of anthropogenic activities (especially, urban and tourism practices) in surface water quality degradation. Moreover, CA suggested that the numbers of the sampling sites could be reduced from 73 to 58 locations, lowering 20.54% of the monitoring cost. Thus, the study recommends scrutinizing the current surface water quality monitoring system to be more economic and urgently implementing appropriate solutions to mitigate coliform pollution in the smaller water bodies.

Occurrence and distribution of antibiotic resistant bacteria and genes in the Fuhe urban river and its driving mechanism

Antibiotic resistance genes (ARGs) in urban rivers can affect human health via the food chain and human pathogenic bacteria diffusion. Sediment can be a sink for ARGs, causing second sources of ARG contamination through diffusion. Therefore, we evaluated the effects of total petroleum hydrocarbons (TPHs) and phytoplankton on the distribution of the ARGs in the sediment and water of Fuhe river in Baoding city, China. The ARGs and human pathogenic bacteria in urban river were analyzed, and the phytoplankton and bacterial abundance, TPH, and physicochemical parameters ranked using the partial least squares path modelling (PLS-PM) and aggregated boosted tree (ABT) analysis. The main ARGs in Fuhe river sediment were sulfonamide and tetracycline resistance genes, with sul2 exhibiting the highest level. The main human pathogenic bacteria in the pathogens pool were Clostridium, Bacillus and Burkholderiaceae, with Clostridium demonstrating a positive correlation with SulAfolP01. The PLS-PM analysis confirmed that, among the multiple drivers, water physicochemical factors, TPH, phytoplankton, and heavy metals positively and directly affected the ARG profiles in sediment while sediment heavy metals and bacterial communities did the similar effect. These factors (nutrient factors, heavy metals, and TPH) in water and sediment posed the opposite total effect on ARGs in the sediment, suggesting medium factors should have a conclusive effect on the distribution of ARGs in the sediment. The ABT analysis showed that dissolved oxygen (DO), total nitrogen (TN) and Chlorophyta were the most important factors affecting the ARGs distribution in the water, while TN affected the distribution of the genes in the sediment.

Potentially toxic elemental contamination in Wainivesi River, Fiji impacted by gold-mining activities using chemometric tools and SOM analysis

Potentially toxic element (PTE) contamination in Wainivesi River, Fiji triggered by gold-mining activities is a major public health concern deserving attention. However, chemometric approaches and pattern recognition of PTEs in surface water and sediment are yet hardly studied in Pacific Island countries like Fijian urban River. In this study, twenty-four sediment and eight water sampling sites from the Wainivesi River, Fiji were explored to evaluate the spatial pattern, eco-environmental pollution, and source apportionment of PTEs. This analysis was done using an integrated approach of self-organizing map (SOM), principle component analysis (PCA), hierarchical cluster analysis (HCA), and indexical approaches. The PTE average concentration is decreasing in the order of Fe > Pb > Zn > Ni > Cr > Cu > Mn > Co > Cd for water and Fe > Zn > Pb > Mn > Cr > Ni > Cu > Co > Cd for sediment, respectively. Outcomes of eco-environmental indices including contamination and enrichment factors, and geo-accumulation index differed spatially indicated that majority of the sediment sites were highly polluted by Zn, Cd, and Ni. Cd and Ni contents can cause both ecological and human health risks. According to PCA, both mixed sources (geogenic and anthropogenic such as mine wastes discharge and farming activities) of PTEs for water and sediment were identified in the study area. The SOM analysis identified three spatial patterns, e.g., Cr-Co-Zn-Mn, Fe-Cd, and Ni-Pb-Cu in water and Zn-Cd-Cu-Mn, Cr-Ni and Fe, Co-Pb in sediment. Spatial distribution of entropy water quality index (EWQI) values depicted that northern and northwestern areas possess "poor" to "extremely poor" quality water. The entropy weights indicated Zn, Cd, and Cu as the major pollutants in deteriorating the water quality. This finding provides a baseline database with eco-environmental and health risk measures for the Wainivesi river contamination.

Potentially toxic elemental contamination in Wainivesi River, Fiji impacted by gold-mining activities using chemometric tools and SOM analysis

Potentially toxic element (PTE) contamination in Wainivesi River, Fiji triggered by gold-mining activities is a major public health concern deserving attention. However, chemometric approaches and pattern recognition of PTEs in surface water and sediment are yet hardly studied in Pacific Island countries like Fijian urban River. In this study, twenty-four sediment and eight water sampling sites from the Wainivesi River, Fiji were explored to evaluate the spatial pattern, eco-environmental pollution, and source apportionment of PTEs. This analysis was done using an integrated approach of self-organizing map (SOM), principle component analysis (PCA), hierarchical cluster analysis (HCA), and indexical approaches. The PTE average concentration is decreasing in the order of Fe > Pb > Zn > Ni > Cr > Cu > Mn > Co > Cd for water and Fe > Zn > Pb > Mn > Cr > Ni > Cu > Co > Cd for sediment, respectively. Outcomes of eco-environmental indices including contamination and enrichment factors, and geo-accumulation index differed spatially indicated that majority of the sediment sites were highly polluted by Zn, Cd, and Ni. Cd and Ni contents can cause both ecological and human health risks. According to PCA, both mixed sources (geogenic and anthropogenic such as mine wastes discharge and farming activities) of PTEs for water and sediment were identified in the study area. The SOM analysis identified three spatial patterns, e.g., Cr-Co-Zn-Mn, Fe-Cd, and Ni-Pb-Cu in water and Zn-Cd-Cu-Mn, Cr-Ni and Fe, Co-Pb in sediment. Spatial distribution of entropy water quality index (EWQI) values depicted that northern and northwestern areas possess "poor" to "extremely poor" quality water. The entropy weights indicated Zn, Cd, and Cu as the major pollutants in deteriorating the water quality. This finding provides a baseline database with eco-environmental and health risk measures for the Wainivesi river contamination.

Physicochemical Characterization and Assessment of Magnitude of Pollution to Contribute to Water Sustainability

As in many countries worldwide, deterioration of quality of water in Morocco’s natural reserves continues, such that an inventory of qualities of these reserves has become necessary. Based on statistical analyses of the data collected by measuring nineteen physicochemical variables, and applying an index, the comprehensive pollution index, to those data, the quality of the waters of Lake Dayat Roumi, Morocco, were assessed. Waters of the lake are currently characterized by a salinity of 921.7 mg Cl−/L and 124.2 mg sulfates/L. The concentration of chloride exceeds the value indicated in the standard norms. This can affect the composition of the sediment, overlying water, and specific composition of biota in the lake. Status and trends of values of other parameters also indicate deterioration of water quality in this lake. Multivariate statistical analysis made it possible to differentiate four clusters of samples according to their physicochemical characteristics. These groups are due to inputs from three sources of materials: leaching of rocks from the watershed and plantations, discharge of domestic wastewater and runoff water. Samples taken from deeper parts of the lake indicate a depression of concentrations of dissolved oxygen during the hot season. The analysis results demonstrate the heterogeneous degradation of the water quality in the peripheral areas and deep parts of the lake, favored by the leaching of soils by rainwater, which, when sufficiently severe, can cause repeated mortalities of fishes. This situation requires regular water quality monitoring to develop a management plan for restoration of water quality in the lake to preserve valued ecological services.

Assessing the factors influencing water quality using environment water quality index and partial least squares structural equation model in the Ebinur Lake Watershed, Xinjiang, China

Surface water quality deterioration is commonly associated with environmental changes and human activities. Although some research has been carried out to evaluate the relationship between various influencing factors and water quality, there is still very little scientific understanding on how to accurately define the key factors of water quality deterioration. This study aims to quantify the impact of environmental factors and land use land cover (LULC) changes on water quality in the Ebinur Lake Watershed, Xinjiang, China. A total of 20 water parameters were used to calculate the Environment Water Quality Index (CWQI). Meanwhile, the partial least squares-structural equation model (PLS-SEM) was used to quantify the impact of eleven factors influencing water quality in the watershed. About 33.3% of the monitoring points that located mostly in the downstream region with dominant anthropogenic activities were detected as poor quality. There were no obvious temporal changes in water quality from 2016 to 2019. The PLS-SEM simulation shows that the latent variable "land use/cover types" (path coefficient =  - 0.600) and "Environmental factor" (path coefficient =  - 0.313) are two major factors affected water quality in the Ebinur Lake Watershed, with a strong explanatory power to water quality change (R² = 0.727). In the latent variable "Environmental factors", the "NDVI" and "night light brightness value" have a great influence on water quality, with the weights of 0.451 and 0.427, respectively. Correspondingly, the "farmland" and "forest land" within the latent variable of "Land use/cover type" have a considerable impact water quality, with the weights of 0.361 and - 0.340, respectively. In conclusion, the influence of anthropogenic activities on surface water quality of the Ebinur Lake Watershed is greater than that of environmental factors. Compared with the traditional multivariate statistical method, PLS-SEM provides a new insight for quantifying the complex relationship between different influencing factors and water quality.

Integrating water quality index, GIS and multivariate statistical techniques towards a better understanding of drinking water quality

Groundwater is considered as an imperative component of the accessible water assets across the world. Due to urbanization, industrialization and intensive farming practices, the groundwater resources have been exposed to large-scale depletion and quality degradation. The prime objective of this study was to evaluate the groundwater quality for drinking purposes in Mewat district of Haryana, India. For this purpose, twenty-five groundwater samples were collected from hand pumps and tube wells spread over the entire district. Samples were analyzed for pH, electrical conductivity (EC), total dissolved solids (TDS), total hardness (TH), turbidity, total alkalinity (TA), cations and anions in the laboratory using the standard methods. Two different water quality indices (weighted arithmetic water quality index and entropy weighted water quality index) were computed to characterize the groundwater quality of the study area. Ordinary Kriging technique was applied to generate spatial distribution map of the WQIs. Four semivariogram models, i.e. circular, spherical, exponential and Gaussian were used and found to be the best fit for analyzing the spatial variability in terms of weighted arithmetic index (GWQI) and entropy weighted water quality index (EWQI). Hierarchical cluster analysis (HCA), principal component analysis (PCA) and discriminant analysis (DA) were applied to provide additional scientific insights into the information content of the groundwater quality data available for this study. The interpretation of WQI analysis based on GWQI and EWQI reveals that 64% of the samples belong to the "poor" to "very poor" bracket. The result for the semivariogram modeling also shows that Gaussian model obtains the best fit for both EWQI and GWQI dataset. HCA classified 25 sampling locations into three main clusters of similar groundwater characteristics. DA validated these clusters and identified a total of three significant variables (pH, EC and Cl) by adopting stepwise method. The application of PCA resulted in three factors explaining 69.81% of the total variance. These factors reveal how processes like rock water interaction, urban waste discharge and mineral dissolution affect the groundwater quality.

Pollution Contribution Response in Governance and Potential Pollution Factors in Licun River

The development of the city results in deterioration of the water quality of the Licun River. As a result, years of governance have been conducted to improve its water quality. In order to clarify the response changes of water quality in the water governance, the governance process is divided into three stages (2000–2007, 2008–2016, 2017–2020) according to different priorities. Spearman’s rank correlation coefficient and the comprehensive pollution index are applied to analyze the variation of water quality response at various stages. In addition, the main pollution contributions with the governance changes were obtained. It is concluded that flood control and incomplete river pollution interception have a limited effect on water quality improvement, with NH3-N (ammonia nitrogen) and COD (chemical oxygen demand) being the main pollution contributions at the first stage. At the second stage, the point source control and sewage treatment facilities significantly improve water quality, and the main pollution contributions are NH3-N and TP (total phosphorus). At the third stage, sewage treatment facilities and supporting pipelines are improved, water sources are replenished, and the main pollution contribution is TN (total nitrogen). For further treatment, the factors affecting pollution are analyzed, including the contradiction of sewage system, point source pollution caused by pipe network problems, shortage of water resources, sludge pollution, and non-point source pollution.

Assessment of spatio-temporal variations of selected water quality parameters of Lake Ziway, Ethiopia using multivariate techniques

Excess agrochemicals input from agricultural activities and industrial effluent around Lake Ziway catchment can pose a serious threat on the lake ecosystem. Lake Ziway is a shallow freshwater lake found in the northern part of the Ethiopian Rift Valley. It is characterized as semi-arid to sub-humid type of climate. Expansions of the flower industry, widespread fisheries, intensive agricultural activities, fast population growth lead to deterioration of water quality and depletion of aquatic biota. The spatial and temporal variations of selected water quality parameters were evaluated using multivariate techniques. The data were collected from nine sampling stations during dry and wet seasonal basis for analysis of fifteen water quality parameters. The physicochemical parameters were measured in-situ with portable multimeter and nutrients were determined by following the standard procedures outlined in the American Public Health Association using UV/Visible spectrophotometer. Mean nutrient concentrations showed increasing trend in all seasons. These sites were also characterized by high electrical conductivity and total dissolved solid (TDS). All the nine sampling sites were categorized into three pollution levels according to their water quality features using cluster analysis (CA). Accordingly, sampling sites Fb and Ketar River (Kb) are highly and moderately polluted in both seasons, respectively. On the other hand, sampling sites at the center (C), Meki river mouth (Ma), Ketar river mouth (Ka), Meki River (Mb), Korekonch (K_o) and Fa in dry season and Ka, C, Ma, Ko, Bulbula river mouth (B) and Fa during wet season were less polluted. Principal component analysis (PCA) analysis also showed the pollutant sources were mainly from Fb during dry season Mb and Kb during wet season. The values of comprehensive pollution index illustrated the lake is moderately and slightly polluted in dry and wet seasons, respectively. Comparatively, the pollution status of the lake is high around floriculture effluent discharge site and at the two feeding rivers (Kb and Mb) due to increasing trends in agrochemical loads. In order to stop further deterioration of the lake water quality and to eventually restore the beneficial uses of the lake, management of agrochemicals in the lake catchments should be given urgent priority.

Assessment of seasonal and spatial fluctuations in wastewater quality using multivariate statistical methods

This study aims at evaluating the seasonal and spatial fluctuations in the quality of wastewater passing through the stormwater flow (SWF) channel located in Kolkata, India, using multivariate statistical methods. In this study, the primary quality data were collected from eight selected sampling stations on the SWF channel during three seasons (summer, monsoon, and winter of 2019) for 10 parameters (ammonia, biochemical oxygen demand, dissolved oxygen, nitrate, orthophosphate as phosphorous, pH, temperature, total coliform, total suspended solids, and discharge). Cluster analysis was used to group the eight sampling stations into three categories of similar water quality characteristics. This resulted in three water quality rating zones: bad, moderately bad, and good. Principal component analysis (PCA) was carried out to identify the significant parameters responsible for the wastewater quality fluctuations during all three seasons. The results of the PCA revealed that temperature and pH are the most important constituents contributing to wastewater quality fluctuations in the SWF channel for all seasons in a year. The PCA studies additionally led to the conclusion that a parameter that may be massive in contribution to wastewater quality fluctuations within the channel once of a year may not be substantial for every different season. The study revealed the current state of the wastewater quality in the SWF channel by using just 1 year of primary data. In addition, it is expected to provide help for future studies on the channel.

Identification and Apportionment of Potential Pollution Sources Using Multivariate Statistical Techniques and APCS-MLR Model to Assess Surface Water Quality in Imjin River Watershed, South Korea

Reliable water quality monitoring data, identifying potential pollution sources, and quantifying the corresponding potential pollution source apportionment are essential for future water resource management and pollution control. Here, we collected water quality data from seven monitoring sites to identify spatiotemporal changes in surface water in the Imjin River Watershed (IRW), South Korea, distinguish potential pollution sources, and quantify the source apportionment from 2018–2020. An analysis was performed based on multivariate statistical techniques (MST) and the absolute principal component score-multiple linear regression (APCS-MLR) model. Statistically significant groups were created based on spatiotemporally similar physicochemical water quality characteristics and anthropogenic activities: low-pollution (LP) and high-pollution (HP) regions, and dry season (DS) and wet season (WS). There were statistically significant mean differences in water quality parameters between spatial clusters, rather than between temporal clusters. We identified four and three potential factors that could explain 80.75% and 71.99% in the LP and HP regions, respectively. Identification and quantitative evaluation of potential pollution sources using MST and the APCS-MLR model for the IRW may be useful for policymakers to improve the water quality of target watersheds and establish future management policies.

Copula-based framework for integrated evaluation of water quality and quantity: A case study of Yihe River, China

Water quantity and quality are two key factors affecting the performance of integrated watershed management. Conventional water resources assessment of rivers often deals with water quantity and quality separately. However, how to make an objective and impartial assessment of water resources by incorporating both water quantity and quality remains unclear, especially in watersheds with significant human activity impacts and high spatiotemporal variations in flows. In such areas, the nonmonotonic relationship between the water quality and discharge rate of a river, in contrast to near-natural conditions, is often ignored. To resolve this problem, this paper develops a new framework for the integrated evaluation of water quantity and quality by incorporating a new index, namely, the water quality improvement degree (WQID). The WQID is proposed to quantify the disturbance degree of human activities to the near-natural relationship between the water quality and discharge rate of a river. The Yihe River in Northern China is selected as a case study to apply the proposed framework. The results show that the observed flow discharge rates of some abnormal months after a specific time of change-point are greater than the estimated discharges under the river's near-natural condition. The WQID values in these abnormal months are less than 1, resulting in a decrease in the modified water resources surplus (WRS*) or an increase in the modified water resources deficit (WRD*). This indicates that the WQID can take into account the near-natural law between water quantity and quality to make a more objective evaluation of integrated water resources management for the months of interest. The proposed framework can serve as a useful and reliable tool for a comprehensive assessment of the watershed management performance of a river system.

Assessment of water quality condition and spatiotemporal patterns in selected wetlands of Punjab, India

Wetlands are one of the most productive aquatic ecosystems on earth, and their water quality is an indicative of their suitability for maintaining various ecosystem services. In this study, different statistical techniques and water quality index (WQI) were employed to access the status and spatiotemporal patterns in water quality of seven selected (two natural and five manmade) wetlands of Punjab. The results revealed that the status of water quality in the selected wetlands was between good and poor during studied seasons (summer, monsoon, and winter) of year 2019. The principal component analysis identified three groups of wetlands with distinct water quality characteristics with spatial patterns: Kahnuwan Chhamb and Keshopur Miani having nearly similar values of pH, total dissolve salts, electrical conductivity, chemical oxygen demand, total alkalinity, bicarbonate and ammonium content; Ropar, Kanjli, and Harike having higher value of nutrients than the other wetlands; and Ranjit Sagar and Nangal with low value of measured water quality characteristics. Further, analysis of variance revealed that all analyzed water quality parameters showed temporal patterns in water quality except water pH, electrical conductivity, dissolved oxygen, biological oxygen demand, and phosphate content. This comparative study enhanced our knowledge about the spatiotemporal patterns in water quality and in the future will be helpful to the policymakers and concerned authorities for developing better water quality management strategies for these wetlands.

Probabilistic risk assessment and water quality index of a tropical delta river

Water plays a major role in supporting the wellness and life processes in living things as well as in the ecological structure's stabilities. However, several environmental scientists have recounted the alarming menace unfit water quality portends as well as the shortfalls of its global utilization in various spheres of life. This study aims to determine the fitness of the Ossiomo River and its likely health risk impact when consumed or used for other domestic purposes. The outcome of the physicochemical and heavy metal characterization showed that most of the parameters surpassed the slated benchmarks. Findings from the study revealed a significant difference (p < 0.05) for water temperature, color, TDS, BOD₅, HCO₃, Na, Fe, Mn, and THC across the four stations respectively. Meanwhile, pH, salinity, turbidity, TSS, DO, Cl, P, NH₄H, NO₂, NO₃, SO₄, Zn, Cu, Cr, Ni, Pb, and V showed no significant (p > 0.05) across the four stations respectively. The pH level of the water was slightly acidic at the range of 4.40-6.82. The outcome of the computed water quality index showed that station 1 (66.38) was poor for human ingestion which was above the set slated benchmarks of 26-50. However, stations 2-4 (163.79, 161.79, and 129.95) were unsuitable for drinking which was above the set slated benchmarks of 100. The outcome of the health risk evaluation revealed that the hazard quotients (HQs) were considered greater than 1 (>1) for Cr (2.55). The hazard index (0.46) via the dermal pathway was <1 while the ingestion (4.35) pathway was >1. The sum of the HQs (4.81) was also > 1. Thus, there are possible non-carcinogenic health risks via direct ingestion of the water. The outcome from the carcinogenic risk for Pb, Cr, and Cd (6 × 10^-3, 4.00 × 10^-1, and 1.22 × 10⁰), was somewhat greater than the target goal (1.0 × 10^-6 to 1.0 × 10^-4) of carcinogenic risks stipulated by the United States Environmental Protection Agency for drinking water, respectively, especially for Cd. There might be a potential carcinogenic risk if the water is consumed when the metal contents are higher than the target limits set. Sustainable farming and treatment of wastes from industrial outputs should be the main management of this watercourse.

Evaluation of Soil and Irrigation Water Quality in Caohai Lakeside Zone

Due to the rapid population growth and over-application of fertilizers in the Caohai surrounding farmlands, controlling the non-point source pollution in the Caohai Lakeside Zone is significant for the local ecology balance and human health safety. A total of 54 soil and 24 irrigation water samples were collected in the Caohai Lakeside Zone to evaluate the current status of soil fertility and heavy metal pollution by measuring soil and water heavy metal content and soil physicochemical properties such as soil total nitrogen, total phosphorus, organic matter, and soil pH. These results showed that the total amounts of organic matter, nitrogen, phosphorus, potassium, and effective nutrient content in the Caohai Lakeside Zone were all at a rich level according to Chinese soil nutrient grade standard; the content of lead (Pb), chromium (Cr), cadmium (Cd), mercury (Hg), and arsenic (As) in the soil all exceeds the safety standard of Chinese classification of soil environmental quality assessment. In addition, the over-standard rates of Cd and Cr were 24.1% and 14.8%, respectively. On the whole, the comprehensive quality index (CQI) of the soil in the Caohai Lakeside Zone is 6.48, which is attributed to the heavy Cd pollution and the good soil fertility. The heavy metal content of the irrigation water met the requirements of irrigation water quality. It is feasible to use the irrigation water of Caohai Lake in the actual agricultural production process. Therefore, in terms of the comprehensive management and pollution control of Caohai, special attention should be paid to the control of Cd, Pb, As, and Hg pollution sources.

Long-term exposure to environmentally relevant concentrations of ibuprofen and aluminum alters oxidative stress status on Danio rerio

Despite the ubiquitous presence of multiple pollutants in aqueous environments have been extensively demonstrated, the ecological impact of chemical cocktails has not been studied in depth. In recent years, environmental studies have mainly focused on the risk assessment of individual chemical substances neglecting the effects of complex mixtures even though it has been demonstrated that combined effects exerted by pollutants might represent a greater hazard to the biocenosis. The current study evaluates the effects on the oxidative stress status induced by individual forms and binary mixtures of ibuprofen (IBU) and aluminum (Al) on brain, gills, liver and gut tissues of Danio rerio after long-term exposure to environmentally relevant concentrations (0.1-11 μg L^-1 and 0.05 mg L^-1- 6 mg L^-1, respectively). Lipid peroxidation (LPO), Protein carbonyl content (PCC) and activity of Superoxide Dismutase (SOD), Catalase (CAT), and Glutathione Peroxidase (GPX) were evaluated. Moreover, concentrations of both toxicants and the metabolite 2-OH-IBU were quantified on test water and tissues. Results show that ibuprofen (IBU) and aluminum (Al) singly promote the production of radical species and alters the oxidative stress status in all evaluated tissues of zebrafish, nevertheless, higher effects were elicited by mixtures as different interactions take place.

Impacts of the linear flowing industrial wastewater on the groundwater quality and human health in Swabi, Pakistan

The present study aimed to probe the extent and mobility of contamination in wastewater and its impact on groundwater and human health in the Swabi region in Pakistan. Representative samples (n = 86) were collected from both wastewater streams and groundwater in an analogous environmental setting. The result showed that pH, color, hardness, alkalinity, chemical oxygen demand, chloride, suspended solids, total dissolved solids, Cr, Cd, Pb, Cu, Fe, Mg, Na, Ca, and K in industrial wastewater were higher than the Pak-EPA (Pakistan Environmental Protection Agency) and the United State Environmental Protection Agency (US-EPA) devised standards. In groundwater, the concentration (μg L^-1) of trace elements, namely, Cd (1.16), Pb (17.4), Fe (12426), Mn (320), Mg (129784), Na (33630), Ca (177944), and K (9558) was significantly higher than the WHO (World Health Organization) acceptable level, showing decreasing tendency with increasing distance from the industrial zone. The study perceived that wastewater caused permanent hardness, while groundwater hardness was decreased from permanent to temporary at a distance from industries. Integrated health risk assessment revealed that Cu, Zn, and Co may cause low risk, Na, Mn, Ni, Pb, and Cr cause medium risk, whereas Cd, Fe, Mg, Ca, and K may cause a high health risk. Moreover, the average daily intake of Fe, Mn, Mg, Na, Ca, and K was comparably higher than Cr, Cd, Pb, Ni, Cu, Zn, and Co in both adults and children. The mode of occurrence of contaminants in groundwater was due to the leaching of contaminated wastewater and the oxidation of metals. Furthermore, carbonates, chloride, and SAR (sodium adsorption ratio) precipitation have a key role in groundwater contamination and influencing the natural water quality. The study concluded that the health problems in the surrounding areas were due to the use of contaminated water for drinking and household purpose. The study suggests filtering the drinking water and treating the wastewater before releasing it into the environment.

Non-Linear Visualization and Importance Ratio Analysis of Multivariate Polynomial Regression Ecological Models Based on River Hydromorphology and Water Quality

Multivariate polynomial regression (MPR) models were developed for five macrophyte indices. MPR models are able to capture complex interactions in the data while being tractable and transparent for further analysis. The performance of the MPR modeling approach was compared to previous work using artificial neural networks. The data were obtained from hydromorphologically modified Polish rivers with a widely varying water quality. The modeled indices were the Macrophyte Index for Rivers (MIR), the Macrophyte Biological Index for Rivers (IBMR), and the River Macrophyte Nutrient Index (RMNI). These indices measure the trophic and ecological status of the rivers. Additionally, two biological diversity indices, species richness (N) and the Simpson index (D), were modeled. The explanatory variables were physico-chemical properties depicting water quality and river hydromorphological status indices. In comparison to artificial neural networks, the MPR models performed similarly in terms of goodness of fit. However, the MPR models had advantages such as model simplicity and ability to be subject to effective visualization of complex nonlinear input–output relationships, as well as facilitating sensitivity analysis using importance ratios to identify effects of individual input variables.

Evaluation of Seasonal and Spatial Variations in Water Quality and Identification of Potential Sources of Pollution Using Multivariate Statistical Techniques for Lake Hawassa Watershed, Ethiopia

The magnitude of pollution in Lake Hawassa has been exacerbated by population growth and economic development in the city of Hawassa, which is hydrologically closed and retains pollutants entering it. This study was therefore aimed at examining seasonal and spatial variations in the water quality of Lake Hawassa Watershed (LHW) and identifying possible sources of pollution using multivariate statistical techniques. Water and effluent samples from LHW were collected monthly for analysis of 19 physicochemical parameters during dry and wet seasons at 19 monitoring stations. Multivariate statistical techniques (MVST) were used to investigate the influences of an anthropogenic intervention on the physicochemical characteristics of water quality at monitoring stations. Through cluster analysis (CA), all 19 monitoring stations were spatially grouped into two statistically significant clusters for the dry and wet seasons based on pollution index, which were designated as moderately polluted (MP) and highly polluted (HP). According to the study results, rivers and Lake Hawassa were moderately polluted (MP), while point sources (industry, hospitals and hotels) were found to be highly polluted (HP). Discriminant analysis (DA) was used to identify the most critical parameters to study the spatial variations, and seven significant parameters were extracted (electrical conductivity (EC), dissolved oxygen (DO), chemical oxygen demand (COD), total nitrogen (TN), total phosphorous (TP), sodium ion (Na+), and potassium ion (K+) with the spatial variance to distinguish the pollution condition of the groups obtained using CA. Principal component analysis (PCA) was used to qualitatively determine the potential sources contributing to LHW pollution. In addition, three factors determining pollution levels during the dry and wet season were identified to explain 70.5% and 72.5% of the total variance, respectively. Various sources of pollution are prevalent in the LHW, including urban runoff, industrial discharges, diffused sources from agricultural land use, and livestock. A correlation matrix with seasonal variations was prepared for both seasons using physicochemical parameters. In conclusion, effective management of point and non-point source pollution is imperative to improve domestic, industrial, livestock, and agricultural runoff to reduce pollutants entering the Lake. In this regard, proper municipal and industrial wastewater treatment should be complemented, especially, by stringent management that requires a comprehensive application of technologies such as fertilizer management, ecological ditches, constructed wetlands, and buffer strips. Furthermore, application of indigenous aeration practices such as the use of drop structures at critical locations would help improve water quality in the lake watershed.

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.

Human health risk assessment of metals and anions in surface water from a mineral coal region in Brazil

Coal mining releases high concentration elements to the environment, which can be deposited in surface water, causing several human health problems. Candiota mine in the south of Brazil is the largest coal reserves in the country, representing approximately 40% of total national coal reserves. Therefore, the present study aimed to estimate the chronic daily dose and the non-carcinogenic risk index for metals and anions in surface waters of Candiota Region, using the USEPA protocols for Human Health Risk Assessment. A total of eight water samples were collected over a distance of up to 15 km from the emission sources of the thermal power generation companies, then the Chronic Daily Intake (CDI), Hazard Quotient (HQ), Hazard Index (HI), and sum of Hazard Index (ΣHI) were calculated. All the elements and anions evaluated showed natural concentrations for continental fresh waters according to Brazilian legislation, except Pb. Individually, none of the metals Pb, As, Cd, Ni, and Se or anions F^- and NO₃^- showed an HI value greater than 1. However, the sum of HI (ΣHI) (five metals and two anions) by sample point showed values close to 1, for one of the eight points analyzed. Pb and Fe were the elements that most contribute to the risk values in the sample points of the study area. Although, there is no human health risk in this scenario, this investigation highlight priority elements to future investigations in coal mine areas. In the current region, Pb and F^- as priority elements for future studies.

Ecological and health risk assessment of trace metals in water collected from Haripur gas blowout area of Bangladesh

The study aims to assess the trace metals and physicochemical properties of water in the adjacent to the Sylhet gas blowout area. Trace metals were analyzed using atomic absorption spectrophotometer, whereas physicochemical parameters were evaluated in-situ state using portable instruments and also in the laboratory. Trace metals Pb, Cd, and Ni were found in the water samples higher than the acceptable limit by WHO standards, whereas the concentration of Cu and Zn were within acceptable limit, respectively. The correlation coefficient matrix and factor loading analysis spectacle that the interrelationship among the physicochemical parameters, trace elements, as well as other ions are moderate to strongly corellated which reflecting the homogeneous source of origin. According to contamination factor, Nemerow multi-factor index, pollution load index, and also, potential ecological risk index, the water of the region is quite polluted in case of Pb, Cd, and Ni but unpolluted for Cu and Zn. The water quality index indicates that treatment of water is required before using it for domestic purposes. The health quotient and hazard index results are less than standard value 1 suggesting that there is no noncarcinogenic risk in the area. The carcinogenic analysis shows that the lifetime incremental cancer risk mean value of Cd and Ni are fairly insignificant and Pb is more significant for children to cause health problem. The ILCR value of Cd and Ni are insignificant whereas Pb is significant to pose health risk for adults. Physicochemical parameters revealed that the water was slightly acidic and soft in nature implying to avoid the water from this area for drinking purposes. At the end, it can be concluded that this study will be useful for the residence as well as the policymaker to take the protective surveillance measures around the areas.

A coherent approach of Water Quality Indices and Multivariate Statistical Models to estimate the water quality and pollution source apportionment of River Ganga System in Himalayan region, Uttarakhand, India

River Ganga covers around 26% of India's land area and sustains diverse ecosystems in this overly populated area. The globally accepted coherent approach of water quality indices (WQIs) and multivariate statistical models (principal component analysis (PCA) and cluster analysis (CA)) were applied on the dataset to evaluate the spatial-temporal variation and pollution source identification and apportionment. Twenty-two hydro-chemical parameters were analyzed by collecting the samples from 20 different vertically elevated monitoring locations for different seasons. The CA evaluation of data, grouped the monitoring locations into five clusters of varied water quality with human perturbations and geo-genic inputs. The PCA analysis of an extensive dataset indicated the seven significant principal components (PCs) explaining 93.0% of the total variance and finalized 8 water quality parameters out of preselected 22 to represent good aspects of the water quality. The seasonal variation in river water quality by the Canadian Council of Ministers for Environment Water Quality Index (CCMEWQI) showed the quality class at a marginal level in summer (62.16), monsoon (59.96), and post-monsoon (60.20) season, whereas in winters (71.18), water quality was in fair condition. The response of National Sanitation Foundation Water Quality Index (NSFWQI) classified the river water in medium quality class for summer, monsoon, post-monsoon, and winter season, respectively. The present observations contribute in the usefulness of these statistical methodologies to interpret and understand large dataset and also provide reliable information to reduce the tedious and cost of water quality monitoring and assessment programs.

Ecological Study of Aquaponics Bacterial Microbiota over the Course of a Lettuce Growth Cycle

The study of microorganisms in aquaponics is an important topic which requires more research before exploiting the full potential of beneficial microorganisms. In this experiment, we focused on the evolution over time of the bacterial communities in four compartments of an aquaponic system i.e., the sump, the biofilter, the lettuce rhizoplane and lettuce root. We studied these communities over the course of a lettuce growth cycle via regular sampling and sequencing of the 16S rRNA gene of the collected bacteria. We also followed the physicochemical parameters of the aquaponic water throughout the experiment. Results show that a different community could be found in each compartment and that all four communities were stable throughout time and resilient to naturally occurring water parameter changes which characterize functioning aquaponic systems. Furthermore, the communities of the sump and biofilter also seem stable over the years as the predominant taxa (Luteolibacter, Flavobacterium, Nitrospira) observed in our study are similar to the ones previously reported for this aquaponic system. Finally, our results provide proof for similarities between aquaponic and soil borne lettuce root communities (gammaproteobacteria, Flavobacterium, Pseudomonadaceae, Sphingomonadaceae) thus showing that aquaponics can be similar to soil production in terms of microbial life.

Impact of anthropogenic activities on an urban river through a comprehensive analysis of water and sediments

The aim of this study was to assess the impact of urban and industrial areas on an urban river through a comprehensive analysis of water and sediments. Six different sites along the San Luis River, Argentina, were characterized by measuring 12 physical-chemical parameters and nine heavy metals according to standard protocols. Metal pollution in sediment samples was evaluated with several indices. Cluster analysis was applied to standardized experimental data in order to study spatial variability. As, Cu, Cr, Mn, Pb, and Zn were the main contributors to sediment pollution, and the industrial zone studied showed moderate enrichment of Co, Cu, and Zn, probably due to anthropogenic activities. Cluster analysis allowed the grouping of the sites: sediment samples were classified into two clusters according to the metal content; water samples were arranged into three groups according to organic matter content. The results were compared with sediment and water quality guidelines. They indicated progressive deterioration of water and sediment quality compared with the background area, mainly in the sites following the industrial park and domestic discharge areas. Moreover, the results showed that the analysis of both water and sediment should be considered to achieve a watershed contamination profile.

Sodium, Potassium, Calcium, and Magnesium in the Scalp Hair and Blood Samples Related to the Clinical Stages of the Parkinson's Disease

Neurodegeneration disorders are complex and multifaceted, leading to many chronic diseases, like Parkinson's disease (PD). Electrolytes imbalance has a significant role in the pathophysiology of neurological disorders, which might serve as a bio-indicator of these problems. In the present study, the disturbances of the electrolytes, calcium (Ca), magnesium (Mg), sodium (Na), and potassium (K), concentrations, and their correlation with biochemical parameters of PD patients at three different age groups (15 to 75 years) and stages were studied. The all resulted data of PD patients was compared with non-diseased/referents (PD) of same age groups. The biological samples (scalp hair, serum and plasma) were collected from Parkinson's disease (PD) patients, diagnosed at three stages, early (15 to 30 years), mild (30 to 60 years) and severe (61 to 75 years). The electrolyte concentrations were measured after acid digested biological samples using flame atomic absorption spectrometry. The precision of the digestion method was verified by matrices matched certified reference materials. The resulted data indicated that the contents of Ca and Mg were found to be higher in scalp hair samples of PD patients at early to severe stages as compared with those results obtained from referents. The concentrations of Na and K were found to be lower for all PD patients groups as compared with referents; however, the difference was not significant (p < 0.05). Electrolytes levels in blood serum and plasma were found to be lower in all patients than healthy groups (p < 0.01). These results suggest a disturbance in the electrolytes homeostasis during the different clinical stages of PD, whereas the higher disturbance was observed in patients at severe stage (61 to 75 years).

Estimation of rainwater harvesting by the reflectance of the purity index of rainfall

Rainwater harvesting is an effective alternative practice, particularly within urban regions, during periods of water scarcity and dry weather. The collected water is mostly utilized for non-potable household purposes and irrigation. However, due to the increase in atmospheric pollutants, the quality of rainwater has gradually decreased. This atmospheric pollution can damage the climate, natural resources, biodiversity, and human health. In this study, the characteristics and physicochemical properties of rainfall were assessed using a qualitative approach. The three-year (2017-2019) data on rainfall in Peninsular Malaysia were analysed via multivariate techniques. The physicochemical properties of the rainfall yielded six significant factors, which encompassed 61.39% of the total variance as a result of industrialization, agriculture, transportation, and marine factors. The purity of rainfall index (PRI) was developed based on subjective factor scores of the six factors within three categories: good, moderate, and bad. Of the 23 variables measured, 17 were found to be the most significant, based on the classification matrix of 98.04%. Overall, three different groups of similarities that reflected the physicochemical characteristics were discovered among the rain gauge stations: cluster 1 (good PRI), cluster 2 (moderate PRI), and cluster 3 (bad PRI). These findings indicate that rainwater in Peninsular Malaysia was suitable for non-potable purposes.

Chemical speciation of selected toxic metals and multivariate statistical techniques used to assess water quality of tropical Mexican Lake Chapala

Mexican Lake Chapala is used as water supply for human consumption. Consequently, water quality of this lake is of paramount importance for the lake's wellbeing. The contribution presented in this paper investigates monitoring and assessment of lake water quality using water quality index (WQI), metal chemical speciation, and multivariate statistical techniques. Descriptive statistics shows total metal concentrations undetected conferring the lake a healthy status. Dissolved Cd and Pb exceed criterion continuous concentration limit, whereas Zn is below this limit indicating that water quality is satisfactory for aquatic life. However, WQI indicates poor water quality attributed to failure of conductivity, total solids, nitrogen, and phosphates, due to industrial and agro-industrial effluents. Metal speciations indicate that the presence of low concentrations of dissolved metals reflect interactions with gills of fish through metal-biotic ligand complexes affecting water quality. Positive correlations are obtained between conductivity and nitrates, indicating that agricultural activities and fertilizer runoffs increase the conductivity and that the environmental state of lake is being altered by human activities. Factors F1 (31%), F2 (19%), and F3 (11%) represent 61% of variability; F1 and F2 corroborate the pressure exerted by pollutants related with fertilizers and agrochemicals; F3 contains Zn and Pb with positive loads attributed to influx of tourist visitors. Sites S4, S5, S6, and S9 are identified as the most environmentally affected by COD, Alk*, pH, Cl^-, nitrites, phosphates, and TS. Multivariate techniques permit to conclude that environmental stress of Lake Chapala is caused by variables pertaining to agrochemical, fertilizers and municipal wastes.

Assessment of groundwater quality and usability of Salda Lake Basin (Burdur/Turkey) and health risk related to arsenic pollution

PURPOSE

In this study the aim was to analyze the seasonal concentration, groundwater quality, usage areas and arsenic-related health risk of major ions and heavy metals in groundwater samples collected from the Salda Lake basin.

METHODS

In this study, 42 groundwater samples were collected from springs and wells in dry and wet seasons in 2015. Hydrogeochemical evaluations were made using different diagrams such as Piper and Gibbs diagrams. Groundwater quality was determined by the water quality index method (WQI) and different diagrams. Finally, health risk assessments related to arsenic were performed.

RESULTS

The dominant water types are Mg-Ca-HCO3 and Mg-HCO3 in the wet season and Mg-HCO3 and Mg-HCO3-CO3 in the dry season. According to calculated WQI values ranged from 24.14 to 56.93 in the wet season ranged from 25.27 to 145.87 in dry season. This situation indicates that the quality of water samples is mostly good both seasons. AsT concentrations were between 2.1-6.3 μg/L in the dry season and 2.9-10.5 μg/L in the wet season. The risk of developing cancer due to arsenic exposure in healthy adults or children is very low. But arsenic has high non-carcinogenic and carcinogenic potentially harmful effect in the study area. In addition, water samples are not appropriate for use as drinking water in terms of fertilizers and trace element concentrations. Also, MH will be an important problem in waters that will be used as irrigation water. The use of some samples is not recommended as it may cause crusting on metal surfaces in industrial areas.

CONCLUSIONS

According to the results obtained, the quality of groundwater in the study area should be monitored and the usage areas should be determined accordingly.

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.

A spatiotemporal analysis of the physicochemical parameters after the operation of the Corumbá IV reservoir (Midwest Brazil) to support better management decision

The study presents the characterization of the water quality of the Corumbá IV reservoir in the State of Goiás, in the Brazilian Cerrado biome, based on data from the operation period between 2007 and 2017. Few are known about the temporal and spatial variations in the water quality of the reservoir. Up to now, the water quality has been analyzed only from the point of view of compliance with the limits required by Brazilian environmental legislation. Therefore, the integrated analysis of water quality parameters and water body dynamics may bring important information to support decision-making in reservoir management. An exploratory analysis of the limnological data series provided by the company in charge of the hydroelectric plant was then carried out. Univariate and multivariate statistical techniques were applied to analyze the data period from 2007 to 2017. The results identify four distinct limnological phases representing the transition of the environment. The first phase (2007 to 2009) characterized by the decomposition of the flooded vegetal organic matter and subsequent phases, after 8 years (2010 to 2017), have featured the transition process from the lotic condition to the consolidation of the lentic environment. The spatial analysis of the results demonstrates that tributaries influence the water quality of the reservoir differently, probably due to the different impacts suffered in the sub-basins (e.g., sewage discharges; runoff). Although it is possible to evidence the impact of anthropic activities on water quality, the reservoir still presents characteristics of an environment with low trophic status.

Geospatial analysis of wetlands based on land use/land cover dynamics using remote sensing and GIS in Sindh, Pakistan

In this study, the Land Use/Land Cover (LULC) change has been observed in wetlands comprises of Manchar Lake, Keenjhar Lake, and Chotiari Reservoir in Pakistan over the last four decades from 1972 to 2020. Each wetland has been categorized into four LULC classes; water, natural vegetation, agriculture land, and dry land. Multitemporal Landsat satellite data including; Multi-Spectral Scanner (MSS), Thematic Mapper (TM), and Operational Land Imager (OLI) images were used for LULC changes evaluation. The Supervised Maximum-likelihood classifier method is used to acquire satellite imagery for detecting the LULC changes during the whole study period. Soil adjusted vegetation index technique (SAVI) was also used to reduce the effects of soil brightness values for estimating the actual vegetation cover of each study site. Results have shown the significant impact of human activities on freshwater resources by changing the natural ecosystem of wetlands. Change detection analysis showed that the impacts on the land cover affect the landscape of the study area by about 40% from 1972 to 2020. The vegetation cover of Manchar Lake and Keenjhar Lake has been decreased by 6,337.17 and 558.18 ha, respectively. SAVI analysis showed that soil profile is continuously degrading which vigorously affects vegetation cover within the study area. The overall classification accuracy and Kappa statistics showed an accuracy of >90% for all LULC mapping studies. This work demonstrates the LULC changes as a critical monitoring basis for ongoing analyses of changes in land management to enable decision-makers to establish strategies for effectively using land resources.