Variations In Surface Water Quality Research Articles

Exploring spatial and seasonal water quality variations in Kelani River, Sri Lanka: a latent variable approach.

Water quality degradation poses a significant challenge globally, especially in developing nations like Sri Lanka. Extensive monitoring programs designed to address escalating river pollution collect multiple water quality parameters over extended periods and varied locations. However, the sheer volume of data can be overwhelming, making it difficult to process effectively and interpret accurately using conventional methods. In this study, latent variable (LV) and unsupervised machine learning techniques were used to investigate spatial and seasonal variations of surface water quality for 17 parameters across 17 locations along the Kelani River, Sri Lanka, using monthly water quality parameters from 2016 to 2020. Pearson's correlation matrix identified 10 parameters significantly affecting water quality variations and factor analysis (FA) generated five LVs, accounting for 77% of the total variance in the dataset. The identified LVs showed multiple methods of river pollution.Hierarchical clustering analysis and self-organizing mapping methods clustered stations in a closely analogous manner. Stations near industrial zones and the river mouth showed higher water quality variance, often exceeding national guidelines. Correlation testing revealed strong relationships between water quality and catchment hydrometeorological variations during monsoonal seasons. Spatial analyses showed increased LV variance in the Lower Kelani River Basin, indicating higher pollutant levels in different seasons. Industrial effluents (LV-2 and LV-4) and domestic and municipal sewage (LV-3 and LV-5) exhibit greater seasonal fluctuations. The results showed that the proposed LV approach has the potential to assist authorities in addressing water pollution amidst the complexity of multiple water quality parameters.

STATISTICAL ASSESSMENT OF WATER QUALITY PARAMETERS FOR POLLUTION SOURCE IDENTIFICATION IN NOYYAL RIVER, COIMBATORE, TAMILNADU

<p>This study aimed to determine the extent of the water quality decrease in the Noyyal River in Tamilnadu by analyzing the seasonal change of water's physicochemical properties, identifying possible sources of pollution, and grouping the monitoring months based on shared characteristics. The measurements were taken during four different seasons. Forty percent of the water quality indices, including turbidity, DO concentration, EC, Cl concentration, TA, and COD in all seasons, were found to be outside the acceptable limits recommended by various agencies, according to the analytical data. A 95% confidence interval's worth of statistical analysis revealed that 52% of the contrasts differed significantly. Four factors accounted for 93.44% of the variation overall, according to the factor analysis, which showed the best fit between the parameters. The significant pollution loading, primarily attributed to toxicological chemicals and industrial discharge, was reflected in Total Dissolved Solids, Biochemical Oxygen Demand, Chemical Oxygen Demand, Electrical Conductivity, Turbidity, Dissolved Oxygen, and Chloride levels. Cluster analysis revealed a seasonal variation in surface water quality, indicating contamination from rainfall or other sources. Nevertheless, seasons did impact the levels of various physicochemical characteristics, with winter recording the highest pollution values. The Noyyal River's seasonal temperature change and increased rainfall were the causes of this self-refining tendency, which goes winter < summer < pre-winter < rainy season.</p>

Evaluation of Spatial Variations in Surface Water Quality of Mahanadi River Basin by Geospatial-FUCOM based Prediction Utilising Fuzzy-TOPSIS Approach

This study highlights an evaluation of surface water quality for drinking purposes in Mahanadi River Basin, Odisha using Full Consistency Method (FUCOM) based WQI (FU-WQI), with reliability-based MCDMs (Multiple-criteria decision making) such as Fuzzy-TOPSIS (F-TOP). Water samples from 19 locations were taken during the period 2018-2023 to test 20 physicochemical parameters. Further, the FU-WQI revealed that 36.84% (n=7 sites) and 5.26% (n=1) of samples belong to poor/unsuitable water quality while 47.37% of sites come under the zone of excellent water (n=9 locations). However, 10.53% of samples indicated a medium water quality. The analysis primarily revealed that at 8 samples, deterioration of domestic water, illegally dumped municipal solid waste, and agricultural runoff were the leading sources causing adulteration of the river’s water quality. As a result, a renowned MCDM model, such as F-TOP, was implemented to resolve conflicts regarding the WQI index. Hence, this innovative technique showed that SP-(9) was the most polluted in comparison with other locations, followed by SP-(8), (19), and (2). This was also accompanied by high values of nine crucial parameters, which were also higher than their desirable concentration and highest among all the locations. Following this, the analytic findings also suggest the same from the FU-WQI values 423, 198, 182 and 184 at these locations. However, it was pertinent that the pollution level at these stations was associated more with increasing and diverse anthropogenic activities. So, it is found that river water is convenient for household usage and, after disinfection, fit for human consumption.

Comparative evaluation of spatiotemporal variations of surface water quality using water quality indices and GIS

AbstractThere is a need for a comprehensive comparative analysis of spatiotemporal variations in surface water quality, particularly in regions facing multiple pollution sources. While previous research has explored the use of individual water quality indices (WQIs), there is limited understanding of how different WQIs perform in assessing water quality dynamics in complex environmental settings. The objective of this study is to evaluate the effectiveness of three WQIs (Canadian Council of Ministers of the Environment (CCME), National Sanitation Foundation (NSF) and System for Evaluation of the Quality of rivers (SEQ-Eau) and a national water quality regulation in assessing water quality dynamics. The pilot study area is the Acısu Creek in Antalya City of Turkey, where agricultural practices and discharge of treated wastewater effluents impair the water quality. A year-long intensive monitoring study was conducted includig on-site measurements, analysis of numerous physicochemical and bacteriological parameters. The CCME and SEQ-Eau indices classified water quality as excellent/good at the upstream, gradually deteriorating to very poor downstream, showing a strong correlation. However, the NSF index displayed less accuracy in evaluating water quality for certain monitoring stations/sessions due to eclipsing and rigidity problems. The regulatory approach, which categorized water quality as either moderate or good for different sampling sessions/stations, was also found less accurate. The novelty of this study lies in its holistic approach to identify methodological considerations that influence the performance of WQIs. Incorporating statistical analysis, artificial intelligence or multi-criteria decision-making methods into WQIs is recommended for enhanced surface water quality assessment and management strategies.

Understanding watershed sources of pollution in Vinh Long Province, Vietnamese Mekong Delta

We explore point source (PS) and non-point source (NPS) pollution impacts on surface water quality in Vinh Long Province, Vietnam. We used data from 60 surface water quality monitoring stations across dry, transitional, and wet seasons from 2017 to 2021, in addition to sampling data collected from 12 wastewater outlets from June to October 2021 to determine the sources of pollution loads. Surface water quality was assessed using both the water quality index (WQI) and the Vietnamese standards QCVN 08:2015, whilst cluster analysis (CA) and principal components analysis (PCA) were used to evaluate spatial variation and key influencing factors. We observed seasonal variation in surface water quality, with a decline in quality during the rainy season. Moreover, the water quality parameters such as chemical oxygen demand (COD), biochemical oxygen demand (BOD5), total nitrogen (TN), and total phosphorus (TP) frequently exceeded the QCVN 08:2015 standard. Across, the different monitoring fixed points and seasons, COD levels were found to range from 8.94 to 15.14 mg/L, while TN levels varied between 0.24 and 0.53 mg/L. The cluster analysis categorized the monitoring fixed points into three groups, based on their water quality parameters, while PCA identified four principal components that explain 69% of the variance, distinguishing between pollution sources and seasonal factors. Our findings emphasize that poor water quality in many areas is affected by non-point source pollution, underscoring the need for watershed and land management. The results and applied methodologies provide insights for watershed management, policy development, and adaptation, applicable to regions facing similar environmental challenges.

Water Quality Assessment Using the Water Quality Index, and Geographic Information Systems in Nador Canal, Morocco

In recent decades, water pollution has emerged as a significant concern, posing a threat to both humans and natural ecosystems. This study aimed to assess the spatial variations in water quality in the Nador Canal, Morocco using the water quality index combined with multivariate statistical techniques and geographic information systems (GIS). The parameters examined were then compared to the maximum permissible limit values recommended by Moroccan surface water standards and the World Health Organization. The results indicated that the WQI of Nador Canal is generally suitable for irrigation and unsuitable for drinking. It indicated that the quality of surface water in the Nador Canal is affected by organic pollutants, and this is evidenced by low levels of dissolved oxygen, the levels of elements were high, especially chlorine and sodium, in addition to a high concentration of ammonia, nitrate, and phosphate in some of the stations studied. Principal component analysis (PCA) results revealed that PC1–PC3 collectively accounted for 73% of the variation in surface water quality within the study area. The cluster analysis also proves that the water quality is relatively polluted. Potential contributing factors to surface water pollution include changes in the hydrological regime, household waste discharges, and agricultural activities. These findings furnish essential insights into water quality, particularly its suitability for irrigation, and contribute to enhancing the water quality management system of the Nador Canal in the Gharb region of Morocco.

Seasonal variation of surface water quality and streamflow in Rispana: A tributary of Ganges river, India

AbstractTo evaluate the seasonal changes in quality and quantity of river Rispana (a tributary of river Ganges—Dehradun region of India) water quality index (WQI) was calculated at four major locations by using the weighted arithmetic method. Sixteen samples in all were taken throughout the pre‐monsoon (April 2022), monsoon (July 2022), post‐monsoon (November 2022), and the Winter season (January 2023). The major parameters, namely, temperature, dissolved oxygen (DO), pH, electrical conductivity (EC), and total dissolved solids (TDS), E‐coliform, sulphate, total alkalinity (TA), total hardness (TH), and biochemical oxygen demand (BOD) were considered for calculation of WQI. The WQI varied from minimum 44.53 (good) at site 1 – Kairwaan Gaon during monsoon season to maximum 302.69 (unfit for drinking) at site 4 – Mothrowala during the pre‐monsoon period. In 75% samples quality of water was unfit for domestic purpose and the contributing factors are DO, BOD, and Coliform which exceeds permissible limit in all samples. The major factors attributed for decline in the Rispana water quality are discharge of sewage, commercial sites effluent, and urban runoff. Pre‐monsoon, monsoon, post‐monsoon, and winter had average total coliform levels of 1849.6, 2419.6, 2419.6, and 1546.25, respectively, in MPN units. The average value of E‐coli for the four season vary from 1306.8 to 1888.1 MPN. The pollution load (physico‐chemical parameters and bacteriological factors) increases as the river Rispana flows to downstream in urban locations. Streamflow was observed as very lean except monsoon season (~1500 cfs) due to more extraction of Rispana's fresh water in upstream and unplanned changes in its catchment basin; thus establishes an extensive decline in availability of fresh water sources (Domestic use) in downstream Dehradun city area. In monsoon season, more streamflow (rain water influx) maintains the WQI also in good‐moderate category. The land use/land cover – LULC analysis in Rispana basin area, depicted 71% enhancement in urbanization (24.16%–41.55%) takes place in 15 years’ span (2003–2017). The study establishes the potential causes (natural and anthropogenic) for Rispana deterioration and provides a baseline (quality index) for aquatic and ecological rejuvenation of its watershed by executing a proper management strategy with people participation. This work contributes discernments for effective water resource management to address the smart city objectives and sustainable development goal‐SDG:6, urban and municipal authorities must take cognizance for revival of this domestic water resource.

Spatial and seasonal variations in surface water quality of the Lower Kinabatangan River Catchment, Sabah, Malaysia

Surface water quality was examined to determine spatial and seasonal variations in the Lower Kinabatangan River catchment, Sabah, Malaysia between October 2004 and June 2005, during the weak La Niña event. The study sought to distinguish between the quality in surface waters draining from an oil palm plantation (OP), a secondary forest (SF) and an oxbow lake (OB); and to identify its seasonal variability. A total of 45 samples were collected during fieldwork campaigns that spanned over the inter-monsoonal period, wet and dry seasons. The Water Quality Index (WQI) was calculated and analysed based on the Malaysia Interim National Water Quality Standard (INWQS). Results show that the quality of the river fall into Class II or moderate level. Discriminant analysis (DA) has been employed to classify independent variables into mutually-exclusive groups. Suspended sediment (SS) and chemical oxygen demand (COD) parameters were found higher during the wet season. COD was found dominant in stream located within the oil palm plantation, whilst SS was dominant in oxbow lake. Surface water quality variations could be influenced by weak La Niña event in 2005/2006, as precipitation anomalies have been observed during the sampling campaign.

Seasonal Variations in Surface Water Quality in River Njoro and Lake Nakuru, Kenya

Water pollution from rivers and lakes has resulted in serious environmental issues on a global scale. The public's growing concern over the decline in river and lake water quality makes it more important than ever to assess the water quality of these bodies of water over a prolonged period of time. During the rainy and dry seasons of 2022, 120 water samples were collected from 5 monitoring stations located within River Njoro and Lake Nakuru. The samples underwent physicochemical analysis of selected water parameters, which included salinity, temperature, pH, turbidity, total nitrogen (TN), total phosphorus (TP), electric conductivity (EC), and total dissolved solids (TDS). The results were compared using the National Environmental Management Authority (NEMA) of Kenya's guidelines and the results showed that the water quality of the Njoro river and Lake Nakuru fluctuated with the seasons, particularly in the lower water column of river Njoro. The quality parameters had the following values; EC values range between 73.33 ± 0.55 μs/cm - 533.33 ± 0.64 - μs/cm, respectively for both seasons; Salinity values range from 0.085 ± 0.02 ppt - 2.59 ± 0.03 ppt; pH values were between 8.8 – 9.3; Temperature was 23.69 ± 0.07 °C – 14.22± 0.07°C; Turbidity varied significantly – 13.95 ± 0.27 NTU - 36.03 ± 0.35 NTU; TDS between 46.67 ± 0.11 ppm- 243.33 ± 0.04 ppm; TN ranges between 5.97 ± 3.24 mg/L - 8.57 ± 3.18 mg/L and TP 7.49 ± 1.7-9.41 ± 1.84 mg/L in the dry and rainy seasons, for River Njoro and Lake Nakuru respectively. This study showed that the degree to which human activity affects water quality varies with the season. Therefore, most of these factors should be considered while controlling rivers downstream in order to ensure the health of aquatic life, also it is essential to increase lake water quality monitoring and regulate human activity. Additionally, the results revealed that water pollution resulted primarily from domestic wastewater, agricultural runoff and industrial effluents.

Water quality index, ecotoxicology and human health risk modelling of surface and groundwater along illegal crude oil refining sites in a developing economy

Water quality index, ecotoxicology and human health risk models were applied to surface and groundwater samples along illegal crude oil refining sites in Rivers State, Nigeria. Eight (8) surface water and four (4) groundwater sampling points were identified along illegal refining sites. Thirty-six (36) samples in triplicates were collected monthly from each of the twelve (12) sampling points over a three (3) month period. Water samples were collected and analyzed using standard methods as prescribed by the American Public Health Association. The mean pH for surface and groundwater ranged from 5.61 ± 0.15 to 7.34 ± 0.10 and 5.80 ± 0.10 to 6.39 ± 0.13, respectively. Turbidity, TDS, and BOD data for surface water samples exceeded the WHO guideline values. The ionic dominance pattern of anions for both surface and groundwater water samples were the same and in the order Cl− > SO42− > NO3− > PO42−. Mean heavy metal concentration was in the order Pb > Ni > Fe > Cd > Mn > Cu for surface water and Pb > Cd > Fe > Mn > Ni > Cu for groundwater. Cd and Pb concentrations in both sources were generally high, with Cd exceeding the WHO guideline value (GV). The CCME water quality index model ranked 62.5% of surface water as marginal, 12.5% as good, 12.5% as poor, and 12.5% as fair. The impact of heavy metals on public health was in the order Pb > Cd > Ni > Fe > Mn, with 83% of samples seriously affected by Pb pollution. The potential ecological risk index ranged from 1.61 × 103 to 2.64 × 103 for surface water and 8.10 × 102 to 2.21 × 103 for groundwater. Heavy metal contamination was very high, and the ecological risk effect was extremely high. The health risk through oral ingestion was in the order of adults > infants > children. Two principal components, PC1 and PC2, explained 50.51% and 16.00% of the variations in surface water quality, respectively. For groundwater quality data, three principal components explained the observed variations in water quality data, of which 51.39% is attributed to PC1, 26.29% to PC2, and 16.58% to PC3.

Population genetic structure of two cryptic duckweed species (Lemna minor &L. turionifera) in Alberta using a genotyping-by-sequencing approach

Identifying population genetic structure is important for the development of species-specific management plans. Investigating the population genetics of cryptic species is even more critical. Here we focus on two cryptic duckweed species easily mistaken for one another, Lemna minor L. and L. turionifera Landolt, which have overlapping ranges in our study region of Alberta, Canada, and elsewhere. We used genotyping-by-sequencing to determine the population genetic structure of both duckweed species. A total of 192 samples was sequenced. After filtering, 16,007 single nucleotide polymorphisms were used to examine patterns of genetic diversity between and within L. minor and L. turionifera. The two species showed clear differentiation. When examining L. minor singly, we discovered at least three genetically distinct populations among the 30 samples from eight sites, even though these were from a small geographic area. In contrast, when examining L. turionifera singly, we found no evidence of genetically distinct populations among 67 samples from 43 sites. We also examined the relationship between surface water quality variables and the distribution of the two Lemna species. The sites containing L. turionifera had a wider range of water chemistry variables suggesting they are more tolerant of different environmental conditions. In contrast, each of the three genetically distinct L. minor groups had different water chemistry profiles. Large differences between L. minor and L. turionifera in their regional distributions and degrees of genetic differentiation highlight the importance of documentation and careful monitoring of Lemna species within Alberta, and in other regions where they co-occur.

Effects of Hydrological Season on the Relationship between Land Use and Surface Water Quality

In recent decades, land use patterns have changed significantly in highly urbanized areas, which is usually linked with the spatial variation of surface water quality at the catchment scale, but little attention has been paid to how hydrological seasons affect this relationship. Taking Pudong New Area of Shanghai, China, as an example, this paper evaluated the influence of hydrological seasons on the relationship between land use and water quality under different hydrological buffers. It was shown that the contribution of land use to the spatial variation of water quality is approximately 30%. In addition, the explanatory ability was greatest in the average season while it was smaller in the dry and wet seasons. Land uses showed scale effects; at a smaller scale, urban areas, agricultural land and water areas were the most important land uses affected by water quality. As the buffers changed from 500 to 1500 m, the impact of urban areas decreased significantly, while that of agricultural land and water areas increased rapidly; however, when the buffer was greater than 1000 m, the explanatory ability of water areas did not increase further but remained stable. Green space is only significant at the 200 m and 500 m scales, which showed the effect of improving river quality. This study is expected to provide references for future decision making of urban construction, environmental planning and management.

Đánh giá sự thay đổi chất lượng nước mặt theo mùa trên dòng chính và một số sông nhánh thuộc lưu vực sông Cả

The purpose of research is to assess the seasonal changes of water quality in mainstream and in specific tributaries in the Ca River Basin. Water samples were collected in the dry season (May 2021) and in the beginning of the rainy season (September 2021) from 4 sites located on Ca River’s mainstream and 5 sites located on Ca River’s tributaries to analyze water quality parameters. Results indicated that physical parameters (pH, EC,salinity, DO) and and heavy metals (As, Cu) are within the standard values according to the National Technical Regulation on Surface Water Quality QCVN 08-MT:2015/BTNMT for domestic water supply purposes (Columne A1). The concentration of nutrients measured in the tributaries is higher than those in the mainstream due to the contribution of nutrients and organic materials from agricultural runoff. In addition, the water flow in the tributaries is lower than in the mainstream, as a result, the concentration of nutrients tends to be higher in the tributaries. The samples revealed that the concentration of nutrients (NO3-, TN, PO43-, TP) and chemical oxygen demand (COD) appeared higher in the beginning of the rainy season than in the dry season. The increase of nutrient concentrations can be explained by the leaching of nutrients into the river. In general, the water quality of Ca River’s tributaries during the rainy season have a high nutrient concentration and also the risk of eutrophication.

A remote sensing tool for near real‐time monitoring of harmful algal blooms and turbidity in reservoirs

AbstractHarmful algal blooms (HABs) diminish the utility of reservoirs for drinking water supply, irrigation, recreation, and ecosystem service provision. HABs decrease water quality and are a significant health concern in surface water bodies. Near real‐time monitoring of HABs in reservoirs and small water bodies is essential to understand the dynamics of turbidity and HAB formation. This study uses satellite imagery to remotely sense chlorophyll‐a concentrations (chl‐a), phycocyanin concentrations, and turbidity in two reservoirs, the Grand Lake O′ the Cherokees and Hudson Reservoir, OK, USA, to develop a tool for near real‐time monitoring of HABs. Landsat‐8 and Sentinel‐2 imagery from 2013 to 2017 and from 2015 to 2020 were used to train and test three different models that include multiple regression, support vector regression (SVR), and random forest regression (RFR). Performance was assessed by comparing the three models to estimate chl‐a, phycocyanin, and turbidity. The results showed that RFR achieved the best performance, with R2 values of 0.75, 0.82, and 0.79 for chl‐a, turbidity, and phycocyanin, while multiple regression had R2 values of 0.29, 0.51, and 0.46 and SVR had R2 values of 0.58, 0.62, and 0.61 on the testing datasets, respectively. This paper examines the potential of the developed open‐source satellite remote sensing tool for monitoring reservoirs in Oklahoma to assess spatial and temporal variations in surface water quality.

Variation of Surface Water Quality in Cu Lao Dung Island, Soc Trang Province, Vietnam

The study aims to evaluate variation of surface water quality in canals in Cu Lao Dung district, Soc Trang province, Vietnam using multivariate statistical methods. Sixteen surface water samples with the parameters of pH, total suspended solids (TSS), dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), NH4+-N, NO2−-N, PO43−-P, Cl−, Fe, coliform were used for the assessment. The results showed that the surface water in the study area was contaminated with microorganisms, salinity and acidity, and nutrient. The concentrations of coliform, Cl−, Fe, TSS and NO2−-N were higher than the specified limits by 4.17, 2.04, 1.91, 1.28 and 1.10 times, respectively. The four principal components could explain up to 81.40% of the total variance of surface water quality. The main water pollution sources could be from natural (rainwater runoff, saltwater intrusion, erosion) and man-made activities from domestic and agricultural activities (livestock, aquaculture, cultivation), industry and navigation activities. Cluster analysis divided surface water quality into two groups by the difference in BOD, COD, NH4+-N, NO2−-N, Fe, coliform and pH. Pearson correlation results demonstrated that only BOD or COD should be monitored since it is mutually predictable. Specific sources and its contribution should be further studied for effective surface water quality management in the study area.

Variation of Surface Water Quality at Bung Binh Thien Reservoir, An Giang Province, Vietnam Using Principal Component Analysis

This study was conducted to assess surface water quality at Bung Binh Thien reservoir, An Giang province, Vietnam. Sixty inhabitants living around the reservoir were interviewed to identify pollution sources. Nine water samples were collected in the dry and rainy seasons and then analyzed for eighteen variables (temperature, pH, electrical conductivity (EC), total dissolved solids (TDS), total suspended solids (TSS), turbidity (Turb), dissolved oxygen (DO), biological oxygen demand (BOD), chemical oxygen demand (COD), sulfate (SO₄²⁻), chloride (Cl⁻), ammonia (NH4+-N), nitrate (NO3--N), total nitrogen (TN), orthophosphate (PO43--P), total phosphorus (TP), and coliform). Principal component analysis (PCA) was used to identify the primary parameters influencing water quality. The results indicated that the major concerns for water quality in the reservoir were suspended solids, organic matters and fecal microbes. There were significant seasonal variations in water quality. While organic pollution was mainly observed in the dry season, the microbial problem was recorded in the rainy season. This pollution was associated with domestic wastes, agricultural production, livestock, and aquaculture. The PCA results also revealed that DO, BOD, COD, N-NH₄⁺, N-NO₃⁻, P-PO₄³⁻, TP, Cl⁻, and coliform greatly influenced water quality variations, thus requiring these parameters in the monitoring program. The local authority should apply proper measures to improve water quality in the reservoir, and inhabitants should not directly use water for their domestic activities without adequate treatment.

Major concerns of surface water quality in south-west coastal regions of Vietnamese Mekong Delta

This study aimed to appraise seasonal variations in surface water quality on the coasts of Southwestern Vietnam using entropy-weighted water quality index (EWQI) and multivariate statistics: cluster analysis (CA), principal component analysis (PCA), and discriminant analysis (DA). Forty-nine samples monitored in Kien Giang province during the rainy and dry seasons were analysed for 16 physiochemical and biological parameters. Compared to the Vietnamese standard, surface water quality in the study areas was contaminated with organic matter (high biological oxygen demand and chemical oxygen demand), nutrients (high ammonium (NH4+), nitrite, and orthophosphate), total suspended solids (TSS), iron (Fe), and coliform. Seasonal variations in surface water quality in the coastal regions were observed. TSS, organic matter and microbial problems in water bodies tend to be more serious in the rainy seasons due to an increase in water flow containing pollutants from upstream and wastes from regional human activities. Meanwhile, the salinity in the dry season (0–32‰) was greatly higher, which caused only 10% of samples to be suitable for irrigation. CA extracted 11 and 13 clusters from 49 locations in the dry and rainy seasons, respectively. Five principal components obtained from PCA can explain 74 and 70% of total water quality variations in dry and rainy seasons, respectively. Moreover, the results of PCA suggested that natural factors (hydrological regimes, temperature, rainfall, sea-level rise) and human sources (domestic, agriculture, industry, and tourism) are accountable for these fluctuations. DA extracted 7 parameters (pH, TSS, salinity, Fe, nitrate, NH4+, and chloride) for leading the difference in water quality, with 88% of correct assignation. EWQI revealed that about 66% of total samples were classified as a very bad quality for drinking in the dry season. However, this ratio declined to 59% in the rainy season. Although the surface water quality was slightly improved during the rainy season, organic matter and microbial pollution need to be concerned. The findings of this study can provide insights into seasonal variations in surface water with the application of multivariate statistics and EWQI, which could support policymakers in developing water management strategies.

Seasonal assessment of water quality and water quality index (WQI) variations, in Jiangsu Kunshan Tianfu National Wetland Park, China

ABSTRACT Seasonal variations in surface water quality are essential for assessing temporal variations in wetlands pollution due to natural or anthropogenic inputs from both point and non-point sources. The goal of this study was to use established methodologies to estimate the water quality of the Tianfu National Wetland Park based on physicochemical features; sampling was done from eight monitoring locations throughout the wetland region in the summer of 2019 and winter of 2020. The water quality index (WQI) is calculated using the following parameters: Turbidity (NTU), Nitrate, Chlorophyll, TOC, DOC, COD, BOD, Chroma, Ammonium nitrogen, pH, Electric Conductivity, and Total Phosphorus. One-way ANOVA and Tukey’s pairwise comparisons with a 5% significance level were used to compare water quality parameters among the monitoring point’s data. T-test analysis was used to compare the parameters between summer 2019 and winter 2020 and the difference between the water inlet and the water outlet. Cluster analysis was done on the WQI results using Ward’s linkage approach. The analyses of variance (ANOVA) of data revealed statistically significant differences between points of sampling (p < 0.05). The paired t-test revealed significant differences in parameters between summer 2019 and winter 2020; however, all parameters in summer show higher values in the water inlet than water outlet. In winter, TOC, DOC, COD, BOD, Chroma, pH, and Electric Conductivity showed higher values than Turbidity (NTU), Nitrate, Chlorophyll, Ammonium Nitrogen, and Total Pospurus. In general, summer showed higher pollution than winter, and water inlets were more polluted than water outlets indicating that other factors may affect the water quality, such as vegetation cover, temperature, water level, and activities in the wetland during the seasons.

Application of Correlation Matrix and Analysis of Variance (Anova) in Profiling Surface Water in Nembe Creek of Niger Delta, Nigeria

Water resource contamination is a major concern in several regions, especially in the Niger Delta, in which the oil exploration activities pose serious risks to human health, water resource and the environment. This present study evaluates the properties of surface water in Nembe Creek. Surface water samples were collected from three (3) control stations and twenty-four (24) sampling stations around the creek during the wet and dry seasons. The samples were subjected to analysis following the standard operating procedures of ASTM and APHA analytical methods. The relationship between the parameters and variations of surface water quality of Nembe creek were determined by using descriptive statistics, Analysis of variance (ANOVA) and Pearson correlation analysis. The results indicated pH had a mean value of 6.67± 0.33 (wet season) and 7.21 ± 0.3 (dry season), Electrical Conductivity ranged 200 – 3950 µS/cm (wet season) and 17900 – 25800 µS/cm (dry season), DO ranged between 4.3 – 5.8 (wet season) and 3.9 – 5.6 (dry season), Nitrate had values of 0.007- 0.068 mg/L (wet season) and 0 – 0.007 mg/L (dry season), Sulphate values range 130.58- 158.76 mg/L (wet season) and 215.12 – 657.35 mg/L (dry season). Iron range 3.23 – 5.6 mg/L (wet season) and 0.26 – 7.87 mg/L (dry season), Zinc ranged 0.02 – 0.47 mg/L (wet season) and 0.13 – 2.22 mg/L (dry season). Across all sampling stations and control areas during the wet season, the values for Total Petroleum Hydrocarbon (TPH), total hydrocarbon Content (THC) and Petroleum Aromatic Hydrocarbon (PAH) were below the detection limit; however, the values varied during the dry season. The Pearson Correlation matrix revealed positive, negative and significant correlations between the pairs of parameters at 95% confidence level. Amongst the sampling and control stations, some parameters had no significant difference (p &gt; 0.05), however some differences were statistically significant (p &lt; 0.05). In conclusion, Nembe Creek is marginally more polluted during the dry season than during the wet season. Most parameters on the Person's Correlation matrix were connected with each other based on the metrics. However, some parameters such as metals, do not significantly correlate with one another, indicating that the sources of contamination may have originated from various places. It is possible that the source may not predominantly originate from oil exploration activities but may involve other natural, geological and anthropogenic activities.

Spatio-temporal characterization of nutrient and organic pollution along with nutrient-chlorophyll-a dynamics in the Geum River

River water pollution is one of the biggest environmental challenges in the world. Therefore, it is imperative to assess the spatial and temporal variability of surface water quality to manage water resources from pollution. This study aimed to identify spatio-temporal variations of Geum River surface water quality and the factors that influence it. Summer monsoon, land-use land-cover (LULC), and weirs are dominant factors determining the dynamics of river water quality. Empirical analysis showed that total phosphorus (TP), total nitrogen (TN), biological oxygen demand (BOD), and chemical oxygen demand (COD) had positive linear functional relations with the agricultural and built-up cover but negative linear relations with forest cover. The results showed that the total suspended solids (TSS), chlorophyll-a (CHL-a), TP, and COD levels were higher in the summer than in any other season. On the other hand, total nitrogen (TN) and electrical conductivity (EC) levels were lower during summer in the river due to the dilution effect. Pollutant-transport theory shows that TSS acts as a TP carrier (R2 = 0.83, p < 0.001). The empirical model suggested that TP (R2 = 0.76, p < 0.001) was the better predictor for CHL-a compared to TN (R2 = 0.13, p < 0.001) as well as showed strong P-limitation based on TN:TP ratios. The high average WQI values of the Geum River (except for S01 and S02) show a higher pollution level, indicating its unsuitability for drinking, irrigation, and industrial usage. Our results suggest that industrial and domestic sewage treatment and agricultural diffuse pollution control could improve the Geum river water quality.