Canadian Council Of Ministers Of The Environment Research Articles

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.

Water quality assessment of Elgo river in Ethiopia using CCME, WQI and IWQI for domestic and agricultural usage

The increasing demand for water due to the escalation in population and aggressive agricultural activities for drinking and irrigation purposes in the rural areas of Ethiopia has put tremendous stress on water requirements. The Elgo River in southern Ethiopia is deteriorating due to sedimentation, soil erosion, stormwater runoff, and anthropogenic activities. Elgo village faces water shortages and a lack of safe drinking water. The purpose of this research was to identify the extent of pollution in Elgo River water using the Canadian Council of Ministers of the Environment (CCME), Water Quality Index (WQI), and Irrigation Water Quality Index (IWQI). A total of 12 water samples were collected from 3 river sampling sites for the dry and wet seasons to test the physicochemical and biological parameters. Results obtained were: turbidity (46.5–156) NTU, colour (103.65–606.5) TCU, EC (182–268) μS/cm, TDS (192.5–275.5) mg/l, TSS (680–2774) mg/l, Ca2+ (22–45) mg/l, Mg2+ (19.5–23.5) mg/l, Cl- (10.5–16.65) mg/l, and SO42- (17.18–47) mg/l for both the dry and wet seasons, respectively. The CCME WQI revealed that the overall results were 38.38 for the dry season and 36.6 for the wet season for drinking water parameters. The CCME WQI categorization indicates that the Elgo River water is classified as poor, with results ranging from 0 to 44. For irrigation purposes 10, parameters such as SAR, PS, PI, MAR, KI, RSC, EC, SSP, TH, and %Na were examined to compute indices using the IWQI model. The overall result of water quality indicated that IWQIs of 81.4 and 62.14 are good for the dry season and poor for the wet season, respectively. This research provides a thorough analysis through modelling to determine the suitability of water for different purposes for the tribal and backward communities of the area.

Mechanistic interaction between climate variables rainfall and temperature on surface water quality and water treatment costs at the Barekese Headworks, Ghana: A time series analysis and water quality index modelling approach

Extreme rainfall and temperatures are climate variables that threaten global water supplies and surface water quality (SWQ). To understand how rainfall and temperature interact with surface water quality and water treatment costs, this study, unlike previous ones, uses time series analysis (TSA) and water quality index (WQI) modelling to fill significant research gaps. The study uses data from the Barekese Water Treatment Headworks, Ghana. Water quality data from 2000 to 2019 for the Barekese Headworks were obtained from the Ghana Water Company Limited. Rainfall data for the catchment was obtained from the Ghana Meteorological Agency. The Mann-Kendall statistical test for trend and the Canadian Council of Ministers of the Environment (CCME) water quality index was applied to data sets. The Mann-Kendall trend test showed no significant change in annual temperatures. An increasing trend for annual rainfall was observed, but this was not statistically significant (Z = 0.21). Sen's slope estimator (Q) showed that rainfall increases at 3.03 mm annually. pH correlated negatively with rainfall (r = - 0.15). Correlations were observed between rainfall and temperature and dissolved oxygen (DO), turbidity, Total Dissolved Solids (TDS), Nitrate (NO3−), Phosphate (PO43−), and Manganese (Mn). Rainfall was observed to increase the cost of liming, coagulation, and disinfection. A 20.26% deterioration in SWQ was observed from 2009 to 2019. The SWQ over the period under study and according to the CCME water quality index was 80% marginal, 10% fair and 10% poor. The findings reveal that the concurrent use of TSA and WQI modelling can help elucidate how rainfall and temperature interact with SWQ and water treatment costs. It further contributes knowledge to attaining the Africa Union Agenda 2063 on climate resilience and the Sustainable Development Goals (SDG) 6 and 6.3 on universal water access and quality improvement.

Preliminary study of fungi from mangrove sediments as a bioremediation agent of lead (Pb) heavy metal

The mangrove ecosystem in Tapak Village is one of the coastal areas in Tugu District, Semarang, Central Java and close to the industrial area. This mangrove ecosystem presumed to be contaminated by heavy metals. This study aims to analysis of lead heavy metal in Tapak, isolate fungi from mangrove sediments, and identify the potential fungus according to molecular approach. The sampling method used a purposive random sampling method with 4 sampling points. The isolation of fungi was carried out using the dilution method and then cultured on the general Potato Dextrose Agar (PDA) media. The purified isolates were tested its ability as a bioremediation agent of lead heavy metal (Pb) and were identified molecularly using ITS1 and ITS4 as universal primers. The results of the analysis of the Pb content in the sediment samples using the Atomic Absorption Spectrophotometer (AAS) ranged from 59.07-76.76mg/Kg, where these results exceeded the CCME (Canadian Council of Ministers of the Environment) quality standards, 2001, with Pb standards of 35mg/Kg. Based on the screening of fungal isolates on media supplemented with (Pb) of 70 ppm, a total 18 isolates were purified. There were 9 isolates with the fastest growth in observations for 7 days. One of the 9 fastest-growing isolates, MT.1.E, was identified molecularly using Internal Transcribe Spacer (ITS) region and the homology was closely related to Aspergillus fumigatus which has a 100% similarity. According to this study, fungi can be proposed as a bioremediation agent.

Characterization of Paper Mill Effluent and Its Impacts on the Environment

he study aimed to characterize paper mill effluents and determine the quality of surface water in the vicinity of the paper mills using a water quality index to understand the pollution level due to the discharge of untreated effluents. Physicochemical parameters and CCME (Canadian Council of Ministers of the Environment) Water Quality Index (WQI) were used to estimate the degree of pollution in the selected paper mills area in Bogura District of Bangladesh. Moreover, a public perception survey was conducted in the study area to illustrate the present scenario regarding paper mill effluent discharge. The analytical results revealed that the concentrations of TSS, EC, COD, BOD5, phenols, K, and NO3 – N were higher than the permissible limit, and the DO level was below the ECR 1997 standard. However, there was no concentrations of heavy metals exceeded the permissible level. The FTIR analysis showed the presence of several toxic pollutants, including lignin, phenol, and halo compound. The CCME WQI showed that sites S-1 and S-2 were ranked as marginal, while site S-3 was ranked as fair. The study observed that the discharge of untreated paper mill effluent has the potential to cause harm to aquatic life and the environment.

Soil contamination in community gardens of Philadelphia and Pittsburgh, Pennsylvania.

Community gardens have been seen sprouting up in and around urban settings such as Philadelphia and Pittsburgh over the past several decades. Due to the long histories of industrial activities and urbanization, these soils in urban regions may be at a high risk for various contaminants such as metals and metalloids. Using inductively coupled plasma mass spectrometry (ICP-MS), we measured 7 elements (lead (Pb), zinc (Zn), copper (Cu), vanadium (V), cadmium (Cd), nickel (Ni), and arsenic (As)) in soil samples collected from a total of 21 community gardens in Philadelphia City, Philadelphia suburban areas, and Pittsburgh City during September and October 2021. We found that the city areas in Philadelphia and Pittsburgh had higher elemental concentrations in community garden soils compared to the suburbs. We found that all elements except vanadium were below the Pennsylvania Department of Environmental Protection (PADEP) guidelines. When compared to more stringent Canadian Council of Ministers of the Environment (CCME) guidelines of a maximum of 140mg/kg of lead in the soil, 36% percent of Philadelphia community gardens, 60% of Pittsburgh gardens, and 20% of the Philadelphia suburb gardens exceeded the CCME guideline. In Philadelphiacity, generally, elemental concentrations exhibited a negative trend with increasing distance to historical smelter locations, although a significant correlation was observed for only zinc. We found that the soil from the raised beds had lower concentrations of lead and arsenic, but many of the samples from the raised beds had higher concentrations of zinc, copper, vanadium, and nickel. This discrepancy in raised beds is most likely attributed to these elements being actively deposited in the soil from present day sources such as vehicles on the road and active industrial sites. Understanding and recognizing such variations of these contaminants in community gardens are essential to understanding how industrial legacies and modern pollution continue to put urban communities at a disproportionate risk of health impacts.

Assessment of potability of surface water and its health implication in Mahanadi Basin, Odisha

Surface water resource plays a crucial role in economic development, human health, and ecological diversity. Population growth, climate change, and water contamination that result from rising residential, agricultural, and industrial needs have put a great deal of strain on the Mahanadi River in Odisha. The study was conducted to analyse surface water quality fluctuations using monitoring data of 20 water quality indicators at 19 locations during 2012–2022. The proposed work includes Weighted Arithmetic (WA) Water Quality Index (WQI), Canadian Council of Ministers of the Environment (CCME) WQI, Synthetic Pollution Index (SPI), Numerow's Pollution Index (NPI), Overall Index of Pollution (OIP), Comprehensive Pollution Index (CPI), Eutrophication Index (EI), Organic Pollution Index (OPI) and multivariate techniques like Cluster analysis (CA) and Principal Component Analysis (PCA) to analyse surface water quality. The results showed that the surface water was contaminated with high TC and TKN. The WQIs results demonstrated that the categories of excellent, good, poor, extremely poor, and unsuitable water quality that fluctuated at the chosen sampling points. Most of the locations fell into the excellent to good zone, as determined by the WQIs and Pollution indexes (PIs). According to several indexing methods, the results show that WA WQI (15.79%), CCME WQI (10.53%), SPI (15.79%), NPI (15.79%), OIP (15.79%), and CPI (15.79%) of the samples had poor, extremely poor, or unsuitable drinking water quality. The watercourse was highly susceptible to eutrophication at few locations as EI was above zero. Three locations (sites 8, 9 and 19) at the downstream of the river are polluted with organic substances with OPI > 1. To examine the link between the water quality measures, the correlation matrix has been developed. To find out the commonalities in the features of the water quality, hierarchical CA divided the 19 monitoring sites into three groups. Five principal components (PCs), which together account for 93.91% of the total variance, were identified via PCA. The first PC was devoted to mineralization, whereas the remaining PCs were constructed using characteristics that suggested contamination. To investigate the spatial distribution, the spatial analyst tools (IDW method) were used. Combining results with GIS also allows for a deeper analysis of drinking water quality. Ultimately, the combined use of various water quality indices along with GIS, CA, and PCA results in the conclusion that samples from the locations ST-8, ST-9 and ST-19 are the most prevalent and fall into the poor to extremely poor group. Considering the entire study, it was determined that the polluting factors were the fertilizers, land development, storm water runoff, and domestic waste water discharge. It is recommended that the sources of contaminations can be further explored to reduce the pollution load, that might be helpful in the promotion of sustainable ecotourism.

Evaluation of River Water Quality Index Using Remote Sensing and Artificial Intelligence Models

To restrict the entry of polluting components into water bodies, particularly rivers, it is critical to undertake timely monitoring and make rapid choices. Traditional techniques of assessing water quality are typically costly and time-consuming. With the advent of remote sensing technologies and the availability of high-resolution satellite images in recent years, a significant opportunity for water quality monitoring has arisen. In this study, the water quality index (WQI) for the Hudson River has been estimated using Landsat 8 OLI-TIRS images and four Artificial Intelligence (AI) models, such as M5 Model Tree (MT), Multivariate Adaptive Regression Spline (MARS), Gene Expression Programming (GEP), and Evolutionary Polynomial Regression (EPR). In this way, 13 water quality parameters (WQPs) (i.e., Turbidity, Sulfate, Sodium, Potassium, Hardness, Fluoride, Dissolved Oxygen, Chloride, Arsenic, Alkalinity, pH, Nitrate, and Magnesium) were measured between 14 March 2021 and 16 June 2021 at a site near Poughkeepsie, New York. First, Multiple Linear Regression (MLR) models were created between these WQPs parameters and the spectral indices of Landsat 8 OLI-TIRS images, and then, the most correlated spectral indices were selected as input variables of AI models. With reference to the measured values of WQPs, the WQI was determined according to the Canadian Council of Ministers of the Environment (CCME) guidelines. After that, AI models were developed through the training and testing stages, and then estimated values of WQI were compared to the actual values. The results of the AI models’ performance showed that the MARS model had the best performance among the other AI models for monitoring WQI. The results demonstrated the high effectiveness and power of estimating WQI utilizing a combination of satellite images and artificial intelligence models.

Effects of rainfall characteristics on runoff quality parameters within an industrial sector in Tennessee, USA

The relationship between rainfall characteristics and pollutant discharge has rarely been investigated in industrial sectors. To address this need, we investigated the pollutant concentrations of surface runoff and the correlation between pollutant discharge and rainfall characteristics using the self-reported stormwater quality data collected under the Tennessee Multi-Sector Permit program for two industrial facilities in West Tennessee. The variation of certain stormwater quality parameters over this period was utilized as an indicator to evaluate the effectiveness of control measures implemented at these two facilities. Furthermore, the Water Quality Index (WQI) as an indicator to assess the temporal changes in stormwater quality at industrial facilities was determined using the Weighted Sum (WSM) and Canadian Council of Ministers of the Environment (CCME) methods. The principal component analysis (PCA) and Pearson correlation coefficient were utilized to understand the correlation between runoff quality parameters, rainfall characteristics, and the sources of pollutants. The results demonstrated lower WQI indices using the WSM method compared to the CCME method. The data analysis revealed that 93.1%, 100%, 86.2%, and 48.3% of Al, Mg, Cu, and Fe experienced a concentration greater than the benchmark level, respectively. There was a significant relationship between Total suspended solids (TSS) and Al, Chemical Oxygen Demand (COD), Fe, oil and grease (O&G), and Zn concentrations. As a result, TSS could be a priority pollutant for designing various best management practices (BMPs) and low impact developments (LIDs). The result of the PCA and Pearson correlation coefficient showed that Al concentration made a significant correlation with the rainfall depth and rainfall duration. This analysis also illustrated that biochemical oxygen demand (BOD5), COD, and O&G concentrations were highly correlated with antecedent dry days (ADDs). However, pH was more related to rainfall depth and rainfall intensity. This study informs both regulatory agencies and industry stakeholders regarding the importance of evaluating self-reported stormwater quality data.

Spatiotemporal Variations in Water Quality of the Transboundary Shari-Goyain River, Bangladesh

This study aimed to investigate the seasonal and spatial variations in water quality parameters and determine the main contamination sources in the Shari-Goyain River, Bangladesh. Therefore, surface water was sampled monthly from six sampling sites, where six water quality parameters were evaluated. Data were analyzed by applying the Canadian Council of Ministers of the Environment (CCME) water quality index (WQI) and multivariate statistical methods. The results reveals that most of the examined water quality parameters crossed the acceptable range, and significant variations were observed spatiotemporally (p < 0.05). Based on the CCME WQI value, the water quality of the river is classified as poor to marginal with a score range between 33.40 and 51.30. This range of values demonstrates that the river’s water quality is far from desirable for aquatic life and that it is being impacted and deteriorated by external drivers. Principal component analysis (PCA) retained two principal components (Factors 1 and 2), explaining about 79.17% of the total variance in the studied parameters and identified acidic pollution sources. Cluster analysis also reveals relative differences in water quality throughout sites and seasons, which supported the CCME WQI and PCA. Finally, Kruskal-Wallis one-way analysis of variance by ranks has identified coal mine drainage (CMD) as the main pollutant source for the Shari-Goyain River. In order to mitigate the CMD impact on land and water, different nature-based solutions are proposed, particularly passive mine water treatment approaches through constructed wetlands that could also mitigate the transboundary waters problem.

Assessment of Shatt Al-Arab Water Quality Using CCME/WQI Analysis in Basrah City of South Iraq

The Water Quality Index (WQI) is an important parameter in describing the water resources' suitability for human uses and is one of the most effective methods of describing water quality and indicative of assessing water quality and suitability for human utilization and the health of ecosystems. WQI of the Canadian Council of Ministers of the Environment (CCME) was used in the study to describe the Shatt al-Arab water quality in Basrah Southern Iraq, and its suitability for drinking use. The data for analyzing river water samples were adopted from five stations along the river every month during the years from 2014 to 2018 by the Iraqi Ministry of Environment, as it included the measurement of acidity function PH, Dissolved Oxygen DO, phosphorous PO4, nitrate NO3, Calcium Ca, potassium K, magnesium Mg, sodium Na, Total Hardness TH, sulfates SO4, chlorides Cl, Electrical Conductivity EC, Total Soluble Salts TDS, and Alkalinity ALK. The distributions of water quality index values along the river were mapped by GIS techniques. Study results were referring to illustrate the poor level of the water quality status of Shatt al-Arab in all study periods at all monitoring stations. The reason for this is due to the deterioration of fresh water quality drained from the Tigris and Euphrates, and the provision of salt wedges from the Arabian Gulf. However, with the continuous discharge of sewage water, industrial and oil effluents and sewage discharged from urban areas, the water quality of Shatt al-Arab was declined during the study period.

Water Quality Assessment of Karnaphuli River of Bangladesh Using CCME-WQI Method

Karnaphuli River is one of the largest recipients of industrial effluent among all the rivers in Bangladesh in the last couple of years. The main purpose of this study is to evaluate the suitability of the river water for irrigation, livestock and other uses and to identify the main pollutants affecting the river during its course through the city. Ten Sampling points along with the Karnaphuli river basin was selected for the WQI assessment. The sampling was conducted for a period of one year from May 2021 to April 2022. Canadian Council of Ministers of the Environment (CCME)-(WQI) Water Quality Index was applied for several water quality parameters namely pH, Total Dissolved Solids (TDS), Dissolved Oxygen (DO), Phosphate, Nitrate, Chloride, Total Hardness, Conductivity, Biological Oxygen Demand (BOD), Cd, Cu, Zn, Pb. Irrigation and livestock indices were analyzed based on Canadian Water Quality Guidelines (CWQGs). The study shows that the river water is mostly alkaline and the pH lies between 6.4 -7.8. The DO value varies from 1.8 to 6 ppm and BOD varies from 1.7 to 3.4 ppm. The concentrations of Cu, Cd, Pb and Zn are Cu- (0.108-0.743 ppm), Cd- (0.073-0.281 ppm), Pb- (0.017-0.699 ppm), Zn- (0.012-0.032 ppm) respectively. Based on the index values, the river water quality has been observed as poor and marginal.

Assessment of deep aquifer groundwater quality in a geographically unique climatic region of Southern Western Ghats, India using water quality indices

AbstractWater quality index (WQI) models are generally used in hydrochemical studies to simplify complex data into single values to reflect the overall quality. In this study, deep groundwater quality in the Chittur and Palakkad Taluks of the Bharathapuzha river basin of Kerala, India, was assessed by employing the WQI method developed by the Canadian Council of Ministers of the Environment (CCME). The assessment of overall water quality is indispensable due to the specific characteristics of the study area, such as geography, climate, over‐drafting, and prevalent agricultural practices. Forty representative samples were collected from the study area for monsoon (MON) and pre‐monsoon (PRM) seasons. The results showed a general increase of contents from MON to PRM. The major cations were spread in the order Ca2+>Na+>Mg2+>K+ and the anions HCO3−>Cl−>CO32− based on their relative abundance. Among various parameters analysed, alkalinity and bicarbonate levels during MON were comparatively high, which is indicative of carbonate weathering, and 90% of the samples failed to meet the World Health Organization (WHO, 2017)/Bureau of Indian Standards (BIS, 2012) drinking water guidelines. The CCME WQI analysis revealed that nearly 50% of the samples during each season represented good and excellent categories. The samples in the poor category comprised 10% in MON and 15% in PRM. The overall WQI exhibited 15% of poor category samples as well. The spatial depiction of CCME WQI classes helped to expose zones of degraded quality in the centre to eastward parts. The spatial and temporal variations of CCME WQI classes and different physicochemical attributes indicated the influence of common factors attributing to the deep groundwater quality. The study also revealed inland salinity at Kolluparamba and Peruvamba stations, where agricultural activities were rampant with poor surface water irrigation.

Assessment of the supplied water quality for Sulaimani, Iraq as a case study using CCME method

Water quality index (WQI) is an important technique used for the evaluating and classifying water quality of supplied water, by summarizing large number of parameters from the result of variety tests of water into less number and terms Water quality index (WQI) value can be determined. Management of water quality is not so easy and simple, it needs to work with a lot of data. In this study evaluating of water quality of (Sulaimani city, KR, Iraq) is presented by using Canadian Council of Ministers of the Environment (CCME). The study conducted by monitoring long term water quality data over past eleven years, collected from 17 sampling points, tanks from which potable water supplied to all of the city residents, located in the (Sulaimani city, KR, Iraq). To obtain the CCME WQI value twelve parameters used : PH, Total dissolved solid (TDS), Chloride (Cl-1), Calcium (Ca), Sodium (Na), Potassium (K), Magnesium (Mg), Total hardness (TH), Total Alkalinity, Chloride (Cl2), Electric conductivity (EC), Sulphate (SO4-2).The obtained patterns present different water quality situations, WQI values ranged from good to excellent, based on the result obtained and analyzed using the from of WQI, it is revealed that the value of WQI ranged from (82) to (94) over the past 11 years, it means the main source of water supplied to the city which is Dokan lake is relatively high and clean as it is over a mountain watershed area.

Evaluation of the Water Quality of River Kaduna, Nigeria Using Water Quality Index

Water is a natural resource of fundamental importance and supports all life forms. The study evaluated the water quality of River Kaduna using the Canadian Council of Ministers of the Environment (CCME) Water Quality Index. The study covered both raining and dry seasons in 10 sampling points. Water parameters analysed were turbidity, Zn, Pb, Cd, Cr, Cu, Mn, Fe, dissolved oxygen, electrical conductivity, pH, TDS and Ni using standard laboratory techniques. The data obtained were used to develop Water Quality Index (WQI) across the 10 sampling points and results showed that the water quality at Barnawa, Kudenda, Tudun Wada, Makera and Angwan Muazu are poor as their index values ranged between 31.8 – 42 while Kawo, Angwan Dosa, Malali, Kigo and Angwan Rimi are marginal as their index ranged between 45 – 61.3. The study concluded that the variety and level of contaminants in River Kaduna was related to the anthropogenic activities in the various parts of Kaduna Metropolis from where run-off and contaminants were received, hence, the water quality of River Kaduna is deteriorating. There is therefore the need for proper environmental education and discouragement in the use of toxic chemicals for farming so that pollution can be controlled at the source.

Comparative assessment of water quality indices-a case study to evaluate water quality for drinking water supply and irrigation in Northern Mexico.

Water quality indices (WQIs) are numerical measures used by researchers and water managers to communicate water quality status to the public. This study analyzes the official databases from the CONAGUA monitoring network of the main tributary rivers in the middle basin of the San Pedro-Mezquital River in Durango, Mexico, for a 6-year period (2013-2018). We applied three WQIs to 432 data (18 sampling sites, four samples per year, 6years): Canadian Council of Ministers of the Environment (CCME) WQI, National Sanitation Foundation (NSF) WQI, and Secretariat of Urban Development and Ecology (SEDUE) WQI. The Canadian index proved to be a flexible, appropriate, and rigorous methodology for assessing water quality based on its use. Results classify the water quality in the studied reservoirs as good, while river water was rated for public use, as marginal to very poor. No statistical significant differences in the quality of water between the rainy (June-October) and dry (November-May) seasons were found. However, tendency shows that in the rainy season the water quality was lower, mainly attributed to agricultural runoffs and bank erosion. The main contamination problem was the presence of fecal coliforms in high concentrations, which is associated to the high population density in the area, low sanitation efficiency, and multiple non-point discharges.

Evaluating the Performance of Water Quality Indices: Application in Surface Water of Lake Union, Washington State-USA

Water quality indices (WQIs) are practical and versatile instruments for assessing, organizing, and disseminating information about the overall quality status of surface water bodies. The use of these indices may be beneficial in evaluating aquatic system water quality. The CCME (Canadian Council of Ministers of the Environment) and NSF (National Science Foundation) WQIs were used for the assessment of surface water (depth = 1 m) in Lake Union, Washington State. These WQIs were used in surface water at Lake Union, Seattle. The modified versions of the applied WQIs incorporate a varied number of the investigated parameters. The two WQIs were implemented utilizing specialized, publicly accessible software tools. A comparison of their performance is offered, along with a qualitative assessment of their appropriateness for describing the quality of a surface water body. Practical conclusions were generated and addressed based on the applicability and disadvantages of the evaluated indexes. When compared to the CCME-WQI, it is found that the NSF-WQI is a more robust index that yields a categorization stricter than CCME-WQI.

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

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

Examining the Effect of Spatial Proximity of Geo-located Dumpsites on Groundwater Quality in Samaru-Nigeria

The effect of improper waste disposal on man’s health and environment due to the closeness of solid waste dumpsites to underground water sources in some parts of the world has raised issues of serious concern. This study thus sought to examine groundwater quality dependence on the spatial proximity of dumpsites in Samaru, Kaduna state-Nigeria. The coordinates of 10 solid waste dumpsites in proximity to groundwater sources (boreholes) in the study area were acquired for spatial analyses with a GPS-enabled smartphone. Ten groundwater samples from boreholes in relation to dumpsites were collected for testing and analyses of 11 physical and chemical parameters of water quality based on the Canadian Council of Ministers of the Environment (CCME) and World Health Organisation (WHO) standard limits. Thereafter, the water quality index (WQI) for all the locations was calculated. The results of the spatial proximity analyses carried out revealed that the requirement for locating dumpsites was not met as specified by the Environmental Protection Agency (EPA) regarding the minimum safe distance from groundwater sources as a majority (about 80%) of the dumpsites were located too close to the boreholes. The results of the study, however, revealed that the majority (about 80%) of the groundwater samples met the conditions for good drinking water (suitable for drinking water) even with their closeness to the dumpsites based on the computed WQI values and ratings. Meanwhile, only Calcium, Dissolved Oxygen, and Biochemical Oxygen Demand concentrations were significantly affected (p < 0.05 at the 95% significance level) by the closeness of the solid waste dumpsites to the boreholes with very strong (R2 = 86%) and strong (R2 = 79%) relationships, respectively. Suggestions were nonetheless made for the monitoring of land use activities in the areas surrounding groundwater sources to prevent groundwater contamination.

Water Quality Index (WQI) of Shitalakshya River Near Haripur Power Station, Narayanganj, Bangladesh

The present investigation is aimed at understanding the water quality parameters and the findings of a water quality index (WQI) to assess the characteristics of the Shitalakshya River near Haripur power station, Narayanganj for five different years (2013-2018) considering monsoon, pre-monsoon, post-monsoon seasonal variations. In this study, three different methods were used to evaluate the WQI named as; Weighted Arithmetic Index Method, Canadian Council of Ministers of the Environment (CCME) WQI Method and National Sanitation Foundation (NSF) Method. Essential parameters i.e. dissolved oxygen, pH, chloride, turbidity, color, biochemical oxygen demand, total dissolved solids, Silica, Iron, electrical conductivity, Phosphate were considered for calculating the WQI. According to Weighted Arithmetic Index Method, the WQI value varied from 80 to 286 for the last five years. From the National Sanitation Foundation Method, the WQI value was found within 36 to 56 for the study duration. The WQI value was varied from 3 to 16 according to the Canadian Council of Ministers of the Environment Water Quality Index Method. Based on WQI values, the Shitalakhya river water was being classified as poor water for the above-mentioned different years. Among the different parameters, mostly turbidity, electrical conductivity, TSS, Iron were the parameters that caused the situation worst. Journal of Engineering Science 12(3), 2021, 45-55