Water Quality Characteristics Research Articles

Seasonal Variations in Groundwater Quality under Different Impacts Using Statistical Approaches

The objective of this study was to evaluate seasonal fluctuations in groundwater quality, determine the effects of different stressors on this resource, and recognize the potential pollution sources in a coastal region of southern Vietnam. Eleven samples collected in Ben Tre province during the dry and wet seasons were then analyzed for sixteen parameters, including pH, total dissolved solids (TDS), salinity, total hardness (TH), ammonium (NH₄⁺-N), nitrite (NO₂ˉ-N), nitrate (NO₃ˉ-N), sulfate (SO₄²ˉ), chloride (Clˉ), iron (Fe), manganese (Mn), lead (Pb), mercury (Hg), arsenic (As), coliforms, and Escherichia coli (E. coli). Pearson correlation analysis, principal component analysis (PCA), and cluster analysis (CA) were employed. The results indicated that total dissolved solids, salinity, total hardness, Clˉ, E. coli and coliform were detected as contaminants in groundwater samples. The trend of fluctuations in the parameters was mostly higher in the dry season. Which Mn and coliform significantly fluctuated between the dry and wet seasons. Activities in industrial-craft areas, landfills and seawater-intruded areas negatively impacted groundwater quality, typically TDS in industrial-craft areas, coliform and E.coliat the landfill area. Six principal components obtained from PCA could explain 93.6% of the variance, and all parameters are responsible for variations in groundwater quality. Geology, discharged wastewater, landfill leachate, agricultural activities, and saltwater intrusion can be considered representative factors. CA grouped the collected samples into four clusters based on the similarity in water properties. The analysis results showed that the locations in each cluster have outstanding water quality characteristics, clusters I and III have high TDS characteristics, cluster II has coliforms, and cluster IV sets of locations with high salinity. This study is promised to partially fill the gap in comprehensive information on groundwater quality in the coastal province so that policymakers can develop sustainable water management strategies in the future. Doi: 10.28991/CEJ-2023-09-03-01 Full Text: PDF

Analysis of Mixing Patterns of River Confluences through 3D Spatial Interpolation of Sensor Measurement Data

Aquatic environmental problems, such as algae, turbid water, and poor oxygen content, have become increasingly common. In river analysis, hydrological and water quality characteristics are used for evaluating aquatic ecological health, which necessitates continuous monitoring. In addition, because measurements are conducted using a fixed measurement method, the hydrological and water quality characteristics are not investigated for the entire river. Furthermore, obtaining high-resolution data is tedious, and the measurement area and time are limited. Hence, low-resolution data acquisition is generally preferred; however, this requires an appropriate interpolation method to obtain a wide range of data. Therefore, a 3D interpolation method for river data is proposed herein. The overall hydraulic and water quality information of a river is presented by visualizing the low-resolution measurements using spatial interpolation. The Kriging technique was applied to the river mapping to improve the mapping precision through data visualization and quantitative evaluation.

Optimal sensor placement for the routine monitoring of urban drainage systems: A re-clustering method

The construction of an efficient monitoring network is critical for the effective and safe management of urban drainage systems. This study developed a re-clustering methodology that incorporates additional perspectives beyond node similarity to improve the traditional clustering process for optimal sensor placement. Instead of targeting event-specific water quality or hydraulic monitoring, the method integrates the water hydraulic and quality characteristics of nodes in response to the demand for routine monitoring. The implementation of this method first applies model simulation to generate the attribute datasets required for clustering analysis, and then re-clusters the initial clustering result according to the constructed re-clustering potential indices. And the information theory-based evaluation metrics were introduced to quantitatively assess the sensor deployment scheme obtained by amalgamating the two clustering results. Two networks with different drainage systems and sizes were chosen as case studies to illustrate the application of the framework. The results demonstrate that the clustering process enables to expand the information contained in the monitoring network, and that the re-clustering strategy can generate more comprehensive and practical solutions upon this basis.

Research on Water Quality Assessment Using the Water Quality Index for the Eastern Route of the South-to-North Water Diversion Project

The South-to-North Water Diversion Project’s Eastern Route (SNWDPC-ER) has drawn a lot of attention as one of China’s most significant water diversion projects. This study calculated the water quality index (WQI) to analyze the spatial and temporal characteristics of water quality in the study area as well as the effects of water diversion, and developed the minimum water quality index (WQImin) model based on stepwise multiple linear regression, using data from 56 monitoring stations along the delivery canal of the SNWDPC-ER (the SNWDPC-delivery ER’s canal) from 2014 to 2018. Here are the findings: (1) The water quality state was rated as “good” and the annual average value of WQI climbed year over year along with improvements in water quality. (2) There was a clear difference in water quality across time and space, with autumn having better water quality than other seasons and the south having better water quality than the north. (3) Water quality is impacted by water diversion; throughout the era of diversion, water quality was steadier. (4) The weighted WQImin model, which is a quick and inexpensive way to assess water quality, can be used to evaluate the water quality in the SNWDPC-delivery ER’s canal. The model’s parameters are DO, NH3-N, BOD5, and TN.

Water quality characteristics and evaluation of Qilian Mountain National Park section in Heihe River Basin based on water quality indices and 3D fluorescence technology.

The water quality of the Heihe River Basin affects the life quality and health of tens of thousands of residents along it. However, there are relatively few studies that evaluate its water quality. In this study, we used principal component analysis (PCA), an improved comprehensive water quality index (WQI), and three-dimensional (3D) fluorescence technology to identify pollutants and evaluate water quality at nine monitoring sites in the Qilian Mountain National Park in Heihe River Basin. PCA was applied to concentrate the water quality indices into nine items. The analysis shows that the water quality in the study area is mainly polluted by organic matter, nitrogen, and phosphorus. According to the revised WQI model, the water quality of the study area is from moderate to good, while the water quality of Qinghai section is worse than that of Gansu section. According to the 3D fluorescence spectrum analysis of the monitoring sites, the organic pollution of water comes from vegetation decay, animal feces, and some human activities. This study can not only provide support and basis for water environment protection and management in the Heihe River Basin, but also promote the healthy development of the water environment in the Qilian Mountains.

Research Progress of High-Salinity Wastewater Treatment Technology

With the continuous expansion of industrial enterprises, a large amount of high-salt wastewater with complex components is produced. Direct discharge will cause great harm to the ecosystem and waste a large amount of potential salt resources. This paper summarizes the source, water quality characteristics, and environmental impact of high-salinity wastewater, and introduces the desalination and treatment technologies of high-salinity wastewater. The desalination technology of high-salinity wastewater mainly includes two processes: concentration and crystallization, obtaining concentrated solution through membrane concentration or thermal concentration and then carrying out crystallization treatment on the concentrated solution, thereby realizing the recovery of salt. The advanced treatment technologies of high-salinity wastewater were analyzed, including physicochemical treatment, biological treatment, and coupling treatment. Catalytic ozonation is one of the most widely used physicochemical technologies for the advanced treatment of high-salinity wastewater. Biological treatment processes operating in the presence of halotolerant bacteria show excellent performance at high salinity. High salinity has a negative impact on the performance of various physicochemical processes and biological treatment technologies. However, high salinity has little effect on the performance of a coupled system designed to treat high-salinity wastewater. In this review, the effect of salinity on the scaling and corrosion of equipment is also illustrated. It is suggested that the research direction of high-salinity wastewater should be to develop new membrane materials and catalysts, develop salt-tolerant microorganisms, explore high-efficiency and energy-saving physico–chemical–biochemical combination processes, improve the treatment efficiency of high-salinity organic wastewater, and reduce treatment costs.

Treatment of Surface Water Runoff in Igala-Mela, Kogi State Nigeria Using Local Materials

Purpose: Water is life and majority of the sicknesses in the world today is either contracted through water or air. There is need to reduce the spread of these diseases that spread by lack of drinkable water available to people. Some areas in Nigeria experiences scarcity of water fit for domestic use, such areas as Igala-Mella area of Kogi State and extended to environs in Nnsuka Enugu State faces this challenge of access to safe water. Most people in the study area obtain drinking water from storm water which is polluted by dust and animal droppings. In view of this, this study is geared to harvesting the storm water, fabricate mini pilot plant, and use locally available material and extract of neem tree which serves as antibacterial to kill the bacterial present in the water.
 Methodology: The pilot plant was fabricated to allow the flow of water under gravity. It has the storage, aeration, chemical inject, stirrer formulated and the filter bed. All the material used were sourced locally. The raw water was fed into the storage, opened to allow to flow through the stages as arranged in the mini pilot plant with the neem extract added. At the end, the treated water was collected. The raw water was tested before treatment to determine the level of contamination. After treatment, the pure water was subjected to quality test.
 Findings: The result shows that there is an improvement in the water quality characteristics as there is reduction in the color, taste, PH, other chemicals such as; Zn, Fe, Nitrate, Nitrite, Potassium, Nitrogen, Phosphate, Cadmium, Lead were reduced after test. Bacteriological test such as oxygen demand, biochemical oxygen demand, shegella, salmonella sp shows reduction in the treated water.
 Unique Contribution to Theory, Policy and Practice: This shows that with mini pilot plant and the extract can be used to treat raw water at household level using this mini plant and the neem tree extract.

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

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

Proposal for a new customization process for a data-based water quality index using a random forest approach

As the water quality index (WQI) represents water quality, it is crucial to customize the WQI for a specific purpose. In this study, to better represent water quality data using WQI, a random forest (RF) approach was used to derive the parameter weight and calculate the WQI according to the watershed and its use. Eight parameters (water temperature, dissolved oxygen, pH, electrical conductivity, suspended solids, total nitrogen, total phosphorus, and total organic carbon) were evaluated using a total of 220,103 data points collected from 900 monitoring sites throughout South Korea between 2011 and 2020. The estimation of parameter weights, key elements in developing the WQI model, was performed through the variable importance estimation method that can be derived from the RF model. The parameter weights were derived based on various spatiotemporal datasets, and it was confirmed that the spatiotemporal differences in weights according to data characteristics represented the regional and seasonal water quality characteristics. Consequently, a customized WQI representing water quality characteristics could be calculated using data-based weights, and it is expected that a data-based customized WQI could be developed to better match the previous WQI to the purpose and target source.

A proposed reporting framework for microplastic-metal mixtures research, with emphasis on environmental considerations known to influence metals.

In recent years, there has been an increase in research to understand the consequences of microplastic contamination. A subset of this research assesses the interaction of microplastics with metals and the subsequent effects of the resulting microplastic-metal complexes in freshwater environments. While our understanding of how microplastics behave in freshwater remains largely unknown, our knowledge of metal behavior in those same environments is well-established. The behavior (partitioning, speciation, bioavailability) of metals is highly dependent on environmental characteristics, including water quality variables such as hardness, pH, and dissolved organic matter. This study reveals that despite our understanding of metal behavior, there is little consideration for these influential factors in the current body of microplastic-metal research. Multiple instances highlighted throughout this study show that even when similar plastic, metal, and biota are utilized, there are conflicting observations as to whether the mixture is toxic; we stress that without adequate reporting of environmental conditions, these contradictions are likely to persist without explanation. Through justification of water quality characteristics known to influence metal behavior, this study proposes a framework of reporting requirements for all future microplastic-metal research.

Water pollution indexing and health risk assessment due to PTE ingestion and dermal absorption for nine human populations in Southeast Nigeria

Traditional human health risk assessment (HHRA) methods are now being replaced with advanced codes. In the present study, HERisk code and water pollution index (WPI) were employed for HHRA and water quality characterization of Umunya, a suburban in Nigeria. This study stands out from previous HHRAs performed in the region by applying the novel HERisk code, which evaluates health risk for nine human populations. The goal of this study was to provide a comprehensive report that will enlighten inhabitants and policymakers on the potential dermal and oral risks associated with the use of metal-contaminated water resources, for various age brackets, in the region. Standard methods were employed. With respect to measured physicochemical parameters, the WPI revealed that 66.7% of the water resources were unsuitable for human use. Based on the HERisk code, potentially toxic elements (PTEs) increased cancer risks in the following order: Ni > Pb > Cr. Total non-carcinogenic risks of drinking the water was found to be moderate. However, the cumulative risks due to dermal absorption of the contaminated water were negligible. The overall trend observed from the HHRA showed that older human populations in the area are less susceptible than younger populations. Nevertheless, it was detected that humans between ages 21 and 65 were less vulnerable than those older than 65 years. The findings of the HERisk code and WPI had a strong agreement, as water samples deemed less fit for human use by the WPI proved to have more health concerns. The WPI and HERisk code indicated that the most influential PTEs in the water were Pb and Ni, respectively. Thus, both PTEs expose water users to a higher risk of developing cancer via water ingestion.

ECOLOGICAL WATER QUALITY

Water quality – is a description of water’s chemical and biological composition and physical properties, which characterize it as an abiotic component of aquatic ecosystem and determine its suitability for specific consumption purposes.
 Ecological water quality (environmental water quality) – refers to the ecological well-being of an aquatic ecosystem, with the main focus on protection of the aquatic environment and human life and health. It comprises a complex of physical, chemical, biological and other parameters reflecting specific features of abiotic and biotic components of aquatic ecosystems.
 The requirements for physical, chemical and biological properties of water are set in the water quality standards, which may be developed by particular countries or introduced by international organizations.
 Ecological water quality depends upon natural and human factors. Natural factors are in their turn divided into abiotic (for example, geological, meteorological, hydrological) and biotic (for example, the ratio of primary production and organic matter destruction). The main human factors affecting water quality include artificial modification of aquatic ecosystems’ hydrological conditions and their pollution with diverse chemical compounds.
 There are a lot of approaches to ecological water quality assessment according to both abiotic (physical and chemical) and biological parameters. Physical and chemical methods take into account such parameters as water transparency, suspended particulate matter concentration (turbidity), ion composition, water hardness, total dissolved salts content, nutrients and organic matter content, dissolved gases concentration, pH. Biological methods are based upon assessing the living organisms’ (biological indicators’) response to mineral and organic substances, present in water. Various living organisms can be used as biological indicators: algae, in particular – diatoms, higher aquatic plants, different species of aquatic invertebrates and fishes. While physical and chemical methods characterize water quality at the moment of sampling, biological methods provide an integral picture of water quality for a certain time period. Besides, biological methods are more informative, because they reflect the aquatic ecosystem’s response to pollution.
 On the whole, the most reliable data on ecological water quality can be obtained by combining physical, chemical and biological methods.

Assessment of the spatiotemporal water quality variations in the Middle Route of China's South-to-North Water Diversion Project by multivariate analysis.

As an important drinking water source for North China, the Middle Route of China's South-to-North Water Diversion Project (MRP) must provide high-quality water to maintain the health and safety of more than 60 million people. However, different water transfer operation modes may affect the water quality status, and the spatiotemporal characteristics of water quality in the MRP, with high water transfer volumes, remain poorly understood. In this study, the differences in water quality in the MRP between the initial stage (Nov. 2015 to Oct. 2017, low transfer volumes) and the current stage (Nov. 2017 to Oct. 2020, high transfer volumes) were compared, and the spatiotemporal water quality variations in the current stage were evaluated using multivariate statistical methods. For this purpose, approximately 12,528 observations, including the datasets of 12 water quality parameters collected from 29 monitoring sites, were used. The results showed that the water quality status improved significantly during the current stage. Based on principal component analysis (PCA), physical parameters (natural), nutrients, organic matter and microbes (anthropogenic), and heavy metals (natural and anthropogenic) were the key factors influencing water quality variations. Based on hierarchical cluster analysis, 12months were classified into two groups: the high-flow period (HFP, Jun.-Oct.) and the low-flow period (LFP, Nov.-May). Additionally, 29 sampling sites were grouped into three sections: the Henan section (HN; S1-S16), Hebei section (HB; S17-S24), and Tianjin-Beijing section (TB; S25-S29). From the perspective of water quality regulation, the total nitrogen concentration and permanganate index in the HB and TB sections of the MRP should be considered throughout the year, and the faecal coliform concentrations in these two sections should also be considered during the HFP. The results of this study could be helpful for local administrations to understand and control pollution and better protect the quality of water in the MRP.

Impact of land-use patterns on water quality characteristics of Rambiarrah stream in Kashmir Himalaya

ABSTRACT Water quality characterization of Himalayan streams that provide variety of ecosystem services including drinking water to zooming population is indispensable. In this background, water quality characterization of the Rambiarrah watershed was carried out from Autumn 2016 to Summer 2018, which revealed that all the drinking water quality parameters were within the prescribed limits of the World Health Organization (WHO) and Beauru of Indian Standards (BIS) except total coliform (TC) and fecal coliform (FC). Hierarchical Cluster Analysis (HCA) displayed 3 clusters, cluster I, II, III with least, moderate and high anthropogenic disturbance respectively. Principal component analysis (PCA) recognized 4 principal components (PCs) and explained a cumulative variance of 70.3%. Redundancy analysis (RDA) highlighted that agriculture, built-up, and plantation land-use classes explained 55% of the variance, while as 57% of the variance was highlighted by observable sensory features (waste disposal, sewage inflow and mineral extraction). The water quality index (WQI) varied from excellent to very poor water quality category. Physico-chemical parameters like pH, EC, TDS, TH, Ca2+, and Mg2+ decipher significant effective weights at upstream sites while as microbial load (TC and FC) highlighted significant effective weights at mid and downstream sites. The spatial–temporal pattern of water quality and aquascape landscape interrelationship identified in this study will contribute to the water quality management endeavor.

Habitat quality–physicochemical water quality–littoral macroinvertebrate community nexus in Lugo Lake (Ethiopia): Priorities for sustainable water resources management

AbstractThe integration of water quality characteristics with habplot‐based habitat quality assessment score (HabQA) has received little attention in ecological quality assessment studies. This study investigated the macroinvertebrate community structure in relation with lake habitat quality and physicochemical water quality variables in Lugo Lake (Ethiopia). Twelve sampling sites (eight agricultural and four recreational) were included. The variation among macroinvertebrates data was significantly explained by HabQA score and soluble reactive phosphorus. The study revealed the greater importance of habitat quality characteristics in comparison with the other conventional physicochemical characteristics on macroinvertebrate community structure. We strongly recommend the use of HabQA system while studying macroinvertebrate community structure for a deeper understanding of the environmental functioning of tropical lakes. The results suggested the need to apply integrated and sustainable protection and management of the lake catchment (including wetlands) to enhance the ecological integrity and hence biodiversity of lakes.

Research on scale inhibition law of high sulfate mine water based on response surface methodology

AbstractThe problem of scale inhibition in thermal power plants using mine water as circulating cooling water is a major focus of current engineering attention. Mine water in North China is predominantly high sulfate mine water, with mine water in Shanxi mines generally having a sulfate content of over 1000 mg/L. Currently, most thermal power plants blindly follow the previous scale inhibitor with carbonate scale as the main scale inhibition target, which leads to a large amount of sulfate scale in its circulating cooling system, which is difficult to remove after the formation of sulfate scale. On the basis of the experiments, the corresponding scale inhibition laws were studied using the response surface method for the water quality characteristics of high sulfate mine water. The scaling process on the heat exchange surface of the circulating cooling water system was simulated by the hanging sheet deposition method, and the quantitative analysis was carried out by the weight method. Using EDTMPS as an example, the scale inhibition law of sulfate‐type scale inhibitors for this type of mine water was systematically investigated. The experiments showed that the scale inhibition rate (reduction of deposited scale after scale inhibitor dosing) reached a peak of 95.21% at a time of 6.1 h, a solution temperature of 70°C and an EDTMPS dosing rate of 6 mg/L.

Variations in Bacteriological and Physicochemical Water Quality Characteristics of Asata River, Enugu, Nigeria

Variations in Bacteriological and Physicochemical Water Quality Characteristics of Asata River, Enugu, Nigeria

Effects of water-coal interactions on coal mine water quality in China: a lixiviation experiment and actual water quality investigation.

Water-coal interactions are dominant factors that affect water quality in coal mines. Using lixiviation, the effects of water-coal interactions on pH, salinity, and hazardous elemental enrichment in coal mine water and associated trends were simulated and analyzed. The salinity and hazardous element contents were low in the alkaline solution filtrate. However, the salinity and contents of hazardous elements (As, Cr, Zn, Cu, Mn, Co, Ni, Cd, Pb, U, and Be) in acid solution filtrate increased significantly with a decrease in pH. The pH of the solution filtrate was affected by the mineral composition of the coal, wherein the pyrite content could generally determine the pH. In addition, the spatial distribution and utilization potential of coal mine water quality in China was determined based on water quality data surveys. For water-deficient regions in northern China, particularly in the northwest, the local mine water had high salinity, a high pH, and a low content of hazardous elements; therefore, the reuse of mine water for water consumption is feasible. Conversely, the mine water in the southwest region had high salinity and a low pH and was enriched in harmful elements with potential ecological and health risks. The actual water quality characteristics of the coal mine water matched the results of the laboratory simulation analysis, confirming the effect from water-coal interactions. This work provides a reference for understanding the determinants of coal mine water quality and the potential for water environment protection.

Water quality assessment of the Nam River, Korea, using multivariate statistical analysis and WQI

Water quality assessment using water quality index (WQI) is performed based on major variables reflecting the river characteristics. We evaluated the water quality of tributaries of the Nam River in South Korea. We analyzed the tributaries spatial characteristics using cluster analyses and selected the main water quality variables (Cluster 1: chemical oxygen demand [COD], total organic carbon [TOC], total nitrogen, and total phosphorus; Cluster 2: water temperature [WT], dissolved oxygen [DO], COD, and TOC; Cluster 3: WT, DO, electrical conductance, COD, and TOC) of the clustered rivers. The WQI for each tributary was calculated using variables selected post statistical analysis. We verified that the WQI calculated in this study was similar to the annual change in water quality of the target river. Finally, it was analyzed that performing river water quality evaluation using the major variables selected using statistical analysis reflects the current water quality status of the river in more detail. (WQI grade was S1 Good (63.0), S2 Poor (53.3), S3 Excellent (98.4), S4 Poor (48.4), S5 (Excellent (100.0), S6 Good (77.6), S7 Good (76.2), S8 Good (76.5), S9 Good (69.9), S10 Excellent (81.5), S11 Good (71.2), S12 Good (63.1), and S13 Good (63.5).) Our method effectively reduced the number of variables required for index calculation compared with WQI methods of the MOE. Further, the reduced number of variables simplified the analysis process, reduced analysis time, and enabled water quality assessment that reflected the water quality characteristics of the river to be evaluated.

Detection algorithm of abnormal characteristics of urban domestic water quality based on K-means clustering

In order to solve the problem of low detection accuracy in water quality anomaly detection, an urban domestic water quality anomaly detection algorithm based on K-means clustering is proposed. Firstly, by constructing the water quality feature extraction system and calculating the pollutant content by fluorescence method, the water quality feature extraction and pollutant content determination are completed. Then, normalise the data and introduce root mean square error to remove redundancy and complete the preprocessing. Finally, taking the pH value, ammonia nitrogen, oxygen consumption, chromaticity and turbidity of urban domestic water quality as abnormal values, the trust degree and data cluster distance between data are calculated through K-means clustering, and the abnormal characteristic detection model of urban domestic water quality is constructed to complete the detection. The results show that the proposed method has high accuracy in detecting the abnormal characteristics of urban domestic water quality.