Assessing water quality of drinking water distribution system in the South Taiwan

This investigation conducted a full-scale survey the drinking water distribution system in Kaohsiung city, Taiwan. The aim was to investigate whether the distribution system was capable of maintaining high water quality from the water treatment facilities through to the end user. The results showed that the distribution system can maintain high water quality, except for suitable chlorine residuals. The authors plotted chlorine residual contour maps to identify areas with low chlorine residuals, helping them prioritize sections that must be flushed or renewal. The contour maps also provide sufficient and clear information for locating booster chlorination stations. Contour maps enable water facilities to identify how water quality decays in the distribution systems and the locations of such decay. Water quality decay can be caused by properties of pipeline materials, hydraulic conditions, and/or biofilm thickness. However, understanding the exact reasons is unnecessary because the contour maps provide sufficient information for trouble-shooting the distribution systems.     

Evaluation of biological stability and corrosion potential in drinking water distribution systems: a case study

The appearance of assimilable organic carbon (AOC), microbial regrowth, disinfection by-products (DBPs), and pipe corrosion in drinking water distribution systems are among those major safe drinking water issues in many countries. The water distribution system of Cheng-Ching Lake Water Treatment Plant (CCLWTP) was selected in this study to evaluate the: (1) fate and transport of AOC, DBPs [e.g., trihalomethanes (THMs), haloacetic acids (HAAs)], and other organic carbon indicators in the selected distribution system, (2) correlations between AOC (or DBPs) and major water quality parameters [e.g. dissolved oxygen (DO), free residual chlorine, and bacteria, and (3) causes and significance of corrosion problems of the water pipes in this system. In this study, seasonal water samples were collected from 13 representative locations in the distribution system for analyses of AOC, DBPs, and other water quality indicators. Results indicate that residual free chlorine concentrations in the distribution system met the drinking water standards (0.2 to 1 mg l(-1)) established by Taiwan Environmental Protection Administration (TEPA). Results show that AOC measurements correlated positively with total organic carbon (TOC) and UV-254 (an organic indicator) values in this system. Moreover, AOC concentrations at some locations were higher than the 50 microg acetate-C l(-1) standard established by Taiwan Water Company. This indicates that the microbial regrowth might be a potential water quality problem in this system. Higher DO measurements (>5.7 mg l(-1)) might cause the aerobic biodegradation of THMs and HAAs in the system, and thus, low THMs (<0.035 mg l(-1)) and HAAs (<0.019 mg l(-1)) concentrations were observed at all sampling locations. Results from the observed negative Langelier Saturation Index (LSI) values, higher Ryznar Stability Index (RSI) values, and high Fe3+ concentrations at some pipe-end locations indicate that highly oxidative and corrosive conditions occurred. This reveals that pipe replacement should be considered at these locations. These findings would be helpful in managing the water distribution system for maintaining a safe drinking water quality.     

Monitoring of Coliforms and chlorine residual in water distribution network of Rawalpindi, Pakistan

The present study was undertaken to examine the drinking water quality of Rawal Treatment Plant, Rawalpindi and its distribution network by collecting samples from eight different locations. The aim was to determine potential relationship between the presence of microorganisms and chlorine residual in the distribution network. Quantification of chlorine residual, turbidity, standard plate count (SPC), fecal and total coliforms by Most Probable Number (MPN) was performed. Three different forms of chlorine were measured at each sampling station such as free chlorine, residual chlorine, chloramines and total chlorine residual. A critical evaluation of data presented indicated that pH generally ranged from 7.02–7.30; turbidity varied from 0.34–2.79 NTU; conductivity fluctuated from 359–374 μS/cm; and TDS values were found to be ranging between 180–187 mg/l. Station # 7 was found to be most contaminated. The value of total chlorine was found to be 0.86 to1.7 mg/l at Station # 3 and 6, respectively. Highest standard plate count was 62 CFU/ml at Station # 7. Total coliforms were less than 1.1 MPN/100 ml at almost most of the stations except at Station # 3 where it was found to be greater than 23.0 MPN /100 ml. Overall aim of this study is to create awareness about contamination of drinking water in the water distribution networks and to make recommendations to provincial agencies such as EPA, CDA and WASA that regular monitoring should be carried out to ensure that the chlorine residual is available at consumer end.     

Assessment of water quality using multivariate statistical techniques in the coastal region of Visakhapatnam,India

The present study was intended to develop a Water Quality Index (WQI) for the coastal water of Visakhapatnam, India from multiple measured water quality parameters using different multivariate statistical techniques. Cluster analysis was used to classify the data set into three major groups based on similar water quality characteristics. Discriminant analysis was used to generate a discriminant function for developing a WQI. Discriminant analysis gave the best result for analyzing the seasonal variation of water quality. It helped in data reduction and found the most discriminant parameters responsible for seasonal variation of water quality. Coastal water was classified into good, average, and poor quality considering WQI and the nutrient load. The predictive capacity of WQI was proved with random samples taken from coastal areas. High concentration of ammonia in surface water during winter was attributed to nitrogen fixation by the phytoplankton bloom which resulted due to East India Coastal Current. This study brings out the fact that water quality in the coastal region not only depends on the discharge from different pollution sources but also on the presence of different current patterns. It also illustrates the usefulness of WQI for analyzing the complex nutrient data for assessing the coastal water and identifying different pollution sources, considering reasons for seasonal variation of water quality.     

Groundwater quality and water quality index at Bhandara District

The present investigation reports the results of a monitoring study focusing on groundwater quality of Bhandara District of central India. Since, remediation of groundwater is very difficult, knowledge of the existing nature, magnitude, and sources of the various pollution loads is a prerequisite to assessing groundwater quality. The water quality index (WQI) value as a function of various physicochemical and bacteriological parameters was determined for groundwater obtained from a total of 21 locations. The WQI during pre-monsoon season varied from 68 to 83, while for post-monsoon, it was between 56 and 76. Significantly (P < 0.01) lower WQI for the post-monsoon season was observed, indicating deterioration of the groundwater overall in corresponding season. The study revealed that groundwater from only 19% locations was fit for domestic use, thus indicating the need of proper treatment before use.     

Determination of an acceptable assimilable organic carbon (AOC) level for biological stability in water distribution systems with minimized chlorine residual

There is considerable interest in minimizing the chlorine residual in Japan because of increasing complaints about a chlorinous odor in drinking water. However, minimizing the chlorine residual causes the microbiological water quality to deteriorate, and stricter control of biodegradable organics in finished water is thus needed to maintain biological stability during water distribution. In this investigation, an acceptable level of assimilable organic carbon (AOC) for biologically stable water with minimized chlorine residual was determined based on the relationship between AOC, the chlorine residual, and bacterial regrowth. In order to prepare water samples containing lower AOC, the fractions of AOC and biodegradable organic matter (BOM) in tap water samples were reduced by converting into biomass after thermal hydrolysis of BOM at alkaline conditions. The batch-mode incubations at different conditions of AOC and chlorine residual were carried out at 20°C, and the presence or absence of bacterial regrowth was determined. The determined curve for biologically stable water indicated that the acceptable AOC was 10.9 μg C/L at a minimized chlorine residual (0.05 mg Cl₂/L). This result indicated that AOC removal during current water treatment processes in Japan should be significantly enhanced prior to minimization of the chlorine residual in water distribution.     

Chlorination and water quality monitoring within a public drinking water supply in Rawalpindi Cantt (Westridge and Tench) area, Pakistan

Concern over the presence of fecal coliform in public drinking water supplies has been expressed in recent years in Pakistan since it has been regarded as pathogenic organism of prime importance in gastroenteritis. Two major drinking water distribution systems in the Cantt area of Rawalpindi district covering the Westridge and Tench areas was monitored over a 2-month period to determine the prevalence of fecal coliform and chlorine residual. The collected samples were examined for total chlorine, free chlorine residual, chloramines, total coliforms, fecal coliforms, and turbidity. The drinking water quality monitoring in the distribution network was performed by collecting samples from water source, overhead reservoir, and residential taps. In the Westridge area, total chlorine varied from the lowest value of 0.27 mg/L at Station # W-5 to the highest value of 0.42 mg/L at Station # W-2, total coliforms varied from 1.1 to 3.6 most probable number (MPN)/100 mL with presence of Escherichia coli in all samples, total dissolved solids (TDS) ranged from 199.5 to 205 mg/L, conductivity fluctuated between 399 and 411 microS/cm, and turbidity varied from 0.43 to 0.73 NTU. In the Tench area, the value of total chlorine ranged from 0.14 mg/L at Station # T-7 to 0.55 mg/L at Station # T-1. Total coliform varied from 3.6 to 5.1 MPN/100 mL and fecal coliform were detected at all the stations except at Station # T-1. TDS ranged from 201.4 to 257 mg/L, conductivity varied from 343 to 513 microS/cm, and turbidity ranged between 0.66 and 1.55 NTU. It is recommended to the respective agencies to ensure that the chlorine residual is available at consumer end.     

基于熵权的WQI法在鄱阳湖水质评价中的应用

基于2009—2018年鄱阳湖15个监测点位的水质监测数据,采用基于熵权改进的综合水质指数（WQI）法研究10年间该湖水质年际、季节演变特征及空间分布情况。结果表明：鄱阳湖WQI多年平均值为78.41,水质总体处于差等级,其中氮、磷污染较为严重;该湖水质空间分布差异较小,各湖区WQI较为接近,湖区西北部和东南部污染相对较为严重;该湖夏季水质较好,水质与降水量及湖面风浪强度紧密相关;该湖污染物主要来自入湖河流周边的工、矿、企业的废水及采砂造成的污染物释放,建议控制、治理入湖河流水质,提高鄱阳湖较重污染区水质。     

Evaluation of water quality index for drinking purposes for river Netravathi, Mangalore, South India

An attempt has been made to develop water quality index (WQI), using six water quality parameters Dissolved oxygen (DO), Biochemical oxygen Demand (BOD), Most Probable Number (MPN), Turbidity, Total Dissolved Solids (TDS) and pH measured at eight different stations along the river basin. Rating curves were drawn based on the tolerance limits of inland waters and health point of view. Bhargava WQI method and Harmonic Mean WQI method were used to find overall WQI along the stretch of the river basin. Five point rating scale was used to classify water quality in each of the study areas. It was found that the water quality of Netravathi varied from Excellent to Marginal range by Bhargava WQI method and Excellent to Poor range by Harmonic Mean WQI method. It was observed that the impact of human activity was severe on most of the parameters. The MPN values exceeded the tolerable limits at almost all the stations. It was observed that the main cause of deterioration in water quality was due to the lack of proper sanitation, unprotected river sites and high anthropogenic activities.     

Comparative analysis of regional water quality in Canada using the Water Quality Index

The Canadian Council of Ministers for the Environment (CCME) has developed a Water Quality Index (WQI) to simplify the reporting of complex water quality data. This science-based communication tool tests multi-variable water data against numeric water quality guidelines and/or objectives to produce a single unit-less number that represents overall water quality. The CCME WQI has been used to rate overall water quality in spatial and temporal comparisons of site(s). However, it has not been used in a comparative-analysis of exposure sites to reference sites downstream of point source discharges. This study evaluated the ability of the CCME WQI to differentiate water quality from metal mines across Canada at exposure sites from reference sites using two different types of numeric water quality objectives: (1) the water quality guidelines (WQG) for the protection of freshwater aquatic life and (2) water quality objectives determined using regional reference data termed Region-Specific Objectives (RSO). The application of WQG to the CCME WQI was found to be a good tool to assess absolute water quality as it relates to national water quality guidelines for the protection of aquatic life, but had more limited use when evaluating spatial changes in water quality downstream of point source discharges. The application of the RSO to the CCME WQI resulted in assessment of spatial changes in water quality downstream of point source discharges relative to upstream reference conditions.     

Assessing the water quality index of water treatment plant and bore wells, in Delhi, India

Water quality monitoring exercise was carried out with water quality index (WQI) method by using water characteristics data for bore wells and a water treatment plant in Delhi city from December 2006 to August 2007. The water treatment plant received surface water as raw water, and product water is supplied after treatment. The WQI is used to classify water quality as excellent, good, medium, bad, and very bad. The National Sanitation Foundation WQI procedure was used to calculate the WQI. The index ranges from 0 to 100, where 100 represents an excellent water quality condition. Water samples were collected monthly from a bore well in Nehru Camp (site 1), a bore well in Sanjay Gandhi pumping station (site 2), and water treatment plant in Haiderpur (site 3). Five parameters were analyzed, namely, nitrate, pH, total dissolved solids, turbidity, and temperature. We found that the WQI was around 73–80 in site 3, which corresponds to “good,” and it decreased to 54.32–60.19 and 59.93–70.63 in site 1 and site 2, respectively, indicating that these bore wells were classified as “medium” quality.     

Application of Water Quality Indices and Dissolved Oxygen as Indicators for River Water Classification and Urban Impact Assessment

The usefulness of water quality indices, as the indicators of water pollution, for assessment of spatial-temporal changes and classification of river water qualities was verified. Four water quality indices were investigated: WQI (considering 18 water quality parameters), WQI(min) and WQI(m) (considering five water quality parameters: temperature, pH, DO, EC and TSS) and WQI(DO) (considering a single parameter, DO). The water quality indices WQI(min), WQI(m) and WQI(DO) could be of particular interest for the developing countries because of the minimum analytical cost involved. As a case study, water quality indices were used to evaluate spatial and temporal changes of the water quality in the Bagmati river basin (Nepal) for the study period 1999-2003. The results allowed us to determine the serious negative effects of the city urban activity on the river water quality. In the studied section of the river, the water quality index (WQI) was 71 units (classified as good) at the entry station and 47.6 units (classified as bad) at the outlet station. For the studied period, a significant decrease in water quality (mean WQI decrease = 11.6%, p = 0.042) was observed in the rural areas. A comparative analysis revealed that the urban water quality was significantly bad as compared with rural. The analysis enabled to classify the water quality stations into three groups: good water quality, medium water quality and bad water quality. WQI(min) resulted in overestimation of the water quality but with similar trend as with WQI and is useful for the periodic routine monitoring program. The correlation of WQI with WQI(min) and DO resulted two new indices WQI(m) and WQI(DO), respectively. The classification of waters based on WQI(m) and WQI(DO) coincided in 90 and 93% of the samples, respectively.     

Environmental impact of coal mining and coal seam gas production on surface water quality in the Sydney basin,Australia

The extraction of coal and coal seam gas (CSG) will generate produced water that, if not adequately treated, will pollute surface and groundwater systems. In Australia, the discharge of produced water from coal mining and related activities is regulated by the state environment agency through a pollution licence. This licence sets the discharge limits for a range of analytes to protect the environment into which the produced water is discharged. This study reports on the impact of produced water from coal mine activities located within or discharging into high conservation environments, such as National Parks, in the outer region of Sydney, Australia. The water samples upstream and downstream from the discharge points from six mines were taken, and 110 parameters were tested. The results were assessed against a water quality index (WQI) which accounts for pH, turbidity, dissolved oxygen, biochemical oxygen demand, total dissolved solids, total phosphorus, nitrate nitrogen and E .coli. The water quality assessment based on the trace metal contents against various national maximum admissible concentration (MAC) and their corresponding environmental impacts was also included in the study which also established a base value of water quality for further study. The study revealed that impacted water downstream of the mine discharge points contained higher metal content than the upstream reference locations. In many cases, the downstream water was above the Australia and New Zealand Environment Conservation Council and international water quality guidelines for freshwater stream. The major outliers to the guidelines were aluminium (Al), iron (Fe), manganese (Mn), nickel (Ni) and zinc (Zn). The WQI of surface water at and downstream of the discharge point was lower when compared to upstream or reference conditions in the majority of cases. Toxicology indices of metals present in industrial discharges were used as an additional tool to assess water quality, and the newly proposed environmental water quality index (EWQI) lead to better trend in the impact of coal and coal seam gas mining activities on surface water quality when compared to the upstream reference water samples. Metal content limits were based on the impact points assigned by the Agency for Toxic Substances and Disease Registry, USA. For environmental and health impact assessment, the approach used in this study can be applied as a model to provide a basis to assess the anthropogenic contribution from the industrial and mining activities on the environment.     

Assessing regulatory violations of disinfection by-products in water distribution networks using a non-compliance potential index

Inactivating pathogens is essential to eradicate waterborne diseases. However, disinfection forms undesirable disinfection by-products (DBPs) in the presence of natural organic matter. Many regulations and guidelines exist to limit DBP exposure for eliminating possible health impacts such as bladder cancer, reproductive effects, and child development effects. In this paper, an index named non-compliance potential (NCP) index is proposed to evaluate regulatory violations by DBPs. The index can serve to evaluate water quality in distribution networks using the Bayesian Belief Network (BBN). BBN is a graphical model to represent contributing variables and their probabilistic relationships. Total trihalomethanes (TTHM), haloacetic acids (HAA5), and free residual chlorine (FRC) are selected as the variables to predict the NCP index. A methodology has been proposed to implement the index using either monitored data, empirical model results (e.g., multiple linear regression), and disinfectant kinetics through EPANET simulations. The index’s usefulness is demonstrated through two case studies on municipal distribution systems using both full-scale monitoring and modeled data. The proposed approach can be implemented for data-sparse conditions, making it especially useful for smaller municipal drinking water systems.     

Evaluation of environmental impacts of Integrated Industrial Estate��Pantnagar through application of air and water quality indices

Large-scale industrialization, population inflow, and rapid urbanization coupled with unfavorable meteorological conditions often induce significant degradation of urban environment. In order to assess the extent of environmental impacts due to establishment of the Integrated Industrial Estate??Pantnagar (IIE-Pantnagar), ambient air and groundwater were monitored from June 2007 to May 2008. Collected baseline information was normalized and interpreted with the application of air (AQI) and water quality indices (WQI). Among the pre-identified air pollutants, suspended particulate matter was found to be the principal culprit to deteriorate ambient air quality, with a maximum annual concentration of 418.5 ??g/m³. Monthly average concentrations of respirable particulate matter (aerodynamic diameter < 10 ??m) also persist at a critical level with an annual maximum of 207.3 ??g/m³. A segmented linear function with maximum operator concept was used to compute AQI, and the developed index was found well suitable to demonstrate temporal variations of ambient air quality. The computed AQI value for the selected study region varied from moderate (97.0) to very poor pollution level (309.2) in respect to developed air quality standards. Furthermore, an integrated WQI was developed comprising 9 parameters, and among all the 10 pre-identified locations, the average groundwater quality was found acceptable in terms of Indian drinking water standards. The maximum WQI (70.6) was found at the Kichha Railway Station during summer months, revealing moderate pollution load. Industrial discharge from IIE-Pantnagar coupled with other industrial setup may hold responsible for such kind of degradation of water quality. In contrast, WQI computed at Rudrapur City demonstrate minimum (15.0?C22.1) pollution load. For 95% of the monitoring period, the computed WQI was found acceptable for all selected locations with few exceptions. The application of WQI to assess temporal variations in groundwater quality was therefore found satisfactory.     

Small drinking water systems under spatiotemporal water quality variability: a risk-based performance benchmarking framework

Traditional approaches for benchmarking drinking water systems are binary, based solely on the compliance and/or non-compliance of one or more water quality performance indicators against defined regulatory guidelines/standards. The consequence of water quality failure is dependent on location within a water supply system as well as time of the year (i.e., season) with varying levels of water consumption. Conventional approaches used for water quality comparison purposes fail to incorporate spatiotemporal variability and degrees of compliance and/or non-compliance. This can lead to misleading or inaccurate performance assessment data used in the performance benchmarking process. In this research, a hierarchical risk-based water quality performance benchmarking framework is proposed to evaluate small drinking water systems (SDWSs) through cross-comparison amongst similar systems. The proposed framework (R _WQI framework) is designed to quantify consequence associated with seasonal and location-specific water quality issues in a given drinking water supply system to facilitate more efficient decision-making for SDWSs striving for continuous performance improvement. Fuzzy rule-based modelling is used to address imprecision associated with measuring performance based on singular water quality guidelines/standards and the uncertainties present in SDWS operations and monitoring. This proposed R _WQI framework has been demonstrated using data collected from 16 SDWSs in Newfoundland and Labrador and Quebec, Canada, and compared to the Canadian Council of Ministers of the Environment WQI, a traditional, guidelines/standard-based approach. The study found that the R _WQI framework provides an in-depth state of water quality and benchmarks SDWSs more rationally based on the frequency of occurrence and consequence of failure events.     

Assessment of odour problem in sewage-treated effluent in a closed loop irrigation system

Uses of wastewater drives significant economic activity, supports countless livelihoods particularly those for developing countries. While using wastewater, the challenge is to identify practical, affordable safeguards that do not threaten the health of users. In Yanbu Al-Sinaiyah, treated sewage effluent (TSE) is used for landscape purposes. In the present study, the odour problem caused by TSE in community area has been addressed. Samples were collected and analysed for total coliform, odour, trihalomethanes (THMs), total organic carbon (TOC) and other physicochemical parameters. Results show that in distribution network, residual chlorine was below the detection limit, turbidity, THMs, TOC and total coliform concentration was much higher than point source, and concentration of these parameters was further increased in problematic areas. It was also observed that areas with odourous problem were at the tail of irrigation network. This indicates that odour problem was due to less residual chlorine high turbidity, high rate of coliform and TOC. In odourous water samples, carbon disulphide and dimethyl sulphide were also identified by GC/MS, while in other areas where there was no odour, both these compounds were not detected. Odour problem was successfully resolved by improving sand filtration system to minimise turbidity the main cause of odour, increasing the residual chlorine at the treatment plant and regularly flushing the distribution network.     

Use of water quality index and multivariate statistical techniques for the assessment of spatial variations in water quality of a small river

Rapid urban development has led to a critical negative impact on water bodies flowing in and around urban areas. In the present study, 25 physiochemical and biological parameters have been studied on water samples collected from the entire section of a small river originating and ending within an urban area. This study envisaged to assess the water quality status of river body and explore probable sources of pollution in the river. Weighted arithmetic water quality index (WQI) was employed to evaluate the water quality status of the river. Multivariate statistical techniques namely cluster analysis (CA) and principal component analysis (PCA) were applied to differentiate the sources of variation in water quality and to determine the cause of pollution in the river. WQI values indicated high pollution levels in the studied water body, rendering it unsuitable for any practical purpose. Cluster analysis results showed that the river samples can be divided into four groups. Use of PCA identified four important factors describing the types of pollution in the river, namely (1) mineral and nutrient pollution, (2) heavy metal pollution, (3) organic pollution, and (4) fecal contamination. The deteriorating water quality of the river was demonstrated to originate from wide sources of anthropogenic activities, especially municipal sewage discharge from unplanned housing areas, wastewater discharge from small industrial units, livestock activities, and indiscriminate dumping of solid wastes in the river. Thus, the present study effectively demonstrates the use of WQI and multivariate statistical techniques for gaining simpler and meaningful information about the water quality of a lotic water body as well as to identify of the pollution sources.     

Water quality index applied to rivers in the Vistula river basin in Poland

Summary A new method of a water quality index has been proposed. The unit indices were determined from the values of individual parameters using continuous functions. The base for such functions were the four water quality classes used in Poland. The summarized WQI is the square root of the harmonic mean of squares of unit indices. Using this mean we have eliminated the use of weights of parameters. Parameters are divided into basic parameters (7) and other additional parameters (19). The additional parameter is considered only if its unit index is lower than WQI from basic parameters. For many measurements at one point the guaranteed WQI has been calculated. The points of WQI were connected and the curves of WQI along the river were obtained.A method of WQI calculating and preparation of WQI curves has been shown using as an example the Pilica river in Poland. The WQI was then calculated for 31 rivers in the Vistula river basin by measuring points.     

Water quality time series for Big Melen stream (Turkey): its decomposition analysis and comparison to upstream

Big Melen stream is one of the major water resources providing 268 km³ year^???1 of drinking and municipal water for Istanbul. Monthly time series data between 1991 and 2004 for 25 chemical, biological, and physical water properties of Big Melen stream were separated into linear trend, seasonality, and error components using additive decomposition models. Water quality index (WQI) derived from 17 water quality variables were used to compare Aksu upstream and Big Melen downstream water quality. Twenty-six additive decomposition models of water quality time series data including WQI had R ² values ranging from 88% for log(water temperature) (P?≤?0.001) to 3% for log(total dissolved solids) (P?≤?0.026). Linear trend models revealed that total hardness, calcium concentration, and log(nitrite concentration) had the highest rate of increase over time. Tukey’s multiple comparison pointed to significant decreases in 17 water quality variables including WQI of Big Melen downstream relative to those of Aksu upstream (P?≤?0.001). Monitoring changes in water quality on the basis of watersheds through WQI and decomposition analysis of time series data paves the way for an adaptive management process of water resources that can be tailored in response to effectiveness and dynamics of management practices.