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.     

A probabilistic water quality index for river water quality assessment: a case study

Available water quality indices have some limitations such as incorporating a limited number of water quality variables and providing deterministic outputs. This paper presents a hybrid probabilistic water quality index by utilizing fuzzy inference systems (FIS), Bayesian networks (BNs), and probabilistic neural networks (PNNs). The outputs of two traditional water quality indices, namely the indices proposed by the National Sanitation Foundation and the Canadian Council of Ministers of the Environment, are selected as inputs of the FIS. The FIS is trained based on the opinions of several water quality experts. Then the trained FIS is used in a Monte Carlo analysis to provide the required input-output data for training both the BN and PNN. The trained BN and PNN can be used for probabilistic water quality assessment using water quality monitoring data. The efficiency and applicability of the proposed methodology is evaluated using water quality data obtained from water quality monitoring system of the Jajrood River in Iran.     

Water quality analysis of surface water: a Web approach

The chemical, physical and biological characteristics of water with respect to its suitability describe its quality. Concentration of pesticides or fertilisers degrades the water quality and affects marine life. A comprehensive environmental data information system helps to perform and complete common tasks in less time with less effort for data verification, data calculations, graph generation, and proper monitoring, which helps in the further mitigation step. In this paper, focus is given to a web-based system developed to express the quality of water in the imprecise environment of monitoring data. Water samples were analyzed for eight different surface water parameters, in which four parameters such as pH, dissolved oxygen, biochemical oxygen demand, and fecal coliform were used for the water quality index calculation following MPCB Water Quality Standards of class A-II for best designated use. The analysis showed that river points in a particular year were in very bad category with certainty level of 0–38 % which is unsuitable for drinking purposes; samples in bad category had certainty level that ranged from 38 to 50 %; samples in medium to good category had certainty levels from 50 to 100 %, and the remaining samples were in good to excellent category, suitable for drinking purposes, with certainty levels from 63 to 100 %.     

Optimizing water quality monitoring networks using continuous longitudinal monitoring data: a case study of Wen-Rui Tang River, Wenzhou, China

Identification of representative sampling sites is a critical issue in establishing an effective water quality monitoring program. This is especially important at the urban-agriculture interface where water quality conditions can change rapidly over short distances. The objective of this research was to optimize the spatial allocation of discrete monitoring sites for synoptic water quality monitoring through analysis of continuous longitudinal monitoring data collected by attaching a water quality sonde and GPS to a boat. Sampling was conducted six times from March to October 2009 along a 6.5 km segment of the Wen-Rui Tang River in eastern China that represented an urban-agricultural interface. When travelling at a velocity of ～2.4 km h(-1), this resulted in water quality measurements at ～20 m interval. Ammonia nitrogen (NH(4)(+)-N), electrical conductivity (EC), dissolved oxygen (DO), and turbidity data were collected and analyzed using Cluster Analysis (CA) to identify optimal locations for establishment of long-term monitoring sites. The analysis identified two distinct water quality segments for NH(4)(+)-N and EC and three distinct segments for DO and turbidity. According to our research results, the current fixed-location sampling sites should be adjusted to more effectively capture the distinct differences in the spatial distribution of water quality conditions. In addition, this methodology identified river reaches that require more comprehensive study of the factors leading to the changes in water quality within the identified river segment. The study demonstrates that continuous longitudinal monitoring can be a highly effective method for optimizing monitoring site locations for water quality studies.     

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.     

Assessment of water quality along a recreational section of the Damour River in Lebanon using the water quality index

Considering that water is becoming progressively scarce, monitoring water quality of rivers is a subject of ongoing concern and research. It is very intricate to accurately express water quality as water quantity due to the various variables influencing it. A water quality index which integrates several variables in a specific value may be used as a management tool in water quality assessment. Moreover, this index may facilitate communication with the public and decision makers. The main objectives of this research project are to evaluate the water quality index along a recreational section of a relatively small Mediterranean river in Southern Lebanon and to characterize the spatial and temporal variability. Accordingly, an assessment was conducted at the end of the dry season for a period of 5 years from 2005 to 2009. The estimated water quality index classified the average water quality over a 5-year period at the various sites as good. Results revealed that water quality of the Damour River is generally affected by the anthropogenic activities taking place along its watershed. The best quality was found in the upper sites and the worst at the estuary. The presence of fecal coliform bacteria in very high levels may indicate potential health risks to swimmers. This study can be used to support the evaluation of management, regulatory, and monitoring decisions.     

Utilization of the water quality index method as a classification tool

The study comprised modification of the Canadian Council of Ministers of the Environment (CCME) Water Quality Index (CCMEWQI) to obtain a tool in classification of surface waters according to quality defined by the European Legislation—75/440/EEC. Three categories were proposed, and the category ranges of CCMEWQI have been modified depending on the objective chosen. The application of the CCMEWQI with modified categorization scheme was demonstrated to assess overall water quality by integrating observed water quality determinants in the Kucuk Menderes Basin, Turkey. In this scope, the samples analyzed for pH, total dissolved solids (TDS), chlorides (Cl), nitrate–nitrogen (NO₃–N), dissolved oxygen (DO), biochemical oxygen demand (BOD₅), sulfate (SO₄), and boron (B), variables taken monthly over 2 years from the five monitoring sites, were processed. Results revealed that the overall surface water mainly fell within the A2 water class. The CCMEWQI with modified categorization scheme is believed to assist water managers to integrate and interpret the picture of overall water quality based on the European legislation concerning the quality required of surface water intended for the abstraction of drinking water in the Member States (75/440/EEC).     

Development and sensitivity analysis of a global drinking water quality index

The UNEP GEMS/Water Programme is the leading international agency responsible for the development of water quality indicators and maintains the only global database of water quality for inland waters (GEMStat). The protection of source water quality for domestic use (drinking water, abstraction etc) was identified by GEMS/Water as a priority for assessment. A composite index was developed to assess source water quality across a range of inland water types, globally, and over time. The approach for development was three-fold: (1) Select guidelines from the World Health Organisation that are appropriate in assessing global water quality for human health, (2) Select variables from GEMStat that have an appropriate guideline and reasonable global coverage, and (3) determine, on an annual basis, an overall index rating for each station using the water quality index equation endorsed by the Canadian Council of Ministers of the Environment. The index allowed measurements of the frequency and extent to which variables exceeded their respective WHO guidelines, at each individual monitoring station included within GEMStat, allowing both spatial and temporal assessment of global water quality. Development of the index was followed by preliminary sensitivity analysis and verification of the index against real water quality data.     

Multi-level modelling of chlorination by-product presence in drinking water distribution systems for human exposure assessment purposes

During drinking water treatment and distribution, chlorine reacts with organic matter occurring in water to form various chlorination by-products (CBPs) such as trihalomethanes (THMs) and haloacetic acids (HAAs). This paper presents the occurrence of THMs and HAAs in different water distribution systems (DS) of the same region and their modelling for exposure assessment purposes. This study was conducted in eight DS supplying chlorinated water to the population of Québec City, Canada. These systems differ in type of water source (i.e. surface, ground or mixed water), in treatment applied at the plant, and in size and structure of the DS. Two spatio-temporal databases for THMs and HAAs were implemented, one for model development and the other for model validation. The analysis of the data demonstrates significant seasonal and spatial variations of these compounds. A multi-level statistical modelling approach was applied to estimate the ranges for occurrence of THMs and HAAs in the eight DS (i.e. a single model for the study region for each CBP species). The modelling approach integrates available or easily measurable parameters. For both THMs and HAAs, a two-level model considering a sampling-site random effect was selected among various models initially developed. The model capacity for estimating the presence of THMs and HAAs in drinking water and its usefulness for exposure assessment purposes in the studied region was demonstrated.     

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.     

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.     

The design of long-term air quality monitoring networks in urban areas using a spatiotemporal approach

The implementation and maintenance of an air pollution monitoring program can be expensive and time consuming, especially when the aim is for long-term monitoring over a significant area. Consequently, it is essential that sites are optimized to provide the best representative cover while minimizing costs. In the past, there has been a tendency to locate sampling stations at pollution hot-spots. While this is acceptable for determining a maximum potential exposure or identifying the extent of a risk, there are limitations to this approach when assessing the potential impact of any future abatement strategies or determining the level of exposure outside the vicinity. This paper presents an approach in which representative air quality assessments can be undertaken for an urban area using the minimum number of measurement sites. A novel methodology is described that involves site selection to capture the maximum variance in measured pollutants, while minimizing spatiotemporal autocorrelation between the selected sites. A case study is presented for Yazd, Iran. Overall, the results show that the proposed methodology can be effective and enable the long-term monitoring of air pollution to be undertaken on a cost-effective basis in urban areas. In addition, there is the potential for the methodology to be utilized for other forms of pollution (e.g., water, soil, and noise).     

Application of water quality index for groundwater quality assessment: Thirumanimuttar sub-basin, Tamilnadu, India

An attempt has been made to understand the hydrogeochemical parameters to develop water quality index in Thirumanimuttar sub-basin. A total of 148 groundwater samples were collected and analyzed for major cations and anions. The domination of cations and anions was in the order of Na>Mg>Ca>K for cations and Cl>HCO₃ >SO₄ in anions. The hydrogeochemical facies indicate alkalis (Na and K) exceed alkaline earths (Ca and Mg) and strong acids (Cl and SO₄) exceed weak acid (HCO₃). Water quality index rating was calculated to quantify overall water quality for human consumption. The PRM samples exhibit poor quality in greater percentage when compared with POM due to effective leaching of ions, over exploitation of groundwater, direct discharge of effluents and agricultural impact. The overlay of WQI with chloride and EC correspond to the same locations indicating the poor quality of groundwater in the study area. SAR, Na%, and TH were noted higher during both the seasons indicating most of the groundwater locations not suitable for irrigation purposes.     

Use of neural networks for monitoring surface water quality changes in a neotropical urban stream

This paper reports the using of neural networks for water quality analysis in a tropical urban stream before (2002) and after sewerage building and the completion of point-source control-based sanitation program (2003). Mathematical modeling divided water quality data in two categories: (a) input of some in situ water quality variables (temperature, pH, O2 concentration, O2 saturation and electrical conductivity) and (b) water chemical composition (N-NO2(-); N-NO3(-); N-NH4(+) Total-N; P-PO4(3-); K+; Ca2+; Mg+2; Cu2+; Zn2+ and Fe+3) as the output from tested models. Stream water data come from fortnightly sampling in five points along the Ipanema stream (Southeast Brazil, Minas Gerais state) plus two points downstream and upstream Ipanema discharge into Doce River. Once the best models are consistent with variables behavior we suggest that neural networking shows potential as a methodology to enhance guidelines for urban streams restoration, conservation and management.     

The SSC cycle: a PDCA approach to address site-specific characteristics in a continuous shallow water quality monitoring project

In any water quality-monitoring project there are several critical success factors that must be adequately addressed in order to ensure the implementation and realization of the monitoring objectives. Site selection is one of these critical success factors. The monitoring sites must be selected to comply with the monitoring and data quality objectives. In the real world, ideal monitoring setting conditions are difficult to achieve, and compromises must be made in order to locate the monitoring stations that best represent the environment to be monitored. Site-specific characteristics are all the environmental, logistical and management factors particular to the monitoring site, that could influence the fulfilment of the monitoring and data quality objectives. Therefore, during the site selection process, it is essential to properly consider and evaluate these site-specific characteristics. The SSC cycle was developed with this goal in mind, to assist the monitoring team to systematically address site-specific characteristics. The cycle is a methodology to organize the site-specific characteristics in different categories, and to ensure a comprehensive overview of these characteristics throughout the project life cycle.     

Development of fuzzy air quality index using soft computing approach

Proper assessment of air quality status in an atmosphere based on limited observations is an essential task for meeting the goals of environmental management. A number of classification methods are available for estimating the changing status of air quality. However, a discrepancy frequently arises from the quality criteria of air employed and vagueness or fuzziness embedded in the decision making output values. Owing to inherent imprecision, difficulties always exist in some conventional methodologies like air quality index when describing integrated air quality conditions with respect to various pollutants parameters and time of exposure. In recent years, the fuzzy logic-based methods have demonstrated to be appropriated to address uncertainty and subjectivity in environmental issues. In the present study, a methodology based on fuzzy inference systems (FIS) to assess air quality is proposed. This paper presents a comparative study to assess status of air quality using fuzzy logic technique and that of conventional technique. The findings clearly indicate that the FIS may successfully harmonize inherent discrepancies and interpret complex conditions.     

Assessment of groundwater quality near the landfill site using the modified water quality index

The purpose of this paper is to assess the groundwater quality near a landfill site using the modified water quality index. A total of 128 groundwater samples were analyzed for pH, electrical conductivity (EC), total organic carbon (TOC), polycyclic aromatic hydrocarbon (PAH), Cd, Pb, Zn, Cu, Cr, and Hg. The analytical results have showed a decreasing trend in concentration for TOC, Cd, Pb, Hg, and Cu and an increasing one for pH, EC, and PAH. The modified water quality index, which was called landfill water pollution index (LWPI), was calculated to quantify the overall water quality near the landfill site. The analysis reveals that groundwater in piezometers close to the landfill is under a strong landfill impact. The LWPI in piezometers ranged from 0.52 to 98.25 with a mean value of 7.99. The LWPI in groundwater from the nearest house wells varied from 0.59 to 0.92. A LWPI value below 1 proves that analyzed water is not affected by the landfill. Results have shown that LWPI is an efficient method for assessing and communicating the information on the groundwater quality near the landfill.     

Heterotrophic bacteria in drinking water distribution system: a review

The microbiological quality of drinking water in municipal water distribution systems (WDS) depends on several factors. Free residual chlorine and/or chloramines are typically used to minimize bacterial recontamination and/or regrowth in WDS. Despite such preventive measures, regrowth of heterotrophic (HPC) and opportunistic bacteria in bulk water and biofilms has yet to be controlled completely. No approach has shown complete success in eliminating biofilms or HPC bacteria from bulk water and pipe surfaces. Biofilms can provide shelter for pathogenic bacteria and protect these bacteria from disinfectants. Some HPC bacteria may be associated with aesthetic and non-life threatening diseases. Research to date has achieved important success in understanding occurrence and regrowth of bacteria in bulk water and biofilms in WDS. To achieve comprehensive understanding and to provide efficient control against bacteria regrowth, future research on bacteria regrowth dynamics and their implications is warranted. In this study, a review was performed on the literature published in this area. The findings and limitations of these papers are summarized. Occurrences of bacteria in WDS, factors affecting bacteria regrowth in bulk water and biofilms, bacteria control strategies, sources of nutrients, human health risks from bacterial exposure, modelling of bacteria regrowth and methods of bacteria sampling and detection and quantification are investigated. Advances to date are noted, and future research needs are identified. Finally, research directions are proposed to effectively control HPC and opportunistic bacteria in bulk water and biofilms in WDS.     

Reservoir water quality: a case from Jordan

Jordan relies heavily on reservoirs building and development to cope with water supply challenges, where monitoring and assessment of reservoir water quality are critically important for the sustainable use of these water supplies. Mujib Dam is an important water supply source in central western Jordan. Evaluation of water quality parameters and their spatial distributions (vertical and horizontal) showed near-neutral pH values with nearly similar values from surface to bottom. The vertical profile of DO and TDS in the dammed reservoir showed slight decreasing trends with increasing depth. Although Ca, Mg, Na, and K concentrations varied slightly with depths, their variations showed no trends. Similarly, the vertical and horizontal distribution patterns of Cl, SO₄, HCO₃, NO₃, and PO₄ in Mujib reservoir water showed insignificant variations in surface water layer and relatively unchanged values or decreasing trends through the water column. Higher values of TN have been observed, especially in the western part, suggesting that agricultural activities and livestock farming in the upstream catchment are impacting water quality. Results revealed that weathering and dissolution of rocks are the major source of water chemistry. The majority of trace metal levels (Cd, Cr, Cu, Fe, Mn, Pb, Zn, Co, Ni, Sr, and B) in water showed relatively similar surface and bottom values. The concentrations of COD and BOD₅ in surface water were relatively low with higher concentrations observed in the northwestern corner, coincided with higher levels of chlorophyll a. The average ratio of TN to TP in surface water suggests that phosphorus is the limiting factor for the algal blooms, whereas the average chlorophyll a level in surface water indicates oligo-mesotrophic water.