Performance of biotic indices in comparison to chemical-based Water Quality Index (WQI) in evaluating the water quality of urban river

In order to evaluate the water quality of one of the most polluted urban river in Malaysia, the Penchala River, performance of eight biotic indices, Biomonitoring Working Party (BMWP), BMWP^Thai, BMWP^Viet, Average Score Per Taxon (ASPT), ASPT^Thai, BMWP^Viet, Family Biotic Index (FBI), and Singapore Biotic Index (SingScore), was compared. The water quality categorization based on these biotic indices was then compared with the categorization of Malaysian Water Quality Index (WQI) derived from measurements of six water physicochemical parameters (pH, BOD, COD, NH₃-N, DO, and TSS). The river was divided into four sections: upstream section (recreational area), middle stream 1 (residential area), middle stream 2 (commercial area), and downstream. Abundance and diversity of the macroinvertebrates were the highest in the upstream section (407 individual and H′?=?1.56, respectively), followed by the middle stream 1 (356 individual and H′?=?0.82). The least abundance was recorded in the downstream section (214 individual). Among all biotic indices, BMWP was the most reliable in evaluating the water quality of this urban river as their classifications were comparable to the WQI. BMWPs in this study have strong relationships with dissolved oxygen (DO) content. Our results demonstrated that the biotic indices were more sensitive towards organic pollution than the WQI. BMWP indices especially BMWP^Viet were the most reliable and could be adopted along with the WQI for assessment of water quality in urban rivers.     

Evaluation of surface water quality by using Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) method and discriminant analysis method: a case study Coruh River Basin

In this study, the water quality of the Coruh River Basin, which is located in the Eastern Black Sea Region of Turkey, was evaluated. The water quality data measurement results obtained by the State Hydraulic Works 26th Regional Directorate from four different sites over a course of 4 years between the years 2011 and 2014 in the Coruh River Basin were used as the data. In this study, the water quality was evaluated by using the Canadian Council of Ministers of the Environmental Water Quality Index (CCME WQI) method and discriminant analysis (DA). The water quality of the Coruh River Basin was calculated as 30.4 and 71.35 by using the CCME WQI and classified as “poor,” “marginal,” and “fair”. These values show that the water of the Coruh River Basin is degraded and under threat and its overall quality is not close to natural or desired levels. The monitoring sites were divided into two groups by the cluster analysis (CA). DA is a multivariate analysis technique used to divide individuals or objects into different groups and assign them into predetermined groups. As a result of DA, calcium (Ca) and sulfate (SO₄) were determined to be significant parameters in the determination of the water quality of the Coruh River Basin. The success of DA depends on the percentage of correct classification. As a result of the analysis, 23% of the parameters in the first measurement point, 69.2% of the parameters in the second and third measurement points, and 76.9% of the parameters in the fourth measurement point were classified correctly. Since the second measurement point is the discharge point of a copper mine, it can be said that the water quality parameters measured may provide accurate results in detecting pollution at this point.     

Evaluation of Water Quality in the Chillán River (Central Chile) Using Physicochemical Parameters and a Modified Water Quality Index

The Chillán River in Central Chile plays a fundamental role in local society, as a source of irrigation and drinking water, and as a sink for urban wastewater. In order to characterize the spatial and temporal variability of surface water quality in the watershed, a Water Quality Index (WQI) was calculated from nine physicochemical parameters, periodically measured at 18 sampling sites (January–November 2000). The results indicated a good water quality in the upper and middle parts of the watershed. Downstream of the City of Chillán, water quality conditions were critical during the dry season, mainly due to the effects of the urban wastewater discharge. On the basis of the results from a Principal Component Analysis (PCA), modifications were introduced into the original WQI to reduce the costs associated with its implementation. WQI_DIR2 and WQI_DIR, which are both based on a laboratory analysis (Chemical Oxygen Demand) and three (pH, temperature and conductivity), respectively, four field measurements (pH, temperature, conductivity and Dissolved Oxygen), adequately reproduce the most important spatial and temporal variations observed with the original index. They are proposed as useful tools for monitoring global water quality trends in this and other, similar agricultural watersheds in the Chilean Central Valley. Possibilities and limitations for the application of the used methodology to watersheds in other parts of the world are discussed.     

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.     

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.     

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.     

江苏省水质全要素代表性监测体系的设计

为了评价并进行城市水环境质量考核排名,介绍了江苏省组织开展涵盖地表水、饮用水、地下水、近岸海域和城市内河5种类型"全要素、代表性"水质监测断面(点位)体系建设工作的情况以及全要素断面设置的基本原则和做法。分苏南、苏北、苏中3个区域,对全省地表水监测代表性进行了量化计算,结果表明,调整后全省水质综合指数极差从41.07降至7.17,标准差从3.16降为0.49;采用德尔斐层次分析法分析,设计了水质代表性指数,含1项一级指标、5项二级指标、12项三级指标,计算表明,调整前全省水质代表性指数得分为69.1分,调整后为88.7分。将调整结果进行论证后再与各市环保主管部门交换意见,取得最终一致后正式实施。     

Stagnant surface water bodies (SSWBs) as an alternative water resource for the Chittagong metropolitan area of Bangladesh: physicochemical characterization in terms of water quality indices

The concern over ensuing freshwater scarcity has forced the developing countries to delve for alternative water resources. In this study, we examined the potential of stagnant surface water bodies (SSWBs) as alternative freshwater resources in the densely populated Chittagong metropolitan area (CMPA) of Bangladesh??where there is an acute shortage of urban freshwater supply. Water samples were collected at 1-month intervals for a period of 1 year from 12 stations distributed over the whole metropolis. Samples were analyzed for pH, water temperature (WTemp), turbidity, electrical conductivity (EC), total dissolved solids, total solids, total hardness, dissolved oxygen (DO), chloride, orthophosphates, ammonia, total coliforms (TC), and trace metal (Cd, Cr, Cu, Pb, As, and Fe) concentrations. Based on these parameters, different types of water quality indices (WQIs) were deduced. WQIs showed most of CMPA-SSWBs as good or medium quality water bodies, while none were categorized as bad. Moreover, it was observed that the minimal water quality index (WQI_m), computed using five parameters: WTemp, pH, DO, EC, and turbidity, gave a reliable estimate of water quality. The WQI_m gave similar results in 72% of the cases compared with other WQIs that were based on larger set of parameters. Based on our finding, we suggest the wider use WQI_m in developing countries for assessing health of SSWBs, as it will minimize the analytical cost to overcome the budget constraints involved in this kind of evaluations. It was observed that except turbidity and TC content, all other quality parameters fluctuated within the limit of the World Health Organization suggested standards for drinking water. From our findings, we concluded that if the turbidity and TC content of water from SSWBs in CMPA are taken care of, they will become good candidates as alternative water resources all round the year.     

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.     

Application of CCME Water Quality Index to Monitor Water Quality: A Case Study of the Mackenzie River Basin, Canada

All six ecosystem initiatives evolved from many years of federal, provincial, First Nation, local government and community attention to the stresses on sensitive habitats and species, air and water quality, and the consequent threats to community livability. This paper assesses water quality aspect for the ecosystem initiatives and employs newly developed Canadian Council of Ministers of the Environment Water Quality Index (CCME WQI) which provides a convenient mean of summarizing complex water quality data that can be easily understood by the public, water distributors, planners, managers and policy makers. The CCME WQI incorporates three elements: Scope – the number of water quality parameters (variables) not meeting water quality objectives (F ₁); Frequency – the number of times the objectives are not met (F ₂); and Amplitude. the extent to which the objectives are not met (F ₃). The index produces a number between 0 (worst) to 100 (best) to reflect the water quality. This study evaluates water quality of the Mackenzie – Great Bear sub-basin by employing two modes of objective functions (threshold values): one based on the CCME water quality guidelines and the other based on site-specific values that were determined by the statistical analysis of the historical data base. Results suggest that the water quality of the Mackenzie-Great Bear sub-basin is impacted by high turbidity and total (mostly particulate) trace metals due to high suspended sediment loads during the open water season. Comments are also provided on water quality and human health issues in the Mackenzie basin based on the findings and the usefulness of CCME water quality guidelines and site specific values.     

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.     

Integrated survey of water pollution in the Suquía River basin (Córdoba, Argentina)

We report a combined two-year seasonal monitoring of Suquía River basin using both chemical parameters and biomarkers measured in Jenynsia multidentata, aiming to correlate external levels of contaminants with the response of oxidative stress biomarkers in this fish. Identified pollution sources correspond to city sewage as well as agricultural and small industry activities downstream from Córdoba city. Physicochemical parameters integrated into a water quality index (WQI) were measured in Suquía River during dry and wet seasons. Ag, Mn, Cu, Cr, Ni, Fe, Pb and Zn were also monitored in water and sediment samples. Biomarkers include detoxication and antioxidant enzymes: catalase (CAT), glutathione peroxidase (GPX), glutathione S-transferase (GST) and glutathione reductase (GR). Enzymes showed a pollution dependent response, with increased activities in fish collected close to the sewage exit and progressive drop further downstream, matching changes in the Water Quality index. The combined use of biomarkers with water quality parameters allowed both the identification of pollution sources and the evaluation of effects of contaminants on the aquatic biota.     

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 Changes in Chini Lake, Pahang, West Malaysia

A study of the water quality changes of Chini Lake was conducted for 12 months, which began in May 2004 and ended in April 2005. Fifteen sampling stations were selected representing the open water body in the lake. A total of 14 water quality parameters were measured and Malaysian Department of Environment Water Quality Index (DOE-WQI) was calculated and classified according to the Interim National Water Quality Standard, Malaysia (INWQS). The physical and chemical variables were temperature, dissolved oxygen (DO), conductivity, pH, total dissolved solid (TDS), turbidity, chlorophyll-a, biochemical oxygen demand (BOD), chemical oxygen demand (COD), total suspended solid (TSS), ammonia-N, nitrate, phosphate and sulphate. Results show that base on Malaysian WQI, the water in Chini Lake is classified as class II, which is suitable for recreational activities and allows body contact. With respect to the Interim National Water Quality Standard (INWQS), temperature was within the normal range, conductivity, TSS, nitrate, sulphate and TDS are categorized under class I. Parameters for DO, pH, turbidity, BOD, COD and ammonia-N are categorized under class II. Comparison with eutrophic status indicates that chlorophyll-a concentration in the lake was in mesotrophic condition. In general water quality in Chini Lake varied temporally and spatially, and the most affected water quality parameters were TSS, turbidity, chlorophyll-a, sulphate, DO, ammonia-N, pH and conductivity.     

2001-2015年松花江流域水污染变化特征研究

利用2001-2015年松花江流域国家监测网30个可比断面监测数据，从流域和断面水质变化、各项指标超标情况和浓度变化、污染负荷等方面分析了松花江流域水质变化情况。结果表明，松花江流域水质总体呈好转趋势，特别是2007年以来有比较明显的改善。该流域长期以来主要污染指标为高锰酸盐指数、石油类、五日生化需氧量和氨氮。高锰酸盐指数、石油类和五日生化需氧量污染均有明显改善，但氨氮污染改善不明显。在继续加强COD排放总量控制的基础上，有效削减氨氮排放是促进松花江水质改善的重点。     

Development of groundwater quality index

Assessing the water quality status for special use is the main objective of any water quality monitoring studies. The water quality index (WQI) is a mathematical instrument used to transform large quantities of water quality data into a single number which represents the water quality level. In fact, developing WQI in an area is a fundamental process in the planning of land use and water resources management. In this study, a simple methodology based on multivariate analysis is developed to create a groundwater quality index (GWQI), with the aim of identifying places with best quality for drinking within the Qazvin province, west central of Iran. The methodology is based on the definition of GWQI using average value of eight cation and anion parameters for 163 wells during a 3-year period. The proportion of observed concentrations to the maximum allowable concentration is calculated as normalized value of each parameter in observing wells. Final indices for each well are calculated considering weight of each parameter. In order to assess the groundwater quality of study area, the derived indices are compared with those of well-known mineral waters. Using developed indices, groundwater iso-index map for study area and the map of areas of which the indices are near to mineral waters was drawn. In the case study, the GWQI map reveals that groundwater quality in two areas is extremely near to mineral water quality. Created index map provides a comprehensive picture of easily interpretable for regional decision makers for better planning and management.     

Surface Water Quality Assessment by Environmetric Methods

This environmetric study deals with the interpretation of river water monitoring data from the basin of the Buyuk Menderes River and its tributaries in Turkey. Eleven variables were measured to estimate water quality at 17 sampling sites. Factor analysis was applied to explain the correlations between the observations in terms of underlying factors. Results revealed that, water quality was strongly affected from agricultural uses. Cluster analysis was used to classify stations with similar properties and results distinguished three groups of stations. Water quality at downstream of the river was quite different from the other part. It is recommended to involve the environmetric data treatment as a substantial procedure in assessment of water quality data.     

Water quality indices as indicators of ecosystem change

The operational management of water quality requires a methodology that can provide precise information on cycles and trends in water quality in an objective and reproducible manner. Such information can be provided by the adoption of a water quality indexing system. The continuous scale afforded by a water quality index allows changes in river water quality to be highlighted. At the same time the sub-division of this scale into a series of water quality and water use categories provides an easy means of relating information to government and public.The development of four independent water quality indices (WQIs) is outlined. These have been applied to data for a number of UK river reaches. The results of these applications indicate the utility of these indices in the classification of water quality and the monitoring of ecosystem change.     

长江源区河流及典型湖泊丰水期水质与鱼类群落分析

为加强长江源区水生态研究,于2017年丰水期调查了长江源区5个湖泊、5条河流的水质和鱼类资源状况,并研究了其空间格局.水质综合指数(WQI)计算结果显示,长江源区WQI范围为41～87,评价等级介于差到良好之间,大部分采样点的水质评价等级为一般,其中,班德湖的水质评价等级为良好.主成分分析结果显示,长江源区河流、淡水湖...     

Water quality index for agricultural systems in Northwest Uruguay

Agricultural systems have experienced rapid expansion and intensification in the last several decades. In Uruguay, since the beginning of 2000, the most common cropping systems have included soybeans. Currently, this crop is expanding towards lowlands traditionally occupied by rice in rotation with pastures. However, the environmental effects of agricultural intensification and diversification are not well known. Thus, some indices have been proposed to quantify the changes in agricultural production systems and assess water quality. The main goal of this study was to develop a water quality index (WQI) to assess the impacts of the diversification of rice production systems in northwest Uruguay. The study was carried out in an agricultural basin where other summer crops have been incorporated in the rice-pasture sequence. Agriculture intensification and crop diversification indices were calculated using information provided by farmers. Water samples were collected downstream of the production area before crop sowing and after crop harvest (2008–2009 to 2010–2011 and 2016–2017 to 2017–2018). Biochemical oxygen demand, nitrates, total phosphorus, fecal coliforms, and total suspended solids were the variables that mainly explained the effects of the agricultural activities on water quality. The proposed water quality index included these unweighted variables, which allowed for the pre-sowing and post-harvest to be differentiated, as well as the degree of diversification. Therefore, the proposed WQI constitutes a tool that can be used to evaluate the water quality in an agricultural basin. Likewise, it can be used to select agricultural sequences that generate the least possible impacts on the associated water resources.