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.     

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 in Lis river, Portugal

In the past 30?years, the Lis river basin has been subjected to constant ecological disasters mainly due to piggery untreated wastewater discharges. The aim of this study was to evaluate the effect of existing domestic, agricultural, and industrial activities on the water quality, and to propose a watershed plan to protect and manage surface water resources within the Lis river basin. For this purpose, 16 monitoring stations have been strategically selected along the Lis river stretch and its main tributaries to evaluate the water quality in six different sampling periods (2003–2006). All samples were characterized in terms of organic material, nutrients, chlorophyll, and pathogenic bacteria. Generally, the Lis river presents poor water quality, according to environmental quality standards for surface water, principally in terms of dissolved oxygen, biochemical oxygen demand, total nitrogen, and fecal coliform, which can be associated mainly with the contamination source from pig-breeding farms.     

Physical and chemical characteristics of water from the hydrographic basin of the Poxim River, Sergipe State, Brazil

The Poxim River is one of Sergipe State’s major waterways. It supplies water to the State capital, Aracaju, but is threatened by urban and agricultural developments that compromise both the quantity and the quality of the water. This has direct impacts on the daily lives of the region’s population. In this work, a multivariate analytical approach was used to investigate the physical and chemical characteristics of the water in the river basin. Four sampling campaigns were undertaken, in November 2005, and in February, May, and September 2006, at 15 sites distributed along the Poxim. The parameters analyzed were conductivity, turbidity, color, total dissolved solids, dissolved oxygen, alkalinity, hardness, chlorophyll-a, and nutrients (total phosphorus, dissolved orthophosphate, nitrite, nitrate, ammoniacal nitrogen, and total nitrogen). Dissolved oxygen contents were very low in the Poxim-Açu River (1.0–2.8), the Poxim River (1.6–4.6), and the estuarine region (1.7–5.1), due to the dumping of wastes and discharges of domestic and industrial effluents containing organic matter into fluvial and estuarine regions of the Poxim. Factor analysis identified five components that were indicative of the quality of the water, and that explained 81.73 % of the total variance.     

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.     

Spatiotemporal classification of environmental monitoring data in the Yeongsan River basin, Korea, using self-organizing maps

Environmental monitoring data for planning, implementing and evaluating the Total Maximum Daily Loads (TMDL) management system have been measured at about 8-day intervals in a number of rivers in Korea since 2004. In the present study, water quality parameters such as Suspended Solids (SS), Biochemical Oxygen Demand (BOD), Dissolved Oxygen (DO), Total Nitrogen (TN), and Total Phosphorus (TP) and the corresponding runoff were collected from six stations in the Yeongsan River basin for six years and transformed into monthly mean values. With the primary objective to understand spatiotemporal characteristics of the data, a methodologically systematic application of a Self-Organizing Map (SOM) was made. The SOM application classified the environmental monitoring data into nine clusters showing exclusively distinguishable patterns. Data frequency at each station on a monthly basis identified the spatiotemporal distribution for the first time in the study area. Consequently, the SOM application provided useful information that the sub-basin containing a metropolitan city is associated with deteriorating water quality and should be monitored and managed carefully during spring and summer for water quality improvement in the river basin.     

Phase I of the Kissimmee River restoration project, Florida, USA: Impacts of construction on water quality

Phase I of the Kissimmee River restoration project included backfilling of 12 km of canal and restoring flow through 24 km of continuous river channel. We quantified the effects of construction activities on four water quality parameters (turbidity, total phosphorus flow-weighted concentration, total phosphorus load and dissolved oxygen concentration). Data were collected at stations upstream and downstream of the construction and at four stations within the construction zone to determine if canal backfilling and construction of 2.4 km of new river channel would negatively impact local and downstream water quality. Turbidity levels at the downstream station were elevated for approximately 2 weeks during the one and a half year construction period, but never exceeded the Florida Department of Environmental Protection construction permit criteria. Turbidity levels at stations within the construction zone were high at certain times. Flow-weighted concentration of total phosphorus at the downstream station was slightly higher than the upstream station during construction, but low discharge limited downstream transport of phosphorus. Total phosphorus loads at the upstream and downstream stations were similar and loading to Lake Okeechobee was not significantly affected by construction. Mean water column dissolved oxygen concentrations at all sampling stations were similar during construction.     

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.     

龙江河流域水环境突发事件智能监控预警系统构建研究

系统调研分析广西龙江河流域内工业企业发展情况、重点污染源排污特征及流域污染监控现状,探索该河流域水环境突发事件智能化监控预警系统构建的思路。提出以水质常规五参数、有机物指标、富营养化指标、特征性指标、生物指标等为重点监控因子,根据全流域监控与分片监控相结合的原则,在现有的河流水质自动站基础上增加建设2座水质自动站。同时,结合龙江河流域的实际情况,提出运用新一代物联网技术构建智能化监控预警系统,实现立体感知、多维数据融合、数据高速传输、信息实时发布、超标预警、可视化展示、应急决策指挥等功能。     

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.     

The use of multivariate statistical methods for optimization of the surface water quality network monitoring in the Paraopeba river basin,Brazil

This study sought to evaluate and propose adjustments to the water quality monitoring network of surface freshwaters in the Paraopeba river basin (Minas Gerais, Brazil), using multivariate statistical methods. A total of 13,560 valid data were analyzed for 19 water quality parameters at 30 monitoring sites, over a period of 5 years (2008–2013). The cluster analysis grouped the monitoring sites in eight groups based on similarities of water quality characteristics. This analysis made it possible to detect the most relevant monitoring stations in the river basin. The principal components analysis associated with non-parametric tests and the analysis of violation of the standards prescribed by law, allowed for identifying the most relevant parameters which must be maintained in the network (thermotolerant coliforms, total manganese, and total phosphorus). The discharge of domestic sewage and industrial wastewater, that from mining activities and diffuse pollution from agriculture and pasture areas are the main sources of pollution responsible for the surface water quality deterioration in this basin. The BP073 monitoring site presents the most degraded water quality in the Paropeba river basin. The monitoring sites BP094 and BP092 are located geographically close and they measure similar water quality, so a possible assessment of the need to maintain only one of the two in the monitoring network is suggested. Therefore, multivariate analyses were efficient to assess the adequacy of the water quality monitoring network of the Paraopeba river basin, and it can be used in other watersheds.     

Testing taxonomic resolution levels for detecting environmental impacts using macrobenthic assemblages in tropical waters

Delta regions of the Cauvery River basin are one of the significant areas of rice production in India. In spite of large-scale utilization of the river basin for irrigation and drinking purposes, the lack of appropriate water management has seemingly deteriorated the water quality due to increasing anthropogenic activities. To assess the extent of deterioration, physicochemical characteristics of surface water were analyzed monthly in select regions of Cauvery Delta River basin, India, during July 2007 to December 2007. Total dissolved solids, chemical oxygen demand, and phosphate recorded maximum levels of 1,638, 96, and 0.43 mg/l, respectively, exceeding the permissible levels at certain sampling stations. Monsoonal rains in Cauvery River basin and the subsequent increase in river flow rate influences certain parameters like dissolved solids, phosphate, and dissolved oxygen. Agricultural runoff from watershed, sewage, and industrial effluents are suspected as probable factors of water pollution.     

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。     

Evaluation of surface water quality characteristics by using multivariate statistical techniques: A case study of the Euphrates river basin, Turkey

The surface water quality of the Euphrates river basin in Turkey are evaluated by using the multivariate statistical techniques known as factor analysis (FA) and multidimensional scaling (MDS) analysis. When FA was applied to the water quality data obtained from the 15 different surface water quality monitoring stations, two factors were identified, which were responsible from the 86.02% of the total variance of the water quality in the Euphrates river basin. The first factor called the urban land use factor explained 44.20% of the total variance and the second factor called the agricultural use factor explained 41.81% of the total variance. MDS technique showed that electrical conductivity (EC), percent sodium (Na%) and total salt are the most important variables causing difference in the water quality analysis.     

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.     

Spatial pattern assessment of river water quality: implications of reducing the number of monitoring stations and chemical parameters

The Tamsui River basin is located in Northern Taiwan and encompasses the most metropolitan city in Taiwan, Taipei City. The Taiwan Environmental Protection Administration (EPA) has established 38 water quality monitoring stations in the Tamsui River basin and performed regular river water quality monitoring for the past two decades. Because of the limited budget of the Taiwan EPA, adjusting the monitoring program while maintaining water quality data is critical. Multivariate analysis methods, such as cluster analysis (CA), factor analysis (FA), and discriminate analysis (DA), are useful tools for the statistically spatial assessment of surface water quality. This study integrated CA, FA, and DA to evaluate the spatial variance of water quality in the metropolitan city of Taipei. Performing CA involved categorizing monitoring stations into three groups: high-, moderate-, and low-pollution areas. In addition, this categorization of monitoring stations was in agreement with that of the assessment that involved using the simple river pollution index. Four latent factors that predominantly influence the river water quality of the Tamsui River basin are assessed using FA: anthropogenic pollution, the nitrification process, seawater intrusion, and geological and weathering processes. We plotted a spatial pattern using the four latent factor scores and identified ten redundant monitoring stations near each upstream station with the same score pattern. We extracted five significant parameters by using DA: total organic carbon, total phosphorus, As, Cu, and nitrate, with spatial variance to differentiate them from the polluted condition of the group obtained by using CA. Finally, this study suggests that the Taiwan EPA can adjust the surface water-monitoring program of the Tamsui River by reducing the monitoring stations to 28 and the measured chemical parameters to five to lower monitoring costs.     

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 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.     

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.