Water quality of arctic rivers in Finnish Lapland

The water quality monitoring data of eight rivers situated in the Finnish Lapland above the Arctic Circle were investigated. These rivers are icebound annually for about 200 days. They belong to the International River Basin District founded according to the European Union Water Framework Directive and shared with Norway. They are part of the European river monitoring network that includes some 3,400 river sites. The water quality monitoring datasets available varied between the rivers, the longest comprising the period 1975–2003 and the shortest 1989–2003. For each river, annual medians of eight water quality variables were calculated. In addition, medians and fifth and 95th percentiles were calculated for the whole observation periods. The medians indicated good river water quality in comparison to other national or foreign rivers. However, the river water quality oscillated widely. Some rivers were in practice in pristine state, whereas some showed slight human impacts, e.g., occasional high values of hygienic indicator bacteria.     

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.     

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.     

Using multivariate techniques as a strategy to guide optimization projects for the surface water quality network monitoring in the Velhas river basin,Brazil

Surface water quality monitoring networks are usually deployed and rarely re-evaluated with regard to their effectiveness. In this sense, this work sought to evaluate and to guide optimization projects for the water quality monitoring network of the Velhas river basin, using multivariate statistical methods. The cluster, principal components, and factorial analyses, associated with non-parametric tests and the analysis of violation to the standards set recommended by legislation, identified the most relevant water quality parameters and monitoring sites, and evaluated the sampling frequency. Thermotolerant coliforms, total arsenic, and total phosphorus were considered the most relevant parameters for characterization of water quality in the river basin. The monitoring sites BV156, BV141, BV142, BV150, BV137, and BV153 were considered priorities for maintenance of the network. The multivariate statistical analysis showed the importance of a monthly sampling frequency, specifically the parameters considered most important.     

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.     

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.     

Design of sampling locations for river water quality monitoring considering seasonal variation of point and diffuse pollution loads

The design of a water quality monitoring network (WQMN) is a complicated decision-making process because each sampling involves high installation, operational, and maintenance costs. Therefore, data with the highest information content should be collected. The effect of seasonal variation in point and diffuse pollution loadings on river water quality may have a significant impact on the optimal selection of sampling locations, but this possible effect has never been addressed in the evaluation and design of monitoring networks. The present study proposes a systematic approach for siting an optimal number and location of river water quality sampling stations based on seasonal or monsoonal variations in both point and diffuse pollution loadings. The proposed approach conceptualizes water quality monitoring as a two-stage process; the first stage of which is to consider all potential water quality sampling sites, selected based on the existing guidelines or frameworks, and the locations of both point and diffuse pollution sources. The monitoring at all sampling sites thus identified should be continued for an adequate period of time to account for the effect of the monsoon season. In the second stage, the monitoring network is then designed separately for monsoon and non-monsoon periods by optimizing the number and locations of sampling sites, using a modified Sanders approach. The impacts of human interventions on the design of the sampling net are quantified geospatially by estimating diffuse pollution loads and verified with land use map. To demonstrate the proposed methodology, the Kali River basin in the western Uttar Pradesh state of India was selected as a study area. The final design suggests consequential pre- and post-monsoonal changes in the location and priority of water quality monitoring stations based on the seasonal variation of point and diffuse pollution loadings.     

Statistical needs in national water quality monitoring programs

The concept that a few well chosen, strategically placed, water quality stations can provide valuable scientific information to water managers is common to many countries. Historically within Canada, water quality regional networks (Great Lakes network, Prairie Provinces Water Board network, Long Range Transport of Airborne Pollutants network, etc.) have been successfully operating for many years. This paper will describe the difficulties associated with developing a national water quality network for a country the size of Canada. In particular, it will describe some of the statistical tools presently being used in regional networks which are suitable for a national network, and discuss the need to develop new statistical tools for environmental monitoring in the 1990's.     

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 %.     

Evaluation of violations in water quality standards in the monitoring network of São Francisco River basin,the third largest in Brazil

The São Francisco River is the largest river located entirely within Brazil, and water scarcity problems have been a major concern of Brazilian society and government. Water quality issues are also a concern and have worsened with the recent intensification of urbanization and industrialization. In this study, violations to water quality standards established by local legislation were calculated as a percentage for 26 selected parameters over a monitoring period of 14 years. The violation percentages were analyzed spatially using the Kruskal-Wallis test, followed by multiple comparison analysis. Temporal analysis was performed using the Mann-Kendall test and Spearman correlation. Some parameters could be identified as cause for concern due to high violation levels, such as the fecal coliform indicator (FCI) and phosphorus—both related to domestic and effluent disposal without treatment or with insufficient treatment—and color, turbidity, manganese, and total suspended solids—which can be affected by erosive processes of natural and anthropogenic causes. The study found that these violations are concentrated in the most urbanized and industrialized areas of the basin. Some metallic parameters, such as iron and arsenic violations, may be related to mining activities in the rich soil of the Iron Quadrangle area located within the Minas Gerais State. Trend analysis results indicated that most monitoring stations did not have significant modification (elevation or reduction) trends over time, which, together with the high violation percentages, might indicate the maintenance of a scenario of constant pressure upon water resources, in particular in those more urbanized areas.     

Drinking water quality monitoring and surveillance for safe water supply in Gangtok, India

To ascertain the quality of drinking water being supplied, water quality monitoring and surveillance was conducted in Gangtok city at various treatment stages, service reservoirs, distribution network, public standposts, and households. No significant change in raw water quality was observed on day-to-day basis. Residual chlorine was found in the range of nil to 0.2 mg/l in the sump water/finished water. Throughout the year (i.e., during summer, winter, and monsoon seasons), the total coliform and fecal coliform counts were ranged from nil to 7 CFU/100 ml and nil to 3 CFU/100 ml, respectively, in sump water of Selep and VIP complex water treatment plant; however, at consumer end, those were observed as nil to 210 CFU/100 ml and nil to 90 CFU/100 ml, respectively. These variations in bacterial counts among the different service reservoirs and consumer ends may be attributed to the general management practices for maintenance of service reservoirs and the possibility of enroute contamination. Evaluation of the raw water quality indicates that the water is suitable for drinking after conventional treatment followed by disinfection. The finished water quality meets the level of standards described as per Bureau of Indian Standard specifications (BIS:10500 1991) for potability in terms of its physicochemical characteristics.     

Multi-objective, decision-based assessment of a water quality monitoring network in a river system

Water quality monitoring network design has historically tended to use experience, intuition and subjective judgement in locating monitoring stations. Better design procedures to optimize monitoring systems need to simultaneously identify significant planning objectives and consider a number of social, economic and environmental constraints. The consideration of multiple objectives may require further decision analysis to determine the preference weights associated with the objectives to aid in the decision-making process. This may require the application of an optimization study to extract such information from decision makers or experts and to evaluate the overall effectiveness of locating strategies. This paper assesses the optimal expansion and relocation strategies of a water quality monitoring network using a two-stage analysis. The first stage focuses on the information retrieval of preference weights with respect to the designated planning objectives. With the aid of a pre-emptive goal programming model, data analysis is applied to obtain the essential information from the questionnaire outputs. The second stage then utilizes a weighted multi-objective optimization approach to search for the optimal locating strategies of the monitoring stations in the river basin. Practical implementation is illustrated by a case study in the Kao-Ping River Basin, south Taiwan.     

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.     

Design of on-line river water quality monitoring systems using the entropy theory: a case study

The design of a water quality monitoring network is considered as the main component of water quality management including selection of the water quality variables, location of sampling stations and determination of sampling frequencies. In this study, an entropy-based approach is presented for design of an on-line water quality monitoring network for the Karoon River, which is the largest and the most important river in Iran. In the proposed algorithm of design, the number and location of sampling sites and sampling frequencies are determined by minimizing the redundant information, which is quantified using the entropy theory. A water quality simulation model is also used to generate the time series of the concentration of water quality variables at some potential sites along the river. As several water quality variables are usually considered in the design of water quality monitoring networks, the pair-wise comparison is used to combine the spatial and temporal frequencies calculated for each water quality variable. After selecting the sampling frequencies, different components of a comprehensive monitoring system such as data acquisition, transmission and processing are designed for the study area, and technical characteristics of the on-line and off-line monitoring equipment are presented. Finally, the assessment for the human resources needs, as well as training and quality assurance programs are presented considering the existing resources in the study area. The results show that the proposed approach can be effectively used for the optimal design of the river monitoring systems.     

Siting analyses for water quality sampling in a catchment

Pollution loads discharged from upstream development or human activities significantly degrade the water quality of a reservoir. The design of an appropriate water quality sampling network is therefore important for detecting potential pollution events and monitoring pollution trends. However, under a limited budgetary constraint, how to site an appropriate number of sampling stations is a challenging task. A previous study proposed a method applying the simulated annealing algorithm to design the sampling network based on three cost factors including the number of reaches, bank length, and subcatchment area. However, these factors are not directly related to the distribution of possible pollution. Thus, this study modified the method by considering three additional factors, i.e. total phosphorus, nitrogen, and sediment loads. The larger the possible load, the higher the probability of a pollution event may occur. The study area was the Derchi reservoir catchment in Taiwan. Pollution loads were derived from the AGNPS model with rainfall intensity estimated using the Thiessen method. Analyses for a network with various numbers of sampling sites were implemented. The results obtained based on varied cost factors were compared and discussed. With the three additional factors, the chosen sampling network is expected to properly detect pollution events and monitor pollution distribution and temporal trends.     

我国河流水质评价污染因子选择方案探讨

在选用综合污染指数法进行地表水水质评价时 ,由于污染因子选择不尽一致 ,造成地表水水质评价结果不具有可比性。为了使地表水评价结果具有可比性 ,必须选择相对固定的评价因子。笔者对我国七大流域 1 990～ 2 0 0 1年水质监测数据进行了全面分析 ,提出了能够反映我国河流污染现状的污染因子选择方案。     

The Duero Diatom Index (DDI) for river water quality assessment in NW Spain: design and validation

Diatom indices developed in certain geographic regions are frequently used elsewhere, despite the strong evidence that such metrics are less useful when applied in regions other than that where species–environment relationships were originally assessed, showing that species have particular autoecological requirements in different geographic areas. The goal of this study was to develop a new metric, the Duero Diatom Index (DDI), aimed at monitoring water quality in Duero basin watercourses (NW Spain). In summer 2008 and 2009, a total of 355 epilithic diatom samples were collected following standard protocols. The 2008 samples were used to develop the DDI, whereas the samples collected during 2009 were used in the index testing. Weighted averages method was used to derive the autoecological profiles of diatoms with respect to pH, conductivity, biological oxygen demand, ammonia, nitrates, and phosphates. The optimum and tolerance values for the measured environmental variables were determined for 137 taxa with abundances and frequencies of occurrence above 1 %, and subsequent trophic indicator and sensitivity values were defined for the DDI. The correlation between the observed and the diatom-inferred nutrient concentrations was highest for phosphates (ρ _S?=?0.72). Significant statistical relationship were observed between DDI values and the chemistry-based General Quality Index values (p?=?0.006) and the specific pollution index (SPI) diatom metric (p?=?0.04). DDI has demonstrated a better correlation with water chemistry than SPI diatom metric.     

Water quality indices across Europe--a comparison of the good ecological status of five river basins

The European Water Framework Directive (WFD) requires the definition of near-natural reference conditions to determine the extent of water bodies' deviation from "good ecological status" caused by stress gradients. However, the classification of ecological quality depends on the assessment method applied and the stressor concerned. While assessment methods that are generally applicable would be favourable, many European countries employ the locally developed water quality metrics that assess the impact of organic pollution (including eutrophication) and the associated decrease in dissolved oxygen. These indices do not specifically address stress from organic toxicants, such as pesticides. The aim of this study was to examine the performance of presently used assessment methods to identify reference conditions of non-contaminated streams in five selected European river basins, covering the geographical region from Spain to Finland, as a crucial prerequisite to indicate toxic gradients. The analysis comprised the Belgium biotic index (BBI), the biological monitoring working party (BMWP) scoring system and the revised German saprobic index. For comparison, we included an adaptation of the recently developed SPEAR index. In two previous field studies, this metric highly correlated with measured pesticide gradients. In this study, SPEAR was the only indicator that was generally applicable to all monitoring data and capable of determining "high ecological status" of reference conditions in all basins. Thus, based upon previous and own results, the authors suggest the species at risk (SPEAR) index to be potentially useful as a European-wide index to address deviations from "good ecological status" due to organic toxicants and recommend it for consideration in integrated water-resource evaluations under the WFD.     

Evaluation of drinking water treatment and quality in Takua Pa, Thailand

After 2004 Indian Ocean Tsunami, which hit and devastated several Countries in Southeast Asia, University of Brescia and Mahidol University started a project on water monitoring and treatment for drinking purposes in Takua Pa district (Thailand), the most damaged by the tsunami. In particular, this paper presents the results of a study conducted to evaluate the effectiveness of Takua Pa drinking water treatment plant and to identify actions that could be adopted to improve its performances. The results show that, even if the effluent usually meets Thai guide values, except for pH which is already too acid in the influent, the plant needs several structural and managerial improvements, such as filtration and sedimentation upgrade, coagulation/flocculation and final disinfection re-organization, use of proper registers to better plan and control employees activities. Moreover, it was determined that water quality in the distribution network is characterized by turbidity and organic matter values higher than those evaluated in the plant effluent.     

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.