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.     

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.     

A real-time monitoring system for Kerava river quality

The hygienic quality of the water of the Kerava river, southern Finland, deteriorates occasionally. The purpose of the study was to design a real-time monitoring system that would inform the public using the river for recreational purposes about the changes in water quality. The system was constrained to consist of on-line sensing of water quality and quantity, and adjacent forecasting models. Four different system alternatives were analyzed and compared. The first alternative observes river flow in real-time; the second alternative also monitors water temperature, turbidity, pH, conductivity and dissolved oxygen. The data collected in this way are used to forecast Streptococcus and E. coli concentrations, using canonical correlation and regression analysis. The third configuration is a two-step procedure, where river flow is first predicted by an ARMAX model and the hygienic state is then based on the flow estimate, as in the first assemblage. The most expensive monitoring system, which at present is the least well-known, is to apply the Lidar system, where the hygienic status of the river quality is observed directly using laser technology, placing less emphasis on modeling. In this paper, the alternatives are formulated and a preliminary comparison is made, using the criteria of operational feasibility, prediction uncertainty, investment and maintenance costs, and suitability for in-situ monitoring.     

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.     

Detection of water quality changes along a river system

Water quality monitoring networks are generally multi-purpose, and thus the data generated are expected to provide information on a set of objectives. Two questions that are fundamental to these objectives are the detection of long term trends and of differences between locations. The extent to which these questions can be answered and the types of statistical methods which can be used are considered in a case study of conventional parameters sampled monthly for nine years. Regression and nonparametric methods, which explicitly account for seasonality, are compared for both the determination of change over time and of differences between locations. Changes over time in the form of step changes and differences between locations which depend upon season were found.     

Chemometric characterization of river water quality

Various industrial facilities in the city of Varanasi discharge their effluent mixed with municipal sewage into the River Ganges at different discharge points. In this study, chemometric tools such as cluster analysis and box–whisker plots were applied to interpret data obtained during examination of River Ganges water quality. Specifically, we investigated the temperature (T), pH, total alkalinity, total acidity, electrical conductivity (EC), biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), nitrate nitrogen (N), phosphate (PO ₄ ^2? ), copper (Cu), cadmium (Cd), chromium (Cr), nickel (Ni), iron (Fe), lead (Pb), and zinc (Zn) in water samples collected from six sampling stations. Hierarchical agglomerative cluster analysis was conducted using Ward’s method. Proximity distance between EC and Cr was the smallest revealing a relationship between these parameters, which was confirmed by Pearson’s correlation. Based on proximity distances, EC, Cr, Ni, Fe, N, COD, temperature, BOD, and total acidity comprised one group; Zn, Pb, Cd, total alkalinity, Cu, and phosphate (PO ₄ ^2? ) were in another group; and DO and pH formed a separate group. These groups were confirmed by Pearson’s correlation (r) values that indicated significant and positive correlation between variables in the same group. Box–whisker plots revealed that as we go downstream, the pollutant concentration increases and maximum at the downstream station Raj Ghat and minimum at the upstream station Samane Ghat. Seasonal variations in water quality parameters signified that total alkalinity, total acidity, DO, BOD, COD, N, phosphate (PO ₄ ^2? ), Cu, Cd, Cr, Ni, Fe, Pb, and Zn were the highest in summer (March–June) and the lowest during monsoon season (July–October). Temperature was the highest in summer and the lowest in winter (November–February). DO was the highest in winter and the lowest in summer season. pH was observed to be the highest in monsoon and the lowest in summer season.     

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.     

Deterioration of water quality of Surma river

Surma River is polluted day by day by human activities, poor structured sewerage and drainage system, discharging industrial and household wastes. The charas (natural channels) are responsible for surface runoff conveyance from its urban catchments to the receiving Surma River. Water samples have been collected from a part of Surma River along different points and analyzed for various water quality parameters during dry and monsoon periods. Effects of industrial wastes, municipal sewage, and agricultural runoff on river water quality have been investigated. The study was conducted within the Chattak to Sunamganj portion of Surma River, which is significant due to the presence of two major industries – a paper mill and a cement factory. The other significant feature is the conveyors that travel from India to Chattak. The river was found to be highly turbid in the monsoon season. But BOD and fecal coliform concentration was found higher in the dry season. The water was found slightly acidic. The mean values of parameters were Conductivity 84–805 μs; DO: dry-5.52 mg/l, monsoon-5.72 mg/l; BOD: dry-1mg/l, monsoon-0.878 mg/l; Total Solid: dry-149.4 mg/l, monsoon-145.7 mg/l. In this study, an effort has been taken to investigate the status of concentration of phosphate (PO⁻⁴) and ammonia–nitrogen (NH₄–N) at four entrance points of Malnichara to the city, Guali chara, Gaviar khal and Bolramer khal. Data has been collected from March–April and September–October of 2004. Concentrations have been measured using UV Spectrophotometer. Although the phosphate concentration has been found within the limit set by DOE for fishing, irrigation and recreational purposes, however ammonia–nitrogen has been found to exceed the limit.     

Revising river water quality monitoring networks using discrete entropy theory: the Jajrood River experience

This paper aims at evaluating and revising the spatial and temporal sampling frequencies of the water quality monitoring system of the Jajrood River in the Northern part of Tehran, Iran. This important river system supplies 23% of domestic water demand of the Tehran metropolitan area with population of more than 10 million people. In the proposed methodology, by developing a model for calculating a discrete version of pair-wise spatial information transfer indices (SITIs) for each pair of potential monitoring stations, the pair-wise SITI matrices for all water quality variables are formed. Also, using a similar model, the discrete temporal information transfer indices (TITIs) using the data of the existing monitoring stations are calculated. Then, the curves of the pair-wise SITI versus distance between monitoring stations and TITI versus time lags for all water quality variables are derived. Then, using a group pair-wise comparison matrix, the relative weights of the water quality variables are calculated. In this paper, a micro-genetic-algorithm-based optimization model with the objective of minimizing a weighted average spatial and temporal ITI is developed and for a pre-defined total number of stations, the best combination of monitoring stations is selected. The results show that the existing monitoring system of the Jajrood River should be partially strengthened and in some cases the sampling frequencies should be increased. Based on the results, the proposed approach can be used as an effective tool for evaluating, revising, or redesigning the existing river water quality monitoring systems.     

跨界河流水质联合监测可比性探讨

影响中哈联合监测可比性的主要因素是由于中哈跨界河流联合监测分析方法和评价方法等方面不统一,因此导致监测结果存在差异。对双方联合监测数据进行实验室间相对平均偏差、数据显著性差异检验t检验、F检验和一元一次线性回归方程分析表明:只要双方采取共同措施,可以最大程度消除分析结果中存在的差异,特别是对超标项目提供论据,可以增加对跨界水体污染程度认知的一致性。     

Optimization models for siting water quality monitoring stations in a catchment

A water quality monitoring network (WQMN) must be designed so as to adequately protect the water quality in a catchment. Although a simulated annealing (SA) method was previously applied to design a WQMN, the SA method cannot ensure the solution it obtained is the global optimum. Therefore, two new linear optimization models are proposed in this study to minimize the deviation of the cost values expected to identify the possible pollution sources based on uniform cost (UC) and coverage elimination uniform cost (CEUC) schemes. The UC model determines the expected cost values by considering each sub-catchment being covered by which station, while the CEUC model determines the coverage of each station by eliminating the area covered by any upstream station. The proposed models are applied to the Derchi reservoir catchment in Taiwan. Results show that the global optimal WQMN can be effectively determined by using the UC or CEUC model, for which both results are better than those from the SA method, especially when the number of stations becomes large.     

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.     

Intensive water quality monitoring in a Taiwan bathing beach

A total of 357 water samples were collected from a public beach in northern Taiwan during beach season, and the densities of enterococci were analyzed by Enterolert methods. The mean enterococci level was 356 MPN/100 ml and ranged from <10 to 2,005 MPN/100 ml, which was classified as high contamination level according to the WHO water quality guideline (95 percentile >1,000 MPN/100 ml). Most of the deteriorated water quality conditions occurred during rainfall. By excluding data from the rain days, the overall beach water quality would be considered in the moderate contamination level (95 percentile 200-1,000 MPN/100 ml). Among the selected microbiological parameters tested, the densities of total coliforms and enterococci exhibited the highest correlation (r = 0.449, p = 0.009), followed by the concentrations of total coliforms and fecal coliforms (r = 0.403, p = 0.02). Nonetheless, no significant correlation was found between enterococci and fecal coliform levels (r = 0.197, p = 0.271).     

Performance of two artificial substrate samplers for macroinvertebrates in biological monitoring of large and deep rivers and canals in Belgium and The Netherlands

Harmonization exercises organized by the European Communities in the 1970s on biological water assessment methods for running waters, because the usual methods were difficult or impossible to apply, explicitly stressed the need for development of standardized sampling procedures for monitoring large and deep rivers and canals. To meet this objective, an extensive monitoring campaign was organized in Belgium and The Netherlands to test the efficiency of artificial substrates colonized by macroinvertebrates as an alternative for natural communities sampled with a handnet. Two types of artificial substrates were tested: a Belgian substrate, composed of a plastic netting filled with medium-sized pieces of brick, and a Dutch substrate consisting of a stainless steel box filled with marbles. The collected biocoenoses were compared qualitatively and quantitatively. Water quality was assessed by means of several biotic indexes. The results show that both the Belgian and the Dutch artificial substrate sampler can replace the usual samples obtained by means of a handnet, and provide a correct assessment. A major drawback of the use of artificial substrates in uncontrolled monitoring sites remains the unforeseen losses. For that reason the cost price of the substrates may have to be considered when making a selection.     

Linking biological and physicochemical water quality

To define water quality, the European Water Framework Directive (WFD) demands complex assessments through physicochemical, biological, and hydromorphological controls of water bodies. Since the biological assessment became the central focus with hydrochemistry playing a supporting role, an evaluation of the interrelationships within this approach deems necessary. This work identified and tested these relationships to help improve the quality and efficiency of related efforts. Data from the 384 km² Weisseritz catchment (eastern Erzgebirge, Saxony, Germany and northern Bohemia, Czech Republic) were used as a representative example for central European streams in mountainous areas. The data cover the time frame 1992 to 2003. To implement WFD demands, the analysis was based on accepted German methods and classifications, WFD quality standards, and novel German methods for the biological status assessment. Selected chemical parameters were compared with different versions of the German Saprobic Index, based on macroinvertebrate indicator taxa. Relevant dependencies applicable for integrated stream assessment were statistically tested. Correlation analysis showed significant relationships. The highest scores were found for nutrients (NO₂ ^???, N_inorg, and total N), salinity (Cl^???, SO₄ ^2???, conductivity), and microelements (K^?+?, Na^?+?, Ca^2?+?, Mg^2?+?). The Saprobic Index used in the Integrated Assessment System for the Ecological Quality of Streams and Rivers throughout Europe using Benthic Macro-invertebrates program seems to be the most sensitive indicator to correlate with chemical parameters.     

A saprobic index for biological assessment of river water quality in Brazil (Minas Gerais and Rio de Janeiro states)

Based upon several years of experience in investigations with macrozoobenthos in rivers in the states of Minas Gerais and Rio de Janeiro, a biological assessment system has been developed to indicate pollution levels caused by easily degradable organic substances from sewers. The biotic index presented here is aimed at determining water’s saprobic levels and was, therefore, named the “Saprobic Index for Brazilian Rivers in Minas Gerais and Rio de Janeiro states” (ISMR). For this purpose, saprobic valences and weights have been established for 122 taxa of tropical macrozoobenthos. Investigations were carried out in little, medium sized and big rivers in mountains and plains. Through ISMR, a classification of water quality and the respective cartographic representation can be obtained. Data collection and treatment methods, as well as the limitations of the biotic index, are thoroughly described. ISMR can also be used as an element to establish complex multimetric indexes intended for an ecological integrity assessment, where it is essential to indicate organic pollution.     

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 new nanosilver-based spectrophotometric method for monitoring Eriochrome black T in river water

In this paper, a new spectrophotometric method is reported for the determination of nanomolar levels of Eriochrome black T in environmental samples. The method is based on the catalytic effect of silver nanoparticles on the oxidation of Eriochrome black T by hexacyanoferrate (III) in acetate–acetic acid medium and at 25 °C. The absorbance is measured at 512 nm with the fixed-time method. It relies on the linear relationship between the absorbance difference (?A) and Eriochrome black T amounts in the range of 40–1,250 nM. Under optimum conditions, the sensitivity of the proposed method, i.e., the detection limit corresponding to 80 s, is about 25 nM. The method is featured with good accuracy and reproducibility for Eriochrome black T determination in river water samples without any pre-concentration and separation step.     

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.