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.     

Design of a new monitoring network and first testing of new biological assessment methods according to water framework directive

In most European member states, more or less completely new monitoring networks and assessment methods had to be developed as basic technical tools for the implementation of the EU Water Framework Directive (WFD). In the river basin of the Stever, the largest tributary to the river Lippe (River Rhine, Northrhine-Westphalia, Germany), a WFD-monitoring network was developed, and new German biological methods for rivers, developed for the purposes of the WFD, have been applied. Like most rivers in the German lowland areas, nearly all the river courses of the Stever system are altered by hydro-morphological degradation (straightening, bank fixation, lack of canopy etc.). In 2005 and 2006, the biological quality components of macroinvertebrates, fish and macrophytes were investigated and evaluated for the assessment of the ecological status of about 50 surface water bodies within the whole Stever system. Basic physical and chemical parameters, as well as priority substances, have been analysed in the same period. In this contribution, the design of the new monitoring network, the core principles of the German biological methods, and the most important results of the pilot monitoring will be presented. As main impacts with severe effects on the faunal and floral communities, the many migration barriers and the bad quality of the river morphology could be stated. Organic pollution is no more a severe problem in the Stever. The pilot project was successfully conducted in close collaboration with the water authorities (District Government Münster) and the water association Lippeverband.     

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).     

Application of statistical modeling to optimize a coastal water quality monitoring program

The long-term water quality monitoring program implemented by the Massachusetts Water Resources Authority in 1992 is extensive and has provide substantial understanding of the seasonality of the waters in both Boston Harbor and Massachusetts Bay and the response to improvements in effluent quality and offshore transfer of the effluent in September 2000. The monitoring program was designed with limited knowledge of spatial and temporal variability and long-term trends within the system. This led to an extensive spatial and temporal sampling program. The data through 2003 showed high correlation within physical parameters measured (e.g., salinity, dissolved oxygen) and in biological measures such as chlorophyll fluorescence. To address the potential sampling redundancies in the measurement program, an assessment of the impact of reduced levels of monitoring on the ability to make water quality decisions was completed. The optimization was conducted by applying statistical models that took into account whether there was evidence of a seasonal pattern in the data. The optimization used model survey average readings to identify temporal fixed effects, model survey-average-corrected individual station readings to identify spatial fixed effects, corrected the individual station readings for temporal and spatial fixed effects and derived a correlation model for the corrected data, and applied the correlation model to characterize the correlation of annual average readings from reduced monitoring programs with true parameter levels. Reductions in the number of sampling stations were found less detrimental to the quality of the data for annual decision-making than reductions in the number of surveys per year, although there is less of a difference in this regard for dissolved oxygen than there is for chlorophyll. The analysis led to recommendations for a substantially lower monitoring effort with minimal loss of information. The recommendation supported an annual budget savings of approximately $183,000. Most of the savings was from fewer surveys as approximately $21,000 came from the reduction in the number of stations monitored from 21 to 7 and associated laboratory analytical costs.     

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.     

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.     

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.     

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.     

水质分段法优化河流监测断面及其在水功能区达标监测中的应用

提出水质分段优化河流水质断面的原则和水质突变点确定的方法,将优化后省级尺度的监测断面直接用于地表水环境功能区达标监测,取得良好的环境效益和社会效益。     

Laser-induced breakdown spectroscopy application in environmental monitoring of water quality: a review

Water quality monitoring is a critical part of environmental management and protection, and to be able to qualitatively and quantitatively determine contamination and impurity levels in water is especially important. Compared to the currently available water quality monitoring methods and techniques, laser-induced breakdown spectroscopy (LIBS) has several advantages, including no need for sample pre-preparation, fast and easy operation, and chemical free during the process. Therefore, it is of great importance to understand the fundamentals of aqueous LIBS analysis and effectively apply this technique to environmental monitoring. This article reviews the research conducted on LIBS analysis for liquid samples, and the article content includes LIBS theory, history and applications, quantitative analysis of metallic species in liquids, LIBS signal enhancement methods and data processing, characteristics of plasma generated by laser in water, and the factors affecting accuracy of analysis results. Although there have been many research works focusing on aqueous LIBS analysis, detection limit and stability of this technique still need to be improved to satisfy the requirements of environmental monitoring standard. In addition, determination of nonmetallic species in liquid by LIBS is equally important and needs immediate attention from the community. This comprehensive review will assist the readers to better understand the aqueous LIBS technique and help to identify current research needs for environmental monitoring of water quality.     

Assessing temporal representativeness of water quality monitoring data

The effectiveness of different monitoring methods in detecting temporal changes in water quality depends on the achievable sampling intervals, and how these relate to the extent of temporal variation. However, water quality sampling frequencies are rarely adjusted to the actual variation of the monitoring area. Manual sampling, for example, is often limited by the level of funding and not by the optimal timing to take samples. Restrictions in monitoring methods therefore often determine their ability to estimate the true mean and variance values for a certain time period or season. Consequently, we estimated how different sampling intervals determine the mean and standard deviation in a specific monitoring area by using high frequency data from in situ automated monitoring stations. Raw fluorescence measurements of chlorophyll a for three automated monitoring stations were calibrated by using phycocyanin fluorescence measurements and chlorophyll a analyzed from manual water samples in a laboratory. A moving block bootstrap simulation was then used to estimate the standard errors of the mean and standard deviations for different sample sizes. Our results showed that in a temperate, meso-eutrophic lake, relatively high errors in seasonal statistics can be expected from monthly sampling. Moreover, weekly sampling yielded relatively small accuracy benefits compared to a fortnightly sampling. The presented method for temporal representation analysis can be used as a tool in sampling design by adjusting the sampling interval to suit the actual temporal variation in the monitoring area, in addition to being used for estimating the usefulness of previously collected data.     

A feasible method to assess inaccuracy caused by patchiness in water quality monitoring

Patchiness is a typical property of water quality in lakes. However, in conventional water quality monitoring, patchiness is usually too expensive to take into account, due to the high number of required samples. This study examines a feasible methodology developed for estimating the representativeness of discrete chlorophyll a measurements. Four spatially extensive data sets were collected from the Enonselkä basin of Lake Vesijärvi in Southern Finland, using a flow trough system with a fluorometer in a moving boat. Data sets were used to estimate (1) the spatial representativeness of discrete sampling; (2) the effect of varying sample size on the detected mean chlorophyll a concentration and on the observed proportion of variance. Spatial representativeness was assessed using semivariogram analysis. Results indicate that the spatial representativeness of discrete sampling can remain undesirably low. Furthermore, in monitoring programs involving just one or only a few samples, there is a significant risk of obtaining a false estimate for the mean value and variance of chlorophyll a concentration over the whole monitoring area.     

辽宁大伙房水库水质生态学监测的研究

1961～1996年对大伙房水库6个站进行了不同季节浮游植物、底栖动物群落特征的生态调查.共发现藻类8门,174种,底栖动物34种,分析了水生生物种类组成,数量变化和生物演替.水质生态学评价结果表明,大伙房水库只受到轻度污染,水质等级为2级.     

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

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

Application of water quality indices and analysis of the surface water quality monitoring network in semiarid North-Central Chile

Surface water quality has increasing importance worldwide and is particularly relevant in the semiarid North-Central Chile, where agriculture and mining activities are imposing heavy pressure on limited water resources. The current study presents the application of a water quality index in four watersheds of the 29°-33°S realm for the period 1999-2008, based on the Canadian Council of Ministers for the Environment approach and the Chilean regulation for irrigation water quality. In addition, two modifications to the index are tested and a comprehensive characterization of the existing monitoring network is performed through cluster analysis. The basins studied show fairly good water quality in the overall, specially the Limarí basin. On the other hand, the lower index values were obtained for the headwaters of Elqui, associated with the El Indio mining district. The first modification of the indicator (i.e., to consider parameters differentially according to their effect on human health or the environment) did not produce major differences with respect to the original index, given the generally good water quality. The second modification (i.e., to consider as threshold values the more restrictive figures derived from a set of regulations) yielded important differences in the indicator values. Finally, an adequate characterization of the monitoring network was obtained. The results presented spatial coherence and the information can be used as a basis for the optimization of the monitoring network if required.     

Efficiency of a standardized artificial substrate for biological monitoring of river water quality

Before using macroinvertebrates in water quality assessment in the Chusovaya River (Russia, the Urals, 50°55N, 60° E), preliminary results of three sampling methods were compared: handnet, circular shovel and a standardized artificial substrate sampler. The artificial substrate consisted of glass marbles ( 20 mm). To compare the efficiency of these sampling methods the total numbers of taxa found at each location per sampling data were considered to be 100%. The highest efficiency was reached with the artificial substrate sampler. 75–100% of the taxa at the different locations were collected with this sampler. Only 5–19% and 10–20% of the taxa at each location per sampling date were collected with the circular shovel in the sand and gravel substrate respectively, being the lowest efficiency. Intermediate results were obtained with the hand net. 23–38% of the taxa were collected with this net. Based on these results and requirements placed upon sampling methods in general, the standardized artificial substrate sampler has been considered to be an optimal sampling device for macroinvertebrates in biological monitoring.     

A systems approach to modeling Community-Based Environmental Monitoring: a case of participatory water quality monitoring in rural Mexico

Community-Based Environmental Monitoring (CBM) is a social practice that makes a valuable contribution to environmental management and construction of active societies for sustainable future. However, its documentation and analysis show deficiencies that hinder contrast and comparison of processes and effects. Based on systems approach, this article presents a model of CBM to orient assessment of programs, with heuristic or practical goals. In a focal level, the model comprises three components, the social subject, the object of monitoring, and the means of action, and five processes, data management, social learning, assimilation/decision making, direct action, and linking. Emergent properties were also identified in the focal and suprafocal levels considering community self-organization, response capacity, and autonomy for environmental management. The model was applied to the assessment of a CBM program of water quality implemented in rural areas in Mexico. Attributes and variables (indicators) for components, processes, and emergent properties were selected to measure changes that emerged since the program implementation. The assessment of the first 3 years (2010–2012) detected changes that indicated movement towards the expected results, but it revealed also the need to adjust the intervention strategy and procedures. Components and processes of the model reflected relevant aspects of the CBM in real world. The component called means of action as a key element to transit “from the data to the action.” The CBM model offered a conceptual framework with advantages to understand CBM as a socioecological event and to strengthen its implementation under different conditions and contexts.     

水环境质量综合评价的新模型

为检验已订的水环境质量评价标准的合理性,解决各单项水质指标的评估结果的不相容性问题,提高水质等级模型的分辨率,提出了一种新的水质评价模型-逻辑斯谛曲线(LOG)模型,它的水质等级是连续的实数值;根据LOG模型的参数值可以分析各水质指标值对水质等级的影响程度,从而检验原订水质等级标准的合理性;并给出了基于实码遗传算法的LOG建模的实施方案.实例研究说明,这套方案是实用的和通用的,在其它环境质量综合评价中也具有广泛的应用价值.     

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

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