Network design for water quality monitoring of surface freshwaters: a review

To date, many water quality monitoring networks for surface freshwaters have been rather haphazardly designed without a consistent or logical design strategy. Moreover, design practices in recent years indicate a need for cost-effective and logistically adaptable network design approaches. There are many variables that need to be included in a comprehensive yet practical monitoring network: a holistic appraisal of the monitoring objectives, representative sampling locations, suitable sampling frequencies, water quality variable selection, and budgetary and logistical constraints are examples. In order to investigate the factors which affect the development of an effective water quality monitoring network design methodology, a review of past and current approaches is presented.     

SCREENING THE RELOCATION STRATEGIES OF WATER QUALITY MONITORING STATIONS BY COMPROMISE PROGRAMMING1

Water quality monitoring network designs historically have tended to use experience, intuition, and subjective judgment in siting monitoring stations only sporadically. Better design procedures for optimizing monitoring systems with respect to multiple criteria decision analysis had rarely been put into practice up front when the needs for intensive monitoring became critical. This paper describes a systematic relocation strategy that is organized to identify several significant planning objectives and consider a series of inherent constraints simultaneously. The planning objectives considered in this analysis are designed to enhance the detection possibility for lower compliance areas, reflect the emphasis for different attainable water uses at different locations, promote the potential detection for the lower degradation areas of pollutants, increase the protection degree of those areas with higher population density in the proximity of the river system, and strengthen the pre‐warning capability of water quality for water intakes. The constraint set contains the limitations of budget, the equity implication, and the detection sensitivity in the water environment. A case study in the Kao‐Ping River Basin, South Taiwan, demonstrates the application potential of this methodology based on a seamless integration between the optimization and the simulation models. It enables identification of the optimal locational pattern stepwise using the embedded screening and sequencing capacity in a compromise programming model. However, a well calibrated and verified water quality model is an indispensable tool in support of this multiobjective evaluation. Extra sampling procedures become necessary for the sites with sparse environmental information. Comparison of planning outcomes of compromise programming is made against previously achieved analyses by using weighted programming and fuzzy programming.     

QUANTITATIVE METHODS FOR PRELIMINARY DESIGN OF WATER QUALITY SURVEILLANCE SYSTEMS1

ABSTRACT: To assure attainment and maintenance of desired water quality levels in our rivers and streams, systematic monitoring must be performed. A preliminary phase of the design of water quality surveillance systems is the specification of sampling frequencies and station locations throughout the basin; that is, the development of an adequate space/time sampling plan. The purpose of this paper is to present some quantitative methods which have been developed to identify candidate sets of sampling frequencies and station locations, and to establish priorities for implementing the different frequencies and locations. These methods are useful in the cost/effectiveness trade-off analyses in surveillance system design, and are based on the surveillance system objective of pollution abatement in which it is desired to detect violations in state-federal water quality standards. A spatial priority measure is developed which is dependent both on the water quality profile in the stream and on the information obtained from monitoring stations located in other reaches. Also, a temporal sampling priority rating is presented which is a measure of the effectiveness of the surveillance system with respect to its ability to detect the violations in the standards. To illustrate the quantitative methods, the procedures are applied to the Wabash River Basin.     

Optimal estuarine sediment monitoring network design with simulated annealing

An objective function based on geostatistical variance reduction, constrained to the reproduction of the probability distribution functions of selected physical and chemical sediment variables, is applied to the selection of the best set of compliance monitoring stations in the Sado river estuary in Portugal. These stations were to be selected from a large set of sampling stations from a prior field campaign. Simulated annealing was chosen to solve the optimisation function model. Both the combinatorial problem structure and the resulting candidate sediment monitoring networks are discussed, and the optimal dimension and spatial distribution are proposed. An optimal network of sixty stations was obtained from an original 153-station sampling campaign.     

UTILIZATION OF REMOTE SENSING IN RIVER BASIN STUDIES1

ABSTRACT: Remote sensing techniques have the potential for significantly reducing the level of effort in a river basin water quality study. An immediate requirement exists, however, for the formulation of the proper methodology for the application of remote sensing to this problem area. A general methodology is proposed for conduct of river basin water quality studies. The primary advantage offered by the proposed methodology is a technique for rapid evaluation of the water quality conditions of a river basin. Remote sensing techniques are a fundamental part of the methodology. The proposed methodology consists of two phases. Phase I deals with the study of the water resource characteristics of the basin as a system and identification of “critical areas.” Phase II of the methodology involves the detailed study of the critical areas by means of computerized water quality simulation models.     

GROUND WATER MONITORING NETWORK DESIGN USING MULTIPLE CRITERIA DECISION MAKING ANT) GEOSTATISTICS1

ABSTRACT: A multi-criteria approach to ground water quality monitoring network design is developed. The methodology combines multi-criteria decision making (MCDM) and modifications of geostatistical variance reduction analysis. Composite programming, a distance based optimization algorithm that employs a hierarchial structure, is used for the MCDM component of the design methodology. MCDM allows the consideration of numerous, often conflicting, design criteria. The methodology is useful for identifying the preferred combination of direct borehole and indirect geo-electric data. It also permits the use of prior information during initial stages of network development. Multi-variate kriging is employed to evaluate network performance using the combination of direct borehole data and indirect geoelectric data. Weighted measures of estimation variance are used as primary measures of performance, with the reduction in estimation variance being computed by the fictitious point method. Case study results demonstrate that the network design methodology can be used in both early and late phases of network development. It also leads to selection of the preferred combination and spatial orientation of direct and indirect data sources while considering cost-effectiveness and performance of alternative designs.     

WATER QUALITY PREDICTION WITHIN AN INTERBASIN TRANSFER SYSTEM1

ABSTRACT A methodology for predicting the spatial and temporal levels of conservative water quality constituents within a multibasin water resource system is presented. Dissolved solids, sulfates, and chlorides are the constituents used during this investigation; however, any other conservative ion or mineral can be incorporated into the simulation model. The methodology is tested on the proposed Texas Water System. The water quality model, QNET-I, utilizes monthly canal and river flows and reservoir storage levels calculated by the Texas Water Development Board's systems simulation model. Discharge-concentration relationships are developed for each source of water in the system, including significant waste-water discharges. Reservoirs in the system are assumed to be completely mixed with respect to conservative constituents. A mass balance analysis is performed for each node and each month during the simulation period. The output from the water quality simulation is a table of the concentrations of the conservative water quality constituents at each demand point in the system and in each reservoir and canal for every month the system is in operation. The desired quality of the water at the demand locations is used to determine the economic utility of transporting and mixing water from various sources.     

SAMPLING FREQUENCY SELECTION FOR REGULATORY WATER QUALITY MONITORING1

ABSTRACT: The selection of sampling frequencies in order to achieve reasonably small and uniform confidence interval widths about annual sample means or sample geometric means of water quality constituents is suggested as a rational approach to regulatory monitoring network design. Methods are presented for predicting confidence interval widths at specified sampling frequencies while considering both seasonal variation and serial correlation of the quality time series. Deterministic annual cycles are isolated and serial dependence structures of the autoregressive, moving average type are identified through time series analysis of historic water quality records. The methods are applied to records for five quality constituents from a nine-station network in Illinois. Confidence interval widths about annual geometric means are computed over a range of sampling frequencies appropriate in regulatory monitoring. Results are compared with those obtained when a less rigorous approach, ignoring seasonal variation and serial correlation, is used. For a monthly sampling frequency the error created by ignoring both seasonal variation and serial correlation is approximately 8 percent. Finally, a simpler technique for evaluating serial correlation effects based on the assumption of AR(1) type dependence is examined. It is suggested that values of the parameter p₁, in the AR(1) model should range from 0.75 to 0.90 for the constituents and region studied.     

Application of best subset method for river water quality modeling: A study on Godavari River,India

The utilization of water quality analysis to inform optimal decision-making is imperative to achieve sustainable management of river water quality. A multitude of research works in the past has focused on river water quality modeling. Despite being a precise statistical regression technique that allows for fitting separate models for all potential combinations of predictors and selecting the optimal subset model, the application of best subset method in river water quality modeling is not widely adopted. The current research aims to validate the use of best subset method in evaluating the water quality parameters of the Godavari River, one of the largest rivers in India, by developing regression equations for different combinations of its physicochemical parameters. The study involves in formulating best subset regression equations to estimate the concentrations of river water quality parameters while also identifying and quantifying their variations. A total of 17 water quality parameters are analyzed at 13 monitoring sites using 13 years (1993–2005) of observed data for the monsoon (June–October) period and post-monsoon (November–February) period. The final subset model is selected among model combinations that are developed for each year's dataset through widely used statistical criteria such as R², F value, adjusted R²_a, AIC_c, and RSS. The final best subset model across all parameters exhibits R² values surpassing 0.8, indicating that the models possess the ability to account for over 80% of the variations in the concentrations of dependent parameters. Therefore, the findings demonstrated the appropriateness of this method in evaluating the water quality parameters in extensive rivers. This work is very useful for decision-making and in the management of river water quality for its sustainable use in the study area.     

STOCHASTIC WATER QUALITY ANALYSIS USING RELIABILITY METHOD1

ABSTRACT: This study developed a QUAL2E‐Reliability Analysis (QUAL2E‐RA) model for the stochastic water quality analysis of the downstream reach of the main Han River in Korea. The proposed model is based on the QUAL2E model and incorporates the Advanced First‐Order Second‐Moment (AFOSM) and Mean‐Value First‐Order Second‐Moment (MFOSM) methods. After the hydraulic characteristics from standard step method are identified, the optimal reaction coefficients are then estimated using the Broyden‐Fletcher‐Goldfarb‐Shanno (BFGS) method. Considering variations in river discharges, pollutant loads from tributaries, and reaction coefficients, the violation probabilities of existing water quality standards at several locations in the river were computed from the AFOSM and MFOSM methods, and the results were compared with those from the Monte Carlo method. The statistics of the three uncertainty analysis methods show that the outputs from the AFOSM and MFOSM methods are similar to those from the Monte Carlo method. From a practical model selection perspective, the MFOSM method is more attractive in terms of its computational simplicity and execution time.     

OBSERVATION WELL NETWORK DESIGN FOR PUMPING TESTS IN UNCONFINED AQUIFERS1

ABSTRACT: This paper presents a method for determining locations of observation wells to be used in conducting pumping tests in unconfined aquifers. Sensitivity coefficients, the distribution of relative errors, and the correlation coefficients between four aquifer parameters (horizontal and vertical hydraulic conductivities K_r and K_z, storage coefficient S, and specific yield S_y) are used as the criteria for the design of observation well networks and the interpretation of pumping tests. The contours of the relative errors over a vertical profile are very useful in selecting the “best” location of an observation well. Results from theoretical analyses suggest that a wide range of locations is suitable for the determination of K_r and that good locations for the determination of K_z and S may be poorly suited for the determination of S_y. Consideration must be given to the position and lengths of the pumping well screen in the selection of observation well locations. For a given location, the quality of test data can be improved by using high pumping rates and frequent sampling of drawdowns. We found that a minimum of two and preferably three observation locations are needed along a given transect. Results of the four parameters from a single well analysis may contain higher uncertainties. However, composite analyses of multiple observation wells can reduce the correlation between the four aquifer parameters, particularly between K_r and S_y, thus, improving the quality of parameter estimation. Results from two pumping tests conducted at sites located in Nebraska were examined with regard to the proposed methodology.     

Application of Two Quality Indices as Monitoring and Management Tools of Rivers. Case Study: The Imera Meridionale River, Italy

On the basis of the European Water Framework Directive (2000/60), the water resources of the member states of the European Community should reach good quality standards by 2015. Although such regulations illustrate the basic points for a comprehensive and effective policy of water monitoring and management, no practical tools are provided to face and solve the issues concerning freshwater ecosystems such as rivers. The Italian government has developed a set of regulations as adoption of the European Directive but failed to indicate feasible procedures for river monitoring and management. On a local scale, Sicilian authorities have implemented monitoring networks of watersheds, aiming at describing the general conditions of rivers. However, such monitoring programs have provided a relatively fragmentary picture of the ecological conditions of the rivers. In this study, the integrated use of environmental quality indices is proposed as a methodology able to provide a practical approach to river monitoring and management. As a case study, the Imera Meridionale River, Sicily’s largest river, was chosen. The water quality index developed by the U.S. National Sanitation Foundation and the floristic quality index based on the Wilhelm method were applied. The former enabled us to describe the water quality according to a spatial–temporal gradient, whereas the latter focused on the ecological quality of riparian vegetation. This study proposes a holistic view of river ecosystems by considering biotic and abiotic factors in agreement with the current European regulations. How the combined use of such indices can guide sustainable management efforts is also discussed.     

WATER QUALITY SAMPLING SCHEMES FOR VARIABLE FLOW CANALS AT REMOTE SITES1

ABSTRACT: Growing interest in water quality has resulted in the development of monitoring networks and intensive sampling for various constituents. Common purposes are regulatory, source and sink understanding, and trend observations. Water quality monitoring involves monitoring system design; sampling site instrumentation; and sampling, analysis, quality control, and assurance. Sampling is a process to gather information with the least cost and least error. Various water quality sampling schemes have been applied for different sampling objectives and time frames. In this study, a flow proportional composite sampling scheme is applied to variable flow remote canals where the flow rate is not known a priori. In this scheme, historical weekly flow data are analyzed to develop high flow and low flow sampling trigger volumes for auto‐samplers. The median flow is used to estimate low flow sampling trigger volume and the five percent exceedence probability flow is used for high flow sampling trigger volume. A computer simulation of high resolution sampling is used to demonstrate the comparative bias in load estimation and operational cost among four sampling schemes. Weekly flow proportional composite auto‐sampling resulted in the least bias in load estimation with competitive operational cost compared to daily grab, weekly grab sampling and time proportional auto‐sampling.     

DESIGN CONSIDERATIONS FOR AMBIENT STREAM QUALITY MONITORING1

ABSTRACT: Existing ambient water quality monitoring programs have resulted in data which are often unsuitable for assessment of water quality trends. A primary concern in designing a stream quality monitoring network is the selection of a temporal sampling strategy. It is extremely important that data for trend assessment be collected uniformly in time. Greatly superior trend detection power results for such a strategy as compared to stratified sampling strategies. In general, it is desirable that sampling frequencies be at least monthly but not greater than biweekly; higher sampling frequencies usually result in little additional information. An upper limit on trend detectability exists such that for both five and ten year base periods it is often impossible to detect trends in time series where the ratio of the trend magnitude to time series standard deviation is less than about 0.5. For the same record lengths trends in records with trend to standard deviation ratios greater than about one can usually be detected with very high power when a uniform sampling strategy is followed.     

NEW ZEALAND'S NATIONAL WATER QUALITY MONITORING NETWORK - DESIGN AND FIRST YEAR'S OPERATION1

ABSTRACT: The design and implementation of a national surface water quality monitoring network for New Zealand are described. Some of the lessons learned from the first year of operation are also addressed. Underpinning the design, and specified in advance, are the goal and objectives, the data quality assurance system, and the mechanism for data interpretation and reporting. Because of the difficulties associated with the use of a multitude of different agencies, only one agency is involved in field work and one laboratory undertakes the analysis. Staff training has been given a high priority. The network has been designed to give good trend detectability for regular sampling over a 5–10 year period.     

A statistical study of the quality of surface water intended for human consumption near Valencia (Spain)

Water quality in the European Union is subject to legislation through directives that are applicable in all Member States. The directives specify a set of physical and chemical parameters that should be regularly controlled using a network of sampling points, with sampling based on the intended use of the water. This paper presents the results of a statistical comparison of the quality of water intended for human consumption at two different locations (the Canal de Benagéber and the Canal Júcar-Turia) near the town of Valencia (Spain). These are currently the only canals that could supply Valencia and other nearby towns with drinking water. The parameters considered in this paper are the ones specified in the European directives for determining the quality of water intended for human consumption. These directives specify that the 95th percentile of the distribution of each parameter should be used to assess water quality, so accurate estimation of these percentiles was essential in this paper. We found statistically significant differences among locations in chlorides, sulfates, temperature, coloration, and manganese, but the results varied depending on the statistical tests that we used; parametric methods gave better results than nonparametric methods.     

CONSOLIDATION OF A STREAM QUALITY MONITORING NETWORK1

ABSTRACT A method for systematic consolidation of a fixed station water quality monitoring network using dynamic programming is described. The approach utilizes a hierarchical structure; stations are allocated to what are termed primary basins on the basis of a weighted attribute score, and specific station locations within each primary basin are specified using a criterion based on stream order numbers. The method has been applied to the Municipality of Metropolitan Seattle (Metro) stream and river quality monitoring network. The results aided in a 1982 metro decision to reduce the scope of its fixed station monitoring from 81 to 47 stations, at an annual savings of approximately $33,000 per year exclusive of equipment depreciation and indirect costs.     

Multivariate statistical characterization of water quality in Lake Lanier, Georgia, USA

Watershed monitoring programs depend on water quality characterization data collected for many parameters, at many times and places, and with limited resources. Our objective is to present a strategy that reduces the measured parameters, locations, and frequency without compromising the quality of the monitoring program. One year of twice-monthly (growing season) and monthly (dormant season) water quality data collected from 17 lake and 10 tributary sites are used in conjunction with multivariate statistical techniques to improve the utility of collected data by identifying key parameters and monitoring locations. Factor analysis shows that tributary water quality data consists of three components-stormwater runoff, municipal and industrial discharges, and ground water-which can be distinguished using total suspended solids, total dissolved solids, and alkalinity plus soluble reactive P, respectively. Lake water quality characterization is more ambiguous than tributary water quality characterization, but factor analysis indicates that anoxia associated with lake stratification is the largest source of lake water quality variation, followed by nutrient abundance, and finally by biomass abundance. Cluster analysis suggests that tributary and lake monitoring stations can be consolidated. Reducing the number of parameters and stations frees up resources for increased monitoring elsewhere.     

Decision making under uncertainty using PEES–fuzzy AHP–fuzzy TOPSIS methodology for landfill location selection

The location selection for landfill municipal solid waste is an important issue in waste management. Selection of the optimal location requires consideration of multiple alternative solutions and evaluation factors because of system complexity. Further, ranking of the alternative locations and selection of the most optimal and efficient locations for landfill waste are an important multi-criteria decision-making problem. In this study, the candidate locations for landfill are determined based on Political, Economical, Environmental and Social factors are assessed through decision-makers’ opinion and by the methodology that incorporates fuzzy analytic hierarchy process (fuzzy AHP) and fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS). Specifically, the fuzzy AHP technique is applied to determine the weights of selected criteria impacting the location selection process, and the fuzzy AHP is adapted to model the linguistic vagueness and ambiguity, which can also be expressed as triangular fuzzy numbers. Furthermore, fuzzy TOPSIS technique is employed to rank the alternative locations. The applicability of this methodology is demonstrated by a case study of landfill waste location selection in the region of Casablanca, Morocco, and the results are compared with other techniques. Finally, to complete the treatment, a sensitivity analysis is performed to examine the impact of the preferences given by decision-makers to choose the best location.     

WATER QUALITY MONITORING NETWORK DESIGN: A PROBLEM OF MULTI-OBJECTIVE DECISION MAKING1

ABSTRACT: Hydrologic data network design is a fairly complicated problem where questions as to the number of gages required, time frequencies to be selected, and benefits/costs of monitoring still remain unresolved. These issues are intensified in case of water quality variables as they are more error-prone, costly, and time consuming to sample. The basic difficulty underlying the design and evaluation of monitoring systems is the lack of an objective criterion to assess: (a) the efficiency, and (b) cost-effectiveness of a network. A statistical procedure based on the entropy principle of information theory is proposed to address the evaluation of both factors. Efficiency is measured quantitatively in terms of the information produced by a network. Similarly, benefits of monitoring are described by informative measures for an objective evaluation of cost-effectiveness. The study presented demonstrates the applicability of the entropy method in assessing the efficiency and the benefits of an existing water quality monitoring network. The method is applied for temporal and spatial features of monitoring, handled as both separate and combined problems. The results are shown in the case of the highly polluted Porsuk River in Turkey. The strengths and shortcomings of the proposed methodology are discussed, with recommendations for future research on the application of the entropy principle in network design.