The “data-rich but information-poor” syndrome in water quality monitoring

Water quality monitoring conducted routinely over time at fixed sites has been a part of most water quality management efforts for many years. It has been assumed that such monitoring plays a major role in management. However, the lack of routine data analysis, and reporting of information derived from such analysis, points up the fact that the exact nature of the role of routine, fixed-station monitoring is poorly defined.There is a need to very clearly define this role in the design of such systems if routine monitoring is to efficiently and effectively meet the information expectations placed on it. Design of routine monitoring systems will therefore have to consider not only the where, what, and when of sampling, but also why. A framework for including the why of monitoring in the design process is proposed and experience with using the framework in New Zealand is discussed.     

The Information Cycle as a Framework for Defining Information Goals for Water-Quality Monitoring

/ The necessity to tailor information becomes increasingly urgent as the information revolution continues to generate ever-increasing flows of data and so-called information. From European experiences, a new approach for monitoring system design is suggested in this paper. In this approach, careful and detailed specification of information needs is a major contributing factor to the effectiveness of information products. To develop better specifications for information products, the process of collecting and transforming data into useful information requires careful thought and guidance. A dialogue between information users on one hand and information producers on the other is essential. This dialogue can be based on the information cycle, describing the continuous process from specifying information needs for water management and a strategy to collect information through data collection and data analysis up to utilization of information by water management. By following the respective steps in the information cycle, the process of information gathering can be completed. The cyclic character provides a quantitative means of connecting monitoring system design and operations with the information expectations and/or products required by management.     

WATER QUALITY MONITORING: WHERE'S THE BEEF?1

ABSTRACT: Water quality monitoring, as a function of society's efforts to manage the environment, is the contact mechanism that management and the public has with the actual water quality in the environment. Water quality monitoring has been studied extensively for many years to ensure that it produces information about water quality conditions. Current efforts to reduce government spending will have negative impacts on those government functions deemed to be non-responsive to the needs of the public. How well does water quality monitoring inform taxpayers about the status and trends in water quality conditions in the United States? This paper reviews a number of past efforts to “improve” water quality monitoring, discusses barriers to such improvement, and suggests ways that monitoring can be made more accountable for the information it should be producing for public understanding of water quality conditions. In particular, the need for standardization in data analysis and reporting of information to the public, is highlighted.     

GOALS AND DATA COLLECTION DESIGNS FOR WATER QUALITY MONITORING1

ABSTRACT: Water quality monitoring cannot address every information need through one data collection procedure. This paper discusses the goals and related procedures for designing water quality monitoring programs. The discussion focuses on the broad information needs of those agencies operating water quality networks. These information needs include the ability to assess trends and environmental impacts, determine compliance with objectives or standards, estimate mass transport, and perform general surveillance. Each of these information needs has different data requirements. This paper outlines these goals and discusses factors to consider in developing a monitoring plan on a site by site basis.     

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.     

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.     

Use of ecological regions in aquatic assessments of ecological condition

Ecological regions are areas of similar climate, landform, soil, potential natural vegetation, hydrology, or other ecologically relevant variables. The makeup of aquatic biological assemblages (e.g., fish, macroinvertebrates, algae, riparian birds, etc.) varies dramatically over the landscape, as do the environmental stresses that affect the condition of those assemblages. Ecoregions delineate areas where similar assemblages are likely to occur and, therefore, where similar expectations can be established. For this reason, ecological regions have proven to be an important tool for use in the process of ecological assessment. This article describes four examples of the use of ecological regions in important aspects of environmental monitoring and assessment: (1) design of monitoring networks; (2) estimating expected conditions (criteria development); (3) reporting of results; (4) setting priorities for future monitoring and restoration. By delineating geographic areas with similar characteristics, ecological regions provide a framework for developing relevant indicators, setting expectations through the use of regional reference sites, establishing ecoregion-specific criteria and/or standards, presenting results, focusing models based on relationships between landscape and surface water metrics, and setting regional priorities for management and restoration. The Environmental Protection Agency and many state environmental departments currently use ecoregions to aid the development of environmental criteria, to illustrate current environmental condition, and to guide efforts to maintain and restore physical, chemical and biological integrity in lakes, streams, and rivers.     

Lake management techniques in Florida,USA: Costs and water quality effects

Economic evaluations of restored or enhanced lakes in Florida indicated gravity drawdown was the least expensive action, whereas effluent diversion was 10,000 times more costly on a per hectare basis, with the other lake treatment costs occurring in the following order: gravity drawdown < grass carp introduction < mechanical drawdown < aeration < stormwater control = drawdown-dredging < effluent diversion. Within a particular treatment category, the costs spanned approximately one and one half orders of magnitude. Contrary to the abundant cost data, which permitted an economic analysis, inappropriate statistical design and lack of commitment toward sampling Florida's restored lakes undermines attempts to understand long-term water quality responses to various enhancement techniques. Using Lake Tohopekaliga as a case study, ordinary statistical tests produced contradictory and unreliable interpretations on the effectiveness of drawdown and phosphorus removal at sewage treatment plants in improving the trophic state index. This emphasizes the need for more robust statistical approaches and more detailed data collection in evaluating lake restoration activities It is unfortunate for Florida's lake restoration program that quantitative conclusions based on inferential statistics, replete with tests of assumptions, is limited to very few lakes     

Water quality monitoring—Some practical sampling frequency considerations

Water quality monitoring involves sampling a population, water quality, that is changing over time. Sample statistics (e.g., sample mean) computed from data collected by a monitoring network can be affected by three general factors: (1) random changes due to storms, rainfall, etc.; (2) seasonal changes in temperature, rainfall, etc.; and (3) serial correlation or duplication in information from sample to sample. (Closely spaced samples will tend to give similar information).In general, these effects have been noted, but their specific effects on water quality monitoring network design have not been well defined quantitatively. The purpose of this paper is to examine these effects with a specific data set and draw conclusions relative to sampling frequency determinations in network design.The design criterion adopted for this study of effects due to the above factors is the width of confidence intervals about annual sample geometric means of water quality variables. The data base for the study consisted of a daily record of 5 water quality variables at 9 monitoring stations in Illinois for a period of 1 year.Three general regions of frequencies were identified: (1) greater than approximately 30 samples per year where serial correlation plays a dominant role; (2) between approximately 10 and 30 samples per year where the effects of seasonal variation and serial correlation tended to cancel each other out; and (3) less than approximately 10 samples per year where seasonal variation plays a dominant role. In region 2, either seasonal variation and serial correlation should both be considered or both ignored. To consider only seasonal variation introduces more error than ignoring it. These results are network averages (over variables and stations) from one network, thus results for individual variables may deviate considerably from the average and from those for other networks.Financial support for this study was provided, in part, by the U.S. Environmental Protection Agency, grant number R805759-01-0.     

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.     

ESTIMATING IRRIGATION WATER USE THROUGH SELECTIVE MONITORING: A NORTH FLORIDA CASE STUDY1

ABSTRACT: Selective placement - under a rigorous statistical sampling design - of newly available monitoring equipment on irrigation systems may provide effective and economical estimates of total irrigation water use in areas where complete water use inventories are impractical. In 1979, a joint effort by the U.S. Geological Survey and Florida's Suwannee River Water Management District was launched to estimate the District's 1979 irrigation water use using a selective monitoring approach. Analysis of previous inventories of irrigation equipment and amounts of water applied in the District indicated that total 1979 water use estimates with six to nine percent sampling error could be obtained using selective monitoring, given the time and equipment limitations for the monitoring program. Restricting monitoring to a sample of farms can introduce systematic error to water use estimates if farmers' participation is related to their water use methods. Preliminary results of the 1979 study indicate tht declining participation rates, if unchecked, could lead to serious systematic eror in future North Florida selective monitoring studies.     

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.     

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.     

WATER CONSERVATION METHODS IN URBAN LANDSCAPE IRRIGATION: AN EXPLORATORY OVERVIEW1

ABSTRACT: The increasing use of irrigation for urban landscapes is causing new demands for efficient watering systems. Conservation techniques for irrigated agricultural fields cannot be applied to urban landscapes without amendment. This paper attempts to review methods of urban landscape water conservation in the context of the diversity and complexity of urban landscapes and the demands upon them for quality of the urban environment. A development's initial site layout and planting design fundamentally determine how much irrigation water will be required; the complexity and creativity inherent in urban design open a number of specific possibilities for reducing water demand. Irrigation hardware is then designed to deliver the required volume of water to the specified landscape efficiently by implementing a number of physical and operational principles. Maintenance of the finished development involves monitoring results and making adjustments as the plantings grow and develop. The potential for conserving urban irrigation water is large. Effective conservation need not compromise other qualities of the urban environment such as aesthetics, screening, or shade. Urban design can address both the kinds of landscapes people need, and minimal consumption of irrigation water.     

Regulating water quantity and quality in irrigated agriculture

This paper largely applies the theoretical model formulated in an earlier paper by the authors, of an input based approach to control an agricultural non-point-source pollution. The empirical problem includes a groundwater aquifer being polluted by several agricultural producers. In order to prevent degradation of the quality and depletion of the quantity of the water in the aquifer, a regulatory agency must intervene. The regulatory agency does not have all the information needed for decision making. The producers» use of water from a surface supply is recorded and additional water is pumped from the ground aquifer, the amount of which is unknown to the agency. The agency also does not know the physical characteristics of the production process that is factored into the pollution process. The model evaluates two monitoring regimes (central and individual) and two regulatory tools (taxes and quotas) associated with each regime. Individual monitoring was found to be superior to central monitoring, both in terms of the physical characteristics of the problem (water quality and quantity) and in terms of regional income. For both the central and the individual monitoring regimes, the optimal paths of the state variables reach steady-state values relatively early, with values in the individual monitoring reaching the steady-state earlier than in the case of central monitoring. The optimal path of investment in monitoring equipment suggested investment in monitoring equipment as early as possible.1998 Academic Press     

湖泊蓝藻水华数字化预警系统构建探讨

构造湖泊蓝藻水华数字化预警系统是我国湖泊水环境管理的一个重要方向。本文探讨了构建湖泊蓝藻水华数字化预警系统的若干技术问题，包括：（1）数字化预警数学模式。提出需重视流域尺度的氮磷营养物和沉积动态输入以及营养物、沉积物对水生态结构动力过程的影响，建立非点源模型和湖泊生态结构动力学模型相耦合的预警数学模型模式；在此基础上提出了各种数学模型的可借鉴模式。（2）湖泊蓝藻水华预警监测技术。总结了常规水质监测的数据筛选方法，探讨了遥感技术和实时传输监测技术在水质监测中的应用模式，提出了实时监测和遥感监测需解决的技术难题和实现方法。（3）湖泊蓝藻数字化预警系统的设计。提出了数学模型系统、水质监控系统的网络化集成设计模式，提出了基于网络化地理信息系统的计算机应用软件实现模式。     

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.     

Water Quality and Land Use Changes in the Alafia and Hillsborough River Watersheds,Florida, USA1

Abstract: Spatial distribution of land use can have a substantial effect on surface and groundwater quality. Our objective was to test for trends in flow components and water quality related to changes in land use in the Alafia and Hillsborough River watersheds in Florida, USA, over the period 1974‐2007. In addition, water quality statistics were evaluated in the perspective of numeric water quality criteria and proposed reclassification of segments of the Alafia River. Trends in 10 water quality parameters and three discharge variables were evaluated using a nonparametric trend detection test. Results of land use analysis indicated substantial urbanization and loss of agricultural land in the study area. Discharge variables did not exhibit significant trends, whereas trends in the majority of water quality concentrations were negative or nonsignificant with total nitrogen and total Kjeldahl nitrogen as exceptions showing positive trends. Changes in nutrient pathways could not be clearly identified. Considering recently promulgated numeric nutrient criteria and standards for dissolved fluoride, much of the Alafia River was found to be out of compliance. While there were land use changes and changes in water quality over the study period, it was difficult to identify a direct cause‐effect relationship. Responses to regulatory efforts, such as the Clean Water Act and improvements in phosphate mining practices, may have had greater impacts on water quality than changes in land use.     

TECHNIQUES FOR DETECTING TRENDS IN LAKE WATER QUALITY1

ABSTRACT: With the advent of standards and criteria for water quality variables, there has been an increasing concern about the changes of these variables over time. Thus, sound statistical methods for determining the presence or absence of trends are needed. A Trend Detection Method is presented that provides: 1) Hypothesis Formulation - statement of the problem to be tested, 2) Data Preparation - selection of water quality variable and data, 3) Data Analysis - exploratory data analysis techniques, and 4) Statistical Tests - tests for detecting trends. The method is utilized in a stepwise fashion and is presented in a nonstatistical manner to allow use by those not well versed in statistical theory. While the emphasis herein is on lakes, the method may be adopted easily to other water bodies.     

Why most conservation monitoring is, but need not be, a waste of time

Ecological conservation monitoring programmes abound at various organisational and spatial levels from species to ecosystem. Many of them suffer, however, from the lack of details of goal and hypothesis formulation, survey design, data quality and statistical power at the start. As a result, most programmes are likely to fail to reach the necessary standard of being capable of rejecting a false null hypothesis with reasonable power. Results from inadequate monitoring are misleading for their information quality and are dangerous because they create the illusion that something useful has been done. We propose that conservation agencies and those funding monitoring work should require the demonstration of adequate power at the outset of any new monitoring scheme.