OREGON WATER QUALITY INDEX A TOOL FOR EVALUATING WATER QUALITY MANAGEMENT EFFECTIVENESS1

ABSTRACT: The Oregon Water Quality Index (OWQI) is a single number that expresses water quality by integrating measurements of eight water quality variables (temperature, dissolved oxygen, biochemical oxygen demand, pH, ammonia+nitrate nitrogen, total phosphorus, total solids, and fecal coliform). Its purpose is to provide a simple and concise method for expressing the ambient water quality of Oregon's streams for general recreational use, including fishing and swimming. The OWQI, originally developed in the 1970s, has been updated based upon improved understanding about water quality behavior. This report describes the historical basis of the OWQI and defines the improved design of the present OWQI. The index allows users to easily interpret data and relate overall water quality variation to variations in specific categories of impairment. This report demonstrates the value of the OWQI in presenting spatial and temporal water quality information. The OWQI improves comprehension of general water quality issues, communicates water quality status, and illustrates the need for and effectiveness of protective practices.     

A STATISTICAL MODEL FOR SMALL LAKE WATER QUALITY MANAGEMENT1

ABSTRACT: Phosphorus loading tolerances of small lakes are analyzed by means of a statistical model of lake eutrophication based upon the work of Vollenweider and Dillon. Using a sample of 195 midwestern and eastern U. S. lakes, it was found that Vollenweider and Dillon's method of predicting the trophic status of relatively deep, slow-flushing lakes can be applied to shallower lakes with much shorter retention times. The statistical model used to replicate the results of Vollenweider and Dillon is stated in detail, for convenience of application to small lake water quality management problems. The model extends the Vollenweider and Dillon results by associating each alternative phosphorous loading with a probability that a given lake can achieve or maintain noneutrophis status. It is applicable to lakes for which only minimal data are available. The major policy conclusion is that the highly variable tolerance for phosphorus loading must be considered in legislating efficient effluent limitations. The paper concludes with a comparison to a recent contribution employing a similar approach.     

ANTIDEGRADATION WATER QUALITY CRITERIA FOR THE DELAWARE RIVER: A DISTRIBUTION-FREE STATISTICAL APPROACH1

ABSTRACT: Existing water quality for the Middle Delaware Scenic and Recreational River is significantly better than is required by current standards, leaving a potential for degradation. A method is presented for deriving candidate antidegradation water quality criteria for this segment of the Delaware River using statistical analysis of historic (ambient) water quality data. Data for 34 water quality parameters are first evaluated for data density, serial correlation, trend, seasonality, and other factors. These preliminary analyses are based on observation of data plots and application of distribution-free statistical techniques that are insensitive to outliers and are robust to relatively mild violations of basic assumptions. Data for 12 of the parameters have sufficient density for further analysis and can reasonably be modeled as independent and identically distributed over time (either seasonally or for the entire data sets). For these 12 parameters, distribution-free statistical methods are developed and used to derive intervals within which there is high confidence (usually greater than 95 percent) that the quantiles with potential use as anti-degradation criteria (the 0.85^th, 0.90^th, and 0.95^th quantiles in this study) for a particular parameter lie.     

ANTIDEGRADATION WATER QUALITY CRITERIA FOR THE DELAWARE RIVER: A DISTRIBUTION-FREE STATISTICAL APPROACH1

ABSTRACT: Existing water quality for the Middle Delaware Scenic and Recreational River is significantly better than is required by current standards, leaving a potential for degradation. A method is presented for deriving candidate antidegradation water quality criteria for this segment of the Delaware River using statistical analysis of historic (ambient) water quality data. Data for 34 water quality parameters are first evaluated for data density, serial correlation, trend, seasonality, and other factors. These preliminary analyses are based on observation of data plots and application of distribution-free statistical techniques that are insensitive to outliers and are robust to relatively mild violations of basic assumptions. Data for 12 of the parameters have sufficient density for further analysis and can reasonably be modeled as independent and identically distributed over time (either seasonally or for the entire data sets). For these 12 parameters, distribution-free statistical methods are developed and used to derive intervals within which there is high confidence (usually greater than 95 percent) that the quantiles with potential use as anti-degradation criteria (the 0.85^th, 0.90^th, and 0.95^th quantiles in this study) for a particular parameter lie.     

ESTABLISHING STATISTICAL DESIGN CRITERIA FOR WATER QUALITY MONITORING SYSTEMS: REVIEW AND SYNTHESIS1

ABSTRACT: Regulatory water quality management has placed fairly extensive information expectations on routine, fixed-station monitoring without a corresponding emphasis being placed on the need to design monitoring systems to meet these expectations. To correct the situation there is increasing interest in developing more quantitative monitoring system design procedures which incorporate the statistical nature of sampling. In examining the development of such quantitative criteria, this paper describes the roles of statistics in a systematic approach to monitoring - initial design and routine reporting of results - and reviews the use of statistics in each. The paper emphasizes the need to tie the two together, via statistical design criteria, in order for the identified information expectations to be met in a statistically sound manner. However, the use of statistics in water quality monitoring is noted as currently being as much an art as it is a science.     

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.     

MULTIVARIATE NONPARAMETRIC TESTS FOR TREND IN WATER QUALITY1

ABSTRACT: National and state fixed station stream quality monitoring networks have now been in existence for over ten years. The resulting data bases provide opportunities and challenges for statistical trend assessment. Although nonparametric tests have been developed that are well suited to such problems, the interpretation of variations in trend significance between seasons and variables remains a problem. One recently developed test is based on the sum of Mann-Kendall statistics over seasons or variables, with the test statistic variance computed as the sum of the covariances of the individual Mann-Kendall statistics. In this method, up- and downtrends can cancel, giving an overall indication of no trend. A related test which is sensitive to trend regardless of direction has been shown to behave poorly for typical stream quality record lengths. An alternative formulation which is sensitive to up- and downtrends and has power approaching that of the covariance sum method, is described. In addition, a variation of a contrast test for discriminating trend directions and magnitudes among variables or seasons where correlation between seasons or variables is present is described, and tests of its performance reported.     

REGULATORY WATER QUALITY MONITORING: A SYSTEMS PERSPECTIVE1

ABSTRACT: Regulatory water quality monitoring has evolved to the point where it is a rather complex system encompassing many monitoring purposes and involving many monitoring activities. Lack of a system's perspective of regulatory monitoring hinders the development of effective and efficient monitoring programs to support water quality management. In this paper the regulatory water quality monitoring system is examined in a total systems context. The purposes of regulatory monitoring are reviewed and categorized according to their legal evolution. The activities of regulatory monitoring are categorized and organized into a system which follows the flow of information through the monitoring program. The monitoring purposes and activities are combined to form a monitoring system matrix - a framework within which the total regulatory water quality monitoring system is defined. The matrix, by defining the regulatory monitoring system and clarifying many interactions within the system, provides a basis upon which a more thorough approach to managing, evaluating, and eventually optimizing regulatory monitoring can be developed.     

ELEMENTS OF A WATER QUALITY INFORMATION SYSTEM FOR THE STATE OF ILLINOIS1

ABSTRACT: A great deal of information can be derived from study of standard stream monitoring data, if these are properly ordered and organized. This information may then be used to make decisions about water quality management. Among critical information items are evaluation of performance to standards, determination of seasonality and time-trends of water quality conditions, and estimation of the effects on water quality to be expected from load reductions or standards modifications. Additional information on the magnitude of individual pollution sources is also critical to water quality management. Each of these items can be derived within the water quality information system which is currently under development for the State of Illinois.     

EVALUATING THE OPTIONS FOR WATER QUALITY MANAGEMENT1

ABSTRACT: The agricultural revolution occurred because the un-managed environment was not providing food in either the quantity or quality that society desired. The “environmental revolution” is developing because the unmanaged environment is clearly not capable of assimilating societal wastes without being seriously degraded. Effective environmental management will require regional and site-specific modification of general principles and practices that can be used at a national or international level. An environmental management system can be operated in the same manner as any industrial quality control system with three basic components: (a) sensors at appropriate locations, (b) rapid generation and feedback of information, and (c) a quality control group capable of taking immediate effective action when system performance is outside predetermined boundary conditions. This discussion focuses primarily on three areas: (a) management options available to regulate intrusion of societal wastes into natural systems, (b) types of methods available for predicting and validating effects on natural systems, and (c) modifications of present legislation that would permit the most flexibility in selecting from the various management options. Also considered are multispecies toxicity tests using species with cosmopolitan distribution in test systems with a high degree of environmental realism. Among the many values of such tests is the ability to exchange information from all parts of the world effectively because the test organisms are not restricted to a particular geographic region.     

ACCOMMODATING CHANGE OF BACTERIAL INDICATORS IN LONG TERM WATER QUALITY DATASETS1

ABSTRACT: In 1996, the State of Oregon adopted a water quality standard based on Escherichia coli (E. coli), recognizing E. coli as an indicator of pathogenic potential. The Oregon Department of Environmental Quality (DEQ) began analysis for E. coli that same year. The Oregon DEQ continued collection and analysis of fecal coliform (a prior indicator organism) for data input to bacterial loading models and the Oregon Water Quality Index (OWQI). The OWQI is a primary indicator of general water quality for the Oregon DEQ and the Oregon Progress Board. The objective of this study was to develop a regression relationship between fecal coliform and E. coli. This relationship would fill data gaps and extend water quality models and indicators. Water quality policy is better informed by the ability of these extended water quality models to determine whether water quality meets present or would have met past bacterial standards. Monitoring resources spent on dual bacterial analyses could be conserved. This study also showed that changes to OWQI values (as a result of changing bacterial indicators) were minimal, and corresponded to improved characterization of water quality with respect to pathogenic potential.     

A MODELING APPROACH FOR STORM WATER QUANTITY AND QUALITY CONTROL VIA DETENTION BASINS1

ABSTRACT: Storm water detention basins have historically been employed for quantity (i.e., flooding) control only. However, recently it has been suggested that these basins may also provide a practical means of storm water quality control. This paper presents the formulation of a mathematical modeling approach which may be used by professionals to simultaneously design detention basins for the dual purpose of storm water quantity and quality control. Model simulations demonstrate that for a given basin, pollutant removal increases as storm frequency increases. The importance of particle size distribution and settling velocity for net pollutant removal is illustrated, The design procedure is demonstrated, and pollutant loading diagrams for estimating pollutant removal as a function of storm size are developed.     

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.     

A DECISION SUPPORT SYSTEM FOR WATER QUALITY DATA AUGMENTATION: A CASE STUDY1

ABSTRACT: Recent developments in water quality monitoring have generated interest in combining non-probability and probability data to improve water quality assessment. The Interagency Task Force on Water Quality Monitoring has taken the lead in exploring data combination possibilities. In this paper we take a developed statistical algorithm for combining the two data types and present an efficient process for implementing the desired data augmentation. In a case study simulated Environmental Protection Agency (EPA) Environmental Monitoring and Assessment Program (EMAP) probability data are combined with auxiliary monitoring station data. Auxiliary stations were identified on the STORET water quality database. The sampling frame is constructed using ARC/INFO and EPA's Reach File-3 (RF3) hydrography data. The procedures for locating auxiliary stations, constructing an EMAP-SWS sampling frame, simulating pollutant exposure, and combining EMAP and auxiliary stations were developed as a decision support system (DSS). In the case study with EMAP, the DSS was used to quantify the expected increases in estimate precision. The benefit of using auxiliary stations in EMAP estimates was measured as the decrease in standard error of the estimate.     

AN ANTIDEGRADATION POLICY FOR PRESERVING SURFACE WATER QUALITY IN FLORIDA1

ABSTRACT: As part of its overall system for protecting aquatic systems from unnecessary degradation, the State of Florida provides special protection for water bodies of unusual importance. Such water bodies are designated as “Outstanding Florida Waters” (OFW5). New discharges to OFWs are possible only if certain stringent criteria are met. A new point source direct discharge to an OFW is usually not allowed if it would cause any lowering of ambient water quality. A new indirect discharge (upstream from an OFW boundary) may be allowed only if it would not significantly degrade the OFW. To date, the advantages of the OFW system have clearly outweighed the disadvantages, and OFW designations are helping to protect Florida's most valuable waters from additional degradation. Florida's system could be a useful model for other jurisdictions wanting to provide special protection to special water bodies.     

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.     

COMPARATIVE EVALUATION OF STATISTICAL METHODS FOR WATER SUPPLY FORECASTING1

ABSTRACT: While the correlation coefficient and standard error of estimate are frequently used when comparing models of seasonal water yield, the following criteria may be more important in selecting one model from among several alternatives: rationality of the regression coefficients, the distribution of the residual errors, and the correctness of indicators of the relative importance of the predictor variables. These criteria were used to compare seasonal water yield models that were calibrated using multiple regression, stepwise regression, principal components regression, polynomial regression using a principal components rotation, and constrained pattern search. Hydrologic data from the Upper Sevier River basin in southern Utah were used to illustrate the comparative analysis process. The prediction equations used the April-July streamflow volume as the criterion variable.     

STATISTICAL ANALYSIS OF WATER CONSUMPTION1

The purpose of this study was to determine the degree of influence of various factors on municipal water consumption in Illinois. For the collection of basic data, questionnaires were sent to all public water works of incorporated towns. The questionnaire was designed to obtain information on factors which may have any effect on water use. The effects of the different parameters on water consumption were based on several correlation and regression combinations of predictands and predictors. It was found that in the Chicago region the percent of services and water used for commercial and industrial purposes and the age of the water works were the most important parameters influencing water consumption (gallons per capita per day) when pumpage is metered at the water works as well as at the customers. For the State, excluding the Chicago region, percent of public water use, persons per service, population and commercial and industrial water use were the most important parameters. It has been recommended that similar statistical analysis be conducted periodically to establish a trend or law of change from the influencing parameters.     

VIRGINIA USA WATER QUALITY, 1978 TO 1995: REGIONAL INTERPRETATION1

ABSTRACT: Nine surface water‐quality variables were analyzed for trend at 180 Virginia locations over the 1978 to 1995 period. Median values and seasonal Kendall's tau, a trend indicator statistic, were generated for dissolved oxygen saturation (DO), biochemical oxygen demand (BOD), pH (PH), total residue (TR), nonfilterable residue (NFR), nitrate‐nitrite nitrogen (NN), total Kjeldahl nitrogen (TKN), total phosphorus (TP), and fecal coliform (FC) at each location. Each location was assigned to one of four physiographic regions, and mean state and regional medians and taus were calculated. Widespread BOD and NFR improvements were detected and FC improvements occurred in the state's western regions. TR and TKN exhibited predominantly increasing trends at locations throughout the state. BOD, TKN, NFR, and TR medians were higher at coastal locations than in other regions. NN, TKN, and TR exhibited predominantly increasing trends in regions with high median concentrations, while declining trends predominated in regions with relatively high BOD, FC, and NFR medians. Appalachian locations exhibited the greatest regional water‐quality improvements for BOD, FC, NFR, and TKN. Factors responsible for regional differences appear to include geology, land use, and landscape features; these factors vary regionally.