IDENTIFICATION OF CRITICAL NONPOINT POLLUTION SOURCE AREAS USING GEOGRAPHIC INFORMATION SYSTEMS AND WATER QUALITY MODELING1

n integrated approach coupling water quality computer simulation modeling with a geographic information system (GIS) was used to delineate critical areas of nonpoint source (NPS) pollution at the watershed level. Two simplified pollutant export models were integrated with the Virginia Geographic Information System (VirGIS) to estimate soil erosion, sediment yield, and phosphorus (P) loading from the Nomini Creek watershed located in Westmoreland County, Virginia. On the basis of selected criteria for soil erosion rate, sediment yield, and P loading, model outputs were used to identily watershed areas which exhibit three categories (low, medium, high) of non-point source pollution potentials. The percentage of the watershed area in each category, and the land area with critical pollution problems were also identified. For the 1505-ha Nomini Creek watershed, about 15, 16, and 21 percent of the watershed area were delineated as sources of critical soil erosion, sediment, and phosphorus pollution problems, respectively. In general, the study demonstrated the usefulness of integrating GIS with simulation modeling for nonpoint source pollution control and planning. Such techniques can facilitate making priorities and targeting nonpoint source pollution control programs.     

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.     

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.     

A MODELLING METHOD FOR EVALUATING WATER QUALITY POLICIES IN NONSERIAL RIVER SYSTEMS1

ABSTRACT: This paper describes a modelling method which simplifies the evaluation of water quality policies for nonserial (branching) river systems. The method introduces dummy facilities at the junctions of the major tributary branches with the mainstream as replacements for the facilities and activities on the tributaries. The cost functions for the dummy facilities and the DO and BOD concentrations at the junctions as determined for each tributary are introduced into the mainstream serial system model which is then solved for the optimal values of the mainstream treatment plant efficiencies, the dummy facility effeciencies, and the tributary system DO and BOD concentrations using nonlinear programming. Given the optimum values for the dummy facility efficiencies and the values for the tributary system DO and BOD concentrations, the optimum values for the tributary treatment plant efficiencies are found using nonlinear programming. The method is applied to a river system with a mainstream and one major tributary which contain industrial and municipal organic and thermal polluters and their associated wastewater treatment plants.     

DEVELOPING BIOLOGICAL INFORMATION SYSTEMS FOR WATER QUALITY MANAGEMENT1

ABSTRACT. Management of aquatic ecosystems requires a clear understanding of the goals to be achieved, appropriate information and the means to achieve the goals. Control measures applied to aquatic ecosystems, in the absence of information on the condition of the system, are apt to be inappropriate and thus may overprotect the receiving system at times and underprotect it at other times since the ability of ecosystems to receive wastes is not constant. A major determinant of the effectiveness and efficiency of ecological quality control is the lag time in the feedback of information. If the lag is too great, the control measures may repeatedly overshoot or undershoot the desired goal. Present techniques for measuring the responses of aquatic organisms and communities require days or weeks, whereas information for ecosystem quality control and prevention of ecological crises should be generated in minutes or hours as is the case for other quality control systems. Two biological monitoring systems have been developed to generate information rapidly. One system measures changes in the movement and breathing of fish in order to provide an early warning of developing toxicity in the wastes of an industrial plant. The other system measures changes in the diversity of algal comunities in streams by means of laser holography. The incorporation and use of these systems in industrial plants is discussed.     

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.     

A VERIFICATION OF THE QUAL-1 WATER QUALITY MODEL FOR THE LOWER MISSISSIPPI RIVER1

ABSTRACT: This paper describes the verification of the QUAL-1 mass transport model for the lower Mississippi River between St. Francisville and Point a la Hache using dye studies conducted by the U. S. Geological Survey. QUAL-1 is a one-dimensional steady-state model for rivers and is capable of predicting longitudinal profiles of soluble materials entering rivers from point sources. Both conservative and nonconservative parameters of water quality can be considered. The major problems surmounted were the determination of a diffusion coefficient and the use of transient data to verify a steady state model.     

COST-EFFECTIVE REGULATORY OPTIONS FOR WATER QUALITY LIMITED STREAMS1

With the pressure from industries and municipalities to reduce the waste water treatment costs associated with the permit limits needed to attain the goals of the Clean Water Act, attention has turned ways of introducing flexibility into the regulations without sacrificing the water quality goals. Wisconsin is the first state to have adopted a variety of options from which dischargers may choose when meeting their water quality requirements. These options were developed for the express purpose of minimizing the costs and maximizing the flexibility of the point source water quality regulations while ensuring that permitted discharge would not violate the water quality standards. This paper presents five options that the state has made available to dischargers, as well as one the state did not adopt. The conclusion is that a mix of options can substantially increase the flexibility and reduce the costs of meeting water quality standards on effluent limited streams.     

STATISTICAL METHODS AND SAMPLING DESIGN FOR ESTIMATING STEP TRENDS IN SURFACE-WATER QUALITY1

ABSTRACT: This paper addresses two components of the problem of estimating the magnitude of step trends in surface water quality. The first is finding a robust estimator appropriate to the data characteristics expected in water-quality time series. The Hodges-Lehmann class of estimators is found to be robust in comparison to other nonparametric and moment-based estimators. A seasonal Hodges-Lehmann estimator is developed and shown to have desirable properties. Second, the effectiveness of various sampling strategies are examined using Monte Carlo simulation coupled with application of this estimator. The simulation is based on a large set of total phosphorus data from the Potomac River. To assure that the simulated records have realistic properties, the data are modeled in a multiplicative fashion incorporating flow, hysteresis, seasonal, and noise components. The results demonstrate the importance of balancing the length of the two sampling periods and balancing the number of data values between the two periods. The inefficiency of sampling at frequencies much in excess of 12 samples per year is demonstrated. Rotational sampling designs are discussed, and efficient designs, at least for this river and constituent, are shown to involve more than one year of active sampling at frequencies of about 12 per year.     

WATER QUALITY IN THE PAWTUXET RIVER: METAL MONITORING AND GEOCHEMISTRY1

ABSTRACT: The Pawtuxet River flows from a relatively rural area through some of the more highly industrialized sections of Rhode Island. During its journey, the river receives many municipal, industrial, and ground water sources of metal constituents. The present report is the first in a two part series in which the water quality of this urban river was evaluated by a chemical monitoring study of the sources, transport mechanisms, and fate of cadmium, chromium, copper, lead, and nickel in the river. The second paper will use the chemical data to derive and calibrate a steady-state water quality model for this river. The metal concentrations In the river tended to increase from the headwaters to the mouth with river stations nearest to point source outfalls showing elevated values. In some sections of the river, levels of a few of the metals could not be explained by the point sources; and other inputs, including sediment resuspension, axe proposed to make up this apparent unbalance. The ability of a municipal secondary treatment plant to remove metals was demonstrated, and the tie-in of the effluent from a major chemical company to the plant did not cause any observable deterioration in treatment efficiency.     

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.     

INTERVENTION ANALYSIS OF WATER QUALITY RECORDS1

The impoundment of the Kootenai River by Libby Dam caused changes in discharge and water quality in the river downstream from Lake Koocanusa. The changes observed downsteam were largely attributable to the depth of withdrawal from the reservoir and the reservoir's ability to store and mix various influent water masses. The preimpoundment and postimpoundment time series of discharge and six water quality variables were autocorrelated and exhibited strong seasonality. Intervention analysis, a technique employing Box-Jenkins time series models, was used to quantify the nature and magnitude of the changes in water quality after the construction of Libby Dam. The models were developed with data from June 1967 through February 1981 and were able to satisfactorily forecast riverine conditions from March 1981 through January 1982.     

USE OF MICROCOMPUTERS FOR THE MANAGEMENT OF WATER QUALITY DATA1

ABSTRACT: Information on raw water quality, treatment process removal efficiency, and distribution system monitoring is essential to the proper management and operation of a water utility system. Microcomputer hardware and software systems using commercially available data base management systems (DBMS) have emerged within the last few years as an effective means of managing, analyzing, and displaying water quality data. Understanding hardware, software, and training requirements is essential to the proper use of these systems. Three types of data base design are common: relational, hierarchical, and network. Only the relational type of data base architecture is widely implemented on microcomputer DBMS. In this paper two examples of the application of DBMS to water utility problems are presented. One example deals with collection and analysis of data concerning the water quality of the Mississippi River. The second example deals with the DBMS as a means of analyzing water quality data in the North Penn Water Authority (NPWA) distribution system.     

CONFLICTS IN ATTAINING NATIONAL GOALS FOR BOTH WATER QUALITY AND ENERGY PRODUCTION1

ABSTRACT: The “policy environment” is defined herein as the institutional setting in which planning is conducted and policy decisions are made with regard to meeting two of the Nation's high priority goals: water quality protection and energy independence. The simultaneous pursuit of these goals has resulted in numerous conflicts among the energy industry, environmentalists, and government. An analysis of selected energy development-water quality conflicts shows that these conflicts can be described in terms of one or more of the following policy environment characteristics: resource scarcity, sense of urgency, lack of experience, administrative complexity, uncertainty about future policies and regulations, technological complexity, and uncertainty about impacts. These characterics provide a useful framework for formulating potential strategies for the resolution of energy development-water quality conflicts.     

PROBABILISTIC METHODS IN STREAM QUALITY MANAGEMENT1

ABSTRACT. Recent advances in water quality modelling have pointed out the need for stochastic models to simulate the probabilistic nature of water quality. However, often all that is needed is an estimate of the uncertainty in predicting water quality variables. First order analysis is a simple method of providing an estimate in the uncertainty in a deterministic model due to uncertain parameters. The method is applied to the simplified Streeter-Phelps equations for DO and BOD; a more complete Monte Carlo simulation is used to check the accuracy of the results. The first order analysis is found to give accurate estimates of means and variances of DO and BOD up to travel times exceeding the critical time. Uncertainty in travel time and the BOD decay constant are found to be most important for small travel times; uncertainty in the reaeration coefficient dominates near the critical time. Uncertainty in temperature was found to be a negligible source of uncertainty in DO for all travel times.     

A WATER QUALITY ASSESSMENT OF DEVELOPMENT IN THE SENEGAL RIVER BASIN1

A study was made to determine the impact on water quality due to water resource development in a large river basin in a semi-arid region of West Africa. Mathematical modeling and the examination of case histories were used to project impacts. The impacts associated with changes in water quality were shown to be slight assuming that modern basin and agricultural management practices are adopted. Analytical techniques normally implemented in studies of more highly developed basins are useful for analysis of water quality impacts in relatively undeveloped basins.     

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.     

OPTIMAL ALLOCATION OF WATER QUALITY CONTROLS IN URBANIZING RIVER BASINS1

ABSTRACT: Urbanizing river basins in the west are encountering serious water quality degradation resulting from the expanded water utilization. In order to avoid aggravating such conditions, water quality controls need to be implemented. The important questions are, therefore, where and how to impose such constraints on the urban and agricultural sectors to achieve the desired level of pollution control. An application of the model developed to address such questions is made in the Utah Lake drainage area of Central Utah as a test of the model's utility. The region is subdivided into five major sub-basins containing both municipal and agricultural water demands. A submodel of each sub-basin is developed which optimizes the water quality control strategies by linking the urban to the agricultural uses and then evaluating the levels of control for each sector. From these results, a cost-effectiveness function for each sub-basin is generated. By jointly considering the cost-effectiveness relationship for each sub-basin, an optimum policy for the entire basin is determined.     

WATER QUALITY MANAGEMENT: THE CASE FOR RIVER BASIN AUTHORITIES1

ABSTRACT: There is a lamentable absence of comprehensive planning in the current cursade to improve water quality. A serious shortcoming is the lack of evaluation of the effects of waste water treatment upon environmental quality. At some point in time the public may ask what they have obtained for their money. The nature of pollution in a river basin demands a coordinated attack against it. Engineering and economic criteria suggest that a properly empowered river basin authority would be the logical organization to plan and operate a water quality management system. Several forms of such authorities have operated effectively and efficiently for many years in the United States and other industrialized countries. Examples of successful river basin authorities and their advantages and methods of operation are discussed.     

USE OF FIRST-ORDER UNCERTAINTY ANALYSIS TO OPTIMIZE SUCCESSFUL STREAM WATER QUALITY SIMULATION1

ABSTRACT: A first-order uncertainty technique is developed to quantify the relationship between field data collection and a modeling exercise involving both calibration and subsequent verification. A simple statistic (LTOTAL) is used to quantify the total likelihood (probability) of successfully calibrating and verifying the model. Results from the first-order technique are compared with those from a traditional Monte Carlo simulation approach using a simple Streeter-Phelps dissolved oxygen model. The largest single difference is caused by the filtering or removal of unrealistic outcomes within the Monte Carlo framework. The amount of bias inherent in the first-order approach is also a function of the magnitude of input variability and sampling location. The minimum bias of the first-order technique is approximately 20 percent for a case involving relatively large uncertainties. However the bias is well behaved (consistent) so as to allow for correct decision making regarding the relative efficacy of various sampling strategies. The utility of the first-order technique is demonstrated by linking data collection costs with modeling performance. For a simple and inexpensive project, a wise and informed selection resulted in an LTOTAL value of 86 percent, while an uninformed selection could result in an LTOTAL value of only 55 percent.