FILTERING OF DISSOLVED OXYGEN DATA IN STREAM WATER QUALITY ANALYSIS1

ABSTRACT: In this study a set of equations was developed which can be used to separate the time varying effects from observed dissolved oxygen (DO) data. A steady state DO profile thus derived allows a reasonable stream stimulation such that both the model and the data used in its formulation do not contain DO due to biological activities. Biological DO production and consumption are complex phenomena. By excluding these highly variable processes, this method simplifies stream DO modeling considerably. The net oxygen input due to these processes exist only part of the day, but, in the stream waste assimilative capacity analysiis and waste load allocation, one would focus his attention on critical condition. Hence, unless the change of stream ecology is the main concern, it is desirable to formulate a stream water quality model without this time varying term.     

MONITORING STRATEGIES TO DETERMINE COMPLIANCE WITH WATER QUALITY OBJIECTIVES1

ABSTRACT: Two sampling strategies designed to test for compliance with water quality objectives are examined. For objectives based on long-term mean requirements, fixed frequency sampling at frequent intervals is most advantageous regardless of the underlying distribution of the data. For objectives that are based on maximum allowable concentrations, effective sampling strategies increase the likelihood of detecting noncompliance. If data are highly autocorrelated or sharply seasonal in distribution, an exceedance-driven sampling strategy is more effective and efficient for detecting violations than fixed frequency sampling. However, data generated by exceedance-driven sampling provide biased estimates of mean and standard deviation.     

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.     

CONSIDERATIONS OF SCALE IN WATER QUALITY MONITORING AND DATA ANALYSIS1

ABSTRACT: An assumption of scale is inherent in any environmental monitoring exercise. The temporal or spatial scale of interest defines the statistical model which would be most appropriate for a given system and thus affects both sampling design and data analysis. Two monitoring objectives which are strongly tied to scale are the estimation of average conditions and the evaluation of trends. For both of these objectives, the time or spatial scale of interest strongly influences whether a given set of observations should be regarded as independent or serially correlated and affects the importance of serial correlation in choosing statistical methods. In particular serial correlation has a much different effect on the estimation of long-term means than it does on the estimation of specific-period means. For estimating trends, a distinction between serial correlation and trend is scale dependent. An explicit consideration of scale in monitoring system design and data analysis is, therefore, most important for producing meaningful statistical information.     

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.     

DATA REQUIREMENTS OF A WATER QUALITY MANAGEMENT PROGRAM1

ABSTRACT: Routine data collection currently consumes a large amount of the total resources devoted to water quality management. All too often data collection becomes an end in itself, with little thought given to the purpose of the data collection. The problem generally stems from a lack of proper routine surveillance system design and a failure on the part of the designers to initially identify the data needs of the management program. This study attempts, in a general way, to delineate the data needs of a water quality management program. This first required an identification of the activities involved in water quality management. The activities were then discussed in terms of the types of information needed to successfully complete their assigned tasks. Several detailed examples are given. The results of the discussion are summarized and several strategies are proposed to relate the results to surveillance system design.     

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.     

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.     

DIGITAL SIMULATION OF THE EFFECT OF THERMAL DISCHARGE ON STREAM WATER QUALITY1

A modified transient version of the Streeter-Phelps model along with the energy balance equation is employed to analyze the effects of waste heat discharge from power plants on stream water quality. Analysis is also made to examine the effects of the upstream water quality and stream velocity on the downstream DO concentration level. The resulting coupled nonlinear hyperbolic partial differential equations representing the energy, BOD and DO concentrations are solved by the method of characteristics and simulated on a digital computer. Final numerical results indicate that the allowable quantity of thermal discharge does heavily depend on the upstream quality.     

EVALUATION OF METHODS FOR ESTIMATING STREAM WATER QUALITY PARAMETERS IN A TRANSIENT MODEL FROM STOCHASTIC DATA1

ABSTRACT: In this study the estimation of parameters in water quality models represented by linear first order partial differential equations is investigated. Two sets of simulated input-output data, one with input noise and the other with output measurement error, were used. The parameters were estimated by a gradient technique (Bard's method) and a pattern search technique. The results indicate that the output measurement error significantly affects the values of parameter estimates as compared to the noise added to the input. Bard's method consistently gave results with a smaller sum of square value.     

GROUND WATER QUALITY PREDICTION USING CLIMATIC INDICES1

ABSTRACT: Drought affects the quality of ground water in certain aquifers used by municipalities in Kansas. Water quality changes occur as a function of the amount of water available for recharge and hence to dilute more mineralized ground waters. Several measures of meteorological drought, including the Palmer Index and Eagleman Aridity Index, were correlated with water quality data to determine the degree of association. Several locations showed sharp delinces in water quality as the drought progressed. These relationships can be used to predict possible variations in present and future well-water supplies in locations subject to drought induced water quality deterioration.     

USING HEAT CAPACITY MAPPING MISSION (HCMM) DATA TO ASSESS LAKE WATER QUALITY1

ABSTRACT A water quality investigation on Utah Lake was conducted during the same time period that the Heat Capacity Mapping Mission (HCMM) satellite was collecting thermal infrared and reflectivity data. Relationships were established and evaluated among HCMM data and lake water quality parameters. Although remotely sensed reflective data have been previously utilized, this study was unique in that thermal emitted data were also correlated to algae concentrations and other indicators. Standard statistical evaluations were made along with utilization of color graphics techniques to identify and plot relationships. The emitted thermal energy was found to have high positive correlations with net algal concentrations and with the predominant species, Aphanizomenon flos-aquae, a blue-green alga. No continuous correlation was found for a less abundant red pigment phytoplankton, Ceratium hirundinella. Similar trends, though for negative correlations, were shown for reflectivity data and algal concentrations throughout the spring and summer. Coincidence of areas of warmer emitted energy and darker relfected energy on colorgraphics displays clearly indicate lake areas of high algal concentrations. Night thermal data displayed a strong negative correlation with algal concentration, opposite to day thermal data. Color graphics of warmer day emitted energy and cooler night emitted energy further verify areas of high algal concentrations.     

USING COMPUTED STREAM FLOW IN WATERSHED ANALYSIS1

Modifications in the computed climatic water budget have made it possible to achieve good agreement between computed and measured stream flow on both a monthly and annual basis in basins without appreciable winter snow cover. Comparisons of computed and measured stream flow in 28 basins on the Delmarva peninsula show that for some basins the agreement is excellent (regression line essentially equals unity), for other basins the regression line has a slope of one but it is displaced above or below the y=x line, while for other basins, the slope of the regression line differs appreciably from unity. Study of the basins where agreement between computed and measured values is only fair to poor reveals that the patterns of disagreement can be used to provide information on the water holding capacity in the root zone of the soil, on the quantity of deep aquifer recharge within the basin, or on the effect of human modifications within the basin. The technique should also reveal the quantity of interbasin transfers or other consumptive uses within the basin. The water budget, thus, becomes a useful tool to study hydrologic characteristics or their changes over time within a basin.     

URBANIZATION AND STREAM QUALITY IMPAIRMENT1

ABSTRACT: A study was conducted in the Piedmont province of Maryland to determine if a relationship exists between stream quality and the extent of watershed urbanization. During the first phase of the study 27 small watersheds, having similar characteristics but varied according to land use, were investigated. Using these controlled conditions, eliminating as many interferences as possible, this first phase was intended to determine if a definite relationship did exist between the two factors. Finding that the first phase was successful the second was initiated which consisted of a comparison of biological sampling data, from other studies, with degree of watershed urbanization. The purpose of this second phase was to ascertain if the relationship between degrees of urbanization and decline in stream quality was linear as watershed area increased and in streams spread throughout the Maryland Piedmont. The principal finding of this study was that stream quality impairment is first evidenced when watershed imperviousness reaches 12%, but does not become severe until imperviousness reaches 30%.     

URBANIZATION IMPACT ON WATER QUALITY DURING A FLOOD IN SMALL WATERSHEDS1

ABSTRACT: The impact of various urban land uses on water flow and quality in streams is being studied by monitoring small streams in the Milwaukee urban area. This paper compares the responses of an urban watershed and an agricultural watershed to an autumn rainfall of 2.2 cm. Flow from the urban basin showed a substantially greater response to the rain than that from the rural. Dilution, resulting from the greater quantities of surface runoff in the urban watershed, caused lower concentrations of sodium, chloride, calcium, magnesium, bicarbonate and total dissolved solids in the urban stream. The total quantity of these materials removed per unit drainage area of the urban basin was much greater, however. Road salt was still among the dominant dissolved materials in the urban water chemistry seven months after the last road salting. Sodium was apparently being released from adsorption by clays in the urban basin. Suspended sediment concentrations and total loads were higher in the urban stream.     

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.     

QUALITY ASSURANCE TECHNIQUES FOR ELECTRONIC DATA ACQUISITION1

ABSTRACT: Electronic instruments are increasingly being used to gather water quality data. Quality assurance protocols are needed which provide adequate documentation of the procedures followed in calibration, collection, and validation of electronically acquired data. The level of precision of many data loggers exceeds the technology which is commonly used to make field measurements. Overcoming this problem involves using laboratory quality equipment in the field or enhanced quality control at the time of instrument servicing. Time control procedures for data loggers are needed to allow direct comparisons of data between instruments. Electronic instruments provide a mechanism to study transient events in great detail, but, without time controls, multiple loggers produce data which contain artifacts due to timing errors. Individual sensors deployed with data loggers are subject to different degrees of drift over time. Certain measurements can be measured with defined precision and accuracy for long periods of time, while other sensors are subject to loss of both precision and accuracy with increasing time of use. Adequate quality assurance requires the levels of precision and accuracy be documented, particularly those which vary with increasing time deployment.     

SUPPLEMENTATION OF MISSING VALUES IN WATER QUALITY DATA1

ABSTRACT The problem of estimating missing values in water quality data using linear interpolation and harmonic analysis is studied to see which one of these two methods yields better estimates for the missing values. The data used in this study consisted of midnight values of dissolved oxygen from the Ohio River collected over a period of one year at Stratton station. Various hypothetical cases of missing data are considered and the two methods of supplementing missing values are evaluated using statistical tests. The results indicate that when the percentage of missed data points exceeded ten percent of the total number in the original sample, harmonic analysis usually yielded better estimates for both the regularly and irregularly missed cases. For data that exhibit cyclic variation, examples of which are dissolved oxygen concentration and water temperature, harmonic analysis as a data generation technique appears to be superior to linear interpolation.     

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.