APPLICATIONS OF A STEADY-STATE,ONE-DIMENSIONAL WATER QUALITY MODEL1

ABSTRACT: A steady-state, one-dimensional water quality model has been formulated to evaluate spatial variations of Biochemical Oxygen Demand, ammonia nitrogen, and dissolved oxygen for nontidal, branched river systems, with point sources of treated wastes and uniform nonpoint-source loads, under aerobic and/or anaerobic stream conditions. For anaerobic conditions, the decay rate of organic matter is assumed to be limited by the rate of oxygen addition to the streams via stream reaeration and net algal photosynthesis and respiration contributions. The model is applicable to stream impact analysis under sustained wet weather conditions, during which storm-runoff loads are generated by storms of sufficiently long duration to approach steady state in the river system.     

REGIONAL WATER QUALITY MANAGEMENT BY THE GENERALIZED REDUCED GRADIENT METHOD1

ABSTRACT: A river basin-wide water quality management system is considered. The river receives thermal as well as organic wastes. At-source treatment of these pollutants is imposed to control the basin-wide water quality. The related water quality standards are: the minimum DO concentration, the maximum allowable BOD concentration, the maximum allowable stream temperature, and the allowable rise in stream temperature. The general dynamic mathematical model representing water quality in streams and the thermal effects on BOD and DO concentrations is presented. The model is highly nonlinear in nature. The optimal management problem involving the model is solved by a recently developed nonlinear propgramming technique - the generalized reduced gradient (GRG) method. Comparison of results obtained by the GRG method vs. dynamic programming, and of results using a more realistic mathematical model vs. a simple model are presented. The analysis procedure can be applied to designing new and examining existing water quality programs, and to study the influence of alternate policies and constraints.     

PHYSICAL DETERMINANTS OF ECONOMIC VALUE OF RIPARIAN BUFFERS IN AN AGRICULTURAL WATERSHED1

ABSTRACT: Economic values of riparian buffers in a watershed are evaluated by the changes in the net economic return for farming with and without riparian buffers when achieving the same water quality objectives. The simulated water quality impacts of alternative farming systems using SWAT and experimental data for riparian buffers are used in a mathematical optimization model to estimate net economic return for farming subject to a water quality objective. Physical characteristics such as stream length, channel slope, average land slope, cropland percentage and several soil attributes are identified in the watershed using ARC/INFO GIS. A regression model is then used to evaluate the impacts of these physical characteristics on the estimated economic values of buffers. The study is conducted in Goodwater Creek watershed, Missouri. The results show the estimated economic value of buffers is significantly affected by some soil properties, stream length, and cropland percentage in watershed and can be used to improve the effectiveness of riparian buffers at watershed and regional levels.     

STREAM TEMPERATURE UNDER AN INADEQUATE BUFFER STRIP IN THE SOUTHEAST PIEDMONT1

ABSTRACT: A paired watershed experiment on the southeastern Piedmont to determine the effect of clearcutting loblolly pine on water quantity, quality, and timing has shown that stream water temperatures we increased as much as 20°F even though a partial buffer strip of trees and shrubs were left in place to shade the stream. Water time minimum stream temperatures were lowered as much as 10°F by the same treatment. A stream temperature model now in use did not predict such elevated temperatures. The authors suggest that forest cover reductions in areas of gentle land relief may elevate the temperature of shallow ground water moving to the stream, even with a substantial buffer strip Ln place.     

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.     

MODELING METALS TRANSPORT AND SEDIMENT/WATER INTERACTIONS IN A MINING IMPACTED MOUNTAIN STREAM1

ABSTRACT: The U.S. Environmental Protection Agency (USEPA) Water Quality Analysis Simulation Program (WASP5) was used to model the transport and sediment/water interactions of metals under low flow, steady state conditions in Tenmile Creek, a mountain stream supplying drinking water to the City of Helena, Montana, impacted by numerous abandoned hard rock mines. The model was calibrated for base flow using data collected by USEPA and validated using data from the U.S. Geological Survey (USGS) for higher flows. It was used to assess metals loadings and losses, exceedances of Montana State water quality standards, metals interactions in stream water and bed sediment, uncertainty in fate and transport processes and model parameters, and effectiveness of remedial alternatives that include leaving contaminated sediment in the stream. Results indicated that during base flow, adits and point sources contribute significant metals loadings to the stream, but that shallow ground water and bed sediment also contribute metals in some key locations. Losses from the water column occur in some areas, primarily due to adsorption and precipitation onto bed sediments. Some uncertainty exists in the metal partition coefficients associated with sediment, significance of precipitation reactions, and in the specific locations of unidentified sources and losses of metals. Standards exceedances are widespread throughout the stream, but the model showed that remediation of point sources and mine waste near water courses can help improve water quality. Model results also indicate, however, that alteration of the water supply scheme and increasing base flow will probably be required to meet all water quality standards.     

STREAM WASTE ASSIMILATIVE CAPACITY ANALYSIS USING REAERATION COEFFICIENTS MEASURED BY TRACER TECHNIQUES1

Atmospheric reaeration is a natural mechanism of oxygen transfer from the atmosphere to a water body. In practice, stream water quality models are developed with reaeration coefficients (K₂) estimated by predictive equations. This leads to uncertainties in modeling analysis because these equations are empirical in nature and may yield greatly different K₂ values for the same stream. Values of K₂ may be adjusted in model calibration, but unfortunately, values of other model parameters are no less easy to identify and require adjustment in model calibration as well. Therefore, validity of a stream model would be enhanced significantly if K₂ could be determined directly and reliably. In this research, values of K₂ in the Canandaiqua Outlet in Central New York have been measured by using a gas tracer method. A successful modeling analysis was conducted using these K₂ values. As a result, effluent limitations of several waste water discharges into the Outlet were established. It was concluded that field measurements of reaeration rate would improve modeling results significantly, and that the gas tracer method can be easily incorporated into intensive water quality surveys normally required for stream modeling.     

MODELING FRAMEWORK FOR MANAGING COPPER RUNOFF IN URBAN WATERSHEDS1

ABSTRACT: A modeling framework was developed for managing copper runoff in urban watersheds that incorporates water quality characterization, watershed land use areas, hydrologic data, a statistical simulator, a biotic ligand binding model to characterize acute toxicity, and a statistical method for setting a watershed specific copper loading. The modeling framework is driven by export coefficients derived from water quality parameters and hydrologic inputs measured in an urban watershed's storm water system. This framework was applied to a watershed containing a copper roof built in 1992. A series of simulations was run to predict the change in receiving stream water chemistry caused by roof aging and to determine the maximum copper loading (at the 99 percent confidence level) a watershed could accept without causing acute toxicity in the receiving stream. Forecasting the amount of copper flux responsible for exceeding the assimilation capacity of a watershed can be directly related to maximum copper loadings responsible for causing toxicity in the receiving streams. The framework developed in this study can be used to evaluate copper utilization in urban watersheds.     

Seeking,Thinking, Acting: Understanding Suburban Resident Perceptions and Behaviors Related to Stream Quality

Theories in risk, psychology, and communication suggest aiming to inform the public about basic ecological facts may not be enough to influence knowledge of risks or behaviors to mitigate water quality risks. The risk information‐seeking and processing model and the theory of planned behavior suggest several additional variables that are likely to influence risk‐mitigating behaviors. We used data from a survey of watershed residents in Ohio to explore a model of behavioral intentions to positively impact stream health. Residents' informational norms, or the perceived pressure to know about local stream health, strongly predicted their information‐seeking behaviors. Active‐seeking behaviors predicted positive attitudes toward behaviors impacting stream health, which predicted intentions to positively impact stream health. Implications for outreach include couching communication in terms of risk found important to the local community, here wildlife were seen as negatively influenced by water quality, as opposed to plain reports typically provided by utility companies. Increasing social pressure to feel informed by emphasizing the existing knowledge of stream ecology among residents could change the norm for the less informed. A low response rate limits the generalizability of findings here, but leveraging these findings in outreach efforts could prove more successful in engaging the public to improve stream health and support policies to improve stream health.     

Modeling the Effects of Land Use Change on the Water Temperature in Unregulated Urban Streams

Streams, in their natural state, are typically diverse and biologically productive environments. Streams subject to urbanization often experience degradation brought about by the cumulative effects of flow alteration, unsanitary discharge and channelization. One of the water quality parameters affected by urbanization is stream temperature. This study offers a model for predicting the impact of land use change on the temperature of non-regulated streams during extreme events. A stream temperature model was created by considering the gains and losses of thermal energy resulting from radiation, convection, conduction, evaporation and advection. A sensitivity analysis showed that out of 14 variables, shade/transmissivity of riparian vegetation, groundwater discharge, and stream width had the greatest influence on stream temperature. These same three variables are highly influenced by land use. Individual component models were developed to predict how urbanization changes stream width and baseflow discharge. Using 3-D computer modeling, a model was also developed to illustrate the effects of altering the extent and composition of riparian vegetation on streams with different orientations. By modeling these three variables as a function of urbanization, the results became inputs into the stream temperature model. The critical urban stream temperature model (CrUSTe), an aggregation of these four models, allows the prediction of stream temperature change as a result of amount, type and location of urbanization within a watershed. It has the potential to become a valuable tool for environmental managers.     

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.     

USE OF GEOSTATISTICS TO EVALUATE WATER QUALITY CHANGES DUE TO COAL MINING1

ABSTRACT: Large variability of water quality data often makes it difficult to judge whether or not the conditions in an aquifier or a stream are deteriorating or not the conditions in an aquifer or a stream are deteriorating or improving. A technique for separation of variograms into positive and negative difference components is proposed. This technique was applied to water quality data from a requality improved with time on the stripmined and undisturbed areas, declined in a seep and an adjoining stream and remained about the same in the deep mined zone.     

PREDICTING THE SUMMER TEMPERATURE OF SMALL STREAMS IN SOUTHWESTERN WISCONSIN1

ABSTRACT: One of the biggest challenges in managing cold water streams in the Midwest is understanding how stream temperature is controlled by the complex interactions among meteorologic processes, channel geometry, and ground water inflow. Inflow of cold ground water, shade provided by riparian vegetation, and channel width are the most important factors controlling summer stream temperatures. A simple screening model was used to quantitatively evaluate the importance of these factors and guide management decisions. The model uses an analytical solution to the heat transport equation to predict steady‐state temperature throughout a stream reach. The model matches field data from four streams in southwestern Wisconsin quite well (typically within 1°C) and helps explain the observed warming and cooling trends along each stream reach. The distribution of ground water inflow throughout a stream reach has an important influence on stream temperature, and springs are especially effective at providing thermal refuge for fish. Although simple, this model provides insight into the importance of ground water and the impact different management strategies, such as planting trees to increase shade, may have on summer stream temperature.     

EXPORT COEFFICIENT MODELING TO ASSESS PHOSPHORUS LOADING IN AN URBAN WATERSHED1

ABSTRACT: An export coefficient modeling approach was used to assess the influence of land use on phosphorus loading to a Southern Ontario stream. A model was constructed for the 1995–1996 water year and calibrated within ± 3 percent of the observed mean concentration of total phosphorus. It was found that runoff from urban areas contributed most to the loading of phosphorus to the stream. When the model was assessed by running it for the 1977–1978 water year, using water quality and land use data collected independently, agreement within ± 7 percent was obtained. The model was then used to forecast the impact of future urban development proposed for the watershed, in terms of phosphorus loading, and to evaluate the reduction in loading resulting from several urban best management practices (BMP). It was determined that phosphorus removal will have to be applied to all the urban runoff from the watershed to appreciably reduce stream phosphorus concentration. Of the BMP designs assessed, an infiltration pond system resulted in the greatest phosphorus load reduction, 50 percent from the 1995–1996 baseline.     

WATER QUALITY MODELING BY MONTE CARLO SIMULATION1

ABSTRACT: The applicability of the Monte Carlo simulation technique to water quality modeling is demonstrated with the aid of a simple Streeter-Phelps model. The model accounts for the stochasticity of the input parameters. Triangular probability density functions are shown to be useful in case insufficient information is available to define meaningful frequency distributions of input parameters. The model output is presented as probability distributions of stream quality parameters.     

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.     

Classifying the Health of Connecticut Streams Using Benthic Macroinvertebrates with Implications for Water Management

Bioassessments have formed the foundation of many water quality monitoring programs throughout the United States. Like many state water quality programs, Connecticut has developed a relational database containing information about species richness, species composition, relative abundance, and feeding relationships among macroinvertebrates present in stream and river systems. Geographic Information Systems can provide estimates of landscape condition and watershed characteristics and when combined with measurements of stream biology, provide a useful visual display of information that is useful in a management context. The objective of our study was to estimate the stream health for all wadeable stream kilometers in Connecticut using a combination of macroinvertebrate metrics and landscape variables. We developed and evaluated models using an information theoretic approach to predict stream health as measured by macroinvertebrate multimetric index (MMI) and identified the best fitting model as a three variable model, including percent impervious land cover, a wetlands metric, and catchment slope that best fit the MMI scores (adj-R ² = 0.56, SE = 11.73). We then provide examples of how modeling can augment existing programs to support water management policies under the Federal Clean Water Act such as stream assessments and anti-degradation.     

Relationships Between Landscape Characteristics and Nonpoint Source Pollution Inputs to Coastal Estuaries

The model can help in examining the relative sensitivity of water-quality variables to alterations in land use made at varying distances from the stream channel. The model also shows the importance of streamside management zones, which are key to maintenance of stream water quality. The linkage model can be considered a first step in the integration of GIS and ecological models. The model can then be used by local and regional land managers in the formulation of plans for watershed-level management.     

Linking Biological Integrity and Watershed Models to Assess the Impacts of Historical Land Use and Climate Changes on Stream Health

Land use change and other human disturbances have significant impacts on physicochemical and biological conditions of stream systems. Meanwhile, linking these disturbances with hydrology and water quality conditions is challenged due to the lack of high-resolution datasets and the selection of modeling techniques that can adequately deal with the complex and nonlinear relationships of natural systems. This study addresses the above concerns by employing a watershed model to obtain stream flow and water quality data and fill a critical gap in data collection. The data were then used to estimate fish index of biological integrity (IBI) within the Saginaw Bay basin in Michigan. Three methods were used in connecting hydrology and water quality variables to fish measures including stepwise linear regression, partial least squares regression, and fuzzy logic. The IBI predictive model developed using fuzzy logic showed the best performance with the R ² = 0.48. The variables that identified as most correlated to IBI were average annual flow, average annual organic phosphorus, average seasonal nitrite, average seasonal nitrate, and stream gradient. Next, the predictions were extended to pre-settlement (mid-1800s) land use and climate conditions. Results showed overall significantly higher IBI scores under the pre-settlement land use scenario for the entire watershed. However, at the fish sampling locations, there was no significant difference in IBI. Results also showed that including historical climate data have strong influences on stream flow and water quality measures that interactively affect stream health; therefore, should be considered in developing baseline ecological conditions.