Identifying Riparian Buffer Effects on Stream Nitrogen in Southeastern Coastal Plain Watersheds

Within the Southeastern (SE) Coastal Plain of the U.S., numerous freshwaters and estuaries experience eutrophication with significant nutrient contributions by agricultural non-point sources (NPS). Riparian buffers are often used to reduce agricultural NPS yet the effect of buffers in the watershed is difficult to quantify. Using corrected Akaike information criterion (AIC_c) and model averaging, we compared flow-path riparian buffer models with land use/land cover (LULC) models in 24 watersheds from the SE Coastal Plain to determine the ability of riparian buffers to reduce or mitigate stream total nitrogen concentrations (TNC). Additional models considered the relative importance of headwaters and artificial agricultural drainage in the Coastal Plain. A buffer model which included cropland and non-buffered cropland best explained stream TNC (R ² = 0.75) and was five times more likely to be the correct model than the LULC model. The model average predicted that current buffers removed 52 % of nitrogen from the edge-of-field and 45 % of potential nitrogen from the average SE Coastal Plain watershed. On average, 26 % of stream nitrogen leaked through buffered cropland. Our study suggests that stream TNC could potentially be reduced by 34 % if buffers were adequately restored on all cropland. Such estimates provide realistic expectations of nitrogen removal via buffers to watershed managers as they attempt to meet water quality goals. In addition, model comparisons of AIC_c values indicated that non-headwater buffers may contribute little to stream TNC. Model comparisons also indicated that artificial drainage should be considered when accessing buffers and stream nitrogen.     

REGRESSION MODELS FOR ESTIMATING HERBICIDE CONCENTRATIONS IN U.S. STREAMS FROM WATERSHED CHARACTERISTICS1

ABSTRACT: Regression models were developed for estimating stream concentrations of the herbicides alachlor, atrazine, cyanazine, metolachior, and trilluralin from use‐intensity data and watershed characteristics. Concentrations were determined from samples collected from 45 streams throughout the United States during 1993 to 1995 as part of the U.S. Geological Survey's National Water‐Quality Assessment (NAWQA). Separate regression models were developed for each of six percentiles (10th, 25th, 50th, 75th, 90th, 95th) of the annual distribution of stream concentrations and for the annual time‐weighted mean concentration. Estimates for the individual percentiles can be combined to provide an estimate of the annual distribution of concentrations for a given stream. Agricultural use of the herbicide in the watershed was a significant predictor in nearly all of the models. Several hydrologic and soil parameters also were useful in explaining the variability in concentrations of herbicides among the streams. Most of the regression models developed for estimation of concentration percentiles and annual mean concentrations accounted for 50 percent to 90 percent of the variability among streams. Predicted concentrations were nearly always within an order of magnitude of the measured concentrations for the model‐development streams, and predicted concentration distributions reasonably matched the actual distributions in most cases. Results from application of the models to streams not included in the model development data set are encouraging, but further validation of the regression approach described in this paper is needed.     

REVIVING URBAN STREAMS: LAND USE,HYDROLOGY, BIOLOGY,AND HUMAN BEHAVIOR1

ABSTRACT: Successful stream rehabilitation requires a shift from narrow analysis and management to integrated understanding of the links between human actions and changing river health. At study sites in the Puget Sound lowlands of western Washington State, landscape, hydrological, and biological conditions were evaluated for streams flowing through watersheds with varying levels of urban development. At all spatial scales, stream biological condition measured by the benthic index of biological integrity (B‐IBI) declined as impervious area increased. Impervious area alone, however, is a flawed surrogate of river health. Hydrologic metrics that reflect chronic altered streamflows, for example, provide a direct mechanistic link between the changes associated with urban development and declines in stream biological condition. These measures provide a more sensitive understanding of stream basin response to urban development than do treatment of each increment of impervious area equally. Land use in residential backyards adjacent to streams also heavily influences stream condition. Successful stream rehabilitation thus requires coordinated diagnosis of the causes of degradation and integrative management to treat the range of ecological stressors within each urban area, and it depends on remedies appropriate at scales from backyards to regional storm water systems.     

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.     

盘锦近岸海域无机氮污染因子削减与预测

通过盘锦海域的海水质量和水文分析,建立盘锦海域潮流场模型。在不同输入条件下,利用潮流场模型对近岸海域的无机氮污染物含量变化响应进行模拟,得出3条河流(辽河、大辽河和大凌河)无机氮削减值,在此条件下可实现近岸海域无机氮达标要求。     

Modeling Flow and Sediment Transport in a River System Using an Artificial Neural Network

A river system is a network of intertwining channels and tributaries, where interacting flow and sediment transport processes are complex and floods may frequently occur. In water resources management of a complex system of rivers, it is important that instream discharges and sediments being carried by streamflow are correctly predicted. In this study, a model for predicting flow and sediment transport in a river system is developed by incorporating flow and sediment mass conservation equations into an artificial neural network (ANN), using actual river network to design the ANN architecture, and expanding hydrological applications of the ANN modeling technique to sediment yield predictions. The ANN river system model is applied to modeling daily discharges and annual sediment discharges in the Jingjiang reach of the Yangtze River and Dongting Lake, China. By the comparison of calculated and observed data, it is demonstrated that the ANN technique is a powerful tool for real-time prediction of flow and sediment transport in a complex network of rivers. A significant advantage of applying the ANN technique to model flow and sediment phenomena is the minimum data requirements for topographical and morphometric information without significant loss of model accuracy. The methodology and results presented show that it is possible to integrate fundamental physical principles into a data-driven modeling technique and to use a natural system for ANN construction. This approach may increase model performance and interpretability while at the same time making the model more understandable to the engineering community.     

Use of artificial neural network black-box modeling for the prediction of wastewater treatment plants performance

A reliable model for any wastewater treatment plant is essential in order to provide a tool for predicting its performance and to form a basis for controlling the operation of the process. This would minimize the operation costs and assess the stability of environmental balance. This process is complex and attains a high degree of nonlinearity due to the presence of bio-organic constituents that are difficult to model using mechanistic approaches. Predicting the plant operational parameters using conventional experimental techniques is also a time consuming step and is an obstacle in the way of efficient control of such processes. In this work, an artificial neural network (ANN) black-box modeling approach was used to acquire the knowledge base of a real wastewater plant and then used as a process model. The study signifies that the ANNs are capable of capturing the plant operation characteristics with a good degree of accuracy. A computer model is developed that incorporates the trained ANN plant model. The developed program is implemented and validated using plant-scale data obtained from a local wastewater treatment plant, namely the Doha West wastewater treatment plant (WWTP). It is used as a valuable performance assessment tool for plant operators and decision makers. The ANN model provided accurate predictions of the effluent stream, in terms of biological oxygen demand (BOD), chemical oxygen demand (COD) and total suspended solids (TSS) when using COD as an input in the crude supply stream. It can be said that the ANN predictions based on three crude supply inputs together, namely BOD, COD and TSS, resulted in better ANN predictions when using only one crude supply input. Graphical user interface representation of the ANN for the Doha West WWTP data is performed and presented.     

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.     

SPARROW Modeling of Nitrogen Sources and Transport in Rivers and Streams of California and Adjacent States,U.S.

The SPARROW (SPAtially Referenced Regressions On Watershed attributes) model was used to evaluate the spatial distribution of total nitrogen (TN) sources, loads, watershed yields, and factors affecting transport and decay in the stream network of California and portions of adjacent states for the year 2002. The two major TN sources to local catchments on a mass basis were fertilizers and manure (51.7%) and wastewater discharge (15.9%). Other sources contributed < 12%. Fertilizer use is widespread in the Central Valley region of California, and also important in several other regions because of the diversity of California agriculture. Precipitation, sand content of surficial soils, wetlands, and tile drains were important for TN movement to stream reaches. Median streamflow in the study area is about 0.04 m³/s. Aquatic losses of nitrogen were found to be most important in intermittent and small to medium sized streams (0.2‐14 m³/s), while larger streams showed less loss, and therefore are important for TN transport. Nitrogen loss in reservoirs was found to be insignificant, possibly because most of the larger ones are located upstream of nitrogen sources. The model was used to show loadings, sources, and tributary inputs to several major rivers. The information provided by the SPARROW model is useful for determining both the major sources contributing nitrogen to streams and the specific tributaries that transport the load.     

An innovative modeling approach using Qual2K and HEC-RAS integration to assess the impact of tidal effect on River Water quality simulation

Water quality modeling has been shown to be a useful tool in strategic water quality management. The present study combines the Qual2K model with the HEC-RAS model to assess the water quality of a tidal river in northern Taiwan. The contaminant loadings of biochemical oxygen demand (BOD), ammonia nitrogen (NH₃-N), total phosphorus (TP), and sediment oxygen demand (SOD) are utilized in the Qual2K simulation. The HEC-RAS model is used to: (i) estimate the hydraulic constants for atmospheric re-aeration constant calculation; and (ii) calculate the water level profile variation to account for concentration changes as a result of tidal effect. The results show that HEC-RAS-assisted Qual2K simulations taking tidal effect into consideration produce water quality indices that, in general, agree with the monitoring data of the river. Comparisons of simulations with different combinations of contaminant loadings demonstrate that BOD is the most import contaminant. Streeter-Phelps simulation (in combination with HEC-RAS) is also performed for comparison, and the results show excellent agreement with the observed data. This paper is the first report of the innovative use of a combination of the HEC-RAS model and the Qual2K model (or Streeter-Phelps equation) to simulate water quality in a tidal river. The combination is shown to provide an alternative for water quality simulation of a tidal river when available dynamic-monitoring data are insufficient to assess the tidal effect of the river.     

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.     

FLOWING WATER RESOURCES1

Using data related to stream order and the morphological characteristics associated with streams of different discharge rates, an estimate of the river resources of the United States is made. The national totals are: 3,200,000 miles total length of rivers; 15,000 square miles of river surface; and 29 cubic miles of water stored in river channels. Using the same techniques, more exact estimates may be made for individual river basins. Suggestions are given for application of the techniques and river data in the management of water resources.     

A STATISTICAL METHODOLOGY FOR PREDICTING THE POLLUTANTS IN A RIVER1

Urban and industrial areas continue to expand and consequently, to create serious water pollution problems to natural streams. The need for the development of accurate, reliable, and sensitive water quality prediction models is most desirable. The first objective of this research is to set guidelines for dividing a natural stream into more or less independent reaches based on some criteria. The second objective is to obtain the predicting equations of the water pollutants in a selected stream. The preliminary phase of this research evaluated water quality data sampled from the Pearl River which flows southwest and then turns south through the states of Mississippi and Louisiana. This evaluation served as guidelines to divide the total river basin into reaches (subsystems) appropriate to the objective of this research. Subsequent to this subsystem assignment, a stepwise multiple regression FORTRAN program was used to regress the pollutants (dependent variables) for both time and space on their water characteristics (independent variables). Based on the results obtained, the proposed statistical approach provides a practical tool for developing regression equations for the purpose of water pollutants' prediction.     

An Ecologically-Sustainable Surface Water Withdrawal Framework for Cropland Irrigation: A Case Study in Alabama

Agricultural production in the state of Alabama, USA, is mostly rain-fed, because of which it is vulnerable to drought during growing season. Since Alabama receives a significant portion of its annual precipitation during winter months, the goal of this study was to evaluate the feasibility of water withdrawal from streams during winter months for irrigation in the growing season. The Soil and Water Assessment Tool (SWAT) was used to estimate the quantity of water that can be sustainably withdrawn from streams during winter high flow periods. The model was successfully calibrated and validated for surface runoff, base flow, and total stream flow. The stream flows generated by the model at several locations within the watershed were then used to examine how much water can be sustainably withdrawn from streams of various orders (first, second and third). Although there was a considerable year-to-year variability in the amount of water that can be withdrawn, a 16-year average showed that first, second, and third order streams can irrigate about 11.6, 10.3, and 10.6% of their drainage areas, respectively. The percentage of drainage area that can be irrigated was not a function of stream order.     

ECONOMIC VALUATION OF RIPARIAN BUFFER AND OPEN SPACE IN A SUBURBAN WATERSHED1

Abstract: This study evaluates the economic value of riparian buffers and open space in a suburban watershed through two nonmarket valuation methods. A contingent valuation survey was implemented in the Dardenne Creek watershed, a suburban watershed of the St. Louis metropolitan area in Missouri, to evaluate the residents' perceptions of and willingness to pay (WTP) for adopting riparian buffers and preserving farmland in a hypothetical real estate market. A hedonic pricing model based on actual sale prices of homes in the watershed was applied to estimate the market value of open space and other environmental conditions such as flood zone and stream proximity in the study area. The results showed that residents' WTP was consistent with the economic values of open space and proximity to streams embedded in existing home prices. Through a better understanding of residents' perceptions and values, riparian buffer and open space programs can be designed and promoted to achieve greater implementation success and environmental benefit.     

A Spatially Explicit Model for Mapping Headwater Streams

Headwater streams are the primary sources of water in a drainage network and serve as a critical hydrologic link between the surrounding landscape and larger, downstream surface waters. Many states, including North Carolina, regulate activity in and near headwater streams for the protection of water quality and aquatic resources. A fundamental tool for regulatory management is an accurate representation of streams on a map. Limited resources preclude field mapping every headwater stream and its origin across a large region. It is more practical to develop a model for headwater streams based on a sample of field data that can then be extrapolated to a larger area of interest. The North Carolina Division of Water Quality has developed a cost‐effective method for modeling and mapping the location, length, and flow classification (intermittent and perennial) of headwater streams. We used a multiple logistic regression approach that combined field data and terrain derivatives for watersheds located in the Triassic Basins ecoregion. Field data were collected using a standard methodology for identifying headwater streams and origins. Terrain derivatives were generated from digital elevation models interpolated from bare‐earth Light Detection and Range data. Model accuracies greater than 80% were achieved in classifying stream presence and absence, stream length and perennial stream length, but were not as consistent in predicting intermittent stream length.     

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.     

Evaluation of a denitrification wall to reduce surface water nitrogen loads

Denitrification walls have significantly reduced nitrogen concentrations in groundwater for at least 15 yr. This has spurred interest in developing methods to efficiently increase capture volume to reduce N loads in larger watersheds. The objective of this study was to maximize treatment volume by locating a wall where a large groundwatershed was funneled toward seepage slope headwaters. Nitrogen concentration and load were measured before and after wall installation in paired treatment and control streams. Beginning 2 d after installation, nitrogen concentration in the treatment stream declined from 6.7 ± 1.2 to 3.9 ± 0.78 mg L and total N loading rate declined by 65% (391 kg yr) with no corresponding decline in the control watershed. This wall, which only comprised 10 to 11% of the edge of field area that contributed to the treatment watershed, treated approximately 60% of the stream discharge, which confirmed the targeted approach. The total load reduction measured in the stream 155 m downstream from the wall (340 kg yr) was higher than that found in another study that measured load reductions in groundwater wells immediately around the wall (228 kg yr). This indicated the possibility of an extended impact on denitrification from carbon exported beyond the wall. This extended impact was inauspiciously confirmed when oxygen levels at the stream headwaters temporarily declined for 50 d. This research indicates that targeting walls adjacent to streams can effectively reduce N loading in receiving waters, although with a potentially short-term impact on water quality.     

NITROGEN AND PHOSPHORUS IN WATER AS RELATED TO ENVIRONMENTAL SEVI'ING IN NEBRASKA1

ABSTRACT: Spatial distributions of nitrogen and phosphorus in water were related to environmental setting as part of a regional water-quality assessment of the Central Nebraska Basins. The environmental settings (Sandhills, Loess Hills, Glaciated Area, and Platte Valley) were characterized by different concentrations of nitrogen and phosphorus in ground water and stream water. Statistically significant differences in nitrate concentrations in both ground-water and stream-water samples were related to regional distributions of cropland and rangeland. Nitrate concentrations were larger, especially in shallow ground water, in environmental settings dominated by cropland and associated fertilizer use than in settings dominated by rangeland. Similarly, total-nitrogen and nitrate concentrations were relatively large in selected streams draining primarily cropland. Comparative concentrations of phosphorus in stream water on the basis of environmental setting were similar to those of nitrogen, although the largest phosphorus concentrations probably relate to wastewater discharge into small streams. Nitrogen and phosphorus concentrations in much of the Platte River apparently reflected the quality of water entering the study unit from upstream and limited base-flow contributions from within the Platte Valley itself.     

Hydrological classification of natural flow regimes to support environmental flow assessments in intensively regulated Mediterranean rivers, Segura River Basin (Spain)

Hydrological classification constitutes the first step of a new holistic framework for developing regional environmental flow criteria: the “Ecological Limits of Hydrologic Alteration (ELOHA)”. The aim of this study was to develop a classification for 390 stream sections of the Segura River Basin based on 73 hydrological indices that characterize their natural flow regimes. The hydrological indices were calculated with 25 years of natural monthly flows (1980/81–2005/06) derived from a rainfall-runoff model developed by the Spanish Ministry of Environment and Public Works. These indices included, at a monthly or annual basis, measures of duration of droughts and central tendency and dispersion of flow magnitude (average, low and high flow conditions). Principal Component Analysis (PCA) indicated high redundancy among most hydrological indices, as well as two gradients: flow magnitude for mainstream rivers and temporal variability for tributary streams. A classification with eight flow-regime classes was chosen as the most easily interpretable in the Segura River Basin, which was supported by ANOSIM analyses. These classes can be simplified in 4 broader groups, with different seasonal discharge pattern: large rivers, perennial stable streams, perennial seasonal streams and intermittent and ephemeral streams. They showed a high degree of spatial cohesion, following a gradient associated with climatic aridity from NW to SE, and were well defined in terms of the fundamental variables in Mediterranean streams: magnitude and temporal variability of flows. Therefore, this classification is a fundamental tool to support water management and planning in the Segura River Basin. Future research will allow us to study the flow alteration-ecological response relationship for each river type, and set the basis to design scientifically credible environmental flows following the ELOHA framework.