Concentration‐Duration‐Frequency Curves for Stream Turbidity: Possibilities for Assessing Biological Impairment1

Abstract: Siltation and subsequent biological impairment is a national problem prompting state regulatory agencies to develop sediment total maximum daily loads (TMDL) for many streams. To support TMDL targets for reduced sediment yield in disturbed watersheds, a critical need exists for stream assessments to identify threshold concentrations of suspended sediment that impact aquatic biota. Because of the episodic nature of stream sediment transport, thresholds should not only be a function of sediment concentration, but also of duration and dose frequency. Water quality sondes can collect voluminous amounts of turbidity data, a surrogate for suspended sediment, at intervals that can be used to characterize concentration, duration, and frequency of elevated turbidity events. To characterize turbidity sonde data in an ecologically relevant manner, a methodology for concentration‐duration‐frequency (CDF) curves was developed using turbidity doses that relate to different levels of biological impairment. To illustrate this methodology, turbidity CDF curves were generated for two sites on Little Pigeon River in the Great Smoky Mountains National Park, Tennessee, using over 30,000 sonde data measurements per site for a one‐year period. Utilizing a Poisson arrival approach, turbidity spikes were analyzed stochastically by observing the frequency and duration of recorded events over a turbidity level that relates to a biological dose response. An exponential equation was used to fit duration and frequency of a specified turbidity level to generate concentric‐shaped CDF curves, where at specific turbidities longer durations occurred less frequently and conversely shorter durations occurred more frequently. The significance of the equation fit to the data was accomplished with a Kolmogorov‐Smirnov goodness‐of‐fit test. Our findings showed that the CDF curves derived by an exponential function performed reasonable well, with most curves significant at a 95% confidence level. These CDF curves were then used to demonstrate how they could be used to assess biological impairment, and identify future research needs for improved development of sediment TMDLs.     

Assessing Linkages in Stream Habitat,Geomorphic Condition,and Biological Integrity Using a Generalized Regression Neural Network

Watershed managers often use physical geomorphic and habitat assessments in making decisions about the biological integrity of a stream, and to reduce the cost and time for identifying stream stressors and developing mitigation strategies. Such analysis is difficult since the complex linkages between reach‐scale geomorphic and habitat conditions, and biological integrity are not fully understood. We evaluate the effectiveness of a generalized regression neural network (GRNN) to predict biological integrity using physical (i.e., geomorphic and habitat) stream‐reach assessment data. The method is first tested using geomorphic assessments to predict habitat condition for 1,292 stream reaches from the Vermont Agency of Natural Resources. The GRNN methodology outperforms linear regression (69% vs. 40% classified correctly) and improves slightly (70% correct) with additional data on channel evolution. Analysis of a subset of the reaches where physical assessments are used to predict biological integrity shows no significant linear correlation, however the GRNN predicted 48% of the fish health data and 23% of macroinvertebrate health. Although the GRNN is superior to linear regression, these results show linking physical and biological health remains challenging. Reasons for lack of agreement, including spatial and temporal scale differences, are discussed. We show the GRNN to be a data‐driven tool that can assist watershed managers with large quantities of complex, nonlinear data.     

Evaluating the Eco‐Geomorphological Condition of Restored Streams Using Visual Assessment and Macroinvertebrate Metrics

The Stream Performance Assessment (SPA), a new rapid assessment method, was applied to 93 restored, 21 impaired, 29 reference, and 13 reference streams with some incision throughout North Carolina. Principal component analysis (PCA) indicated restored streams align more closely with reference streams rather than impaired streams. Further, PCA‐based factor analysis revealed restored streams were similar to reference streams in terms of morphologic condition, but exhibited a greater range of scores relative to aquatic habitat and bedform. Macroinvertebrate sampling and GIS watershed analyses were conducted on 84 restored streams. SPA and watershed data were compared to Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa to determine which factors indicate stream health. SPA and watershed factors were used in least squares, ridge, and principal component regression (PCR) to develop a prediction model for EPT taxa. All three methods produced reasonable predictions for EPT taxa. Cross‐validation indicated ridge regression resulted in the lowest prediction error. The ridge model was then used to predict EPT taxa numbers for 21 impaired and 25 reference streams in addition to the 84 restored streams. Statistical comparisons of the predicted scores indicated urban streams (>10% impervious watershed cover) have lower expected numbers of EPT taxa. Rural restored streams have macroinvertebrate metric scores similar to those predicted for rural reference streams.     

Recovery of the Benthic Macroinvertebrate Community in a Small Stream After Long-Term Discharges of Fly Ash

Recovery of the benthic macroinvertebrate community in a small east Tennessee stream impacted by fly ash discharges from a power plant was investigated over a period of 6.5 years. The rate of recovery was greatest in the first 2 years after an initial 75% reduction in coal use led to a similar reduction in ash discharges and associated contaminants; further recovery followed after all fly ash discharges ceased. Recovery of the stream progressed through two phases. In the first phase, which lasted for approximately the first 2 years, most density and richness metrics increased considerably. In the second phase of recovery, the increases in metric values were followed by declines before fluctuating in and out of the lower reference ranges for the metrics. Detrended correspondence analyses and indicator species analyses showed that changes in species composition and community structure were ongoing throughout the second phase. Thus, the first phase was characterized by species additions, while the second phase involved species replacements and shifts in community dominants. Further recovery of the macroinvertebrate community will probably depend on additional flushing of fly ash deposits from the streambed and flood plain, because their continued presence reduces habitat quality in the stream and serves as a potential source of contaminants. Further recovery also may be limited by the availability of vagile species in nearby watersheds.     

A Biological Assessment of Streams in the Eastern United States Using a Predictive Model for Macroinvertebrate Assemblages1

Abstract: A predictive model (RIVPACS‐type) for benthic macroinvertebrates was constructed to assess the biological condition of 1,087 streams sampled throughout the eastern United States from 1993‐2003 as part of the U.S. Geological Survey’s National Water‐Quality Assessment Program. A subset of 338 sites was designated as reference quality, 28 of which were withheld from model calibration and used to independently evaluate model precision and accuracy. The ratio of observed (O) to expected (E) taxa richness was used as a continuous measure of biological condition, and sites with O/E values <0.8 were classified as biologically degraded. Spatiotemporal variability of O/E values was evaluated with repeated annual and within‐site samples at reference sites. Values of O/E were regressed on a measure of urbanization in three regions and compared among streams in different land‐use settings. The model accurately predicted the expected taxa at validation sites with high precision (SD = 0.11). Within‐site spatial variability in O/E values was much larger than annual and among‐site variation at reference sites and was likely caused by environmental differences among sampled reaches. Values of O/E were significantly correlated with basin road density in the Boston, Massachusetts (p < 0.001), Birmingham, Alabama (p = 0.002), and Green Bay, Wisconsin (p = 0.034) metropolitan areas, but the strength of the relations varied among regions. Urban streams were more depleted of taxa than streams in other land‐use settings, but larger networks of riparian forest appeared to mediate biological degradation. Taxa that occurred less frequently than predicted by the model were those known to be generally intolerant of a variety of anthropogenic stressors.     

Development and Use of a Sedimentation Risk Index for Unpaved Road‐Stream Crossings in the Choctawhatchee Watershed1

Abstract: Unpaved road‐stream crossings increase sediment yields in streams and alter channel morphology and stability. Before restoration and sedimentation reduction strategies can be implemented, a priority listing of unpaved road‐stream crossings must be created. The objectives of this study were to develop a sedimentation risk index (SRI) for unpaved road‐stream crossings and to prioritize 125 sites in the Choctawhatchee watershed (southeastern Alabama) using this model. Field surveys involved qualitative and quantitative observations of 73 metrics related to waterway conditions, crossing structures, road approaches, and roadside soil erosion. The road‐stream crossing risk analyses involved elimination of candidate metrics based on redundancy, skewness, lack of data, professional judgment, lack of nonzero values, unbalanced box plots, and limited ranges of values. A final selection of 12 metrics formed the SRI and weighed factors involving soil erodibility, road sedimentation abatement features, and stream morphology alteration. The SRI was organized into narrative categories (excellent, good, fair, poor, and very poor) based on the distribution of scores. No excellent sites (scores ≥55) were found in this study, 17 (20.7%) were good (low sedimentation risk), 37 (45.1%) were fair (moderate sedimentation risk), 26 (31.7%) were poor (high sedimentation risk), and two (2.5%) were very poor (high sedimentation risk). There was no significant difference in SRI scores among crossing structure type (round culverts, box culverts, and bridges) (H = 4.31, df = 2, p = 0.058). A future study of the Choctawhatchee watershed involving the same study sites could assess the success of restoration plans and activities based on site score improvement or decline.