Stream Quality Monitoring Research Articles

An Assessment of In-stream Sampling Activity of Macroinvertebrates and Stream Channelization in Dug Run, Allen County, Ohio, USA

Macroinvertebrates are good indicators of stream quality. Changes in populations of sensitive macroinvertebrates help to show stressors to the stream. Student sampling of a section of Dug Run in northwestern Ohio has occurred since 2015. This work has been to identify how changes on the campus including construction, tree removal, and channelization may be impacting stream macroinvertebrates. Student sampling, however, also causes disturbances that may negatively impact macroinvertebrate populations. A break in student sampling—due first to the use of an adjacent off-site location in 2019 and then to COVID-19 beginning in 2020—was expected to impact the number of mayfly nymphs and caddisfly larvae captured, both considered sensitive macroinvertebrates in the stream. To measure the impact of channelization in Dug Run, the study area was split into a channelized reach, an upstream reach, and a downstream reach. Stream habitat was also studied in each reach with macroinvertebrates collected from riffles, undercuts, and pools. After a break in sampling, caddisfly larvae increased initially but have declined in the 2 following years, while mayfly nymphs increased in the last 2 years of the study. No significant differences were found in stream quality monitoring (SQM) index scores between the channelized reach compared to upstream and downstream reaches (H = 4.15; p = 0.126). There was a significant difference in taxa richness among pools, riffles, and undercuts (H = 14.09; p < 0.001). A significant difference was also found in the moderately sensitive macroinvertebrates captured in riffles between the channelized, upstream, and downstream reaches (H = 6.82; p = 0.033). A break in sampling resulted in an initial increase in mayfly nymph and caddisfly larvae samples, but it appears a variety of factors may be responsible for the numbers captured. The channelized reach had higher numbers of scuds and crayfish in riffles among the 3 reaches, which may be the result of a change in their distribution related to lack of undercuts. Both scuds and crayfishwere found in significantly greater abundance in undercuts compared to pools and riffles.

Effects of Stormwater Management and an Extended Culvert on Stream Health in Dug Run, Allen County, Ohio, USA

Changes in stream hydrology and habitat—associated with urbanization—have impacted diversity, abundance, and movement of both macroinvertebrates and fish. In 2008 the University of Northwestern Ohio began developing the western half of the campus, incorporating stormwater management practices. This provided an opportunity to examine 3 sections of the Dug Run stream that flows through campus: 1 section on the western half of campus that filters stormwater through the soil, and 2 sections on the eastern half of campus which are affected by both urbanization and a culvert that extends under a building and a road. Significant differences in macroinvertebrate Stream Quality Monitoring (SQM) index scores ( p < 0.001), fish diversity ( p < 0.010), and abundance of Orangethroat Darters (Etheostoma spectabile) ( p < 0.001) were observed between the western and the 2 eastern sections of Dug Run. Lower SQM index scores and lower Orangethroat Darter abundances were found in the urbanized sections of the stream, while lower fish diversity numbers were found upstream of the culvert. The western portion of campus, designed to filter stormwater runoff through the soil, was the only section studied with sensitive macroinvertebrates, a higher SQM index score, and a greater abundance of Orangethroat Darters.

Seasonality of total fatty acid profiles in acid mine drainage impaired streams

Pre-regulation coal mining and subsequent acid mine drainage (AMD) have drastically altered stream quality in the Appalachian region of the USA. Streams impaired by AMD often times demonstrate lowered pH, increases in specific conductance, and increase in dissolved metal concentrations. These changes in the chemical environment are reflected in the biotic community with drastic reductions in diversity and biomass. Recently, there has been an increase in applying traditional measures of food quality to understand how the biofilm community is altered by environmental condition and use for stream quality monitoring. The purpose of this study was two-fold: (1) to use fatty acid profiles to distinguish between biofilm communities in AMD impaired and unimpaired streams and (2) to determine the consistency of biofilm fatty acid profiles throughout the summer sampling period. Impaired streams showed significantly lower pH and increased specific conductance. Biofilm samples from the AMD impaired streams had lower fatty acid content with a decreased proportion of polyunsaturated fatty acids. Fatty acid profiles easily and rapidly separated biofilm communities into their respective categories, either as being impaired by AMD or unimpaired by AMD, using multivariate statistical approaches. Fatty acid profiles were similar within stream type throughout the summer sampling season, and the profiles were correlated to pH and specific conductance. The results of this study suggest that fatty acid profiles can rapidly and accurately categorize the biofilm community responses to environmental impairment.

MULTIVARIATE NONPARAMETRIC TESTS FOR TREND IN WATER QUALITY1

ABSTRACT: National and state fixed station stream quality monitoring networks have now been in existence for over ten years. The resulting data bases provide opportunities and challenges for statistical trend assessment. Although nonparametric tests have been developed that are well suited to such problems, the interpretation of variations in trend significance between seasons and variables remains a problem. One recently developed test is based on the sum of Mann‐Kendall statistics over seasons or variables, with the test statistic variance computed as the sum of the covariances of the individual Mann‐Kendall statistics. In this method, up‐ and downtrends can cancel, giving an overall indication of no trend. A related test which is sensitive to trend regardless of direction has been shown to behave poorly for typical stream quality record lengths. An alternative formulation which is sensitive to up‐ and downtrends and has power approaching that of the covariance sum method, is described. In addition, a variation of a contrast test for discriminating trend directions and magnitudes among variables or seasons where correlation between seasons or variables is present is described, and tests of its performance reported.

By James W. Male and Richard R. Noss1“Consolidation of a Stream Quality Monitoring Network”2

by James W. Male and Richard R. Noss¹“Consolidation of a Stream Quality Monitoring Network”²

“Design Considerations for Ambient Stream Quality Monitoring,” by Dennis P. Lettenmaier2

“Design Considerations for Ambient Stream Quality Monitoring,” by Dennis P. Lettenmaier²

DISCUSSION by David L. Egar, A. L. Wilson, and R. K. Aylesworth1“Design Considerations for Ambient Stream Quality Monitoring”2

DISCUSSION by David L. Egar, A. L. Wilson, and R. K. Aylesworth¹“Design Considerations for Ambient Stream Quality Monitoring”²

DESIGN CONSIDERATIONS FOR AMBIENT STREAM QUALITY MONITORING1

ABSTRACT: Existing ambient water quality monitoring programs have resulted in data which are often unsuitable for assessment of water quality trends. A primary concern in designing a stream quality monitoring network is the selection of a temporal sampling strategy. It is extremely important that data for trend assessment be collected uniformly in time. Greatly superior trend detection power results for such a strategy as compared to stratified sampling strategies. In general, it is desirable that sampling frequencies be at least monthly but not greater than biweekly; higher sampling frequencies usually result in little additional information. An upper limit on trend detectability exists such that for both five and ten year base periods it is often impossible to detect trends in time series where the ratio of the trend magnitude to time series standard deviation is less than about 0.5. For the same record lengths trends in records with trend to standard deviation ratios greater than about one can usually be detected with very high power when a uniform sampling strategy is followed.