Date of Award

12-2011

Degree Type

Thesis

Degree Name

Master of Science

Major

Environmental Engineering

Major Professor

John S. Schwartz

Committee Members

Glenn A. Tootle, Qiang He

Abstract

Excessive suspended sediment is a major cause of pollution in US streams, as reported by the USEPA. Also known as siltation, having excessive sediment in a stream harms the biology of a stream through directly affecting living organisms, but also through harming natural habitats. Too much excessive sediment leads to a stream being declared impaired. Testing for suspended sediment levels is difficult and time consuming, so indirect methods of testing for total suspended solids (TSS) are desirable. While turbidity has been an oft used TSS surrogate in the past, this study takes the next step of looking at potential relationships between biological metrics and turbidity, to see if turbidity can be used to directly test for biological impairment, since turbidimeters can be installed in situ in streams. For this study we installed turbidimeters and depth samplers in 10 streams in East Tennessee that recorded data over a nine month period. The streams selected had pre-existing biological data available from the Tennessee Department of Environmental Conservation (TDEC). This allowed information from the turbidity probes to be compared to the biological integrity of the stream. This study first successfully correlates turbidity and TSS for our study sites through stream samples analyzed in the lab. We then statistically compared the turbidity data to the habitat scores and index scores (specifically the Tennessee Macroinvertebrate Index) of the streams. The main turbidity metric used was turbidity threshold exceedance, but unfortunately we were unable to include a duration factor. Changes in turbidity compared to changes in flow were also examined. The results showed reinforced the relationship between TSS and turbidity, while showing that while there is a correlation between turbidity threshold exceedance and index/habitat scores, it would be inappropriate to use them for stream impairment predictions at this time. More investigation with both a wider range and number of streams in a single dataset, along with the ability to include turbidity duration may yield more valuable results.

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