Date of Award

2021

Document Type

Undergraduate Thesis

Degree Name

BS

Department

Civil, Coastal, and Environmental Engineering

Faculty Mentor

Kevin White

Abstract

Three Mile Creek has been identified as an impaired urban stream and is now a priority for cleanup for both the City of Mobile and the Alabama Department of Environmental Management. Methods to better manage storm water runoff on the USA campus have begun, with a goal to reduce sediment and nutrient inputs to Three Mile Creek. Both sediment and nutrient inputs to Three Mile Creek disrupt habitat and lower dissolved oxygen concentrations, which are detrimental to overall stream health. Low Impact Development strategies are an innovative way to use nature-like, green-infrastructures to minimize storm water runoff quantity and improve runoff quality. A specific type of Best Management Practice (BMP), called bio-infiltration basins, have been installed on the University of South Alabama’s campus between Meisler Hall and the Admin Building to capture, store, and infiltrate storm water runoff before it reaches the stream inlet; therefore, decreasing the amount of sediment and nutrients entering the stream. This project looked to sample storm water runoff both upstream and downstream of the installed bio-infiltration basins to determine sediment concentrations, determine sediment and load reductions, and evaluate two BMP-load-reduction models to determine the most accurate predictor of load reductions, using actual sample data for comparison. Methods involved collecting sample bottles distributed on the Meisler Commons watershed, measuring total suspended solids (TSS), and calculating the reduction rate from uphill to downhill. The Region 5 and Spreadsheet Tool for Estimating Pollutant Load Models predicted a 75% reduction in the Meisler Commons BMP area. Our field results showed that the TSS tested on April 19, 2018 for the whole area was reduced by 82. 14%. Over the summer of 2018, each basin averaged a 65% reduction. In conclusion, these basins are filtering the storm-water entering the creek at an appropriate rate in comparison with the model predictions.

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