Date of Award


Document Type


Degree Name

Master of Science (MS)

Legacy Department

Biosystems Engineering

Committee Chair/Advisor

Dr. Tom Owino, Co-Advisor

Committee Member

Dr. Daniel R. Hitchcock, Co-Advisor

Committee Member

Dr. David L. White

Committee Member

Dr. Christophe Darnault


This study seeks to quantify runoff volume generation and peak flow rates from the urban Sand River Headwaters to determine the most effective placement of additional green infrastructure in Aiken, SC. ArcMap 10.1, HEC-GeoHMS, and HEC-HMS were used to delineate a total outlet watershed along with subwatershed(s) for urban stormwater infrastructure system by 'burning' the stormwater system at an artificial elevation below the existing topologically-based Digital Elevation Model (DEM). The result was a higher resolution DEM that allowed for storm routing and subsequent volume and flow predictions compared to that based on the original DEM created by using Light Detecting and Ranging (LiDAR) surface elevation data. Ten key monitoring locations were identified for flow accumulation determination within the total watershed area, not only at the outlet for the entire watershed but also at inclusive subwatersheds that were selected based on City Engineer recommendations and field evaluations of the complex piped urban stormwater network. Stage data collected from SonTekTMIQ-Pipe® acoustic Doppler sensors at each monitoring location were used to calculate flow rates and volumes based on flow through the pipe and Manning's n derived from the material of the conduit. Calculated volumes and flow rates at each subwatershed were used for calibration and validation of both ArcMap 10.1 and HEC-HMS based prediction models. HEC-HMS outputs underestimated runoff generation and peak flow rates over all storm events while ArcMap output volumes demonstrated underestimation for smaller storm events but overestimation for larger storms. Runoff volume generation and peak flow rate were then used, along with percent impervious surface and average curve number (CN) based on subwatershed data, to determine the location recommendations for additional green infrastructure within the urban Aiken watershed (which also serves as the Sand River Headwaters) to allow for the greatest influence on stormwater quantity reduction and water quality improvement. Results demonstrated that the most effective placement for additional green infrastructure upon landscapes was within Subwatersheds 3 and 9 with the largest amount of runoff flow and least amount of percent impervious surface out of the four subwatersheds contributing to the 67 percent area of the total watershed. The most effective place to install additional green infrastructure upon hardscapes was within Subwatershed 2 with one of the largest amounts of individual runoff flow and highest amount of impervious surface of the subwatersheds with the highest individual area contribution. An additional space for landscape green infrastructure installations may also exist within Subwatersheds 6 and 7 closer to the natural areas near the watershed outlet with very low percent impervious surface, but significantly smaller area for placement.



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