The potential real-time control (RTC) has to improve the performance of existing stormwater management systems is a topic of increasing interest as hydraulic and hydrologic modeling capabilities proliferate. The benefits of incorporating precipitation forecast data into a RTC algorithm to allow for prediction-based control of an urban watershed is explored using an EPA SWMM 5.1 watershed model. One reactive and two predictive RTC algorithms are simulated in various configurations across seven dry detention ponds located in the 162 hectare urbanized watershed. The hydraulic benefits they provide at the site and watershed outlet in regards to peak flow and the flow duration curve are compared to conventional, static control. The ponds retrofit with the novel predictive RTC algorithm had lower peak flows during 24-hour design storms more consistently than when retrofit with reactive RTC. The duration of erosive flows at the site level was decreased by the novel predictive RTC in most cases. Improvements at the watershed outlet depended on where RTC was applied as hydrograph compounding was observed during some RTC implementations. / Master of Science / The consequences of watershed urbanization on nearby waterways has become a more relevant concern as urbanization increases and climate change continues to develop. Conventional stormwater management practices are employed to control peak flows from urbanized drainage areas for certain design storm criteria. Real-time control (RTC) technology has the potential to enable existing stormwater facilities to improve their performance during storm events different from their design conditions. This study compares the performance of several reactive and predictive rule-based RTC algorithms simulated as retrofits on seven dry detention ponds in a 162 hectare urbanized watershed. The results indicate that RTC algorithms that use rainfall forecast data for predictive decision making have the most potential to reduce stream erosion when applied appropriately throughout the watershed.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/98754 |
| Date | 04 June 2020 |
| Creators | Honardoust, Dylan Russell |
| Contributors | Civil and Environmental Engineering, Dymond, Randel L., Hodges, Clayton Christopher, Young, Kevin D. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
Page generated in 0.0026 seconds