Date of Award

Summer 7-16-2021

Degree Type


Degree Name

Master of Science (MS)


Civil and Environmental Engineering


Davidson, Cliff


Environmental Engineering, Green Infrastructure, Green Roof, Water Resources Management

Subject Categories

Civil and Environmental Engineering | Engineering


Green infrastructure has the potential to alleviate stormwater runoff and reduce combined sewer overflows. Green roofs have stormwater mitigation potential in urban areas but further analysis to predict performance is needed. This research aims to understand how rainfall parameters affect green roof retention and reduction during storm events and whether a one-dimensional hydrologic model can be used to accurately predict performance. An extensive network of sensors on the OnCenter green roof in downtown Syracuse, New York, was utilized for analysis and modeling. This roof is larger than nearly all other green roofs that have been previously studied, and the layer of engineered soil is thinner (7.6 cm) than that on most other green roofs. Furthermore, there is merely a drainage mat at the base of the soil without a fleece or extra volume to hold excess rainfall. Water flowing down the 1% roof slope within the soil encounter conduits which are connected to the roof drains. The study period was June 2016 to June 2018.

Statistical differences in roof performance for three size ranges of rainfall duration and rainfall depth were identified. Using ANOVA and Tukey's Honestly Significant Difference, it is found that rainfall duration and rainfall depth impact the percent retention and peak reduction on the green roof. Large rainfall events (>2 cm) had significantly different retention and peak reduction compared to medium events (1.0 – 2.0 cm) and small events (0.2 – 1.0 cm). No statistical difference was found for the influence of antecedent dry weather period or rainfall peak intensity. A total of 37 rainfall events were simulated through HYDRUS-1D. Hydrographs plotting rainfall intensity, measured drainage intensity, and modeled drainage intensity (cm/hr) over time (hr) were generated to compare modeled outputs to measured drainage. It is found that HYDRUS-1D can successfully model the hydrology of this green roof. This was confirmed using the Nash-Sutcliffe efficiency index (NSE) and the root mean square over measured drainage standard deviation (RSR). Twelve rainfall events exceeded both NSE and RSR criteria. Limitations of this model showed greater predictability for larger sized events, where 8 of the 10 modeled events exceeded the criteria. No small rainfall events met the criteria. HYDRUS-1D consistently overpredicted drainage, with the rate of overprediction decreasing with increase in rainfall size. Because of the small slope and thin soil, the influence of the drainage conduits (which were not included in the model) is believed to be small, hence most flow is believed to be essentially vertical through the soil to the drainage mat followed by flow down the 1% slope to the roof drains.


Open Access



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