Modelling the stormwater benefits of green roofs in the City of Toronto

Green roofs have been built in Toronto primarily by private building owners. For a variety of reasons, green roofs have not been recognized to be a cost-effective measure in improving our living environment. It is partly attributed to the misunderstanding of the construction and maintenance costs and the lack of data to quantify both private and public benefits. This paper describes the modeling of stormwater benefits in the city of Toronto. The storm water impacts of green roofs were modeled using a continuous simulation model called HSPF. Unit-Response Functions (URFs), which represent the annual runoff volume from a unit area, were derived for different land uses. The URFs were subsequently calibrated under current and projected green roof scenarios. GIS was then used to aggregate the storm water diversion for various watersheds across the city. Three types of storm water benefits were examined: stormwater BMP saving, pollutant reduction, reduction of receiving stream erosion. Three types of BMPs (e.g. pervious pavements in residential high-rise buildings and commercial areas, and underground storage in commercial area) can be substituted by green roofs. The difference in unit cost (including construction and maintenance costs) between green roofs and these BMPs becomes cost savings of green roofs. Pollutant reduction benefit and erosion reduction benefit were estimated using the benefit functions determined by the City of Waterloo’s study. Based on a 4,984 ha of potential green roofs in Toronto, the total stormwater benefit was estimated to be ranging from $42 to $118 million. Combined sewer overflow (CSO) benefits were determined by estimating the reduction of storage required for the control of CSO in Toronto. The City of Toronto has developed a continuous simulation model (i.e. QQS model) to simulate the CSO condition. For planning level analysis of greenroof’s effect on CSO, a simplified approach was used in this study. It is based on analytical probabilistic models, SUDS, which transform the probability density functions (pdf) of rainfall event characteristics (e.g. volume, duration , and interevent time) into pdf of overflow characteristics. SUDS was calibrated with QQS’s simulation results and used to estimate the reduction of underground storage after green roof implementation. The CSO benefits of green roofs were determined by the reduction of underground storage for the same level of CSO control and a unit cost of $1,340/m3 for underground storage (City of Toronto 2003). Based on the SUDS model simulations, the existing and future CSO volumetric controls could be 17.4% and 59.7% respectively. With 5% and 15% implementation of potential green roofs, the existing CSO volumetric control could be improved to 17.8% and 18.8%. To achieve the future 59.7% volumetric control, the reduction of underground storage due to 5% and 15% implementation of potential green roofs were estimated to be 11,712 m3 and 34,752 m3. The total infrastructure saving for 5% and 15% of potential green roofs were estimated to be $15.7 million and $46.6 million respectively.