Flooding in urban areas can cause significant property damage and human injury. Recent extreme precipitation events in the Toronto area have highlighted the need for enhanced warning systems to inform decision making prior to a storm’s arrival. To improve the accuracy and lead time of flood forecasting, Computational Hydraulics International and the Toronto and Region Conservation Authority have developed a high resolution, deterministic, physically-based remote-sensing real-time flood forecasting and web-based decision support system, and applied it to the Don River and Etobicoke Creek watersheds. Using PCSWMM Real-Time, NEXRAD radar data, US EPA SWMM5, HTML5 and Google Maps the system forecasts near-future water surface elevations and relays the information to a single integrated web-based platform for analysis and decision making. Key features of the flood forecasting system to be presented include: real-time radar rainfall acquisition, processing and forecasting, real-time flow and rain gauging, continuous hydrologic modelling, flood vulnerable asset analysis and predictive weather modelling. Parameterization and calibration of the underlying hydrologic model, incorporation of pre-existing HEC-RAS models, testing of available radar bias correction methods and case studies will be reviewed. Future planned improvements to the system and the challenges of accurately modelling floods associated with unprecedented storm events are also discussed.
Randall, Mark; James, Rob; James, William; Finney, Karen; and Heralall, Michael, "PCSWMM Real Time Flood Forecasting – Toronto, Canada" (2014). CUNY Academic Works.