Low-impact Development Measures Implemented as Part of Stormwater Management at the Conestoga College South Campus

Brian Verspagen, Ann Sychterz and Tim Schill


Mitigating the quantity, quality, flow, and temperature of storm water has presented a need for innovative, environmentally sensitive engineering solutions. Through a system of bioswales, infiltration galleries, detention ponds, oil

and grit separators, and cooling rock cribs, the design factors can be modified in order for a new development to meet or exceed existing conditions. These design measures were implemented and monitored as part of the storm water management system at Conestoga College's new Cambridge Campus. The location of the new campus is south of the existing Doon Campus adjacent to Highway 401. The site was equipped with bioswale infiltration gallery inspection ports, seepage collection system monitoring locations, groundwater monitoring locations, temperature monitors, and water level monitors to assist in assessing the performance of the design to mitigate for development and measure the success of the design in maintaining and enhancing the local environment. The monitoring data was extracted for a 6-month period for the purposes of comparison to existing conditions and the proposed design objectives. In conjunction with rainfall and ambient temperature data, the effectiveness of the storm water system to reduce the volume of runoff/enhance groundwater recharge, mitigate peak flows, and maintain discharge temperature to a receiving coldwater fishery was assessed via statistical analysis. Runoff volume reduction and peak flow mitigation targets were readily achieved. The temperature differential across the monitoring stations demonstrated that there was an average cooling of the runoff, thus validating the stormwater management system. Temperature differential was compared to initial conditions such as ambient temperature, initial run-off temperature, or water level. Each of these relationships fit a linear regression, which indicates a good method for predicting future performance.

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