UBC Theses and Dissertations
Genomics tool for monitoring engineered stormwater treatment wetlands LeNoble, Jesisca
In the context of this research, stormwater consists of precipitation that falls onto impervious surfaces and fails to infiltrate into the ground. Traditional stormwater management involves diverting stormwater into storm sewers followed by discharge to a watercourse. However, in Vancouver and elsewhere, there is a push from governments for a more integrated approach which makes use of low impact design (LIDs) features. For this reason, engineered wetlands, which are designed to optimize natural processes for water diversion and treatment, are becoming a more common and desirable treatment option for stormwater. However, there are barriers for the implementation of engineered wetlands and other LIDs because traditional water quality monitoring often does not provide a reliable enough validation that the wetlands are meeting water treatment objectives, thus leading to a lack of accountability for designers and operators. In this research, a genomics‐based approach was applied at an operating stormwater treatment wetland (the Lost Lagoon wetland located in Stanley Park, Vancouver British Columbia, Canada), with the goal to provide proof of concept data to inform the development of a genomics‐based tool for stormwater treatment wetlands and other LIDs. In addition, a laboratory based stormwater dosing study was performed to allow for cross comparison of results. Microbial communities and functional genes with known adaptations for the contaminants found in stormwater were correlated with contaminant levels to increase the reliability and certainty of findings. Results from DNA sequencing were compared using samples extracted from the Lost Lagoon wetland and several outcomes suggested that bacteria may correlate with the performance of treatment wetlands. This was generally supported further using results from samples extracted during the stormwater dosing study. Cost estimates performed for various treatment wetland monitoring scenarios suggested that in the future, a genomics‐based monitoring approach may supply more accurate treatment performance data at a lower overall cost and effort level than traditional stormwater treatment monitoring. Proof of concept, for the application of genomics‐based monitoring of stormwater treatment wetlands, was provided. It was demonstrated that genomics could supply benefits for future monitoring endeavors and that additional investigation into this field may be worthwhile.
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