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Faculty of Graduate Studies

Gillian Voss

  • BSc (University of Victoria, 2022)

Notice of the Final Oral Examination for the Degree of Master of Science

Topic

Evaluating Vegetation as a Dust Storm Mitigation Tactic in the Hydroelectric Reservoir Environment through Drone Surveying and GIS Modelling

Department of Geography

Date & location

  • Thursday, September 4, 2025

  • 11:00 A.M.

  • David Turpin Building

  • Room B215

Reviewers

Supervisory Committee

  • Dr. Christopher Bone, Department of Geography, University of Victoria (Supervisor)

  • Dr. Nancy Shackelford, School of Environmental Studies, UVic (Outside Member) 

External Examiner

  • Dr. Jerome-Etienne Lesemann, Earth Science Department, Vancouver Island University 

Chair of Oral Examination

  • Dr. Jen Baggs, School of Business, UVic

     

Abstract

Dust storms are a growing problem in Canada as hydroelectric reservoirs, an increasing popular energy source, create environments that are highly vulnerable to such events due to the vast expanses of fine sediment that are exposed when reservoir levels are lowered. Mitigation tactics, most commonly the planting of vegetation, are being implemented at these sites to reduce dust erosion. However, the vastness of the reservoir beaches keeps project costs high and the fluctuating water levels limit the amount of time when seeding is possible. This thesis addresses these issues of high costs and a limited time frame by identifying ways in which that seeding can be optimized, both in rate and location, without sacrificing the quality of dust reduction. This study was conducted on Middle Creek North Beach on the eastern side of the Williston Reservoir in British Columbia and involved data collection via Unmanned Aerial Vehicle (UAV) and as well as in situ measurements. In Chapter 2, UAVs are evaluated as a tool for monitoring vegetation in the reservoir beach environment. This evaluation included a comparison of sensors (LiDAR and photogrammetric) and three flight parameters (altitude, speed, and side lap). In this environment and with the small-scale vegetation as the subject, the photogrammetric sensor significantly outperformed the LiDAR, and a lowered altitude was found to be the most impactful flight parameter on data quality. In Chapter 3, a series of regression models quantifying the relationship between dust, vegetation, and topographic variables are tested and compared. It was determined from this analysis that low seeding rate produces similar dust reduction to that of higher (and most costly seeding rates), and that the windward edge and the shoreline of the beach were especially vulnerable areas that should be prioritized for future mitigation. This thesis shows how modern technologies such as UAVS and GIS can be implemented into dust storm mitigation efforts. The methods developed in the thesis have the potential to be applied to hydroelectric settings facing similar challenges which will be crucial as this industry continues to grow.

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