Grant: Collaborative Research and Development Grants

The reclamation of the Athabasca Oil Sands (AOS) will occur at an unprecedented scale, requiring the construction of a mosaic of landscapes of lakes, wetlands and forestlands that characterize the undisturbed Boreal Plains. However, there is currently a critical trade-off in future reclamation plans. The limited water resources available within this sub-humid region must currently be used to support either healthy aquatic ecosystems or productive forests for timber harvest. To achieve the true potential of a reconstructed landscape and to meet AOS reclamation targets, hybrid landscapes that maximize the environmental and economic benefits from each component of these complex interconnected environments need to be developed. This requires an accurate understanding of the spatial and temporal variability in water storage and movement within the Boreal Plains. We will address this key knowledge gap by examining how the hydrology, ecology, geology and climate interact at a range of temporal and spatial scales. We will identify through field-based research and detailed numerical modeling how the different components of the mosaic landscape can be organized and interconnected to achieve the required reclamation goals. Research will be undertaken at the Utikuma Region Study Area, which represents the broad range of potential mature landscape designs. The research takes advantage of a 80,000 ha wildfire that burned a substantial proportion of the study region, providing a natural analogue for a range of future reclaimed AOS landscapes in the initial years post construction; when risk of ecosystem and landscape failure are most significant. A total of 15 BSc, 9 MSc and 8 PhD students, 8 postdoctoral fellows and 3 technicians will be trained during this project. The work will provide the knowledge to inform the design and construction of the next generation of reclaimed AOS landscapes that maximize landscape configuration to ensure engineering stability, the best environmental conditions and maximum economic benefit.