CRRC Days ECR Award Winners

CRRC Days ECR Award Winners

by | Dec 17, 2021

Congratulations to the early career researcher award winners from the CRRC Days held in late November. There were two classes of awards this year, one for standard research talks, and another for our 3-minute thesis competitions, which challenge participants to sum up their work in short but effective stories. 

Standard Research Talk Award Winners

Arisha Imran (Best paper award)

MSc Student, University of Waterloo

Supervisors: Brent Wolfe (WLU), Roland Hall (UW)

Effects of large-scale flooding in 2020 on hydrological conditions of lakes in the Peace-Athabasca Delta (Alberta, Canada)

Monitoring hydrological processes in remote, northern landscapes is challenging, but necessary as climate change and anthropogenic stressors continue to threaten security of water supply. The Peace-Athabasca Delta is a northern freshwater floodplain in Alberta and recognized Ramsar Wetland of International Importance that has experienced recent drying and lake-level decline. In 2020, we collaborated with Wood Buffalo National Park and community-based monitoring groups to assess hydrological conditions across the delta based on field sampling at 60 lakes and 9 river sites. Water isotope tracers were used to quantify the spatial extent of flooding, the contribution of inputs from floodwater, snowmelt and rainfall to lakes, and the influence of evaporation on lake water balance. Lake-level loggers were used to identify the timing and spatial extent of open-water flooding and captured several instances of prolonged, intense rainfall events. Results show that strongly positive lake water balances persisted across the landscape in 2020, in contrast to the previous 5 years, due to unusually high snowfall and rainfall and associated high river discharge that caused substantial ice-jam and open-water flooding. Continued monitoring of the physical and chemical conditions of the lakes one year after the 2020 flooding will aim to improve our understanding of the relationships between lake hydrology and limnology within the PAD. The new knowledge generated from this research will be key for forecasting hydrolimnological responses to shifting flood regimes in a northern region vulnerable to climate-driven change.

Emily Ogden (runner-up)

MSc Student, Wilfrid Laurier University

Supervisor: Jenn Baltzer (WLU)

Impacts of changing permafrost conditions on plant productivity in the northern boreal

Plant productivity across the boreal forest has increased over the past several decades. However, at a regional scale there is large variation in productivity from increased (greening) to decreased (browning) productivity, and large areas with no measured change. Some of this variation can be explained by disturbances, such as wildfire, or by increased climate variability. However, in northern regions underlain by permafrost, the interactions between climate, disturbance, and plant productivity may be more complex. Our project uses a combination of field-based and remote sensing methods to assess the interactions between changing permafrost conditions and plant productivity in the northwestern boreal. Long-term (1984-2019) permafrost monitoring sites (n=135) established by the Geological Survey of Canada offer a unique opportunity to directly evaluate how permafrost conditions have changed across the Mackenzie Valley of the Northwest Territories, Canada. Using ground thermal data collected from these sites, we characterized changes in active layer thickness and permafrost conditions. Remote sensing techniques were used to evaluate changes in the normalized difference vegetation index (NDVI) as a proxy for plant productivity. Strong association between NDVI and active layer thickness were found in earlier (1984-2000) decades, with significant differences across latitudes. When evaluating the impacts of permafrost thaw, we found that the fastest rates of greening were occurring at sites that had recently undergone permafrost thaw. This increase in productivity may be a result of newly released soil nutrients from the previously frozen ground. These results suggest that permafrost thaw and active layer thickness are important drivers of forest productivity and can help explain some of the site-specific variation in productivity that has been observed.

Kristine Haynes (runner-up)

Post-doctoral Fellow, Wilfrid Laurier University

Supervisor: Bill Quinton (WLU)

Long-term trends in wetland event response with permafrost thaw-induced landscape transition and hummock development

Northwestern Canada’s discontinuous permafrost landscape is transitioning rapidly due to permafrost thaw, with the conversion of elevated, forested peat plateaus to low-lying, treeless wetlands. Increasing hydrological connectivity leads to partial drainage of previously-isolated wetlands, which subsequently develop hummock microtopography. Ultimately, the ecohydrological feedbacks associated with climate-driven permafrost thaw have led to the expansion of treed wetlands in plateau-wetland complexes. Field research and aerial imagery analyses were conducted at the Scotty Creek Research Station, Northwest Territories to examine land cover transition, the development of hummock microtopography and the hydrological response of wetlands connected to the basin drainage network over time. The area of peat plateaus underlain by permafrost declined between 2010 and 2018. The total hummock area increased in the basin wetlands over the same time period, with an overall decrease in the hummock perimeter-to-area ratio as small individual hummocks developed into larger hummock complexes occupied by re-establishing trees. With the development and expansion of hummock area, the tortuosity of flowpaths draining wetlands connected to the drainage network increased. The average time of water level rise in response to precipitation events and the subsequent constants of water level recession for connected wetlands became shorter over the 15-year period of record, as precipitation was directed quickly to runoff. Permafrost thaw-induced wetland transition triggers ecohydrological feedbacks with the potential to alter the availability and sustainability of freshwater resources.

3m Thesis Award Winners

Alicia Pouw

MSc Student, Wilfrid Laurier University

Supervisor: Homa Kheyrollah Pour (WLU)

Mapping Lake Ice Snow Distribution over Canada’s Subarctic Lakes Using Remote Sensing Techniques

Knowledge of the lake ice thickness and the overlying snow cover is an important requirement when addressing interactions between the lake and the atmosphere during winter at high latitudes. The presence of snow on lake ice largely influences the ice thickness, and therefore, concerns rise as changes in the snowpack will significantly impact northern communities that rely on lake ice for transportation and livelihood. To accurately estimate ice thickness spatially, extensive snow depth measurements must be collected across the entire lake. This is a challenge that requires a great deal of time spent in the field. Methods of ice thickness retrieval proposed to date usually use an empirical relationship between snow depth and ice thickness with an assumption made on ice and snow density as well as the snow distribution. Studies have explored the use of remote sensing techniques to map snow distribution over land, however, our understanding of such over lake ice is minimal. This research project will use in-situ measurements (snow depth/ density, ice thickness) combined with remote sensing techniques such as ground penetrating radar (GPR) and remotely piloted aircraft systems (RPAS) to develop a systematic method to estimate the spatial distribution and depth of snow over lake ice in Yellowknife, NWT. Through utilizing a multi-method approach, we can develop a framework for accurately mapping the snow depth and distribution on lakes. While the proposed project will directly benefit the North Slave communities in NWT, the research outcome will be transferable to other northern lakes.

Arash Rafat

MSc Student, Wilfrid Laurier University

Supervisor: Homa Kheyrollah Pour (WLU)

Investigating Interannual Lake Ice Evolution and Composition in Canadian Subarctic Lakes using Thermistor String-based Snow and Ice Mass Balance Apparatus Buoys

Based on Canada’s Climate Change Report, the duration of seasonal lake ice cover has declined across Canada over the past five decades due to later ice formation in fall and earlier spring breakup. Lake ice thickness and extent are being directly influenced by these changes, which play important roles in regulating lake hydrological and biogeochemical processes as well as regional climatic conditions. They also play important roles in socio-economic activities as transportation infrastructure, and recreational activities. The safety of communities is therefore directly impacted by how lake ice thicknesses are changing over a winter season. As Canada’s subarctic region is densely populated with lakes, changes in ice thickness and extent are important indicators of regional climate variability and changes. While increasing air temperature may reduce maximum ice thickness, greater snowfall associated with climate change and variability may increase the proportion of snow-ice (white-ice), which can play an important role in regulating lake ice energy and mass balances. To better understand the influence of climate variability and changes on lake ice evolution, two Snow and Ice Mass Balance Apparatus (SIMBAs) buoys will be installed on two lakes with different physical and hydrological characteristics during winter 2021-22. The SIMBAs will collect high-frequency (15 minutes) real-time temperature profiles through the air-snow-ice-water column to monitor snow depth and ice growth. The usage of these data enhances community and infrastructure protection while determining the influences of climate variability and changes on lake ice evolution in lakes with different hydrological and physical characteristics.

Ethan Lim

High School Student / Research Assistant, Wilfrid Laurier University

Supervisor:Homa Kheyrollah Pour (WLU)

Estimation of Lake Depth from Landsat Lake Surface Temperature

Northern lakes are sentinels of climate change and respond physically and biogeochemically to land-based pressures as well as direct climate forcing. For example, lakes influence local precipitation patterns and store heat to moderate regional temperatures. Lake depth is an important control on lake physical and biogeochemical processes, including lake mixing and freeze-up processes. Furthermore, it is an important parameter for numerical weather prediction models, as it helps outline the interaction between the lake surface and the atmosphere. However, accurate measurements of lake depth using sonar sensors are limited because collecting in-situ data presents logistical challenges, especially for sub-arctic lakes which are remote and hard to access. This research will use Landsat 8 images, thermal infrared sensor (TIRS) bands (100 m spatial resolution), of two subarctic lakes (Handle Lake and Long Lake) and in-situ bathymetric data to develop an algorithm to estimate lake depth. The algorithm will look at trends in temperatures for northern lakes over different months and contrast modelled and measured depths using an AI (Artificial Intelligence) model. The approach will be transferred to other cold region lakes in Canada’s subarctic regions.