Investigating the seasonality of subarctic lakes in a changing climate using satellite & field data

Regions: North Slave Region

Tags: physical sciences, water quality, climate change, lake ice, remote sensing

Principal Investigator: Kheyrollah Pour, Homa (3)
Licence Number: 17110
Organization: Wilfrid Laurier University
Licensed Year(s): 2022 2021
Issued: Aug 17, 2022
Project Team: Mike Palmer, Mike English, Bruce Hanna

Objective(s): To explore the relationship of seasonal lake ice growth/ablation and water quality across a wide range of lake characteristics.

Project Description: This licence has been issued for the scientific research application No.5335.

This proposed research is directed at understanding the impact of current/future climate warming on subarctic lake ecosystems. The aim is to explore the relationship of seasonal lake ice growth/ablation and water quality across a wide range of lake characteristics (size, volume, productivity, catchment characteristics. Complimentary to this objective the research team will relate remote sensing observations (drone to satellite scale) to water quality differences within the selected range of study sites selected, especially productivity. Meteorological data from Yellowknife airport will provide the team data to employ simple degree day models (and applying appropriate coefficients for the snow-on-ice offset of lake-to-atmosphere thermal gradients) for approximating ice growth. Lake water quality measurements for nitrogen, phosphate, dissolved organic (and inorganic) carbon, pH, conductivity, chlorophyll-a will be taken in stratified fashion during early and mid-winter, early spring, summer and prior to ice formation in the fall. Drone surveys employing a range of sensors will document changes in ice cover throughout the fall, and winter.

Objective 1: Characterize seasonality of physical, biological and chemical lake properties (ice thickness, temperature, conductivity, dissolved oxygen, dissolved organic carbon, dissolved inorganic carbon, nutrients (N and P) at the range of lakes being monitored for the study. Objective 2: Relate remote sensed data to field-based observations in order to evaluate seasonal changes and variability in lakes in the North Slave region near Yellowknife. Objective 3: Examine the relationships accomplished in Objective 2 on other lakes in the region with lack of field-based observations to test the applicability of the relationships across a broader range of lakes.

Six lakes (training lakes) in the North Slave region will be sampled across seasons to characterize seasonal changes in ice thickness and water quality. These data will be used as a training data set for algorithm development and evaluating remotely sensed observations. Developed lake specific algorithm on ice-on/off dates, ice extent and chlorophyll-a from satellite will be applied for the other lakes with lack of ground observations. The training lakes will span a range of sizes, morphometry, and land use. Six training site lakes have been selected and will be sampled 6 times per year (September, November, January, April, May, and July).

Lake morphology: Surface area, mean/maximum depth, volume, catchment area, drainage characteristics and vegetation will be explored.
Lake physical parameters: Water column temperature, conductivity and dissolved oxygen (surface to sediment), date of ice-on and ice-off, ice thickness and ice type (white ice versus congelation ice), snow depth, and secchi depth will be explored.
Lake water quality: Nutrients, major ions, alkalinity, dissolved organic (and inorganic), turbidity, total suspended sediment, carbon and redox sensitive metal(loid)s will be explored.

Selection of 6 Training site lakes/sampling these lakes for water quality and physical parameters (winter observations: Ground-penetrating radar (GPR)-ice physical development (Training lakes); Summer observations: Water sampling (Training lakes)). Drone: drone using multispectral and thermal sensors will fly over the selected Training Lakes. Drone observations might be used over Selected Lakes (winter observations: RGB, Multispectral; Summer observations: Multispectral and Thermal). Satellite data: Satellite data will be applied over Selected Lakes (winter observations: RADARSAT-2/Sentinel 1; summer observations: Landsat; Sentinel 3).

Data collected will be made publicly available and uploaded to the Mackenzie DataStream. Local Indigenous community members will be hired through the Dechita Naowo program with the Yellowknives Dene First Nation for participation in field activities and training.

A kick-off workshop for community-only members as a first step to identify community priorities, identification of priority areas with opportunities for community input and feedback throughout, and developing a community-based consensus plan of action for addressing these needs. An annual meetings with northern stakeholders will take place to discuss project progress and to gather feedback about future project development. At minimum the team will meet with representatives from Environment and Natural Resources, Yellowknives Denes First Nation, North Slave Metis Alliance, and NWT Centre for Geomatics once per year. Annual workshops to bring together researchers, community members and decision-makers to discuss current research results and key funding opportunities (2021-2023) (Note, these meetings will all be virtual until COVID related travel restrictions are lifted) will take place. The research team will give annual (scientific and plain language) and final project reports and presentation at NWT Cumulative Impact Monitoring workshop.

The fieldwork for this study will be conducted from August 16, 2022 to December 31, 2022