Characterising the spatial variability of permafrost measurements in different landscape types at the climate impacted coastal communities in the Inuvialuit Settlement Region, Canada, using Ground Penetrating Radar

Changing climate conditions are causing significant impacts for Arctic communities and the landscapes, ecosystems and infrastructure they rely on. Rapid permafrost degradation is not uniform over space or time and there are a variety of variables contributing to the vulnerability of different infrastructure to thaw-related hazards. These include event-based changes such as heat waves, rainfall, and storm surge events, and longer term shifts such as rising sea levels, groundwater processes during thaw season, and heat transfer from construction materials. The relative influences and interactions between these controls on the rate and nature of permafrost degradation remain poorly understood.

This work leverages correlated Ground Penetrating Radar (GPR) validated with ground probing to examine the spatial changes of the depth to base of the active layer. The GPR data have been characterised into different landscape types; those with a sand/sea interface, untouched tundra, road construction, airport aprons, and made (constructed) ground. The use of GPR prevents destruction and disruption to the already vulnerable permafrost and provides continuous subsurface mapping data. Simplified 2D numerical models have been created using electromagnetic simulation software (gprMax) to parameterise the findings from the measured field data. The purpose of this is to verify the assumptions of the processed GPR data, without the need for destructive borehole testing or coring, as would have been used historically. The combination of modelling and survey data shows the impact of the different landcover types on permafrost degradation and provides the community with valuable knowledge on the impacts of distinct alterations in land use on permafrost, allowing more informed decisions on best building practices.

These findings demonstrate the impact of assumptions made in the field of GPR settings and highlight its effectiveness in detecting the permafrost to active layer interface under different conditions. When combined with the 2D model interpretations GPR surveys offers a targeted training dataset that can potentially be scaled with earth observation data, targeting specific features, settings and infrastructure that impact permafrost degradation.