EGU2020-21789, updated on 14 Sep 2023
https://doi.org/10.5194/egusphere-egu2020-21789
EGU General Assembly 2020
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Comparing streamflow analysis and remote sensing observations to assess climate change impact on permafrost degradation

flore sergeant1, rene therrien2, ludovic oudin3, anne jost4, and françois anctil5
flore sergeant et al.
  • 1Université Laval, Géologie et génie géologique, Canada (flore.sergeant.1@ulaval.ca)
  • 2Université Laval, Géologie et génie géologique, Canada (Rene.Therrien@ggl.ulaval.ca)
  • 3Université Pierre et Marie Curie, Laboratoire METIS, France (ludovic.oudin@sorbonne-universite.fr)
  • 4Université Pierre et Marie Curie, Laboratoire METIS, France (anne.jost@upmc.fr)
  • 5Université Laval, Département génie civil et génie des eaux, Canada (Francois.Anctil@gci.ulaval.ca)

ABSTRACT

Due to polar amplification of climate change, high latitudes are warming up twice as fast as the rest of the world. This warming leads to permafrost thawing, which induces greenhouse gases release, ground subsidence, and modifies surface and subsurface hydrologic regimes. Ground subsidence in turn affects local infrastructure stability. In this context and to better manage future infrastructures and water resources of northern regions, it is crucial to be able to evaluate the thawing rate of permafrost.

In many Arctic zones, the frequency of environmental disturbances caused by permafrost thawing increases so rapidly that maintaining an accurate inventory of the state of permafrost at a regional scale represents a great challenge. Moreover, depending on the study area and the permafrost ice content, the thawing rate can vary from millimetres to decimeters per year. Another current challenge is the limited availability of temporal and spatial data on permafrost thawing rates.

To address the above challenges, two indirect methods are used: (1) Arctic river streamflow analysis method and (2) Ground settlement analysis method via satellite image observation. Both methods use free-access data that have an exceptionally large temporal and spatial coverage capacity for such a poorly instrumented region. The first method analyses the recession events’ behavior of Arctic streams and relates those behaviors to changes in catchment-scale depth to permafrost that influences storage-discharge dynamics. This work differs from previous hydrological system analysis in northern systems in that it looks at long-term trends (>10 years) in recession intercept to assess permafrost dynamics, while other studies looked at recession characteristics within a season to assess active-layer dynamics. The second method analyses satellite images of the Arctic ground and associates surface elevation change to long-term permafrost degradation due to climate change.

Both methods have already been tested through multiple local investigations and gave promising results. The recession flow analysis method has been applied to Yukon river basin, northern Sweden basins and Lena basin in Siberia, while the remote sensing analysis method has been tested on Baffin Island, Herschel Island in Canada, North Slope of Alaska and the Tibetan Plateau. However, no comparative study and no large-scale application have been conducted so far. Extending the analysis to hundreds of Arctic basins and comparing the resulting permafrost-thawing rate values from both methods constitute the innovative aspect of this project.

 

KEY WORDS: climate change, permafrost thawing, storage-discharge dynamics, ground subsidence, satellite images

How to cite: sergeant, F., therrien, R., oudin, L., jost, A., and anctil, F.: Comparing streamflow analysis and remote sensing observations to assess climate change impact on permafrost degradation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21789, https://doi.org/10.5194/egusphere-egu2020-21789, 2020.

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