Estimating Permafrost Distribution Using Co‐Located Temperature and Electrical Resistivity Measurements

Uhlemann, S.; Shirley, I.; Wielandt, S.; Ulrich, C.; Wang, C.; Fiolleau, S.; Peterson, J.; Lamb, J.; Thaler, E.; Rowland, J.; Hubbard, S. S.; Dafflon, B.

doi:10.1029/2023gl103987

Cited by 4 publications

(3 citation statements)

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“…From 2013 to 2017, the mean annual air temperature is −1.02 • C and the yearly rain and snow precipitation are 450 mm, and 1705 mm, respectively (Léger et al 2019). The site has mostly south-east facing slopes and the general geology consists of a thin layer of organic materials overlying silts, with schist bedrock beneath (Uhlemann et al 2023).…”

Section: Study Site and Datasetsmentioning

confidence: 99%

Local-scale heterogeneity of soil thermal dynamics and controlling factors in a discontinuous permafrost region

Wang,

Shirley,

Wielandt

et al. 2024

Environ. Res. Lett.

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In permafrost regions, the strong spatial and temporal variability in soil temperature cannot be explained by the weather forcing only. Understanding the local heterogeneity of soil thermal dynamics and their controls is essential to understand how permafrost systems respond to climate change and to develop process-based models or remote sensing products for predicting soil temperature. In this study, we analyze soil temperature dynamics and their controls in a discontinuous permafrost region on the Seward Peninsula, Alaska. We acquired one-year temperature time series at multiple depths (at 5 or 10 cm intervals up to 85 cm depth) at 45 discrete locations across a 2.3 km2 watershed. We observed a larger spatial variability in winter temperatures than that in summer temperatures at all depths, with the former controlling most of the spatial variability in mean annual temperatures. We also observed a strong correlation between mean annual ground temperature at 85 cm and mean annual or winter season ground surface temperature across the 45 locations. We demonstrate that soils classified as cold, intermediate, or warm using hierarchical clustering of full-year temperature data closely match their co-located vegetation (graminoid tundra, dwarf shrub tundra, and tall shrub tundra, respectively). We found that the spatial heterogeneity in soil temperature is primarily driven by spatial heterogeneity in snow covers, which induces variable winter insulation and soil thermal diffusivity. These effects further extend to the subsequent summer by causing variable latent heat exchanges. Finally, we discuss the challenges of predicting soil temperatures from snow depth and vegetation height alone by considering the complexity observed in the field data and reproduced in a model sensitivity analysis.

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Section: Study Site and Datasetsmentioning

confidence: 99%

Local-scale heterogeneity of soil thermal dynamics and controlling factors in a discontinuous permafrost region

Wang,

Shirley,

Wielandt

et al. 2024

Environ. Res. Lett.

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“…Samples with temperatures <1.8°C were classified as permafrost, but if resistivity values exceeded 3,000 Ωm, the temperature threshold for classification was increased to 2.4°C. Full details of the co-located measurement classification schemes are given in Uhlemann et al (2023).…”

Section: Geophysical Observationsmentioning

confidence: 99%

“…The transects were chosen to image areas that were previously identified by frost probing to represent transitions between presence and absence of near-surface permafrost; however the ERT data provide a more continuous measurement of near-surface permafrost presence compared to probing alone. ResIPy (Blanchy et al, 2020) was used to pre-process and invert the ERT data to derive the resistivity distribution (Uhlemann et al, 2023).…”

Section: Geophysical Observationsmentioning

confidence: 99%

High‐Resolution Maps of Near‐Surface Permafrost for Three Watersheds on the Seward Peninsula, Alaska Derived From Machine Learning

Thaler,

Uhleman,

Rowland

et al. 2023

Earth and Space Science

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Permafrost soils are a critical component of the global carbon cycle and are locally important because they regulate the hydrologic flux from uplands to rivers. Furthermore, degradation of permafrost soils causes land surface subsidence, damaging infrastructure that is crucial for local communities. Regional and hemispherical maps of permafrost are too coarse to resolve distributions at a scale relevant to assessments of infrastructure stability or to illuminate geomorphic impacts of permafrost thaw. Here we train machine learning models to generate meter‐scale maps of near‐surface permafrost for three watersheds in the discontinuous permafrost region. The models were trained using ground truth determinations of near‐surface permafrost presence from measurements of soil temperature and electrical resistivity. We trained three classifiers: extremely randomized trees (ERTr), support vector machines (SVM), and an artificial neural network (ANN). Model uncertainty was determined using k‐fold cross validation, and the modeled extents of near‐surface permafrost were compared to the observed extents at each site. At‐a‐site near‐surface permafrost distributions predicted by the ERTr produced the highest accuracy (70%–90%). However, the transferability of the ERTr to the sites outside of the training data set was poor, with accuracies ranging from 50% to 77%. The SVM and ANN models had lower accuracies for at‐a‐site prediction (70%–83%), yet they had greater accuracy when transferred to the non‐training site (62%–78%). These models demonstrate the potential for integrating high‐resolution spatial data and machine learning models to develop maps of near‐surface permafrost extent at resolutions fine enough to assess infrastructure vulnerability and landscape morphology influenced by permafrost thaw.

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Improved 3D characterization of in-situ soil desiccation cracking by multi-source data integration

Zhang,

Tang,

et al. 2024

Geoderma

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Estimating Permafrost Distribution Using Co‐Located Temperature and Electrical Resistivity Measurements

Cited by 4 publications

References 50 publications

Local-scale heterogeneity of soil thermal dynamics and controlling factors in a discontinuous permafrost region

Local-scale heterogeneity of soil thermal dynamics and controlling factors in a discontinuous permafrost region

High‐Resolution Maps of Near‐Surface Permafrost for Three Watersheds on the Seward Peninsula, Alaska Derived From Machine Learning

Improved 3D characterization of in-situ soil desiccation cracking by multi-source data integration

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