Predictive Mapping of the Variable Response of Permafrost Terrain to Climate Change for Optimal Roadway Routing, Design, and Maintenance Forecasting in Northern Canada

McKillop, Robin J.; Sacco, D.; Cronmiller, D.

doi:10.1061/9780784482599.073

Cited by 3 publications

(3 citation statements)

References 2 publications

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“…In this context of a warming climate and warming permafrost, knowledge of thaw sensitivitythe susceptibility of permafrost terrain to thawrelated subsidenceis important for understanding permafrost conditions and the evolution of permafrost landscapes. Because thaw subsidence is typically controlled by the presence of excess ice, observations of thaw subsidence can be used to infer ground ice occurrence and can be useful for understanding heat and mass transfer in permafrost conditions (Gruber 2020), understanding active layer development (Tarnocai et al 2004), predicting thaw sensitivity of the landscape (Antonova et al 2018), understanding thaw susceptibility of infrastructure (Fortier and Savard 2010;Short et al 2014;McKillop et al 2019), or guiding land-use planning (Flynn et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Permafrost thaw sensitivity prediction using surficial geology, topography, and remote-sensing imagery: a data-driven neural network approach

2022

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Seasonal or degradational thaw subsidence of permafrost terrain affects the landscape, hydrology, and sustainability of permafrost as an engineering substrate. We perform permafrost thaw sensitivity prediction via supervised classification of a feature set consisting of geological, topographic, and multi-spectral variables over continuous permafrost near Rankin Inlet, Nunavut, Canada. We build a reference classification of thaw sensitivity using process-based categorization of seasonal subsidence as measured from differential interferometric synthetic aperture radar whereby categories of thaw sensitivity are reflective of ground ice conditions. Classification is performed using a neural network trained on both dispersed and parcel-based reference data. For Low, Medium, High, and Very High thaw sensitivity categories, generalized classification accuracy is 70.8% for 20.6 km2 of dispersed training data. In all cases, the majority classes of Low and Medium thaw sensitivity are predicted with higher accuracy and more certainty, while the minority classes of High and Very High thaw sensitivity are under-predicted. Minority classes can be combined to improve accuracy at the expense of a reduced level of discrimination. The two-class problem can be classified with an accuracy of 81.8%, thereby effectively distinguishing between stable and unstable ground. The method is applicable to similar low-Arctic permafrost terrain with geological and topographical controls on thaw sensitivity. However, generalized accuracy is reduced for parcel-based training, indicating that reference samples are not totally representative for inference beyond the parcel, and any deployment of the network to other geographical regions would benefit from full or partial re-training with local data.

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Section: Introductionmentioning

confidence: 99%

Permafrost thaw sensitivity prediction using surficial geology, topography, and remote-sensing imagery: a data-driven neural network approach

2022

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“…For example, along a section of the Dempster Highway, 75% of mapped mass movement events were influenced by the existence of permafrost (Fig. 2.9) (McKillop et al 2016).…”

Section: Slope Processesmentioning

confidence: 99%

“…Landslides and washouts occur frequently in the Ogilvie section due to the proximity of the highway to hillslopes where slope failures are occurring more frequently 132 in response to climate warming, forest fires, and increased precipitation (McKillop 2016).…”

Section: Physical Basis For Expendituresmentioning

confidence: 99%

Climate change induced increases in maintenance costs for Yukon highways, 1994–2022

Schetselaar

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Climate-related maintenance expenditures in 1994-2022 were examined for 20 maintenance sections of the highway network in Yukon. Maintenance activities, including snow clearing, icing control, culvert activities, washout repair, and landslide removal are directly linked to climate but primarily associated with hydrologic processes.Despite relatively stable total operation and maintenance budgets, climate-related maintenance expenditures increased across the network, both in absolute terms and as a proportion of the overall budget.

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Effect of surficial geology mapping scale on modelled ground ice in Canadian Shield terrain

O'Neill,

Wolfe,

Duchesne

et al. 2024

The Cryosphere

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Abstract. Ground ice maps at small scales offer generalized depictions of abundance across broad circumpolar regions. In this paper, the effect of surficial geology mapping scale on modelled ground ice abundance is examined in the Slave Geological Province of the Canadian Shield, a region where the geological and glacial legacy has produced a landscape with significant variation in surface cover. Existing model routines from the Ground ice map of Canada (GIMC) were used with a 1:125 000-scale regional surficial geology compilation and compared to the national outputs, which are based on surficial geology at a 1:5 000 000 scale. Overall, the regional-scale modelling predicts much more ground ice than the GIMC due to greater representation of unconsolidated sediments in the region. Improved modelling accuracy is indicated by comparison of the outputs to empirical datasets due to improved representation of the inherent regional heterogeneity in surficial geology. The results demonstrate that the GIMC significantly underestimates the abundance and distribution of ground ice over Canadian Shield terrain. In areas with limited information on ground ice, regional-scale modelling may provide useful reconnaissance-level information to help guide the field-based investigations required for planning infrastructure development. The use of current small-scale ground ice mapping in risk or cost assessments related to permafrost thaw may significantly influence the accuracy of outputs in areas like the Canadian Shield, where surficial materials range from bedrock to frost-susceptible deposits over relatively short distances.

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Predictive Mapping of the Variable Response of Permafrost Terrain to Climate Change for Optimal Roadway Routing, Design, and Maintenance Forecasting in Northern Canada

Cited by 3 publications

References 2 publications

Permafrost thaw sensitivity prediction using surficial geology, topography, and remote-sensing imagery: a data-driven neural network approach

Permafrost thaw sensitivity prediction using surficial geology, topography, and remote-sensing imagery: a data-driven neural network approach

Climate change induced increases in maintenance costs for Yukon highways, 1994–2022

Effect of surficial geology mapping scale on modelled ground ice in Canadian Shield terrain

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