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Record W3131228867

The changing influence of permafrost on peatlands hydrology

2021· dissertation· en· W3131228867 on OpenAlexaboutno aff
Élise Devoie

Bibliographic record

VenueUWSpace (University of Waterloo) · 2021
Typedissertation
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsPermafrostPeatHydrology (agriculture)Environmental sciencePhysical geographyGeographyGeologyGeotechnical engineeringOceanographyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Hydrology and hydrological modelling in the far north is understudied, and many gaps exist in the current understanding and representation of northern thermal and hydrological systems. A combination of fieldwork and modelling was used to gain a better understanding of landscape evolution and thaw processes in the peatland-dominated discontinuous permafrost region of the Northwest Territories. Data collected at the Scotty Creek Research Station and modelling tools are developed and used to identify and quantify controls on isolated and connected talik formation in discontinuous permafrost peatland systems which include soil moisture, snow cover, surface temperature and subsurface lateral flow. The formation of a talik was shown to be a tipping point in permafrost degradation after which several positive feedback cycles led to more rapid permafrost loss. \n \n \nGiven the widespread prevalence of taliks in this discontinuous permafrost peatlands environment, seasonal pressure and temperature gradients were analyzed in different talik configurations to determine the impacts of taliks on the landscape. It was found that the formation of taliks led to a balance between increased hydrologic storage due to isolated talik prevalence, and increased discharge from the basin due to connected talik features allowing previously inaccessible runoff features to be connected to the drainage network. Thermodynamically speaking, the interplay between subsurface temperature, thaw rates, subsidence, snow accumulation, canopy coverage and soil moisture were discussed supporting the idea that talik formation is a positive feedback for permafrost loss. It is also noted that the loss of permafrost causes subsidence and geophysical destabilization leading to ecosystem change and a change in greenhouse gas emission regimes. \n \n \nExisting models representing permafrost and other cold-regions processes are either computationally expensive physically-based models, or empirically based. This limits their predictive ability at the watershed scale or larger. Large-scale predictions of the impacts of changing climate and subsequent permafrost thaw are needed to improve our understanding of long-term evolution of semi-discontinuous permafrost landscapes. To extend predictions to this scale, a novel physically-based interface model of active layer and permafrost evolution is developed and validated against both field data and a benchmarked continuum numerical model. This simplified model is designed to be incorporated into a semi-distributed hydrological model that will be used to predict hydrologic impacts of changes in permafrost dynamics at the basin scale. This model was used to inform the current understanding of permafrost thaw mechanisms in this environment. \n \n \nIn order to quantify the rate of permafrost loss, different parts of the landscape are classified based on the mechanisms for permafrost thaw including conduction and advection in both the vertical and lateral directions. These results help to explain the observed heterogeneity in thaw rates in the landscape. It was found that conduction is responsible for much of the thaw in the vertical direction, while advective processes do play a role in flow-through talik features. Lateral thaw is occurring more rapidly than vertical thaw, due both to conduction and advective heat transfer. Finally, thaw from below is documented both due to geothermal heat flux, and observed deep thermistor temperature profiles. The combined fieldwork and modelling efforts provide a better understanding of the rapidly changing discontinuous permafrost environment, help to predict hydrologic and landscape changes in Canada's north, and create tools which are transferable to other cold-regions environments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.186
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2021
Admission routes1
Has abstractyes

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