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Record W7048747939

Measuring and modelling thermal and moisture regimes in seasonally frozen soils, Wolf Creek, Yukon Territory

2019· dissertation· en· W7048747939 on OpenAlexaboutno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2019
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsInfiltration (HVAC)SnowmeltSoil waterSnowHydrology (agriculture)PrecipitationMoistureWater contentSurface runoffSubarctic climatePermafrost
DOInot available

Abstract

fetched live from OpenAlex

Frozen ground is an important consideration in cold regions hydrology because pore ice can impede the ability of water to infiltrate into and migrate within soils, thereby altering water flow paths and increasing surface runoff. High latitude regions are particularly susceptible to changes in climate, where increases in temperature and changing precipitation trends can alter soil freeze/thaw dynamics. However, there has been limited research on infiltration processes in subarctic alpine environments due to sparse historic data and difficulties with gathering direct measurements. In addition, few hydrological models consider the complexity of frozen soils in such environments. The objectives of this thesis are to assess the ability of the GeoStudio finite element modelling suite to simulate observed soil temperature and moisture data and to evaluate the sensitivity of the models to changing climate scenarios. GeoStudio’s Multiphysics model integrates several models that allow it to simulate concurrent water flow and temperature dynamics in variably saturated environments experiencing soil freezing and thawing. Field data for this study are obtained from Wolf Creek Research Basin (WCRB) in southern Yukon, Canada. Data for quantifying snowmelt, soil moisture, soil temperature, and soil composition were collected at three sites in WCRB from April 2015 to August 2016, adding to the available historical data. Results of the GeoStudio models illustrate the dominance of snow in controlling freeze/thaw dynamics and simulate the study environment to reasonable accuracy with some discrepancies in timing and variability. In addition, GeoStudio is particularly sensitive to surface conditions affecting both coupled heat and water flow processes compared to independent changes of air temperature and precipitation, suggesting future climatic scenarios may have a notable impact on frozen soils. This research helps elucidate the complex heat transfer and water movement processes that control infiltration in northern environments and provides a quantitative assessment of their sensitivity to future climate warming.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.491
Threshold uncertainty score0.987

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.015
GPT teacher head0.199
Teacher spread0.184 · 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 designSimulation or modeling
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

Citations0
Published2019
Admission routes1
Has abstractyes

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