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Record W2995166918 · doi:10.11575/prism/37240

Measurement and Simulation of Preferential Flow in Frozen Soils

2019· dissertation· en· W2995166918 on OpenAlexfundaboutno aff
Aaron A. Mohammed

Bibliographic record

VenueOpen MIND · 2019
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaAlberta InnovatesAlberta Environment and Parks
KeywordsSoil waterFlow (mathematics)Environmental scienceSoil scienceMechanicsPhysics

Abstract

fetched live from OpenAlex

The infiltrability of frozen soils strongly influences the partitioning of snowmelt and hydrological functioning of cold regions. Preferential flow in macropores may enhance infiltration into frozen soil, but flow dynamics are complicated by coupled water and heat transfer processes. Field studies were conducted in the Canadian Prairies to evaluate the dominant mechanisms controlling preferential flow in frozen soils, and the combined influence of soil freeze-thaw and preferential flow on snowmelt-driven infiltration and groundwater recharge. Results showed that preferential flow enabled relatively large amounts of snowmelt infiltration when the soil was still frozen, but that refreezing of infiltrated meltwater during winter snowmelt events progressively reduced soil infiltrability and enhanced runoff generation over subsequent events. Preferential flow allowed meltwater to bypass portions of the frozen soil and facilitated the lateral transport of meltwater between high and low topographic positions and groundwater recharge through frozen ground. Insights gained from field studies were used to develop a dual-permeability model of unsaturated flow in frozen soils that assumes two interacting pore domains (macropore and matrix) with distinct water and heat transfer regimes. This dual-permeability formulation was incorporated into the hydrological model HydroGeoSphere to account for liquid-ice phase change in macropores, such that porewater freezing in macropores is governed by macropore-matrix energy transfer. The model was tested against field and laboratory observations and used to examine the effects of preferential flow on snowmelt partitioning between surface and subsurface flow in frozen soils. Simulations were able to reproduce measured profile-scale infiltration and drainage in frozen soil due to macropores, as well as hillslope-scale partitioning of snowmelt input between runoff, infiltration and groundwater recharge. Incorporating macropore flow and freeze-thaw processes was key to simulating the hydrologic functioning of the prairie grassland landscape, and results highlighted that refreezing of infiltrated water governed by macropore-matrix heat transfer is an important subsurface process controlling runoff generation in frozen soils. This study improves our understanding of, and ability to predict, the effects of preferential flow and freeze-thaw on frozen soil infiltrability, and how these processes dictate the partitioning of snowmelt between surface runoff, soil moisture and groundwater recharge in seasonally frozen landscapes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.729
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0170.000

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 head0.107
GPT teacher head0.310
Teacher spread0.203 · 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 teacher head, not a consensus.

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

Citations1
Published2019
Admission routes2
Has abstractyes

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