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Record W2021394130 · doi:10.1002/hyp.320

Estimating areal snowmelt infiltration into frozen soils

2001· article· en· W2021394130 on OpenAlexafffund
Donald M. Gray, Brenda Toth, Litong Zhao, John W. Pomeroy, R. J. Granger

Bibliographic record

VenueHydrological Processes · 2001
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsEnvironment and Climate Change CanadaUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSnowmeltInfiltration (HVAC)Soil waterMeltwaterEnvironmental scienceHydrology (agriculture)Water contentSnowSoil scienceGeologyGeotechnical engineeringGeomorphologyGeographyMeteorology

Abstract

fetched live from OpenAlex

Abstract An algorithm for estimating areal snowmelt infiltration into frozen soils is developed. Frozen soils are grouped into classes according to surface entry condition as: (a) Restricted —water entry is impeded by surface conditions, (b) Limited –capillary flow predominates and water entry is influenced primarily by soil physical properties, and (c) Unlimited —gravity flow predominates and most of the meltwater infiltrates. For Limited soils cumulative infiltration over time is estimated by a parametric equation from surface saturation, initial soil moisture content (water + ice), initial soil temperature and infiltration opportunity time. Total infiltration into Unlimited and Limited soils is constrained by the available water storage capacity. This constraint is also used to determine when Limited soils have thawed. The minimum spatial scale of the infiltration model is established for Limited soils by the variabilities in surface saturation, snow water equivalent, soil infiltrability, soil moisture (water + ice) and depth of soil freezing. Since snowmelt infiltration is influenced by other processes and factors that affect snow ablation, it is assumed that the infiltrability spatial scale should be consistent with the scales used to describe these variables. For open, northern, cold regions the following order in spatial scales is hypothesized: frozen ground ≥ snowmelt ≥ snow water equivalent ≥ frozen soil infiltrability ≥ soil moisture (water + ice) and snow water. For mesoscale application of the infiltration model it is recommended that the infiltrability scale be taken equal to the scale used to describe the areal extent and distribution of the water equivalent of the snowcover that covers frozen ground. Scaling the infiltrability of frozen soils in this manner allows one to exploit established landscape‐stratification methodology used to derive snow accumulation means and distribution. Scaling of soil infiltrability at small scales (microscale) is complicated and requires information on the association(s) between the spatial distributions of soil moisture (water + ice) and snow water. A flow chart of the algorithm is presented. Copyright © 2001 John Wiley & Sons, Ltd.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.246
Teacher spread0.214 · 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

Citations243
Published2001
Admission routes2
Has abstractyes

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