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Record W204342280

The fine-scale spatial and temporal variability of hydrologic attributes associated with the process of infiltration in 'nano-catchments' during a rainfall event.

2006· article· en· W204342280 on OpenAlexaboutno aff
Peter. Andrew-McBride

Bibliographic record

VenueScholarship at UWindsor (University of Windsor) · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicIntegrated Water Resources Management
Canadian institutionsnot available
Fundersnot available
KeywordsInfiltration (HVAC)Environmental scienceHydrology (agriculture)Scale (ratio)Event (particle physics)Spatial variabilityCartographyGeologyGeographyMeteorologyStatisticsMathematicsGeotechnical engineering
DOInot available

Abstract

fetched live from OpenAlex

The dynamism of a variety of hydrologic phenomena tied to the process of infiltration are studied here in relation to their spatial and temporal variability within subhectare bowl-like depressions, or 'nano-catchments'. The process of infiltration is becoming increasingly important to understand as a result of anthropogenically driven changes to the near-surface soil matrix, which alters this process. Within the context of infiltration, the spatial variability of soil moisture is assessed under a changing hydrologic regime in south-central Ontario during a rainfall event. With an increase in soil moisture following precipitation events, the spatial auto-correlation increases for both samples that incorporate 15 cm and 30 cm samples. The pattern of soil moisture is influenced by local topographic shape; however this pattern is also altered by the effect of vegetation in the form of active photosynthesizing vegetation and leaf detritus. The effect of vegetation is such that the relationship between topographic gradient and soil moisture is enhanced under active vegetation, while this same relationship is muted under leaf litter. The variability of infiltration to the point of soil saturation is also assessed. A number of estimates of hydraulic conductivity are used, as well as differing estimates of soil moisture to evaluate the bias of using single point measures versus areal estimates in the modelling of infiltration within these nano-catchments. In conjunction with infiltration modelling, matric potential throughout two nano-catchments is assessed in relation to site characteristics including vegetation, macropores and topographic position. Conclusions support that in monitoring infiltration and soil moisture cannot be fully represented by single point measurements, even at a sub-hectare scale.Dept. of Earth Sciences. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2006 .A537. Source: Masters Abstracts International, Volume: 45-01, page: 0259. Thesis (M.Sc.)--University of Windsor (Canada), 2006.

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 score0.101
Threshold uncertainty score0.201

Distilled classifier scores by category (both heads)

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

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 head0.180
Teacher spread0.175 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

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