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Application of Harmonic Analysis of Water Levels to Determine Vertical Hydraulic Conductivities in Clay‐Rich Aquitards

2003· article· en· W1985877003 on OpenAlexaffabout
Brigitte EJ Boldt-Leppin, M. Jim Hendry

Bibliographic record

VenueGround Water · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsGeologyHydraulic conductivityHarmonicGeotechnical engineeringMineralogySoil sciencePhysicsAcoustics

Abstract

fetched live from OpenAlex

A harmonic analysis method was used to determine vertical hydraulic conductivities (Kv) in geologic media between vertically separated piezometers using water level measurements. In this method, each water level time series was filtered and then decomposed using harmonic analysis into a sum of trigonometric components. The phase and amplitude of each harmonic function were calculated. These data were used to estimate Kv values between vertically separated data sets assuming one-dimensional transient flow. The method was applied to water level data collected from nested piezometers at two thick clay-rich till aquitards in Saskatchewan, Canada. At one site, routine water levels were measured in 12 piezometers (installed between 1 and 29 m below ground surface) since installation (1995). At the other site, water levels were measured in seven piezometers (installed between 4 and 53 m below ground surface) since installation (1998-1999). The Kv calculated using harmonic analysis decreased with depth below the water table at both sites, approaching matrix estimates of hydraulic conductivity between 10 and 11 m and between 21 and 43 m below ground surface. These depths reflected the depth of extensive vertical fracturing at the sites and showed that the depth of fracturing may be site specific.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.593

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)0.0010.000

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 head0.025
GPT teacher head0.246
Teacher spread0.221 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations34
Published2003
Admission routes2
Has abstractyes

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