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HISTORICAL AND ESTIMATED GROUND WATER LEVELS NEAR WINNIPEG, CANADA, AND THEIR SENSITIVITY TO CLIMATIC VARIABILITY<sup>1</sup>

2003· article· en· W1971339104 on OpenAlexaffabout
Grant Ferguson, Scott St. George

Bibliographic record

VenueJAWRA Journal of the American Water Resources Association · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsGeological Survey of CanadaUniversity of Manitoba
Fundersnot available
KeywordsPrecipitationAquiferHydrographHydrology (agriculture)GroundwaterBoreholeEnvironmental sciencePiezometerGeologyDendrochronologyClimate changePhysical geographyDrainage basinGeographyMeteorologyPaleontology

Abstract

fetched live from OpenAlex

ABSTRACT: Long term well hydrographs and estimated ground water levels derived from hydroclimatic and biological data were used to evaluate trends within the Upper Carbonate Aquifer (UCA) near Winnipeg, Canada, during the 20th Century. Ground water records from instruments have been kept since the early 1960s and are derived from piezometers in the overlying sediments and in open boreholes in the UCA. Some boreholes extend into an underlying Paleozoic carbonate sequence. Shallow well hydrographs show no obvious long term trends but do exhibit variations on the order of three to four years that are correlated with changes in annual temperature and precipitation at lags up to 24 months. Trends observed in deeper wells appear to be largely related to ground water usage patterns and show little correlation with climate over the past 35 years. Stepwise multiple regression modeled average annual hydraulic head in the shallow wells as a function of regional temperature, precipitation, and tree ring variables. Estimated hydraulic heads had a slightly greater range prior to the 1960s, most prominently during an interval of lowered ground water levels between 1930 and 1942. Regression results demonstrate that moisture sensitive tree ring data are viable predictors of past ground water levels and may be useful for studies of aquifers in regions that lack long, high quality precipitation records.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0000.000

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 head0.009
GPT teacher head0.198
Teacher spread0.189 · 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 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

Citations44
Published2003
Admission routes2
Has abstractyes

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