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Record W3215794871 · doi:10.1007/s10040-021-02422-z

Landscape controls of surface-water/groundwater interactions on shallow outwash lakes: how the long-term groundwater signal overrides interannual variability due to evaporative effects

2021· article· en· W3215794871 on OpenAlexaffabout
Kelly Hokanson, Benjamin J. Rostron, K. J. Devito, Chris Hopkinson, C. A. Mendoza

Bibliographic record

VenueHydrogeology Journal · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsUniversity of LethbridgeUniversity of Alberta
Fundersnot available
KeywordsOutwash plainGroundwaterHydrology (agriculture)HydrogeologySurface waterGeologyGroundwater dischargeAquiferEnvironmental scienceGroundwater flowGlacial periodGeomorphology

Abstract

fetched live from OpenAlex

Abstract The spatial and temporal controls on variability of the relative contributions of groundwater within and between flow systems to shallow lakes in the low-relief glaciated Boreal Plains of Canada were evaluated. Eleven lakes located in a coarse glacial outwash, of varying topographic positions and potential groundwater contributing areas, were sampled annually for stable O and H isotope ratios over the course of 8 years. It was demonstrated that landscape position is the dominant control over relative groundwater contributions to these lakes and the spatial pattern of the long-term isotopic compositions attributed to groundwater overrides interannual variability due to evaporative effects. Lakes at low landscape positions with large potential groundwater capture areas have relatively higher and more consistent groundwater contributions and low interannual variability of isotopic composition. Isolated lakes high in the landscape experience high interannual variability as they have little to no groundwater input to buffer the volumetric or isotopic changes caused by evaporation and precipitation. An alternative explanation that lake morphometry (area and volume) control long-term isotopic compositions is tested and subsequently refuted. Landscape position within coarse outwash is a strong predictor for relative groundwater input; however, surface-water connections can short circuit groundwater pathways and confound the signal. A hydrogeological case study for three of the study lakes is used to contextualize and further demonstrate these results.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.244
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.011
GPT teacher head0.224
Teacher spread0.213 · 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

Citations11
Published2021
Admission routes2
Has abstractyes

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