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Record W2615101319 · doi:10.1002/2017gl073322

The rapid yet uneven turnover of Earth's groundwater

2017· article· en· W2615101319 on OpenAlexaff
Kevin M. Befus, Elco Luijendijk, Tom Gleeson, M. Bayani Cardenas

Bibliographic record

VenueGeophysical Research Letters · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsUniversity of VictoriaUniversity of Calgary
FundersNational Science Foundation
KeywordsGroundwaterAquiferGroundwater rechargeGeologyHydrology (agriculture)WeatheringEnvironmental scienceLast Glacial MaximumGlacial periodGeomorphology

Abstract

fetched live from OpenAlex

Abstract The turnover of groundwater through recharge drives many processes throughout Earth's surface and subsurface. Yet groundwater turnover rates and their relationship to regional climate and geology remain largely unknown. We estimated that over 200 × 106 km3 of groundwater has recharged since the Last Glacial Maximum (LGM), which is 10 times the volume of global groundwater storage. However, flushing is very unevenly distributed throughout Earth's one million watersheds, with some aquifers turned over thousands of times to others with <1% turnover. The median global groundwater turnover of 5 ± 3 times since the LGM highlights groundwater's active role in Earth system processes. Incomplete groundwater turnover since the LGM beneath a third of land areas reveals the imprint of relict climate conditions on modern‐day groundwater resources. The bulk groundwater turnover calculated here enables better quantification of groundwater's impact in dynamic global water budgets and the transport of nutrients, contaminants, and geologic weathering products.

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 score0.005
Threshold uncertainty score0.010

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 communication0.0010.001
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 head0.035
GPT teacher head0.282
Teacher spread0.248 · 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

Citations53
Published2017
Admission routes1
Has abstractyes

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