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Record W4414146764 · doi:10.1029/2025ef006221

Peak Groundwater: Aquifer‐Scale Limits to Groundwater Withdrawals

2025· article· en· W4414146764 on OpenAlexafffund
John A. Cherry, Leonard F. Konikow, Richard G. Taylor, Beth L. Parker

Bibliographic record

VenueEarth s Future · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGroundwater and Isotope Geochemistry
Canadian institutionsUniversity of Guelph
FundersForeign, Commonwealth and Development OfficeNatural Sciences and Engineering Research Council of CanadaInternational Development Research CentreCanadian Institute for Advanced Research
KeywordsGroundwaterAquiferGroundwater flowGroundwater modelHydrology (agriculture)Sustainable managementSurface water

Abstract

fetched live from OpenAlex

Abstract “ Peak Groundwater ” is the maximum withdrawal rate of groundwater from an aquifer system that precedes a decline in withdrawals resulting from aquifer depletion. This paper traces generalizable phases in groundwater‐withdrawal regimes in individual aquifer systems and their associated impacts on eco‐ and geosystem services. The concept seeks to address common misunderstandings of fundamental concepts in hydrogeology, which have practical consequences for the management of groundwater systems that sustain these services. The Peak Groundwater concept highlights the critical need to acknowledge the nested character of transient groundwater flow systems and the effects of groundwater withdrawals beyond the aquifer boundary. Importantly, estimations of sustainable groundwater withdrawals need to consider indirect human‐environmental risks of withdrawals, such as surface water depletion and land subsidence. Estimating acceptable steady‐state limits for future groundwater withdrawals presents an “optimization challenge.” Solving this optimization challenge, estimating sustainable withdrawals for balanced groundwater budgets, is rooted in societal priorities and demands high‐quality simulation models and monitoring tools and practices such as 4D monitoring systems that are complementary in type and scale. Recognition and prediction of Peak Groundwater can guide groundwater managers on how to operate within sustainable limits of abstraction. Proactive adaptive groundwater management can prevent Peak Groundwater and associated decline in withdrawal capacities.

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)0.001
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.203
Teacher spread0.197 · 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
Published2025
Admission routes2
Has abstractyes

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