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Analytical methodology for determining the extent of pumped freshwater lenses in recharge-limited, circular islands

2024· article· en· W4394015605 on OpenAlexafffund
Barret L. Kurylyk, Ying‐Fan Lin, S. Cristina Solórzano‐Rivas, Adrian D. Werner

Bibliographic record

VenueAdvances in Water Resources · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsDalhousie University
FundersCanada Research ChairsFlinders University
KeywordsGroundwater rechargeAquiferLens (geology)GeologyHydrology (agriculture)GroundwaterGeotechnical engineeringPetroleum engineering

Abstract

fetched live from OpenAlex

Island freshwater lenses are often subjected to pumping to support the freshwater needs of isolated communities. Investigations of the lens extent commonly involve the application of analytical solutions, although the effects of pumping from circular island aquifers have not been assessed in previous analytical methodologies. In this study, a new analytical solution is derived based on Green's functions that accommodate freshwater inputs (recharge) and outputs (multiple wells) when obtaining the head distribution and sharp-interface lens shape. The solution is verified using a finite-element model for an illustrative pumping scenario. The solution is also differentiated with respect to pumping rates, recharge, and island radius to obtain vulnerability indices to characterize the lens sensitivity to changes in stresses. Finally, the analytical methodology is modified to examine the effects of non-uniform recharge. Python code incorporating the new solution is included to enable users to investigate a range of recharge and pumping scenarios.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.878
Threshold uncertainty score0.271

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.040
GPT teacher head0.308
Teacher spread0.268 · 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 designNot applicable
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

Citations7
Published2024
Admission routes2
Has abstractyes

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