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Record W2758355183 · doi:10.1088/1748-9326/aa8ac0

Dry groundwater wells in the western United States

2017· article· en· W2758355183 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnvironmental Research Letters · 2017
Typearticle
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsUniversity of Calgary
FundersS. D. Bechtel, Jr. Foundation and Stephen Bechtel Fund
KeywordsGroundwaterAgricultureWater wellWater resource managementHydrology (agriculture)ProductivityEnvironmental scienceWater scarcityGeographyGeologyArchaeology

Abstract

fetched live from OpenAlex

Declining groundwater levels are common in parts of the western US, but their impact on the ability of wells to pump groundwater is not known. Here we collate groundwater well records for the western United States and present the recorded locations, depths, and purposes of more than two million groundwater wells constructed between 1950 and 2015. We then use the well records to estimate the percentage of wells that were dry during the years 2013–2015. During the two year period, dry wells were concentrated in rural areas with high agricultural productivity, such as parts of the California Central Valley and the High Plains. Our results support anecdotal evidence that wells used for domestic purposes are more susceptible to drying than wells used for agricultural purposes throughout California’s Central Valley because the former tend to be shallower. However, this is not the case in all regions. Our findings suggest that declining groundwater levels are threatening drinking water reliability and agricultural productivity, and consequently, have key implications for both domestic and agricultural water security. Ongoing reductions to groundwater storage are drying groundwater wells in the western US, and this manifestation of water scarcity warrants innovative groundwater management transcending status quos.

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.

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)0.000
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 score0.259
Threshold uncertainty score0.408

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
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 head0.027
GPT teacher head0.257
Teacher spread0.230 · 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