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Record W4416409888 · doi:10.1029/2025gl118580

Plausibility Criteria for GRACE‐Derived Groundwater Storage Changes From Aquifers Globally

2025· article· en· W4416409888 on OpenAlexfundno aff
Arifin Arifin, Mohammad Shamsudduha, Agus M. Ramdhan, Ashraf Rateb, Bridget R. Scanlon, Taat Setiawan, Munib Ikhwatun Iman, Abdullah Husna, Richard G. Taylor

Bibliographic record

VenueGeophysical Research Letters · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsnot available
FundersLembaga Pengelola Dana PendidikanCanadian Institute for Advanced Research
KeywordsAquiferGroundwaterHydrology (agriculture)ResidualStructural basinGravimetryWater storageClimate changeSustainability

Abstract

fetched live from OpenAlex

Abstract Monitoring changes in groundwater storage (ΔGWS) is critical to assess sustainability of groundwater use under climate variability. Satellite gravimetry from the GRACE missions is used to infer ΔGWS by deducting changes in monitored or modeled water components from GRACE‐derived changes in total water storage (ΔTWS). As a residual parameter, ΔGWS is highly sensitive to arithmetic inconsistencies and uncertainties in both GRACE data and model‐derived inputs. Here we present a framework to evaluate the physical plausibility of GRACE‐derived ΔGWS estimates across 37 large global aquifer systems. The results show that the proportion of plausible ΔGWS estimates per realization, derived from multiple GRACE products and land surface model combinations, varies from <10% to >60%. Exclusion of implausible estimates improved correlations between ΔGWS and ΔTWS substantially ( r ≥ 0.9, p ‐value <0.05) in most aquifers (31/37) and with in situ observations in the Bengal Basin ( r = 0.8, p ‐value <0.05).

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.843
Threshold uncertainty score0.983

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 science0.0010.000
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 head0.075
GPT teacher head0.334
Teacher spread0.259 · 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 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

Citations1
Published2025
Admission routes1
Has abstractyes

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