Plausibility Criteria for GRACE‐Derived Groundwater Storage Changes From Aquifers Globally
Bibliographic record
Abstract
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).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.101 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".