Renewed thinking on groundwater age
Bibliographic record
Abstract
Groundwater age and mean residence times have been invoked as measures of groundwater sustainability, with the idea that old or "fossil" groundwater is non-renewable. This idea appears to come from the link between groundwater age and background recharge rates, which are also of questionable use in assessing the sustainability of groundwater withdrawals. The use of groundwater age to assess renewability is further complicated by its relationship with flow system geometry. Young groundwaters near recharge areas are not inherently more renewable than older groundwaters down gradient. Similarly, there is no reason to preferentially use groundwater from smaller aquifers, which will have smaller mean residence times than larger aquifers for the same recharge rate. In some cases, groundwater ages may provide some information where groundwater recharge rates were much higher in the past and systems are no longer being recharged. However, there are few examples where the relationship between depletion and changes in recharge over long time periods has been rigorously explored. Groundwater age measurements can provide insights into the functioning of groundwater flow systems and calibration targets for numerical models and we advocate for their continued use, but they are not a metric of sustainable development. Simple metrics to assess groundwater sustainability remain elusive and a more holistic approach is warranted to maintain water levels and environmental flows.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.015 |
| Scholarly communication | 0.005 | 0.024 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".