The Hidden Hydrogeosphere: The Contribution of Deep Groundwater to the Planetary Water Cycle
Bibliographic record
Abstract
The canonical water cycle assumes that all water entering the subsurface to form groundwater eventually reenters the surface water cycle by discharge to lakes, streams, and oceans. Recent discoveries in groundwater dating have challenged that understanding. Here we introduce a new conceptual framework that includes the large volume of water that is estimated to account for 30–46% of the planet's groundwater but that is not yet incorporated in the traditional water cycle. This immense hidden hydrogeosphere has been overlooked to date largely because it is stored deeper in the crust, on long timescales ranging from tens of thousands to more than one billion years. Here we demonstrate why understanding of this deep, old groundwater is critical to society's energy, resource, and climate challenges as the deep hydrogeosphere is an important target for exploration for new resources of helium, hydrogen, and other elements critical to the green energy transition; is under investigation for geologic repositories for nuclear waste and for carbon sequestration; and is the biome for a deep subsurface biosphere estimated to account for a significant proportion of Earth's biomass. ▪ We provide a new conceptual framework for the hidden hydrogeosphere, the 30–46% of groundwater previously unrecognized in canonical water cycles. ▪ Geochemico-statistical modeling groundwater age distributions allows deconvolution of timing, rates, and magnitudes of key crustal processes. ▪ Understanding and modeling this deep, old groundwater are critical to addressing society's energy, resource, and climate challenges.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".