Inferring Hillslope Groundwater Recharge Ratios From the Storage‐Discharge Relation
Bibliographic record
Abstract
Abstract Accurate observation of hillslope groundwater storage and instantaneous recharge remains difficult due to limited monitoring and the complexity of mountainous landscapes. We introduce a novel storage‐discharge method to estimate hillslope recharge and the recharge ratio—the fraction of precipitation that recharges groundwater. The method, which relies on streamflow data, is corroborated by independent measurements of water storage dynamics inside the Rivendell experimental hillslope at the Eel River Critical Zone Observatory, California, USA. We find that along‐hillslope patterns in bedrock weathering and plant‐driven storage dynamics govern the seasonal evolution of recharge ratios. Thinner weathering profiles and smaller root‐zone storage deficits near‐channel are replenished before larger ridge‐top deficits. Consequently, precipitation progressively activates groundwater from channel to divide, with an attendant increase in recharge ratios throughout the wet season. Our novel approach and process observations offer valuable insights into controls on groundwater recharge, enhancing our understanding of a critical flux in the hydrologic cycle.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".