Upland Hillslope Groundwater Subsidy Affects Low‐Flow Storage–Discharge Relationship
Bibliographic record
Abstract
Abstract Large‐scale cross‐site scientific synthesis on low‐flow storage–discharge relation can promote developing transferable hypotheses on the interactions among critical zone attributes and on how such interactions affect catchments’ water vulnerabilities. This study leverages cross‐site empirical and theoretical analyses and develops a similarity index, based on the interactions among critical zone attributes, to help determine the less‐explored influence of upland hillslope groundwater subsidy on storage–discharge relation. We show that an increase in the relative extent of upland hillslope groundwater subsidy to low‐flow discharge, occurring through deep slow low‐moving (e.g., bedrock) storage unit, leads to (a) an increase in the nonlinearity of low‐flow discharge sensitivity to storage (β1) and (b) an increase in the convexity of low‐flow storage–discharge relation. Our findings also raise new hypotheses on the applicability of Boussinesq‐based hydraulic groundwater theory at low‐flow condition. Empirical results show that in a portion of our study catchments, particularly in those with a relatively small extent of upland hillslope groundwater subsidy, the theory’s proposed range of nonlinearity sufficiently explains the nonlinearity of low‐flow storage–discharge relation. However, in catchments with a strong influence of upland hillslope groundwater subsidy through deep slow‐moving storage unit, the current state of hydraulic groundwater theory, using one single (non)linear representative storage unit, may not be sufficient to explain the large nonlinearity and convexity of low‐flow storage–discharge relation (or the long tail of hydrograph late recession). Considering β1 informs the low‐flow vulnerability of catchments, the findings of this study deepen and generalize our understanding of where low‐flow discharge is vulnerable to storage’s change.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".