Quantifying hyporheic exchange in a tidal river using temperature time series
Bibliographic record
Abstract
An investigation into groundwater‐surface water interaction (GSWI) beneath a large tidally influenced river was conducted to determine the effect of tides on the development of a hyporheic zone (HZ) and to quantify mixing of river water and groundwater. Temperature measurements, coupled with independent hydraulic head measurements, were used to detect groundwater flow within the riverbed. GWSI under tidal forcing produced a 1 m deep HZ. Time‐averaged riverbed temperature profiles displayed a distinct compressed convex pattern: clear evidence of net groundwater discharge. However, the instantaneous time series data indicate that riverbed temperatures were affected by tidal forcing to a depth of 1 m. Heat transport modeling revealed that instantaneous velocities within the shallow sediments of the riverbed are rather high, creating a zone of vigorous exchange during either a flooding or ebbing tide. Furthermore, the magnitude of the tidal pressure gradient was found to be significantly greater than the pressure gradient expected across 0.8 m high dunes, evidence that bed‐form‐driven exchange under these conditions, and this scale of observation, did not contribute to the development of the HZ. Conditions for exchange induced by shear and current bed form are favorable during ebbing tidal conditions only; flow paths are therefore limited in depth. Exchange flow paths in an estuary setting are complex; they are limited in duration and space and dominated by tidal pumping.
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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 | 0.000 |
| 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) | 0.000 | 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".