How Do Fractures Influence Hyporheic Exchange in Sedimentary Rock Riverbeds?
Bibliographic record
Abstract
Abstract Bedrock rivers represent a hydrogeological environment in which surface water flows along an exposed bedrock surface. Studies of hyporheic exchange have exclusively involved rivers composed of unconsolidated fluvial sediments, leaving a critical knowledge gap. This study evaluates the conditions that could support bedform‐scale hyporheic exchange within a fractured sedimentary bedrock river based on field data collected near Guelph, Canada. Hyporheic exchange at the bedform‐scale was evaluated by numerically modeling the migration of a conservative solute tracer through a bedrock riverbed within a two‐dimensional vertical cross‐section along the flow direction. A stochastic discrete fracture‐matrix framework was developed to represent measured subsurface fractured bedrock properties, producing a probabilistic distribution of potential hyporheic exchange pathways. Flow and transport model results indicate that: (a) bedform‐scale hyporheic exchange within a bedrock river exists with high fluid flow velocities in fractures, yet long solute residence times due to diffusion across the fracture‐matrix boundary; (b) the coincidence of fractures and hydrodynamic head gradients across the riverbed controls the spatial extent of bedform‐scale hyporheic exchange; and (c) the potential variability in hyporheic exchange residence time is large (i.e., tens of years) due to the inherent variability in facture network properties. Our field‐based numerical study indicates that the average (median) residence time may not be a good proxy for the potential natural attenuation capacity of a fractured sedimentary bedrock riverbed and that hyporheic exchange has the potential to emplace surface water contaminants within the fractured porous rock matrix that could become a long‐term source of trace contaminants.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".