Characterizing Groundwater Discharge from a Cobble Armored Streambed, Alder Creek, Ontario, Canada
Bibliographic record
Abstract
Quantifying flow across the groundwater-surface water interface (GWSWIn) is necessary for a detailed understanding of the hydrological connectivity between groundwater and surface water, and for the effective management of water resources in general. Fluxes across the GWSWIn can be used to monitor both water transport and the movement of contaminant mass, which in turn can be used to estimate mass discharge or loading. These estimates are of great value for the assessment of risk and the preservation of human and ecosystem health. Numerous techniques have been used to measure water movement across the GWSWIn, with new, innovative techniques emerging to extend the opportunities for GWSWIn research. This study conducted a detailed survey of two stream reaches of Alder Creek (Ontario, Canada): a meander with cobbles 1-15 cm in diameter lining the streambed and a straight channel with minimal cobbles visibly present on the sediment surface. The reaches were surveyed to determine the velocities of water crossing the GWSWIn for the purpose of assessing the mechanics of flow in the shallow streambed. The Streambed Point Velocity Probe (SBPVP) was used to measure seepage velocities without reference to Darcy’s Law calculations (i.e. ‘direct’ measurements via small-scale tracer testing). Measurements were able to be made between the cobbles (0-10 cm below the streambed surface) and were later compared to seepage velocities estimated from temperature-depth profiles (10-50 cm below the streambed surface). When compared, the SBPVP results were found to be 2 orders of magnitude larger than the temperature-depth profile values. This observed difference was attributed to a combination of factors, including the depth of measurement, seasonal variations, shallow horizontal flow, and the presence of flow-obstructing cobbles on the streambed. Our analysis indicates that the cobbles played a significant role in influencing flow dynamics of the shallow streambed, notably directing flow to the limited area between the cobbles, thereby increasing shallow groundwater velocity. By correcting for the cobble density in the SBPVP derived measurements, and accounting for the fraction of flow that was measured to occur vertically from the bed to the channel (a weighted velocity average) the SBPVP-derived velocity values were comparable to those derived from the temperature-depth profile velocities. Two-dimensional modeling of flow in the streambed, in section, recreated the measured patterns of multidirectional flow and provided visualizations of the flow redirection caused by the presence of the cobbles. Utilizing the measured vertical velocity values at the meander site, interpolated velocity values between the measurement points, and the distribution of nitrate in the shallow groundwater beneath the channel, a mass flux estimate of nitrate was calculated to be about 8 kg/day NO3- . This loading partially explained a small increase in stream channel concentrations of nitrate along the reach, suggesting that nitrate entering the stream from the banks may be an important contributor in addition to groundwater discharge from below. The findings from this study demonstrate the application of modern methods for obtaining detailed information to characterize GWSW interactions in armored streambeds, with beneficial insights for the assessment of risk due to contaminant loadings.
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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 | 0.002 | 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".