Characterizing River-Aquifer Interaction in the Hyporheic Zone Using Cross-Sectional Measurements and MODFLOW-USG
Bibliographic record
Abstract
Understanding river-aquifer interaction in the hyporheic zone is essential for overall stream ecosystem health and nutrient cycling. In this study, cross-sectional measurements of temperature and groundwater and surface water levels were conducted at two locations along the Bulkley River in northern British Columbia, Canada. River–aquifer interaction in the hyporheic zone was assessed using two methods: (1) the river and aquifer water temperatures as a tracer of heat movement and (2) the vertical hydraulic gradient across the streambed. At both locations, temperature patterns indicated a gaining system from August to early September, as groundwater temperature fluctuations were highly damped relative to river temperatures. Groundwater temperature followed river temperature fluctuations from mid-September to early October, which showed a losing system. From mid-October to November, groundwater temperature remained consistently greater than river temperature, with reduced thermal exchange during the colder season. The hydraulic gradient analysis revealed that at the Topley location, the groundwater level was greater than the river level until early October (gaining system), followed by a reversal to a losing system by November. Similarly, at the McKilligan location, the groundwater level remained greater than the river level from August to September 21 (gaining system) and ultimately changed to a losing system by November. A numerical model was also developed using the MODFLOW-USG code to quantify the River–aquifer interaction. The streambed hydraulic conductivity was 0.0047 m/day at the Topley location and 0.0216 m/day at the McKilligan location, as measured using the seepage meter method. The interaction components include the recharge from the river to the aquifer (Isw), which was 33.4 m³/d (0.06 m³/m²/d), and groundwater drainage (Dg), which was 72.4 m³/d (0.13 m³/m²/d) within the McKilligan location, while I sw was 4.5 m³/d (0.003 m³/m²/d) and D g was 9.04 m³/d (0.005 m³/m²/d) within the Topley location. Simulation findings demonstrate significant spatial variability in the interaction components, which is strongly controlled by the streambed hydraulic conductivity. This study can lead to enhanced understanding and characterization of river–aquifer interaction in the hyporheic zone by considering three methods. The developed numerical method could also be used to evaluate potential future scenarios.
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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".