Comparison of two modeling approaches for groundwater–surface water interactions
Bibliographic record
Abstract
Abstract An assessment of interactions between groundwater and surface water was carried out by applying two different modeling approaches to a small‐scale study area in the municipality of Havelock, Quebec. The first approach involved a commonly used sequential procedure that consists in determining the daily recharge rate using a quasi 2D infiltration model (HELP), applied in the next step as an imposed flux to a 3D finite‐element groundwater flow model. The flow model was calibrated under steady‐state and transient conditions against measured water levels. The second approach was based on a recently developed physically based, 3D fully coupled groundwater–surface water flow model (CATHY) applied to the entire flow domain in an integrated manner. Implementation, calibration, and results of the simulations for both approaches are presented and discussed. For equal annual precipitation (1038 mm/y) and evapotranspiration (556 mm/y), the second approach computed a recharge rate of 233 mm/y (8.9% higher than the first approach) and a net upward flow from the fractured aquifer (the first approach predicted a net downward flow to the rock). The simulated annual discharge was similar for the two approaches (9.6% difference). Both approaches were found to be useful in understanding the interactions between groundwater and surface water, although limitations are apparent in the sequential procedure's inability to account for surface–subsurface feedbacks, for instance near stream reaches where groundwater discharge is prevalent. The decoupled, two‐model approach provides disaggregated surface, vadose, and aquifer flows, and a simple aperçu at the different components of total discharge. The fully coupled model accounts for continuous water exchanges between the land surface, subsurface, and stream channel in a more complex manner, and produces a better match against observed data. Copyright © 2012 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 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 teacher head, 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".