Numerically quantifying the relative importance of topography and buoyancy in driving groundwater flow
Bibliographic record
Abstract
Both topography and buoyancy can drive groundwater flow;however,the interactions between them are still poorly understood.In this paper,the authors conduct numerical simulations of variable-density fluid flow and heat transport to quantify their relative importance.The finite element modeling experiments on a 2-D conceptual model reveal that the pattern of groundwater flow depends largely upon the relative magnitude of the flow rate due to topography alone and the flow rate due to buoyancy alone.When fluid velocity due to topography is greater than that due to buoyancy at large water table gradients,topography-driven 'forced convection' overwhelms buoyancy-driven 'free convection'.When flow velocity due to buoyancy is greater than that due to topography at small water table gradients,mixed free and forced convection takes place.In this case,free convection becomes dominant,but topography-driven flow still plays an important role since it pushes the free convection cells to migrate laterally in the downhill direction.Consequently,hydrothermal fluid flow remains changing periodically with time and no steady state can be reached.The presence of a low-permeability layer near the surface helps eliminate the topography effect on the underlying free convection.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".