Application of a physically-based numerical model of surface and subsurface water flow and solute transport
Bibliographic record
Abstract
A fully-integrated numerical model is presented which considers the flow of water and transport of multiple solutes on the two-dimensional land surface and in the three-dimensional, dual-continua subsurface, under variably-saturated conditions. Linkage between the various continua is through first-order, physically based flux relationships or through pressure head and concentration continuity assumptions. Full coupling of flow and transport is achieved by assembling and solving one system of discrete algebraic equations such that water and solute fluxes between continua are determined simultaneously. To achieve a high degree of computational efficiency, robust and efficient discretization and solution techniques are utilized. The numerical model was tested by simulating a controlled field experiment described by Abdul & Gillham (1989) involving coupled surface-subsurface flow and tracer transport in a small subcatchment at CFB Bordon, Ontario. Observed surface discharge volumes and timings arising from the application of artificial rainfall containing a tracer were simulated with reasonable accuracy using published or measured parameter values and minimal calibration. The observed dynamic response is shown to be a nonlinear function of surface and subsurface flow processes that are affected by subsurface permeability, surface roughness, topography, and initial conditions. Excess rainfall and groundwater seepage that flows overland initially, generate surface ponding within microtopographic depressions, including those located in the initially dry stream channel. The ponded surface water forms an internal, transient constraint on the porous medium pressure head near the land surface which is not reflected in solutions making use of traditional seepage face algorithms. The dominant streamflow mechanism deduced from the simulations is infiltration excess over an increasing contributing area, with the contributing area controlled by rapid response of the capillary fringe. Water originating above the initial water table overshadows groundwater contributions in this case.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".