Simulation of Capillary Pressure Overshoot in Snow Combining Trapping of the Wetting Phase With a Nonequilibrium Richards Equation Model
Bibliographic record
Abstract
Abstract The timing and magnitude of snowmelt discharge and subsequent runoff are controlled by both matrix and preferential flows of water through snowpacks. Matrix flow can be estimated using the Richards equation, and recently, preferential flow in snowpacks has been represented in 2D and 3D models. A challenge for representing preferential flow through porous media in 2D or 3D is capillary pressure overshoot in 1D. Soil studies have developed sophisticated and largely realistic approaches to represent capillary pressure overshoot, but it has not been addressed in snowpack water flow models. Here a 1D nonequilibrium Richards equation model is implemented with dynamic capillary pressure and is combined with a new concept of entrapment of liquid water within the pore space. This new model well represented capillary pressure overshoot, as estimated by published capillary pressure measurements in snow samples of various grain sizes under different rates of liquid water infiltration. Three model parameters were calibrated, and their impacts on model outputs were evaluated. This improvement is a substantial step toward better understanding and simulating physical processes occurring while liquid water percolates an initially dry snowpack.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".