Modeling Groundwater-Soil-Plant-Atmosphere Exchanges in Fractured Porous Media
Bibliographic record
Abstract
Models for the soil-plant-atmosphere system, especially large scale models, frequently ignore interactions with underlying groundwater, and ignore fractures or macropores which may strongly influence the system response. Unsaturated fractured porous media can exhibit a range of behavior, depending on both the characteristics of the porous matrix and the fractures, and the climatic conditions to which they are subject. A dominant characteristic in surficial fractured porous geological formations is the vertical distribution of fractures in the near surface region. This paper explores how these different modes of behavior operate at various field sites and under different climatic conditions. Two diverse fractured porous settings are considered: fractured glacial till of the semi-arid, seasonally frozen Canadian prairies and the Chalk in humid, temperate south east England. Interpretations from hypothetical hillslope scale model simulations provide insights into how the properties of the material, and in particular the distribution of the fractures and the matrix hydraulic conductivity, affect the spatial distribution of evapotranspiration and the timing, magnitude and spatial distribution of groundwater recharge. Such behavior is not captured in conventional large scale models which consider only a shallow, one-dimensional soil moisture balance.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".