Revisiting water retention curves for simple hydrological modelling of peat
Bibliographic record
Abstract
Accurate modelling of peat water contents (θ) is critical for wetland studies. We modified the Campbell and Van Genuchten soil water retention curves (SWRCs) by replacing their empirical parameters with measurable properties. Combining the water table depth (dWT) into SWRCs, we derived formulae for calculating volumetric θ from dWT, coded in a simple model to test our hypotheses that dWT is a reliable predictor of θ for peat of low and high water holding capacity at near-saturation. We compared our simulations with time-domain reflectometry θ measurements at Mer Bleue bog (Ontario, Canada) and the Western Peatland fen (Alberta, Canada). Constraining Campbell SWRC at extreme drying and waterlogging rather than wilting point and field capacity produced superior results. The Van Genuchten SWRC was approximated by hyperbolic and inverse hyperbolic segments. When simplified, its performance reconciles with that of the modified Campbell SWRC. Overall, our formulae performed well with generalized peat parameters.
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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 | 0.002 | 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) | 0.002 | 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 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".