Hydrological modeling in swelling/shrinking peat soils
Bibliographic record
Abstract
Peatlands respond to natural hydrologic cycles of precipitation and evapotranspiration with reversible deformations due to variations of water content in both the unsaturated and saturated zone. This phenomenon results in short‐term vertical displacements of the soil surface that superimpose to the irreversible long‐term subsidence naturally occurring in drained cropped peatlands because of bio‐oxidation of the organic matter. These processes cause changes in the peat structure, in particular, soil density and void ratio. The consequential changes in the hydrological parameters need to be incorporated in water flow dynamical models. In this paper, we present a new constitutive relationship for the soil shrinkage characteristic (SSC) in peats by describing the variation of porosity with moisture content. This model, based on simple physical considerations, is valid for both anisotropic and isotropic three‐dimensional peat deformations. The capability of the proposed SSC to accurately describe the deformation dynamics has been assessed by comparison against a set of laboratory experimental results recently published. The constitutive relationship has been implemented into a Richards' equation–based numerical code and applied for the simulation of the peat soil dynamics as observed in a peatland south of the Venice Lagoon, Italy, in an ad hoc field experiment where the relevant parameters are continuously measured. The modeling results match well a large set of field data encompassing a period of more than 50 days and demonstrate that the proposed approach allows for a reliable reproduction of the soil vertical displacement dynamics as well as the hydrological behavior in terms of, for example, water flow, moisture content, and suction.
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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 | 0.000 |
| 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) | 0.000 | 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".