Unified Solution for Infiltration and Drainage with Hysteresis Theory and Field Test
Bibliographic record
Abstract
Hysteresis has been found in both the hydraulic conductivity, K , vs. pressure head, ψ, relationship, and the soil water content, θ, vs. ψ relationship. This limits the application of a unified solution for infiltration and drainage. A Haines' Jump model of hysteresis is proposed and combined with the Broadbridge and White form of K (θ) and the diffusivity, D , relationship, D (θ). This allows a unified analytical solution for infiltration and drainage. This solution accounts for hysteresis by allowing the inverse macroscopic capillary length scale, α, to be hysteretic. A method of a priori estimating the hysteretic nature of α is proposed and tested. The hysteretic change in α can be estimated from other θ(ψ) hysteresis models and then used in combination with the Broadbridge and White hydraulic functions. The predicted hysteresis in α was similar to that obtained from inverse procedures. The unified solution was applied to field‐measured soil water storage during infiltration and drainage. Neglecting hysteresis resulted in poor prediction of water storage during drainage based on hydraulic parameters estimated from infiltration. This was especially true for drainage with high initial water content. Incorporating the proposed hysteresis model resulted in prediction error less than measurement error. In addition, a single unified inverse procedure for estimating hydraulic parameters from combined infiltration and drainage measurements can now be developed.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".