Improvement of the solute transfer in a conceptual unsaturated zone scheme: a case study of the Seine River basin
Bibliographic record
Abstract
Abstract For predicting the evolution of solute concentrations in groundwater and testing the impact of remediation policies, a coupling between the agronomical model STICS and the hydrogeological model MODCOU was implemented. When applied to the Seine River basin, this model accurately represents the temporal evolution of average nitrate concentrations in the aquifer, but with large local errors. We propose an improvement to the simple unsaturated zone (UZ) scheme NonsatSW used in STICS–MODCOU. The modifications are based on a comparison with the mechanistic model Metis considered as a reference as it solves Richards' equation. A more realistic saturation profile and a varying percolation rate are integrated in NonsatSW. This new model, named NonsatVG, is assessed by comparing it with NonsatSW and Metis. In an ideal case, NonsatVG generates a solute transfer and a dispersion closer to that of Metis than of NonsatSW. In real cases, without additional calibration, NonsatVG and Metis simulate better the average transfer velocities of the observed nitrate profiles. Furthermore, modifications in NonsatVG give a direct relationship between the depth of the water table and the saturation profile. We obtain, therefore, as in Metis, an evolution of the solute transfer velocity depending on the piezometric level. These dynamics are not simulated in NonsatSW. Despite a modified water transfer through the UZ, NonsatVG is also as valid as NonsatSW in the modelling of water transfer to the saturated zone. Finally, an application to the Seine basin shows that solute transfer velocities are lower with NonsatVG than with NonsatSW, but are in better agreement with literature. Copyright © 2010 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".