Application of a reactive transport processes module for a coupled (groundwater/surface water) physically based model on a vineyard hillslope (Beaujolais, France)
Bibliographic record
Abstract
In the context of the European Water Framework Directive (WFD, 2000/60/EC), which aims to achieve a good ecological and chemical status for all natural aquatic environments, it is necessary to better quantifying pesticide transfers in agricultural watersheds. Modeling is a relevant tool to study the processes occuring in the fate of pesticides, and identifying sound managing solutions to water contamination. Physically-based and spatially distributed models are particularly useful to represent in detail processes and interactions between the soil surface and subsurface. In particular, they can help to assess the role of landscape elements such as vegetative buffer strips, ditches, ... . The present study aims to test a recently added reactive transport to the coupled surface water/groundwater 3D model CATHY, in order to represent pesticide transfers at the watershed scale. Contaminant reactions implemented are linear adsorption and degradation (first order kinetics). The model has been successfully validated on laboratory data and submitted to a sensitivity analysis as a further step of validation. In this study, we tested the model on field conditions, simulating a 150 m x 40 m hillslope in the Morcille catchment (Beaujolais, France). The hillslope is predominantly covered with a chemically weeded vineyard crossed by 4 very shallow ditches gathering the runoff towards a concrete channel. The flow coming from the vineyard plot in then conducted on a 25 m long vegetative buffer strip. The site is instrumented with piezometers, lysimeters, flow and solute concentration measurement devices. Real field conditions makes the model's application more difficult because of the complexity in representing the interactive processes in a large domain, combined to uncertainty on input parameters that is important in field experiments. However, such challenging modeling allows a more comprehensive understanding of solute transfers and gives some keys to evaluate the efficiency of mitigation elements of the landscape.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".