Implementing and evaluating a surface-subsurface flow and reactive solute transport model at the hillslope scale
Bibliographic record
Abstract
Pesticide use in agricultural watersheds leads to an important surface and subsurface water contamination in France.\nAwaiting a deep evolution of agricultural practices and a sustained decrease in pesticide use, it is of interest to limit\ntransfers form agricultural fields to rivers. A deepen knowledge of processes at stake and their potential interactions is\nmade possible with large field databases, or with physically-based modeling. Physically-based models are built on\nmechanistic equations and are able to represent the processes and the physics observed on the field if the system is well\ndescribed. Integrated surface and subsurface hydrologic models (ISSHM) are complex models taking into account the\nmajor water pathways and their interctions. Two ISSMH intercomparison studies from Maxwell et al. (2014) and Kollet\net al. (2017) show that models such as CATHY (Camporese et al., 2010), HydroGeo-Sphere (Brunner et al., 2012), and\nParflow (Kollet 2006) share many common features. Their behaviours in simulation on virtual and real hillslope are\ncoherent. However, they de not use the same surface-subsurface coupling strategies and include solute transport with various complexity levels. The coupling strategy of CATHY is based on the switching boundary conditions regarding to the situation of each surface cell at each time step. It has been proved to be very efficient and able to correctly represent water flow interactions between surface and subsurface (Sulis et al., 2010 ans Guay et al., 2013). \nRecently, reactive solute transport has been implemented in the CATHY model (Weill et al., 2011 and Gatel et al., 2017submitted). In the present work, the surface-subsurface switching procedure for solutes is improved in order to achieve a better mass conservation, and a mixing module is implemented to represent the solute mobilisation from the top soil to surface runoff. The new coupled model named CATHY-Pesticide is evaluated for an intense rain event on an experimental vineyard hillslope.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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 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".