Extension of the River Water Quality Model No. 1 with the fate of pesticides
Bibliographic record
Abstract
The existing River Water Quality Model No. 1 (RWQM1) was extended with processes determining the fate of non-volatile pesticides in the water phase and sediments. The exchange of pesticides between the water column and the sediment is described by three transport processes: diffusion, sedimentation and resuspension. Burial of sediments is also included. The modified model was used to simulate the concentrations of diuron and chloridazon in the river Nil. A good agreement was found between the simulated pesticide concentrations and measured values resulting from a four-month intensive monitoring campaign. The simulation results indicate that pesticide concentrations in the bulk water are not sensitive to the selected biochemical model parameters. It seems that these concentrations are mainly determined by the imposed upstream concentrations, run-off and direct losses. The high concentrations in the bulk water were not observed in the sediment pore water due to a limited exchange between the water column and the sediment. According to a sensitivity analysis, the observed pesticide concentrations are highly sensitive to the diffusion and sorption coefficients. Therefore, model users should determine these parameters with accuracy in order to reduce the degree of uncertainty in their results.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".