Intégration d'un filtre de Kalman dans le modèle hydrologique HBV pour la prévision des débits
Why this work is in the frame
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Bibliographic record
Abstract
Un filtre de Kalman standard a été développé en vue de la mise à jour de certaines variables d'état de la fonction du sous-sol et de la sortie du modèle HBV. La version globale du modèle HBV, fonctionnant au pas de temps horaire, a été calée par essais et erreurs sur les bassins tunisiens des Oueds Barbara et Mellila. Le pas de temps journalier a été considéré pour évaluer la qualité de la reconstitution. Le modèle a été ensuite couplé avec le filtre en reformulant le modèle conceptuel en un système d'équations d'état dynamiques et en implémentant la procédure du filtre de Kalman. L'hydrogramme des débits horaires constitue la mesure introduite pour la correction des états. Malgré un choix suivant la littérature des erreurs sur les mesures et les états du système, ce filtre a permis de réduire nettement l'incertitude sur le débit engendré par le processus pluie—débit et la pluie d'entrée. \n \n<h2>Abstract</h2> \nA standard Kalman filter was developed with the purpose of updating certain state variables of the lower zone function and the output of the HBV model. The global version of the HBV model, functioning with an hourly time step, was calibrated by trial and error to the Tunisian basins of the Barbara and Mellila Wadis. The daily time step was considered for evaluating the quality of the data reconstitution. The model was then coupled with the Kalman filter by reformulating the conceptual model as a system of dynamic state equations and implementing the Kalman filter procedure. The hourly discharge hydrograph constitutes the introduced measurement to correct state variables. Despite a literature-driven selection of the errors on measurements and system states, this filter clearly allowed reduction of the uncertainty on discharge produced by the rainfall—runoff process and the precipitation input.
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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 | 0.011 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it