Évaluation de l'impact du vent et des manoeuvres hydrauliques sur le calcul des apports naturels par bilan hydrique pour un réservoir hydroélectrique
Bibliographic record
Abstract
RESUME Le debit d’apport naturel qui alimente un reservoir hydroelectrique est une donnee tres importante pour un gestionnaire de ressources hydriques. En effet, Hydro-Quebec utilise les apports naturels historiques pour effectuer une prevision journaliere de la quantite d’eau qui sera recue a chacun des reservoirs de son parc hydroelectrique. Cette prevision permet d’etablir des regles de gestion des centrales hydroelectriques dans le but d’optimiser la production sans toutefois compromettre la securite des ouvrages. Afin d’obtenir une prevision d’apport naturel precise, les apports naturels des jours precedents doivent etre precis. Cependant, il peut s’averer tres difficile de mesurer adequatement ces apports naturels a cause des nombreux ruisseaux et rivieres qui alimentent les reservoirs. Par consequent, Hydro-Quebec utilise une methode indirecte pour le calculer. Cette methode indirecte consiste a evaluer l’equation du bilan hydrique. Or, cette equation n’est pas a l’abri des erreurs et des incertitudes. Un des intrants de cette equation est le niveau d’eau mesure par un ou plusieurs limnimetres. Plusieurs sources d’erreurs, dont l’effet du vent et des manoeuvres hydrauliques, peuvent affecter la lecture de ces instruments. Les fluctuations du niveau d’eau causees par ces effets se repercutent jusque dans l’equation de bilan hydrique faisant en sorte que le signal d’apport naturel devient bruite et entache d’erreurs.----------ABSTRACT Natural inflow is an important data for a water resource manager. In fact, Hydro-Quebec uses historical natural inflow data to perform a daily prediction of the amount of water that will be received in each of its hydroelectric reservoirs. This prediction allows the establishment of reservoir operating rules in order to optimize hydropower without compromising the safety of hydraulic structures. To obtain an accurate prediction, it follows that the system’s input needs to be very well known. However, it can be very difficult to accurately measure the natural supply of a set of regulated reservoirs. Therefore, Hydro-Quebec uses an indirect method of calculation. This method consists of evaluating the reservoir’s inflow using the water balance equation. Yet, this equation is not immune to errors and uncertainties. Water level measurement is an important input in order to compute the water balance equation. However, several sources of uncertainty including the effect of wind and hydraulic maneuvers can affect the readings of limnimetric gages. Fluctuations in water level caused by these effects carry over in the water balance equation. Consequently, natural inflow’s signal may become noisy and affected by external errors.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".