78. Spatial and Temporal Extension of Large Basin Hydrometeorological Records Using a Distributed Modelling Approach
Bibliographic record
Abstract
The use of simulation models to analyse impacts of water management decisions for large river basins is constrained by lack of available streamflow and meteorological records of adequate duration, quality, and spatial distribution. This paper describes an effort to extend the limited meteorological and hydrometric records for the Peace River basin, an area encompassing nearly 300,000 km2 in western Canada. For temperature and precipitation, continuous spatial and temporal datasets were developed for 1909–1997 using a combination of surface observations, coarse mesh upper air data, and a mesoscale boundary layer model incorporating terrain effects. An analogue technique was used for the period prior to the availability of upper air data. A distributed hydrological model “WATFLOOD/SPL” with parameterization based on land cover Grouped Response Units (GRUs) was applied to the basin. The model is an effective tool for estimating streamflows from ungauged areas and for running long-term water management simulations,
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".