Low flow frequency study for Newfoundland and Labrador
Bibliographic record
Abstract
The objectives of this study were to quantify the characteristics of low flows in rivers of the province of Newfoundland and Labrador, and to develop equations which could be used to estimate the magnitude, frequency, duration, and spells of low flow events. These different aspects of low flows were analyzed by applying methods of flow frequency, flow duration, and flow spell analysis, respectively. Sixty hydrometric stations in the Island of Newfoundland which have more than 20 years of complete data were selected for the current low flow study. Because of the sparseness and shortness of hydrometric data in Labrador, sites with more than 15 years of data were chosen with a total of 12 stations. An L-moment based approach was applied for regional frequency analysis of annual minimum 1-day and 7-day flows for two separate homogeneous regions, Island of Newfoundland, and Labrador and it yielded prediction equations for low flows of different durations and return periods. The performance of these regional models was verified using new sets of data, and showed reliable results. Therefore, one can use these prediction models for ungauged sites in Newfoundland and Labrador. To perform regional flow duration analysis, physiographic parameters of the regions under study were regressed against quantiles of flow duration curves obtained for each hydrometric station to produce a regional model for predicting flow duration curves at any ungauged sites. Regional model of flow durations were validated successfully using a new set of data, and the results were promising. Different hydrological methodologies were applied to define flow spells for rivers in Newfoundland and Labrador, and regional models were defined to predict the annual maximum flow spell variables in Newfoundland and Labrador.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".