Hydrologically Based Environmental Flow Methods Applied to Rivers in the Maritime Provinces (Canada)
Bibliographic record
Abstract
Abstract The demand for water withdrawal continues to increase worldwide. These water withdrawals from rivers can affect fish habitat and aquatic life. As such, environmental flow assessment methods are used in order to protect rivers against excessive water withdrawals. The concept of environmental flow relates to the quantity of water required in rivers to sustain an acceptable level of living conditions for aquatic biota at various phases of their development. For many agencies, environmental flow methods are essential in environmental impact assessments and in the protection of important fisheries resources. The present study deals with the evaluation of hydrologically based environmental flow methods within the Maritime Province of Canada. In total, six hydrologically based environmental flow methods were compared using data from 52 hydrometric stations across the region. Some methods provided adequate environmental flow protection (e.g. 25% mean annual flow and Q 50 flow duration method); however, other methods did not provide adequate flow protection (e.g. Q 90 flow duration method and 7Q10 and 7Q2 low‐flow frequency). The 70% Q 50 method provided adequate flow protection only under good baseflow conditions and should be applied with extreme caution. The present study shows the importance of the hydrologic flow regime, particularly as it pertains to the baseflow component, as a significant determinant in the level of instream flow protection. © 2014 Her Majesty the Queen in Right of Canada. River Research and Applications © 2014 John Wiley & Sons, Ltd.
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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 | 0.001 |
| 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".