A Continuous Dye Injection System for Estimating Discharge in Snow-choked Streams
Bibliographic record
Abstract
Abstract A simple method is presented which demonstrates the use of continuously injected Rhodamine WT dye to provide automated around-the-clock estimates of flow during the spring breakup. Dye of a known concentration is injected at a constant rate upstream from a sampling point, and the dilution of the dye in the sampled downstream water is a measure of discharge. Field trials conducted in and around Inuvik, Northwest Territories in two small snow-choked streams during spring breakup of 1995 to 1999 suggest that some dye is adsorbed to suspended sediment in the stream channel, resulting in an overestimate of discharge. However, there is still a strong linear relationship between the discharge as estimated by the dye method and that determined by conventional current metering. Correcting the dye values by a linear regression equation line results in a reasonable estimate of streamflow. This method's most promising application is in the monitoring of small basins where much of the annual discharge occurs during the spring melt. Given the occurrence of rapid changes in discharge in these basins due to both diurnal variations in snowmelt and changing runoff source area, and the excessive manpower required to carry out a sufficient number of current meterings needed to properly observe this changing discharge, the dye dilution method often provides a more accurate estimate of discharge.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".