Detecting the Timing of Morphologic Change Using Stage-Discharge Regressions: A Case Study at Fishtrap Creek, British Columbia, Canada
Bibliographic record
Abstract
Nine submersible pressure transducers were installed at various locations in a study reach of Fishtrap Creek during the 2006 freshet. The channel morphology of the reach underwent a moderate change in 2006, due to the effects of the McLure forest fire which, in 2003, killed all of the riparian vegetation in the study reach and burned about 62% of the Fishtrap Creek watershed. By examining the changes in the rating relations between the water stage recorded by the pressure transducers and the discharge measured at a Water Survey of Canada gauging station located just downstream of the study reach, we were able to determine the timing of morphologic changes in the stream over the course of the freshet. Shifts in the rating curve were identified by first graphically analysing the stage-discharge relations, and then constructing stage discharge regressions for that part of the record for which the rating relation appeared to be stable. The residuals associated with the calculated rating equations were then computed for the entire period of record, and used to assess the temporal pattern of changes in the rating relation. The analysis shows that the largest changes in the rating relation occurred in the vicinity of the largest morphologic changes (as determined by analysis of repeated cross-sectional surveys) and that, in areas where the morphology was nearly stable, the rating relation remained relatively stable. The sensitivity of the rating relations to changes in the channel morphology suggests that deployment of submersible pressure transducers may be a suitable and cost-effective means for monitoring channel stability near existing gauging stations or stable control cross-sections where the rating relation is unlikely to change.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".