A century of landscape-level changes in the Bow watershed, Alberta, Canada, and implications for flood management
Bibliographic record
Abstract
This study used a comparison of one hundred and forty-eight historical (1888-1913) and current (2008-2014) oblique photographs from thirty-two stations to identify land cover changes that have occurred in portions of the Bow and Elbow valleys as well as surrounding Kananaskis Country region. Implications of these changes for flooding and flood management were explored. Forest cover was found to have drastically increased over the past century, particularly in the Bow valley, as did areas of direct human development. In the same time period, grasslands increased in the Elbow valley but decreased in the Bow, while regenerating areas decreased uniformly throughout both valleys. An analysis of pre (2008)-and-post (2014) flood conditions demonstrated no change in coniferous forest cover in both valleys over the 6-year period, but uncovered a decline of 20% in the Elbow and 3% in the Bow in the broadleaf/mixedwood category. The Elbow’s channel zone was larger in 2014 compared to 2008, whereas the extent of the Bow’s channel zone remained constant. However, both the Bow and Elbow’s bare exposed bars increased substantially, most likely as a result of the 2013 flood. The major source of water flows that contributed to the 2013 flood event originated in high elevation rock and scree areas, which, unlike floodplains, are elements of the watershed that cannot be manipulated over time. It is now recognized that forest cover should act as a buffer to floods. Nevertheless, the 2013 flood event occurred despite the massive buffering effect of a huge increase in older forest stands across the study area. The final discussion includes recommendations for improving flood management in the area.
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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 | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".