Hydrological resilience of a Canadian Rockies headwaters basin subject to changing climate, extreme weather, and forest management
Bibliographic record
Abstract
Abstract Marmot Creek Research Basin in the Canadian Rockies has been the site of intensive streamflow, groundwater, snow accumulation, precipitation, and air temperature observations at multiple elevations. The basin was instrumented in 1962, subjected to forestry experiments in the mid‐1970s, and experienced extreme flooding in 2013. Climate change, forest cover change, and recent extreme weather make the basin an ideal laboratory for studying hydrological resilience. Observations show increases in low elevation air temperature, multiple day and spring precipitation, interannual variability of precipitation, and high elevation groundwater levels. Observations also show decreases in peak seasonal snow accumulation and low elevation groundwater levels. Despite these substantial hydrometeorological and groundwater changes, streamflow volume, timing of peak, and magnitude of the peak are not changing. Streamflow volumes are also insensitive to forest cover changes and teleconnections. The June 2013 flood was unprecedented in the period of record, and the basin significantly moderated the hydrological response to the extreme precipitation; the 2013 storm precipitation depth was 65% greater than the next highest storm total over 51 years; however, the 2013 peak streamflow was only 32% greater than the next highest peak flow recorded. The hydrology of Marmot Creek Research Basin displays remarkable resilience to changing climate, extreme weather, and forest cover change. Copyright © 2015 John Wiley & Sons, Ltd.
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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 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".