Spatially coherent regional changes in seasonal extreme streamflow events in the United States and Canada since 1950
Bibliographic record
Abstract
Complex hydroclimate in the United States and Canada has limited identification of possible ongoing changes in streamflow. We address this challenge by classifying 541 stations in the United States and Canada into 15 "hydro-regions," each with similar seasonal streamflow characteristics. Analysis of seasonal streamflow records at these stations from 1910 to present indicates regionally coherent changes in the frequency of extreme high- and low-flow events. Where changes are significant, these events have, on average, doubled in frequency relative to 1950 to 1969. In hydro-regions influenced by snowmelt runoff, extreme high-flow event frequency has increased despite snowpack depletion by warming winter temperatures. In drought-prone hydro-regions of the western United States and Southeast, extreme low-flow event frequency has increased, particularly during summer and fall. The magnitude and regional consistency of these hydrologic changes warrant attention by watershed stakeholders. The hydro-region framework facilitates quantification and further analyses of these changes to extreme streamflow.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".