Comment on egusphere-2023-2391
Bibliographic record
Abstract
Abstract. In the Arctic, the thawing of permafrost affects how catchments store and release water. However, the effects of thawing on the hydrological response remain poorly documented. In addition, it remains unclear how the effects of a thawing landscape will propagate through nested catchments. Here we investigate 10 nested catchments within the Yukon basin (Alaska and Canada) to study how permafrost thaw impacts catchments’ streamflow seasonality and storage-discharge relationships, and how these effects cascade through the nested catchments, from headwaters to downstream. Our results indicate that upstream catchments, characterized by continuous permafrost, have stronger streamflow seasonality and that these catchments also exhibit the most nonlinear storage-discharge relationships. Larger catchments downstream sustain year-round streamflow with baseflow continuing during winter. Since the 1950s flow regimes have become increasingly seasonal in the upstream catchments, with an earlier and more abrupt freshet, whereas further downstream flow seasonality has remained stable. Across the Yukon, storage-discharge relationships for 9 out of 10 sub-catchments have become increasingly nonlinear over time, with the biggest change occurring in the largest downstream catchments. In smaller catchments, each season has distinct recession characteristics, but those seasonal differences are not apparent further downstream. Upstream catchments are strongly influenced by localized change, whereas downstream catchments receive the effects of many different localized upstream impacts, making it difficult to detect a singular cause of change. Seasonal and long-term shifts in storage-discharge relationships are typically not accounted for by hydrological models and make accurate streamflow predictions more difficult. These shifts highlight how the changing landscape of the Arctic has far-reaching hydrological consequences.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.022 | 0.011 |
| Insufficient payload (model declined to judge) | 0.333 | 0.219 |
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".