Recent Changes to the Hydrological Cycle of an Arctic basin at the Tundra-Taiga Transition
Bibliographic record
Abstract
Abstract. The impact of observed changes in climate and vegetation on the hydrology of Arctic basins is often considered to be most sensitive at the tundra-taiga transition where the region is warmest and sub-arctic vegetation is nearest. This study uses weather and land cover observations and a cold regions hydrological model to investigate historical changes in modelled hydrological processes driving the streamflow response of a small Arctic permafrost-underlain basin at the tundra-taiga transition. The physical processes found in this environment and explicit changes in vegetation type and density were simulated and validated against observations of streamflow discharge, snow water equivalent and active layer thickness. Mean air temperature and all-wave irradiance have increased by 3.7 °C and 8.4 W m−2, respectively, while precipitation has decreased from 369 to 321 mm since 1960. Two modelling scenarios were created to separate the effects of changing climate and vegetation on hydrological processes. Results show that over 1960–2016 most hydrological changes were driven by climate changes, such as decreasing snowfall by 7.8 mm decade−1, deepening active layer thickness by 1.8–4.2 cm decade−1, earlier snowcover depletion and ground thaw initiation dates from 1.5 to 3 and by 1 to 3 days decade−1, respectively, and diminishing annual sublimation and soil moisture by 1.3 and 5.9 mm decade−1, respectively. Evapotranspiration decreased by 2.5 mm decade−1, due to decreasing irradiance and soil moisture. Shrub expansion and densification decreases blowing snow redistribution by 20 to 40 mm and sublimation by 1 to 10 mm. Streamflow dropped by 40 mm as a response to the 48 mm decrease in precipitation, suggesting a small degree of hydrological resiliency. These results represent the first detailed estimate of hydrological changes occurring in small Arctic basins, and can be used as a reference to inform other studies of Arctic climate change impacts.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".