Past and Future Hydrology Near the Arctic Treeline
Bibliographic record
Abstract
The Arctic has warmed rapidly, increasing shrub cover and density, and thawing permafrost. Understanding, quantifying and predicting the impact of these environmental changes on the hydrological regime of Arctic headwater basins represents a great scientific challenge, particularly due to the sparse monitoring network, limited understanding of governing physical processes and their interaction, and the uncertainty in future climate projections. The purpose of this research is to better understand the impact of climate and vegetation change on the hydrology of Arctic basins near the treeline. This thesis is divided into four sections with the following objectives: (1) to test the coupling of a ground freeze/thaw algorithm with a hydrological model at two research sites in northern Yukon; (2) to diagnose the hydrology of a small Arctic basin near the treeline using a physically based hydrological model; (3) to quantify its historical long-term changes and investigate the individual and combined effect of changing climate and vegetation on its hydrology; and (4) to use high-resolution climate simulations under a high gas concentration scenario along with expected vegetation changes, to investigate changes to hydrological processes and regime. Results revealed the importance of including vegetation dynamics such as changes in shrub extension and density in hydrological models, to capture their impact on blowing snow redistribution and sublimation, and canopy interception and sublimation of snow, something neglected by current studies. This study demonstrated that increasing shrub extension and density near the Arctic treeline slightly compensates the historical decrease in mean annual discharge produced by the decreasing precipitation, providing a small degree of hydrological resiliency. Historical change analysis revealed that hydrological processes are decelerating near the Arctic treeline, such as decreasing evapotranspiration, soil moisture, sublimation and streamflow, mostly driven by climate change. However, under sufficient climate change (38% and 6.1 °C increase in mean annual precipitation and temperature, respectively) significant hydrological changes are expected, reversing the simulated historical changes. Projections show a significant increase in mean annual streamflow discharge, shortening of the snowcover seasons, deepening of the active layer thickness, increasing peak snow accumulation and earlier and larger peak streamflow. Whilst specific to one basin, they indicate the nature of hydrological changes facing Arctic hydrology. These changes will have significant impacts on ecosystems, infrastructure, landscape evolution and atmospheric feedbacks, which are required to be properly understood and quantified to design sustainable and effective mitigation and adaptation plans. The analyses and discussions presented in this study to diagnose the past and predict future Arctic hydrology are relevant for the scientific community of hydrologists, engineers, water managers and policy makers, particularly those interested in cold regions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".