Simulation of proglacial forefield morphodynamics and their implications for the filtering of subglacial sediment export following glacier retreat
Bibliographic record
Abstract
Abstract Proglacial forefields are geomorphologically active zones with rivers that may buffer sediment connectivity between glaciers and downstream regions. To date, there are few studies of the magnitude of this process and the role of system‐internal perturbations, such as meltwater discharge rates, subglacial sediment supply and changing valley topography (e.g. valley slope, lateral accommodation space) following glacier retreat. Here, we use a physically‐based morphodynamic model, calibrated using continuous field‐collected data, to investigate the geomorphic response of these fluvial systems to varying topographical, sedimentological and hydrological boundary conditions. Results confirm the central role of the supply to transport capacity ratio in determining both proglacial stream geomorphic response and downstream sediment delivery rates, particularly for bedload particles; while suspended sediment transport is less affected by morphodynamic processes. Simulations also showed that the filtering effect is influenced by the lateral accommodation space and valley bottom slope. These observations not only suggest that the filtering varies between geomorphological settings, but also that the form of a valley (width, slope), as it is revealed following glacier retreat, will also impact filtering. These findings are important for understanding the future evolution of the longitudinal sediment connectivity in deglaciating catchments, in light of likely peak water and peak sediment. In the near‐future, the evolution of the proglacial margin filtering will have repercussion for the supply of sediment towards downstream regions, for the management of hydropower plants and for aquatic ecosystems.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".