Rapid proglacial delta growth from meltwater pulses in Lituya Bay, Alaska
Bibliographic record
Abstract
Over past decades, sustained meltwater discharge has formed rapidly growing proglacial deltas in the fjords and bays along the glaciated coast of Alaska. These deltas are efficient traps of glaciofluvial sediment, buffering sediment flux from land to the ocean and altering coastal ecosystems. In addition to seasonal meltwater discharge, rates of proglacial sediment transport in Alaska can be elevated by episodic Glacier Lake Outburst Floods (GLOFs). Here we explore the contribution of GLOFs to sediment accumulation on two deltas that simultaneously formed at the head of Lituya Bay, Glacier Bay National Park, Alaska. Both deltas share a similar tectonic, climatic, and glaciologic setting. However, one of them, Lituya delta, is frequently flooded during outbursts of an ice-dammed lake, while the other, Crillon delta, had no reported lake outburst floods. Our goal is to quantify the competing roles in sedimentation during average seasonal and extreme GLOF discharges. To this end, we tracked the growth of the two deltas from a time series of satellite images, measured clast sizes on the deltas, and conducted a multi-beam depth survey of Lituya Bay. We find that the lake outburst floods cover most of Lituya delta almost every year, transporting boulders up to 7 m in diameter and carving deeply incised channels into the delta. By contrast, the average clast size on Crillon delta is approximately one order of magnitude smaller and the distributary channels are less deep than on Lituya delta. In the past six decades, both deltas have rapidly prograded into the bay. However, Lituya delta grew 45% more in area than Crillon delta under comparable catchment properties, suggesting that the geomorphic work during outburst floods greatly surpasses that of the 'normal' glaciofluvial discharge from Crillon Glacier. Overall, we find that at least 0.57 km3 of sediment accumulated in Lituya Bay between 1959 and 2023, one of the highest sedimentation rates in the coastal mountain ranges of Alaska. Out of this volume, 0.23 km3 of sediment accumulated within the exposed area of Lituya delta alone, nearly twice the volume compared to Crillon delta with 0.13 km3. In our contribution, we will assess the spatial and temporal variability of delta growth and discuss the relative contributions of glacier advance and retreat, sediment sources, and outburst floods. Thereby, our work enhances the understanding of how GLOFs and shifting climatic and glaciological conditions impact coastal sedimentation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".