Monitoring sediment processes in different delta systems in Swiss peri-alpine lakes through 4D bathymetric mapping
Bibliographic record
Abstract
Deltas represent transfer zones where sediment is moved from terrestrial to the subaquatic domains. They are depositional areas and a source for sediments simultaneously. One of the aspects in this highly dynamic environment that has experienced so far little attention are slope failures in deltas. Such failures are, however, mentioned as potential cause for large (up to m-scale), graded deposits in the sedimentary record, often referred to as megaturbidites or homogenites. In some cases, they may have generated tsunamis in the near-shore area. These delta failures can be triggered, amongst other causes, by spontaneous slope collapses (e.g. Muota delta 1687 in Lake Lucerne, Switzerland). To better understand the controlling factors of slope stability in deltas, we need to comprehend the interplay between deltaic deposition and erosion through time and monitor their evolution.Repeated bathymetric mapping has been used as powerful tool to better understand the short-term processes occurring in deltas. In this contribution, repeated bathymetric mapping is used to better characterize, which short-term processes may shape subaqueous delta fronts. Using the dataset acquired in recent years in Swiss lakes, we seek to answer (1) what processes can be visualized based on repeated bathymetric mapping?; (2) which areas are prone to depositional/erosion processes?; and (3) what type of delta is more prone to slope failures? We present the first datasets of differential maps from four deltas in Switzerland that show different processes of erosion and deposition on short and long time scales. In addition, we will present the design of a planned multi-method monitoring campaign for delta processes in a sublacustrine delta in a peri-alpine lake in Switzerland.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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".