Gravel‐bed river evolution in earthquake‐prone regions subject to cycled hydrographs and repeated sediment pulses
Bibliographic record
Abstract
Abstract Sediment often enters rivers in the form of sediment pulses associated with landslides and debris flows. This is particularly so in gravel‐bed rivers in earthquake‐prone mountain regions, such as Southwest China. Under such circumstances, sediment pulses can rapidly change river topography and leave the river in repeated states of gradual recovery. In this paper, we implement a one‐dimensional morphodynamic model of river response to pulsed sediment supply. The model is validated using data from flume experiments, so demonstrating that it can successfully reproduce the overall morphodynamics of experimental pulses. The model is then used to explore the evolution of a gravel‐bed river subject to cycled hydrographs and repeated sediment pulses. These pulses are fed into the channel in a fixed region centered at a point halfway down the calculational domain. The pulsed sediment supply is in addition to a constant sediment supply at the upstream end. Results indicate that the river can reach a mobile‐bed equilibrium in which two regions exist within which bed elevation and surface grain size distribution vary periodically in time. One of these is at the upstream end, where a periodic discharge hydrograph and constant sediment supply are imposed, and the other is in a region about halfway down the channel where periodic sediment pulses are introduced. Outside these two regions, bed elevation and surface grain size distribution reach a mobile‐bed equilibrium that is invariant in time. The zone of fluctuation‐free mobile‐bed equilibrium upstream of the pulse region is not affected by repeated sediment pulses under the scenarios tested, but downstream of the pulse region, the channel reaches different fluctuation‐free mobile‐bed equilibriums under different sediment pulse scenarios. The vertical bed structure predicted by the simulations indicates that the cyclic variation associated with the hydrograph and sediment pulses can affect the substrate stratigraphy to some depth. Copyright © 2017 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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.
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