Bedload Sediment Transport Regimes of Semi‐alluvial Rivers Conditioned by Urbanization and Stormwater Management
Bibliographic record
Abstract
Abstract Watershed urbanization and stormwater management (SWM) alter the hydrologic processes of rivers. Although differences have been documented in channel morphology and sediment yield pre‐ and posturbanization, little is known about how the modified hydrology affects grain‐scale bedload transport dynamics. This study aims to characterize the bedload sediment transport regime of three rivers with different hydrologic settings: rural, urban with no SWM, and urban with peak‐shaving SWM. The rivers are “semi‐alluvial,” characterized by an alluvial layer over a cohesive till. Bedload transport was monitored using tracer stones over 3 years. Hydrograph characteristics of the streams fit with what is expected in urban and SWM systems, and the rural stream has an episodic transport regime typical of gravel‐bed rivers. Entrainment thresholds are not detectably impacted by the semi‐alluvial bed cover, but travel lengths of grains relative to their size are longer than in alluvial gravel‐bed streams. Downstream displacement rates of particles up to the D90 are accelerated in the urban river due to more frequent mobilization rather than increased event‐based travel lengths and may explain channel enlargement. SWM decreases the mobility and travel lengths of particles below those in the rural system, which is combined with channel narrowing, and the loss of bed forms suggests a shift toward a competence‐limited transport regime. This new regime is a result of reduced shear stresses that are insufficient to transport coarse material. This study presents empirical evidence of the effects of watershed urbanization and SWM on bedload transport and provides recommendations for process‐based river management strategies.
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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".