Contrasting stream stability characteristics in adjacent urban watersheds: Santa Clara Valley, California
Bibliographic record
Abstract
Abstract A comparative study of two adjacent stream channels in the Santa Clara Valley region of California provided an opportunity to study the relative effects of multi‐faceted watershed‐urbanization impacts on channel evolution and stability. Berryessa Creek (15.5 km2) and Upper Penitencia Creek (61.3 km2) have similar intrinsic watershed characteristics; however, urbanization processes have imposed distinctly different evolutionary trends in each watershed. The influences of drainage network manipulation, hydrologic routing and engineering infrastructure has resulted in Upper Penitencia Creek remaining relatively stable throughout the course of urbanization, while Berryessa Creek has experienced system‐wide channel instability problems. This study enumerates the many anthropogenic impacts and provides insight into basin alterations that can have either positive or negative feedbacks in maintaining or degrading channel stability throughout the course of urbanization. Results show that infrastructure that disrupts the bed material sediment continuity (such as large drop structures or sedimentation ponds) generate long‐term downstream channel instabilities leading to channel degradation and continued maintenance. Off‐line flow diversions (in this study percolation ponds) that do not disrupt bed material transport can emulate pre‐urbanization conditions offsetting channel degradation resulting from changes in hydrology. This study also demonstrates the degradational responses of a stream due to losses in riparian vegetation from water table lowering transforming a perennial stream into an ephemeral stream resulting in increased bank instability. The importance of maintaining floodplains for flood access and channel stability has also been identified and compared to conditions of channel encroachment to facilitate maintenance, which have further exacerbated downstream channel degradation, long‐term channel maintenance and dredging. Copyright © 2009 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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".