Bibliographic record
Abstract
Removal of low-head and mill pond dams throughout North America has garnered considerable attention over the past twenty years. Dam removal along watercourses is frequently being considered to address private and public liability regarding the failure of old and/or abandoned dams, removal of aquatic migration barriers and, to improve nutrient spiraling to enhance both downstream and upstream ecological diversity. A significant number of studies have been conducted over the past 50 years regarding the ecological impacts of dams, rates of reservoir sedimentation and, down stream erosion. Further, several more studies have examined and employed strategies for the decommissioning of dams, limiting downstream sediment deposition and improving fish migration. However, few studies have examined the upstream impacts of dam decommissioning beyond the backwater limits of reservoirs. This study examines the upstream effects of low-head dam decommissioning on channel morphology using the analog of existing failed dams by natural processes. The most drastic method of dam decommissioning is the "blow and go" approach, whereby a dam is removed and the watercourse is simply allowed to reassume a stable morphology (often assumed to be the pre-dam morphology). A series of low-head and mill pond dams were studied in southern Ontario which failed between 6 – 45 years before present and at locations where no upstream channel mitigation has taken place to provide an analog to the "blow and go" methodology. In each study reach, longitudinal profiles and cross-sectional field surveys were conducted from below the dam faces for several meander wave lengths upstream of each reservoir backwater limits. Numerical models were developed for the historical dam operational and current hydraulic conditions. Pavement samples were collected from riffles and headcuts within and above the reservoir regions of each reach and tractive force and sediment transport analyses conducted. Findings demonstrate that erosional disturbances typically in the form of headcuts and lateral migration are frequently observed at considerable distances upstream of reservoir limits. Depending upon the upstream bedload grain size distribution, the rate of channel armouring and dam height (i.e. localized friction slope), channel disturbances may continue for several decades and continue to degrade a given watercourse for several kilometers upstream of a reservoir. Findings further support the need to consider upstream grade-control and floodplain re-connectivity as part of such restoration initiatives to minimize degradational impacts, down stream sedimentation and to stabilize aquatic and riparian habitat.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".