Conversion of a Missouri River Dam and Reservoir to a Sustainable System: Sediment Management<sup>1</sup>
Bibliographic record
Abstract
Abstract: A present and future challenge for water resources engineers is to extend the useful life of our dams and reservoirs. Ongoing reservoir sedimentation in impoundments must be addressed; sedimentation in many reservoirs already limits project benefits and effective project life. Sustainability requires that incoming sediment be moved downstream past the impounding dam. We use Lewis and Clark Lake, the most downstream of the six Missouri River main stem reservoirs, to demonstrate how a reservoir in advanced stages of its project life could be converted to a sustainable system with local benefits exceeding costs by a factor of 1.5. Full consideration of benefits would further enhance project justification. The proposed strategy involves four phases that will take about 50 years to complete. Cost estimates for this potential project range from the quantitative to the plausible, but it is clear that the results justify a full engineering, environmental, and economic study of this model project. If implemented, the project will create scientific knowledge and develop technologies useful for achieving sustainability at many other reservoirs in the Mississippi River basin and beyond.
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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 | 0.001 | 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) | 0.005 | 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".