A Methodology for Reservoir Site Selection for the Maintenance of Impounded Water Quality
Bibliographic record
Abstract
A METHODOLOGY FOR RESERVOIR SITE SELECTION FOR THE MAINTENANCE OF IMPOUNDED WATER QUALITY Deterioration of the quality of impounded water due to an inflow of groundwater occurs in some surface reservoirs in Saskatchewan. A methodology to aid in reservoir site selection for the maintenance of high quality impounded waters has been developed as the result of an investigation of the cause of water quality deterioration in the Blackstrap Reservoir. A study region that encompasses the Blackstrap Reservoir and the area between the South Saskatchewan River and the Allan Hills Upland was established. Background information on pedology, geology, and geomorphology was reviewed. A base map of the study region was compiled from National Topographic System maps. Information from many hundreds of existing testholes and water wells was plotted on the base map. Water wells in the vicinity of the Blackstrap Reservoir, preferably those with completion records, were selected for water quality sampling. Water levels, pH and electrical conductivity measurements were taken in the field at the time the several stratigraphic cross-sections of the study region were prepared. By sampling water wells completed in both the glacial and the upper bedrock formations a hydrochemical profile was established. The stratigraphy, static water levels, and the water chemistry established the regional and local groundwater framework. A finite element model was used to confirm the evidence of groundwater discharge into the Blackstrap Reservoir. By defining the geology, hydrochemistry and the surface and ground water hydrology, the interaction between a reservoir and the physical environment may be predicted. This methodology provides a scientific basis for reservoir site selection for the maintenance of water quality.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".