Geophysical Exploration for Water Resources in Buried Valleys in Western Canada
Bibliographic record
Abstract
Most of Western Canada is devoid of extensive regional aquifers. In the Prairie Provinces, while most large cities rely on surface water, smaller municipalities generally rely on groundwater. In such cases, buried valley aquifers are often the only viable source of a large yield groundwater source. Other than municipalities, many mines, power plants, farmers, oil and gas operations, and various industrial facilities also rely on water supplies derived from buried valley aquifers. Most of these aquifers are difficult to identify and delineate. Usually, they are covered by a significant thickness of till varying from 10 m to greater than 50 m, making air photo identification usually ambiguous, and often impossible. Even where the valleys can be approximately delineated from existing borehole information, air photo interpretation, airborne geophysical data, or legacy oil and gas seismic reflection data, most of the valley fill may be silt and clay. As such, easily accessed information may not be sufficient to identify high yielding aquifers within the buried valleys. This paper will describe the systematic evolution and integrated use of a variety of ground geophysical techniques in exploring for, and delineating buried valley aquifers, including high resolution seismic reflection, time domain EM, fixed frequency EM, and electrical resistivity tomography. Case studies will be presented from Saskatchewan, Alberta, and British Columbia. Case study applications will include municipal and rural water supply, oil and gas source water, agricultural supply, and mine dewatering.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".