Electrical Resistivity Tomography Investigation of Buried Valley Aquifer Systems in the Edmonton Area, Alberta
Bibliographic record
Abstract
Buried valley aquifers underlying the Edmonton region are a potential source of potable groundwater. The location of the valleys has been mapped previously via borehole investigations, however valley fill heterogeneities and geometry are less known and are important for assessing the buried valley groundwater flow systems. This study focusses on the use, and implementation of electrical resistivity tomography (ERT) for aquifer investigations of buried valleys within the greater Edmonton area. ERT is a geophysical tool used in many applications, including hydrogeological. In this thesis, an overview is provided on ERT use, and factors to consider when carrying out investigations. These factors include array setup and choice, inversion techniques and parameters, error negation, and interpretation based on site knowledge. This study builds upon previous work by more closely examining Edmonton buried valley geometry and heterogeneity through ERT resistivity measurements at a reconnaissance scale. Areas of hydrogeological interest, considerable sediment thickness and proximity to mapped features were a priority. Using reference lithologies, resistivity forward models were developed as a reference point. ERT resistivity values produced two categories of results. Low to moderate resistivity profiles (<50 Ω m) were present in areas with poor drainage, and more likely to exist in areas with high water tables. Moderate to high resistivity profiles (~50 – >500 Ω m) were present in areas with greater drainage. Within each type, up to three resistivity units were identified. Glaciolacustrine silt and surficial clays: 9-12 Ω m; coarse valley fill: 20 – 100 Ω m; and bedrock shale and sandstone: 18 – 30 Ω m. Local tills could not be differentiated through resistivity values, as this was a transitionary unit between valley fill sediments and surface sediments. \n ERT data was found to be most valuable in combination with ground truthing field data, as changes in resistivity may be confidently assigned to geologic units. We experienced variable success in buried valley geometry interpretations. Clear bedrock topography is visible at several sites, while valley sidewalls were not confidently identified. We suggest to supplement ERT data with other data such as borehole lithology, mapping, AEM data, forward modelling, and sediment exposures. In sites of interest, ERT is useful as a reconnaissance-scale tool to determine buried valley presence, and identify areas with thicker coarse basal sediment. The ERT data in this study has provided better characterization of buried valleys in the Edmonton area, and these results can be used to make informed decisions regarding the water security in central Alberta.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".