The Novel Application of Electrical Resistivity Tomography for Spatiotemporal Monitoring of Urban Stormwater Bioretention Systems
Bibliographic record
Abstract
Bioretention systems are an increasingly popular low-impact development (LID) stormwater management approach that are used to reduce the water quantity and quality impacts of urban stormwater. The study investigated the feasibility and benefits of using non-invasive time-lapse electrical resistivity tomography (ERT) to understand the infiltration and soil moisture dynamics within bioretention systems. This was achieved through monitoring two field-scale operational bioretention systems in London, Ontario, Canada. High-resolution two-dimensional time-lapse ERT surveys were first completed during synthetic and natural rain events to assess the viability of time-lapse ERT to monitor soil moisture changes during events. Following this, three-dimensional ERT surveys were conducted during synthetic and natural rain events to provide increased spatial understanding across the entire bioretention system and thus provide new insights into the infiltration and soil moisture dynamics. Overall, this study shows that ERT is a viable method for in situ monitoring of bioretention systems and that soil moisture dynamics in bioretention systems are highly complex and spatially heterogeneous.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".