How much water can bioretention retain, and where does it go?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Bioretention is a type of green stormwater infrastructure for the urban environment that mimics a natural hydrologic system by reducing peak flows and runoff volumes and encouraging infiltration and evapotranspiration. This study examines the complete water balance of a bioretention system located in Vaughan, Ontario, Canada, between 2018 and 2019. The water balance was further broken down by event size, where the event size was determined by rainfall frequency analysis. Recharge was the largest component of the water balance overall (88% of inflow), as well as by event size. Evapotranspiration was the next largest water balance component (6% of inflow overall), and was a significant component of inflow (19%) when considering only small events (50% probability of recurrence). Evapotranspiration is a slow but consistent process, averaging 2.3 mm/day overall and 2.9 mm/day during the growing season. Climate change is likely to bring more wet days and higher temperatures, which will impact the bioretention water balance by increasing evapotranspiration and inflow. Design standards for retention targets should be updated based on the most recent rainfall frequency analyses to adjust for changing climate conditions.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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 it