An event-based hydrologic simulation model for bioretention systems
Bibliographic record
Abstract
Bioretention systems are designed to treat stormwater and provide attenuated drainage between storms. Bioretention has shown great potential at reducing the volume and improving the quality of stormwater. This study introduces the bioretention hydrologic model (BHM), a one-dimensional model that simulates the hydrologic response of a bioretention system over the duration of a storm event. BHM is based on the RECARGA model, but has been adapted for improved accuracy and integration of pollutant transport models. BHM contains four completely-mixed layers and accounts for evapotranspiration, overflow, exfiltration to native soils and underdrain discharge. Model results were evaluated against field data collected over 10 storm events. Simulated flows were particularly sensitive to antecedent water content and drainage parameters of bioretention soils, which were calibrated through an optimisation algorithm. Temporal disparity was observed between simulated and measured flows, which was attributed to preferential flow paths formed within the soil matrix of the field system. Modelling results suggest that soil water storage is the most important short-term hydrologic process in bioretention, with exfiltration having the potential to be significant in native soils with sufficient permeability.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".