Phosphorus retention in a bioretention cell: Insights from process-based modelling
Bibliographic record
Abstract
Bioretention cells (BRCs) have emerged as one of the Green Infrastructure and low impact development (LID) practices to reduce peak discharge and nutrient export in urban areas. Despite growing implementation globally, understanding of P cycling and retention mechanisms in BRC is limited. In this presentation, we present a novel numerical reactive transport model to simulate the fate and transport of P in a BRC system in the greater Toronto metropolitan area. Unlike existing BRC models, our model incorporates a detailed representation of the biogeochemical reaction network that control P cycling and retention within the BRC. We used this model as a diagnostic tool to determine the relative importance of different P removal processes and their contributions to the P accumulation trajectory within the BRC over 8 years of operation. Model results were validated against time series flow data, plus water chemistry and soil filter media P concentration depth profiles measured between 2012 and 2019. A sequential extraction analysis was also applied to soil cores collected in 2019 to validate the model-derived P pools profiles. The model simulations reproduce the total P (TP) and soluble reactive P (SRP) outflow loads with the TP accumulation rate in the soil filter media and the partitioning of P between different soil chemical pools. The simulation results indicate that groundwater recharge is the dominant mechanism responsible for decreasing the surface water discharge from the BRC (63% runoff reduction), which implies potential impact of infiltrated stormwater on groundwater quality. But that bioretention cell is still efficient at reducing P concentration of infiltrated stormwater since accumulation in the soil filter media is the predominant P removal mechanism (57% of TP influx), and the filter media was not saturated after 8 years of operation. Of P retained within the soil filter media, 48% is highly stable, 41% potentially remobilizable, and 11% easily remobilizable. In addition to elucidating P cycling, our model can help to assess the impact of BRC design choices on P retention efficiency and the stability of the retained P within the soil filter media and eventually to predict the P transport to groundwater aquifers.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".