Interactions between shallow groundwater and low‐impact development underdrain flow at different temporal scales
Bibliographic record
Abstract
Abstract Low‐impact development (LID) practices are effective in managing surface run‐off, mitigating nonpoint source pollution, and recharging groundwater. However, they are often less effective in shallow groundwater environments as their surface infiltration and bottom exfiltration rates could be reduced, and the underdrains (i.e., underground drains within the media of the LID practices) may drain groundwater and alter groundwater dynamics. To evaluate and better understand the interactions between shallow groundwater and LID underdrain flow at different temporal scales, multiple statistical analyses were conducted on the monitored groundwater table depth and underdrain flow of porous pavements at the Central Kitsap Community Campus (Washington) and both porous pavements and bioretention cells at the IMAX parking lot (Ontario, Canada). The wavelet power, which represents oscillation behaviour and is obtained by continuous wavelet transform, of underdrain flow was a hybrid of that of rainfall and groundwater table depth. Rainfall variations at finer temporal scales (5 min to 10 days) resulted in finer scale underdrain flow, whereas groundwater fluctuations at coarser temporal scales (10 to 30 days) accounted for coarser scale underdrain flow and extended the duration of it. The impact of groundwater on underdrain flow was greater when the groundwater table was shallower than the underdrain (e.g., <0.6 m), particularly at finer temporal resolutions (5 min to 1 hr), which correspond to short‐term responses of LID practices and their corresponding effects on flooding. It was possible that the local groundwater mounds formed by infiltrated water instead of regional groundwater fluctuations that affected the underdrain flow in these conditions. Finally, through an evolutionary polynomial regression, two simple equations were obtained to predict the total amount and peak of LID underdrain flow using event‐based rainfall, groundwater table depth, and the hydraulic conductivity of media and in situ soils. The results may facilitate LID design and planning, and their implementation in shallow groundwater areas. The derived equations may benefit the real‐time control of LID‐related sewer and treatment systems in shallow groundwater urban catchments.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".