Hydrologic Response to Effluent Infiltrating from At‐Grade Line Sources to Shallow Groundwater
Bibliographic record
Abstract
Core Ideas Quantifying hydrologic responses helps in groundwater risk assessment. Signal analysis is a robust tool for separating regional and local input signals. Temporal change in vadose zone thickness is critical for onsite wastewater treatment. Understanding of wastewater flow and transport processes through soil‐based onsite wastewater treatment systems (OWTS) remains a challenge. An extensive field research program was executed in Alberta, Canada to investigate the treatment effectiveness of a new, litter‐fermented‐humic layer (LFH), at‐grade, soil‐based OWTS. The site had been receiving secondarily treated and ultraviolet (UV)‐disinfected effluent via pressurized, at‐grade laterals for 4 yr before the start of this research. The objective of this study was to investigate the hydrologic response of a shallow groundwater table to effluent infiltration. Following a detailed site characterization of groundwater flow direction and wastewater plume extent, daily groundwater fluctuation, effluent and atmospheric fluxes were monitored for more than 2 yr. Considering the local existing regulatory requirement of 7‐d effluent travel depth through the vadose zone to achieve a treatment objective, weekly cycle hydrologic responses were interpreted using signal analysis tools. Findings indicated (i) a significant hydrologic response to effluent infiltration from the at‐grade laterals at a weekly scale, and (ii) effluent reaches the groundwater within 1 wk of application approximately 15% of the time in the spring and summer periods when effluent loading rates are ≥5 cm 3 cm −2 d −1 and the water table is ≤0.5 m below the ground surface. These conditions also coincided with the significant 7‐d cycle of the effluent input function, which is a function of the weekly cycle of facility use, that is, more intensive facility use on weekends. The results presented in here contribute significantly to the understanding of wastewater flow and transport under boundary conditions typical of OWTS and shallow groundwater conditions.
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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 | 0.000 |
| 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".