Evaluating equilibrium and non‐equilibrium transport of ammonium in a loam soil column
Bibliographic record
Abstract
Abstract Release of nitrogen compounds into groundwater, particularly those compounds from excessive agricultural fertilization, is a major concern in an aquifer recharge. Among the nitrogen compounds, ammonium ( ) is a common one. In order to assess the risk of agricultural fertilizer contamination to an aquifer through infiltration, adsorption onto a loamy agricultural soil profile (0–0.60 m depth) was studied using a soil column experiment and modelling simulation. The soil used in the experiment was drawn from an agricultural field in Xinzhen, Fangshan district, Beijing, China, and reconstituted in laboratory soil columns. Column experiments were conducted using bromide (conservative tracer) and ‐bearing aqueous solutions. The ammonium concentrations in the soil water samples were measured, and their values were plotted as the breakthrough curves. The chemical's soil–water distribution coefficients (Kd) were calculated using breakthrough curves. Then the retardation factor (R) in saturated soil was calculated. For the ‐bearing aqueous solutions, the strongest adsorption occurred at the soil depth of 0.30–0.45 m. The convection–dispersion equation model and chemical non‐equilibrium model in Hydrus‐1D were used to simulate transport in the loamy soil. The two‐site chemical non‐equilibrium model in Hydrus‐1D was best to simulate transport through the soil column. Parameter sensitivity study was conducted to investigate the influences of solute transport by Kd, the fraction of exchange sites assuming to be in equilibrium with the solution phase (f), the longitudinal dispersivity (λ), and the first‐order rate coefficients (ω). The sensitivity analysis results indicate Kd is the most critical parameter.
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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) | 0.000 | 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".