Comparison of Continuous Core Profiles and Monitoring Wells for Assessing Groundwater Contamination by Agricultural Nitrate
Bibliographic record
Abstract
Abstract Studies that assess groundwater contamination by agricultural nitrate ( NO 3 − ) commonly measure groundwater chemistry in samples collected from monitoring wells. This approach can be limited by coarse vertical resolution and aquifer heterogeneity. In this paper, we compare continuous core profiles against samples from monitoring wells for assessing agricultural nitrate contamination. Stable isotopes ( δ 2 H and δ 18 O ), chloride (Cl − ), and NO 3 − were measured in four nested wells and continuous core collected to depths of up to 20 m on three different sampling dates at a site in Alberta, Canada. Continuous core profiles of stable isotopes are used to define solute transport zones (advection‐dispersion dominated vs. diffusion dominated), which then informs the interpretation of the Cl − and NO 3 − profiles. Data from monitoring wells were particularly useful for capturing the temporal dynamics near the water table, but could not be used to define the dominant transport zones. Given the temporal variation in mass input of agricultural NO 3 − , the increased spatial resolution of continuous core profiles provides an advantage over samples from monitoring wells to assess groundwater contamination by agricultural NO 3 − . The relatively fine spatial resolution of continuous core profiles is particularly useful for assessing rates of NO 3 − attenuation through denitrification. This benefit is offset by the need to resample the entire profile at each sampling time, in contrast to groundwater wells, which can be sampled repeatedly with time. Vertical profiling of continuous core is recommended in addition to monitoring wells to assess near‐surface groundwater contamination, particularly at sites where vertical heterogeneity in hydraulic conductivity on the scale of metres or less is likely.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".