Water Table Management as a Natural Bioremediation Technique of Nitrate Pollution
Bibliographic record
Abstract
Abstract Nitrate-nitrogen (NO3--N) pollution of water resources is a worldwide problem. Field trials were conducted from 1997 to 1998 to investigate the combined impacts of water table management (WTM) and N fertilization rate on soil NO3--N level and concentration of NO3--N in drainage water. Treatments consisted of two water table treatments: free drainage (FD) with open drains at a 1.0-m depth from the soil surface and subirrigation (SI) with a design water table of 0.6 m below the soil surface, and two N fertilizer rates: 200 kg N ha-1 (N200) and 120 kg N ha-1 (N120) in a split-plot design. Subirrigation reduced NO3--N concentration in the soil compared to FD by 37% in the spring of 1997 but not significantly (2%) in 1998; and 45% and 19% in the fall of 1997 and 1998, respectively. Higher rates of fertilization (N200) resulted in greater levels of NO3--N in the soil profile than the N120. Nitrate-N concentrations in drainage water from SI were 74% and 80% lower than those from FD in 1997 and 1998, respectively. Water table management can effectively reduce NO3--N pollution of water.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".