Modeling water flow and phosphorus fate and transport in a tile-drained clay loam soil using HYDRUS (2D/3D)
Bibliographic record
Abstract
Phosphorus (P) is an important agricultural non-point source pollutant that could contribute to eutrophication of surface waters.In this study, the HYDRUS (2D/3D) model was evaluated for simulation of water flow and P transport in a clay loam soil in southern Ontario.The model was calibrated and validated using field data from two 0.1 ha test plots between 2008-2011.These plots have controlled tile drainage and a corn-soybean crop rotation.The surface and sub-surface water flows in test plots were monitored and samples collected continuously year round using an auto-sampling system.The model simulated water flow and P relatively well, with weekly modeling efficiency of 0.513 to 0.738 for validation of water flow, and weekly modeling efficiency of 0.587 to 0.768 for validation of dissolved P loss in tile drainage.Most of the deviation of simulated water flow occurred between November to February, which suggests the model would greatly benefit from optimization of snow dynamics and frozen soil conditions.Some of the simulation errors may also be attributed to soil cracking in the summer which consequently enhanced macropore flow.The model predicted daily water flow poorly, suggesting presence of time lag between simulation and measurements.Limitations of the model include lack of simulation of particulate P loss and surface runoff P loss.This model should be tested further for other soils in southern Ontario as well as other parts of Canada before its validity can be established.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".