Modeling and Mitigating Phosphorus Losses from a Tile‐Drained and Manured Field Using RZWQM2‐P
Bibliographic record
Abstract
Prediction of P losses from manured agricultural fields through surface runoff and tile drainage is necessary to mitigate widespread eutrophication in water bodies. However, present water quality models are weak in predicting P losses, particularly in tile‐drained and manure‐applied cropland. We developed a field‐scale P management model, the Root Zone Water Quality Model version 2–Phosphorus (RZWQM2‐P), whose accuracy in simulating P losses from manure applied agricultural field is yet to be tested. The objectives of this study were (i) to assess the accuracy of this new model in simulating dissolved reactive phosphorus (DRP) and particulate phosphorus (PP) losses in surface runoff and tile drainage from a manure amended field, and (ii) to identify best management practices to mitigate manure P losses including water table control, manure application timing, and spreading methods by the use of model simulation. The model was evaluated against data collected from a liquid cattle manure applied field with maize ( Zea mays L.)–soybean [ Glycine max (L.) Merr.] rotation in Ontario, Canada. The results revealed that the RZWQM2‐P model satisfactorily simulated DRP and PP losses through both surface runoff and tile drainage (Nash–Sutcliffe efficiency > 0.50, percentage bias within ±25%, and index of agreement > 0.75). Compared with conventional management practices, manure injection reduced the P losses by 18%, whereas controlled drainage and winter manure application increased P losses by 13 and 23%, respectively. The RZWQM2‐P is a promising tool for P management in manured and subsurface drained agricultural field. The injection of manure rather than controlled drainage is an effective management practice to mitigate P losses from a subsurface‐drained field. Core Ideas RZWQM2‐P satisfactorily simulated P losses from the manure‐applied field. A field experiment revealed that the nongrowing season dominated the P losses. Particulate P loss dominated the average annual P loss as per the field experiment. RZWQM‐P adequately simulated seasonal P losses and dominant P loss type. Injected manure application was found effective to mitigate P losses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 teacher head, 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".