Simulation of nitrate leaching in Yala season in Batticaloa - A modeling approach
Bibliographic record
Abstract
The leaching behaviour of NO3--N was evaluated through field experiments with those predicted by LEACHM-N, a uni-dimensional, water flow, solute transport and plant uptake model. Therefore, the objective of this study was to evaluate the application of LEACHM-N for predicting nitrate leaching in Batticaloa during Yala 2005. Field experiments were carried out from April 12th 2005 to June 30th 2005. The experimental treatments were 3 nitrogen rates (0, 70 and 140 kg N/ha) together with 3 irrigation rates (7, 14 and 30 mm) which resulted in 9 treatment combinations. The treatments were arranged in a split plot design in 3 replicates. Twenty seven cylindrical lysimeters with 1 m height and 50 cm diameter were built in at the experimental site. Outlets from each lysimeters were fixed with outflow pipes, directed to an underground sampling point, from where the water samples were collected. Red onion (Allium cepa; var. Vethalan) was planted in the lysimeters. Nitrogen fertilizer was applied 3 times during the cropping season. Irrigation water was delivered using a micro sprinkler system. Leachates from individual outlets were collected separately and NO3--N was determined spectrophotometrically by the Cadmium reduction method. A moderately good agreement has been found out in between the measured and the predicted NO3--N losses, but the model overestimated the losses. The treatment combination 140 kg N/ha with 30 mm of irrigation showed better simulation accuracy. It was also found out that the model was unable to predict preferential flow.Keywords: LEACHM-N, leaching, sandy regosols,Yala, lysimeter, preferential flowDOI: http://dx.doi.org/10.4038/josuk.v5i0.4089 J Sci.Univ.Kelaniya 5 (2010): 33-45
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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 | 0.001 | 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 | 0.001 |
| 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".