DESIGN, CONSTRUCTION, AND INSTALLATION OF LARGE DRAINAGE LYSIMETERS FOR WATER QUANTITY AND QUALITY STUDIES
Bibliographic record
Abstract
Six large drainage lysimeters (4.85 3.65 1.35 m) were designed, constructed, and installed for quantifyingcrop coefficients and water quality impacts of drip and seepage irrigated watermelon in south Florida. Monitoring systemsdesigned for the lysimeters included water quantity (irrigation, rainfall, runoff, drainage, soil moisture, and water tabledepth) and quality (nutrient concentrations in the root zone, saturated zone, drainage, and runoff). Lysimeters, made of mildsteel plate, containing two plastic mulch plant beds and an irrigation ditch, were installed in a watermelon field. The soilprofile (A and E horizons) was reconstructed using native soil from the field. Bi-weekly soil solution and saturated zonesamples, and event-based drainage and runoff water quality samples were collected and analyzed for nitrogen (NH4-N,NO3-N, TKN) and total phosphorus. The watermelon crop was planted on plastic mulch beds. Four lysimeters received dripirrigation and two received seepage irrigation. Preliminary data for the first six weeks of watermelon crop for the drip andseepage irrigation systems indicated that lysimeters were working properly. Seepage lysimeter systems had higher ETccompared with drip irrigated lysimeters due to wetter soil and high evaporation losses during irrigation. Water quality datashowed that total dissolved nitrogen discharges from the seepage lysimeters were higher than the drip lysimeters. Lowernitrogen loadings for the drip lysimeters were mainly attributed to higher soil water storage capacity and fertigation. Thedesign and installation described in this study will be helpful for future studies with large lysimeters.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".