Modeling the Distribution of Agricultural Drought by Means of Soil Water Deficit
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Bibliographic record
Abstract
The extreme hydrologic events in Buenos Aires province (Argentina) had been a constant in its social - economic development. Their impacts mainly over the agriculture have been studied with different scales and point of views. In spite of that, there is a lack of studies of their temporal and spatial distribution in Argentina. Drought is initiated by a reduction in precipitation. The time requires for a lack of rainfall to create a significant deficit in the supplies is variable and could vary from a few weeks to several years. This paper studies the soil water deficit from 1969 to 2008 in the whole Buenos Aires province (307,571 km2) which is divided in 16 sectors according its basins (National Water Resources) and with soil water balance using soil data obtained “in situ”. It was performed using the evapotranspitation formula of Penman - Monteith and considering the soil water constants: Field Capacity, Soil Water Moisture and Soil Wilting Point for all the different types of soils of the region. For the statistical study, the obtained data series of soil water deficit were adjusted by means of the theoretical Normal Cubic-root probability distribution. An annual threshold value of 200 mm is considered because it is an ecological limit and upper which the drought is the consequence. The intensity of it has been arbitrary classified in: mild, moderate, severe and extreme according the annual values reached. Mann Kendall statistical test was performed and significance trends at levels 0.1, 0.05 and 0.01 were found.
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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 it