Application of the Standardized Precipitation Index and Normalized Difference Vegetation Index for Evaluation of Irrigation Demands at Three Sites in Jamaica
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Agricultural production is a significant contributor to the economy of Jamaica, which is situated in the northwestern Caribbean Sea; this production is heavily dependent on seasonal rainfall because only approximately 10% of Jamaica’s cultivated lands are irrigated. Drought is a disastrous natural phenomenon that has a significant impact on socioeconomics, agriculture, and the environment. In the 2000–2001 drought experienced in Jamaica, there were crop losses amounting up to US$6 million. Hence, drought index information is essential for better planning for drought impacts and allows for the introduction of mitigation measures in the agricultural sector. Therefore, the objective of this paper is to evaluate the suitability of both the Standardized Precipitation Index (SPI) and the Normalized Difference Vegetation Index (NDVI) in reflecting water stressed conditions and irrigation demand requirements for three agricultural sites: Savanna-la-Mar in the parish of Westmoreland, Beckford Kraal in the parish of Clarendon, and Serge Island in the parish of St. Thomas, all in Jamaica. These sites were selected based on soil characteristics, historical rainfall data, and farming practices. The results indicate that the NDVI provides a suitable representation of these areas for only the driest months of the year, and that either the one-month or three-month SPI was found to be more representative of soil moisture conditions. Furthermore, a correlation analysis was also conducted between the SPI and soil moisture for El Niño years only, because the El Niño/Southern Oscillation phenomenon has been responsible for many of the droughts Jamaica has experienced. In these years, good correlations between soil moisture and the one-month and three-month SPI were obtained in some wet months, in addition to the dry months. This paper provides soil moisture values for all of the different categories and values of the SPI relating to water scarcity. It also provides irrigation requirements for the “moderately dry” and “severely dry” SPI drought categories.
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.
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 | 0.000 |
| 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