Effect of land management on runoff and soil losses from two small watersheds in St Lucia
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
Abstract The influence of land use on runoff and soil loss was assessed on two small watersheds in the Eastern Caribbean island of St Lucia, under contrasting land management regimes. The data generated from these watersheds revealed that the soil losses from an intensively cultivated agricultural watershed were 20‐times higher in magnitude than that of a forested watershed both for peak rainfall event and for total duration of analysis. This was due to higher surface runoff rates and exposure of soil to direct raindrop impact within cultivated areas. Whereas the forest canopy cover in combination with higher infiltration capacities of the forested land reduced the erosive runoff from the forest watershed and thus the soil loss. Moreover, the energy intensities of large storms in excess of 40 mm were estimated and found to range between 400 MJ mm ha −1 h −1 and 1834 MJ mm ha −1 h −1 . 1 Megajoules‐millimeters per hectare‐hour. Soil loss from the agricultural watershed was strongly correlated ( R 2 = 0·85) to storm energy‐intensity (EI 30 ). However, the correlation of soil loss with the EI 30 ( R 2 = 0·71) was poor for the forest watershed due to the effect of canopy vegetation, which significantly reduced the energy of raindrop impact. Over the study period, cumulative soil losses were 10·0 t ha −1 for the agricultural site and 0·5 t ha −1 for the forest site. 2 Metric tons per hectare. The largest storm observed during the study period resulted in erosion losses of 3·78 t ha −1 and 0·2 t ha −1 from the agricultural and forest sites respectively. The regression models were developed using the measured data for prediction of runoff and soil loss over the watersheds of St Lucia under similar conditions. This study contributed towards efficient watershed management planning and implementation of suitable water conservation measures in St Lucia. Copyright © 2005 John Wiley & Sons, Ltd.
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 | 0.000 | 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