Effects of climate change on water availability for the Usumacinta river environmetal flow (Mexico)
Why this work is in the frame
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Bibliographic record
Abstract
The water availability in the Usumacinta River sub-basin is determined through the analysis of the amount and frequency of precipitation, associated with the quantity, frequency and magnitude of flow regimes (environmental flows). The river is located in south-eastern Mexico. The precipitation of preimpact (1960-1983) and post-impact (1984-2008) periods was analysed using a climatological mesh database created by CICESE (Center of Scientific Research and Higher Education of Ensenada) covering the period 1960-2008. For the analysis of flows, the hydrometric information the IHA V7 program was used to define the main trends in the temporal variation of the daily flows of the pre and post-impact periods. A number of several factors such as: the increase in monthly precipitation in the rainy season and a decrease of the precipitation in the dry season in the post-impact period, the significant increase in the number of days with zero precipitation, the increase in the number of days a year with a greater amplitude in the maximum rainfall, a positive tendency of precipitation in rainy season and a significant decrease in the dry season; implies that now in the wet period it rains more and in dry season it rains less, indicating that the climate is more extreme, aspects that can be associated with the effects of climate change. Also, torrential rains that can be associated to the changes in the precipitation rates are due to the effects of climatic change. The natural flow shows a slight decrease in the flow during the rainy season, or a significant decrease in the flow rates for some months in the post-impact period. This condition does not coincide with the increase in precipitation for this period and in this part of the basin, a situation that may be related to the anthropic use of the resource. The Usumacinta basin is relevant for the environmental services that it provides.
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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 | 0.001 | 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