Moisture Sources and Rainfall δ18O Variability over the Central Andes of Peru—A Case Study from the Mantaro River Basin
Bibliographic record
Abstract
The Mantaro River Basin is one of the most important regions in the central Peruvian Andes in terms of hydropower generation and agricultural production. Contributions to better understanding of the climate and hydrological dynamics are vital for this region and constitute key information to support regional water security and socioeconomic resilience. This study presents eight years of monthly isotopic precipitation information (δ18O, Dxs) collected in the Mantaro River Basin. The isotopic signals were evaluated in terms of moisture sources, including local and regional climatic parameters, to interpret their variability at monthly and interannual timescales. It is proposed that the degree of rainout upstream and the transport history of air masses, also related to regional atmospheric features, are the main factors influencing the δ18O variability. Moreover, significant correlations with precipitation amount and relative humidity imply that local processes in this region of the Andes also exert important control over isotopic variability. Two extreme regional climate events (the 2010 drought and the 2017 coastal El Niño) were evaluated to determine how regional atmospheric circulation affects the rainfall isotope variability. Based on these results, recommendations for hydroclimate studies and paleoclimate reconstructions are proposed in the context of the Mantaro River Basin. This study intends to encourage new applications considering geochemical evidence for hydrological studies over the central Andean region.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".