The hydrological regime of a forested tropical Andean valley
Bibliographic record
Abstract
Abstract. The hydrology of tropical mountain catchments plays a central role in ecological function, geochemical and biogeochemical cycles, erosion and sediment production, and water supply in globally important environments. There have been few studies quantifying the seasonal and annual water budgets in the montane tropics, particularly in cloud forests. We investigated the water balance and hydrologic regime of the Kosñipata Valley (basin area 164.4 km2) over the period 2010–2011. The valley spans over 2500 m in elevation in the eastern Peruvian Andes and is dominated by tropical montane cloud forest with some high elevation puna grasslands. Catchment wide rainfall was 3028 ± 414 mm yr−1, calculated by calibrating Tropical Rainfall Measuring Mission (TRMM) 3B43 rainfall with rainfall data from 9 meteorological stations in the valley. Cloud water input to streamflow was 316 ± 116 mm yr−1 (~10% of total inputs), calculated from an isotopic mixing model using deuterium excess (Dxs) and δD of waters. Field stream flow was measured in 2010 by recording height and calibrating to discharge. River runoff was estimated to be 2796 ± 126 mm yr−1. Actual evapotranspiration (AET) was 909 ± 182 mm yr−1, determined using the Priestley and Taylor – Jet Propulsion Laboratory (PT-JPL) model. The overall water budget was balanced within 10%. Relationships between monthly rainfall and river runoff follow an anti-clockwise hysteresis through the year, with a persistence of high runoff after the end of the wet season. The size of the soil- and shallow ground-water reservoir is most likely insufficient to explain sustained dry season flow. Thus, the observed hysteresis in rainfall-runoff relationships is best explained by sustained groundwater flow in the dry season, which is consistent with the water isotope results that suggest persistent wet season sources to stream flow throughout the year. These results demonstrate the importance of transient groundwater storage in stabilizing the annual hydrograph in this region of the Andes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".