A review of the current state of knowledge of proglacial hydrogeology in the Cordillera Blanca, Peru
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
The rapidly melting glaciers of Peru are posing new risks to regional dry season water supplies, and this is evident in the Cordillera Blanca, the mountain range with the world's largest concentration of tropical glaciers. Permanent ice loss is causing reductions to dry season streamflow, which is coupled with shifting demands and control over water access and entitlements in the region. A full evaluation of hydrologic inputs is required to inform future water management in the relative absence of glaciers. Over the last decade, new studies have shown groundwater to be a significant component of the regional water budget during the dry season, and it cannot be ignored when accounting for water quality and quantity downstream of the Cordillera Blanca's alpine catchments. Distinctive common features of the Cordillera Blanca's proglacial catchments are sediment‐filled valleys that were once under proglacial lake conditions. The combination of lake sediments with other alpine depositional features results in storage and interseasonal release of groundwater that comprises up to 80% of the valley's streamflow during the driest months of the year. We summarize the emerging understanding of hydrogeologic processes in proglacial headwater systems of the region's principal river, the Rio Santa, and make suggestions for future research that will more clearly characterize the spatial distribution of stored groundwater within the mountain range. As glaciers continue to recede, differences in aquifer thickness and groundwater residence time between alpine catchments in the region will increasingly control dry season water availability at the local and basin scale. This article is categorized under: Science of Water > Hydrological Processes Science of Water > Water and Environmental Change Engineering Water > Planning Water
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it