Exploring the connectivity between glacier melt, groundwater and climate change in the Cordillera Blanca, Peru
Bibliographic record
Abstract
Glacier melt is known to provide an important source of water to streamflow in glacierized tropical regions, especially during the dry season. Groundwater also contributes a significant amount to streamflow. However, the linkage between the two is often unclear: How much groundwater originates from glacier melt? More broadly, how will groundwater and surface water contributions to streamflow change as glaciers retreat and climate changes? We developed a glacio-hydrological model in the Cold Region Hydrological Modelling platform to explore the complex interactions among the cryosphere, surface water, and groundwater in Peru's Cordillera Blanca, specifically in the Quilcayhuanca valley. The model uses meteorological observations from the valley and is parameterized using numerous data sources and process-based studies in the valley. Our findings reveal that during the dry season, 24 % of streamflow is routed through the groundwater reservoir, increasing to 40 % during the lowest flows. In a simulation without glaciers, streamflow discharge decreases by 34 % during the wet season and by 54 % during the dry season, with the groundwater contribution to streamflow decreasing by 55 % and 52 % for the wet and dry seasons, respectively. This simplified approach suggests that approximately half of the annual groundwater contribution to the stream originates from glacier wastage. We conducted sensitivity scenarios to evaluate the basin's resilience to the range of possible changes in precipitation, temperature and glacier cover expected by 2100. In a nearly deglaciated basin, the sensitivity to the range of tested temperature (+0 to 5 °C) produced a streamflow ranging from -60 to -49 % of current conditions in the dry season, and the range of tested precipitation (-20 % to +20 %) produced a streamflow ranging between -78 to -35 % of current conditions, indicating a larger sensitivity to potential changes in precipitation. Expected ratio changes were smaller during the wet season but followed a similar pattern. In the most likely scenarios by 2100, under RCP 8.5, wet season streamflow is predicted to decrease by 17 to 27 %, and dry season streamflow by 28 to 52 %. Despite a substantial decline in snow and ice contributions under climate change and deglaciation, the groundwater zone's contribution to streamflow shows relatively minor changes, demonstrating the low sensitivity of the groundwater system to climate shifts and glacier variations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".