Cryosphere-groundwater connectivity in the mountain water cycle - where does meltwater go?
Bibliographic record
Abstract
Both the mountain cryosphere -- comprising glaciers, snow, and permafrost -- and groundwater play crucial roles in shaping the hydrological cycle. However, their connectivity is not well understood. Understanding the importance of sub-surface meltwater flowpaths and the role of groundwater in mountain regions is critical to untangle 1) the fate of meltwater in the hydrological cycle and 2) the sensitivity of groundwater to a changing meltwater supply due to climate change.Here, we synthesize studies which investigated the dynamics of meltwater flow through mountain aquifers. In general, snow-groundwater connectivity is better described than glacier-groundwater connectivity. However, estimations of meltwater recharge fluxes vary considerably across studies, which is not only a function of inherent catchment characteristics but also of the different methods used for the assessments. Estimates of the source contributions of mountain groundwater range between 2-60% for glacier melt and between 40-80% for snowmelt. These large numbers suggest that cryosphere-groundwater connectivity and the consequent delay in meltwater flow needs to be part of our conceptual understanding of the mountain water cycle. Still, there is a clear lack of understanding at which spatio-temporal scales this connection operates.As glaciers retreat and snowpack diminishes, the relative importance of groundwater as catchment storage is expected to increase. This increase may however be partly compromised by declining recharge from the mountain cryosphere and changed recharge dynamics, with yet unknown effects on catchment-scale hydrological processes. We suggest a roadmap for future work to better quantify mountain cryosphere-groundwater connectivity and to predict climate change impacts on mountain water supplies.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".