Inferring hydraulic properties of alpine aquifers from the propagation of diurnal snowmelt signals
Bibliographic record
Abstract
Abstract Alpine watersheds source major rivers throughout the world and supply essential water for irrigation, human consumption, and hydroelectricity. Coarse depositional units in alpine watersheds can store and transmit significant volumes of groundwater and thus augment stream discharge during the dry season. These environments are typically data scarce, which has limited the application of physically based models to investigate hydrologic sensitivity to environmental change. This study focuses on a coarse alpine talus unit within the Lake O'Hara watershed in the Canadian Rockies. We investigate processes controlling the hydrologic functioning of the talus unit using field observations and a numerical groundwater flow model driven with a distributed snowmelt model. The model hydraulic parameters are adjusted to investigate how these properties influence the propagation of snowmelt‐induced diurnal signals. The model results expectedly demonstrate that diurnal signals at the talus outlet are progressively damped and lagged with lower hydraulic conductivity and higher specific yield. The simulations further indicate that the lag can be primarily controlled by a higher hydraulic conductivity upper layer, whereas the damping can be strongly influenced by a lower hydraulic conductivity layer along the base of the talus. The simulations specifically suggest that the talus slope can be represented as a two layer system with a high conductivity zone (0.02 m s −1 ) overlying a 10 cm thick lower conductivity zone (0.002 m s −1 ). This study demonstrates that diurnal signals can be used to elucidate the hydrologic functioning and hydraulic properties of shallow aquifers and thus aid in the parameterization of hydrological models.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".