Strategies for karst groundwater flow characterization in remote, mountainous, snowmelt-dominated catchments
Bibliographic record
Abstract
The Front Ranges of the Canadian Rockies are home to extensive carbonate assemblages that host karst aquifers. New caves and karst springs have recently been discovered in the mountains from Banff, Alberta extending all the way to the United States border, although little research has been conducted on them due to the challenging terrain. In this study, we focus on the Watridge Karst Spring, which is located on a forested hillside in a mountain range that reaches an elevation of 3400 m. This perennial spring can discharge up to 3000 L/s. Karst catchments in these snowmelt-dominated, glacierized areas have sparse vegetation, heavy snowfall, and high hydraulic gradients, leading to efficient groundwater infiltration. As a result, the hydrochemistry of these springs often exhibits strong and rapid fluctuations. The effects of rapid conduit flow are expressed at the Watridge Karst Spring by an increase in discharge followed by a lagged decrease in electrical conductivity (EC), occurring over a diurnal-scale and a longer-scale (e.g., episodic snowmelt or heavy storm). This research aims to use hydrologically relevant metrics to understand the recharge, flow paths, and storage capacity of the aquifer. Particularly, we used signal processing of the fluctuations in discharge, EC and air temperature to estimate groundwater response time, defined here as the lag time between a hydrologic event and a resulting change in hydrochemistry. Response time can be used to approximate celerity in the case of discharge, and velocity in the case of EC. Additionally, automatic water sampling allowed for the observation of rapid changes in major ion chemistry.The results yielded an estimated groundwater conduit velocity on the order of 0.1 m/s that steadily decreases with diminishing flow. It was also found that a distinct shift in the EC signal phase and an associated change in mineral dissolution marks the drainage of an overflow conduit path. This is supported by dye tracer experiments of up to 14 km distance where a maximum velocity of 0.14 m/s has been recorded. Our results show that continuous hydrochemical monitoring of discharge and meteorological conditions at a high-temporal resolution can be used as a first step in characterizing conduit system response. For alpine karst springs with strong hydrochemical fluctuations, this strategy may limit the need to conduct tracer tests involving laborious field work in remote, mountainous locations.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".