Local vs. Regional Groundwater Flow Delineation from Stable Isotopes at Western North America Springs
Bibliographic record
Abstract
Abstract The recharge location for many springs is unknown because they can be sourced from proximal, shallow, atmospheric sources or long‐traveled, deep, regional aquifers. The stable isotope ( 18 O and 2 H ) geochemistry of springs water can provide cost‐effective indications of relative flow path distance without the expense of drilling boreholes, conducting geophysical studies, or building groundwater flow models. Locally sourced springs generally have an isotopic signature similar to local precipitation for that region and elevation. Springs with a very different isotopic composition than local meteoric inputs likely have non‐local recharge, representing a regional source. We tested this local vs. regional flow derived hypothesis with data from a new, large springs isotopic database from studies across Western North America in Arizona, Nevada, and Alberta. The combination of location‐specific precipitation data with stable isotopic groundwater data provides an effective method for flow path determination at springs. We found springs in Arizona issue from a mix of regional and local recharge sources. These springs have a weak elevation trend across 1588 m of elevation where higher elevation springs are only slightly more depleted than low elevation springs with a δ 18 O variation of 5.9‰. Springs sampled in Nevada showed a strong elevation‐isotope relationship with high‐elevation sites discharging depleted waters and lower elevation springs issuing enriched waters; only a 2.6‰ difference exists in 18 O values over an elevation range of more than 1500 m. Alberta's springs are mostly sourced from local flow systems and show a moderate elevation trend of 1200 m, but the largest range in δ 18 O , 7.1‰.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".