Oxygen 18 fractionation during snowmelt: Implications for spring flood hydrograph separation
Bibliographic record
Abstract
Isotopic hydrograph separation (IHS) to define sources of event and preevent water during hydrological episodes has greatly improved the understanding of water, solute, and contaminant transport to streams during recent decades. However, the large variation in snowmelt isotopic composition, caused by fractionation during melting, has impeded an accurate separation of streamflow during spring flood episodes. Here we present a method that greatly improves the separation of event and preevent water during snowmelt by accounting for both the temporal change in the snowmelt isotopic signal and the temporary storage of meltwater in the catchment. Comparison of results of this technique with previous results, using isotopic data from the 1997 spring flood on a small catchment in northern Sweden, suggests that earlier techniques significantly underestimate the preevent contribution. This paper also explores the importance of lateral mixing across the catchment of temporally varying event inputs for the IHS results.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".