Use of major ion and stable isotope geochemistry to delineate natural and anthropogenic sources of nitrate and sulfate in the Kettle River Basin, British Columbia, Canada
Bibliographic record
Abstract
The Kettle River Basin in South central British Columbia (Canada) is under increasing anthropogenic pressures affecting both water quantity and quality of surface waters and aquifers. We investigated water quality and sources and processes influencing NO 3 – and SO 4 2– in the Kettle River Basin using a combination of chemical and isotopic techniques. The dominant water type in the Kettle River Basin is Ca–HCO 3 with surface waters having total dissolved solids (TDS) concentrations of < 115 mg/L and groundwaters having TDS values of up to 572 mg/L. Based on δ 15 N NO 3 and δ 18 O NO 3 values and concentration data, NO 3 – in surface waters originates primarily from natural soil nitrification processes, with additional influences from anthropogenic activities, such as waste water effluents at sampling locations downstream from population centres. The source of NO 3 – in groundwater was predominantly nitrification of soil organic matter, although nitrate in a few groundwater samples originated from anthropogenic sources, including manure or septic systems. The dominant source of SO 4 2– in surface water and groundwater samples was the natural oxidation of sulfide minerals. With increasing distance downstream, surface water δ 18 O SO 4 values increase beyond the range of oxidation of sulfide minerals and into the range of soil and atmospheric-derived SO 4 2– that is in part derived from anthropogenic emissions. Hence, we conclude that recent anthropogenic impacts have affected water quality only marginally at only few sites in the Kettle River Basin. The presented data will serve as an excellent baseline against which future impacts can be assessed.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".