Regional variability in stream dissolved organic matter characteristics across forested regions of Canada, and its implications for drinking water treatability
Bibliographic record
Abstract
Forested watersheds are a major source of drinking water for more than two thirds of Canadians. However, drinking water security is increasingly pressured by the combination of higher demands resulting from population growth and industrial development and climate change-exacerbated landscape disturbances (e.g., wildfires, hurricanes). These may lead to deteriorated, more variable source water quality that can challenge treatment operations beyond their response capacities and have the potential to cause service disruptions. The character and concentration of dissolved organic matter (DOM), as well their shifts in response to seasonal and event-based changes in streamflow, make DOM a key driver of drinking water treatment infrastructure needs and operational challenges. As part of the forWater NSERC Network, which seeks to evaluate the impacts of pre-emptive forest management approaches on drinking water treatability in Canada, the objective of this study is to characterize differences in DOM concentrations and composition in headwater streams in different forested regions, including both undisturbed and disturbed catchments, and to evaluate the implications for drinking water treatability. Our pan-Canadian study was conducted using existing long-term research sites, which span an area from 48.5° to 63° N between Canada’s east and west coasts, and represent six major forested ecozones. These ecozones exhibit significant differences in soils, vegetation, hydrological systems, and consequently surface water chemistry. At each research site, 2 to 6 headwater streams were sampled several times in 2019 and 2020 to characterize seasonal and spatial variations in water chemistry. Where relevant, both disturbed (harvested or burned) and undisturbed catchments were sampled. The spatial and temporal variability in DOM characteristics, including the effects of disturbances, were evaluated, and the links between DOM characteristics and drinking water treatability were explored. Distinct regional differences in the concentrations of major ions, dissolved organic carbon and nutrients were observed. Variations in DOM composition, as assessed through UV-vis absorbance and excitation-emission matrix (EEM) fluorescence spectroscopy, Fourier-transform ion cyclotron mass spectrometry (FT-ICR-MS), and asymmetric flow field-flow fractionation (AF4), were also detected. To characterize drinking water treatability, relative implications to coagulant demand, membrane fouling, and distribution system stability were evaluated. The true disinfection by-product formation potential for trihalomethanes and haloacetic acids after complete oxidation resulting from chlorination was also assessed. Collectively, the results of this study underscore the importance of better understanding and anticipating natural variations in stream DOM as well as the impacts of landscape disturbance to ensure the uninterrupted supply of safe drinking water.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".