Impact of the Horse River wildfire on the form and mobility of particulate phosphorus in a drinking water reservoir: Efficacy of dredging to manage internal phosphorus loading
Bibliographic record
Abstract
Forests are critical source water regions that are under increasing threat of wildfire which can accelerate the transfer of sediment from hillslope to receiving streams and downstream environments such as reservoirs. These pyrogenic materials are often enriched in bioavailable forms of phosphorus (P) that can alter the nutrient status of reservoirs and challenge drinking water treatment and the provision of safe drinking water. The purpose of this study is to examine abiotic controls on the form and mobility of particulate phosphorus (PP) in fine benthic sediment of two drinking water reservoirs in Alberta, Canada with special emphasis on the effects of the 2016 Horse River Wildfire and post-fire dredging. Bottom sediment was collected from wildfire- and non-wildfire-impacted drinking water reservoirs post-wildfire in 2017 and after dredging in 2020. A sequential extraction scheme and bench-top sorption isotherm experiments were conducted to assess the influence of severe wildfire on the form (non-apatite inorganic P, apatite P, organic P) and mobility (equilibrium phosphorus concentration, EPC0) of PP, respectively in these systems. Post-wildfire and post-dredge sediments in the wildfire-impacted reservoir were evaluated to assess the efficacy of dredging as a management technique to control internal P loading in the reservoir. \nTotal particulate P (TPP), bioavailable PP and EPC0 in wildfire-impacted reservoirs were significantly higher than in non-wildfire-impacted reservoirs. Post-dredge sediments had lower concentrations of TPP but a higher proportion of that TPP was total bioavailable P (NAIP) relative to what was observed at initial post-wildfire conditions. The EPC0 of post-dredge sediment was significantly higher compared to initial post-wildfire conditions, which suggests that sediment from the wildfire-impacted drinking water has the potential to act as a long-term source of soluble reactive phosphorus (SRP) to the water column. Due to persistent inputs of external P-enriched wildfire materials from the Athabasca River, one-time dredging is likely not a sufficiently effective strategy for mitigating the effects of internal P loading in the reservoir. Dredging, coupled with other treatment options such as the addition of coagulants and a redesign of the reservoir to reduce sunlight should be further investigated as a more sustainable solution to internal P loading and mitigation of algal blooms in drinking water reservoirs.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".