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Record W7017977204

Coagulant addition for managing sediment-associated phosphorus bioavailability to prevent cyanobacterial blooms in drinking water reservoirs

2021· dissertation· en· W7017977204 on OpenAlexaboutno aff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2021
Typedissertation
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsRaw waterWater qualityWater supplyFish killWater treatmentFlood mythWater resourcesWater storageClimate changeStreamflow
DOInot available

Abstract

fetched live from OpenAlex

To ensure the uninterrupted supply of adequate amounts of drinking water, many utilities rely on reservoirs for raw (i.e., untreated) water storage prior to treatment. For example, reservoirs are integral to storing water originating as mountain snowpack that melts and slowly releases water to downstream rivers and lakes, serving ~75% of the western United States and Canada and approximately two billion people globally. Although raw water supply reservoirs have been historically managed for water quantity, not quality, reservoir management objectives are rapidly evolving. The importance of reservoir management for source quality is increasing as the relationships between source water quality, treatment costs, finished water quality, and public health protection are better understood, and climate change-exacerbated pressures on that relationship are better described. \n \nWater supply reservoir management is increasingly recognized as an integral component of risk management in the water industry due to the inextricable connection of climate change to source water quality and treatment costs, finished water quality, and public health protection. Multipurpose reservoirs frequently provide seasonal flow equalization, storage during periods of high precipitation (i.e., rain, snow melt), hydroelectric power, and flood mitigation; they also ensure that demand can be met during low flow periods and droughts. Notably, reservoirs are not typically managed for influxes of fine sediment and associated nutrients, which are more frequent in many areas because of climate change-exacerbated landscape disturbances such as wildfires and extreme precipitation. \n \nAlgae, especially cyanobacteria, blooms are one of the biggest threats to water quality and the provision of safe drinking water globally. High densities of algal cells have the potential to lead to customer complaints, service disruptions, and even outages, especially in water treatment plants lacking advanced treatment options. Phosphorus (P) is the limiting nutrient for primary productivity in freshwater. Fine sediment is the primary vector of phosphorus transport in aquatic systems, thus fine sediment management to mitigate or prevent releases of bioavailable P to the water column could be integrated into water treatment operations, potentially as a climate change adaptation strategy. Drinking water reservoirs are not typically designed to manage internal loading of phosphorus; while this has been well studied in lakes, investigations of management strategies such as coagulant addition to prevent phosphorus release from bottom sediments (i.e., phosphorus inactivation) to mitigate the proliferation of cyanobacteria in raw water storage reservoirs are scant. \n \nHere, a series of lab- and field-scale analyses were conducted to (i) describe phosphorus release from fine sediment in a raw water reservoir, (ii) characterize its availability for biological uptake, (iii) evaluate phosphorus inactivation by application of common coagulants (FeCl3, alum, PACl), and (iv) evaluate the combination of strategically-timed reservoir dredging and coagulant application on phosphorus inactivation and turbidity reduction. This study demonstrated that significant amounts of phosphorus were readily released from fine sediment in the study reservoir, suggesting the need for fine sediment management. Application of typical doses of common chemical coagulants, especially FeCl3 effectively inactivated phosphorus to below target thresholds in the presence of fine sediment, as would be expected. Moreover, the combination of reservoir dredging and coagulant application during higher algae risk periods not only inactivated phosphorus, but also eliminated the potential for its re-release to the reservoir water column with the concurrent benefit of turbidity reduction. Thus, this study demonstrated that seasonal coagulant application coupled with strategically-timed reservoir dredging may offer utilities reliant on offline raw water storage reservoirs an effective P inactivation approach for risk management and climate change adaptation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.007
GPT teacher head0.195
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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