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Enregistrement W7017977204

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

2021· dissertation· en· W7017977204 sur OpenAlexaboutno aff

Notice bibliographique

RevueUWSpace (University of Waterloo) · 2021
Typedissertation
Langueen
DomaineEnvironmental Science
ThématiqueAquatic Ecosystems and Phytoplankton Dynamics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésRaw waterWater qualityWater supplyFish killWater treatmentFlood mythWater resourcesWater storageClimate changeStreamflow
DOInon disponible

Résumé

récupéré en direct d'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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Méthodes · Signal consensuel: aucune
Score de désaccord entre enseignants0,005
Score d'incertitude au seuil0,010

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,007
Tête enseignante GPT0,195
Écart entre enseignants0,188 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreMéthodes

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2021
Routes d'admission1
Résumé présentoui

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