Coagulant addition for managing sediment-associated phosphorus bioavailability to prevent cyanobacterial blooms in drinking water reservoirs
Notice bibliographique
Résumé
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.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».