2017
DOI: 10.3390/w9020131
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Modelling Dissolved Oxygen/Sediment Oxygen Demand under Ice in a Shallow Eutrophic Prairie Reservoir

Abstract: Dissolved oxygen is an influential factor of aquatic ecosystem health. Future predictions of oxygen deficits are paramount for maintaining water quality. Oxygen demands depend greatly on a waterbody's attributes. A large sediment-water interface relative to volume means sediment oxygen demand has greater influence in shallow systems. In shallow, ice-covered waterbodies the potential for winter anoxia is high. Water quality models offer two options for modelling sediment oxygen demand: a zero-order constant rat… Show more

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Cited by 43 publications
(22 citation statements)
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References 26 publications
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“…Dissolved oxygen (DO) is important for all forms of life (Terry et al, 2017). Low DO in the water can cause physiological stress for fish and macroinvertebrates.…”
Section: Dissolved Oxygenmentioning
confidence: 99%
“…Dissolved oxygen (DO) is important for all forms of life (Terry et al, 2017). Low DO in the water can cause physiological stress for fish and macroinvertebrates.…”
Section: Dissolved Oxygenmentioning
confidence: 99%
“…Akomeah et al [52] and Terry et al [53] both used surface water quality models to investigate the water quality of ice-covered water bodies, the former concentrating on a river and the latter on a lake within the Qu'Appelle river-lake system on the Canadian Prairies. Both studies are initial steps in larger projects to investigate the dynamics of dissolved oxygen concentrations and sediment oxygen demand during the winter seasons.…”
Section: Water Qualitymentioning
confidence: 99%
“…This rate was selected based on similar studies at nearby catchments and reported values which ranged from 0.1/day to 0.2/day [32,38].…”
Section: Initial Conditionmentioning
confidence: 99%
“…At a low water quality model complexity, like the Streeter and Phelps dissolved oxygen balance, other process parameters are constrained, allowing models to be properly calibrated to few parameters. Building a model by gradually adding complexity is a strategy adopted by some modelers [32]. Complex models increase the number of processes being modeled, the output variables, and parameters [32].…”
Section: Introductionmentioning
confidence: 99%
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