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Challenges of modelling water quality in a shallow prairie lake with seasonal ice cover

•Ice model sensitive to ending albedo values.•Variable albedo rate influences timing of spring bloom.•Great uncertainty in modelling a shallow lake. The link between under ice processes and open water eutrophication dynamics has been proven in the field. Water quality models still lack the capabilit...

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Bibliographic Details
Published in:Ecological modelling 2018-09, Vol.384, p.43-52
Main Authors: Terry, Julie A., Sadeghian, Amir, Baulch, Helen M., Chapra, Steven C., Lindenschmidt, Karl-Erich
Format: Article
Language:English
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Summary:•Ice model sensitive to ending albedo values.•Variable albedo rate influences timing of spring bloom.•Great uncertainty in modelling a shallow lake. The link between under ice processes and open water eutrophication dynamics has been proven in the field. Water quality models still lack the capability to capture the connection between both environments. The hydrodynamic-ecological model CE-QUAL-W2 is being applied to a eutrophic drinking water reservoir on the Canadian Prairies as part of larger collaborative research project. CE-QUAL-W2 is one of the few water quality models that includes an ice algorithm, yet is restricted by a fixed albedo coefficient. Field studies have shown albedo to change through the ice cover season – varying the solar radiation that reaches the ice-water interface as a result. In order to better represent the light and heat environment during the under ice periods we modify the ice algorithm to incorporate a variable albedo rate. While assessing the modified version of CE-QUAL-W2 on the reservoir we encounter a number of challenges during the calibration process. These challenges pertain to difficulties with modelling the under ice environment, and with modelling shallow lakes and reservoirs. We recommend a targeted monitoring program to supplement available data that will reduce the uncertainty associated with the results of the reservoir model.
ISSN:0304-3800
1872-7026
DOI:10.1016/j.ecolmodel.2018.06.002