Application of continuous turbidity sensors to supplement estimates of total phosphorus concentrations in the Grand River, Ontario, Canada

Irvine, Cameron A.; Backus, Sean M.; Cooke, Sandra; Dove, Alice; Gewurtz, Sarah B.

Application of continuous turbidity sensors to supplement estimates of total phosphorus concentrations in the Grand River, Ontario, Canada

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dc.contributor.author: Irvine, Cameron A.; Backus, Sean M.; Cooke, Sandra; Dove, Alice; Gewurtz, Sarah B.
dc.date.accepted: 2019-05-08
dc.date.accessioned: 2024-01-24T19:39:06Z
dc.date.available: 2024-01-24T19:39:06Z
dc.date.issued: 2019-08
dc.date.submitted: 2018-11-19
dc.description.abstract - en: Accurate estimates of total phosphorus (TP) loadings to eastern Lake Erie are critical for developing load reduction targets and for determining if commitments are being met under the <i>Great Lakes Water Quality Agreement, 2012</i> (GLWQA). Currently, loading calculations from Canadian priority tributaries are supported by year-round event-focused water quality sampling using automated samplers and laboratory water quality measurements. Here we evaluate the suitability of continuously-measured parameters, namely turbidity and flow, to supplement or enhance knowledge about TP concentrations in the Grand River, ON, by providing continuous data alongside event-focused sample measurements. A series of simple and multiple linear regression models were evaluated and compared with respect to their ability to predict TP water concentrations as a function of different combinations of explanatory variables. Explanatory variables included turbidity, flow, season and flow condition (i.e. hysteresis). The models that performed best explained 63–65% of the variation of TP which is comparable to surrogate model applications in the U. S and elsewhere. Additional model calibration work is needed due to gaps in turbidity data particularly during high flow events. We emphasize the need for continued automated, event-focused water quality sampling. However, provided that operational challenges are overcome, our results indicate that sensor-derived water quality parameters to predict TP concentrations is a promising technique that may supplement and improve nutrient loading estimates in the Grand River into the future and provides guidance for the utilization of this method in other tributaries.
dc.identifier.doi: https://doi.org/10.1016/j.jglr.2019.05.007
dc.identifier.issn: 2773-0719; 0380-1330
dc.identifier.uri: https://open-science.canada.ca/handle/123456789/1896
dc.language.iso: en
dc.publisher: Elsevier
dc.rights - en: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
dc.rights - fr: Creative Commons Attribution - Pas d'utilisation commerciale - Pas de modification 4.0 International (CC BY-NC-ND 4.0)
dc.rights.openaccesslevel - en: Gold
dc.rights.openaccesslevel - fr: Or
dc.rights.uri - en: https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.uri - fr: https://creativecommons.org/licenses/by-nc-nd/4.0/deed.fr
dc.subject - en: Nature and environment; Water; Science and technology
dc.subject - fr: Nature et environnement; Eau; Sciences et technologie
dc.subject.en - en: Nature and environment; Water; Science and technology
dc.subject.fr - fr: Nature et environnement; Eau; Sciences et technologie
dc.title - en: Application of continuous turbidity sensors to supplement estimates of total phosphorus concentrations in the Grand River, Ontario, Canada
dc.type - en: Article
dc.type - fr: Article
local.article.journalissue: 4
local.article.journaltitle: Journal of Great Lakes Research
local.article.journalvolume: 45
local.pagination: 840-849
local.peerreview - en: Yes
local.peerreview - fr: Oui
local.requestdoi: No