Journal
CANADIAN WATER RESOURCES JOURNAL
Volume 36, Issue 2, Pages 171-191Publisher
TAYLOR & FRANCIS INC
DOI: 10.4296/cwrj3602849
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Funding
- Natural Sciences and Engineering Research Council of Canada (NSERC)
- Newfoundland and Labrador Department of Environment and Conservation
- Institute for Biodiversity, Ecosystem Science and Sustainability (IBES)
- School of Graduate Studies at Memorial University
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In this paper regression models are developed for predicting water temperature and the concentration of dissolved oxygen in rivers monitored by the Newfoundland and Labrador Real-Time Water Quality Monitoring (RTWQM) network. The developed models can be used to predict mean, maximum and minimum water temperatures and dissolved oxygen at the monthly, weekly and daily time scales. A nonlinear logistic model is found to best represent the S-shaped relationship between water temperature at the real-time stations and air temperature collected from meteorological stations 5-50 kilometers away. There is a clear tendency for monthly and weekly models to be more accurate for prediction than the daily models. Both linear and nonlinear exponential decay models were found to best represent the relationship between water temperature and dissolved oxygen at the real-time stations. A novel graphical method of linking air temperature to water temperature and dissolved oxygen has been developed and may prove to be a valuable simple tool in the assessment of the health of the rivers in the real-time network.
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