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Beschta, R.L., Bilby, R.E., Brown, G.W., Holtby, L.B. and Hofstra, T.D. (1987) Stream Temperature and Aquatic Habitat: Fisheries and Forestry Interactions. In: Salo, E.O. and Cundy, T.W., Eds., Streamside Management: Forestry and Fishery Interactions, University of Washington, Institute of Forest Resources, Seattle, Contribution No. 57, 191-232.

has been cited by the following article:

• TITLE: Predicting Hourly Stream Temperatures Using the Equilibrium Temperature Model

  AUTHORS: Cindie Hébert, Daniel Caissie, Mysore G. Satish, Nassir El-Jabi

  KEYWORDS: Stream Temperature, Modeling, Equilibrium Temperature

  JOURNAL NAME: Journal of Water Resource and Protection, Vol.7 No.4, March 13, 2015

  ABSTRACT: Water temperature is a key physical habitat determinant in lotic ecosystems as it influences many physical, chemical and biological properties of rivers. Hence, a good understanding of the thermal regime of rivers is essential for effective management of water and fisheries resources. This study deals with the modeling of hourly stream water temperature using the equilibrium temperature model. This water temperature model was applied on two thermally different watercourses, namely, the Little Southwest Miramichi River (LSWM) and Catamaran Brook (CatBk; New Brunswick). The equilibrium temperature model is a simplified version of a deterministic model. As such, in the equilibrium temperature model the total heat flux at the surface is assumed proportional to the difference between the water temperature and an equilibrium temperature. In the present study, the equilibrium temperature was assumed to vary linearly with hourly air temperature. This study showed that there was a good relationship between the equilibrium and air temperature at the hourly time scale. The root-mean-square error (RMSE) obtained with the hourly equilibrium temperature model was similar to results reported in previous studies with values of 1.05°C (CatBk) and 1.36°C (LSWM). The model’s performance was best in late summer and autumn when water levels were low. In contrast, the presence of snowmelt in the spring resulted in poorer performances. This study also showed good results in estimating the daily mean (Tmean) and maximum (Tmax) water temperatures from the predicted hourly water temperatures, which were often required in fishery management.