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Predicting river water temperatures using the equilibrium temperature concept with application on Miramichi River catchments (New Brunswick, Canada)

✍ Scribed by Daniel Caissie; Mysore G. Satish; Nassir El-Jabi


Book ID
102265477
Publisher
John Wiley and Sons
Year
2005
Tongue
English
Weight
335 KB
Volume
19
Category
Article
ISSN
0885-6087

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✦ Synopsis


Water temperature influences most of the physical, chemical and biological properties of rivers. It plays an important role in the distribution of fish and the growth rates of many aquatic organisms. Therefore, a better understanding of the thermal regime of rivers is essential for the management of important fisheries resources. This study deals with the modelling of river water temperature using a new and simplified model based on the equilibrium temperature concept. The equilibrium temperature concept is an approach where the net heat flux at the water surface can be expressed by a simple equation with fewer meteorological parameters than required with traditional models. This new water temperature model was applied on two watercourses of different size and thermal characteristics, but within a similar meteorological region, i.e., the Little Southwest Miramichi River and Catamaran Brook (New Brunswick, Canada). A study of the long-term thermal characteristics of these two rivers revealed that the greatest differences in water temperatures occurred during mid-summer peak temperatures. Data from 1992 to 1994 were used for the model calibration, while data from 1995 to 1999 were used for the model validation. Results showed a slightly better agreement between observed and predicted water temperatures for Catamaran Brook during the calibration period, with a root-mean-square error (RMSE) of 1Ð10 °C (Nash coefficient, NTD D 0Ð95) compared to 1Ð45 °C for the Little Southwest Miramichi River (NTD D 0Ð94). During the validation period, RMSEs were calculated at 1Ð31 °C for Catamaran Brook and 1Ð55 °C for the Little Southwest Miramichi River. Poorer model performances were generally observed early in the season (e.g., spring) for both rivers due to the influence of snowmelt conditions, while late summer to autumn modelling performances showed better results.


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