Abstract

Water temperature is an important factor modifying fish distribution patterns and community abundance in streams, and this is especially true for salmonids. Knowing that dams often modify the thermal regime of rivers, understanding these changes is of crucial importance for fish habitat management. This study aims to improve knowledge about the impact of dams on the thermal regime of rivers during the summer season and to assess the relative efficiency of two modelling tools used to predict water temperature downstream of dams. A deterministic model (Stream Network Temperature (SNTEMP)) and a statistical model based on a canonical correlation analysis were calibrated on the Fourchue River (St-Alexandre-de-Kamouraska, Québec, Canada) upstream and downstream of a reservoir. SNTEMP was used to simulate mean water temperature time series using meteorological inputs and discharge. The statistical model was used to directly estimate thermal indices (descriptive statistics of the thermal regime). The two models were compared based on their efficiency to estimate thermal indices such as mean and maximum monthly water temperatures and other parameters of importance in the understanding of the distribution and growth of ichthyofauna. Water temperature was monitored at 18 locations in the Fourchue River during the summers of 2011 and 12 locations in 2012 to describe the thermal regime and calibrate the models. The statistical model achieved better results than SNTEMP in estimating most of the thermal indices, especially the mean and maximum daily ranges with root mean square errors of 4.1 and 4.9 °C, respectively, for SNTEMP as compared to 0.5 and 1.1 °C for the leave-one-out validation and 0.6 and 1.4 °C for the split-sample mode for the statistical model. The better performance of the statistical model for metrics related to thermally stressful events for fish makes it more appealing as a management tool for water resources and fisheries managers. However, SNTEMP should be considered when the objective is to investigate the impact of climate change, reservoir operations or other anthropogenic impacts.

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