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A comprehensive picture of the spatial and temporal patterns of river thermal regimes requires temperature recorded over continuous long time series and across various environments. Unfortunately, these data are generally scarce in extended areas. In Canada, the first attempt to a general large-scale characterization of river thermal regimes was done using a standardized three-parameter Gaussian function and continuous temperature records collected in 158 Québec rivers. This model provided estimates of the river temperature annual maximum, the date of the annual maximum occurrence and the duration of the warm season, with confidence intervals linked to the duration of the available time series. This resulting thermal map was however limited spatially by the geographical location of the monitoring stations, restricted to the eastern portion of the province. It was also based on relatively short and recent temperature series, with most records shorter than five years and starting after 2010. In this work, we expanded both the space and time spans of the Québec rivers thermal map by adding new temperature data sources, namely satellite thermal data and spot measurements. Satellite data provided thermal information in remote northern regions where  in situ  data acquisition is difficult, from early 1980s until today. Spot measurements from the Banque de données sur la qualité des milieux aquatiques allowed to add nearly 250 rivers to the Québec thermal regimes characterization, with several stations operating since 1979. These three data sources were combined to characterize Québec rivers thermal regimes in more than 400 rivers and streams, over an extended geographical distribution. Uncertainty brought by the coarser temporal resolution of the spot and combined time series was assessed and found to result in substantially larger confidence intervals on the estimated model parameters, as compared with the confidence intervals obtained when using continuous time series of similar length.

Modeling of the thermal regime of rivers subject to seasonal ice cover using data from different sources and temporal resolutions