Short‐term stream water temperature observations permit rapid assessment of potential climate change impacts

Assessment of potential climate change impacts on stream water temperature (Tₛ) across large scales remains challenging for resource managers because energy exchange processes between the atmosphere and the stream environment are complex and uncertain, and few long‐term datasets are available to evaluate changes over time. In this study, we demonstrate how simple monthly linear regression models based on short‐term historical Tₛobservations and readily available interpolated air temperature (Tₐ) estimates can be used for rapid assessment of historical and future changes in Tₛ. Models were developed for 61 sites in the southeastern USA using ≥18 months of observations and were validated at sites with longer periods of record. The Tₛmodels were then used to estimate temporal changes in Tₛat each site using both historical estimates and future Tₐprojections. Results suggested that the linear regression models adequately explained the variability in Tₛacross sites, and the relationships between Tₛand Tₐremained consistent over 37 years. We estimated that most sites had increases in historical annual mean Tₛbetween 1961 and 2010 (mean of +0.11 °C decade⁻¹). All 61 sites were projected to experience increases in Tₛfrom 2011 to 2060 under the three climate projections evaluated (mean of +0.41 °C decade⁻¹). Several of the sites with the largest historical and future Tₛchanges were located in ecoregions home to temperature‐sensitive fish species. This methodology can be used by resource managers for rapid assessment of potential climate change impacts on stream water temperature. Copyright © 2014 John Wiley & Sons, Ltd.