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

Assessment of potential climate change impacts on stream water temperature (T-s) 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 T-s observations and readily available interpolated air temperature (T-a) estimates can be used for rapid assessment of historical and future changes in T-s. Models were developed for 61 sites in the southeastern USA using 18months of observations and were validated at sites with longer periods of record. The T-s models were then used to estimate temporal changes in T-s at each site using both historical estimates and future T-a projections. Results suggested that the linear regression models adequately explained the variability in T-s across sites, and the relationships between T-s and T-a remained consistent over 37years. We estimated that most sites had increases in historical annual mean T-s between 1961 and 2010 (mean of +0.11 degrees C decade(-1)). All 61 sites were projected to experience increases in T-s from 2011 to 2060 under the three climate projections evaluated (mean of +0.41 degrees C decade(-1)). Several of the sites with the largest historical and future T-s changes 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 (c) 2014 John Wiley & Sons, Ltd.