Publication Date:
2014-10-14
Description:
Assessment of potential climate change impacts on stream water temperature (T〈inf〉s〈/inf〉) 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〈inf〉s〈/inf〉 observations and readily available interpolated air temperature (T〈inf〉a〈/inf〉) estimates can be used for rapid assessment of historical and future changes in T〈inf〉s〈/inf〉. 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〈inf〉s〈/inf〉 models were then used to estimate temporal changes in T〈inf〉s〈/inf〉 at each site using both historical estimates and future T〈inf〉a〈/inf〉 projections. Results suggested that the linear regression models adequately explained the variability in T〈inf〉s〈/inf〉 across sites, and the relationships between T〈inf〉s〈/inf〉 and T〈inf〉a〈/inf〉 remained consistent over 37years. We estimated that most sites had increases in historical annual mean T〈inf〉s〈/inf〉 between 1961 and 2010 (mean of +0.11°C decade-1). All 61 sites were projected to experience increases in T〈inf〉s〈/inf〉 from 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 T〈inf〉s〈/inf〉 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. © 2014 John Wiley & Sons, Ltd.
Print ISSN:
0885-6087
Electronic ISSN:
1099-1085
Topics:
Architecture, Civil Engineering, Surveying
,
Geography
