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Air‐Water Temperature Relationships in the Trout Streams of Southeastern Minnesota's Carbonate‐Sandstone Landscape
Authors:Lori A Krider  Joseph A Magner  Jim Perry  Bruce Vondracek  Leonard C Ferrington Jr
Institution:1. Department of Bioproducts and Biosystems Engineering, University of Minnesota, , St. Paul, Minnesota, 55108;2. Department of Fisheries, Wildlife and Conservation Biology, University of Minnesota, , St. Paul, Minnesota, 55108;3. U.S. Geological Survey, Minnesota Cooperative Fish and Wildlife Research Unit, , St. Paul, Minnesota, 55108;4. Department of Entomology, University of Minnesota, , St. Paul, Minnesota, 55108
Abstract:Carbonate‐sandstone geology in southeastern Minnesota creates a heterogeneous landscape of springs, seeps, and sinkholes that supply groundwater into streams. Air temperatures are effective predictors of water temperature in surface‐water dominated streams. However, no published work investigates the relationship between air and water temperatures in groundwater‐fed streams (GWFS) across watersheds. We used simple linear regressions to examine weekly air‐water temperature relationships for 40 GWFS in southeastern Minnesota. A 40‐stream, composite linear regression model has a slope of 0.38, an intercept of 6.63, and R2 of 0.83. The regression models for GWFS have lower slopes and higher intercepts in comparison to surface‐water dominated streams. Regression models for streams with high R2 values offer promise for use as predictive tools for future climate conditions. Climate change is expected to alter the thermal regime of groundwater‐fed systems, but will do so at a slower rate than surface‐water dominated systems. A regression model of intercept vs. slope can be used to identify streams for which water temperatures are more meteorologically than groundwater controlled, and thus more vulnerable to climate change. Such relationships can be used to guide restoration vs. management strategies to protect trout streams.
Keywords:karst hydrology  surface water/groundwater interactions  linear regression models  climate change/variability  rivers/streams  land management
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