GNLCC Regional Stream Temperature Model

A new regional stream temperature modeling project has been initiated with funding from the Great Northern LCC. One of the goals of the project is to compile existing stream temperature data from federal, state, tribal, and private sources across the five state region that comprises the US portion of the GNLCC. These data will be developed into a comprehensive, integrated regional database that is made available to all interested parties. The stream temperature database will also be used with new spatial statistical models for river networks to develop an accurate regional model capable of predicting stream temperatures for all fish-bearing streams. The model will be used to simulate a variety of historic and future climate scenarios and to assess effects on the distributions of thermal habitat for multiple aquatic species. Spatially continuous maps of stream temperature predictions and thermal habitats will be made available as GIS layers at the end of this project to assist in conservation and management planning.

The first phase of this project is simply assembling the database of stream temperature information from the many sources across the GNLCC. For those interested in learning more about the project or possibly contributing temperature data, please visit the project website http://nrmsc.usgs.gov/gnlcc/str_tempDB, where detailed instructions for data submissions, project boundaries, methodologies, and contact information are provided below.

For more information about the project, please contact:

Dan Isaak (disaak@fs.fed.us ; 208.373.4385)
Jeff Kershner (jkershner@usgs.gov ; 406.994.5304)
Jason Dunham (jdunham@usgs.gov ; 541.750.7397)

Maps showing status of temperature database by state

	Montana		Wyoming
	Idaho		Oregon
	Washington

Air Temperature Based Thermal Stream Habitat Model 

This model was developed for predictions across the interior Columbia River basin in the Pacific Northwest.  The model predicts the distribution of thermally suitable habitat for bull trout by incorporating air temperature, elevation, latitude, and longitude.

Spatial Statistical Stream Temperature Model

This stream temperature modeling approach uses thermograph data and the predictor variables: air temperature, solar radiation, elevation, and stream flow. GIS and spatial statistical models that account for network topology were used to predict stream temperatures at 1 km intervals throughout a 2,500 km river network.

Multiple Regression Stream Temperature Model

This modeling approach uses thermograph records and a simple set of geomorphic predictor variables derived from digital elevation models (DEM).  A multiple regression model and GIS are used to predict stream temperatures for individual reaches throughout a river network.