Thermal Sensitivity of Perennial Mountain Springs in the Gibson Jack Watershed
Faculty Mentor Information
Dr. Sarah Godsey, Idaho State University
Presentation Date
7-2025
Abstract
Mountain springs are commonly thought to be reliable, cold, high-quality water sources in semi-arid landscapes like Idaho. However, some springs have been observed to dry during hot summer months. These observations suggest that the capability of a spring to maintain cold water flows throughout the year may vary across the state, but springs are usually excluded from watershed models and no exhaustive inventory of Idaho springs currently exists. This limits accurate predictions of which springs will remain thermally stable. To explore the drivers of thermal sensitivity, we developed an inventory of springs throughout a research watershed, and collected elevation, latitude, longitude, canopy cover, discharge, water temperature, lithology, catchment area, and curvature data at each of the perennial springs. The thermal sensitivity of each spring was calculated by determining the slope of the best-fit line between the daily air temperature and daily water temperature for each spring, and a random forest model was then constructed to predict thermal sensitivity based on the observed characteristics. We found that all random forest models performed poorly, suggesting springs’ thermal sensitivity may have a complex connection between surface and subsurface elements. By understanding the controls of thermal stability in mountain springs, we may be able to more accurately predict environments that could support robust ecosystems and provide cold, reliable, high-quality water in a warming climate.
Thermal Sensitivity of Perennial Mountain Springs in the Gibson Jack Watershed
Mountain springs are commonly thought to be reliable, cold, high-quality water sources in semi-arid landscapes like Idaho. However, some springs have been observed to dry during hot summer months. These observations suggest that the capability of a spring to maintain cold water flows throughout the year may vary across the state, but springs are usually excluded from watershed models and no exhaustive inventory of Idaho springs currently exists. This limits accurate predictions of which springs will remain thermally stable. To explore the drivers of thermal sensitivity, we developed an inventory of springs throughout a research watershed, and collected elevation, latitude, longitude, canopy cover, discharge, water temperature, lithology, catchment area, and curvature data at each of the perennial springs. The thermal sensitivity of each spring was calculated by determining the slope of the best-fit line between the daily air temperature and daily water temperature for each spring, and a random forest model was then constructed to predict thermal sensitivity based on the observed characteristics. We found that all random forest models performed poorly, suggesting springs’ thermal sensitivity may have a complex connection between surface and subsurface elements. By understanding the controls of thermal stability in mountain springs, we may be able to more accurately predict environments that could support robust ecosystems and provide cold, reliable, high-quality water in a warming climate.