Using Python and Jupyter Notebook to Retrieve and Visualize the Water Temperature Data of the Logan River, Utah

The mainstem Logan River is a suitable habitat for cold-water fishes such as native populations of cutthroat trout (Budy & Gaeta, 2018). On the other hand, high water temperatures can harm cold-water fish populations by creating physiological stresses, intensifying metabolic demands, and limiting suitable habitats (Williams & et al., 2015). In this regard, the State of Utah Department of Environmental Quality (UDEQ) has identified the Logan River as a suitable habitat for cold-water species, which can become unsuitable when the water temperature rises higher than 20 degrees Celsius (Rule R317-2, 2022). However, the UDEQ does not provide any details on how to evaluate the violations from the standard. One way to evaluate violations is to look at water temperature distributions (i.e., histograms) along the river from high elevations to low elevations at different locations. In this report, I used three different Python libraries to manipulate, extract, and explore the water temperature data of the Logan River from 2014 to 2021 obtained from the Logan River Observatory website. The results (i.e., the generated histograms by executing Jupyter Notebook in the HydroShare environment) show that the Logan River tends to experience higher water temperatures as its elevation drops regardless of the season. This can provide some insights for the UDEQ to simultaneously consider space and time in assessing violations from the standard.