66 Vegetation Response to Discharge in Red Butte Canyon and Albion Basin

Faculty Mentor: Sara Warix (Geology and Geophysics, University of Utah)

Introduction

Vegetation patterns are shifting in response to a changing climate. These changes affect when and where vegetation green-up periods occur, particularly in sensitive riparian zones. This summer, I analyzed long-term NDVI (Normalized Difference Vegetation Index) trends in two contrasting Utah canyons, Red Butte Canyon and Albion Basin, to explore how vegetation responds to streamflow variability over time. My goal was to assess how changes in discharge, or the amount of water flowing through a watershed, influence riparian vegetation health.

Methods

To conduct this study, I gathered three key datasets for each site: NDVI, stream locations, and discharge measurements. NDVI data was extracted using Google Earth Engine (GEE) with JavaScript, pulling from both Landsat 7 and Sentinel-2 satellite missions. Landsat 7 provided data from 2000 to 2019, while Sentinel-2 filled in the record from 2019 to 2025. After downloading the imagery, I used ArcGIS Pro to clip and map stream features for each watershed, defining riparian buffer zones for analysis.

For discharge, I accessed daily streamflow records from USGS gauging stations. Red Butte Canyon had a local gauge at the base of the watershed, offering highly accurate, site-specific data. Albion Basin lacked a local gauge, so I used a downstream station where Little Cottonwood Creek merges with the Jordan River. While this provided consistent timing patterns, the discharge volumes were likely inflated due to contributions from lower elevations.

Once I collected the necessary data, I developed a Python script to process it and create maps with a buffer zone around the streams to isolate the riparian NDVI data and initiate the data processing.

Results

While NDVI and discharge were not tightly coupled in a direct correlation, long-term NDVI patterns did show meaningful shifts. The NDVI data revealed a shortening of the growing season over time, likely linked to changes in snowmelt timing, temperature, and precipitation dynamics. Red Butte Canyon displayed a longer growing season compared to Albion Basin, which I attribute to its lower elevation, earlier snowmelt, and more stable climate conditions.

Reflection

Through this research, I developed advanced skills in satellite remote sensing, GIS-based spatial analysis, and environmental data processing. I gained confidence using Python and Google Earth Engine to manage large geospatial datasets and became proficient in applying custom symbology and visualization techniques to communicate scientific results clearly. More importantly, I deepened my understanding of riparian ecosystem dynamics and how climate variability can shape vegetation response in mountainous watersheds. This experience has strengthened my interest in environmental science and prepared me for graduate study and future work in GIS and remote sensing.

Bibliography

Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 202, 18–27. https://doi.org/10.1016/j.rse.2017.06.031

Tucker, C. J. (1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8(2), 127–150.

U.S. Geological Survey (USGS). (n.d.). National Water Information System: Web Interface. https://waterdata.usgs.gov