Rate My Professor Patricia Broxton

Broxton's primary research focus is snow hydrology, encompassing snow-forest interactions, snow mapping, snow modeling, mountain ecohydrology, and seasonal to subseasonal streamflow forecasting. She examines how snowpack dynamics affect streamflow in semiarid southwestern U.S. watersheds and the influences of forest changes from thinning, insect infestations, fires, and climate variability. Notable contributions include developing and maintaining the real-time gridded University of Arizona Snow Water Equivalent (UA SWE) dataset from 1981 to present at 4 km resolution for the conterminous U.S., integrating snowfall, accumulation, and remote sensing data. She creates decision support tools and visualizations for hydrometeorologic monitoring, employs machine learning with Sentinel-1, Airborne Snow Observatory, and UA snowpack data to enhance mountain snowpack estimation, and uses lidar and structure-from-motion techniques for fine-scale forest structure analysis impacting snow budgets. Key publications feature 'Snowpack change from 1982 to 2016 over conterminous United States' (2018), 'Quantifying the effects of vegetation structure on snow accumulation and ablation in mixed-conifer forests' (2015), 'A global land cover climatology using MODIS data' (2014), 'Improving Mountain Snowpack Estimation Using Machine Learning with Sentinel-1, Airborne Snow Observatory, and University of Arizona Snowpack Data' (2024), 'Forest Patch Geometry and Climate Regulate The Impact of Forest Thinning on Snowpack in the Southwest U.S.' (2025), 'Snow Simulation for the Rangeland Hydrology and Erosion Model' (2024), and 'Subseasonal to Seasonal Streamflow Forecasting in a Semiarid Watershed' (2023). She teaches Renewable Natural Resources (RNR 696A) and her work, cited over 3,000 times, informs water resource management amid climate change.