Patrick D. Broxton, Ph.D

Associate Research Scientist

Arizona Remote Sensing Center, School of Natural Resources and the Environment, University of Arizona


Phone: 520-626-6568


I am a researcher at the University of Arizona, where I received my M.S. in hydrology and Ph.D in hydrometeorology. I am interested in a broad range of topics related to hydrology, atmospheric science, GIS, and remote sensing. My current research is focused on understanding how snowpack affects streamflow in the semiarid southwestern US and how it might be affected by forest changes due to logging, insect infestations, and fire. As part of my research activities, I like to create useful visualizations of hydrometeologic datasets (see below).

    • I am currently working on a project funded by the Salt River Project, a provider of water and hydropower for millions of customers in central Arizona to understand how streamflows might be impacted by forest thinning along Arizona's Mogollon Rim. As part of this project, I have performed snowpack modeling and created a real-time web-based decision support tool, called "SnowView" to improve SRP's seasonal streamflow forecasts to improve their reservoir operations. The project has also involved substantial collection of field data, including 3-D modeling of snow thickness from Airborne LiDAR from manned aircraft and Structure from Motion using photography from unmanned aircraft, ground based snow surveys, and automatic collection of timeseries of snow depth and other hydrological data.

My other research projects include:

    • helping to design optimal forest treatments to maximize snowpack on the west shore of Lake Tahoe using an energy balance snow model called SnowPALM, which is capable of resolving fine scale forest structure impacts on snow due to its fine spatial resolution (1 m).
    • Evaluating and improving the representation of snow and snow processes in the National Water Model

I have also created datasets that are useful for global weather and climate studies, including as input to high resolution hydrologic and meterological modeling:

    • Most recently, I have created a snow dataset over the conterminous US and used it to evaluate snow in various weather and climate models and analyze snowpack trends across the conterminous US since the early 1980s. This dataset and analysis of snow trends was featured in press releases by UA News and AGU, and was referenced by various media outlets including the New York Times, Tucson Daily Star, Wired Magazine, Pinal Central, Cronkite News, Arizona Public Media (1,2), and others.
    • I have also developed global datasets for vegetation (including a dataset for vegetation greenness and a widely used dataset for land cover type)
    • I helped develop a depth to bedrock dataset

In the past, I have also performed hydrologic studies at field sites in New York's Catskill Mountains and in the Valles Caldera in northern New Mexico.

Web-based Visualizations:

LiDAR data in Google Earth

SnowView - Visualize snow data across the conterminous United States

DroughtView - Map drought and vegetation health across the conterminous United States

  • Structure from Motion Point Clouds