John Kemper

Title: Researcher

Institution: Utah State University

Address: 5210, BNR 269, Logan, Utah 84322

Email: john.kemper@usu.edu

Phone: (267) 566-4303

Visit John’s Research Website

Research Interests: Geomorphology, sediment transport, large wood, post-wildfire erosion, water quality (phosphorus and salinity)

View John’s CV


Biographical Sketch:

I am a fluvial geomorphologist and watershed scientist who studies the transport of material – water, sediment, wood, nutrients, etc. – through river basins to understand how river landscapes act, react, and evolve as connected networks of processes. In general, I am interested in understanding how watersheds respond to and recover from disturbances, and how we might better predict and forecast vulnerability to (and following) disturbance. My work seeks to yield knowledge that has tangible management and operational implications, such as understanding where and when downstream communities and infrastructure may be threatened following wildfire and how we might manage burned watersheds to reduce those risks and encourage swift recovery.

My research primarily uses field-based measurements and sampling in conjunction with lab analyses and advanced computational techniques like machine learning to understand how watersheds react to disturbances across time and space. I have extensive experience as a field geomorphologist collecting data to answer big geomorphological questions, and expertise using machine learning techniques to better understand the patterns and processes reflected in that data.


Education:

Ph.D. from Colorado State University (Fort Collins, CO), 2022

M.S. from University of Maryland Baltimore County (Baltimore, MD), 2017

B.S. from University of Maryland (College Park, MD), 2013

Professional Certifications:

Wilderness First Responder (NOLS Wilderness Medicine)


Other Research:

  • Post-processing National Water Model Output with Spatially Distributed Turbidity Sensing to Forecast Turbidity Loading and Source for Reservoir Operation Management
  • Coupling spatially distributed nutrient monitoring and National Water Model output to forecast nutrient loading and inform implementation of EPA mandated nutrient reduction targets

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