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Surface Water Hydrology, Hydrologic Modeling, Hydrologic Information Systems, Terrain Analysis in Hydrology, Stochastic Hydrology, and Snowmelt.  My research crosses the disciplinary interface between hydrology and information technology. I focus on advancing the capability for hydrologic prediction by developing models that take advantage of new information and process understanding enabled by new technology. I strive to synthesize modeling and numerical analysis with field observations and hydrologic information systems and tailor software and computing systems to the needs of hydrologists.

I lead the development of HydroShare (www.hydroshare.org), a hydrologic information system for sharing hydrologic data and models operated by the Consortium of Universities for the Advancement of Hydrologic Science, Inc.  HydroShare is a platform for users to share and publish data and models in a variety of flexible formats, and to make this information available in a citable, shareable and discoverable manner in support of transparent and reproducible science. Hydroshare also includes tools (web apps) that can act on content in HydroShare providing users with a gateway to computing and analysis.  I also work on terrain analysis for hydrology, terrain stability mapping and stream sediment inputs, geomorphology, stochastic and nonparametric statistical methods in hydrology, and snow hydrology. My group has developed and supports open source software packages implementing many of the research capabilities developed.  This includes the Terrain Analysis using Digital Elevation Models (TauDEM) package for derivation of hydrologic information from digital elevation models, and the Utah Energy Balance snowmelt model. 

My work includes the use of Geographic Information Systems to take advantage of spatially distributed information for hydrologic prediction.  I believe that models serve as a way to codify and make precise our understanding as well as apply this understanding to practical and management purposes. My general approach to research focuses on the following objectives:

  • Development of a sound physical understanding of the processes involved.
  • Incorporation of this physical understanding into concise parameterizations of the important processes.
  • Development of precise representations of the physical environment and information system tools for using this representation in numerical models.
  • Recognition of nonlinearity, physical feedbacks and interactions which lead to interesting behavior which needs to be understood.
  • Recognition of heterogeneity and spatial variability. The development of techniques (often statistical) to account for heterogeneity and spatial variability.

Current Projects

Completed Projects