Praveen Kumar

University of Illinois, Urbana Champaign

Praveen Kumar holds a B.Tech. (Indian Institute of Technology, Bombay, India 1987), M.S. (Iowa State University 1989), and Ph.D. (University of Minnesota 1993), all in civil engineering, and has been on the UIUC faculty since 1995.  He is also an Affiliate Faculty in the Department of Atmospheric Science.  His research focus is on complex hydrologic systems bridging across theory, modeling, and informatics. He presently serves as the Director of the NSF funded Critical Zone Observatory for Intensively Managed Landscapes, which is part of a national and international network. He has been an Associate of the Center for Advanced Studies, and two-times Fellow of the National Center for Super Computing Applications. He is an AGU Fellow and the recipient of the Xerox Award for Research, and Engineering Council Award for Excellence in Advising. From 2002-2008, he served as a founding Board member for CUAHSI, a consortium of over 110 universities for the advancement of hydrologic science. From 2009-2013 he served as the Editor-in-Chief of Water Resources Research, the leading journal in the field with about 500 published articles per year. Prior to that he also served as the Editor of Geophysical Research Letters, a leading journal for inter-disciplinary research.

Simulation Based Exploration of Critical Zone Dynamics

The advent of high-resolution measurements of topographic and (vertical) vegetation features using areal LiDAR are enabling us to resolve micro-scale (~1m) landscape structural characteristics over large areas. Availability of hyperspectral measurements is further augmenting these LiDAR data by enabling the biogeochemical characterization of vegetation and soils at unprecedented spatial resolutions (~1-10m). Such data have opened up novel opportunities for modeling Critical Zone processes and exploring questions that were not possible before.  We show how an integrated 3-D model at ~1m resolution can enable us to resolve micro-topographic and ecological dynamics and their control on hydrologic and biogeochemical processes. We address the computational challenge of such detailed modeling by exploiting hybrid CPU and GPU computing technologies. We show results of moisture, biogeochemical, and vegetation dynamics from studies in the Critical Zone Observatory for Intensively managed Landscapes (IMLCZO) in the Midwestern United States.

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