Venkat graduated from University of Roorkee in 1987 with a degree in Civil Engineering and a Doctorate in Civil and Environmental Engineering in 1996 from Princeton University. He is currently the John L Newcomb Professor of Engineering in the Department of Civil and Environmental Engineering at the University of Virginia. He has served as Cox Visiting Professor at Stanford University 2006-2007 and 2015-2016 and Program Director for Hydrologic Sciences at the National Science Foundation (2017-2018). Venkat is a fellow of the American Society of Civil Engineers (ASCE), Geological Society of America (GSA), American Society of Agronomy (ASA), American Association for the Advancement of Science (AAAS), and he has over 200 peer-reviewed articles and around 600 presentations and thesis supervisor for 25 graduate students. He is currently serving as editor for Vadose Zone Journal and the founding editor-in-chief of Remote Sensing in Earth System Science (Springer Journals). He is currently serving as a member of the Water Science and Technology Board, National Academy of Sciences and President of the Hydrology Section of the American Geophysical Union
In order to study land surface hydrology, we need to use a multitude of tools, namely, modeling, observations and their synergism. After multiple decades of hydrological modeling, we still have major challenges. However, we have novel observations and mathematical methods that are now available and can be harnessed to achieve progress. These include earth observations that are available at global scales and at high spatial resolutions and frequent temporal repeat. Artificial Intelligence and Machine Learning (AI/ML) can be used (specifically Transfer Learning) to determine streamflow in un-gaged or poorly-gaged watersheds.
In this talk, I will focus on four major questions and provide examples for each of the questions. These examples will highlight both advances and limitations for each issue.
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Do earth observations compare well with in-situ counterparts?
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2. How important is rainfall in hydrological modeling?
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Can we get higher spatial resolution of earth observations?
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4. How do we study un-gaged/poorly gaged watersheds?