Venkatesh Merwade

Dr. Venkatesh Merwade is a professor in the Lyles School of Civil Engineering at Purdue University, where he has been since 2006. During 2004 – 2006, he worked as a post-doctoral fellow at the Center for Research in Water Resources at the University of Texas at Austin. Dr. Merwade received his Bachelor of Engineering in Environmental Engineering from Shivaji University, India in 1997, MSc in Engineering Hydrology from the National University of Ireland, Galway, Ireland in 2000, and Ph.D. in Civil Engineering from the University of Texas at Austin, USA in 2004. From 1997-1999, he worked as a project engineer at Montgomery Watson (now part Stantec) in Mumbai, India.
His research and teaching interests include surface water hydrology with specific focus on flood modeling and mapping. Much of his work has been on improving the simulation of hydrologic processes for flood prediction by using geographic information systems (GIS), data driven techniques and advances in cyberinfrastructure. He has authored more than 80 peer reviewed journal articles and conference proceedings in the area of river channels, watershed hydrology and flood modeling. Some of his awards include the Outstanding Achievement Award (2018) from the Indiana Water Resources Association for work related to flood prediction and mapping for Indiana streams, Excellence in GIS Award (2017) from Indiana Geographic Information Council for Soil-Based Floodplain Maps for Indiana, and the Quentin Martin Best Practice Paper (2011) from the ASCE Journal of Water Resources Planning and Management. Dr. Merwade disseminates his educational material as online tutorials, which have been used by tens of thousands of students, faculty and working professionals around the world for learning GIS and hydrologic modeling.

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Computational Watershed Hydrology (edX) EdX
Purdue University,PurdueX

Computational Watershed Hydrology (edX)

Dive into the world of watershed hydrology with our online course, Computational Watershed Hydrology. Gain expertise in analyzing hydrological systems, managing water resources, and applying computational models for effective decision-making. Learn from real observations and geospatial data to understand and model complex watershed processes.

Jan 10th 2022
13-24 Weeks
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