Posted on: January 23, 2021
Merging multi-platform sensors , models and artificial intelligence for advanced hydrologic prediction
Dr. Hernan A. Moreno
Thursday, February 25, 2021
Time: Feb 25, 2021 12:30 PM Eastern Time (US and Canada)
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Meeting ID: 818 0797 8651
Video courtesy of NOAA CESSRST via Zoom.
"Hyper-resolution, distributed hydrologic models coupled with high-resolution, distributed information from ground stations and remote sensing (from satellites, radars or intelligent systems) have become an important tool for predicting the behavior of hydrosystems due to the comprehensive capabilities of their process-based representation, accurate results and minimal calibration. The conceptual framework on which these models are built determine their broad applicability to a set of problems such as drought prediction, flood forecasting, water sustainability and watershed responses under climate and land cover changes. Machine learning, as an emerging tool, complement observations and model outputs through big data synthesis, feature elicitation, pattern recognition, clustering and the finding of dynamic data-based mathematical relationships.
"Hernan Moreno is an Assistant Professor at the Department of Earth, Environmental and Resource Sciences at University of Texas- El Paso. Professor Moreno is an Early Career awardee of the Army Research Office in the field of Earth Science and Engineering. He held two post doctoral appointments at Arizona State University and University of Wyoming, and obtained his PhD degree in Civil, Environmental and Sustainable Engineering from Arizona State University".
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