Advances in Streamflow Forecasting at Hourly to Seasonal Scales under Changing Climate

Moderator(s)

• LK

  Levent Kavvas

  Distinguished Professor
  University of California, Davis
  UC Davis

Presentations:

• 3:00 PM – 3:15 PM PDT

  An Uncertainty-Aware, Machine Learning-Enabled Reservoir Inflow Forecast Model
  

  Author: Dan Lu – Oak Ridge National Laboratory

  Co-Author: Sudershan Gangrade, Ph.D. – Oak Ridge National Laboratory

  Co-Author: Shih-Chieh Kao, Ph.D. – Oak Ridge National Laboratory
• 3:15 PM – 3:30 PM PDT

  Can Unmanned Aerial Vehicles be the way forward for urban hydrology?
  

  Author: Rubab Saher – Desert Research Institute, Las Vegas

  Co-Author: Ariane Middel – Arizona State University
• 3:30 PM – 3:45 PM PDT

  Machine learning derived streamflow projections in the presence of climate change
  

  Author: Abhinav Gupta – Desert Research Institute
• 3:45 PM – 4:00 PM PDT

  An Appraisal of Machine and Deep learning Techniques to Forecast Streamflow in a Snow-Dominant Catchment
  

  Author: Savalan Naser Neisary, Ph.D. Student (he/him/his) – University of Alabama

  Co-Author: Danyal Aziz, Ph.D. Student – University of Alabama

  Co-Author: Md Shahabul Alam (he/him/his) – Alabama Water Institute

  Co-Author: Steven J. Burian, PE – Alabama Water Institute
• 4:00 PM – 4:15 PM PDT

  WEHY modeling and its sensitivity to precipitation field input: A case study from Cottonwood Creek Watershed.
  

  Author: Felipe E. Ulloa Henriquez – University of California, Davis

  Co-Author: Yoshihiko Iseri, PhD – University of California, Davis

  Co-Author: Levent M. Kavvas – University of California, Davis