Towards adaptive reservoir operation: Applications of artificial intelligence and subseasonal-to-seasonal (S2S) forecasts

Department of Hydrology and Atmospheric Sciences
 
4 pm Thursday, April 28, 2022
Available via zoom
 
Contact the department for details or to subscribe to the email list
 
Tiantian Yang
Assistant Professor, School of Civil Engineering and Environmental Science, University of Oklahoma

Abstract

Reservoirs are fundamental, human-built, multi-functional water infrastructures that collect, store, and deliver fresh surface water for a multitude of uses, including flood and fire control, recreation, wildlife habitat, residential, industrial, and agricultural water supply, hydro-electric power generation, supply source during droughts, and more. The reservoir release decisions directly influence various aspects of social-economic functioning and our nation’s security. In recent years, more frequent and severe abrupt weather extremes, climate change, natural hazards, aging infrastructure, and increases in water demands due to population growth, has placed another great barrier preventing effective, sustainable, and flexible operation of our nations’ reservoir systems. Therefore, new technologies and data are essentially needed for improving the reservoir operation and the management of water infrastructures in our nation.

In this talk, Dr. Tiantian Yang will introduce his past and current research on applying advancing Artificial Intelligence and Data Mining (AI&DM) tools in support of reservoir operation under different problem settings and research focuses. The uses of AI&DM tools are further extended to solving other classical hydrology and environmental engineering problems, such as rainfall-runoff simulations and removing biases associated with the outputs from various weather and climate models. Some recent research on evaluating Subseasonal-to-Seasonal (S2S) precipitation forecasts and improving extremes predictions, supported by the NSF EPSCoR Track 1 program and the US Army Corps’ Engineering With Nature program, will help reservoir operators and local utility agencies to adjust their operation strategies and to decide when and how much reservoir releases are needed to better prepare for potential water supply shortages and flooding events.

Bio

Dr. Tiantian Yang is currently a tenure-track assistant professor from the School of Civil Engineering and Environmental Science (CEES) at the University of Oklahoma (OU), and associate director of the OU Hydrology & Water Security (HWS) online master’s degree program. Before joining the University of Oklahoma, Dr. Yang was a research scientist/ hydrologist at Deltares (the former of Delft Hydraulics, Netherland). Dr. Yang obtained his Ph.D. degree in Civil Engineering from the Department of Civil and Environmental Engineering (CEE) of the University of California Irvine (UC Irvine), mentored by Distinguished Professor Soroosh Sorooshian at the Center for Hydrometeorology and Remote Sensing (CHRS). Yang has a master’s degree from the Department of Mechanical Engineering at UC Irvine and a bachelor's degree in Mechanical Engineering from Tsinghua University, China.