Abrupt weather extremes, changing climate and frequent natural hazards such as floods and droughts create challenges for our nation’s aging reservoir systems.
Abrupt weather extremes, changing climate and frequent natural hazards such as floods and droughts create challenges for our nation’s aging reservoir systems. Tiantian Yang, Ph.D., an assistant professor in the Gallogly College of Engineering at the University of Oklahoma, has received a prestigious Faculty Early Career Development (CAREER) Award from the National Science Foundation to help mitigate these problems.
During the five-year project, Yang will seek to develop an integrated solution that addresses the variability and uncertainty of precipitation and develop a novel artificial intelligence and data mining tool to aid reservoir operators’ decision-making.
“We use machine learning and artificial intelligence tools to detect patterns of precipitation and improve subseasonal-to-seasonal forecasts so that we can better inform the future operation of reservoirs,” Yang said.
Read more at: University of Oklahoma
Tiantian Yang, Ph.D., an assistant professor in the Gallogly College of Engineering, will use a five-year CAREER Award from the National Science Foundation to develop an integrated solution that addresses the variability and uncertainty of precipitation and develop a novel artificial intelligence and data mining tool to aid water reservoir operators’ decision-making. (Photo Credit: University of Oklahoma)
