“I think this is the perfect place for students to learn, for faculty to excel, and for me to develop the next chapter of my academic journey,” says Tiantian Yang, who has joined the faculty at the University of Michigan School for Environment and Sustainability (SEAS) as an associate professor, specializing in Sustainable Systems (SusSys) and Geospatial Data Sciences (GDS). 

Yang, who came to SEAS from the University of Oklahoma (OU), says his research on the interconnection of hydrological science, water resources engineering, weather and climate sciences, and artificial intelligence (AI) will be well-situated here, near the Great Lakes. 

Yang had many detours in his educational training and career path, which led him to where he is now. He earned his bachelor's degree in mechanical and aerospace engineering from Tsinghua University in Beijing, China, with aspirations to become an astronaut. He then went to the University of California, Irvine (UC Irvine), where he earned a master's degree in mechanical and aerospace engineering to continue to work toward his goals.

It was when he decided to pursue a PhD, also at UC Irvine, that he switched gears to civil and environmental engineering with a focus on hydrology and water resources. This first led him to work for a Dutch-based environmental and water resources consulting firm, Deltares, but eventually he decided he wanted to pursue a career in academia, allowing him to work with students while bringing in research to solve real-world problems in hydrology. 

At OU, and now at SEAS, Yang is delving deep into how AI machine learning tools can help with flood forecasting, reservoir and lake planning and management, as well as extreme weather predictions and impacts on natural water systems (i.e., rivers, streams, lakes and ponds), in addition to human-built infrastructures (i.e., channels, levees, hydropower and dams). He says AI is becoming an important tool for systems planning and data analytics in these systems. 

“There is hope that AI can bring in a new management strategy and be more efficient for sustainable surface water management,” says Yang. “We are finding that we might be able to add some physical laws into the architecture of AI tools. Make it more intelligent and capable of understanding the mass conservation of water flows, because it’s important to follow specific hydrologic theories and laws to make predictions and understand data, so that it does not violate the physical law that water will not suddenly appear out of nowhere or disappear within a system, such as a watershed, a reservoir and a given region. I want to focus on the fact that we are the creators of intelligent AI models and meaningful environmental data, not just simply the users of existing tools and information.”

This can lead to powerful and useful outcomes. For example, Yang says that AI can assist farmers with land and irrigation management, helping them know when to pump groundwater or irrigate their land. Still, he says it’s important to be cautious, because the reality is that data centers can threaten water supplies both regionally and globally.

“A lot of data centers are owned by private companies. The water consumption is huge, and this will create a problem for the local water supply because the reservoirs that the water originates from only hold a fixed amount each water year,” he explains. “If the data center consumes a huge part of that fresh water supply, then there is only a very small portion, and not enough left over for the farmers, residents, or other industrial sectors.” 

He adds that the water price is also affected because it becomes more scarce and that, to study this phenomenon, “we need comprehensive data on how a specific center will consume the water, impact the entire water supply system as a whole, and what the environmental impacts are once the fresh water is used to cool down the machines.”

Other water-related issues he’s looking into include aging water and energy infrastructure, and how these infrastructures can deal with more extreme weather events. 

“We need to understand how the climate is changing and how we can redefine the water supply infrastructure—reservoirs, dams, city supply systems—to better cope with the potential impacts of extreme weather.

Yang looks forward to working on these issues when he starts teaching at SEAS in the fall. He is still finalizing the topics, but says they will align with water system planning, water system modeling and optimization, while incorporating AI tools into the curriculum. He says his biggest hope for his students is to help them get closer to their dream career. He wants to share his experience with them and make sure they find what they want to do for the rest of their life.

“I hope that students will always find what they want to do for their career, target that goal, build the skills, enrich their resume and gain the necessary knowledge that can help them move toward their goals,” says Yang.