Dr. Tiantian Yang’s research explores how we can better understand, predict, and manage water in a rapidly changing world. His work sits at the intersection of hydrology, water resources engineering, climate science, and artificial intelligence, focusing on how weather extremes, climate change, subseasonal-to-seasonal precipitation forecasts, and human decisions influence the sustainability and resilience of hydrologic and surface water systems. These systems include rivers, streams, lakes, ponds, reservoirs, and dams that support essential services such as drinking water supply, flood protection, agriculture, clean energy production through hydropower, and ecosystem services.

A major goal of Dr. Yang’s research is to develop next-generation tools that help society make smarter and more intelligent water management and planning decisions. His group investigates how emerging artificial intelligence technologies, such as Deep Learning architectures and large language models (LLMs), can improve hydrologic modeling, river and flood forecasting, reservoir and lake operations, and water–energy–food system planning and management. By combining modern AI methods with traditional physical models and understanding of hydrologic processes, the research aims to build reliable and interpretable models and data that can support real-world water and infrastructure decision making under weather and climate uncertainties.

Applications of Dr. Yang's research span a wide range of critical environmental systems and challenges, including flood forecasting, extreme rainfall and hurricane prediction, drought risk assessment, climate variability and subseasonal-to-seasonal weather prediction, and improving climate model projections of precipitation and temperature. These efforts contribute to better disaster preparedness, more resilient water infrastructure, and sustainable resource management under climate change.

Students working with Dr. Yang will have the opportunity to engage in interdisciplinary research that integrates hydrology, climate science, artificial intelligence, and water systems engineering. The research group collaborates closely with federal agencies, national laboratories, and universities to translate scientific advances into operational tools for water management. Students gain hands-on experience in cutting-edge modeling, high-performance computing, and interdisciplinary collaboration, while also participating in the broader scientific community through conference presentations and journal publications. Dr. Yang is also serving as editor and associate editor for many journal homes, including Journal of Hydrology, Environmental Modeling and Software, Journal of Hydrometeorology, Journal of Applied Meteorology and Climatology, Atmospheric Research, Journal of Hydroinformatics, Journal of Water Resources Planning and Management, and Artificial Intelligence for the Earth Systems.