CUAHSI Board Spotlight with Tao Wen
Posted Mar 10, 2026
Tao Wen, Assistant Professor, Department of Earth and Environmental Sciences, Syracuse University
It is a privilege to join the CUAHSI Board of Directors and contribute to a community that has played such an important role in advancing hydrologic science. I am an Assistant Professor in the Department of Earth and Environmental Sciences at Syracuse University, where I lead the Hydrogeochemistry And eNvironmental Data Sciences (HANDS) and Noble Gases in Earth Systems Tracing (NEST) Research Laboratories. My research integrates hydrology, geochemistry, and environmental data science to better understand how water and solutes move through Earth systems and interact with natural and human-driven processes. In addition to my research program, I have been actively involved in community cyberinfrastructure initiatives that support open and collaborative hydrologic science, including platforms that enable researchers to access, integrate, and analyze large geological and environmental datasets.
My research is motivated by a long-standing curiosity about how water moves through Earth’s surface systems and carries chemical signals that reveal interactions among water, rock, ecosystems, and human activities. Working with large geochemical and hydrologic datasets has made me realize that many important insights about water systems are hidden in complex, distributed data. Yet these datasets are often fragmented across institutions, formats, and disciplines. This realization has shaped much of my work: developing approaches that combine hydrogeochemistry, open data infrastructure, and machine learning to better understand water systems and their connections to elemental cycles, energy development, and climate and environmental change.
One example is the Shale Network (https://shalenetwork.org/), a community database that compiles water quantity and quality data associated with oil and gas development. The project initially focused on the Marcellus Shale region, and we are now working to expand the database across North America. The platform enables researchers to synthesize thousands of measurements across regions and time, supporting studies of water quality, watershed processes, and the environmental impacts of energy development. By making these data openly accessible and standardized, the Shale Network has helped accelerate collaborative research and improve transparency in environmental monitoring.
More recently, my team and collaborators have been developing GRID-DB (Global River-land Integrated Database; https://grid-db.github.io/), a next-generation data platform designed to integrate diverse datasets related to rivers and watersheds. GRID-DB brings together information such as river discharge, hydrogeochemistry, watershed properties, and environmental predictors into a unified and accessible data infrastructure. By combining large environmental datasets with modern data science and machine learning tools, the platform aims to help researchers and decision-makers better understand freshwater availability, hydrologic extremes, and watershed biogeochemical processes. The long-term vision of GRID-DB is to build an open and collaborative data ecosystem that supports interdisciplinary research and data-driven solutions for water management and environmental sustainability.
Looking ahead, I see hydrology entering a new era in which advances in environmental sensing, data integration, and artificial intelligence allow us to observe and model water systems with unprecedented detail. Over the next decade, I hope to contribute to building community data infrastructure and analytical tools that enable researchers and practitioners to work across disciplines and scales—from local watersheds to global environmental change. Ultimately, my vision is to help transform the growing streams of geological and environmental data into knowledge that improves how we understand and steward water systems.