Dams play a crucial role in water management but have also significantly altered the natural flow of rivers worldwide, sometimes in unpredictable ways, which is why new research to be led by Cornell aims to advance the study of hydrologic processes in river basins impacted by dam operations.

Stefano Galelli, associate professor of civil and environmental engineering, received a three-year grant from the National Science Foundation’s Hydrologic Science Program to address critical gaps in current hydrologic models, which often adopt fragmented and simplistic representations of dam operations, limiting the understanding of hydrologic processes and their broader applications.

The project, “Hydrologic Process Inference in Large-Scale Models Under Human Impacts,” seeks to rectify this by developing a comprehensive computational framework that integrates remote sensing, diagnostic tools, and hydrologic and dam operation models. With co-principal investigator Jonathan Herman, associate professor of civil and environmental engineering at the University of California, Davis, the framework will be demonstrated across 18 large river basins in the continental United States, encompassing approximately 200 dams.

The project has four key objectives:

• Characterize the structural uncertainty linked to dam operation models
• Explore how uncertainty affects the parameterization of large-scale hydrologic models
• Quantify the impact of uncertainty on hydrologic simulations and process inference
• Develop practical guidelines for improving modeling efforts

“It is a timely moment for this research because recent progresses in remote sensing and data collection provide us information on human actions with unprecedented granularity, so we now have a tangible opportunity to advance the field of coupled human-natural system modeling,” said Galelli, who instructs the Critical Infrastructure Systems Lab at Cornell. “Improvements in large-scale hydrologic models will benefit several applications, such as ecologic impact assessments, climate services, or studies informing the clean energy transition.”

Beyond technical advancements, the project will also contribute to the broader research community by providing open datasets and benchmark models to support further studies. 

Additionally, the project will build on Galelli’s experience providing training to postdoctoral, graduate and undergraduate researchers from diverse backgrounds, and will engage the scientific community through dedicated workshops organized in concomitance with the 2025 and 2026 Fall Meetings of the American Geophysical Union.