Stefano Galelli
Cornell University, NY·Earth & Environmental Science
Predicting how much water will flow down a river is the basis of flood warnings, drought planning, and water supply management. Computer models do this by linking climate — rainfall, snowmelt, temperature — to streamflow.
- Fields
Earth & Environmental Science
Engineering
Computer Science
- Topics
hydrologic modeling
streamflow prediction
dam operations
- Grants
- 1 known grant, through Aug 2027
What they work on
- Characterize the structural uncertainty that comes from choosing one dam operation model over another, using a computational framework applied to 18 large river basins spanning every major U.S. hydrologic region and about 200 dams.
- Explain how uncertainty in representing dam operations propagates into the parameterization and calibration of large-scale hydrologic models that link climate to streamflow.
- Quantify how this uncertainty affects simulated hydrologic processes and fluxes in regulated river basins, and generalize the results into practical modelling guidelines.
- Build an observational dataset of dam operations across the continental United States from observed and remotely sensed reservoir storage, and test the framework's generality on the heavily managed Colorado and Columbia River basins.
More about the research
But rivers are not natural anymore. Dams control roughly 75% of annual runoff in the continental United States, and how operators choose to store and release water is poorly represented in these models. That gap is a major reason streamflow estimates remain uncertain, and it grows as human influence on the water cycle changes.
Why it matters
Flood forecasts, drought outlooks, and water supply plans all rest on streamflow models that currently handle dams crudely. By showing how much error that introduces and offering guidelines for doing better, this work could make predictions more reliable in managed basins such as the Colorado and Columbia, where cities, farms, and hydropower operators depend on them. The planned open dataset of observed U.S. dam operations would also give other modellers something they currently lack.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
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Hoori Ajami
University of California-Riverside, CA·Earth & Environmental Science·Early-career
Measure water balance dynamics, water residence times and bedrock groundwater's contribution to streams in the Kaweah River watershed using hydrometric observations and hydrochemical tracers.
The school
Cornell University: 37 labs on PI Pages, $1.6B a year on research, 537 research doctorates a year.
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