Hydrological forecasting and the water/energy nexus

Clean, available water is a critical and often-overlooked resource for human activity, food production, biological diversity and all aspects of life on our planet. Drawing on data streams from a national network of research collaborators and water sensor networks, the research team is creating and consolidating databases, detailed data-driven models, and publicly-available software systems to understand and predict the availability and location of water from the complex, real-world catchments and basins in which it collects and drains naturally, in order to forecast where and when water will be available. The software developed will apply tools from machine learning and information theory to support robust data analysis across many areas of environmental science. BIDS Senior Fellow Laurel Larsen leads this project, with BIDS Data Science Fellow Zexuan Xu and Senior Fellow Fernando Pérez collaborating.

BIDS Affiliates

Leader

Laurel Larsen

Geography

Zexuan Xu

Hydrology, CERC-WET, LBNL
Alumni - DATA SCIENCE FELLOW

Fernando Pérez

Statistics
Co-I for Moore/Sloan Data Science Environments