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 announces 2018 Data Science Research Projects
September 12, 2018 | BIDS News