The Chesapeake Bay Program (CBP) partnership, guided by the 2014 Watershed Agreement, has long invested in monitoring, modeling, implementation, and research across the Bay and its watershed. As artificial intelligence and machine-learning (AI/ML) gain traction in ecology and water management, STAC convened a workshop, “Leveraging AI/ML to Advance Chesapeake Bay Research and Management,” on February 24–25 in Edgewater, Maryland, bringing together 50+ federal, state, academic, and NGO partners. The workshop reviewed current AI/ML applications in tidal and non-tidal systems, identified key challenges (e.g., data gaps and harmonization, communicating insights, and coordination across institutions), and developed practical recommendations to advance Bay restoration. The resulting report synthesizes lessons learned and outlines opportunities to deliver clear, actionable, data-driven insights for managers in supporting the CBP’s goals and measurable outcomes.
Workshop webpage with related materials.
Image: Chesapeake Bay Program, Integration & Application Network, Freepik
Suggested Citation:
Zhang, Q., M. Baker, I. Bertani, B. Dennison, L. Linker, K. Maloney, R. Sabo, C. Shen, G. Shenk, K. Van Meter, and M. Cole. 2025. Leveraging Artificial Intelligence and Machine Learning to Advance Chesapeake Bay Research and Management: A Review of Status, Challenges, and Opportunities. STAC Publication Number 25-005, Edgewater, MD. 45 pp.