Session Lead: Qian Zhang (University of Maryland Center for Environmental Science / USEPA Chesapeake Bay Program)
Co-Lead(s): Kaylyn Gootman (USEPA Chesapeake Bay Program), Peter Tango (U.S. Geological Survey / USEPA Chesapeake Bay Program), Breck Sullivan (U.S. Geological Survey / USEPA Chesapeake Bay Program)
Session Format: Oral presentations
Session Description:
Restoration of complex aquatic ecosystems such as Chesapeake Bay requires sustained collaboration between the science and management communities. Over more than three decades, systematic monitoring and progressively refined modeling tools have provided critical feedback on restoration progress. While these efforts have supported significant gains in water quality, new challenges are emerging as we confront a rapidly changing natural and human environment. One of the most pressing is how to harness a new generation of monitoring and modeling tools to sustain progress in this dynamic future. This session focuses on the development and deployment of tools that expand our ability to observe and simulate water quality. Topics include high-resolution in situ sensors, remote sensing platforms, satellite applications, and innovative modeling frameworks. Special attention will be given to how artificial intelligence and machine learning are being applied to enhance or emulate mechanistic models. Presentations will highlight advances that improve how we collect, integrate, and simulate data to better track restoration progress and anticipate future challenges. This is Part I of two connected sessions organized by the Chesapeake Bay Program’s Integrated Trends Analysis Team.