Sampling strategy and design for Chesapeake Bay habitat assessment
Dr. Dong Liang, University of Maryland, Center for Environmental Science.
The Chesapeake Bay has had a large monitoring program for water quality for the last four decades. Given the advancement of continuous monitoring infrastructure, recent studies pointed to the high values of small numbers of in-situ monitoring stations with high temporal frequency to provide a sound basis for water quality assessment. In addition, a coupling of on-shore and off-shore monitoring can further inform the habitat assessment. This study will couple big data from hydrodynamic models to evaluate the monitoring strategies that incorporate novel continuous in-situ monitoring technologies. The computing needs involve storage of large NetCDF files generated from a high-resolution hydrodynamic model covering the Chesapeake Bay, as well as Monte Carlo simulations to evaluate a large collection of potential sampling scenarios. The newer monitoring, in turn, will enhance the Chesapeake Bay habitat assessment and address stakeholder planning needs. This study will consider agency-specific logistic constraints on site locations while optimizing for habitat assessment.