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Forecasting freshwater cyanobacterial harmful algal blooms for Sentinel-3 satellite resolved U.S. lakes
Citation:
Meyers, K. AND B. Schaeffer. Forecasting freshwater cyanobacterial harmful algal blooms for Sentinel-3 satellite resolved U.S. lakes. EPA Region 1 stakeholder meeting, Durham (Virtual), NC, February 22, 2024.
Impact/Purpose:
In summary the CyAN project provides real-time data, software, training, and annual metrics. We discuss the ability of satellite technology to detect cyanobacteria and over viewed some validation work. A Bayesian spatio-temporal model was applied to forecast World Health Organization alert level 1 exceedance. We demonstrated weekly forecasts for all 2,192 satellite resolved lakes. If this modeling method complemented existing efforts of field monitoring and real-time remote sensing, it could become part of a more comprehensive management toolbox for monitoring water quality. A hypothetical example might include a 7-day forecast that informs managers to watch a subset of lakes with high forecasted probabilities of an event; this could be done by using daily satellite data and then complementary field observations for toxin analysis if imagery confirms the event is occurring. This Bayesian spatio-temporal model is transferable and could be applied to other countries in need of cyanoHAB forecasts.
Description:
This overview is designed for a general audience without expertise in satellite remote sensing and forecasting. It is meant to highlight how the Cyanobacteria Assessment Network, CyAN , might provide useful real-time data, software, training, annual summary metrics, and 1-week forecasting for the largest 2,192 lakes in the United States.