A validation of satellite derived cyanobacteria detections with state reported events and recreation advisories across U.S. lakes.
Peter Whitman, Blake Schaeffer, Wilson Salls, Megan Coffer, Sachidananda Mishra, Bridget Seegers, Keith Loftin, Richard Stumpf, P Jeremy Werdell
Author Information
Peter Whitman: Oak Ridge Institute for Science and Education, U.S. Environmental Protection Agency, Durham, NC 27709, USA. Electronic address: whitman.peter@epa.gov.
Blake Schaeffer: U.S. Environmental Protection Agency, Office of Research and Development, Durham, NC 27709, USA.
Wilson Salls: U.S. Environmental Protection Agency, Office of Research and Development, Durham, NC 27709, USA.
Megan Coffer: Oak Ridge Institute for Science and Education, U.S. Environmental Protection Agency, Durham, NC 27709, USA; Center for Geospatial Analytics, North Carolina State University, Raleigh, NC 27606, USA.
Sachidananda Mishra: Consolidated Safety Services Inc. Fairfax, VA 22030, USA; National Oceanic and Atmospheric Administration, National Centers for Coastal Ocean Science, Silver Spring, MD, USA.
Bridget Seegers: Ocean Ecology Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA; Universities Space Research Association, Columbia, MD, USA.
Keith Loftin: U.S. Geological Survey, Kansas Water Science Center, Lawrence, KS, USA.
Richard Stumpf: National Oceanic and Atmospheric Administration, National Centers for Coastal Ocean Science, Silver Spring, MD, USA.
P Jeremy Werdell: Ocean Ecology Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA.
cyanobacteria harmful algal blooms (cyanoHABs) negatively affect ecological, human, and animal health. Traditional methods of validating satellite algorithms with data from water samples are often inhibited by the expense of quantifying cyanobacteria indicators in the field and the lack of public data. However, state recreation advisories and other recorded events of cyanoHAB occurrence reported by local authorities can serve as an independent and publicly available dataset for validation. State recreation advisories were defined as a period delimited by a start and end date where a warning was issued due to detections of cyanoHABs over a state's risk threshold. State reported events were defined as any event that was documented with a single date related to cyanoHABs. This study examined the presence-absence agreement between 160 state reported cyanoHAB advisories and 1,343 events and cyanobacteria biomass estimated by a satellite algorithm called the cyanobacteria Index (CI). The true positive rate of agreement with state recreation advisories was 69% and 60% with state reported events. CI detected a reduction or absence in cyanobacteria after 76% of the recreation advisories ended. CI was used to quantify the magnitude, spatial extent, and temporal frequency of cyanoHABs; each of these three metrics were greater (r > 0.2) during state recreation advisories compared to non-advisory times with effect sizes ranging from small to large. This is the first study to quantitatively evaluate satellite algorithm performance for detecting cyanoHABs with state reported events and advisories and supports informed management decisions with satellite technologies that complement traditional field observations.
