Quantifying national and regional cyanobacterial occurrence in US lakes using satellite remote sensing

Abstract

Cyanobacterial harmful algal blooms are the most common form of harmful algal blooms in freshwater systems throughout the world. However, in situ sampling of cyanobacteria in inland lakes is limited both spatially and temporally. Satellite data has proven to be an effective tool to monitor cyanobacteria in freshwater lakes across the United States. This study uses data from the European Space Agency Envisat MEdium Resolution Imaging Spectrometer and the Sentinel-3 Ocean and Land Color Instrument to provide a national overview of the percentage of lakes experiencing a cyanobacterial bloom on a weekly basis for 2008–2011, 2017, and 2018. A total of 2321 lakes across the contiguous United States were included in the analysis. We examined four different thresholds to define when a waterbody is classified as experiencing a bloom. Across these four thresholds, we explored variability in bloom percentage with changes in seasonality and lake size. As a validation of algorithm performance, we analyzed the agreement between satellite observations and previously established ecological patterns, although data availability in the wintertime limited these comparisons on a year-round basis. Changes in cyanobacterial bloom percentage at the national scale followed the well-known temporal pattern of freshwater blooms. The percentage of lakes experiencing a bloom increased throughout the year, reached a maximum in fall, and decreased through the winter. Wintertime data, particularly in northern regions, were consistently limited due to snow and ice cover. With the exception of the Southeast and South, regional patterns mimicked patterns found at the national scale. The Southeast and South exhibited an unexpected pattern as cyanobacterial bloom percentage reached a maximum in the winter rather than the summer. Lake Jesup in Florida was used as a case study to validate this observed pattern against field observations of chlorophyll a. Results from this research establish a baseline of annual occurrence of cyanobacterial blooms in inland lakes across the United States. In addition, methods presented in this study can be tailored to fit the specific requirements of an individual system or region.

Quantifying the Human Health Benefits of Using Satellite Information to Detect Cyanobacterial Harmful Algal Blooms and Manage Recreational Advisories in U.S. Lakes

“…Various satellite data sources have a range of spatial, temporal, and spectral resolutions, which balance trade‐offs with other geophysical considerations such as ground resolution and revisit time (Mouw et al, 2015). Satellites have many limitations to consider such as interference from cloud cover and detection for only the upper depths of the water column (Coffer et al, 2020). Only water bodies of sufficient size and shape may be considered in order to accommodate the spatial resolution of the satellite data, where the ability of a satellite to resolve a water body depends on the ideal pixel size of the sensor and on the combined size and geometry of the water body (Clark et al, 2017).…”

Quantifying Scales of Spatial Variability of Cyanobacteria in a Large, Eutrophic Lake Using Multiplatform Remote Sensing Tools

“…With many lakes across the globe experiencing an increase in the frequency and severity of harmful algal blooms of cyanobacteria (Taranu et al, 2015;Ho et al, 2019), there is a need to develop of tools for water managers to understand and predict their inception. Satellite-based remote sensing tools have emerged as a solution for water managers to monitor the onset and development of harmful algal blooms (Coffer et al, 2020). This research provides data for ground-truthing and algorithm validation, which is essential before widespread use and data interpretation of these satellite products can take place.…”

“…where, λ 681 nm, λ + 709 nm, and λ − 665 nm. This algorithm was later refined to incorporate an exclusionary criterion for the spectral shape at 665 nm (SS{665}), where, λ 665 nm, λ + 681 nm, and λ − 620 nm (Matthews et al, 2012;Lunetta et al, 2015;Coffer et al, 2020). The SS{665} exclusionary criterion targets the 620 nm band, which is a phycocyanin absorption feature (Lunetta et al, 2015).…”

Acute health effects associated with satellite-determined cyanobacterial blooms in a drinking water source in Massachusetts

“…Satellite, sensor, and algorithm improvements now allow for the study of numerous inland lakes, improving our ability to remotely assess cyanoHABs in water bodies that serve as sources of drinking water or as recreational venues [ 3 ]. Satellite images acquired by the European Space Agency’s (ESA’s) MEdium Resolution Imaging Spectrometer (MERIS) can measure phytoplankton spectral signatures [ 24 ], and are now used to estimate cyanobacteria abundance in water [ 5 , 25 , 26 ].…”