Cyanobacterial Bloom Phenology in Green Bay Using MERIS Satellite Data and Comparisons with Western Lake Erie and Saginaw Bay

Wynne, Timothy T.; Stumpf, Richard P.; Pokrzywinski, Kaytee L.; Litaker, R. Wayne; De Stasio, Bart T.; Hood, Raleigh R.

doi:10.3390/w14172636

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Cyanobacterial Bloom Phenology in Green Bay Using MERIS Satellite Data and Comparisons with Western Lake Erie and Saginaw Bay

2022
By Wynne, Timothy T. ; Stumpf, Richard P. ; Pokrzywinski, Kaytee L. ; ...
Source: Water, 14(17), 2636

[PDF-3.79 MB]

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Details:

Journal Title:

Water
Personal Author:

Wynne, Timothy T. ; Stumpf, Richard P. ; Pokrzywinski, Kaytee L. ; Litaker, R. Wayne ; De Stasio, Bart T. ; ... More +

Wynne, Timothy T. ; Stumpf, Richard P. ; Pokrzywinski, Kaytee L. ; Litaker, R. Wayne ; De Stasio, Bart T. ; Hood, Raleigh R. Less -
NOAA Program & Office:

NOS (National Ocean Service) ; NCCOS (National Centers for Coastal Ocean Science)

NOS (National Ocean Service) ; NCCOS (National Centers for Coastal Ocean Science) Less -
Description:

Cyanobacteria blooms have been reported to be increasing worldwide. In addition to potentially causing major economic and ecological damage, these blooms can threaten human health. Furthermore, these blooms can be exacerbated by a warming climate. One approach to monitoring and modeling cyanobacterial biomass is to use processed satellite imagery to obtain long-term data sets. In this paper, an existing algorithm for estimating cyanobacterial biomass previously developed for MERIS is validated for Green Bay using cyanobacteria biovolume estimates obtained from field samples. Once the algorithm was validated, the existing MERIS imagery was used to determine the bloom phenology of the cyanobacterial biomass in Green Bay. Modeled datasets of heat flux (as a proxy for stratification), wind speed, water temperature, and gelbstoff absorption along with in situ river discharge data were used to separate bloom seasons in Green Bay from bloom seasons in nearby cyanobacteria bloom hotspots including western Lake Erie and Saginaw Bay. Of the ten-year MERIS dataset used here, the highest five years were considered “high bloom” years, and the lowest five years from biomass were considered “low bloom” years and these definitions were used to separate Green Bay. Green Bay had a strong relationship with gelbstoff absorption making it unique among the water bodies, while western Lake Erie responded strongly with river discharge as previously reported. Saginaw Bay, which has low interannual bloom variability, did not exhibit a largely influential single parameter.
Keywords:

[+]

Aquatic Science Biochemistry Geography, Planning And Development Water Science And Technology
Source:

Water, 14(17), 2636
DOI:

https://doi.org/10.3390/w14172636
ISSN:

2073-4441
Format:

PDF
Publisher:

MDPI AG
Document Type:

Journal Article
License:

https://creativecommons.org/licenses/by/4.0/
Rights Information:

CC BY
Compliance:

Submitted
Main Document Checksum:

[+]

urn:sha256:782856f0f4ec37479e060b781924ca22f3a31d4dd4773222eb88de1ced64772e
Download URL:

https://repository.library.noaa.gov/view/noaa/49251/noaa_49251_DS1.pdf
File Type:

Machine readable version (XML)

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