Publications

Vazyulya, S; Kopelevich, O; Sahling, I; Kochetkova, E; Lange, E; Khrapko, A; Eremina, T; Glukhovets, D (2023). Regional Algorithm of Quantitative Assessment of Cyanobacteria Blooms in the Eastern Part of the Gulf of Finland Using Satellite Ocean Color Data. JOURNAL OF MARINE SCIENCE AND ENGINEERING, 11(9), 1746.

Abstract
Summer blooms of potentially harmful cyanobacteria are common in the Baltic Sea. Under clear sky conditions, the cyanobacterial blooms are easily detectable from space. We propose a new regional algorithm for cyanobacteria biomass estimation from satellite data in the eastern part of the Gulf of Finland, developed on the basis of field measurements in July-August 2012-2014. The multi-regression equation defines the cyanobacteria biomass as a function of the particle backscattering coefficient and chlorophyll concentration. The use of this equation provides the best performance in comparison to the linear one, which is reflected in both R2 and RMSE values (0.61 and 272 mg m(-)3 respectively). Unlike other algorithms, which determine only the cyanobacteria bloom area in the Baltic Sea, our algorithm allows the determination of both a bloom area and its intensity. Considering the algorithm errors, the bloom detection threshold has been shifted from the 200 mg m-3 determined by biologists to 300 mg m(-3). Based on data from the MODIS-Aqua satellite ocean color scanner, the spatial and temporal variability of cyanobacterial blooms in this region from 2003 to 2022 was analyzed. Significant interannual variability of cyanobacteria biomass was revealed in the central part of the studied region, with minimum values in 2014 and maximum in 2004. The record bloom during the studied period occurred in July 2004 (the average cyanobacteria biomass was 780 mg m(-3)). The weakest blooms were observed in 2009, 2010, and 2014, when both in July and August, the bloom areas did not exceed 30% of the study region.

DOI:
10.3390/jmse11091746

ISSN:
2077-1312