Multivariable integrated risk assessment for cyanobacterial blooms in eutrophic lakes and its spatiotemporal...

Climate change has catalyzed the global expansion of cyanobacterial blooms in eutrophic , lakes and threatens water security. In most studies, the cyanobacterial bloom risk levels in lakes were evaluated using field-collected data from multiple indicators or spatially continuous data from one cyanobacteria-related indicator. Nevertheless, the occurrence of cyanobacterial blooms in lakes has clear spatial heterogeneity and is affected by numerous factors. Therefore, we developed a multivariable integrated risk assessment framework for cyanobacterial blooms in lakes using five spatially continuous datasets to estimate the risk level of cyanobacterial blooms at the pixel scale (250 m). The spatial and temporal variations in cyanobacterial bloom risk levels from May 1, 2002, to October 31, 2020, were investigated for three typical eutrophic lakes in China: Lakes Taihu, Chaohu, and Dianchi. Seasons and regions of high cyanobacterial bloom risk were identified for each lake. Environmental characteristics were discussed. A long-term investigation revealed that owing to its warm climate, the cyanobacterial risk levels in summer and autumn were much higher than those in the other two seasons. At the synoptic scale, Lake Taihu had a lower cyanobacterial bloom risk than Lakes Chaohu and Dianchi. A further comparison found that precipitation, wind speed, and temperature were responsible for the differences in cyanobacterial bloom risk levels among the three lakes. At the pixel scale, the risk map indicated that the cyanobacterial bloom risk levels of Lake Taihu were unevenly distributed, and the cyanobacterial bloom risk of the lakeshore was higher than that of the other subregions. Nutrient levels played the most critical role in the regional differences in cyanobacterial bloom risk levels in a lake. While the differences of cyanobacterial bloom risk levels in three lakes were resulted by the climates. Bloom events were defined and classified as "long-term bloom" or "flash bloom" according to their duration (over or below a year). Overall, this study can assist in advanced water management with a pixel-scale evaluation of cyanobacterial bloom risk levels.