Owasco Lake is the sixth largest of the Finger Lakes in Central New York. The lake has consistently high nutrient loading, which the NYSDEC (Owasco Lake, 2017) attributes to the high drainage basin to surface area ratio, draining a catchment of 540 km2 into a lake of only ~27km2 of surface area.
Because of this consistently high anthropogenic nutrient loading, Owasco Lake has faced recurring years of cyanobacterial blooms. Cyanobacteria poses a huge threat to human health, producing various serious toxins that affect the brain, liver, skin, and other vital organs. Due to the risk of toxicity, monitoring cyanobacteria during the peak time of year, between late summer and early fall, is essential. Stakeholders depend largely upon citizen science to monitor, record, and report possible blooms to those with the authority to help manage risk (NYSDEC, 2017). In this way, citizens must instead rely on the vigilance of others to safeguard their own health.
In an effort to offer local stakeholders a potential tool that might allow for more efficient and effective monitoring of the cyanobacteria, this model was created as a means to gauge the impact of various environmental parameters on bloom vigor. By simply considering watershed topography, water temperature, light intensity, wind speed, and precipitation, the model created performs decently well on predicting cyanobacterial blooms. 71% of recorded blooms were predicted correctly. The model was shown to overpredict blooms, however, but this could be a reflection of the monitoring capability as it is currently conducted. As it is or with furhther improvements, this simple model could serve as a powerful tool to potentially warn stakeholders when conditions are ideal for a bloom event. With this knowledge, stakeholders can focus field monitoring efforts and also make more informed decisions regarding the health of the community.