Overview
Cyanobacterial harmful algal blooms (CyanoHABs) produce toxins and odors in public water bodies and drinking water. Current process-based models predict algal blooms by modeling chlorophyll-a concentrations, but chlorophyll-a represents all algae — so a method for predicting the proportion of harmful cyanobacteria is required.
Model Setup
This study proposed a technique to predict harmful cyanobacteria concentrations based on the source codes of the Environmental Fluid Dynamics Code from the National Institute of Environmental Research. A graphical user interface was developed to generate information about general water quality and algae, which was then used in the model to predict harmful cyanobacteria concentrations. Predictive modeling was performed for the Hapcheon-Changnyeong Weir to Changnyeong-Haman Weir section of the Nakdong River from May to October 2019, the season in which CyanoHABs predominantly occur.
Key Findings
To evaluate the model’s success rate, a detailed five-step classification of harmful cyanobacteria levels was proposed. The modeling results demonstrated high prediction accuracy of 62% for harmful cyanobacteria. The study concludes that, for CyanoHAB management, harmful cyanobacteria — rather than chlorophyll-a — should be used as the index, allowing direct inference of cell densities. The proposed method may help improve the existing Harmful Algae Alert System in South Korea.