Risk Analysis of Algal Blooms Using the Conditional Copula Model

In Korea, algal blooms are repeated every year in the four major rivers. Especially, the frequency and duration of algal blooms have increased due to climate change (increase in the atmosphere and water temperature) and environmental changes (river development projects and weir construction), which has led to the development of related research. However, it is still difficult to elucidate the cause of algal blooms because of a complicated mechanism. In this study, the concentration of Chlorophyll-a was selected as an indicator of algae occurrence, and representative hydrometeorological factors affecting the algal phenomenon were selected. Then, the optimal marginal distribution for each variable was found. The risk of algal blooms was analyzed through bivariate copula analysis by identifying the relationship between the influencing factors and the concentration of Chlorophyll-a. As a result, it was possible to identify the factors that had the most significant influence on the occurrence of algal blooms. Further, this study will employ the Vine Copula function to improve the complex relationship between variables in the context of multivariate modeling.