LAUSR

Phytoplankton blooms have a simple generation mechanism but myriad influencing factors. The compounding effects of water quality, weather conditions, and geological factors are site-specific to single river basin and can exhibit distinctive characteristics. To investigate the site-specific patterns of Chlorophyll-a outbreaks for each sub-part of the river, we statistically analyzed the results of water quality monitoring for the Nakdong River to classify the locations of the monitoring stations into upstream, midstream, and downstream sites. Then, based on the combination of the influencing factors, the rules explaining Chlorophyll-a concentration levels were extracted and interpreted using a decision tree algorithm, CHAID. The results revealed that for upstream, weather conditions were the primary factor influencing phytoplankton blooms because of the relative absence of pollutants compared with the midstream and downstream. For midstream, weather conditions and nutritional factors were influential in the generation of phytoplankton blooms. For downstream, the notable amount of pollutants originating from upstream not only reflected a high nutrient level for the phytoplankton but also caused the water quality factor to be the primary cause of phytoplankton blooms. The deduced tree, a tool for data-driven modeling, demonstrated its usefulness by extracting practical influencing factors and patterns of interest from the given data.