Algae development in rivers with artificially constructed weirs: Dominant influence of discharge over temperature - Kim, Hyunju; Lee, Gyesik; Lee, Chang Gu; Park, Seong Jik (Journal of Environmental Management, 2024)
Algal blooms contribute to water quality degradation, unpleasant odors, taste issues, and the presence of harmful substances in artificially constructed weirs. Mitigating these adverse effects through effective algal bloom management requires identifying the contributing factors and predicting algal concentrations. This study focused on the upstream region of the Seungchon Weir in Korea, which is characterized by elevated levels of total nitrogen and phosphorus due to a significant influx of water from a sewage treatment plant. We employed four distinct machine learning models to predict chlorophyll-a (Chl-a) concentrations and identified the influential variables linked to local algal bloom events. The gradient boosting model enabled an in-depth exploration of the intricate relationships between algal occurrence and water quality parameters, enabling accurate identification of the causal factors. The models identified the discharge flow rate (D-Flow) and water temperature as the primary determinants of Chl-a levels, with feature importance values of 0.236 and 0.212, respectively. Enhanced model precision was achieved by utilizing daily average D-Flow values, with model accuracy and significance of the D-Flow amplifying as the temporal span of daily averaging increased. Elevated Chl-a concentrations correlated with diminished D-Flow and temperature, highlighting the pivotal role of D-Flow in regulating Chl-a concentration. This trend can be attributed to the constrained discharge of the Seungchon Weir during winter. Calculating the requisite D-Flow to maintain a desirable Chl-a concentration of up to 20 mg/m3 across varying temperatures revealed an escalating demand for D-Flow with rising temperatures. Specific D-Flow ranges, corresponding to each season and temperature condition, were identified as particularly influential on Chl-a concentration. Thus, optimizing Chl-a reduction can be achieved by strategically increasing D-Flow within these specified ranges for each season and temperature variation. This study highlights the importance of maintaining sufficient D-Flow levels to mitigate algal proliferation within river systems featuring weirs.
Keywords: Adverse effect; Algae blooms; Algal blooms; Chlorophyll a; Chlorophyll-a concentration; Constructed weir; Discharge flow rates; Harmful substances; Machine-learning; Water quality degradation; China; Chlorophyll; Chlorophyll A; Environmental Monitoring; Eutrophication; Nitrogen; Phosphorus; Rivers; Temperature; Water Quality; Algae bloom; Chlorophyll-a; Constructed weirs; Discharge flow rate; Machine learning; Temperature