Causal impact analysis of weir opening on cyanobacterial blooms and water quality in the Yeongsan River, Korea: A bayesian structural time-series analysis and median difference test.

ABSTRACT

The construction of weirs in Korea's Four Major Rivers Project has led to an increase in cyanobacterial blooms, posing environmental challenges. To address this, the government began opening weirs in 2017. However, interpreting experimental results has proven to be complex due to the multifaceted nature of blooms. This study aimed to assess the impact of opening the Juksan Weir on cyanobacterial blooms and water quality in the Yeongsan River. Using a median difference test (MDT) and causal impact analysis (CIA) with Bayesian structural time-series (BSTS) models, changes in cyanobacterial cell density (Cyano) and chlorophyll a concentration (Chl-a) before (January 2013 to June 2017) and after (July 2017 to December 2021) the weir-opening event were analyzed. The MDT revealed no significant change in Cyano post-weir opening (p = 0.267), but Chl-a significantly increased by 48.1 % (p < 0.01). As a result of CIA, Cyano decreased, albeit statistically insignificantly (p = 0.454), while Chl-a increased by 59.0 % (p < 0.01). These findings contradict the expectation that Cyano decrease due to the increased flow velocity resulting from weir opening. The absence of changes in Cyano and the increase in Chl-a can be attributed to several factors, including the constrained and inadequate duration of full weir opening combined with conducive conditions for the proliferation of other algae such as diatoms and green algae. These findings suggest that the effectiveness of weir opening in controlling Cyano may have been compromised by factors influencing the overall aquatic ecosystem dynamics. Further analysis revealed that factors such as elevated water temperatures (≥ 30 °C) and reduced flow rates (< 37 m3/s) contributed to the flourishing of cyanobacteria, whose concentrations exceeded 10,000 cells/mL. In analyzing causal relationships in environmental management, especially when there are complex causal interactions, the application of MDT and CIA provides valuable insights.