Author(s): Hossein Amini; Man Yue Lam; Reza Ahmadian
Linked Author(s): Reza Ahmadian, Man Yue Lam
Keywords: Fecal Indicator Organisms causation causal inference machine learning bating water
Abstract: Fecal indicator organisms (FIOs) which are one of the main drivers of water quality at bathing water sites quality is heavily affected by the climatic conditions and anthropogenic activities. The examination of water quality stressors and how changes in the temporal dynamics of each variable might affect the faecal indicator organism’s concentrations is crucial to ensure good water quality. While common Artificial Intelligence (AI) models have been developed to understand the water quality stressors, these models identified correlations between stressors and FIO concentrations, which may not reflect causations. In this study, we used machine learning causal inference algorithms to delve into the detail of causal effect of role players of the FIOs concentration (Here E. coli, and Enterococci).
Year: 2025