Studying the causality of the key variables inflluencing the fecal indicator organsims [Abstract]

Amini, Hossein, Lam, Man Yue ORCID: https://orcid.org/0000-0001-7259-968X and Ahmadian, Reza ORCID: https://orcid.org/0000-0003-2665-4734 2025. Studying the causality of the key variables inflluencing the fecal indicator organsims [Abstract]. Book of Extended Abstracts of the 41st IAHR World Congress (Singapore, 2025) , 37699.

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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).

Item Type:	Short Communication
Date Type:	Publication
Status:	Published
Schools:	Schools > Engineering
Additional Information:	Published in; Book of Extended Abstracts of the 41st IAHR World Congress (Singapore, 2025). Publisher: IAHR ISBN: 978-90-835589-5-0 Editor(s): Adrian Wing-Keung Law and Jenn Wei Er Conference details: 41st IAHR World Congress held in Singapore 22-27 June 2025.
Last Modified:	22 Jan 2026 14:48
URI:	https://orca.cardiff.ac.uk/id/eprint/184111

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