Author(s): Arthur Guillot-Le Goff; Yoann Cartier; Paul Kennouche; Brigitte Vincon-Leite; Remi Carmigniani
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Keywords: Urban bathing; Water quality; Forecasting
Abstract: Urban swimming has re-emerged as a popular activity, yet maintaining water quality in dense cities poses significant challenges, especially with the increasing frequency of extreme weather events linked to climate change. This study explores a framework to anticipate health risks at urban bathing sites by linking rain intensity to water contamination levels. Using high-frequency bacteriological monitoring data from the Seine River, collected between 2021 and 2023, we established a correlation between a global rain indicators and water quality. A combination of meteorological and hydrological data was analyzed using principal component analysis (PCA) and dimensionality reduction techniques to simplify contamination risk prediction using a single global rain indicator. The results demonstrate the viability of using rain forecast data to anticipate water quality in urban swimming sites.
Year: 2024