Yoann CARTIER

Doctorant LHSV

Publications

Yoann Cartier, Arthur Guillot-Le Goff, Rémi Carmigniani, David Métivier, Thomas Einfalt, et al.. Modelling combined sewer overflow based on sewer network graph representation and rain radar data: application to the Seine river . EGU General Assembly 2025 - Session: Precipitation and Urban Hydrology, Apr 2025, Vienne, Austria. ⟨10.5194/egusphere-egu25-11965⟩. ⟨hal-05084227⟩
Arthur Guillot - Le Goff, Yoann Cartier, Rémi Arthur Carmigniani, Damien Malardé, Mohamed Saad, et al.. Predicting water quality in urban rivers: Linking high frequency monitoring and spatial rainfall. 16 th International Conference on Urban Drainage, TU Delft, Jun 2024, Delft, Netherlands. ⟨hal-05045353⟩

Predicting microbiological contamination in urban rivers: an event-based indicator approach applied to the Seine river during the 2024 Paris olympic and paralympic games
- Guillot - Le Goff Arthur
- Cartier Yoann
- Vinçon-Leite Brigitte
- Boyaval Sébastien
- Carmigniani Rémi
Journal of Hydrology, Elsevier , 2026, 674, pp.135504 . Urban rivers are subject to microbiological contamination following the discharge of wastewater after heavy rains. These peaks of faecal contamination lead to health risks, particularly in urban bathing areas. To prevent these risks, European legislation requires early warning systems to be operated. This study proposes a new methodology for implementing an early warning system based on high-frequency measurements of bacteriological contamina tion proxies and hydro-meteorological data. By analysing these high-frequency data collected over three summer seasons (2021-2023) in the Seine River, Paris, France, the proposed framework defines rainfall events and their impact on microbial water quality. Dimensionality reduction techniques, including Principal Component Analysis (PCA) and Manifold ISOMAP, are applied and compared to identify key explanatory characteristics and build a predictive model. A global rain parameter (GRP) is derived, which effectively classifies rainfall events based on their potential impact on water quality. The method was successfully tested during the 2024 Paris Olympic and Paralympic Games, demonstrating its potential for real-time water quality management. (10.1016/j.jhydrol.2026.135504)
DOI : 10.1016/j.jhydrol.2026.135504
Statistical modelling of combined sewer overflow
- Cartier Yoann
- Guillot-Le Goff Arthur
- Carmigniani Rémi
- Métivier David
- Einfalt Thomas
- Vinçon-Leite Brigitte
- Kennouche Paul
, 2025, pp.22 p. . Rivers are at the heart of human activity. They provide many ecosystem services: drinking water, agriculture, transport, hydropower, bathing, freshness, etc. They are also hotspots for biodiversity. However, the water quality of these rivers is deteriorated as a result of human activity. The current work focuses on fecal contamination, which is a discriminating criterion for bathing. In urban watersheds, fecal bacteria contamination comes from point sources related to the operation of the drainage network. During rainy weather, the combined sewer network, mixingboth wastewater and stormwater, can become saturated. As a consequence, part of the flow is discharged directly into the river via combined sewer overflows (CSOs). This is the case for the city of Paris. The possible CSO overflow can be modeled by a function linking its discharge toprecipitation. This relationship is currently poorly understood, with little related work, and even less for the Seine river.To build such linking function, we rely on a dataset that includes location and hourly discharged volume of the monitored CSOs in the Seine River within Paris. Urban watersheds have been delineated within the study site. Rainfall height over these watersheds have been obtained from eather radar. We broke down the data timeseries into events. An event begins with the cause, the rain, and ends with the consequence, the overflow. To link rainfall to CSOs a directional graph based on the drainage network map, was created. It represents the wastewater transport from one watershed to another. This highlights which rainfall variables to consider regarding the CSO location. Principal component analysis (PCA) is used to assess for rain characteristics selection. An unsupervised non-linear technique (Isomap) is then used to build linking function structure.The overflow volume in time can be modeled by a triangular shape. This shape is described by the overflow initial time, its total and maximum volume and the time of the maximum. We expect to retrieve these overflow variables by reducing the number of rainfall event characteristics to single indicators using sequentially PCA and Isomap.Modeling and forecasting source discharges would enable better management of bathing and water supply risks, and better evaluation of mitigation infrastructures. (10.5194/egusphere-egu25-11965)
DOI : 10.5194/egusphere-egu25-11965
Predicting water quality in urban rivers: Linking high frequency monitoring and spatial rainfall
- Guillot - Le Goff Arthur
- Cartier Yoann
- Carmigniani Rémi Arthur
- Malardé Damien
- Saad Mohamed
- Dubois Philippe
- Einfalt Thomas
- Brigitte Vinçon-Leite
, 2024 .