Cyanobacterial blooms in lakes and ponds, and some rivers, represent an increasingly major issue in terms of human, animal and plant health (Zhang et al. 2022; Igwaran et al. 2024). Some species are particularly capable of producing toxins called CyanoHABs. In the context of climate change, and more particularly global warming, these CyanoHABs are increasing (O’Neil et al. 2012; Visser et al. 2016; Huisman et al. 2018). Due to environmental and human issues, it is essential to monitor their spatio-temporal variation. However, in-situ monitoring is often both expensive and limited in frequency (in spatial and temporal coverage, Rogalus et al. 2008). Remotely sensed Earth observation data, supported by predictive models, has the potential to provide regular monitoring of cyanobacterial blooms (Wu et al., 2025). Monitoring performance depends on multiple factors (e.g., water body type, surrounding environment), pointing to a need to develop models tailored to specific regions. In this context, this thesis proposes to examine the potential of Earth observation data to track cyanobacteria in lakes and rivers in the Pays de la Loire region in France – for instance, the summer of 2025 revealed major issues with cyanobacterial proliferation in several water bodies and waterways, questioning the production of drinking water and leading to the banning of activities (fishing, tourism, bathing). The expected increase in the frequency and intensity of extreme weather and climate events underscores the need for a comprehensive understanding of the dynamics of the spatio-temporal evolution of cyanobacteria in water bodies in the region.

A number of water bodies in the Pays de la Loire region have been identified for potential monitoring: the Vioreau, Grand Lieu, and/or Beaulieu lakes, as well as the Erdre River. The thesis will involve 3 main objectives: 

1) Characterization of landscape and environment, and cross-validation of parameters for cyanobateria tracking by the synergistic use of in-situ and remote sensing. For ground-based measurements, we will use the YSI ExO probe, already acquired, which allows of phytocyanin, water temperature, pH, conductivity, dissolved oxygen, chlorophyll-a; sampling will take place between September 2026 and September 2028 (measurements will be also carried out from April 2026 by the supervisors), with weekly (October to April) or sub-weekly (May to September) frequency to account for seasonality. In fact, cyanobacteria blooms proliferate mainly between May and October, favored by warm, phosphorus-rich waters (Pitois and Barguil, 2021). Furthermore, a continuous dataset since 2005 at several points along the Erdre with various parameters (physicochemical, microalgae, etc.) is already available via the “Syndicat du bassin versant de l’Erdre” (Edenn). Earth observations will be based on Sentinel 2 and 3, as well the future Trishna satellite, for Chlorophyll-a, phycocyanin, land use, water temperature, etc. For climate data we will use Meteo-France ground-based observations, as well as available satellite-based products such as IMERG precipitation, and GLDAS for soil moisture and surface temperature.

2) Evaluation of the potential of Earth observation data associated with machine learning approaches (KNN, decision tree, SVR, Bagging, Boosting) to design water quality monitoring methods. Such methods developed for this field are relatively recent, starting around 2020. A mixed approach will be applied, in which in a first step, both in-situ and remote sensing data will be used to train the model; in a second step, only remote sensing data will be used, and performances between modes, methods and approaches will be compared.

3) Analysis of the impact of climate change on the evolution of water quality, considering two future periods of climate change (2030-2059 and 2070-2100) for 3 SSPs (shared socio-economic Pathways): SSP1-2.6, SSP2-4.5, SSP5-8.5. Indeed, in the Pays de la Loire region, the current trajectory of air temperatures projects an increase of +1.3 to +1.6 °C from 2050, and from +2.5 °C in the middle of the century to +4 °C by 2100 for the most pessimistic scenario (IPCC Pays de la Loire, June 2022). Furthermore, all scenarios predict a marked decrease in river flows in summer (IPCC Pays de la Loire, 2022). 

The thesis will focus on seeking a better understanding of the role of climate and environmental conditions as determinants of the spatio-temporal dynamics of cyanobacterial bloom, as well as the implementation of a predictive model to support decision making. Interactions with local stakeholders, e.g., the “DREAL Pays de la Loire”, the Edenn, the “syndicat Grand Lieu Estuaire”, etc. are also planned. The proposed thesis goes hand in hand with ongoing research by the team, using a similar tele-epidemiological approach to monitor other water quality parameters (Escherichia coli, MAMIWATA, TELESSAO, MOQA and PERLE projects) in watercourses in Tropical and mid-latitude zones.

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For more Information about the topics and the co-financial partner (found by the lab!); contact Directeur de thèse - elodie.robert@univ-nantes.fr

Then, prepare a resume, a recent transcript and a reference letter from your M2 supervisor/ engineering school director and you will be ready to apply online  before March 13th, 2026 Midnight Paris time!