The warming of river water temperatures is an undeniable consequence of climate change and human activities, as shown by global studies (Liu et al., 2020) and those conducted in various European countries (Piccolroaz et al., 2024). The direct consequences of increasing water temperature are already measurable at all levels of socio-ecosystems: physiological and/or behavioral responses in aquatic organisms (Isaak and Rieman, 2013), anoxia in ecosystems (Diamond et al., 2023), algal blooms, cyanobacteria toxicity (Massey et al., 2020), more difficult cooling of nuclear power plants, drinking water supply issues, etc. While the consequences of rising water temperature are systemic, research remains fragmented and does not yet allow for a comprehensive analysis of biological processes or a clear quantification of thermal regime changes, including the respective effects of climate change and human activities. Water temperature time series are rarely available or standardized, and aquatic ecology research often uses air temperature as a substitute to model species distribution (Turschwell et al., 2017). However, the relationship between water temperature and air temperature is complex at landscape scales, which makes biological models imprecise (Arismendi et al., 2014). Additionally, anthropogenic factors and associated processes exacerbate the impact of rising water temperatures, threatening aquatic ecosystems and their biodiversity. Habitat fragmentation and the alteration of flow and thermal regimes by dams increase the impact of rising temperatures on aquatic ecosystems.

Recent advances in monitoring and data collection, as well as in statistical and mathematical modeling, have enabled significant improvements in understanding aquatic thermal landscapes. Despite the heterogeneity and scarcity of long-term data, the use of low-cost sensors capable of continuously measuring water temperature has exploded, making it possible to collect data at various temporal and spatial scales (Isaak et al., 2012). Detecting and anticipating these disruptions requires systematic long-term monitoring of river temperatures at appropriate spatial scales.

The doctoral project focuses on understanding and predicting river thermal regimes in the context of climate change and human activities. The goal is to improve the prediction of river temperature models across France using new statistical models, which will simulate daily water temperature data and its variability, benefiting ecological studies. The project also aims to analyze thermal regimes, both natural and altered, at the spatial scale. By leveraging a national dataset on water temperature, the research will address the key methodological challenges related to data heterogeneity and uncertainty.

This work is structured around three main objectives and one application-oriented goal. The first objective focuses on modeling the temporal variability of river temperatures in France using statistical and machine learning models (e.g., linear regression, LSTM neural networks, etc.), incorporating variables like discharge and radiation, with an emphasis on uncertainty assessment. Climate and hydrological projections (e.g., SSP1-2.6 and SSP5-8.5 scenarios) will be used to simulate future changes in the 21st century. Particular attention will be given to the analysis of temperature extremes in conjunction with discharge. The second objective aims to characterize natural thermal regimes and spatialize these results at the scale of river basins. This will allow for the mapping of thermal regimes and provide a better understanding of their sensitivity to climate change. The third objective will focus on the impact of human activities (dams, reservoirs, etc.) on thermal regimes, quantifying anthropogenic alterations and comparing these with the natural thermal regimes identified previously. The application-oriented goal will focus on fish species, integrating modeled thermal metrics to assess favorable or constraining habitat conditions in the context of climate warming.

References

• Arismendi, Ivan, Mohammad Safeeq, Jason B. Dunham, et Sherri L. Johnson. 2014. « Can Air Temperature Be Used to Project Influences of Climate Change on Stream Temperature? » 9 (8). https://doi.org/10.1088/1748-9326/9/8/084015.
• Diamond, Jacob S., Florentina Moatar, Rémi Recoura-Massaquant, Arnaud Chaumot, Jay Zarnetske, Laurent Valette, et Gilles Pinay. 2023. « Hypoxia is common in temperate headwaters and driven by hydrological extremes ». Ecological Indicators 147 (mars):109987. https://doi.org/10.1016/j.ecolind.2023.109987.
• Isaak, D. J., S. Wollrab, D. Horan, et G. Chandler. 2012. « Climate Change Effects on Stream and River Temperatures across the Northwest U.S. from 1980–2009 and Implications for Salmonid Fishes ». Climatic Change 113 (2): 499‑524. https://doi.org/10.1007/s10584-011-0326-z.
• Isaak, Daniel J., Seth J. Wenger, Erin E. Peterson, Jay M. Ver Hoef, David E. Nagel, Charles H. Luce, Steven W. Hostetler, et al. 2017. « The NorWeST Summer Stream Temperature Model and Scenarios for the Western U.S.: A Crowd-Sourced Database and New Geospatial Tools Foster a User Community and Predict Broad Climate Warming of Rivers and Streams ». Water Resources Research. 53: 9181-9205. 53:9181‑9205. https://doi.org/10.1002/2017wr020969.
• Isaak, D.J., et B.E. Rieman. 2013. « Stream Isotherm Shifts from Climate Change and Implications for Distributions of Ectothermic Organisms ». Global Change Biology 19 (3): 742‑51. https://doi.org/10.1111/gcb.12073.
• Jackson, Faye, Iain Malcolm, et David Hannah. 2015. « A novel approach for designing large-scale river temperature monitoring networks ». Hydrology Research 47 (novembre):569‑90. https://doi.org/10.2166/nh.2015.106.
• Massey, Isaac, Muwaffak Osman, et Fei Yang. 2020. « An overview on cyanobacterial blooms and toxins production: their occurrence and influencing factors ». Toxin Reviews, novembre. https://doi.org/10.1080/15569543.2020.1843060.
• Piccolroaz, S., S. Zhu, R. Ladwig, L. Carrea, S. Oliver, A. P. Piotrowski, M. Ptak, et al. 2024. « Lake Water Temperature Modeling in an Era of Climate Change: Data Sources, Models, and Future Prospects ». Reviews of Geophysics 62 (1): e2023RG000816. https://doi.org/10.1029/2023RG000816.
• Turschwell, Mischa P., Stephen R. Balcombe, E. Ashley Steel, Fran Sheldon, et Erin E. Peterson. 2017. « Thermal habitat restricts patterns of occurrence in multiple life-stages of a headwater fish ». Freshwater Science 36 (2): 402‑14. https://doi.org/10.1086/691553.