Exploring snow and glacier melt contributions to streamflow in the French Alps through processedbased simulations of high-alpine catchments

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INRAE presentation

The French National Research Institute for Agriculture, Food, and Environment (INRAE) is a major player in research and innovation. It is a community of 12,000 people with 272 research, experimental research, and support units located in 18 regional centres throughout France. Internationally, INRAE is among the top research organisations in the agricultural and food sciences, plant and animal sciences, as well as in ecology and environmental science. It is the world’s leading research organisation specialising in agriculture, food and the environment. INRAE’s goal is to be a key player in the transitions necessary to address major global challenges. Faced with a growing world population, climate change, resource scarcity, and declining biodiversity, the Institute has a major role to play in building solutions and supporting the necessary acceleration of agricultural, food and environmental transitions.

Work environment, missions and activities

General context of the subject

 In many mountain regions, including the French Alps, a part of the precipitation is temporarily (or permanently) stored in the mountain cryosphere, mainly in the form of seasonal snow and glacier ice. The hydrology of such catchments is therefore strongly impacted by cryospheric processes that dictate when and how much water is released through melt. Snow and glacier fed catchments thus feature specific hydrological regimes, which are key to sustaining downstream water uses especially during warm and dry periods in spring and summer (Van Tiel et al., 2021). Today’s warming climate is drastically altering the mountain cryosphere, resulting in shorter snow seasons, more frequent of rain-on-snow events, and accelerating glacier retreat (Matiu et al., 2021; Sommer et al., 2020). Combined with increased frequency and duration of summer heat waves, the consequences of these changes on Alpine hydrology will be profound. Improved understanding of the role of snow and glaciers in the Alpine water cycle today can help make a cause for the fundamental need to limit climate warning, as well as mitigate the impact of changes in the future. However, quantifying the contribution of snow and glaciers to catchment runoff faces multiple challenges related to data availability, model adequacy, and methodology (Mimeau et al., 2019; Weiler et al., 2018) 

Project description

 During this PhD, we propose to study the contribution of snow and glacier melt to catchment runoff at high spatiotemporal resolution based on model simulations obtained with a dedicated, processbased modelling chain. Hydrological models traditionally include simple representations of snow and glacier melt based only on degree-day approaches, which neglect many of the complex driving processes. One of the reasons for this lies in the difficulty to provide high-quality meteorological forcing at high altitudes, which is needed for spatially distributed energy-balance-based models to yield meaningful results (Réveillet et al., 2018). Recent advances in meteorological downscaling approaches and spatially distributed snow- and glacier models now allow reassessing their potential for better quantifying surface water inputs from cryospheric components, as well as their temporal evolution (Berg et al., 2024). To address this research gap, the modelling chain envisioned for this project will incorporate detailed representations of seasonal snow and glaciers mass balance. The French Alps offer an ideal setting to develop, test and apply this methodology, thanks to a long standing cryospheric monitoring efforts in the context of the GLACIOCLIM observatory (https ://www.glacioclim.osug.fr) and various recent research projects, as well as runoff measurements operated by the state and various stakeholders from the private sector (e.g. EDF, CNR). The PhD project will comprise three major activities: 1. Compilation and acquisition of datasets for model forcing and evaluation: Gridded meteorological forcing fields at hourly resolution and for a study period of ~5 years will be assembled for 3-5 study areas, including partially glacierized catchments and observation sites (GLACIOCLIM, Jardin du Lautaret). For model evaluation and further finetuning, snow distribution datasets are of particular interest and will be acquired as part of this project to extend the existing data record. Operational glacier mass balance and streamflow measurements will also be considered. 2. Modelling of seasonal snow and glacier mass balance: The dedicated snow model FSM2trans will be set up for the study sites and assessed against observational datasets. FSM2trans has recently seen many additions, such as the implementation of lateral snow transport and ice melt. This project will represent one of the first applications to high-alpine terrain, thus enabling further finetuning for such use cases, and yield spatially distributed simulations of snow and ice melt at daily resolution. 3. Hydrological modelling and analysis: As last step, the outputs from FSM2trans will be used as surface water input to the hydrological model J2000. The resulting hydrological simulations will serve as basis to assess the contribution of snow and glacier melt to runoff at the sub-seasonal scale. Objectives The above activities will allow tackling the following research questions (to be tailored according to the candidate’s interests): 1. To what extent are observed spatio-temporal patterns of snow accumulation and melt affected by topography, the variability of meteorological forcings, and snow redistribution processes? 2. Is this spatio-temporal variability adequately captured by FSM2trans, and which model adaptations may further improve its performance? 3. Which features of the spatio-temporal variability of snow and ice melt matter for simulated catchment runoff at various spatial scales and topographic configurations? 4. How do the contributions of snow and glacier melt to runoff differ between catchments with varying land cover characteristics, e.g. between partly glacierized and non-glacierized catchments? 5. How do snow and glacier melt contributions to runoff and their seasonality depend on meteorological conditions, e.g., how do they differ between warm and cold winters, and what is the buffering effect of snow and glacier melt during dry spring and summer periods?

 

Objectives

 The above activities will allow tackling the following research questions (to be tailored according to the candidate’s interests): 1. To what extent are observed spatio-temporal patterns of snow accumulation and melt affected by topography, the variability of meteorological forcings, and snow redistribution processes? 2. Is this spatio-temporal variability adequately captured by FSM2trans, and which model adaptations may further improve its performance? 3. Which features of the spatio-temporal variability of snow and ice melt matter for simulated catchment runoff at various spatial scales and topographic configurations? 4. How do the contributions of snow and glacier melt to runoff differ between catchments with varying land cover characteristics, e.g. between partly glacierized and non-glacierized catchments? 5. How do snow and glacier melt contributions to runoff and their seasonality depend on meteorological conditions, e.g., how do they differ between warm and cold winters, and what is the buffering effect of snow and glacier melt during dry spring and summer periods?

 

Environment of the PhD project

 This PhD project will be at the interface of meteorology, cryospheric sciences, and hydrology, and include both an observational and a modelling component. Hosted by the Institute of Geosciences and Environment (IGE), it will benefit from a diverse research team featuring glaciologists, hydrologists, snow and climate scientists (e.g. Marion Réveillet, Thomas Condom, Martin Ménégoz, Laurent Oxarango), as well as a strong network of collaborators. The experimental part of the project will be conducted with GLACIOCLIM and IGE’s drone platform (collaboration Laurent Arnaud, Bruno Jourdain). These teams have acquired snow and glacier accumulation datasets at the sites of interest in the past using drone- and ground-based sensors (optical, LiDAR, GPR) and will advise and support further data acquisition and processing during this project. The project will use the process-based snow model FSM2trans, originally developed as open-source research model FSM (Essery, 2015). The model is now widely used, has been incorporated in Switzerland’s operational snow-hydrological modelling system (Mott et al., 2023) and further extended to include snow redistribution by wind and avalanches (Quéno et al., 2024) as well as an ice module for future coupling with the Open Global Glacier Model OGGM (B. Recinos, ongoing development). The application of FSM2trans to glacierized catchments is currently being tested for Swiss sites (collaborations Louis Quéno, Tobias Jonas (SLF), Matthias Huss, Marin Kneib (ETHZ)), will be further improved as part of this project, and potentially contribute to the integration of FSM2trans and OGGM (Maussion et al., (2019) collaboration Nicolas Champollion). Meteorological forcing data required to run FSM2trans will rely on the SAFRAN numerical weather prediction model and downscaling/assimilation approaches developed and applied at MétéoFrance/CEN (Vernay et al., (2022) collaboration Isabelle Gouttevin, Matthieu Lafaysse). Hydrological modelling will be performed in strong collaboration with the team RiverLy at INRAE, active users and developers of the J2000 model (Branger et al., (2016); collaboration Flora Branger, Olivier Champagne). The candidate will have the opportunity to co-supervise student internships as part of the project and disseminate research results at national and international scientific conferences and through publications in peer-reviewed journals.

The project is funded through the Juniour Professor Chair of Giulia Mazzotti (ANR package). Fieldwork will benefit from the GLACIOCLIM observatory and IGE’s drone platform (instrumentation and field support, access to data, data processing, etc.). Office space and the necessary IT infrastructure are provided. Datasets and model code (most of which is freely accessible) will be made available by the thesis supervisors and project collaborators. Finally access to the GRICAD laboratory's Dahu computing center will be offered to the PhD student.

Training and skills

We are looking for a highly motivated candidate with a background in Earth or environmental sciences, meteorology, or similar, a general interest in snow and glaciology, and proficiency in English speaking and writing. Affinity with physics and applied mathematics is necessary, programming skills are a plus. The candidate should further be keen on conducting fieldwork in Alpine terrain under cold conditions and enjoy working in a team.

INRAE's life quality

By joining our teams, you benefit from (depending on the type of contract and its duration):

- up to 30 days of annual leave + 15 days "Reduction of Working Time" (for a full time);
- parenting support: CESU childcare, leisure services;
- skills development systems: training, career advise;
- social support: advice and listening, social assistance and loans;
- holiday and leisure services: holiday vouchers, accommodation at preferential rates;
- sports and cultural activities;
- collective catering.

How to apply

I send my CV and my motivation letter