PhD position on modeling of future shoreline evolution (BRGM & EPOC, France)
Déborah Idier
Doctoral School: Ecole Doctorale #304 Sciences & Environnement (Université de Bordeaux)
Employer: BRGM
Salary (approximately): 27.6 k€ (gross) / year
Location: France/Orléans (BRGM), with short stays at France/Pessac (BRGM/EPOC)
ABSTRACT
Sandy beaches, which cover approximately one third of the world’s ice-free coastline, provide essential recreational, tourism, and ecosystem services while also acting as buffer zones against flooding. A recent analysis of shoreline changes based on satellite imagery revealed that one quarter of the world’s sandy beaches are undergoing chronic erosion (Luijendijk et al., 2018). This situation is expected to worsen with climate change and sea-level rise (Vousdoukas et al., 2020). However, accurately predicting this evolution remains challenging. First, the evolution of sandy beaches is influenced by numerous nonlinear natural processes that interact across different temporal (from a few hours to several centuries) and spatial scales (from a few meters to several hundred kilometers), mainly driven by waves and changes in mean sea level. Therefore, estimating future changes based on past trends has significant limitations, particularly at sites that may experience shifts in their evolutionary trajectories due to system nonlinearities. Projections of future shoreline retreat are highly uncertain because of intrinsic uncertainties (e.g., internal variability of the climate system) and knowledge-related uncertainties (e.g., shared socioeconomic pathway scenarios, coastal erosion models), resulting in deep uncertainty (Thiéblemont et al., 2021). Coastal management approaches or adaptation strategies constitute an additional factor generating uncertainty in future evolution predictions, as these strategies are themselves intrinsically linked to shoreline changes. An optimal coastal planning strategy, which may vary over time and space, must therefore take into account all these determining factors, how they interact with one another and may evolve in the future to impact shoreline change, as well as how human intervention could influence this evolution. To achieve this goal, there is an urgent need to improve shoreline change prediction methods by incorporating coastal adaptation strategies (e.g., hard protection structures, beach nourishment) and the associated uncertainties for the coming decades. Indeed, uncertainties related to management measures and adaptation pathways are most often neglected, and there are very few quantitative applications of DAPP for coastal erosion management, with the exception of, for example, (Toimil et al., 2021), which limits a comprehensive assessment of uncertainties associated with shoreline change projections.
The ANR SHORECAST project (2026–2031), within which this PhD is embedded, aims to develop a robust and computationally efficient hybrid modeling approach to predict the evolution of sandy coastlines, accounting for climate change and dynamic coastal management strategies across various contexts and spatial and temporal scales (from local to regional, and from annual to centennial).
The PhD research will primarily focus on: (1) hybrid modeling of shoreline evolution under the combined effects of waves and sea-level rise, dynamically incorporating coastal management actions; (2) quantification of the associated uncertainties and the resulting cascade of uncertainties.
The main research question is: “What uncertainties are associated with the effects of sea-level rise and management strategies in modeling future shoreline evolution?”
The underlying research questions are:
• How can future shoreline evolution be modeled in a fast and robust manner?
• What are the possible adaptation pathways for the selected sites, and the associated shoreline changes?
• How can the cascade of uncertainties be quantified?
This PhD aims to: (1) extend the scope of reduced-complexity models such as LX-Shore (Robinet et al., 2018; a shoreline evolution model co-developed by BRGM & EPOC) by using a hybrid modeling approach that combines wave metamodeling techniques and data assimilation, and that allows dynamic simulation of coastal management actions; (2) assess how the cascade of uncertainties may affect shoreline forecasts over time. With regard to objective (1), this PhD will build upon developments carried out elsewhere within the SHORECAST project.
This work will be conducted at a minimum of two sites, including one corresponding to one of the two planned demonstration (DEMO) sites (i.e., a site involving interactions and workshops with coastal managers).
References
Luijendijk et al., The State of the World’s Beaches, Sci Rep. 8 (1) (2018).
Robinet et al., A reduced-complexity shoreline change model combining longshore and cross-shore processes: The LX-Shore model, Environ. Modell. Soft. 109 (2018)
Thiéblemont et al., Deep uncertainties in shoreline change projections: an extra-probabilistic approach applied to sandy beaches, Nat. Hazards Earth Syst. Sci.. 21 (7) (2021).
Toimil et al., Using quantitative dynamic adaptive policy pathways to manage climate change-induced coastal erosion, Clim. Risk Manag. 33 (2021)
Vousdoukas et al., Sandy coastlines under threat of erosion, Nat. Clim. Chang. 10 (3) (2020).
Keywords
Modeling, shoreline, climate change, sea-level rise, management actions, adaptation
Funding
This work will be funded by the ANR SHORECAST project (2026–2030), involving BRGM, EPOC, IMT, ISAE-SUPAERO, and WMC, with numerous international collaborations. The project will also cover the PhD’s operating costs (computer equipment, participation in conferences and workshops, publication fees, etc.). The PhD candidate will be employed by BRGM.
CANDIDATE PROFILE
We seek highly motivated candidates with:
● MSc degree in Physical Oceanography, Fluid Mechanics, Numerical Computations, coastal engineering, physical oceanography, or a closely related discipline;
● Good knowledge of nearshore and/or morphodynamic processes;
● Strong background in numerical modelling and scientific programming (e.g.: Fortran, Python, Matlab).
● Proficient in English and excellent scientific writing skills.
● Strong motivation for academic research.
The selected candidate should, if possible, have also the following qualities: autonomy, scientific curiosity, open-mindedness. She/he should have if possible excellent teamwork, writing and communication skills. Skills in French reading, writing and speaking will also be appreciated.
APPLICATION PROCEDURE
The PhD contract is for a duration of three years, with a start date in October 2026. Applicants must send the documents listed below by email to Bruno Castelle (bruno.c...@u-bordeaux.fr) and Déborah Idier (d.i...@brgm.fr) before April 28, 2026. Pre-selected candidates will be interviewed on May 6, 2026.
● Letter of motivation
● CV
● Master's grades
● Contact details of 2 referees
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