Overseas risks, tsunami, and hydro-climatic risks in Overseas Territories

Research axes and expected outcomes

The research work is organized around three axes:

1. Developing innovative multi-sensor instrumentation for observing seismo-volcanic phenomena and monitoring building damage within a neighborhood

This axis focuses on creating a borehole sensor network on Martinique to detect early disturbances in the physico-chemical processes of magma storage systems, which may signal potential magma ascent. A major challenge is to design a resilient network capable of acquiring data before, during, and after an eruption. Scientists also deploy a low-cost sensor network to monitor in real time the vibrational response and deformation of buildings (private, strategic, and critical infrastructure) in order to characterize the diversity of damage within a given area, and among similar building types. They further analyze the social and political dimensions of deploying such instrumentation, the ways it can be integrated into existing observation and monitoring systems, its adoption by various stakeholders (citizens, public and private actors), and its impact on collaborations among scientists, citizens, and public authorities in understanding, reducing, and managing risks.

2. Estimating damage and socio-economic impacts linked to tsunami risk

This axis focuses on developing a chain of tools that link advanced mathematical and numerical models with geophysical, geological, civil engineering, geographic, and economic data to analyze hazards, risks, and socio-economic impacts of tsunamis generated by landslides in an active seismo-volcanic context.

Scientists rely on data collected by the Mayotte Volcanological and Seismological Monitoring Network (REVOSIMA) and prior research. They refine tsunami-generating sources corresponding to the most probable and damaging scenarios (an essential step in tsunami risk assessment) and simulate wave generation near these sources. These tools will help characterize exposure and vulnerability and quantify impacts on housing and infrastructure on Mayotte. Vulnerability analyses will identify levers for prevention and crisis management adapted to the local context. These insights are essential for developing decision-making support tools and co-designing preventive solutions with territorial stakeholders, such as decision-makers, managers, and local populations.

3. Cyclone crisis management and coral island adaptation

This axis addresses, first, risks linked to extreme cyclone events, with New Caledonia as the study area, located along the path of Pacific cyclones. The objective is to characterize marine flooding and landslide hazards during crisis situations, ultimately aiming to automate hazard forecast bulletins associated with cyclone landfalls.

Scientists rely on data collected by the Mayotte Volcanological and Seismological Monitoring Network (REVOSIMA) and prior research. They refine tsunami-generating sources corresponding to the most probable and damaging scenarios (an essential step in tsunami risk assessment) and simulate wave generation near these sources. These tools will help characterize exposure and vulnerability and quantify impacts on housing and infrastructure on Mayotte. Vulnerability analyses will identify levers for prevention and crisis management adapted to the local context. These insights are essential for developing decision-making support tools and co-designing preventive solutions with territorial stakeholders, such as decision-makers, managers, and local populations.

Second, it focuses on risks related to climate change on coral islands, with as pilot sites Bora Bora (a high island with an urbanized barrier reef) and the nearby uninhabited atoll of Tupai in French Polynesia. Scientists aim to characterize shoreline evolution since the 1950s, the protective and sediment-producing role of coral reefs, and inhabitants’ perceptions of observed phenomena. Laboratory experiments are used to assess coral responses to climate hazards (sea-level rise and wave forces), and these data are used in numerical simulations of coastal erosion based on future scenarios. These results support the development of coastal evolution trajectories and the identification of possible adaptation strategies based on nature-based solutions.