On May 10^th, 2018, an unprecedented long and intense seismic crisis started offshore, east of Mayotte, the easternmost of the Comoros volcanic islands. The population felt hundreds of events. Over the course of one year, 32 earthquakes with magnitude greater than 5 occurred, including the largest event ever recorded in the Comoros (M_w = 5.9 on May 15^th, 2018). Earthquakes are clustered in space and time. Unusual intense long lasting monochromatic very long period events were also registered. From early July 2018, Global Navigation Satellite System stations and Interferometric Synthetic Aperture Radar registered a large drift, testimony of a large offshore deflation. We describe the onset and the evolution of a large magmatic event thanks to the analysis of the seismicity from the initiation of the crisis through its first year, compared to the ground deformation observation (GNSS and InSAR) and modelling. We discriminate and characterise the initial fracturing phase, the phase of magma intrusion and dike propagation from depth to the sub-surface, and the eruptive phase that starts on July 3^rd, 2018, around fifty days after the first seismic events. The eruption is not terminated two years after its initiation, with the persistence of an unusual seismicity, whose pattern has been similar since summer 2018, including episodic very low frequency events presenting a harmonic oscillation with a period of ∼16 s. From July 2018, the whole Mayotte Island drifted eastward and downward at a slightly increasing rate until reaching a peak in late 2018. At the apex, the mean deformation rate was 224 mm yr⁻¹ eastward and 186 mm yr⁻¹ downward. During 2019, the deformation smoothly decreased and in January 2020, it was less than 20 per cent of its peak value. A deflation model of a magma reservoir buried in a homogenous half space fits well the data. The modelled reservoir is located 45 ± 5 km east of Mayotte, at a depth of 28 ± 3 km and the inferred magma extraction at the apex was ∼94 m³ s⁻¹. The introduction of a small secondary source located beneath Mayotte Island at the same depth as the main one improves the fit by 20 per cent. While the rate of the main source drops by a factor of 5 during 2019, the rate of the secondary source remains stable. This might be a clue of the occurrence of relaxation at depth that may continue for some time after the end of the eruption. According to our model, the total volume extracted from the deep reservoir was ∼2.65 km³ in January 2020. This is the largest offshore volcanic event ever quantitatively documented. This seismo-volcanic crisis is consistent with the trans-tensional regime along Comoros archipelago.

Data provided by accelerometric networks are important for seismic hazard assessment. The correct use of accelerometric signals is conditioned by the station site metadata quality (i.e., soil class, V_S30, velocity profiles, and other relevant information that can help to quantify site effects). In France, the permanent accelerometric network consists of about 150 stations. Thirty-three of these stations in the southern half of France have been characterized, using surface-wave-based methods that allow derivation of velocity profiles from dispersion curves of surface waves. The computation of dispersion curves and their subsequent inversion in terms of shear-wave velocity profiles has allowed estimation of V_S30 values and designation of soil classes, which include the corresponding uncertainties. From a methodological point of view, this survey leads to the following recommendations: (1) perform both active (multi-analysis surface waves) and passive (ambient vibration arrays) measurements to derive dispersion curves in a broadband frequency range; (2) perform active acquisitions for both vertical (Rayleigh wave) and horizontal (Love wave) polarities. Even when the logistic contexts are sometimes difficult, the use of surface-wave-based methods is suitable for station-site characterization, even on rock sites. In comparison with previous studies that have mainly estimated V_S30 indirectly, the new values here are globally lower, but the EC8-A class sites remain numerous. However, even on rock sites, high frequency amplifications may affect accelerometric records, due to the shallow relatively softer layers.

Quantitative estimation of seismic risk over a region requires both an underlying probabilistic seismic hazard model and a means to characterise shallow site response over a large scale. The 2020 European Seismic Risk Model (ESRM20) builds on the 2020 European Seismic Hazard Model (ESHM20), requiring additional information to firstly parameterise the local site condition across all of Europe, and subsequently determine its influence on the prediction of seismic ground motion. Initially, a harmonised digital geological database for Europe is compiled, alongside a model of topographic/bathymetric elevation and a database of 30 m averaged shearwave velocity measurements ( $$V_{S30}$$VS30 ), in order to produce separate 30 arc-second maps of inferred $$V_{S30}$$VS30 based on topography and on geology. We then capitalise on a large database of seismic recording stations in Europe for which site-to-site ground motion residuals ( $$\delta S2S_{S}$$δS2SS ) have been determined with respect to the shallow crustal ground motion model used in the ESHM20. These residuals allow us to incorporate site amplification functions into the European GMM calibrated upon either observed or inferred $$V_{S30}$$VS30 , or on the European geology and topography models. We present the resulting pan-European seismic site amplification model and assess its impact on seismic hazard and risk compared against other approaches. The new site amplification model fulfils the requirements of the ESRM20 and, providing uncertainty is fully propagated, yields estimates of seismic hazard and risk at a large space scale that may be comparable to other methods often applied at local/urban scale where better-constrained site information is available.

This article studies the effects of the soil data and exposure data of residential building inventories, as well as their spatial resolution, on seismic damage and loss estimates for a given earthquake scenario. Our aim is to investigate how beneficial it would be to acquire higher resolution inventories at the cost of additional effort and resources. Seismic damage computations are used to evaluate the relative influence of varying spatial resolution on a given damage model, where other parameters were held constant. We use soil characterization maps and building exposure inventories, provided at different scales from different sources: the European database, a national dataset at the municipality scale, and local field investigations. Soil characteristics are used to evaluate site effects and to assign amplification factors to the strong motion applied to the exposed areas. Exposure datasets are used to assign vulnerability indices to sets of buildings, from which a damage distribution is produced (based on the applied seismic intensity). The different spatial resolutions are benchmarked in a case-study area which is subject to moderate-to-average seismicity levels (Luchon valley in the Pyrénées, France). It was found that the proportion of heavily damaged buildings is underestimated when using the European soil map and the European building database, while the more refined databases (national/regional vs. local maps) result in similar estimates for moderate earthquake scenarios. Finally, we highlight the importance of pooling open access data from different sources, but caution the challenges of combining different datasets, especially depending on the type of application that is pursued (e.g., for risk mitigation or rapid response tools).

Over recent years, many studies devoted to large-scale seismic risk analyses have been carried out in different regions and by various research teams. A wide variety of software is available to perform these analyses: they are more or less flexible and use different levels of precision to model ground motion and vulnerability of the built environment. All are based on risk calculation through the convolution of hazard and vulnerability. This article presents a seismic risk analysis tool, Armagedom, implemented over the past five years on a variety of urban seismic contexts: Bouzareah (Algeria), four provinces in Iran, the French Departments lying along the French/Spanish border, and Overseas Departments in the French Antilles. The objectives and requirements of these studies differed with respect to the level of precision that was sought and the surface areas examined. In order to meet differing project targets, three levels of seismic risk assessment were defined based on the macroseismic and mechanical approaches for vulnerability and damage estimation presenting different levels of precision: Level N0 estimates seismic risk on a regional territorial scale based on the macroseismic approach and existing statistical data; Level N1 yields the seismic risk at a district level based on the macroseismic approach and on visual evaluation of the vulnerability of structures over an itinerary in the area to be analyzed; and Level N2 also establishes the seismic risk at a district level, but the hazard description is represented by a spectrum and vulnerability is estimated based on mechanical models. The software, with a modular design, was developed in order to optimize computation time and automate execution of the three levels of analysis. In this article, the software modules are illustrated by maps derived from the seismic risk analyses performed. We further use the available event information to test, validate, and update the methods and software presented in this article.