South-East France is found in a continental active tectonic domain where seismic activity is low to moderate and crustal deformation is slow, nevertheless historical seismic catalogs (Rovida et al., 2022) present about 10 Mw 5 and 1 Mw 6 events per century. In a region of such seismic activity the identification and characterisation of active faults is a challenging task, as neither seismicity nor surface deformation records (~ 1000 years of macroseismic data, ~ 60 years of instrumental seismicity, and ~ 25 years of GNSS acquisitions) provide conclusive evidence for larger events with long recurrence intervals (> 1000 years). Moreover the geological structure is complex due to the diverse tectonic history of the region. This results in the presence of a dense network of compound fault systems and difficults the identification of which faults are accommodating the deformation. This region has however been one of the most densely instrumented in France for over 20 years with seimic (Sismalp, Langlais et al., 2024)  and GNSS networks (Walpersdorf et al., 2018), hence, presenting a notable resolution of geophysical observations.

The aim of this study is to constrain earthquake recurrence models which exploit the vast amount of up-to-date geophysical and geological data with a culminating objective of PSHA (Probabilistic Seismic Hazard Assessment) for SE France. We present 2 earthquake source models. The first integrates main faults, in which we determine the geometry, potential maximum magnitude after empirical scaling relationships (Leonard et al., 2014) based on maximum length, potential slip rates based on a systematic analysis of local GNSS velocities and the resulting magnitude-frequency distributions. Fifteen faults are considered, critically selected from the newly built SEFPAF (South-East France Potentially Active Faults) catalog and combined with a smoothed seismicity model for off-fault earthquakes. The second source model is a 3 dimensional tectonic zonation which takes into account not only static criteria (geological maps and structures) but also dynamic criteria such as seismogenic depth (Sismalp; SIHex, BCSF-Rénass, 2022), seismic flux and maximum observed magnitudes (FCAT, Manchuel et al., 2017; ESHM20, Danciu et al., 2024), focal mechanisms (Mathey et al., 2020), surface strain derived from GNSS and InSAR (Piña-Valdés et al., 2022, Mathey et al., 2021), local stress derived from gravimetric models (Camelbeeck et al., 2014), the Moho depth derived from tomographic studies (Nouibat et al., 2022) and 3D geological models (Bienveignant et al., 2024). Once combined with ground motion models, these different source models will then be analysed in terms of resulting seismic hazard levels to better understand the impact of the hypotheses and assumptions underlying PSHA in this region.

How to cite: Mowbray, V., Beauval, C., Sue, C., Mathey, M., Walpersdorf, A., Baize, S., and Lemoine, A.: Combining updated structural and geophysical data into earthquake recurrence models for the SE of France, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16987, https://doi.org/10.5194/egusphere-egu25-16987, 2025.

Earthquakes Early Warning Systems (EEWS) are one of the most effective tools to prevent and mitigate the damage that can be caused by earthquakes. Since October 2015, the Department of Earth Physics and Astrophysics of the Complutense University of Madrid has implemented an operational EEWS throughout the Ibero–Maghrebian Region (IMR). This system is based on the PRESTo (Probabilistic and Evolutionary Early Warning SysTem, Satriano et al. [2011]) software. Currently, a new EEWS (QuakeUp, Zollo et al. [2023]) based on the progressive temporal prediction of ground motion (‘’shaking’’) is being implemented in the same department. Not only does it provide an early determination of the hypocenter and magnitude, like the current EEWS, but the new method also combines Peak Ground Velocity (PGV) predictions calculated from observed P-wave amplitudes and region-specific Ground Motion Prediction Equation (GMPE) for the IMR, while using progressively updated estimates of earthquake location and magnitude.  As a result, it provides an ‘early’ P-wave-based shake map that is updated over time, offering a real-time, evolving map of the Potential Damage Zone (PDZ) defined as those zones where the Instrumental Intensity (I_MM), calculated in terms of PGV, exceeds a previously defined threshold. This EEWS method has been validated using data from the 2016 Alboran Sea seismic series (M_w 5.0–6.4), which showed minimal discrepancies in origin time, epicenter location, and magnitude estimates compared to previous studies. A retrospective performance analysis for the M_w 6.4 main shock indicated lead-times of 14 to 62 s at a PGV threshold of 0.20 cm/s, with lead-times increasing with distance. At a higher threshold of 0.60 cm/s, the lead-time was 20 seconds for distances up to 170 km. The accuracy of impact predictions improved over time, with successful alerts rising from 72% to 90% as the final predictions were made. Despite some limitations due to focusing on moderate-magnitude earthquakes (M_w ≤ 6.4), the EEWS method has proven effective for offshore events in areas with sparse instrumentation.

How to cite: Escudero, L., Zollo, A., Mattesini, M., Rea, R., Elia, L., Colombelli, S., and Buforn, E.: Performance of an impact-based Earthquake Early Warning System in the Alboran Sea, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4255, https://doi.org/10.5194/egusphere-egu25-4255, 2025.

This study is part of the Probabilistic Fault Displacement Hazard Analysis (PFDHA) framework, which assesses the hazard posed by coseismic surface faulting to infrastructure systems (e.g., lifelines, nuclear power plants, and dams) located on or near an earthquake fault trace. The primary objective of this study is to estimate the probability of surface rupture on the principal fault—the main fault responsible for seismic moment release—based on faulting style, seismogenic thickness, fault geometry, and rupture size (i.e., earthquake magnitude). Current methods for estimating the probability of surface rupture on the principal fault are primarily based on empirical models. These models rely on observations of surface rupture occurrences versus non-occurrences, analyzed through logistic regressions using global or regional datasets of historical crustal earthquakes. However, empirical models have several limitations, including potential biases, catalog incompleteness (i.e., missing surface rupture data), and inconsistencies in fault geometry information and seismotectonic settings (e.g., seismogenic thickness). To overcome these limitations, we propose a numerical approach to compute the Conditional Probability of Surface Rupture (CPSR). This approach incorporates faulting style (normal, reverse, strike-slip), seismogenic thickness, fault dip, magnitude-dependent scaling relations for rupture shape and size, nucleation position within the rupture, and the statistical distribution of hypocenters within the seismogenic crust. These parameters are derived from statistical analyses of global fault rupture databases and earthquake distributions in various non-subduction seismotectonic settings. Our results indicate that CPSR probabilities are strongly influenced by seismogenic thickness and fault dip angle. Moreover, comparison between numerical results and empirical models suggests that CPSR depends on the specific characteristics of the study area. This model can be integrated into PFDHA as an epistemic alternative to purely empirical approaches. Additionally, the numerical code for CPSR computation has been developed and is openly available on GitHub.

How to cite: Mammarella, L., Visini, F., Boncio, P., Baize, S., Scotti, O., Beauval, C., Pace, B., and Thompson, S.: A numerical approach for estimating the probability of earthquake surface rupture, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5092, https://doi.org/10.5194/egusphere-egu25-5092, 2025.

A robust seismic hazard model for a region, in principle, requires a sense of the likelihood of every conceivable earthquake affecting that region - or, short of that, the likelihood of an exhaustive (with respect to hazard) set of possible earthquake scenarios. A central component of this (as implemented in recent seismic hazard models for California, New Zealand, the United States and elsewhere) is a "grand inversion" approach (Page et al., 2014; Field et al., 2014, 2021; 2024; Milner et al., 2022; Milner and Field, 2024), in which one:

1) generates a large (order 1e5-1e6) set of simple scenario ruptures on known faults, noting their magnitudes and how much surface slip each would produce (model matrix G);

2) assembles geologic and geodetic constraints on total fault-slip rates, paleoseismologic constraints on large-earthquake recurrence intervals, and seismic-catalogue constraints on the total magnitude-frequency distribution in the system (constraint vector d);

3) "inverts" the constraint vector and model matrix to estimate the rate of each scenario rupture in the system.

The model space is large and underdetermined (Page et al., 2014), so up to now, a simulated-annealing approach has been used to efficiently find a global-minimum solution that best fits the constraints. Then the uncertainties on the constraints, trade-offs between model elements, and prediction uncertainties have been propagated into the solution space by carrying many grand inversions with different input constraints (e.g. geologic or geodetic data or both, various b-values, various slip scaling laws) in each branch of a large logic tree, and by toggling importance weights on different constraints.

These grand inversions formed a central component of the New Zealand National Seismic Hazard Model 2022 (Gerstenberger et al., 2024). In this process, we identified two characteristics that merit further work and may substantially impact estimated hazard levels. First, the current simulated-annealing approach return very sparse solutions. The input scenario-rupture sets for New Zealand feature several hundred faults, several thousand fault subsections and 1e5-1e6 plausible ruptures, but the grand inversions typically assign a rate of 0 to all but ~1000 ruptures, and many faults have only one or a few nonzero-rate ruptures (effectively a nearly characteristic model). Second, the grand inversions output only the global-minimum solution rather than the entire model-space exploration. This means that many of the uncertainties on the constraints (those that are not toggled overhead as alternate logic-tree branches), such as fault slip rate uncertainties, are not propagated into the model space except as weights. To overcome these limitations, we are making the grand inversions Bayesian by replacing the simulated-annealing approach with a Monte Carlo search with No U-Turn Sampling, and outputting the full posterior distribution of the model space. This will allow the grand inversions to propagate the full range of possible scenario ruptures on each fault into hazard estimates (modulo the data constraints) rather than only a few select ruptures.

How to cite: Rollins, C., DiCaprio, C., Jurgens, O., and Gerstenberger, M.: Estimating the likelihoods of many earthquake scenario ruptures in a region in hazard models: Making grand inversions Bayesian, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5251, https://doi.org/10.5194/egusphere-egu25-5251, 2025.

The 2023 Mw 6.8 earthquake that struct the Al Haouz region in Morroco causes significant ground shaking. This event took place in the western part of the Moroccan High Atlas domain and it had a major effect on the built environment. Many buildings collapsed, roughly, 3,000 people were killed and 6,000 were injured as a result of the earthquake. Unreinforced masonry and adobe buildings in isolated mountain settlements suffered the worst damage. Ground motion parameters such as peak ground acceleration (PGA), peak ground velocity (PGV), and spectral acceleration (SA) are crucial in estimating the seismic performance of structures, assessing the effect of site effects, modeling ground motions for seismic hazard assessments, and update of seismic design regulations. The seismic features of ground movement in Al Haouz were analyzed, identifying factors such as fault rupture, soil conditions, and earthquake source characteristics that influence the strong shaking. One of the three-component acceleration records that was investigated was from a seismic station located near the earthquake epicenter (24 km away), which had a peak (horizontal) ground acceleration of ~0.28 g. We discuss vertical motions recorded from this earthquake as the vertical movement of the ground during earthquakes can also greatly influence the structural integrity of buildings. Finally, preliminary distributions and measures of the average shear wave velocity (Vs30) in the Al Haouz region are discussed, as these values have been used to represent site effects in many ground motion studies and building codes.

How to cite: EL Hilali, M., Silva, V., Timoulali, Y., and Allaoui, A.: Assessment of the strong ground motions from the Mw 6.8 earthquake on September 08, 2023 (High Atlas, Morocco) , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9721, https://doi.org/10.5194/egusphere-egu25-9721, 2025.

Empirical methods for the development of fragility functions employ observational damage data collected after an earthquake. Observations at various locations, which are graded based on a predefined damage scale, are correlated to a ground motion intensity measure and as a result of this statistical process fragility functions are generated. This procedure essentially requires characterization of corresponding ground motion intensity levels that the buildings in the damage data set have experienced. Ideally, recorded ground motion data across the surveyed areas would be used for intensity level assignments. However, due to the scarcity of ground motion recordings, ground motion intensity values over the geographical extent where the damaged buildings spread out are obtained, in practice, through ground motion prediction equations (GMPEs) or physics based ground motion simulations, which come with certain complexities and at additional computational cost. The estimated ground motions can then be further improved by the incorporation of the recorded values, if any available. After the Feb. 6, 2023 Kahramanmaraş-Türkiye earthquakes we derived fragility functions (Hancilar and Acikgoz, 2024a) using the official field based damage data (2023) and the rapid ground shaking estimations (Hancilar et al., 2023). We recently revisited our analyses for the computation of the spatial distributions of ground shaking intensities by incorporating different local site effect models, ground motion predictive models as well as by implementing bias adjustments on the ground motion estimations with the addition of more strong motion recording stations (Hancilar and Acikgoz, 2024b). This study deals with the re-derivation of fragility functions with different ground motion inputs while the building damage data kept unchanged. The resulting fragilities are compared and the effect of the ground motion uncertainty is examined.

How to cite: Hancilar, U. and acikgoz, N.: Ground Motion Uncertainty in Deriving the Empirical Fragility Functions after the Feb. 6 2023 Kahramanmaraş-Türkiye Earthquakes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-579, https://doi.org/10.5194/egusphere-egu25-579, 2025.

Retrofitting techniques that address energy efficiency and seismic performance are necessary since aging buildings face challenges in achieving sustainability and resilience standards, especially in Taiwan. Exoskeleton reinforcement and exoskeleton systems, combined with photovoltaic (PV) panel walls, are the two retrofitting solutions evaluated in this study. These strategies aim to enhance building performance by mitigating seismic losses and energy performance and assessing environmental impacts. The FEMA P-58 approach, which incorporates near-field ground motion data from the PEER database, applies to evaluate seismic performance. Key performance indicators include carbon emissions, embodied energy, repair time, and cost. According to findings, exoskeleton retrofitting significantly improves structural resilience, which lowers repair costs and enhances recovery after seismic occurrences. By reducing operating expenses and carbon emissions and promoting renewable energy generation, the incorporation of photovoltaic (PV) panel walls further maximizes energy efficiency. These combined retrofitting techniques successfully advance sustainability goals by presenting a comprehensive strategy for reducing environmental effects and improving seismic safety. This research emphasizes integrating technology with advanced seismic retrofitting procedures to achieve long-term sustainability and resilience in the built environment. The outcomes provide helpful information for engineers, stakeholders, and users, supporting retrofitting as an economical and sustainable way to transform aging facilities.

How to cite: Permata, R. and Lin, S.-Y.: Integrated Retrofitting Strategies for Aging Buildings: Bridging Seismic Risk Mitigation and Sustainability, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7872, https://doi.org/10.5194/egusphere-egu25-7872, 2025.

Lebanon is an earthquake-prone country along the Levant Fault System, with three branches within 35 km of Beirut. Thus, this study focused on establishing seismic risk scenarios for Beirut, Lebanon, through the Deterministic Seismic Hazard Analysis (DSHA) approach considering lithological site effects. Three seismic scenarios were studied on the Mount Lebanon Thrust fault, Roum Fault, and Yammouneh Fault. Seismic hazard determination was done through the estimation of the Peak Ground Acceleration (PGA) using the Ground Motion Models (GMM) of Akkar et al. (2014), Chiou and Youngs (2014), and Kotha et al. (2020) and then converting these values to macroseismic intensities. In all models and scenarios, lower PGA and intensities were found, located along the Achrafieh and Ras Beyrouth hills. PGA of up to 1.50 g was obtained for Mount Lebanon Thrust fault, resulting in an intensity of up to XI. Meanwhile, both Roum and Yammouneh Faults generated a maximum PGA of 0.25 g and a maximum intensity of VIII. Mean damage grade and damage grade distribution prediction in Beirut were determined based on the vulnerability indices of the buildings that are based on the RISK-UE methodology. Beirut consists mainly of masonry and reinforced concrete buildings with a maximum plausible vulnerability index of 0.953 and 0.800, respectively. Beirut was found to have the highest mean damage grade of 4.53 due to the seismic scenario of the Mount Lebanon Thrust fault. Earthquakes on both Roum and Yammouneh Faults generated similar mean damage grades at 1.71. For the damage grade distribution, 30 – 40% of the buildings in Beirut were expected to experience moderate to very heavy damage. However, the impact of site effect on the damage grade distribution in Beirut was not observed, suggesting that lithologic site effects play no significant role in damage grade prediction in the Beirut context. The results of this study can serve as a basis for improving the building code of Beirut and Lebanese seismic design, to strengthen and regulate earthquake safety and conditions. Potential improvements in policies related to these results are essential economically and help in preserving cultural heritage, as historical buildings are among the most vulnerable structures to earthquakes.

How to cite: Varela, R. K., Bertrand, E., Brax, M., and Bourdeau-Lombardi, C.: Seismic risk scenarios for Beirut, Lebanon, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-169, https://doi.org/10.5194/egusphere-egu25-169, 2025.

Italian National Civil Protection Exercises play a pivotal role in enhancing emergency response capabilities by testing operational efficiency, verifying emergency plans, and fostering cooperation among institutions and the public. The Exe Flegrei 2024 exercise exemplifies these objectives, focusing on the volcanic risk associated with the densely populated and geologically complex Campi Flegrei area in Italy. This exercise also integrates advanced data model outputs and scientific contributions from scientific partners of the Civil Protection Dept, including the CNR-IMAA, who provides essential tools and platforms for integrating data on risk planning and emergency management.

Objectives and Scope:

Exe Flegrei 2024 aims to simulate a large-scale volcanic emergency, testing various aspects of preparedness, including:

• Emergency Plan Validation: Ensuring that plans are coherent, effective, and applicable to real-world scenarios.
• Interinstitutional Coordination: Strengthening collaboration among national, regional, and local authorities as well as private organizations.
• Public Awareness and Training: Educating citizens on self-protection measures and evacuation protocols.
• Data Interoperability: Assessing the integration of diverse datasets and model outputs, provided by scientific institutions, to support decision-making during crises.

The Role of CNR-IMAA and Data Interoperability:

One of the distinguishing features of Exe Flegrei 2024 is its focus on testing the interoperability of data and model outputs from the scientific competence centers of the National Civil Protection Department. Among these, the CNR-IMAA (National Research Council – Institute of Methodologies for Environmental Analysis) plays a key role by delivering:

• Tools and platforms for integrated data management.
• Solutions to facilitate the visualization and analysis of risks and emergency scenarios.
• Support for the operational planning of risk mitigation strategies.

Scenario Simulation:

The exercise simulates a hypothetical escalation in volcanic activity leading to a potential eruption. Key actions include:

• Activating alert levels.
• Planning and managing mass evacuations.
• Simulating emergency response operations, including real-time monitoring and communication.

The exercise also examines how scientific data flows, including geophysical and environmental modeling, can be effectively integrated into operational decision-making frameworks.

Outcomes and Lessons:

Exe Flegrei 2024 demonstrated that National Exercises produce significant benefits, including:

• Enhanced efficiency in evacuation procedures and resource allocation
• Improved public awareness and preparedness
• Identification of operational or logistical weaknesses
• Strengthened collaboration between institutions and scientific centers

A critical focus is the validation of data interoperability mechanisms to ensure seamless integration of scientific inputs into emergency operations. By leveraging platforms provided by institutions like CNR-IMAA, the exercise demonstrates the importance of advanced technological and methodological support in modern civil protection strategies.

Conclusion:

Exe Flegrei 2024 underscores the strategic importance of national exercises in addressing complex risks like those posed by the Campi Flegrei volcanic system. Beyond traditional objectives, it highlights the critical role of scientific and technological contributions, especially in the realm of data interoperability and decision support. These initiatives build a culture of preparedness, improve operational response, and ensure a more resilient society.

How to cite: Amato, L., Izzi, F., Cavarra, L., La Scaleia, G., Salvia, V., and Maio, D.: The Crucial Role of National Exercises and Data Interoperability in Enhancing Emergency Management: Lessons from Exe Flegrei 2024, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18620, https://doi.org/10.5194/egusphere-egu25-18620, 2025.