The range of topics currently addressed by the tsunami scientific community includes
-Analytical and numerical modelling of tsunami generation, propagation and inundation from various triggering mechanisms, including single or multi-causative sources (from large subduction to more local earthquakes generated in tectonically complex environments, from subaerial/submarine landslides to volcanic eruptions and atmospheric disturbances)
-Deterministic and probabilistic tsunami hazard, vulnerability, and risk assessments, including a multi-hazard perspective
-Forecasting tsunamis using emerging technologies, such as AI
-EWS, emphasizing innovative marine and seafloor observation methods, sensors and data processing techniques to improve the early characterization of tsunami sources and detection
-Societal and economic impacts of tsunami events on coastal communities
-Hazards perceptions, communication, engagement
-Present and future challenges related to global climate change (e.g. the impact of sea level rise)
The session aims to deepen understanding of tsunamis and improve the ability to build safer, more resilient communities. It welcomes contributions on observation data, real-time networks, modeling, risk assessments, and tools for effective warnings. Submissions on recent events, like the 2025 Kamchatka tsunami, are especially encouraged as they are expected to provide valuable insights for advancing research and improving preparedness strategies.
On 8 October 2023, enigmatic tsunamis with maximum wave heights of ~60 cm were observed in the Izu Islands and southwestern Japan, although only mb 4.3–5.4 seismic events were reported near Sofu Seamount in the Izu–Bonin arc in the USGS catalog. To investigate the source process, we analyze tsunami waveforms recorded by ocean-bottom pressure gauges of the DONET array off southwestern Japan. Stacked waveforms reveal recurrent arrivals of multiple wave trains. Deconvolution using a waveform segment of the tsunami from an early isolated event identifies at least 14 successive events that intermittently generated tsunamis over ~1.5 h. Their timings closely coincide with individual events of the seismic swarm and strong seawater acoustic waves (T waves) recorded by ocean-bottom seismometers, indicating a common source. Larger events later in the sequence occurred at intervals comparable to the tsunami period, amplifying later wave phases. Our tsunami waveform analyses summarized above, reported in Sandanbata et al. (2024, GRL), indicate a shallow, repetitive, and atypical non-tectonic tsunami source processes, consistent with volcanic activity. Subsequent independent studies have provided additional constraints supporting a volcanic origin. Recent bathymetric surveys revealed evidence of a submarine eruption near Sofu Seamount (Minami and Tani, 2024, Mar. Geol.). In addition, Kubota et al. (2024, GRL) constrained tsunami source locations to the vicinity of the seamount based on independent tsunami waveform analyses, while Takemura et al. (2024, JGR: Solid Earth) inferred shallow source depths using high-frequency seismic body and T waves. We propose that repetitive volcanic unrest, potentially involving submarine eruptions, caldera deformation, and/or flank collapses, generated the enigmatic tsunamis, although the exact mechanisms remain unresolved.
How to cite: Sandanbata, O., Satake, K., Takemura, S., Watada, S., Maeda, T., and Kubota, T.: Enigmatic tsunami waves due to repetitive volcanic processes near Sofu Seamount, Izu–Bonin Arc, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4476, https://doi.org/10.5194/egusphere-egu26-4476, 2026.
While consolidated methodologies exist for tsunami hazard quantification related to seismic sources, hazard studies for other tsunamigenic sources are rare and are usually based on the analysis of specific scenarios. In fact, the generation and propagation of tsunamis produced by submarine landslides are complex processes that require specific knowledge about potential sources and sophisticated modeling of both the source and the tsunami generation and propagation. Given the scarcity of direct data for most of submarine structures and the high computational cost of sophisticated models, there are no systematic studies capable of quantifying the tsunamigenic potential of non-seismic sources over an entire basin while accounting for the full source variability. However, such sources may be significant, and may be even dominating in areas at low seismicity, such as the Tyrrhenian Sea, a geologically complex region hosting numerous submerged volcanic edifices in the central Mediterranean. Here, an innovative approach is developed to identify the most relevant tsunamigenic sources in terms of their potential impact on the surrounding coasts. A simplified modeling approach for the tsunamigenic source is developed and coupled with a nonlinear model for the subsequent tsunami propagation (Tsunami-HySEA). This model is tested and calibrated using well-known sources at Marsili volcano, modeled with a more complex model (Landslide-HySEA), which allows for fully coupled modeling of the landslide and the water body. The simplified model can be homogeneously applied to all the existing potential sources in a large source areas in order to quantify their tsunamigenic potential in terms of the maximum at the coast. The results consist of non-trivial prioritization maps for each target area, allowing for the identification of the sources that deserve specific attention as they may potentially dominate the hazard at the target. Such prioritization maps may constitute a first fundamental step toward hazard quantification for such a type of source.
How to cite: Albano, G., Sánchez, C., Macías Sánchez, J., and Selva, J.: Assessment of the tsunamigenic potential of seamounts in the Tyrrhenian sea, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5054, https://doi.org/10.5194/egusphere-egu26-5054, 2026.
Tsunamis generated by subaerial landslides can cause severe damage along shorelines over large distances, making run-up assessment a critical component of landslide hazard and risk analysis. While site-specific numerical modelling provides detailed insight into wave generation and propagation, such approaches are often time-consuming and data-intensive. For preliminary hazard assessments, more general methods requiring limited input parameters are therefore needed. Empirical relationships offer a practical means to rapidly estimate tsunami impact and associated risk prior to undertaking detailed numerical modelling.
In this study, we evaluate the performance of the SPLASH empirical formula (Oppikofer et al., 2019) by applying it to several well-documented landslide-generated tsunami events in Greenland and Alaska. Modelled run-up estimates are compared with mapped run-up observations, and for one case, with results from numerical modelling. Our results indicate that the SPLASH empirical formula is a valuable and promising tool for first-stage hazard and risk assessment of unstable rock slopes located above water bodies. Finally, we discuss potential improvements to the formula to enhance its applicability and predictive capability.
Oppikofer, T., Hermanns, R.L., Roberts, N.J., Böhme, M., 2019. SPLASH: semi-empirical prediction of landslide-generated displacement wave run-up heights. Geol. Soc. Lond. Spec. Publ. 477, 353–366. https://doi.org/10.1144/SP477.1
How to cite: Fiolleau, S., Hermanns, R., Oppikofer, T., and Svennevig, K.: Assessing the SPLASH Empirical Formula for Run-Up Prediction of Subaerial Landslide-Generated Tsunamis, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5272, https://doi.org/10.5194/egusphere-egu26-5272, 2026.
Due to their rare nature, very large tsunami events are often only known from their sedimentary deposits. However, our lack of physical understanding on precisely how the sediments are deposited means we are currently unable to fully recreate a tsunami wave that created the deposit from the deposit alone. Moreover, local environmental and topographic controls on the deposit are often overlooked due to the paucity of available data. Here, we analyse a tsunami deposit from a unique site where high resolution spatial sampling of the deposit is possible, such that we can then compare these to a very high resolution (5 metre minimum resolution) numerical model of the tsunami. Our results demonstrate clear differences in the simulated conditions depending on both the model and topographic resolution used. Local topographic controls are shown to dictate sediment transport pathways and can explain sedimentary changes seen in the cored deposits; underscoring the need for careful consideration of both the paleao-geographic reconstructions and model resolution used. There is a clear positive relationship between deposit thickness and simulated maximum flow depth, but only when the model resolution is high. Our results show that our current understanding of tsunami depositional processes is inadequate. Reconstructing the wave is not possible using current inversion techniques which produce spurious results when compared to the forward numerical model. Ultimately, improving the ability to derive wave characteristics from sedimentary records remains critical for refining future tsunami risk assessments.
How to cite: Hill, J., Garrett, E., Simms, A., Benderz, H., Hazlett, H., Sykes, D., Shennan, I., and Andrews, L.: Sampling the Storegga tsunami: the impacts of sampling and model resolution on tsunami sediment interpretations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5769, https://doi.org/10.5194/egusphere-egu26-5769, 2026.
Numerical simulations of the 8150 BP Storegga slide event in the Norwegian Sea need to be consistent both with landslide runout and with observations of tsunami run-up. Here we focus on the southern North Sea, South East of Dogger Bank, and the shores of Denmark and Germany. The slide volume and dynamics need to generate a realistic initial tsunami wave and the simulation of the propagation and inundation of the tsunami would need the correct bathymetry of the North Sea 8150 years ago. From both Denmark and Germany there have been reports of deposits claimed to be associated with the Storegga tsunami. We simulate the slide using a recent cohesive landslide model, that has demonstrated success in predicting both the extent of runout deposits and tsunami run-up heights farther north, and we run suites of tsunami simulations to predict tsunami surface elevations, velocities, and arrival times. Appreciating the uncertainty associated with the paleobathymetry, we parametrize a continuum of bathymetric models between the present day topobathymetry and two different paleobathymetric models and perform simulations for multiple candidate bathymetric models. For many models in which Dogger Bank is completely submerged, the shallow water in this part of the North Sea still represents a significant barrier to the tsunami propagation. We compare tsunami metrics between the alternative topobathymetries systematically and conclude that the tsunami surface elevations and velocities in the southeastern North Sea are probably too small to have caused erosion and significant deposition of tsunami debris along the coasts of Denmark and Germany. All numerical simulation results performed for this study are openly archived on the Geo-INQUIRE Simulation Data Lake.
We acknowledge Geo-INQUIRE, funded by the European Commission under project number 101058518 within the HORIZON-INFRA-2021-SERV-01 call, DT-GEO, funded by Horizon Europe under Grant Agreement No 101058129, and ChEESE-2P, funded by the European Union and the European High Performance Computing Joint Undertaking (JU) together with Spain, Italy, Iceland, Germany, Norway, France, Finland, and Croatia under grant agreement No 101093038.
How to cite: Gibbons, S. J., Bondevik, S., Kurjanski, B., de la Asunción, M., Magni, V., Macías Sánchez, J., Emery, A. R., and Løvholt, F.: Propagation of the Storegga tsunami in the south eastern North Sea, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16703, https://doi.org/10.5194/egusphere-egu26-16703, 2026.
In this study, we present a physics-based framework for generating stochastic earthquake source models that jointly account for depth-dependent rigidity and stress-drop variability. This formulation extends previous approaches by explicitly linking the co-evolution of mechanical properties with depth to rupture geometry, slip concentration, and rupture duration, providing a consistent representation of subduction earthquake sources from shallow to deeper domains. The methodology is designed for ensemble-based Seismic Probabilistic Tsunami Hazard Assessment (S-PTHA) and ensures consistency between individual-event rupture characteristics, seismic moment release, and tsunami hazard estimates.
We systematically explore three depth-dependent rigidity–stress-drop models characterised by different rigidity gradients, spanning the range between a constant stress-drop end-member case, (Bilek & Lay, 1999) and the Preliminary Reference Earth Model (PREM). For a fixed seismic moment, rupture size and propagation velocity are calibrated to reproduce observed rupture durations, allowing stress-drop variability with depth to emerge naturally. Results show that steeper rigidity gradients lead to more spatially compact rupture areas with higher shallow slip amplitudes, whereas smoother gradients promote larger rupture extents and more distributed lower slip. These differences are most pronounced for shallow events and progressively diminish at greater depths, where mechanical properties converge, and rupture behaviour becomes less sensitive to parameter variability.
To reconcile stochastic shallow slip amplification with long-term tectonic convergence, we modified the balancing procedure, which was introduced by Scala et al., 2020, to a depth-based approach that enforces long-term slip consistency across the ensemble according to the depth-dependent contribution of individual ruptures. This approach removes the artificial overrepresentation of shallow events while preserving physically motivated shallow slip amplification at the single-event scale, enabling meaningful comparisons of hazard outcomes across models.
Applying this framework in the Mediterranean basin to the Calabrian, Hellenic, and Cyprus subduction zones using three-dimensional slab geometries, we perform S-PTHA calculations to offshore points of interest (POIs). We use as the hazard metric the maximum offshore wave height. Results for the regional models indicate a clear depth and distance-dependent control on tsunami hazard, with near-field hazard outcomes particularly sensitive to the joint treatment of depth-dependent rigidity and stress-drop variability. Indeed, steeper stress-drop gradients with depth significantly reduce slip amplitudes for large shallow events by promoting larger rupture areas, hence leading to lower probabilities of exceedance for a given tsunami height level. In contrast, far-field tsunami hazard is primarily governed by rigidity, as the effect of the extended-source features associated with stress drop variability diminishes with distance. Consequently, peak slip amplitude, mainly controlled by rigidity, emerges as the dominant factor for far-field hazard.
To further assess the implications of these depth-dependent source effects at the coastal scale, the same rupture ensembles are implemented within a high-resolution local PTHA framework for Catania and Siracusa, two test sites along eastern Sicily, for which we will provide preliminary results. This application enables a site-specific investigation of how alternative rigidity-stress-drop formulations translate into differences in nearshore wave amplification and inundation potential, providing a physically consistent basis for comparison with more conventional earthquake source representations.
How to cite: Vishnu, K. N., Scala, A., Lorito, S., Romano, F., Tonini, R., Volpe, M., Bayraktar, H. B., Kalligeris, N., Charalampakis, M., and Festa, G.: Depth-Dependent Rigidity and Stress Drop Control on Near- and Far-Field Tsunami Hazard from Mediterranean Subduction Earthquakes and Site-Specific PTHA, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13541, https://doi.org/10.5194/egusphere-egu26-13541, 2026.
We model the 2010 Mw 7.8 Mentawai tsunami earthquake using dynamic rupture simulations with heterogeneous, self-similar stress drop following a 1/k spatial spectrum. Rupture is confined to ~40 km of the deformation front based on high-rate GPS data, with stress and pore-pressure conditions defined by a three-dimensional critical wedge solution, a hypocentral depth of 10 km, and a constant fault dip of 4° from marine geophysical surveys. Random stress drop is implemented through dynamic friction, allowing natural incorporation of inelastic wedge deformation. With minimal tuning, elastic and inelastic models fit the GPS data comparably well, indicating that geodetic observations primarily constrain rupture extent. Inelastic wedge deformation produces >5 m of seafloor uplift despite reduced shallow slip—over three times that of elastic models—and is amplified by shallow slip strengthening via increased fault shear stress. This mechanism explains the disproportionate tsunami generated by the Mentawai earthquake, is consistent with pop-up structures observed in marine reflection data, and highlights the importance of including wedge inelasticity in probabilistic seismic and tsunami hazard assessments in global accretionary margins.
How to cite: Ma, S. and Hung, R.-J.: Dynamic Rupture Modeling of the 2010 Mw 7.8 Mentawai Tsunami Earthquake with Self-Similar Stress Drop and Wedge Inelasticity, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2122, https://doi.org/10.5194/egusphere-egu26-2122, 2026.
The Sea of Marmara represents one of the most critical seismotectonic regions worldwide, as it hosts the offshore segments of the North Anatolian Fault Zone (NAFZ), a major right-lateral strike-slip fault system [1, 2]. This fault system has generated numerous destructive earthquakes and constitutes a major seismic hazard for Istanbul, a megacity with a population exceeding 16 million. Most recently, on 23rd April 2025, a Mw 6.3 earthquake ruptured a segment of the NAFZ beneath the Sea of Marmara, producing strong to severe ground shaking across many coastal settlements around the basin. According to the KOERI rapid response report, a potential for light structural damage has been identified, particularly in the districts of Silivri, Büyükçekmece, Beylikdüzü, Avcılar, and Küçükçekmece, corresponding to approximately 0.8 per thousand of Istanbul’s total building inventory. Being located underwater, the earthquake also generated a small tsunami that was observed in many tide gauges (TG) along the coasts of the Marmara Sea.
In this work, we present a thorough analysis of the available sea level data from the day of the event. To start, available TG signals from that day are analysed using modern Time-Frequency (TF) techniques, namely the Fast Iterative Filtering (FIF) [3] that produces a data-driven decomposition of a given signal and the IMFogram [4], to obtain their TF representation. From here, we are able to determine arrival times, amplitude and main periods of the tsunami.
After the TF analysis, we simulate the tsunami through numerical modelling with different fault models using the JAGURS [5] software. First, we consider the case of faults with homogeneous slip distribution that we obtained from available Centroid Moment Tensor (CMT) solutions using scaling laws. Then, we propose a distributed-slip fault model. Such model has been obtained with a grid search like method and is composed of two uniform slip patches: a long shallow section with slip of around 1 m and a deeper and more compact one with slip around 0.66 m. This composite reproduces experimental time series with minimal error and its scalar seismic moment agrees with solutions found in the published literature [6].
At last, the possible presence of a secondary tsunami source is discussed, in order to explain an anomalous signal observed in Armutlu. Arguments in favour of a possible submarine landslide are presented and discussed.
[1] Barka, A. A. (1992). Annales tectonicae (Vol. 6, pp. 164-195).
[2] Şengör, A. M. et al. (2005). Annu. Rev. Earth Planet. Sci., 33(1), 37-112.
[3] Cicone, A., & Zhou, H. (2021). Numerische Mathematik, 147(1), 1-28.
[4] Cicone, A., et al. (2024). Applied and Computational Harmonic Analysis, 71, 101634.
[5] Baba, T., et al. (2015). Pure and Applied Geophysics, 172(12), 3455-3472.
[6] Eken, T., et al. (2025). Journal of Seismology, 1-29.
How to cite: Angeli, C., Armigliato, A., Zanetti, M., Zaniboni, F., Cambaz, M. D., Turhan, F., Meral Özel, N., and Yalciner, A. C.: Tsunami Generation by the Moderate 23rd April 2025 Earthquake occurred in the Marmara Sea, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7949, https://doi.org/10.5194/egusphere-egu26-7949, 2026.
We have examined three prominent near-field tsunamis that devastatingly impacted the contiguous Pacific coasts of Mexico. The 1985 tsunami was generated by a major (Mw 8.0) earthquake off the Mexican state of Michoacán on September 19 that caused serious damage and killed more than 5000 people. Tsunami waves from this event were observed at numerous sites along the coast, including Lázaro Cardenas, Zihuatanejo, Acapulco, and Manzanillo. The normal-fault earthquake that occurred on 8 September 2017 in the Gulf of Tehuantepec (Chiapas, Mexico) was an even stronger event (Mw 8.2), resulting in tsunami waves that were measured by a large number of high-resolution tide gauges on the Pacific coasts of California, Mexico and Central America and by three open-ocean DART stations located in the offshore region. The third tsunami was produced by a thrust fault Mw 7.6 earthquake on 19 September 2022 within the coastal zone of Michoacán, Mexico, i.e., on the same date and almost at the same location as the 1985 event. This tsunami was recorded by six coastal tide gauges and by DART 43412. All three tsunamis have been thoroughly examined and numerically simulated. Both the observational data and the modelling results demonstrate that the “strength” of the tsunami waves was mostly determined by the distance from the source rather than by the specific resonant characteristics of the individual recording sites. Numerical modelling of the events closely reproduced the coastal and offshore tsunami records. Our modelling also reveals markedly different anisotropic features for the tsunami energy radiation patterns, whereby the low-frequency energy was mostly concentrated in trapped edge modes propagating along the shelf while higher frequency leaky waves radiated tsunami energy outward from the source with the main beam directed like a “searchlight” normally to the mainland coast. The “trapping coefficients” – a measure of the trapped mode contribution to the tsunami wave energy – were estimated theoretically for all events, with values ranging from 60 to 80.
How to cite: Rabinovich, A., Ivanova, A., Zaytsev, O., and Thomson, R.: The destructive September tsunamis of 1985, 2017 and 2022 on the Pacific coast of Mexico: Numerical modelling and wave directivity, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18526, https://doi.org/10.5194/egusphere-egu26-18526, 2026.
The effects of tsunami-induced damage on coastal communities commonly fall short in addressing two critical influencing parameters: the multi-scale temporal and spatial domain of the system. Local tsunamigenic earthquakes often cause a sequential impact of seismic and tsunami waves on coastal communities, whose arrivals are strongly influenced by generation, propagation and site-effects. Moreover, the characterization of effects on tsunami flows due to regional bathymetry and urban topology, along with multiphysics fluid-structure, remains a modeling challenge. Physical and numerical models require highly specialized and sophisticated resources, while data to calibrate and validate solutions are scarce or nonexistent.
By developing a synergistic framework that incorporates these multi-scale demands (natural hazards assessment) and infrastructural resistance (geometric and material nonlinear behavior), this research combines valuable and unique high-resolution reconnaissance data with modeling approaches to yield a deeper understanding of the failure mechanisms observed on the built environment during the 2024 Noto Peninsula event. This international collaboration, addressing tsunami pathways and structural vulnerabilities, aims at providing quantifiable insights into the effectiveness of risk reduction strategies.
How to cite: Reis, C., Omira, R., Asai, T., Koyama, T., Fukutani, Y., and Omura, H.: Multiscale Tsunami-Induced Effects on the Natural and Built Environments: The Reconnaissance and Modeling of the 2024 Noto Earthquake-Tsunami Sequence in Japan Coastal Infrastructure, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21642, https://doi.org/10.5194/egusphere-egu26-21642, 2026.
The Mw 8.8 earthquake near the Kamchatka Islands triggered a Pacific-wide tsunami alert, leading to the activation of regional and national tsunami warning systems and emergency response procedures, including in French Polynesia and its 118 islands with three different warning levels. This event offers a unique opportunity to evaluate tsunami warning performance, observational capabilities, and hazard assessment strategies for Pacific Island environments.
This contribution presents a feedback from the tsunami alert and warning process during the Kamchatka event, with a focus on the early detection, source characterization, alert issuance timeline, and consistency between forecasted tsunami parameters and observed signals available in realtime and post-event observations.
These tsunami observations from coastal tide gauges, deep-ocean pressure sensors, and post-event field surveys conducted in French Polynesia are analyzed to document wave properties, arrival times, and local amplification effects but also evaluate model performance, particularly regarding the persistence of hazardous sea-level oscillations and the estimation of the end of warning.
Special emphasis is placed on the presentation of this new forecasting tool used for the first time in the warning context with its capability to forecast the estimation of the end of warning. The tools are developed by the Centre Polynésien de Prévention des Tsunamis (CPPT), the French Polynesian Tsunami Warning Center, which has been operational for more than 60 years. This methodology is based on an early robust source characterization that allow to perform a global numerical modeling to evaluate the potential tsunami impact for more than 24 hours after the first arrival time in complex island and atoll environments.
The study also identified gaps and objectives that still remains about early tsunami source evaluation and also the need to rebuild and update the tsunami hazard assessments for Pacific Island territories using a global probabilistic approach, highlighting key challenges such as limited bathymetry knowledge, limited historical data, sparse instrumentation, and strong site-specific effects.
Lessons learned from the Kamchatka Mw 8.8 tsunami emphasize the importance of combining communities and operational warning feedback, field observations, and methodological innovation to enhance tsunami preparedness and resilience in the Pacific.
How to cite: Jamelot, A., Sarret, N., Oopa, N., Quema, S., and Hyvernaud, O.: The 2025 Kamchatka Tsunami Event: Warning Performance, Field Survey, and New Applied Methodologies for Pacific Islands., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8414, https://doi.org/10.5194/egusphere-egu26-8414, 2026.
On July 29, 2025, a great mega-thrust earthquake of magnitude Mw 8.8 occurred near the Kamchatka Peninsula, Russia, generating a local tsunami comparable to that of its larger 1952 (Mw 9.0) predecessor. In contrast, the 1952 event caused a larger tsunami on the far-field Pacific shorelines. In addition, the 2025 tsunami was also smaller than anticipated by the life-saving tsunami warning issued for the far-field Pacific shorelines (e.g., Japan, Hawaii, South America). Here, we investigate the tsunami source of the 2025 event by jointly inverting the SWOT (Surface Water and Ocean Topography) and DART tsunami data with the static coseismic deformation measured by InSAR and GNSS. The tsunami Green’s functions are computed by considering the Kurils-Japan subduction interface parameterised by means of triangular subfaults, and the JAGURS code that solves the nonlinear shallow water equations with Boussinesq terms and also takes into account seawater density stratification, elastic loading, and gravitational potential change. Geodetic Green’s functions, as well as the tsunami initial conditions, are computed through the analytical formulation proposed by Nikkhoo and Walter (2015) for triangular dislocations considering also the contribution of the horizontal displacement. The slip model obtained after the inversion using the Simulated Annealing algorithm, highlights a southwestern unilateral rupture whose pattern partially overlaps the 1952 source zone consistently with the stress that had enough time to build up again since 1952. We show that the smaller earthquake magnitude (Mw 8.8 vs 9.0) and the overall relatively deep slip generated smaller tsunami potential energy, thus explaining the moderate far-field impact. Conversely, some shallow tsunamigenic displacement, reaching the trench, explains the enhanced local run-up comparable to the 1952 run-up, despite the smaller 2025 earthquake magnitude. Finally, we show that our findings are supported by a comparison with tsunami sources and observations for the 2010 Mw 8.8 Maule (Chile), and the 2005 Mw 8.5 Nias (Indonesia) earthquakes.
How to cite: Lorito, S., Romano, F., Bayraktar, H. B., Kalligeris, N., Rodríguez Gálvez, J. F., Piccolo, A., Atzori, S., Piatanesi, A., Cascone, V., Volpe, M., Tonini, R., and Amati, G.: Limited impact of the July 29, 2025 Kamchatka tsunami explained by the complex seismic rupture, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20239, https://doi.org/10.5194/egusphere-egu26-20239, 2026.
The 2025 Mw 8.8 Kamchatka earthquake triggered a transoceanic tsunami across the Pacific Ocean, with noticeable wave heights and coastal oscillations observed as far away as Chile. To investigate the transoceanic propagation of this event, we compiled a comprehensive observational dataset consisting of 41 high-quality DART (Deep-Ocean Assessment and Reporting of Tsunamis) buoys and eight representative coastal tide gauges distributed along the Pacific margins. We first applied three fault slip models released by the USGS and employed the PSGRN-PSCMP framework to simulate the tsunami generation process in a multi-layered elastic crust. The JAGURS tsunami package was employed for propagation modelling. The simulated waveforms were systematically validated against closest DARTs to the epicentre to identify the fault model that best reproduces the recorded tsunami (Figure 1). Detailed waveform, spectral, and energy-distribution analyses of both deep-ocean and coastal records were conducted to characterise the tsunami source properties and its transoceanic propagation patterns. Our results reveal pronounced tsunami directivity in both energy radiation and dominant wave periods. Tsunami energy propagates significantly more strongly along the fault-width direction than along the fault-length direction. Moreover, wave propagation parallel to the fault length is dominated by longer periods of 45–120 min, whereas energy components along the fault-width direction are concentrated at shorter periods of 8–45 min.
How to cite: Hu, G., Heidarzade, M., Mulia, I., and Watada, S.: Transoceanic propagation of the tsunami from 2025 Mw 8.8 Kamchatka Earthquake in the Pacific Ocean, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10908, https://doi.org/10.5194/egusphere-egu26-10908, 2026.
Sudden vertical deformation of the seafloor during an earthquake is the main cause of tsunamis. Besides the generation of long waves, the perturbation of the water column induces currents that carry information about the underlying deformation. While tsunami source inversions commonly rely on seismic, GNSS, tide gauges, deep-ocean pressure sensors among other sources of data, surface currents have only recently been proposed as a complementary and potentially noise-robust data source. Existing current-based inversions, however, typically rely on restrictive assumptions such as flat bathymetry, absence of background currents or waves.
We present a PDE-constrained optimal control framework for tsunami source inversion that estimates both the initial surface elevation and the vertical seafloor deformation from time series of surface velocity fields. The governing equations are the non-linear Shallow Water Equations with spatially variable bathymetry, Coriolis forcing and optional background flows, such as tidal or wind-driven currents. The inverse problem is formulated as a regularized optimization constrained by the PDE, and can incorporate spatially and temporally variable sensor coverage, measurement errors and noise through a flexible observation operator acting on a virtual sensor array. The methodology can accommodate joint inversions to combine surface current measurements with sea-level or seafloor observations, such as tide-gauges or ocean-bottom pressure sensors.
We test the method using synthetic deformation fields over a range of bathymetric configurations, from simple idealized profiles to realistic bathymetry, and for different sensor distributions, types and sampling intervals. Background currents and different uncertainty levels are included to assess the robustness of the source inversions. Finally, the Mw 8.8 Maule 2010 event is used as a benchmark to test the methodology under a realistic coseismic deformation pattern.
Our results show that, even with sparsely distributed surface current measurements, the method can recover the main features of the tsunami source and initial surface height distribution. Within the region covered by current measurements, the spatial resolution is approximately uniform in both along-strike and along-dip directions and is mainly affected by the sensor coverage density rather than other factors, such as bathymetry, showing that even sparse, non-uniformly distributed networks may be adequate for estimating the source of tsunami events, with near homogeneous resolution above the ruptured area. The addition of tide-gauge or pressure sensor records significantly improves the reconstruction of complex source geometries, particularly near the shoreline and when current measurements are sparse, spatially non-uniformly distributed or strongly clustered. The inversion is robust to measurement noise and it exhibits low sensitivity to bathymetric complexity. Time-varying and incomplete sensor networks, represented in our methodology tests by random and systematic sensor dropout, degrade only moderately the solution as long as sufficient sensor coverage is maintained. Resolution is mostly homogeneous, increasing with sensor density, faster sampling rates, and the inclusion of complementary sea-level or ocean-bottom data.
How to cite: Cifuentes-Lobos, R., Behrens, J., and Calisto, I.: A PDE-constrained optimization method for tsunami source inversion from surface current measurements, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13378, https://doi.org/10.5194/egusphere-egu26-13378, 2026.
Nowadays, Earthquake and Tsunami Early Warning Systems (ETEWSs) worldwide rely on ground-motion observations from strong-motion accelerometers and broadband seismometers. These measurements enable the rapid estimation of magnitude, hypocenter, and other source parameters, allowing the location and intensity of strong shaking to be determined. Although ETEWSs perform well in estimating the magnitude of small-to-moderate earthquakes, traditional inertial sensors generally struggle to capture the full dynamic range of ground displacements, particularly at low frequencies, i.e., below the relative corner frequency. This limitation becomes especially pronounced during large earthquakes (Mw > 7), which are dominated by near-field body forces generated at the source. Consequently, early warning algorithms face significant challenges in estimating source parameters in real time, particularly for these highly damaging, large-magnitude events that are potentially tsunamigenic provided seafloor deformation is involved.
To address this limitation, geodetic data - specifically GNSS displacements - have recently been incorporated into early warning algorithms and ground-motion models, serving as a critical complement to traditional seismic approaches. This study focuses on the use of high-rate Global Navigation Satellite System (GNSS) observations (>1 Hz), which provide high-fidelity recordings of ground displacement that are essential for rapid magnitude estimation.
We analyze some moderate-magnitude (Mw 5 - 6.5) seismic events in the Mediterranean region for which high-rate GNSS solutions are available. For each event with a known moment magnitude (Mw), an empirical scaling factor has been derived by fitting the observed displacement spectrum to the low-frequency plateau of the theoretical Brune source model. The primary objective of this research is to investigate the stability and potential variability of this scaling factor across the compiled event catalogue. Assessing the existence of a robust or “general” scaling factor is crucial, as its reliable determination could be directly applied to rapid magnitude estimation in the immediate aftermath of future moderate and large earthquakes, thereby significantly improving early warning system performance.
How to cite: Miele, P., Avallone, A., Herrero, A., Bernardi, F., Lorito, S., Piatanesi, A., Romano, F., Margheriti, L., and Vicari, A.: On the rapid magnitude estimation via empirical fitting of the Brune source model from high-rate GPS solutions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17784, https://doi.org/10.5194/egusphere-egu26-17784, 2026.
Prompt Elasto-Gravity Signals (PEGS) are light-speed gravity perturbations that can be recorded by broadband seismometers before the arrival of P waves. This characteristics has raised interest for potential early warning applications but the emerging nature of PEGS and their extremely small amplitudes (nm/s2) have challenged their operational use. We developed a deep learning approach to rapidly estimate the magnitude and location of large earthquakes from PEGS. In order to optimize the performances, we designed a graph neural network (PEGSGraph) capturing the geometrical information of the seismic network. This approach is not subject to saturation and can reliably estimate the magnitude of Mw ≥ 7.6 earthquakes within 2 minutes from initiation in Alaska, making it a viable solution for tsunami warning. We are currently testing possible implementations of PEGSGraph into the tsunami early warning systems of Peru and Alaska and including GNSS version in the deep learning framework.
How to cite: Bletery, Q., Hourcade, C., Juhel, K., Arias, G., Jarrin, P., Licciardi, A., Ampuero, J.-P., Vallée, M., and Inza, A.: The potential of prompt elasto-gravity signals and graph neural networks for tsunami early warning, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7385, https://doi.org/10.5194/egusphere-egu26-7385, 2026.
Digital Twin for Tsunami Disaster Resilience - Development of TsunamiCast:Real-time Impact-based Tsunami Forecast Facility
Digital twin is generally defined as a digital representation of physical objects in the real world, stored in cyberspace and used to simulate processes and consequences of target phenomena. Recognizing the importance of this concept, we propose Tsunami Digital Twin (TDT) as a new paradigm in tsunami science and engineering aimed at enhancing tsunami disaster resilience. We report recent progress in TDT applications and practical implementations.
Current TDT developments in Japan focus on multi-platform computing capabilities to extend tsunami forecasting technologies to other countries. As part of this effort, we have launched a new project, “TsunamiCast,” which aims to construct both fully cloud-based and on-premises end-to-end tsunami inundation forecasting facility for at-risk coastal communities. The standard TsunamiCast infrastructure integrates two kinds of urgent computing platforms of cloud computing system and on-premises servers having GPU computing capabilities.
The facility first ingests earthquake source information to determine a potential tsunami source model. This process consists of four levels: L1) estimation of earthquake magnitude and hypocenter; L2) centroid moment tensor (CMT) solutions; L3) GNSS-based solutions; and L4) a hybrid procedure that integrates L3 solutions with offshore data assimilation, which is currently under testing. Based on the derived tsunami source, the system performs tsunami propagation and inundation simulations on multiple high-performance computing platforms. These simulations generate time series of tsunami at offshore and coastal tide gauges, and critical points on the land to estimate tsunami travel and arrival times, inundation extents, and maximum flow depth distributions.
The tsunami modeling is conducted using the TUNAMI-N2 model of Tohoku University, which solves the nonlinear shallow-water equations using a finite-difference scheme. Based on the resulting maximum flow depth distributions, the facility conducts GIS-based analyses to estimate exposed populations and assess structural damage by applying tsunami fragility curves. The results are disseminated as map-based products to responders and stakeholders, including national government and regional municipalities, to support emergency response and tsunami disaster management activities. In the other words, TsunamiCast is designed to support two major United Nations global initiatives: Early Warnings for All (EW4ALL) and Tsunami Ready.
How to cite: Koshimura, S., Tanioka, Y., Mas, E., Musa, A., Morimatsu, N., Abe, T., Sato, Y., Suzuki, T., Yoshino, J., Ohta, Y., Kataya, S., and Kuwahara, N.: Digital Twin for Tsunami Disaster Resilience - Development of TsunamiCast : Real-time Impact-based Tsunami Forecast Facility, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22158, https://doi.org/10.5194/egusphere-egu26-22158, 2026.
Tools for tsunami impact analysis like USGS’s PAGER near-real-time impact assessments for earthquakes has been lacking within operational tsunami post-event assessments. Here, we introduce a new global model designed to estimate population exposure to tsunamis within minutes to hours after an event, supporting rapid post-event assessment developed within the ARISTOTLE-ENHSP. In a nutshell, the model combines model combines Tsunami-HySEA scenario simulations with Maximum Inundation Heights (MIHs) obtained by means of amplification factors and look up tables for population exposure. The method of amplification factors applies key wave parameters from Tsunami-HySEA, including offshore wave amplitude, period, and polarity, extracted through a dedicated time series analysis tool. To estimate inundated areas and human exposure, MIHs are extrapolated across a global digital elevation model (DEM) using a simplified bathtub-like friction-loss law. Pre-calculated inundation polygons, generated in discrete steps, enable rapid determination of affected regions. By overlaying these polygons with publicly available population datasets from the Global Human Settlement Layer (GHSL), the model produces exposure estimates within minutes to hours of an event. The approach prioritizes speed and global applicability over local precision; indeed, it does not incorporate high-resolution topography or detailed hydrodynamic simulations, and results carry significant uncertainty. However, this uncertainty is quantified based on the variability in inundation estimates and on bias offsets of the amplification factor approximation. A key focus of this presentation is to show selected comparisons with historical tsunami events, both towards inundation and exposure estimates. We finally discuss its intended role as a new supplement for providing rapid, approximate exposure estimates to inform post-event emergency response.
How to cite: Løvholt, F., Glimsdal, S., Harbitz, C. B., Sverdrup-Thygeson, K., Norderhaug Drøsdal, I., Romano, F., and Gonzalez Vida, J. M.: A new global tsunami exposure model for rapid post event assessment, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9049, https://doi.org/10.5194/egusphere-egu26-9049, 2026.
The GeTEWS Oceania Initiative is an international effort under the IUGG Commission on Geophysical Risk and Sustainability. It aims to strengthen tsunami monitoring and early warning capabilities across the Pacific region through the deployment and integration of real-time GNSS observation networks.
Oceania occupies a unique and highly vulnerable position, being both a source and a recipient of tsunamis generated by the intense tectonic and volcanic activity of the Pacific Ring of Fire. Recent events, including the 2022 Tonga eruption and tsunamis, have highlighted critical gaps in existing tsunami early warning systems, particularly for non-seismic and complex multi-source tsunamis.
Continuous GNSS observations can provide real-time estimates of crustal deformation, and atmospheric variability, offering a powerful complement to existing tsunami early warning systems. Despite this potential, GNSS infrastructure across Oceania remains sparse compared to other tsunami-prone regions.
The GeTEWS Oceania Initiative addresses this gap by promoting the development of a sustainable, regionally coordinated network of continuously operating GNSS stations and real-time analysis centers, designed to support tsunami early warning and disaster risk reduction. The initiative builds on two decades of progress in tsunami science and early warning, as synthesized during the GeTEWS 2017 Workshop, and incorporating lessons learned from recent major events and aligning with international priorities for multi-hazard monitoring.
The initiative has entered its implementation phase through two complementary pilot projects. The Tonga GNSS Network Pilot Project, led by the Ministry of Lands and Natural Resources of the Kingdom of Tonga in collaboration with Central Washington University and IUGG, has deployed four GNSS stations (with further expansion planned) and established real-time data streaming to analysis centers. A second pilot project focuses on federating existing GNSS infrastructures across Oceania into a “Network of Networks,” enabling data sharing among regional and global systems and revitalizing underutilized or dormant networks, such as those in Vanuatu.
By fostering multinational collaboration, shared data infrastructures, sustainable GNSS maintenance, reliable broadband connectivity, and integrated regional computational and analysis capabilities, the GeTEWS Oceania Initiative aims to enhance tsunami detection and monitoring, improve early warning performance for both seismic and non-seismic tsunamis, and strengthen long-term resilience to tsunami hazards across Pacific coastal communities.
How to cite: Ravanelli, M., LaBrecque, J., Melbourne, T., Craddock, A. B., D'Anastasio, E., Folau, V., Fry, B., Lal, A., Martire, C., Massenet, J., Miyahara, B., Moseley, A., Paea, A., Perrine, D., Perosanz, F., Riddel, A., Rolland, L., Ruddick, R., Sacotte, A., and Song, Y. T.: The GNSS enhanced Tsunami Early Warning System (GeTEWS) Oceania Initiative, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10392, https://doi.org/10.5194/egusphere-egu26-10392, 2026.
A tsunami is one of the most powerful and destructive natural hazards. Tsunamis occur in a result of a sudden and large displacement of the ocean that, in turn, are mostly caused by large submarine earthquakes.
Tsunami hazard risks are assessed based on the following set of parameters: 1) seismic source dimensions and the amplitude of the co-seismic crustal uplift to infer the tsunamigenic potential of an earthquake; 2) the wave heights and the speed of a tsunami propagating in the open ocean. However, despite recent developments, the near-real-time (NRT) monitoring and forecasting of both local (<800 km from the source, arrival in less than 1 hour) and distant (>800 km from the source, and trans-ocean propagation) tsunamis remain very challenging. As of today, even the most advanced seismo-geodetic methods still fail to estimate the tsunamigenic potential for large (Mw>8) earthquakes.
In response to these fundamental challenges, since 2022, we have been developing a GNSS-observation-based European system for earthquake and tsunami risk assessment “GO-EUREKA”. GO-EUREKA will use quasi-continuous observations of GNSS-based ionospheric total electron content (TEC) from ground-based and ship-based dual-frequency GNSS-receivers in order to assess earthquake and tsunami related hazards. The data will be collected and pre-processed by the module ALTRUIST (PI-M. Ravanelli). Further, the following steps will be performed for the NRT assessment of tsunami hazards: 1) automatic detection of co-seismic and co-tsunamic ionospheric disturbances (CSID and CTID, respectively); 2) confirmation of the origin of the detected disturbances; 3) inversion for earthquake magnitude and co-seismic crustal uplift from CSID (for the near-field); 4) inversion of tsunami wave heights and the propagation speed based on analysis of features of CTID (for the far-field).
This contribution will present recent developments in the field of NRT tsunami hazard assessment from the ionospheric observations, including the NRT detection of CSID/CTID, NRT estimation of propagation speed of CSID/CTID, confirmation of the link between the detected disturbances and earthquakes/tsunamis, by newly developed rapid simulation tools for CSID, and by NRT-compatible identification of the source of ionospheric disturbances.
How to cite: Astafyeva, E., Rolland, L., Ravanelli, M., Mikesell, T. D., Kherani, E. A., Brisssaud, Q., Maletckii, B., Sanchez Juarez, S., Ouar, I. D., Gibbons, S. J., Crespi, M., Munaibari, E., Maréchal, C., Saliby, C., Herrera, G., Adebayo, O. M., Honda, R. H., and Barad, R.: GO-EUREKA: GNSS-observation based European system for earthquake and tsunami risk assessment in near-real-time , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11775, https://doi.org/10.5194/egusphere-egu26-11775, 2026.
Tsunamis pose a major hazard to coastal communities, costing thousands of lives and destroying infrastructure across extensive coastal areas. Whilst the role of large floating debris in amplifying tsunami impacts is well recognised, the influence of finer sediment (sand, silt and clay) on the tsunami flow dynamics and hazard remains poorly understood. Current hazard assessments assume a turbulent, dilute tsunami flow with sediment concentrations below 5%, yet predictive models cannot resolve the internal variability within the flow during inundation. Such variation is evident in other environmental flows, such as subaqueous gravity currents, where a denser component at the base or front of the flow develops over time, markedly altering the flow behaviour. To observe whether similar processes can occur during tsunamis, we analysed helicopter footage of the Tōhoku-oki 2011 tsunami in the Sendai Plain, Japan, focusing on the evolution of the flow front during inundation at two study sites situated 1 km and 1.9 km inland. Using georeferenced video frames and pre-tsunami satellite imagery, we quantified spatial-temporal variations in the flow front velocity over 20-second intervals. Flow front gradients were also estimated where the flow front was observed to overtop large polytunnels. Results revealed rapid temporal and abrupt spatial changes in velocity, with variations of up to 8 ms-1 across the 20-second periods at both sites. Such fluctuating velocities are indicative of the pulsed surging typical of high-concentration debris flows, contrasting with the more uniform velocities of turbulent flow fronts. Furthermore, the front developed a steep gradient (~25-59°), which can only be maintained in a cohesive, debris flow, being incompatible with a dilute flow that is typically assumed. This state was observed to develop from an initially dilute, turbulent flow in the nearshore that progressively transitioned to a darker, more viscous and debris-laden state further inland. Sedimentary evidence revealed a transition from sand-dominated deposits in the nearshore to mud-rich deposits in the mid- and far-shore, with sustained erosion for at least 2 km inland. The evidence shows that continuous erosion and entrainment of mud-rich substrates (rice paddies, canals) markedly increased the cohesivity of the flow front into a debritic head, which rapidly transformed from the initially dilute, turbulent state. Beyond ~2 km inland, as erosion ceased, the slowing debritic head was likely overtaken by a trailing, more fluidal flow, analogous to similar processes in subaqueous gravity currents. In the mid-shore region, the enhanced viscosity (1000-10000x higher) and density of a debritic head will alter the flow hydrodynamics and exert a greater force on infrastructure, cf. the dilute flow front previously assumed. Future numerical modelling will aim to quantify the change in hazard in similar coastlines. These findings challenge prevailing assumptions and highlight the need to incorporate debritic heads into tsunami hazard assessments on mud-rich coastlines, where the hazard will be enhanced.
How to cite: Sharrocks, P., Peakall, J., Hodgson, D., Barlow, N., McKay, J., and Naruse, H.: Debritic head formation during the Tōhoku-oki 2011 tsunami reveals enhanced risk, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9474, https://doi.org/10.5194/egusphere-egu26-9474, 2026.
Port infrastructure plays a critical role in the functioning of global and regional economies, acting as key nodes in the logistics and supply chains. However, despite their strategic importance, the threat posed by tsunamis continue to be largely overlooked in current port disaster risk planning and management frameworks. This oversight is particularly significant in coastal regions exposed to active tsunami sources, where high-impact and low-probability, events can have catastrophic consequences. Historical events shows that ports are highly vulnerable to tsunamis. For example, the 2011 Tohoku event in Japan affected over 300 commercial ports and almost 1,700 marina facilities, resulting in economic losses of around US$12 billion (Chua et al., 2021; World Bank, 2023). Nevertheless, port management in many cases continues to be based on reactive approaches and simplified hazard analyses that focus mainly on the extent of flooding, without systematically integrating exposure, structural vulnerability and functional impacts.
In this context, the aim of this study is to propose a tailored probabilistic methodological framework for assessing tsunami risk in port environments. This framework is intended to support decision-making and strengthen risk management and preparedness strategies. The methodology enables the consistent identification and quantification of physical damage and expected losses to key port assets and elements of the logistics chain, within ship-to-shore transfers and storage areas. The approach goes beyond conventional hazard analyses, integrating the following: (i) probabilistic numerical modelling of seismotectonic tsunami generation, propagation and flooding (Seismic Probabilistic Tsunami Hazard Assessment - SPTHA); (ii) assessment of the static and dynamic exposure of typical port assets superstructure; (iii) characterization of vulnerability through the fragility functions of port logistics chain assets, and (iv) assessment of damage associated with loss of functionality, economic losses, and human casualties.
The framework's applicability is validated through a study in the Cádiz Port, Spain, which highlights its potential as an operational tool for port disaster managers. Likewise, the work highlights the transfer of knowledge between the scientific community and the port industry, promoting effective collaboration that allows the incorporation of tsunami threats into comprehensive risk planning and management in port facilities. The results will support Spain’s Port Authority, as well as emergency and response systems at the national, regional, and local levels. Internationally, the developed methodology will serve as a practical approach for assessing tsunami risk in ports exposed to this hazard, while also guiding response protocols and evacuation plans. Given its transferability to other regions, it may also serve as an additional instrument for Tsunami Warning and Mitigation Systems worlwide.
How to cite: Padilla Álvarez, S., Aguirre-Ayerbe, I., González, M., Aniel-Quiroga, Í., Galán Perez, D., and Garrido López, A.: Site-specific tsunami risk assessment at Port of Cádiz, Spain, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19842, https://doi.org/10.5194/egusphere-egu26-19842, 2026.
The Algerian coastline, located in a seismically active region of the western Mediterranean, remains vulnerable to understudied but potentially catastrophic tsunami hazards. The 2003 Mw 6.8 Boumerdès earthquake and its associated locally generated tsunami highlighted both the region’s complex tectonic setting and the lack of effective tsunami early-warning capabilities. This preliminary study investigates the potential of integrated geodetic observations to enhance tsunami hazard assessment and early-warning strategies along the Algerian margin. Continuous GNSS data from permanent Algerian and IGS stations are used to detect co-seismic and interseismic vertical and horizontal crustal displacements relevant to tsunami generation. In parallel, Sentinel-1 and ALOS-2 InSAR measurements resolve onshore deformation, coastal subsidence, and potential submarine slope instabilities. Satellite altimetry data from Jason and SARAL missions are analyzed to identify anomalous sea-surface height signals possibly associated with offshore seismic or tectonic processes. These multi-sensor datasets are integrated within a unified geodetic modeling framework and combined with tide-gauge records and numerical tsunami simulations using the Tsunami-HySEA model. Preliminary findings highlight the critical role of geodetic data in early-warning systems and risk mapping, particularly for densely populated coastal cities (Algiers, Oran). This interdisciplinary approach bridges geodesy, seismology, and coastal management, proposing a framework for proactive disaster resilience in North Africa.
Keywords: Tsunami hazard assessment, Algerian Mediterranean coast, GNSS geodetic monitoring, InSAR, Crustal deformation, Early Warning Systems.
How to cite: Tachema, A.: Tsunami hazard assessment along the Algerian Coast: A preliminary geodetic mapping approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2559, https://doi.org/10.5194/egusphere-egu26-2559, 2026.
The Atlantic coast of Morocco is exposed to potentially damaging tsunami events generated by offshore seismic sources. Although several studies have investigated tsunami hazard along the Moroccan coastline, most have relied on deterministic approaches and remain limited in their ability to quantify uncertainty.In this study, we perform a Probabilistic Tsunami Hazard Assessment (PTHA) for the Rabat–Salé coastal region based on thousands of high-resolution tsunami simulations. The methodology follows a three-step workflow: (1) hazard disaggregation and scenario selection, (2) high-resolution tsunami modeling using the Tsunami-HySEA model, and (3) hazard aggregation. High-resolution topo-bathymetric datasets provided by the Moroccan Ministry of Equipment and Water are incorporated to ensure accurate simulation of wave propagation and inundation processes. The results include local hazard curves and probabilistic inundation maps that provide quantitative estimates of tsunami hazard for risk-informed coastal planning and decision-making. This work represents one of the first local-scale PTHA implementations along the Moroccan Atlantic coast and demonstrates the added value of combining advanced numerical modeling with detailed national geospatial datasets for improved coastal risk management. This work was carried out under the Geo-INQUIRE project, funded by the European Commission under project number 101058518 within the HORIZON-INFRA-2021-SERV-01 call.
How to cite: Baouham, A., Gibbons, S., Volpe, M., Løvholt, F., Magni, V., Sánchez, C., Lanucara, P., Cherif, S.-E., and Sakami, S.: Probabilistic Tsunami Hazard Assessment for the Rabat-Salé Coastline ,Morocco., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7852, https://doi.org/10.5194/egusphere-egu26-7852, 2026.
Producing a probabilistic tsunami hazard assessment (PTHA) at an inundation level for a large-scale region is computationally demanding. The main reasons are the vast number of scenarios and the high spatial resolution in coastal areas required. Various methodologies have been proposed to overcome these challenges. However, they are limited to local scales or specific sites. In addition, the scarcity of high quality and accuracy of digital elevation model (DEM) that create this task is even more expensive. Here, we applied a two-stage framework to perform a large-scale inundation PTHA and utilised open sources DEM from BATNAS [1] and DeltaDTM [2]. As a pilot study area, we focused on the southern coast of Java Island, Indonesia, covering over 1,000 km length of coastal area. This region has high potential tsunami from the Java megathrust earthquake with high density population at several locations.
At the first stage, we focused on simulating offshore tsunami propagation in a low-resolution configuration model using the JAGURS code [3]. Further, tsunami elevation timeseries at 10 m isobath were extracted and used as boundary conditions for high-resolution inundation modelling at the second stage utilising the SFINCS code [4]. We generated a synthetic earthquake event catalogue by adopting a space-time Epidemic-Type Aftershock Sequence (ETAS) model [5] and coupled it with heterogenous earthquake slip models [6].
This is a proposed modular framework where we could strategically adjust the configuration as needed to suit a range of risk-based applications and the facilities availability. For example, users might apply other hydrodynamic software for the simulations, consider different tsunamigenic sources, and refine the Stage 2 results by incorporating a better quality of DEM without redo the whole processes. Finally, it enables us to progressively develop a national, regional, or even at a global level in parallel processes.
References: [1] BATNAS: https://tanahair.indonesia.go.id/portal-web/; [2] DeltaDTM: https://doi.org/10.4121/21997565; [3] JAGURS: https://github.com/jagurs-admin/jagurs/; [4] SFINCS: https://github.com/Deltares/SFINCS/tree/v2.1.1_Dollerup_release/; [5] Petrillo, G., & Zhuang, J. (2024). Bayesian earthquake forecasting approach based on the Epidemic Type Aftershock Sequence model. Earth, Planets and Space, 76(1), 78; [6] RPTHA to generate random slip models: https://github.com/GeoscienceAustralia/ptha
How to cite: Pranantyo, I. R., Petrillo, G., Salman, R., and Dal Zilio, L.: A two-stage framework for a large-scale probabilistic tsunami inundation hazard assessment: A study case for the southern coast of Java, Indonesia, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10971, https://doi.org/10.5194/egusphere-egu26-10971, 2026.
Tsunamis pose a significant and ongoing threat to communities along British Columbia's coast. The tsunami-generated waves and currents, combined with climate-change-driven sea level rise, can cause extensive damage to coastal infrastructure, threaten vessels, and, in severe cases, result in the loss of life. British Columbia is particularly vulnerable due to its proximity to the Cascadia and Alaska-Aleutian subduction zones. This methodology introduces a geospatial framework for generating tsunami hazard, inundation, and asset-at-risk maps to inform communities about potential tsunami impacts and guide emergency preparedness plans. The framework described in this methodology converts numerical tsunami simulations generated in FUNWAVE-TVD into a GIS-compatible format using Python-based processing that includes unit conversion, horizontal datum alignment, and the creation of gridded points. Regional-scale hazard maps are generated as continuous raster surfaces confined to overwater areas, with values interpolated from the gridded points using inverse distance weighting (IDW) to represent maximum wave amplitude (hmax) defined as wave height above a still-water surface and maximum wave current speed (umax) defined in knots.
Localized inundation mapping is achieved by integrating a 10m resolution tsunami model with a 1m resolution coastal digital elevation model that was developed from up-to-date high-resolution bathymetric and LiDAR data. Raster-based analysis defines inundation extents and derives water depth surfaces by intersecting the modelled wave heights, referenced to the Canadian Geodetic Vertical Datum of 2013 (CGVD2013) and adjusted for tidal and sea-level-rise variations, with ground elevation. This workflow enables the representation of coastal inundation and supports consistent hazard classification across multiple tsunami scenarios. The final stage of the framework involves deriving asset-at-risk products that identify building structures and road networks that are potentially susceptible to damage or compromise from tsunami-induced flooding. Asset exposure is classified using a hazard index based on inundation depth and wave velocity, and is visualized on a graduated scale from low to high risk.
These methods developed for the British Columbia coast provide a reproducible, transferable workflow for integrating numerical tsunami model results into multi-scale mapping products applicable to different tsunami models created from varying source types and influenced by differing coastal topography. These products inform coastal communities and stakeholders about potential tsunami risks and support evidence-based decision-making.
How to cite: Lee, C., Bosma, C., Samson, J., Rankin, M., Kouhi, S., Amouzgar, R., and St-Germain, P.: A Geospatial Framework for Mapping Tsunami Hazard, Inundation, and Exposure in Coastal British Columbia, Canada, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14059, https://doi.org/10.5194/egusphere-egu26-14059, 2026.
Tsunami hazard along subduction-zone coastlines is governed not only by earthquake source characteristics but also by frequency-dependent interactions between tsunami waves and local bathymetric and geomorphological features, which can lead to resonance and wave amplification in specific coastal settings. Such effects can significantly modulate tsunami impact and are therefore essential to consider in hazard assessments. In this study, we conduct a fully probabilistic tsunami hazard assessment (PTHA) to quantify tsunami inundation along the Chilean coast using physics-based numerical simulations. The analysis incorporates seismic scenarios spanning a broad moment magnitude range (Mw 7.5–9.5) and applies multiple sampling strategies to evaluate the sensitivity of hazard estimates to the number of simulated events. The assessment is performed at a nationwide scale while considering tsunami inundation at several cities of interest, allowing comparing the effect of tsunami resonance across varying bays, embayments, and continental shelf structures. More than 40,000 stochastic earthquake–tsunami scenarios are simulated to characterize spatial variability in inundation metrics, including maximum flow depth, inundation extent, and temporal wave amplification, allowing to address uncertainties in both seismic sources and local amplification, as well as to test the convergence of typical PTHA statistics. These are compared with existing scenario-reduction strategies to assess their applicability and capability to preserve the statistical properties of the full catalogue. By linking PTHA with scenario reduction, it becomes feasible to both quantify hazard and explore effective risk-reduction strategies. These findings demonstrate that tsunami hazard is strongly region-dependent and controlled by both source variability and local resonance effects, providing critical input for risk-informed coastal planning, tsunami mitigation, and emergency management strategies in Chile. This work has been supported under the Geo-INQUIRE project, funded by the European Commission under project number 101058518 within the HORIZON-INFRA-2021-SERV-01 call.
How to cite: Catalan, P. A., Zamora, N., Gibbons, S., Løvholt, F., Volpe, M., Lorito, S., and Macias Sanchez, J.: Nationwide Probabilistic Tsunami Hazard Assessment of Chile, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-23133, https://doi.org/10.5194/egusphere-egu26-23133, 2026.
Landslide-Tsurrogate v1.0 is an open-source Python and MATLAB framework designed to efficiently estimate tsunami hazards generated by submarine landslides. Rather than relying on thousands of computationally expensive deterministic simulations in real time, the tool constructs surrogate models that can rapidly reproduce tsunami responses at a fraction of the computational cost once an event occurs. The approach is based on generalized polynomial chaos expansion, which enables an efficient exploration of uncertainties in landslide parameters and their impact on tsunami generation.
The framework allows users to perform sensitivity analyses, identify the most influential parameters, and quantify the variability of tsunami outcomes in a probabilistic manner. To facilitate accessibility and transparency, Landslide-Tsurrogate v1.0 is distributed with a Jupyter Notebook User Manual and interactive MATLAB and Jupyter Notebook interfaces, enabling straightforward model configuration, surrogate construction, and result visualization.
The performance of the model is demonstrated through a real-world application to five submarine landslide-prone zones offshore Mayotte (France). In this case study, surrogate convergence is achieved with only 135 deterministic simulations per zone, and probabilistic tsunami hazard estimates are produced in less than 2 seconds on a standard laptop. These results highlight the strong computational efficiency of the approach.
Beyond this application, the framework is readily transferable to other coastal regions exposed to submarine landslide hazards. By combining physical modeling, statistical methods, and user-oriented design, Landslide-Tsurrogate v1.0 provides a fast, transparent, and practical tool for probabilistic tsunami hazard assessment.
How to cite: Denamiel, C., Marboeuf, A., Mangeney, A., Le Friant, A., Peruzzetto, M., Lucas, A., Castro Díaz, M. J., and Fernández-Nieto, E.: Towards digital-twin-enabled tsunami hazard assessment: Landslide-Tsurrogate v1.0, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4898, https://doi.org/10.5194/egusphere-egu26-4898, 2026.
Landslide tsunami hazard analysis is characterized by substantial uncertainty, particularly in estimating exceedance probabilities for tsunami heights. As a result, no standardized hazard methodology exists for landslide tsunamis, and most studies rely on deterministic or scenario-based approaches, while Probabilistic Tsunami Hazard Analysis (PTHA) methods are seldom applied. The limited use of probabilistic frameworks is largely due to scarce observational data on past landslide tsunamis and the increased modelling complexity required to represent landslide sources, especially subaerial failures producing impact tsunamis.
To address these challenges, we apply a Landslide Probabilistic Tsunami Hazard Analysis (LPTHA) framework previously developed for Norwegian fjord environments, focusing here on the potentialÅkerneset and Hegguraksla rockslides in western Norway. The LPTHA combines landslide occurrence rates derived from slope stability assessments with an event-tree formulation describing uncertainty in key landslide kinematic parameters controlling tsunami generation, such as impact velocity, impact frontal area, and runout distance. Quantification of epistemic uncertainty requires large ensembles of simulations spanning wide parameter ranges, which necessitates computationally efficient modelling approaches.
In this study, tsunami generation is represented using a "rounded block” landslide source model, coupled with a linear dispersive wave propagation model and a non-linear shallow-water model for nearshore propagation and inundation. The resulting LPTHA provides probabilistic estimates of tsunami and run-up heights within the fjord system, explicitly accounting for uncertainty in landslide dynamics and tsunami response. The analysis highlights the sensitivity of hazard estimates to landslide source parameterization and demonstrates the applicability of LPTHA as a systematic framework for probabilistic tsunami hazard assessment in fjord settings affected by large unstable rock slopes. Finally, the methodology enables a presentation of run-up heights with corresponding probabilities as required by the Norwegian Planning and Building Act.
How to cite: Magni, V., Glimsdal, S., Storrøsten, E., Løvholt, F., and Harbitz, C.: A Landslide Probabilistic Tsunami Hazard Analysis for the Åkerneset and Hegguraksla rockslides (Norway) , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18105, https://doi.org/10.5194/egusphere-egu26-18105, 2026.
Digital twin is recognized as a digital copy of a physical world stored in a digital space and used to simulate the sequences and consequences of a target phenomenon. By incorporating observed data into the digital twin, a full view of the target is obtained through real-time feedback. In our tsunami disaster digital twin platform, the tsunami inundation is first forecasted in real-time using high-performance computing.
Our target area is the Nankai Trough subduction zone in Japan, where a great earthquake is expected to occur soon and cause a significant tsunami disaster along the coast. In this subduction zone, the dense observation systems, including pressure sensors connected by cables (DONET and N-net) were recently installed at the ocean bottom. Also, the dense GNSS observation network is available on land.
When a great Nankai earthquake occurs, the source model of the earthquake is quickly estimated from the GNSS data using the REGARD method (Kawamoto et al., 2017). Our digital twin platform can compute the tsunami inundation along the coast of Shikoku in Japan using a high-performance computer within 5 minutes after the earthquake. However, because the GNSS network is on land, the resolution of the slip amount along the plate interface near the Nankai trough is low.
Therefore, we developed a novel data assimilation method using dense ocean bottom pressure data to improve the forecasted tsunami wavefield originally estimated from GNSS data using the REDARD method. Then that tsunami wavefield was used to compute the tsunami inundation along the coast by a high-performance computer as an accurate tsunami forecast.
We tested our data assimilation method for one of the slip distributions of the great Nankai earthquake expected to occur. The reference tsunami wavefield and tsunami inundation were computed from that slip distribution. The pressure data at the actual sensors were calculated from the reference tsunami as inputs for our data assimilation. We also assumed a few preliminary fault models, which are supposed to be estimated from the GNSS data. Results show that the data assimilation method significantly improves the tsunami wavefield; therefore, the forecasted tsunami inundation along the coast is also significantly improved. Especially, the underestimation of the forecast inundation from the preliminary fault model was resolved by using our data assimilation method.
We conclude that our novel data assimilation method with a preliminary estimated fault model is effective for real-time tsunami inundation forecasting as a tsunami Digital-Twin.
How to cite: Tanioka, Y., Ratnasari, R., Atobe, Y., Suzuki, T., Koshimura, S., Musa, A., Morimatsu, N., Sato, Y., and Yoshino, J.: Digital Twin for tsunami disaster resilience, incorporating data Assimilation of ocean bottom pressure data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6310, https://doi.org/10.5194/egusphere-egu26-6310, 2026.
Tsunamis pose severe threats to the infrastructure and economies of coastal nations, particularly in Chile, where high seismic activity intersects with concentrated coastal populations and economic assets. Despite the rising risks, current risk assessment frameworks often overemphasize hazard metrics, such as occurrence probability and run-up height, while neglecting the comprehensive integration of economic vulnerability. Furthermore, existing research on adaptation strategies predominantly focuses on the local engineering design of seawalls, lacking systematic, regional-scale cost-benefit analyses (CBA). This limitation hinders the comprehensive evaluation of adaptation measures and restricts the scientific basis for disaster mitigation policymaking.
This study establishes a comprehensive probabilistic risk assessment framework that integrates vulnerability and economic exposure. By generating a stochastic earthquake event set and utilizing the COMCOT numerical simulation model, we constructed a risk model that accounts for multidimensional economic factors. Validation results demonstrate that incorporating vulnerability significantly mitigates the overestimation inherent in single-exposure assessments, aligning the results closer to historical observations and improving estimation accuracy by 150.13%.
The results exhibit significant spatial heterogeneity in risk distribution. Spatially, risk is concentrated in the central region, exceeding levels in the north and south. Notably, a divergence exists between relative and absolute risk hotspots within the central area: Coquimbo exhibits the highest relative impact (2.69% of regional GDP), whereas Valparaíso incurs the highest absolute risk, with an Annual Average Loss (AAL) of US$380 million. These findings establish the quantitative benefit baseline for the subsequent cost-benefit analysis.
Based on this framework, we evaluated the economic feasibility of regional seawall strategies under various scenarios of economic development and investment costs. The results indicate that future average benefits under the "Economic Development" scenario are approximately double those of the "Economic Stagnation" scenario, with benefit fluctuations ranging from 1.5 to 2.5 times. Under current economic conditions with low investment costs, seawall construction is feasible in eight regions; however, feasibility diminishes as investment costs rise. Notably, in an "Economic Stagnation" scenario combined with medium-to-high investment costs, no regions present economically feasible solutions. This research fills a critical gap in regional-scale economic evaluations of adaptation strategies, providing a robust decision-support tool for tsunami disaster risk reduction.
How to cite: Zou, Z. and Cheng, C.: Probabilistic Tsunami Risk Assessment and Cost-Benefit Analysis of Seawall Adaptation Strategies: A Case Study of Coastal Chile, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19751, https://doi.org/10.5194/egusphere-egu26-19751, 2026.
Qualitative analysis of synoptic conditions associated with extreme high-frequency sea level oscillations recorded at selected Mediterranean tide gauge stations is presented. Two types of extreme events are considered: (1) events in which high-frequency component is dominant component of the residual sea level height; and (2) events in which the contributions of both high-frequency and low-frequency component to residual signal are nearly equal. We show that, on average, events of type (1) are accompanied by westerly winds at 500 hPa height, north-to-south temperature gradient at 850 hPa, and weak gradients of mean sea level pressure field. Events of type (2) are, on average, characterized by south-westerly winds at 500 hPa height, inflow of warmer, southern air from Africa towards the affected regions, detectable at 850 hPa height, and more enhanced gradients of mean sea level pressure. Further sub-classification of both types of events, based on the wind direction at 500 hPa height is proposed. Three subtypes of events are considered for each of the two groups, events characterized by (a) north-westerly; , (b) south-westerly, and (c) westerly winds. For events of type (1) we find that subtype (a) is characterized by the advection of colder air of northern latitudes over affected areas at 850 hPa height and strong gradients in mean sea level pressure field, caused by high-pressure fields found to the west and low-pressure fields to the east from the affected areas. In contrast, for subtype (b) we observe the inflow of warmer, southern air towards the affected areas at 850 hPa height and mean sea level pressure lows at and around all affected locations. Subtype (c) is characterized by mostly homogenous mean sea level pressure fields, with typical north-to-south temperature gradients at 850 hPa. For events of type (2), we observe that all three subtypes of events qualitatively resemble the subtypes discussed in context of events of type (1). However, air pressure lows observed in mean sea level pressure field in case of type (2) events are noticeably deeper. These new findings are expected to contribute to overall understanding of synoptic conditions driving different types of sea level extremes, potentially leading to further development in forecasting of these events.
How to cite: Jukic, I., Balic, M., Ruic, K., and Sepic, J.: Qualitative assessment of synoptic patterns linked to different types of high-frequency sea level extremes in Mediterranean, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9798, https://doi.org/10.5194/egusphere-egu26-9798, 2026.
The conditions for the occurrence and development of the meteotsunami events of May 7, 2007, on the northern Bulgarian coast, June 27, 2014, near Odessa and in the port of Illichivsk (Sukhoi Liman), and July 19, 2017, in the waters of the Belosarayskaya Spit in the Sea of Azov were analysed. All events occurred under similar macroscale synoptic conditions over southeastern Europe: according to Rabinovich's classification, these were "good weather" meteotsunamis. Due to the fact that in the Sea of Azov and in the western part of the Black Sea there is a lack of a sufficient number of high-precision observation points for sea level and atmospheric pressure, determining the mechanism for generating sharp fluctuations in sea level causes certain difficulties. To identify visual observations of tsunami-like sea level fluctuations necessary and sufficient conditions have been determined, the fulfilment of which can give us confidence in determining the nature of the observed sea level fluctuations as generated by atmospheric processes – a meteotsunami event. The necessary conditions for the occurrence of a “good weather” meteotsunami in a coastal area should be considered the presence of a wide sea shelf. Such shelf areas in the Azov-Black Sea region exist in the Sea of Azov and only in the western Black Sea (the coasts of Bulgaria, Romania, and Ukraine). The topography of the Azov Sea bottom suggests that the velocity of a tsunami-generating atmospheric formation should not exceed 10 m/s. For the Belosaraysk meteotsunami, this conclusion is supported by satellite data on the movement of the corresponding convective cell. To determine the sufficient condition for the occurrence of a meteotsunami, one must consider the meteorological, or more precisely, the synoptic, aspect of the meteotsunami generation process. Rabinovich and Šepić called this synoptic situation for the mesoscale region under consideration a "tumultuous atmosphere." What this term implies is that the sufficient condition should not be considered to be a specific atmospheric gravitational disturbance, but rather the specific structure local atmosphere. A comparative analysis of synoptic charts on the specified dates the meteotsunami occurrence for the Azov-Black Sea region reveals a classic pattern of frontal interaction between the Lesser Asian Depression (with dry and very warm air of African origin) and the cold and moist (polar) air of the anticyclone over Eastern Europe. A good qualitative correspondence is noted between the structure of the pressure fields and the location of fronts and zones of convective cloud cover. Aerological data indicate an influx of warm and dry air into the lower troposphere, resulting in an inversion in the surface temperature field, as well as the presence of fairly strong wind speeds in unstable atmospheric layers.
How to cite: Matygin, A.: Meteotsunamis of the Black and Azov Seas, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9662, https://doi.org/10.5194/egusphere-egu26-9662, 2026.
Meteotsunamis are atmospherically-driven sea-level oscillations that can trigger hazardous coastal flooding, particularly in semi-enclosed and resonant harbors. Their accurate simulation and forecasting remain challenging because the ocean response depends critically on the intensity, propagation speed and spatio-temporal structure of mesoscale atmospheric pressure disturbances, which are often under-resolved even by state-of-the-art products.
This contribution evaluates Meteo-HySEA, a GPU-accelerated code designed for reproducing meteotsunami generation, propagation, coastal amplification and high-resolution inundation using a nested-grids approach. We benchmark Meteo-HySEA in the Adriatic Sea against the CPU-based AdriSC-ADCIRC modeling system for three well-documented events (June 2014, June–July 2017, May 2020), using WRF downscaling of ERA reanalyses and validation with high-frequency tide-gauge and microbarograph observations from the MESSI network complemented by additional coastal pressure records.
Results show that Meteo-HySEA generally reproduces the timing and spatial variability of simulated meteotsunami oscillations and often yields larger amplitudes than AdriSC-ADCIRC under identical forcing, while systematically overestimating dominant wave periods, especially in enclosed basins. For the 2017 and 2020 events, both modeling frameworks significantly underestimate observed amplitudes at key hotspots (e.g., Vela Luka and Stari Grad), consistent with deficiencies in the modeled atmospheric disturbances, highlighting atmospheric forcing as the dominant source of uncertainty. Controlled synthetic-pressure experiments further indicate systematic differences in energy trapping and damping within harbors, emphasizing sensitivity to nearshore resolution, dissipation/parameterizations, the treatment of wetting–drying fronts and inundation.
Crucially, GPU acceleration enables order-of-magnitude gains in computational efficiency, supporting rapid high-resolution simulations and making Meteo-HySEA a strong candidate for ensemble-based meteotsunami forecast, extending the modeling chain from offshore oscillations to onshore flooding. This functionality is particularly relevant for risk assessment and civil protection, as it allows the estimation of direct impacts on vulnerable harbors and urban waterfronts.
How to cite: Gonzalez del Pino, A., Lumina Denamiel, C., and Macías Sánchez, J.: Assessing Meteo-HySEA Performance for Adriatic Meteotsunami Events., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3740, https://doi.org/10.5194/egusphere-egu26-3740, 2026.
The tsunamis resulting from the earthquakes of 2004 (Sumatra), 2010 (Chile), 2011 (Tohoku), or 2015 (Chile) caused more than 250,000 deaths and damage to both the built and natural environments, some of which is irreparable. However, they also triggered a global awareness of the combined earthquake-tsunami risks. Awareness must be accompanied by actions that foster preparedness and response capacity — a principle enshrined in the Sendai Framework. In this context, structures for public warnings have been created in Lisbon. Specific programmes to promote resilience have been launched, and the revision of the Municipal Master Plan (PDM) provided the framework for generating tsunami inundation maps. This work presents the principles and methods leading to the calculation of the extent of tsunami-inundated areas following an earthquake with the same magnitude as that of 1755, describes risk awareness and risk communication measures undertaken, including risk perception initiatives and presents simulations of evacuation scenarios for Lisbon’s waterfront, taking in consideration the inundation time line, building-related vulnerability and the proposed evacuation meeting points.
Vulnerability associated to risk perception can be reduced by increasing the quality of information on tsunami propagation, evacuation routes, and safe meeting points. The perception of Lisbon’s population regarding tsunami risk, self-protection behaviours, and knowledge of exposed and safe zones is shown to be ambiguous – good knowledge about the phenomenon does not translate into adequate self-protection response. The simulation platform for the evacuation of Lisbon's waterfront areas, based on social forcing concepts, was specifically employed to provide data to discuss the impact of information previously received by the population on evacuation quantifiers, including the inundation timeline and maximum extent, and the most adequate routes. The evacuation simulations allowed to understand to what extent information and awareness-raising actions contribute to increased risk perception and self-protection behaviours and the increase of survival rates.
Acknowledgement: This works was supported by the Portuguese Foundation for Science and Technology (FCT) through research centre CERIS UIDB/04625/2020
How to cite: L Ferreira, R. M., Guarda, C., Lopes, M., Amaral Ferreira, M., Pousada, C., Pinto, C., Milho, R., Queiroz, S., and Castro Martins, M.: Tsunami risk perception and evacuation strategy. A case study in lisbon., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22066, https://doi.org/10.5194/egusphere-egu26-22066, 2026.
The 2004 tsunami left the world with a wealth of examples of possible responses to an unprecedented disaster. Related to this, disaster research has encouraged more learning from the activities of local NGOs that have not been adequately represented in the literature. Further, researchers have put forth a strong call to integrate psychosocial interventions with disaster response and recovery activities to curb hazard-induced psychological morbidities. In this work, we address each of these issues through a case study that examines the comprehensive, culturally specific responses of one NGO after the 2004 tsunami. The LNGO incorporates both development and psychosocial frameworks as well as the nuances beyond both, in a small but intensely tsunami-impacted location in southern India. These nuances, in particular, indicate beyond the “what” was done and may inform the less studied aspects of the “how” of effective psychosocial and development disaster responses. To gain insight into the contextual realities and finer details of the LNGO's disaster response and management, multiple data collection methods were used. We conclude that LNGO's local knowledge of the cultures of the affected communities contributes to specific, nuanced interventions that can greatly support effective disaster responses and potentially mitigate psychological morbidity. Based on these findings, we introduce the Sustainable Psychosocial Development Approach (SPDA) for Disaster Response.
The incident served as a catalyst for a revolutionary shift in disaster management, moving from a rigid "command and control" structure to a dynamic, community-centric model. As highlighted in the practitioner’s guide, Community Resilience (CR) is not merely the ability to survive a hazard, but the capacity to "vuild back better", transforming and growing stronger in the aftermath. By focusing on the interplay between natural hazards, community vulnerability, and individual exposure, practitioners can move beyond simple relief toward a state of enhanced absorption and adaptation capacity.
To achieve true stability, interventions must address five critical dimensions simultaneously: social, economic, institutional, infrastructural, and community resilience. Strengthening social capital involves rebuilding trust and connectedness, while economic resilience is bolstered through livelihood diversification, such as teaching new skills like plumbing or driving. Institutional resilience is built through long-term programs like the Tsunami Ready Program, while infrastructural resilience is solidified through physical assets like the Amrita Setu bridge, which provides vital redundancy for evacuation and market access.
While traditional Disaster Management Cycles (DMC) often treat Mitigation as a separate, final stage, the unique approach exemplified in Alappad demonstrates that mitigation must be interwoven into every phase. In the response phase, immediate actions, such as turning off electrical transformers to prevent electrocution, serve as early mitigation. In the recovery phase, building tsunami-resistant houses with pile foundations and rooftop access ensures the community is structurally prepared for future events. This "build back better" philosophy ensures that the community does not just return to its pre-disaster state but evolves into a more robust entity.
Keywords: Disaster Risk Reduction (DRR), Coastal Resilience, Community Recovery, 2004 Indian Ocean Tsunami, Multi-hazard Assessment
How to cite: Rao, B. R., Ekkirala, H. C., and Ramesh, M. V.: Ruin to Resilience: Integrating psychosocial interventions for the 2004 Indian Ocean Tsunami, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22056, https://doi.org/10.5194/egusphere-egu26-22056, 2026.
Tsunamis generated by impulsive sources such as submarine landslides and earthquakes commonly exhibit N-wave structures, including Leading Depression (LDN), Leading Elevation (LEN), and symmetric/isosceles forms. As these waves propagate offshore, their evolution may endure nonlinear effects, which can produce trailing dispersive tails. During propagation across variable bathymetry, these long waves may remain well described by non-dispersive shallow-water equations (SWE), or they may undergo dispersive spreading that reshapes the leading wave packet before coastal impact. Identifying the onset of dispersion for realistic N-wave families is therefore critical for near-field warning, where lead times are short and offshore transformation strongly conditions shoreline amplification and inundation.
We develop a controlled workflow to predict the onset of dispersion for tsunami-like N-waves using a Korteweg–de Vries (KdV) solver as the propagation model. Approximately two-hundred tsunami-like N-wave cases are initialized following Tadepalli and Synolakis’ idealized leading-wave model. These initial conditions span wave type, amplitude, and crest–trough separation. Dispersion onset (tdisp) is labeled by a physically grounded criterion: dispersion begins when the tallest trailing ripple exceeds 5% of the initial leading-crest amplitude. For each simulation we extract dimensional and dimensionless descriptors, including an effective wavelength, dispersive strength, and nonlinearity.
We then train an interpretable, two-stage machine-learning framework using XGBoost: (i) a classifier for whether dispersion is detected within the simulation horizon, and (ii) a regressor predicting tdisp for detected cases. The resulting surrogate enables accelerated prediction by eliminating the need for full numerical simulation when estimating dispersion onset time, supporting rapid estimates that can be integrated into real-time forecasting workflows. It also provides parameter sensitivity, revealing which wave characteristics (e.g., steepness, amplitude, and length-scale measures) most strongly control dispersion timing and thereby improving physical understanding of N-wave evolution. Once trained, the framework offers generalizability to unseen wave configurations, supporting analysis and hazard assessment. Finally, we include analytical benchmarking by comparing ML-predicted onset behavior against both the simulation outputs and analytical dispersion scaling (e.g., Glimsdal et al., 2013), testing robustness across the full parameter space and strengthening confidence in the resulting dimensionless dispersion-onset screening parameter. This parameter enables faster and more defensible model-selection triage in early warning (SWE vs. dispersive (e.g., Boussinesq)), more targeted inclusion of dispersive physics in hazard-map scenario libraries, and clearer communication of “dispersion-sensitive” conditions for coastal communities and critical infrastructure planning, including future-condition scenarios under sea-level rise and evolving bathymetry.
By creating a high-fidelity dataset and ML framework, this research not only advances fundamental tsunami science but also delivers practical tools for agencies, researchers, and modelers worldwide to improve early-warning systems and better understand dispersive wave phenomena.
How to cite: Malik, R. and Synolakis, C.: Fast Screening of Dispersion-Sensitive Tsunami Waves: For Early Warning and Hazard Mapping, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1325, https://doi.org/10.5194/egusphere-egu26-1325, 2026.
Meteotsunamis are sea-level oscillations within the conventional tsunami period band (minutes to hours) generated by fast-moving atmospheric disturbances rather than by seismic, volcanic or mass-movement sources. They belong to the broader family of non-seismic sea-level oscillations at tsunami timescales (NSLOTT), which can contribute substantially to coastal extremes and therefore deserve explicit consideration in hazard assessments. In the Mediterranean, meteotsunamis are commonly reconstructed from atmospheric pressure and tide-gauge data, while constraints on nearshore impact and the associated circulation response remain comparatively limited. Although several Mediterranean events have been investigated, detailed reconstructions for the Strait of Sicily and the adjacent Maltese shelf are still limited.
In this work, supported by the Interreg VI-A Italia–Malta project WAVEGUARD, we examine the July 2024 Sicily Channel meteotsunami (“Marrobbio”) using a tightly co-located, multi-sensor dataset that combines barometric arrays and tide gauges with two observational components that are still underexploited for this class of events: coastal seismometers and high-frequency (HF) coastal radars, complemented by atmospheric reanalysis. Coastal seismic stations provide a direct, time-resolved proxy for shoreline impacts. Time–frequency analysis of the seismic wavefield isolates long-period energy and resolves distinct impact phases, yielding robust arrival windows even where sea-level records are unavailable or strongly affected by local filtering. Tide-gauge residuals from resonance-prone harbors show sustained oscillations consistent with strong port amplification and a dominant shelf/harbor control on the recorded signal.
Using the pressure networks, we triangulate the translating atmospheric disturbance and retrieve a fast NW–SE moving front (~18–24 m s⁻¹). This speed is consistent with the expected long-wave phase speed over the broad, shallow Sicilian shelf, supporting near-Proudman conditions as the main pathway for efficient energy transfer. We then apply the same timing framework to tide-gauge residual onsets and to seismic vector-RMS arrivals. Both reproduce the NW–SE progression but yield much lower apparent speeds (~2–6 m s⁻¹), demonstrating that the propagation inferred from sea level and seismicity primarily reflects delayed oceanic adjustment and resonance effects, rather than the atmospheric forcing kinematics.
HF radar measurements independently capture short-lived anomalies in nearshore surface currents that coincide with the strongest sea-level oscillations, indicating that this meteotsunami measurably modulated coastal circulation. Overall, the combined observations constrain the full atmosphere–ocean–solid earth response chain for the July 2024 event and demonstrate how integrating coastal seismology and HF radar with routine pressure and sea-level monitoring can improve detection and characterization of meteotsunamis in the central Mediterranean, with clear implications for future operational warning.
How to cite: D'Amico, S., Cannata, A., Capodici, F., Ciraolo, G., D'Amico, S., Gauci, A., Lo Re, C., Marinaro, G., Micallef, A., Nardone, G., Panzera, F., Giacalone, G., Bonanno, A., and Aronica, S.: Multiple observations of the July 2024 Sicily Channel meteotsunami from coastal seismology, pressure-sea level networks and High Frequency radar sensors, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3391, https://doi.org/10.5194/egusphere-egu26-3391, 2026.
The work assesses the distribution and strength of meteorological tsunamis (meteotsunamis) along the European coasts. The first step of the assessment is based on the evaluation of historical events observed along the European coasts and on the analysis of decadal time series of 1-minute sea level time series measured at more than 200 tide gauges. The analysis reveals that meteotsunamis are most prominent and contribute most strongly to extreme sea levels along the coasts of the Mediterranean Sea, but also affect other European coasts, including the Black Sea, the Baltic Sea, the North Sea and the European Atlantic coast. The second step of the assessment involves analysing atmospheric conditions during European meteotsunamis. Several atmospheric tsunamigenic sources are suggested: (i) atmospheric gravity waves and convective jumps that occur during otherwise fair weather (so-called “good weather meteotsunamis”), and (ii) convective jumps and pressure changes associated with extratropical cyclones, in particular with their cold fronts. Finally, the potential for the generation of meteotsunamis is assessed by analysing (i) the bathymetric and coastal characteristics of the European coasts and (ii) the prevalence of atmospheric conditions that can generate meteotsunamis. A positive superposition of these two factors leads to the highest meteotsunami generation potential over the Mediterranean Sea, as also suggested by the distribution of historical events and the analysis of 1-minute sea level time series.
How to cite: Sepic, J., Balic, M., Ruic, K., and Jukic, I.: Meteotsunamis along the European coastlines: distribution, atmospheric background and generation potential, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18917, https://doi.org/10.5194/egusphere-egu26-18917, 2026.
Meteotsunamis are tsunami-like sea-level oscillations initiated by atmospheric disturbances and amplified by resonance. Using a Portugal meteotsunami catalogue for 2010-2020 (39 events: 14 good-weather and 25 bad-weather), we propose an operational decision workflow that couples physically interpretable diagnostics with an atmospheric machine-learning (ML) trigger. We first test whether a compact physical formulation can explain sea-level variation. For “good-weather” cases, a regression model combining a direct pressure-response term with a resonance term improves (R² ≈ 0.40) and indicates peak amplification near a pressure-jump speed of U ≈ 20 m/s. Applying the same model to the full catalogue fails, suggesting that "bad-weather” cases may involve additional forcing and/or more complex atmospheric structure.
We then develop a meteotsunami detector using atmospheric pressure observation: pressure-jump candidates (ΔP ≥ 1.0 hPa) are consolidated, and converted into fixed 12-h multi-channel windows for a Temporal Convolutional Network (TCN) for each meteorological observatory. On an independent 2020 test set, the coastwide ensemble achieves event-level recall = 1.0 at τ = 0.30 (precision = 0.50; F1 = 0.67), but with substantial false alarms. To mitigate these limitations, we propose a two-stage warning strategy: an ML-driven atmospheric watch/advisory followed by tide-gauge (and future Distributed Acoustic Sensing, DAS) screening that first flags sea-level anomalies and then confirms meteotsunami-consistent signatures. This structure is designed to reduce false alarms while capturing events that may be weakly observed by the meteorological network.
How to cite: Kim, J. and Omira, R.: Toward operational meteotsunami warning on the Portuguese coast, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15219, https://doi.org/10.5194/egusphere-egu26-15219, 2026.
Meteotsunami waves entering harbour basins can generate rapid and potentially hazardous sea-level oscillations and associated currents, posing a serious threat to navigation, mooring safety, and port infrastructure. Large commercial ports are typically subdivided into multiple interconnected but functionally distinct basins, each serving specific operational purposes. Among these, small recreational marinas – although integral to major port systems – are often particularly vulnerable due to their limited spatial extent, complex geometry, and reduced hydrodynamic damping. The Smiltynė marina within the Port of Klaipėda represents a characteristic example of such a setting. In this study, we aim to numerically reconstruct the meteotsunami-induced water-level variability and the spatial distribution of current velocities observed during documented events in the Port of Klaipėda, with a specific focus on the hydrodynamic response of the Smiltynė marina using a Smoothed Particle Hydrodynamics modelling framework.
Smoothed Particle Hydrodynamics (SPH) is a mesh-free, fully Lagrangian numerical method that has become increasingly important for simulating complex free-surface flows in coastal and harbour environments. In contrast to traditional grid-based models, SPH represents the fluid as a collection of discrete particles that move with the flow, allowing for a natural treatment of large deformations, rapidly evolving water surfaces, and non-linear hydrodynamic processes. These characteristics are particularly relevant for meteotsunami events, which are often associated with short-lived but intense water-level oscillations and strongly transient current patterns in confined basins.
The particle-based formulation of SPH enables accurate representation of complex and irregular harbour geometries, narrow basins, and interactions with coastal structures without the need for dynamic remeshing. This is a key advantage when modelling small marinas, where localized flow acceleration, basin-scale resonance, and wave–structure interactions can play a dominant role in determining hydrodynamic response. Furthermore, SPH is well suited for resolving fluid–structure interactions and extreme flow conditions near quays and mooring facilities, where conventional depth-averaged or grid-based approaches may struggle to capture spatial heterogeneity. Owing to its ability to directly couple long-wave propagation, resonance processes, and current generation within a single modelling framework, SPH provides a robust and flexible tool for investigating meteotsunami-induced water-level variability and current velocities in small harbour environments. These capabilities make SPH particularly valuable for hazard assessment, operational risk evaluation, and infrastructure-oriented analyses in marinas exposed to extreme long-wave forcing. The first modelling results allow the identification of the most hazardous quays for vessel mooring under meteotsunami forcing. These findings are of direct relevance to marina operators, vessel owners, and coastal engineers, providing a scientific basis for risk-aware operational decisions and for the future planning and development of the marina infrastructure. This study was partially funded by the WaveWise project, which received funding from the Research Council of Lithuania (LMTLT) under agreement No. SMIP-24-140.
How to cite: Žalys, M., Nesteckytė, L., and Kelpšaitė-Rimkienė, L.: Numerical modelling of meteotsunami wave induced currents in Marinas using SPH, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14006, https://doi.org/10.5194/egusphere-egu26-14006, 2026.
To elucidate the formation of ridge-trapped waves, this study employs ray theory to derive the ray trajectories and wave crest equations for waves propagating over a triangular ridge. The results indicate that the ray trajectories above such topography follow trochoidal curves. The envelope formed by the cycloidal arches constitutes the caustic, whose shape is influenced by the incident wave frequency, wavenumber, ridge slope, and water depth over the ridge crest. The condition for wave trapping requires that the trough line of the incident wave spatially coincides with the crest line of the reflected wave along the caustic. Based on this condition, the relationship between the crest line of the trapped wave and its wavelength is established, leading to the dispersion relation for trapped waves over a triangular ridge. Although the dispersion relation obtained from ray theory differs in form from that derived from the linear long-wave equation, the results are in close agreement for triangular ridges with gentle slopes. Furthermore, the spatial distribution of wave crest lines is used to explain the variation in wave height for ridge-trapped waves.
How to cite: Wang, G. and Hu, D.: Ray Theory of Ridge-Trapped Waves over a Triangular Profile, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5604, https://doi.org/10.5194/egusphere-egu26-5604, 2026.
The process of ice melting is often accompanied by calving events, raising growing concern about calving-induced tsunamis, also referred to as iceberg-tsunamis (IBTs) [1]. Despite their potential impact, the generation mechanisms of IBTs remain relatively poorly understood. This study investigates IBTs generation in the geometry and bathymetry of the Wolstenholme Fjord, in northwestern Greenland, through a systematic parameter study.
Numerical simulations are performed using the open-source Smoothed Particle Hydrodynamics (SPH) code DualSPHysics v5.2.0. The model setup has been previously calibrated and validated against laboratory experiments reported in the literature [2]. Idealised solid ice blocks are first considered, with impact locations along the fjord, block dimensions, and volumes systematically varied to quantify how different calving failure mechanisms influence water displacement and near-field wave characteristics. Both falling and overturning calving scenarios are analysed within this framework. In a later stage, the assumption of a rigid ice block is relaxed by modelling the calving mass as deformable, allowing a first-order assessment of the role of ice fragmentation in wave generation. In a final phase, variations in glacier front positions, based on satellite observations and representative of seasonal advance and retreat, are also explored to assess its influence on wave generation.
If time allows, further validation of the numerical framework using observational datasets from the Italian MACMAP Project (A Multidisciplinary Analysis of Climate Change Indicators in the Mediterranean and Polar Regions) will be presented [3]. In particular, high-sampling sea-level measurements from the meteo-hydrometric station operating at Wolstenholme Fjord provide a valuable opportunity to compare simulated wave signals with observed calving-induced events. To enable this comparison, near-field wave features from DualSPHysics are coupled with the JAGURS software [4], which solves the two-dimensional nonlinear (possibly dispersive) shallow-water equations, allowing the investigation of wave propagation along the fjord up to the tide-gauge location.
[1] Heller, V., Attili, T., Chen, F., Gabl, R., Wolters, G. (2021). Large-scale investigation into iceberg-tsunamis generated by various iceberg calving mechanisms. Coast. Eng. 163, 103745, https://doi.org/10.1016/j.coastaleng.2020.103745
[2] Liu, J., Heller, V., Wang, Y., Yin, K. (2025). Investigation of subaerial landslide-tsunamis generated by different mass movement types using Smoothed Particle Hydrodynamics. Eng. Geol. 352, 108055, https://doi.org/10.1016/j.enggeo.2025.108055
[3] Danesi, S., Salimbeni, S., Muscari, G., Guarnieri, A., Fratianni, C., Sensale, G., Zaniboni, F. (2023). Meteo-hydrodynamic data, Wolstenholme Fjord, Greenland PITUFFIK_METEO (Version 1) [Dataset]. INGV, https://doi.org/10.13127/pituffik/meteo_hydro
[4] Baba, T., Takahashi, N., Kaneda, Y., Ando, K., Matsuoka, D., Kato, T. (2015). Parallel implementation of dispersive tsunami wave modeling with a nesting algorithm for the 2011 Tohoku tsunami. Pure Appl. Geophys. 172, 3455-3472, https://doi.org/10.1007/s00024-015-1049-2
How to cite: Guglielmin, A., Heller, V., Armigliato, A., and Zaniboni, F.: Numerical investigation of iceberg-tsunamis with DualSPHysics, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7694, https://doi.org/10.5194/egusphere-egu26-7694, 2026.
In this study, we developed an efficient framework for tsunami source inversion based on the Neural Operator (NO). Tsunami simulations calculate the spatio-temporal evolution of sea surface height, using vertical seafloor displacement as the initial condition. However, high-resolution simulation over large computational domains involves significant computational costs. Furthermore, inverse analysis to estimate fault parameters from observed waveforms requires repeated forward simulations, making computational efficiency a critical challenge. To address these issues, we developed a surrogate tsunami simulation model based on the NO framework. Unlike conventional numerical solvers, the trained NO model can instantly predict the spatio-temporal wavefield from a given initial seafloor displacement.
We employed the U-shaped Neural Operator (U-NO), which combines a U-Net-like encoder-decoder structure with the efficient Fourier-space convolutions. The training dataset was generated using the open-source tsunami simulation code JAGURS: we first simulated 2000 seafloor displacement patterns derived from randomly selected fault parameters. Then JAGURS was used to calculate the subsequent tsunami wavefields, and the NO model learned the relationship between the initial conditions and the wavefields. Validation using unseen test cases confirmed that the NO model successfully reproduces the spatio-temporal propagation patterns of the tsunamis, although spectral analysis revealed a tendency to underestimate short-wavelength components.
A significant advantage of our PyTorch-based NO model is its compatibility with automatic differentiation, enabling direct computation of gradients of the output wavefield with respect to the input parameters. Leveraging this capability, we performed gradient-based source inversion by minimizing the misfit between observed and predicted waveforms. To address the underdetermined nature of estimating parameters over tens of thousands of grid points, spatial smoothing via Laplacian regularization was introduced.
Furthermore, we developed an integrated model by connecting the NO model with Okada (1985)’s crustal deformation formulas implemented in PyTorch. This integrated model enables direct prediction of tsunami wavefield from fault parameters (e.g., location, slip amount). This approach also enables efficient exploration of nonlinear parameter space using gradient-based optimization, offering a significant computational advantage over traditional grid-search approaches. While challenges remain, such as sensitivity to initial parameter selection and the presence of local minima due to strong nonlinearity, the proposed framework demonstrates great potential for rapid source estimation. Future work will focus on (1) improving the representation of short-wavelength components, (2) extending this framework to more complex governing equations such as dispersive tsunami models, and (3) application to real observation data.
How to cite: Someya, M. and Furumura, T.: Surrogate Modeling of Tsunami Simulation using Neural Operator: Application to Rapid Source Inversion, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8891, https://doi.org/10.5194/egusphere-egu26-8891, 2026.
About 150 km off the western coast of Calabria (Italy) lies the Marsili seamount, the largest and most active submarine volcano in the Mediterranean region, representing one of its most significant geohazards. Due to its proximity to densely populated coastal areas, a potential flank collapse could generate extreme tsunami events.
In this work, we perform high-resolution numerical simulations to explore multiple risk scenarios associated with Marsili-induced tsunamis. The model solves the depth-averaged Shallow Water Equations using a shock-capturing HLL scheme combined with the cut-cell technique to accurately represent coastal boundaries. Realistic bathymetric data were employed to simulate tsunami propagation over an area of approximately 69km2 , encompassing northern Sicily, western Calabria, and the Aeolian Islands.
The results provide insight into tsunami dynamics and highlight the importance of advanced numerical modeling for improving regional hazard assessments and early-warning strategies in the central Mediterranean.
This study was carried out within the Space It Up project, funded by the Italian Space Agency (ASI), and the Ministry of University and Research (MUR), under Contract Grant No. 2024-5-E.0–CUP no. I53D24000060005.
How to cite: Congacha, A., Caparelli, V., Carbone, F., and Servidio, S.: Risk Scenarios of Extreme Tsunamis Caused by Marsili in the Mediterranean Sea , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9300, https://doi.org/10.5194/egusphere-egu26-9300, 2026.
To improve the understanding of tsunami generation and propagation mechanisms and to enable more rigorous coastal hazard assessments, numerical simulation has become an indispensable tool. In most tsunami models, seismic dynamics are simplified as an instantaneous displacement of the seafloor; however, atypical events such as the 2018 Palu tsunami have highlighted the limitations of this assumption and demonstrated that seismic dynamics can play a critical role when rupture propagation occurs at speeds comparable to tsunami wave propagation. Fully coupled three-dimensional fluid–solid interaction models can account for these effects, but their computational cost makes them impractical for the parametric studies required in risk analysis.
In this work, we investigate the influence of dynamic seafloor motion on tsunami generation using a simplified modeling framework based on modified Saint-Venant equations. We propose a two-dimensional nonlinear spectral solver founded on the Fourier Continuation (FC) method, which provides high-order resolution of the governing equations while effectively eliminating numerical dispersion. This property significantly improves long-range accuracy and makes the method particularly well suited for capturing the multiple spatial and temporal scales involved in seismogenic tsunami modeling. Compared to commonly used finite-volume or finite-difference approaches, which can often suffer from dispersion errors that accumulate during propagation that require costly refinement, the spectral FC-based solver offers a fast (FFT-comparable), accurate, and low-cost alternative.
The solver has been validated against a range of analytical and experimental benchmarks, demonstrating its relevance for high-fidelity tsunami simulations. New results further highlight its capability to model both the generation and propagation of tsunamis driven by dynamically evolving seismic sources obtained from 3D rupture simulation software facilitated by discrete and spectral element methods. These results extend previous one-dimensional studies to a fully two-dimensional framework and open new perspectives for the efficient and accurate numerical investigation of tsunami hazards.
How to cite: Melkior, T., Bhat, H., and Amlani, F.: A high-order solver for simulating tsunami genesis and propagation induced by highly time-dependent earthquake ground motion, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10036, https://doi.org/10.5194/egusphere-egu26-10036, 2026.
Subaerial landslides-induced tsunamis are challenging due to their interaction with air and water. This implies the need for modelling granular collision stresses, fluid-grain interaction and impact shock, and also the resulting cratering. Fully three-dimensional models can be too computationally expensive in practical use such as for analysing parameter sensitivity. Depth-averaged models offer an alternative by enabling faster simulations. The challenge then is in retaining essential physical processes in the depth-averaged process. This work focuses on the development of a two-phase depth-averaged model designed to simulate both subaerial and submarine landslides and the waves they generate using a variant of the μ(I) landslide model for the granular rheology. The approach aims to capture the interaction between solid and fluid phases while maintaining computational efficiency. We compare results using this new model (presently under development) with simpler existing models. We also cover some key challenges encountered during model formulation and implementation, including mathematical and numerical issues such as ill-posedness, instability, and the need for well-balanced schemes. We examine the suitability of various numerical schemes and solvers for this application and present landslide parameter sensitivity analysis. Finally, we compare our approach with alternative modelling frameworks to evaluate performance and reliability and briefly discuss gaps in current depth-averaged modelling approaches. By addressing these questions, we attempt steps towards advancing efficient and robust tools for simulating landslide-generated waves and improving coastal hazard assessment through embedding more advanced landslide formulations in depth averaged models.
How to cite: Bhure, A., Castro Díaz, M. J., Storrøsten, E., Løvholt, F., Tregaskis, C., and Brodtkorb, A.: An Efficient Landslide–Tsunami Model with Two-Phase Rheology: Challenges and Implementation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10451, https://doi.org/10.5194/egusphere-egu26-10451, 2026.
This work presents an overview of two sets of experiments, carried out at the Hydrodynamics Laboratory of the University of Oslo in a small 3 m long and 10 cm wide wave tank, filled with 5 cm of water. The purpose of the experiments was to examine how tsunami-driven transport of boulders is influenced by the presence of sand or any other smaller sediments on the bottom.
The “tsunami” wave input for all three experiments was kept the same and was presented by breaking solitary waves with an amplitude normalized by water depth a/ℎ = 0.5. Generated solitary waves propagated towards a 1:10 beach, which was also kept the same for all experiments.
The boulders were represented by concrete blocks of different shape and size. They were placed alternately (one at a time) at different locations on the beach slope with respect to the wave breaking point.
Experiment 1 was conducted in two set-ups: (i) empty Polymethyl methacrylate (PMMA) bottom of the flume, (ii) the slope covered by a thin layer of 65 μm sand. Transport of boulders and their dynamics was studied with respect to boulder characteristics (size, orientation), their initial position regarding the wave breaking point and inclusion of sediment. It was shown that presence of sediment enhanced boulder transport. In particular, in this set-up, the presence of sediment increased the boulder transport in 2–5 times. The maximum displacement increase was observed for boulders with the smallest length and height and the largest width initially located at the breaking position.
Another result regarded the type of boulder motion. The boulders experienced either sliding or turning over. Boulders whose height was at least twice as large as their length exhibited turning-over. This held for boulders placed both on an empty PMMA slope and on a sedimentary slope. However, the largest boulder displacement on an empty PMMA slope occurred due to turning over, while on a sedimentary slope it occurred due to sliding.
Experiment 2 examined the influence of the thickness and the size of the sediments. In this set of experiments the slope was covered with a thicker layer of sediment (2 cm) compared to the one used in Experiment I, and in addition to the 65 μm sand, coarser sand with a grain size of 250 μm was used. For this 60 cm long, 10 cm wide, and 2 cm deep section was carved out of the slope and filled with either 65 μm sand or 250 μm sand, forming a sandy beach. The results showed that boulders traveled farther over the coarser sand due to reduced friction. Furthermore, the sandy slopes caused the boulders to rotate or turn over.
How to cite: Didenkulova, I., Su, P.-T., and Jensen, A.: Boulder transport by tsunamis: what happens if we add some sand?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12445, https://doi.org/10.5194/egusphere-egu26-12445, 2026.
The M7.3 East Cape Earthquake on 5th of March 2021 generated a tsunami whose observed signals challenge earthquake-only modelling approaches. The earthquake occurred at just after 2 am (NZT), at the northern end of the Hikurangi Subduction Zone of the East Cape of Aotearoa New Zealand, followed by a modest tsunami detected on GeoNet’s DART and coastal gauge network. This study investigates the tsunami signals of this event.
The earthquake was initially challenging to characterise, with a large variety of depths and focal mechanisms determined by various seismic agencies. Subsequently, Okuwaki et al. (2021) and Xie et al. (2022) took seismological approaches to better understand the mechanism, concurring that the rupture comprised two related subevents.
Our tsunami modelling suggests that none of the various proposed earthquake solutions reproduced the full spread of observed waves detected, particularly the varied amplitude persistence across different sensors. We use the COMCOT tsunami model with a nested array of bathymetric grids. We perform a methodology validation on the 2016 Te Araroa earthquake and tsunami, which occurred in a very similar location. With a slight origin relocation similar to Kubota et al.’s (2016) proposal, we are able to match the observed signals well. The identified limitations of earthquake-only source characterisation lead us to explore the potential contribution of an additional landslide source.
We therefore test alternative mixed source mechanisms, exploring a potential partial reactivation of the historical submarine Ruatoria Debris Avalanche only a few kilometers away from the proposed earthquake locations. Mixed source tests are currently ongoing with full results to be presented at the meeting. Our work highlights the importance of understanding the hazard of potential submarine landslides near the coast of New Zealand and the importance of considering multi-mechanism tsunami sources in real time during tsunami response.
How to cite: Rapson Nuñez del Prado, C., Roger, J., and Davidson, S.: More Than a Quake? Exploring a multi-mechanism source of the 2021 East Cape Tsunami, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-855, https://doi.org/10.5194/egusphere-egu26-855, 2026.
The recent resumption of the unrest at the Campi Flegrei caldera, located near the large metropolitan area of Naples (southern Italy), has raised significant concerns about the potential effects of volcanic events in such a densely urbanized environment. This volcanic structure is well documented in historical records, and its peculiar volcanic and seismic activity, manifesting by uplift cycles and the phenomenon of “bradyseism”, is intensively studied and continuously monitored.
One of the least considered volcanic-related phenomena is the potential mass destabilization, which in turn can interact with water and generate tsunamis. In particular, the Campi Flegrei caldera extends beneath the Gulf of Pozzuoli, a 20-km wide sub-basin of the larger Gulf of Naples, whose coasts are characterized by a high degree of anthropization, including both industrial structures and tourist facilities, which significantly increases exposure and vulnerability.
In this work, four landslide scenarios are defined, three of which are in the submarine domain. These are realized based on the limited bathymetric and geophysical studies and data available for the area. The reconstructed volumes span 2 to 4 million cubic meters and are in shallow water, in three distinct locations within the basin. The fourth scenario, with a smaller volume of around half million cubic meters, is positioned onshore, near a coastal stretch which recently experienced the collapse of cliffs induced by an earthquake. The dynamics of these landslides and the ensuing tsunamigenic impulse are reconstructed through dedicated numerical codes, developed and maintained by the University of Bologna research team; the propagation of the respective waves is simulated through the code JAGURS [1]. This approach provides insights into the tsunami energy distribution in the basin and its interaction with the coastlines.
The results show that the submarine landslides do not generate catastrophic waves; however, they are able to damage small boats and induce resonance effects in small sub-basins, posing a potential hazard. In contrast, the subaerial scenario, while characterized by a minor volume, can generate local catastrophic waves, exceeding 4 m in amplitude. The role of wave dispersion in landslide-tsunami propagation, and the way if affects much more this last case in comparison with the submarine ones is discussed as well.
[1] Baba, T., Takahashi, N., Kaneda, Y., Ando, K., Matsuoka, D., & Kato, T. (2015). Parallel implementation of dispersive tsunami wave modeling with a nesting algorithm for the 2011 Tohoku tsunami. Pure and Applied Geophysics, 172(12), 3455-3472.
How to cite: Zaniboni, F., Sabino, L., Angeli, C., Zanetti, M., and Armigliato, A.: Exploring the tsunamigenic potential of unstable masses in the Gulf of Pozzuoli (Naples, Italy), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12646, https://doi.org/10.5194/egusphere-egu26-12646, 2026.
Situated at the northeastern end of the Red Sea, the Gulf of Aqaba is a narrow, semi-enclosed, deep basin between the Sinai and Arabian peninsulas. Earthquake- and (submarine) landslide-generated tsunamis have been documented in historical records and supported by recent studies, posing a potential hazard to surrounding coastal communities. However, limited observational data hinder a comprehensive understanding of tsunami source processes and associated hazards in the region. Ongoing coastal development, including the NEOM project in northwestern Saudi Arabia, together with continued expansion of tourism, further underscores the need for improved tsunami hazard assessment in the Gulf of Aqaba.
In this study, we model multiple landslide-generated tsunami scenarios to investigate how landslide processes and source locations influence tsunami hazard in the Gulf of Aqaba. Simulations are performed with the open-source code D-Claw, a depth-averaged, finite-volume framework coupling shallow-water hydrodynamics with dense granular landslide flow. Results show that tsunami excitation is sensitive to landslide thickness, source volume, and material properties. In particular, solid volume fraction and permeability exert a pronounced control on tsunami generation efficiency: contractive, low-permeability slides produce larger waves than non-contractive, high-permeability counterparts. In addition, the landslide location strongly modulates localized tsunami wave heights along the Gulf coast. The narrow basin geometry yields short arrival times and promotes repeated reflections and resonant sloshing that persist for approximately 50 minutes, with the strongest response along shorelines proximal to the source. Taken together, these results highlight the critical role of landslide source characteristics and the topography–bathymetry in shaping tsunami hazard in confined basins such as the Gulf of Aqaba, underscoring the need for scenario-based, physics-driven hazard assessments.
How to cite: Dai, J., Li, B., and Mai, P. M.: Scenario-based landslide-generated tsunami modeling in the Gulf of Aqaba, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13962, https://doi.org/10.5194/egusphere-egu26-13962, 2026.
Seaports are critical coastal infrastructures whose disruption during tsunami events can trigger major economic losses and cascading impacts across global supply chains, including indirect effects on ports that are not directly impacted but are operationally and logistically linked to affected ports through inter-port dependencies. Existing approaches to assessing their operational vulnerability often fail to simultaneously capture both component-level and system-level effects, as well as the inherent uncertainties in port operations. This study presents a comprehensive framework using a Bayesian network (BN) to assess disruption at affected ports and the resulting indirect business loss at other ports under varying tsunami intensities. The proposed approach considers offshore wave height and amplification to derive the probability distribution of inundation depth as the primary hazard intensity measure, which is then propagated through interconnected port subsystems and port-to-port dependencies to enable probabilistic inference of both direct and indirect disruptions. The 2011 Great East Japan Tsunami is used as a case study to assess port disruptions in the Tohoku region and the associated indirect impacts on other ports. Our preliminary results indicate that a tsunami inundation depth of 2.0-4.0 m leads to significant operational impacts, with a 55% probability of port disruption exceeding 90 days and a cumulative 84% probability of the disruption lasting at least 50 days. Stress testing is also employed to evaluate how port functionalities respond under a spectrum of tsunami scenarios. This probabilistic approach provides port authorities and coastal planners with a decision-support tool to evaluate potential direct and indirect disruptions and optimize recovery strategies, thereby enhancing maritime infrastructure resilience against future tsunami hazards.
How to cite: Ashrafuzzaman, M., Jalayer, F., and Ghaffarian, S.: Probabilistic Assessment of Seaport Disruptions under Tsunami Events, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14622, https://doi.org/10.5194/egusphere-egu26-14622, 2026.
Various approaches exist to generate physically plausible tsunami source models in order to quantify source uncertainty in tsunami hazard assessments. Among these, stochastic slip models are widely used due to their low computational cost. Finite-fault models derived from inversion results are also sometimes used to anticipate the slip distributions of future ruptures.
In this study, we compare synthetic tsunamis generated using a stochastic slip model with far-field DART observations from 14 tsunami events. We construct eight classes of source models based on combinations of two scaling relations (Murotani et al., 2013; Strasser et al., 2010), circular and rectangular rupture geometries, and depth-independent versus depth-dependent rigidity and coupling. For each class, we simulate a number of synthetic tsunamis using stochastic slip distributions of earthquakes of magnitude and location similar to those of the earthquakes that generated the 14 tsunamis. The results indicate that nearly all source model classes exhibit a mild—though not statistically significant—tendency to generate synthetic tsunamis which overestimate the observed tsunami amplitudes.
We further conduct a quantitative comparison of slip distributions and tsunami time series from the best-fitting stochastic scenarios with those obtained from finite-fault teleseismic inversion models, some of which are constrained also by tsunami data. Overall, the best-fitting stochastic models reproduce observed tsunami waveforms more accurately than models derived from teleseismic-only inversions. However, for some events, specific slip patterns inferred from inversion models, such as an annular shape, cannot be adequately reproduced by the stochastic approach, leading to poorer fits to the observations.
How to cite: Bayraktar, H. B., Lorito, S., Scala, A., Festa, G., Romano, F., Abbate, A., Volpe, M., Lay, T., Sánchez-Linares, C., Catalan, P., and Davies, G.: Performance of Stochastic Tsunami Source Models Compared with Observations and Finite-Fault Inversions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14076, https://doi.org/10.5194/egusphere-egu26-14076, 2026.
Tsunami Warning Systems have been progressively developed over the past six decades, with significant expansion and improvement in the last 20 years, in the aftermath of the 2024 Indian Ocean tsunami. In the NE Atlantic and Mediterranean region (NEAM), five Tsunami Service Providers (TSPs) (Portugal, France, Italy, Greece, Turkey) are operating on a permanent basis, following recommendations of the IOC/UNESCO within the ICG/NEAM (Intergovernmental Coordination Group). Frequent exercises are necessary to ensure a high level of operation and preparedness. Every 2-3 years, ICG/NEAM organizes regional exercises, called NEAMWave.
The NEAMWave26 exercise was conducted in March 2026 to test the TSPs’ warning chains and procedures at multiple operational levels. Five scenarios were designed across the NEAM region. The scenario built for the NE Atlantic is based on the 1755 Lisbon earthquake, with an estimated moment magnitude of approximately 8.5. This event triggered a catastrophic tsunami and remains the largest natural disaster in Europe in the last 500 years, in terms of loss of lives and destruction. We present here a detailed analysis of this scenario and the lessons learned from the NEAMwave26 exercise in the NE Atlantic. Using numerical modeling, we show how tsunami waves propagated across the NE Atlantic, generating hazard and threat levels, both at regional and local scales. The tsunami warning messages issued by two operating TSPs (CENALT, France, and IPMA, Portugal) are presented to illustrate the sequence of the operational procedures in response to tsunami threat in the NE Atlantic. Moreover, the exercise outcomes are analyzed in light of feedback from subscribers and local authorities to draw key lessons learned from this exercise.
How to cite: Hébert, H., Carrilho, F., Dupont, A., Gailler, A., Omira, R., and Roudil, P.: NEAMWave26 exercise in the NE Atlantic Ocean: an opportunity for a better preparedness and operational response to large tsunamis off the Iberian margin, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14731, https://doi.org/10.5194/egusphere-egu26-14731, 2026.
Tsunamis are low-frequency but high-consequence hazards, and following the 2004 Indian Ocean and 2011 Tohoku events, probabilistic approaches have become essential for long-term risk characterization. The East Sea (Sea of Japan) is a semi-enclosed marginal sea with numerous active submarine faults and a history of recurrent tsunami events. Major cities and industrial complexes are concentrated along Korea's eastern coast. However, probabilistic tsunami hazard assessment (PTHA) studies incorporating multiple source zones with systematic deaggregation remain limited for this region.
This study conducts a comprehensive PTHA for the entire eastern coast of Korea, integrating six seismic source zones in the East Sea. A logic-tree framework was developed to represent epistemic uncertainties, comprising 2,160 simulation branches derived from source parameters including magnitude, fault geometry, dip, and strike. These simulation branches were coupled with statistical branches representing three return periods and four Aida’s K values, yielding a total of 25,920 scenario combinations. Numerical simulations were performed using the COMCOT model with nested grids at approximately 40 m nearshore resolution. Maximum tsunami heights were used to construct exceedance probability curves based on a Poisson model. Deaggregation analysis was then applied to quantify the contributions of magnitude, source distance, and source zone to site-specific hazard levels.
Hazard analysis reveals pronounced regional disparities. Sokcho and Donghae were identified as critical locations with significantly higher projected tsunami heights. This hazard amplification is attributed to wave energy focusing induced by complex bathymetric features, specifically the Yamato Rise and the K-shaped ridge. Furthermore, deaggregation analysis reveals that fault ruptures along the central eastern margin of the East Sea (Sea of Japan) are the dominant contributors to the hazard in these regions. By systematically isolating the contributions of magnitude and source zones, this study provides a physically interpretable framework for prioritizing site-specific mitigation strategies and identifying potential dominant sources.
Acknowledgement
This work was supported by the Korea Environment Industry & Technology Institute (KEITI) through the R&D Program for Innovative Flood Protection Technologies Against Climate Crisis, funded by the Ministry of Climate, Energy and Environment (MCEE) of Korea (RS-2023-00218873).
How to cite: Oh, S., Koh, M. J., and Son, S.: Probabilistic Tsunami Hazard Assessment and Deaggregation for the Eastern Coast of Korea, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17872, https://doi.org/10.5194/egusphere-egu26-17872, 2026.
To implement effective mitigation strategies and coastal planning, it is crucial to understand the hydrodynamics of Extreme Wave Events (EWE) including major storms, hurricanes or tsunamis. One of such examples is the CE1755 tsunami that affected the shores of several regions around the Atlantic. Despite its magnitude, the exact seismogenic source of this event is still an open discussion, with hypotheses ranging form the Horseshoe Fault (HSF) and the Marques de Pombal Fault (MPF) to the Gorringe Bank (GB) and the Cadiz Accretionary Wedge (CAW).
This study specifically focused on the embayments of Martinhal, Boca do Rio and Lagos (along the southern coast of Portugal, immediately to the east of Sagres) where detailed geological and historical records are available facilitating ground truth on the adopted modelling approach.
Hydrodynamic modeling was made using Delft3D-FLOW to simulate wave generation, propagation and inundation. Five potential tectonic scenarios were tested: the four singular faults mentioned above and a combined “Scenario 1” (HSF+GB). To ensure accuracy in the nearshore interactions, high-resolution nested grids were generated, refining the spatial resolution down to 50 meters.
The model outputs were validated by cross-referencing reported wave heights (e.g., ~6.6m at Martinhal, ~11-13m at Boca do Rio) and arrival times. The comparative analysis reveals that the Horseshoe Fault (HSF) and the combined faults (Scenario 1) provided the best fit with historical accounts and geological evidence. Contrarily, the Cadiz Accretionary Wedge scenario produced wave heights significantly lower than those historically reported, making it an unlikely source. These findings contribute to the ongoing effort to better understand EWE impacts along the Iberian coasts.
This work is supported by FCT, I.P./MCTES through national funds (PIDDAC): LA/P/0068/2020 - https://doi.org/10.54499/LA/P/0068/2020 , UID/50019/2025 and https://doi.org/10.54499/UID/PRR/50019/2025, UID/PRR2/50019/2025. Finally, this work is a contribution to project iCoast (project 14796 COMPETE2030-FEDER-00930000).
How to cite: Magalhães, R., Costa, P., and Dourado, F.: Hydrodynamic Modeling of the CE1755 Tsunami along the Western Algarve (Portugal), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19431, https://doi.org/10.5194/egusphere-egu26-19431, 2026.
Probabilistic Tsunami Forecasting (PTF) provides a rapid estimation of tsunami hazard intensity probabilities at given forecast points when a potentially tsunamigenic earthquake has occurred. According to predefined rules provided by the decision makers, PTF can also convert these values into uncertainty-informed alert levels that can be used in operational tsunami early warning or post-event actions for risk reduction (for example, evacuation). The PTF workflow is planned to become operational at the Italian Tsunami Warning Center (CAT-INGV) with a specific setting for delivering early warning messages in the Mediterranean area. Indeed, the PTF implemented for the CAT-INGV relies on the long-term hazard model NEAMTHM18 and on a large database of precomputed tsunami scenarios.
Here we present the first prototype of the PTF extension at global scale, where the ensemble of seismic scenarios is defined from scratch using real-time data (hypocenter and magnitude of the event) and moment tensor solutions provided by an ad hoc integrated tool and external agencies in quasi real time. Each source parameter is discretized within a given range of values around the provided solution and the corresponding uncertainties are assigned through weight distributions of these parametrizations. For each scenario, the initial sea floor displacement is computed based on a standard uniform rupture model. The corresponding tsunami impact is estimated using on-the-fly numerical simulations, requiring dedicated HPC resources.
This global-scale version of the PTF is here presented through the hindcast of two major megathrust events in the Pacific Ocean; the 2010 Mw 8.8 Maule, Chile and the 2011 Mw 9.1, Tohoku, Japan earthquakes and tsunamis.
This work was partially funded by the DT-GEO project (A Digital Twin for GEOphysical extremes, https://dtgeo.eu/) through the European Union’s Horizon Europe research and innovation programme under grant agreement nº 101058129.
How to cite: Tonini, R., Volpe, M., Magni, V., Di Stefano, A., Bernardi, F., Bruni, S., Di Benedetto, A., Romano, F., Vitiello, L., Løvolt, F., and Lorito, S.: Probabilistic tsunami forecasting for earthquakes at global scale, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19797, https://doi.org/10.5194/egusphere-egu26-19797, 2026.
Volcanic landslides along the Sciara del Fuoco (SdF) flank of Stromboli frequently enter the sea, triggering near-field tsunamis. These tsunamis produce static pressure loads on the seafloor and coastal areas, inducing elastic ground deformation detectable by nearby broadband seismic stations as measurable ground tilt signals.
We present a comprehensive investigation of tsunami-induced ground tilt recorded at inland coastal seismometers to test the potential for early tsunami detection and modeling. Our analysis focuses on near-field coastal broadband seismic records generated by the tsunamigenic landslide event of 3 July 2019 at Stromboli. These records are dominated by tilt induced by static tsunami loading, exhibiting distinctive horizontal very-long-period (VLP) seismic signals ranging from about 70 to 120 seconds, polarized perpendicular to the coastline.
To establish the physical connection between tsunami generation and the observed coastal ground tilt signals, we implemented a model to compute the effect of elastic ground deformation induced by quasi-static tsunami loading, using outputs from the tsunami modeling of this specific event.
Tsunami generation and propagation were simulated using the Multilayer-HySEA hydrodynamic numerical model (Macías et al., 2021), which accurately reproduces the observed tsunami signals at three sea-level stations around Stromboli. Moreover, the tilt signals computed from the tsunami load model fit satisfactorily the observed seismically derived tilt signals at the coastal broadband seismic stations, capturing even the early tsunami phase. The analysis demonstrated the early detectability of the tsunami: clear tilt signals emerge ~0.5-1.5 minutes before tsunami arrival at the nearest offshore and coastal gauges, respectively. This highlights the potential of coastal seismic sensors as a tsunami detector and for providing short-term early warnings before the tsunami reaches the coast.
The recorded tsunami-induced tilt amplitudes range from 0.05 to 0.15 µrad, decreasing with the station’s distance from the coast and remaining detectable up to ~500 m. This underscores the importance of station proximity for effective tsunami detection.
We also establish an empirical scaling relationship between coastal tilt amplitudes and tsunami height, potentially providing a practical tool to estimate tsunami amplitudes for future events. After further testing, this approach may complement traditional tsunami monitoring and warning systems.
How to cite: Othman, A., Babeyko, A., Gálvez, J. F. R., Armigliato, A., Lorito, S., Romano, F., Tadini , A., de' Michieli Vitturi, M., Coltelli, M., and Cavallaro, D.: Analysis and Modeling of Near-Field Tsunami-induced Tilt Signals at Coastal Broadband Seismometers at Stromboli Volcano, Italy , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20139, https://doi.org/10.5194/egusphere-egu26-20139, 2026.
A fully integrated tsunami monitoring unit, funded by the Italian National Civil Protection Department, was installed in July 2025 by INGV, offshore the Sciara del Fuoco, Stromboli, under the coordination of two INGV centres, the CME (Centro Monitoraggio Eolie) and CAT (Centro Allerta Tsunami), and has been operating reliably since.
The seafloor module, anchored to a reinforced-concrete deadweight, hosts multiple sensors, including a pressure sensor to detect rapid sea-level changes, a hydrophone to capture volcanic and underwater activity and an accelerometer to observe seafloor dynamics.
Information is exchanged bidirectionally between the buoy and the seafloor module through an elastic electromechanical cable, also supplying energy to the seafloor module, and simultaneously providing elastic mooring.
The elastic cable can extend up to 2.5 times its unstretched length while maintaining its mechanical and electrical integrity. To reach the installation depth, two cable segments were connected using an intermediate connection buoy. A mechanical release system can be triggered acoustically to release the seafloor module from the deadweight.
The depth of the seafloor module, approximately 88 meters, was chosen so that pressure data can be converted into tsunami height values to limit as much as possible the deep-water high-wavenumber attenuation effects, as tsunamis induced by mass flows over the Sciara del Fuoco feature shorter periods signals than earthquake-generated tsunamis.
Data streams are transmitted via radio and Wi-Fi to the shore station on Stromboli Island, then forwarded to the INGV-Osservatorio Etneo data center at the COA (Centro Operazioni Avanzate) in Stromboli. From there, the data are transmitted to the INGV-CAT. An STA/LTA algorithm, first introduced by Ripepe & Lacanna (2024) for the tsunami warning at Stromboli from the elastic beacons at a similar location, is applied experimentally to the data stream. The data will become in the future an important source of information for the tsunami warning system in Stromboli.
How to cite: Costanza, A., Macaluso, F., Fertitta, G., Coltelli, M., Lazzaro, D., D'Agostino, M., Lorito, S., Amato, A., Piatanesi, A., Bruni, S., Romano, F., Abbate, A., Cascone, V., and Di Benedetto, A.: Deployment of a Multi-Parameter Volcanic Tsunami Monitoring System Offshore Sciara del Fuoco, Stromboli, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21354, https://doi.org/10.5194/egusphere-egu26-21354, 2026.
The NEAM-COMMITMENT project, funded by the European Commission’s DG ECHO and aiming to support improved tsunami risk management and planning in the North-Eastern Atlantic, Mediterranean, and connected seas (NEAM) region, has entered the final phase of its implementation. Here, we present the progress achieved so far in two key components of tsunami risk governance: (1) capacity building through tsunami hazard assessment and mapping at the national scale, and (2) improved tsunami evacuation planning at the local level through a novel multi-hazard approach.
For the first component, the project aims to develop national tsunami inundation maps for Cyprus, Greece, and Spain by applying a GIS-based methodology previously implemented in Italy, leveraging offshore inputs from the NEAM probabilistic tsunami hazard model (NEAMTHM18; Basili et al., 2021, Frontiers in Earth Science) to define large-scale coastal inundation zones. A capacity-building workshop has already been held in Rome to train partners on the new tools and to gather feedback for further methodological improvements. At the national level, technical workshops have been conducted in the three countries developing the maps, during which design parameters and safety factors (to translate offshore hazard curves into runup values) were selected through a science-informed, participatory decision-making approach. This process enables decision-makers to take ownership of the products and maximizes implementation effectiveness.
For the second component, the objective is to develop and test a multi-hazard approach to tsunami evacuation management that accounts for cascading effects, thus complementing existing guidelines. This approach is being applied at local pilot sites in Greece and Italy, focusing on earthquake–tsunami and volcano–tsunami scenarios, respectively. In this context, hazard workshops were conducted in Methoni and Stromboli, where scientists engaged with local communities and explained the multiple hazards affecting each area. The outcomes of these workshops will inform the next step in the process, to help designing tsunami evacuation maps for both sites.
The project builds on previous and ongoing initiatives, including TSUMAPS-NEAM, CoastWAVE, EPOS TCS Tsunami, and the Global Tsunami Model, among others, and fosters multinational collaboration among 13 institutions from four NEAM countries. This collaboration strengthens cooperation within the NEAM Tsunami Warning System and the EU Civil Protection Mechanism. The resulting national and local tsunami mapping products will be supported by open-access guidelines, tools, and OGC web services that ensure compliance with the FAIR (Findable, Accessible, Interoperable, and Reusable) principles, with the aim of contributing to improved tsunami risk management in the NEAM region and beyond.
How to cite: Charalampakis, M., Kalligeris, N., Graziani, L., Aguirre Ayerbe, I., Di Manna, P., Silva, V., Macias, J., Russo, D., E. Synolakis, C., Antonakos, A., Pilidou, S., D'Angelo, L., and González González, C. and the NEAM-COMMITMENT project team: NEAM-COMMITMENT: Strengthening Tsunami Risk Governance through National Inundation Mapping and Multi-Hazard Evacuation Planning, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19981, https://doi.org/10.5194/egusphere-egu26-19981, 2026.
The Global Tsunami Model Association (GTM) is presently finalizing a Probabilistic Tsunami Hazard Assessment (PTHA) for earthquake-generated tsunamis at the global scale. Compared to the Davies et al. (2018) global PTHA, the GTM-PTHA incorporates several new features, including stochastic slip models, a spatially higher resolution of calculation points (which also includes relatively small islands), and the consideration of tides and long-term sea level variations. An important aspect is that the GTM-PTHA is interoperable with seismic source models and risk calculation tools from Global Earthquake Model (GEM) (e.g., OpenQuake Engine). The preliminary GTM-PTHA Python framework tool can be used to calculate hazard curves from different subduction interfaces at different points of interest, presently limited to the coasts of the Pacific Ocean. The steps implemented in the workflow integrate long-term seismic information, numerical tsunami simulations of unit sources to build a database of Green’s Functions (GF), a linear combination of the GF, and probabilistic hazard calculations. Specifically, the workflow begins with the definition of a probabilistic earthquake model, based on synthetic earthquake scenarios generated at each subduction interface. The occurrence rates of each scenario depend on the frequency-magnitude distribution specific to each subduction zone. Then, the tsunami waveforms associated with each synthetic rupture are computed through a linear combination of precalculated GF defined for each subduction zone (assuming a linear tsunami propagation). In the final step, probabilistic tsunami hazard curves are generated by combining the annual occurrence rates of the earthquake scenarios with the maximum wave amplitudes computed on a set of predefined points. A dedicated sensitivity analysis is also being performed, whose preliminary results will be illustrated, providing insight into the epistemic uncertainties associated with the new hazard model.
The authors thank the EU ChEESE-2P project (Centre of Excellence for Exascale in Solid Earth, https://cheese2.eu/), which funded part of this project under grant agreement No 101093038.
Davies, G., Griffin, J., Løvholt, F., Glimsdal, S., Harbitz, C., Thio, H. K., ... & Baptista, M. A. (2018). A global probabilistic tsunami hazard assessment from earthquake sources. Geological Society of London. [doi: 10.1144/SP456.5].
How to cite: Cascone, V. and the GTM-PTHA Working Group: Towards the Global Tsunami Model Probabilistic Tsunami Hazard Analysis (GTM-PTHA) tool , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20928, https://doi.org/10.5194/egusphere-egu26-20928, 2026.
Shared virtual access services and interoperable tools can significantly improve the effectiveness, reliability, and resilience of tsunami early warning systems at both regional and global scales.
Here, we present the rationale behind the Tsunami Service Provider InterOperability Tool (TSP-IOT) running prototype, that is being developed at the moment to support Tsunami Early Warning operations in the NEAM (North-Eastern Atlantic, the Mediterranean and Connected Seas) region through virtual access (VA) to an integrated web-based platform. The activity is fundamental to improving interoperability among warning centres, enabling more effective information exchange and coordinated response during tsunami events.
The system incorporates tools that enable real-time data exchange, including sea-level state information, provided by Sea Level Station Monitoring Facilities (e.g. UNESCO-IOC SLSMF; https://www.ioc-sealevelmonitoring.org/), tsunami warning messages, and enhanced operational products, such as alert levels and tsunami travel time maps. These capabilities allow Tsunami Service Providers (TSPs) to access consistent, up-to-date information during both routine operations and acute event processing. In its final version, TSP-IOT will provide access to a common database that includes earthquake parameters, bathymetric data sets, pre-computed tsunami scenarios, and finite fault models, ensuring harmonized inputs for tsunami analysis and forecasting.
By adopting shared services and standardized interfaces, TSP-IOT supports greater interoperability and consistency among TSPs, reducing discrepancies in warning products and facilitating cross-centre collaboration. Additionally, the tool enhances the overall robustness of tsunami early warning systems by increasing redundancy and providing fallback solutions in case of partial system failures or high operational loads during emergencies.
The development and enhancement of TSP-IOT is the result of a collaborative effort involving the five TSPs of the ICG/NEAMTWS (Intergovernmental Coordination Group for the Tsunami Early Warning and Mitigation System in the North-Eastern Atlantic, the Mediterranean and Connected Seas) of UNESCO-IOC, that is CAT-INGV (Italy), HLNTWC-NOA (Greece), KOERI (Türkiye), CENALT (France), and IPMA (Portugal). All of the activities are carried out within the framework of the EPOS ON European Project (https://www.epos-eu.org/on), which aims, among other objectives, to contribute to tackling societal challenges and make a step forward in defining concrete actions through which EPOS may provide added value for society. In addition; TSP-IOT is provided via the EPOS Integrated Core Services portal, as part of the Tsunami Thematic Core Service (TSC Tsunami).
How to cite: Romano, F., Kalligeris, N., Cambaz, M. D., Lorito, S., Vitiello, L., Charalampakis, M., Bruni, S., Piatanesi, A., Hébert, H., Omira, R., Vermaere, S., Turhan, F., Ergün, T., and Özel, N. M.: The Tsunami Service Provider InterOperability Tool (TSP-IOT) for the NEAM region, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20141, https://doi.org/10.5194/egusphere-egu26-20141, 2026.
The growth of urbanisation in Mediterranean coastal areas, along with the development of tourist infrastructure and high-impact industrial facilities (R.I.R.), escalates the threat of marine hazards, including tsunamis for coastal populations.
In this context, tsunami risk can be mitigated by strengthening early warning systems, as well as preparedness and response strategies at the local community level. The Tsunami Ready programme, promoted by UNESCO, aims to enhance the knowledge, awareness and response capacity of coastal communities that voluntarily join the initiative, through the achievement of twelve indicators.
This is the first study to conduct an ex‑ante assessment of tsunami‑risk information needs in Italian coastal municipalities, focusing on those currently enrolled in the. The objective is to analyze the population’s level of awareness, risk perception and preparedness with respect to tsunami risk.
To assess these aspects, a structured questionnaire, developed as part of the CoastWAVE project promoted by UNESCO-IOC and funded by European DG-ECHO funds, was used. The questionnaire was administered to a sample of residents stratified by age, gender and education level representative of coastal communities to make the survey statistically robust. A total of 303 interviews were collected in the individual coastal municipalities involved in the development of the Tsunami Ready programme, considering two coastal municipalities to the north and two to the south of the target municipality.
The ongoing study aims to conduct a deep analysis of issues related to the population’s knowledge of marine hazards, trust in warning systems, sources of information used, level of preparedness in response to a potential alert, and the expectations placed on the institutions responsible for risk management. All these elements were brought together in a multi‑hazard survey tool.
The expected results will allow us to identify the main information gaps and communication weaknesses and provide operational guidance for more effective and context‑appropriate risk communication strategies, in line with the Tsunami Ready programme. The study will also produce recommendations to improve the messages and tools used by early warning and marine‑risk mitigation systems in the municipalities involved. From a European perspective, this work is relevant for UNESCO both for its methodological approach and for the use of a shared survey instrument that can be replicated in different coastal communities.
How to cite: Cugliari, L., Brizuela, B., Filosa, S., and Amato, A.: Social impact, risk perception and tsunami knowledge in communities participating in the Tsunami Ready programme., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21925, https://doi.org/10.5194/egusphere-egu26-21925, 2026.
