Given the complexity of earthquake-related hazards and their impact on different systems, diverse seismic hazard and risk models are needed at multiple spatial and temporal scales, relying on multi-disciplinary data and requiring testing and validation of all components to ensure effective mitigation.
From the real-time integration of multi-parametric observations is expected the major contribution to the development of operational time-Dependent Assessment of Seismic Hazard (t-DASH) systems, suitable for supporting decision makers with continuously updated seismic hazard scenarios. A very preliminary step in this direction is the identification of those parameters (seismological, chemical, physical, etc.) whose space-time dynamics and/or anomalous variations can be, to some extent, associated with the complex process of preparation of major earthquakes.
This session includes studies on various aspects of seismic risk research and assessment, ground and satellite-based data analysis and methods, within the t-DASH and Short-term Earthquakes Forecast perspectives:
- Development of physical and statistical models (including AI and machine learning) for hazard, exposure and vulnerability;
- Studies on time-dependent seismic hazard and risk assessments
- Development of systems providing pre- and post-event information, together with early warning and alert tools for effective emergency management;
- Earthquake cascading hazards (e.g. landslides and tsunamis) and multi-risk scenarios development;
- Social vulnerability assessment, along with advances in citizen-science, communication, governance and risk awareness research.
- Studies devoted to the description of genetic models of earthquake’s precursory phenomena
- Infrastructures devoted to maintain and further develop our present observational capabilities of earthquake-related phenomena, also contributing to building a global multi-parametric EarthQuakes Observing System (EQuOS) to complement the existing GEOSS initiatives.
Orals: Wed, 6 May, 08:30–12:30 | Room 1.15/16
The extraction of reliable seismic anomalies for searching earthquake precursors remains a challenging problem in understanding earthquake preparation processes. We address this through frequency-domain validation of lithosphere-coversphere-atmosphere-ionosphere (LCAI) coupling using the 2023 Turkey earthquake doublet (Mw 7.8, Mw 7.5) as a case study. By adding frequency criteria to conventional deviation-space-time (DST) analysis, our Deviation-Space-Time-Frequency (DSTF) framework requires the potential anomalies to simultaneously satisfy four rigorous criteria such as, (D): robust anomaly detection with anomaly magnitude exceeding ±1.4σ from the 15-day rolling baseline, (S): anomalies must align with geosphere-specific manifestation zones scaling as ρLC = 10(0.433M-0.39) km (lithosphere/coversphere), ρA = 10(0.433M+0.20) km (atmosphere), and ρI = 10(0.433M+0.54) km (ionosphere), (T): quasi-synchronous activation across geospheres with physically plausible propagation delays and (F): band-specific power enhancement (+3 dB in 2–10-day pre-seismic band; +6 dB in 0.2–5 mHz co-seismic band) with cross-layer coherence C ≥ 0.5, physically consistent phase lags, and transient nonstationary dynamics. Integrating multiple parameters across multiple geosphere’s microwave brightness temperature (MBT), surface latent heat flux (SLHF), outgoing longwave radiation (OLR), total electron content (TEC), and Swarm electron density/temperature we demonstrate systematic vertical coupling under geomagnetically quiet conditions (Dst > -30 nT, Kp < 4, F10.7 < 160 SFU). Wavelet coherence analysis reveals SLHF leads TEC by 2.5 ± 0.3 days (C = 0.71) and OLR by 1.2 ± 0.2 days (C = 0.61) during the pre-seismic phase. Co-seismic coupling exhibits elevated MBT-TEC coherence (C = 0.70–0.85) on February 6, distinguishing impulsive seismic forcing from gradual multi-day atmospheric buildup. The DSTF framework achieves 89% true positive rate with 8% false alarms (F-score = 0.90). This quantitative validation transforms LCAI from conceptual model to testable hypothesis with reproducible detection criteria. The integration of seismological, atmospheric, and electromagnetic observations under long-term analysis conditions contributes to advancing future multi-parametric monitoring infrastructures and better understanding of inherent mechanisms underlying earthquake precursory phenomena.
How to cite: Rasheed, R.: LCAI Multi-Parameter Analysis of the 2023 Turkey Doublet Earthquake for Enhanced Anomaly Extraction using Deviation-Space-Time-Frequency (DSTF) Criterion, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-482, https://doi.org/10.5194/egusphere-egu26-482, 2026.
Understanding the processes occurring before earthquakes constitutes one of the fundamental challenges in earthquake sciences due to the complex and heterogeneous nature of crustal deformation in the earthquake preparation stage. Many geochemical worldwide observations have indicated that precursory anomalies prior to earthquakes may exist. Hydrogeochemical changes observed in spring waters are regarded as sensitive indicators of subsurface processes associated with stress accumulation and fluid migration in seismically active regions. This study aims to investigate hydrogeochemical anomalies in spring waters preceding earthquakes by distinguishing tectonically driven signals from seasonal and meteorological effects using rainfall data. Within this framework, hydrogeochemical parameters covering periods of 9 to 15 months were obtained from commercially bottled water samples from the Marmara Region and the Aegean Extensional Province (AEP) in western Türkiye. In this study, two distinct moderate (Mw ~5.0) earthquakes on the North Anatolian Fault Zone and one Mw 5.0 on the submerged section of the Menderes Fault Zone in the AEP were monitored using data from five distinct spring water sites. To this end, collected spring waters’ electrical conductivity (EC) and major ion concentrations (Cl⁻, SO₄²⁻, Na⁺, K⁺, Mg²⁺, Ca²⁺) have been measured. The results suggest that anomalies exist at least 30 days in two spring waters before moderate earthquakes. However, no reliable anomaly was observed at some other spring water sites. This variability may be caused by the distance of these stations from fault zones and/or these spring waters are located on different tectonic blocks where pre-earthquake strain accumulation could not be transferred effectively to the adjacent blocks. Therefore, the effectiveness of hydrogeochemical monitoring appears to be strongly controlled by the structural connectivity between the spring system and the earthquake epicentre. These observations illuminate the importance of examining the relationship between hydrogeochemical variations observed in spring waters and pre-earthquake processes for their potential use as earthquake precursors. These findings suggest that future monitoring strategies incorporating denser spatial coverage, longer observation periods, and multi-parameter datasets are essential to better constrain the role of fault proximity and tectonic block configuration in controlling the detectability of pre-earthquake hydrogeochemical anomalies.
How to cite: Saygın, M. N. and Yakupoğlu, N.: Pre-earthquake geochemical anomalies in spring waters: site-dependent responses from western Türkiye, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7084, https://doi.org/10.5194/egusphere-egu26-7084, 2026.
The time series of the total electron content (TEC) extracted from the global ionosphere map (GIM) is useful to detect seismo-ionospheric anomalies at a certain region. When the detected anomalies are similar to those repeatedly appearing before large earthquakes in the same region, it might be considered temporal SIPs (seismo-ionospheric precursors) being observed. To discriminate the possible SIPs from global effects (such as solar disturbances, magnetic storms, etc.), a global search on anomalies of the GIM TEC is ideal to be employed. The spatial analysis simultaneously detects anomalies similar to the temporal SIP at each lattice of GIM and finds the distribution or pattern of the detected anomalies of the globe. When the detected anomalies specifically and continuously appear specifically near the monitoring region, we can declare spatial SIPs of the GIM TEC being observed. The distance between northern and southern crests of equatorial ionization anomaly (EIA) in GIM TEC along the earthquake longitude can be used to estimate electric fields associated with the observed SIPs. Meanwhile, radio occultation (RO) observations of FORMOSAT-3/COSMIC (F3C) satellites are useful to examine the vertical electron density structures. Results show that GIM TEC and the electron density at the F2-peak, NmF2, of F3C/RO profiles significantly increase specifically over the epicenter 3-4 days before the quake, which suggests SIPs of the Tohoku earthquake being detected. The EIA crests poleward motion and the F3C RO electron density profiles uplift indicate that the eastward electric fields have been enhanced during the SIP days.
How to cite: Liu, J.-Y. (., Chang, F.-Y., Wu, T.-Y., and Chen, Y.-I.: A 15-year revisit on seismo-ionospheric precursors associated with the 11 March 2011 M9.0 Tohoku Earthquake observed by the global ionosphere map of total electron content and FORMOSAT-3/COSMIC of electron density profiles, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18469, https://doi.org/10.5194/egusphere-egu26-18469, 2026.
The Mexico City conurbation, hosting more than 20 million inhabitants, is exposed to significant geological hazards due to its location within the Trans-Mexican Volcanic Belt and the ongoing subduction of the Cocos Plate beneath the North American Plate. In addition to regional volcanic and tectonic activity, intense groundwater extraction has induced land subsidence and surface fracturing, exacerbating seismic risk and damage to critical urban infrastructure. Recent shallow microseismic events (<4.0 Mw) recorded in May and December 2023, with epicenters at depths of 1–2 km in the western sector of the city, highlighted the need for improved characterization of poorly known active or reactivated faults beneath densely urbanized areas. This contribution presents an integrated application of two complementary geophysical methodologies - magnetotellurics (MT) and two-dimensional electrical resistivity tomography (ERT-2D) - aimed at multiscale subsurface characterization in Mexico City. Deep MT surveys were designed to image electrical resistivity structures down to 2–3 km depth along one profile crossing the urban area, providing insight into regional fault systems and lithological contrasts potentially associated with earthquake generation. This MT profile demonstrates good data quality using robust impedance estimation and shows strong correlation with lithological information from deep boreholes drilled after the 1985 Mw 8.1 earthquake, validating the methodology for urban hazard studies. At the local scale, ERT-2D surveys were implemented to investigate an E–W oriented surface discontinuity exceeding 800 m in length, associated with recent microseismicity and severe infrastructure damage. Two orthogonal ERT profiles, acquired using a dipole–dipole array despite significant urban noise, resolved subsurface structures to depths of ~80–90 m. Inverted resistivity models reveal a heterogeneous shallow subsurface, showing low-resistivity saturated horizons, intermediate resistivity unconsolidated volcanic and sedimentary units, and high-resistivity zones interpreted as massive rocks or weak, unconsolidated tuffs. The combined MT–ERT approach demonstrates the value of integrating deep and shallow geophysical imaging to identify fragile geological structures in complex urban environments, providing a scientific basis for seismic hazard assessment, urban planning, and civil protection strategies in Mexico City.
How to cite: Arango-Galvan, C., Chavez-Segura, R. E., Castro-Soto, C. D., Ruiz-Aguilar, D., Vásquez-Serrano, A., Arce-Saldaña, J. L., and Ramirez-Serrato, N.: From Basin to Block: Integrated Magnetotelluric and Electrical Resistivity Imaging of Active Structures Beneath Mexico City, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14083, https://doi.org/10.5194/egusphere-egu26-14083, 2026.
Robust Satellite Techniques have been applied to the analysis of long-term satellite TIR (Thermal InfraRed) radiances to identify those anomalous transients (in the spatial/temporal domain) possibly associated with the occurrence of major earthquakes. A possible limitation associated to the used RETIRA (Robust Estimator of TIR Anomalies) index is related to the spatial distribution over the scene of meteorological clouds which affect the computation of the average thermal background that is used to remove those, large-scale temperature variations, due to warm/cold fronts and or anticipation/delay of seasonal behaviors (e.g. Aliano et al., 2008). In order to take into account such possible effects, also simplifying the process of thermal anomalies identification, a new index RETIRSA (Robust Estimator of TIR Slope Anomalies) has been introduced, which allows for taking into account possible large-scale meteorological forcing, without the need to estimate ground thermal conditions at the large scale. Such an index allows for investigating the “nocturnal heating” effect - already proposed by Bleier et al. (2009) as a potential precursor of major earthquakes – by an RST-based approach. In this work, the known ability of the RST methodology to discriminate anomalous TIR transients possibly related to seismic events from those TIR variations related to other causes (e.g. meteorological) has been verified by comparing previous results based on the RETIRA index with those achievable by using the new RETIRSA index. Preliminary results of such a comparison over a long (June 2004 - December 2014) time-series of MSG/SEVIRI TIR observations over Italy will be presented
How to cite: Tramutoli, V., Colonna, R., Filizzola, C., genzano, N., Lisi, M., Mancusi, I., Nayak, K., and Pietrapertosa, C.: Moving from the RETIRA to the RETIRSA index in the application of Robust Satellite Techniques to short-term seismic hazard forecast: the case of the Italian region, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20336, https://doi.org/10.5194/egusphere-egu26-20336, 2026.
This study aims to understand the physical connection between the Lithospheric-Atmospheric-Ionospheric Coupling (LAIC) concept, defined by pre-earthquake anomalies, and a macroscopic one, using an AI-driven, multi-scope approach.
Currently, earthquake precursor information is divided into two main categories: microscopic (detectable by ground- and satellite-based instruments) and macroscopic (detectable by human senses or direct observation). LAIC relies solely on microscopic observations for analysis. In the broader context, macroscopic precursors are physical, biological, or atmospheric phenomena that can be observed by the human senses or basic instruments without requiring complex laboratory analysis. These "anomalies" often occur during the earthquake preparation stage, when tectonic stress has reached a critical level. Very often, the macroscopic anomalies have been met with scientific skepticism, even though these reports are often rooted in historical accounts. In this study, macroscopic information has been used only as a marker of the physical phenomenon, without quantification.
We have analyzed information on the top events in Europe, particularly in the Mediterranean and Alpine regions, which provide some of the most scientifically rigorous documentation of the "Precursor Chain” in Europe. For example, (1) L’Aquila, Italy (2009) – has shown biogeochemical & geodetic synergy, and this event is the modern benchmark for linking radon outgassing with biological responses and satellite-based ground monitoring. (2) Friuli, Italy (1976) – has revealed electromagnetic & luminous synergy, because the Alpine environment of Northern Italy provided a unique case of "rock-to-atmosphere" electrical coupling. (3) Izmit, Turkey (1999) – has revealed geochemical & biological synergy, because the North Anatolian Fault (NAF), though transcontinental, exhibits many European seismic characteristics, including high-density geochemical shifts. (4) Messina, Italy (1908) – has revealed hydrological & atmospheric synergy, and, as one of the most destructive events in European history, this quake was preceded by classic "Dilatancy-Diffusion" indicators. (5) Athens, Greece (1999) – has shown ionospheric & satellite thermal synergy, as Greece sits atop a complex subduction and transform system where atmospheric coupling is frequently observed. (6) Umbria-Marche, Italy (1997) – has shown foreshock & hydrological synergy, along with the Colfiorito sequence, which provided deep insights into how fluids move through the Apennine limestone.
In many cases, our out-of-place findings are entirely unexpected, showing that modern instruments, human and animal observations, and some direct measurements were collected within close timeframes, with re-occurrences of anomalies with similar patterns and time-lags across the same and different seismo-tectonic settings. That might indicate that common multi-parameter coupling mechanisms, similar to LAIC, are in place, and validating them is the next step in this exploration to deepen our understanding of the nature and complexity of pre-earthquake phenomena.
How to cite: Ouzounov, D. and Vallianatos, F.: Understanding the synergy between LAIC and macroscopic pre-earthquake anomalies, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15458, https://doi.org/10.5194/egusphere-egu26-15458, 2026.
Understanding the spatiotemporal evolution of ground deformation preceding earthquakes is a key objective in contemporary seismotectonic research, as such deformation may reflect preparatory processes within the crust. Possibly preceding an earthquake event, variations in deformation rates and patterns prior to seismic rupture have been reported in different tectonic settings and are commonly interpreted in terms of stress accumulation, aseismic slip, or fluid-related processes along active faults. Satellite-based Interferometric Synthetic Aperture Radar (InSAR), particularly when exploited through long and spatially dense deformation time series, offers a unique opportunity to retrospectively evaluate these pre-seismic signals at wide-area scale.
In this context, this study highlights the potential of the European Ground Motion Service (EGMS) Ortho products for investigating pre-earthquake deformation behaviour. As an illustrative example, the Mw 6.3 Thessaly earthquake (central Greece, March 2021) is analysed using the first EGMS Ortho data release, covering the period from January 2016 to December 2021. The dataset provides vertical (Up–Down) and horizontal (East–West) deformation time series on a regular 100 m grid, enabling a homogeneous spatial assessment of deformation patterns.
Our results show that the spatial distribution of linear deformation velocities derived from two distinct temporal phases. The first phase (January 2016–March 2020) represents the long-term background behaviour and is characterised by overall stability and the absence of coherent deformation anomalies. In contrast, the second phase, covering the year preceding the earthquake (March 2020–March 2021), reveals a clearly distinguishable and spatially coherent deformation pattern concentrated around the epicentral area, indicating a marked departure from background conditions. Moreover, the resulting acceleration fields show a pronounced anomaly centred near the epicentre, particularly evident in the vertical (Up–Down) component. The horizontal (East–West) acceleration pattern is less pronounced but exhibits a block-like spatial organisation, characterised by sign changes across adjacent domains. This block behaviour is more evident in the East–West direction and comparatively weaker in the vertical component.
Overall, this example demonstrates that EGMS Ortho products can effectively capture subtle yet spatially structured changes in deformation behaviour prior to seismic events. These results underscore the value of EGMS as an open, continental-scale resource for systematic exploration of pre-seismic deformation patterns and their potential contribution to seismic hazard research.
How to cite: Eskandari, R., Scaioni, M., and Genzano, N.: On the potential of InSAR EGMS data for the Analysis of Pre-Seismic Deformations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22520, https://doi.org/10.5194/egusphere-egu26-22520, 2026.
Let us focus on a specific question that may has an ability of answering to build an efficient method that may give us possibility for producing the most effectively resistant and undestroyable buildings even if they get the most significant seismic activities. That question may be set up by discussions about possible expansions through topologically analytic mechanisms involving connective and transitive processes among significant seismic activities, thermodynamics, and electromagnetism; unfortunately, the expansions must be available of topological processes between thermodynamics and electromagnetism as the first stage, this stage takes one to build the thermodynamical electromagnetism as second stage. A unification is given in classical seismology as common between the natural earthquake related seismic activities and thermodynamic events without exact functional relations of these events; unfortunately, this unification is almost well-posed for earthquakes of less than 5.9 Richter magnitude, but it is ill-posed for earthquakes of equal and/or greater than 5.9 Richter magnitude1, beside this, the well-posed unification is possible between significant seismic activities and electromagnetism2, 3. The unification gives some results of those three events, these results may have significant roles in earthquake safe building construction engineering.
Principle 1: The electrical charge has non-zero volume and non-zero surface even if it is a free charge, an induced charge, and/or an ionic charge; therefore, there always be naturally correlation for electrical charge density through the kinetic energy with both heat and pressure.
The principle 1 gives the basic rules of transitions among heat, pressure, and electromagnetic interactions. The electromagnetic field distribution gains major effects at places near the activity domain than mechanical effects depending mechanical displacements and fluctuations during the most significant naturally seismic activities. The electromagnetically constitutive parameters change of everything in the active zone, significantly as consequences of those majorant effects; therefore, electromagnetic parameters have majorant effects rather than mechanically constitutive parameters in geophysical modeling and/or geotechnical modeling during the most significant natural seismic activities. That result plays the important and principal role in engineering for constructing, possibly the effectively resistant and undestroyable buildings during the most significant seismic activities. The earthquake zones spread forward to new seismic activities from passed activities; therefore, that result keeps its importance at all the geographic domains even if it is far away from the activity domains, but they are in the major geographic domain of the activity.
1https://doi.org/10.5194/egusphere-egu2020-21121.
2https://doi.org/10.1109/APS.1996.549734.
4ISBN 951-22-5474-3, ISSN 1456-632X.
How to cite: Sengor, T.: The Modifying Effects of Significant Seismic Activities on the Electromagnetically Constitutive Parameters: On the Global Principles for the Effectively Resistant and Undestroyable Building Engineering During Significant Seismic Activities, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1235, https://doi.org/10.5194/egusphere-egu26-1235, 2026.
The ionosphere is one of the most important layers of the atmosphere, and for its electric properties is used in communication and navigation services. In addition to being influenced by geomagnetic and solar activity, in recent decades, it has been observed that the ionosphere may also exhibit variability due to effects caused by events of terrestrial origin, such as earthquakes. However, objectively identifying when a variation is an anomaly related to an earthquake remains a challenge.
This study presents a methodology based on machine learning to automatically detect the relationship between this type of irregularity and earthquakes. For this purpose, electron density (Ne) data recorded by the European Space Agency’s Swarm satellite constellation are used. Following the previously published NeAD anomaly detection algorithm, a combination of machine learning techniques is applied to group the detected anomalies according to their characteristics, to correct and automatically distinguishing the anomalies truly associated with the earthquake under study.
As a case study, the Mw 7.6 earthquake that occurred in Mexico on September 19, 2022, is presented. Five types of anomalies were distinguished, showing that duration and intensity are the most important factors for differentiating them.
The results suggest that one of the five anomaly groups can be associated exclusively with processes related to the main earthquake, while the other four groups are linked to other phenomena such as other minor earthquakes, tropical cyclones, or volcanic eruptions.
This automated approach opens new possibilities for improving the classification of ionospheric anomalies and understanding how the lithosphere, atmosphere, and ionosphere interact with each other in the dynamics of our planet.
How to cite: Varela-Mendez, A., Arquero-Campuzano, S., Migoya-Orué, Y., De Santis, A., and Herraiz-Sarachaga, M.: Automatic classification of ionospheric anomalies potentially linked to earthquake occurrence using machine learning techniques, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21255, https://doi.org/10.5194/egusphere-egu26-21255, 2026.
Large recent earthquakes offer an opportunity to investigate the seismic preparatory phase from a geosystemic, multiparametric perspective, integrating lithospheric, atmospheric and ionospheric observations within the Dobrovolsky region. Using the Mw 7.1 Wushi (Xinjiang, 22 January 2024) and Mw 7.7 Myanmar (Sagaing Fault, 28 March 2025) earthquakes as natural laboratories, we jointly analyze medium‑term lithospheric signals (multi‑year) and short‑term atmospheric/ionospheric anomalies (days to months before the mainshocks). In the Wushi case, about 60 anomalies are detected: lithospheric changes persist for about one year, whereas atmospheric and ionospheric perturbations cluster within the last three months, including outgoing longwave radiation anomalies from four days before to four days after the mainshock, consistent with imminent‑stage precursors. For the Myanmar event, eleven classes of candidate precursors exhibit a characteristic sigmoid evolution in time, typical of a critical system approaching failure, and their space–time concentration supports the lithosphere–atmosphere–ionosphere coupling (LAIC) framework. A focused analysis of Swarm satellite magnetic data over the Myanmar Dobrovolsky area reveals Y‑component anomalies on 22 of 85 half‑orbits up to eight days before the earthquake; empirical magnitude estimates based on anomaly–epicentre distance yield M ≈ 7.2, in reasonable agreement with the observed M 7.7, while anomaly “energy” values cluster within a narrow range, suggesting a possible characteristic signature of seismic‑related disturbances. Overall, these case studies indicate that (i) multi‑scale, multi‑parameter anomalies often accelerate following exponential or sigmoid trends towards the mainshock, (ii) combined ground‑ and satellite‑based observations can help constrain the location of an impending event, and (iii) satellite magnetic and radiative anomalies may provide valuable input for short‑term forecasting schemes, although systematic validation on larger datasets is required before operational use.
The present work has been funded by the Italian Ministry of University and Research (Pianeta Dinamico - Unitary Project) and ASI (Space It Up and LIMADOU EXPO Projects).
How to cite: Cianchini, G., De Santis, A., Campuzano, S. A., D'Arcangelo, S., De Caro, M., Orlando, M., Perrone, L., Sabbagh, D., Soldani, M., Zhang, X., Xiong, P., Alimoradi, H., Rahimi, H., and Mendez, A. V.: Geosystemic signatures of the seismic preparatory phase: Insights from the 2024 Wushi and 2025 Myanmar Earthquakes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12919, https://doi.org/10.5194/egusphere-egu26-12919, 2026.
DEVELOPMENT OF A BUILDING EXPOSURE MODEL BASED ON UAV AND 360 IMAGERY FOR SEISMIC RISK ASSESSMENT IN NEJAPA (EL SALVADOR)
We develop an exposure and seismic vulnerability database for seismic risk applications in the city centre of Nejapa (El Salvador). This area, as most of the country, is characterised by a very limited availability of open cadastral data, street-level and aerial imagery and LiDAR point clouds.
We carry out an on-site campaign integrating aerial street-level images. Aerial images are captured in a drone flight and are used to identify building footprints and roof properties. Façade photos are obtained with a 360º camera during a walk-down survey, provindng information about the number of storeys and wall materials. These data are combined to generate a 3D model of the city centre. Next, buildings are identified, characterised, and assigned a vulnerability and fragility models.
This database is used to estimate seismic risk for a simulated Mw 6.7 earthquake on the Guaycume fault near the city. Results show that 71% of buildings would suffer complete damage and 68% of the population would be homeless, with losses exceeding USD 15 million.
A dashboard integrating these data are set up to help disseminating the results of the study into stakeholders and decision makers.
How to cite: Gaspar-Escribano, J. M., Torres, Y., Martín, J., Staller, A., and Martínez-Cuevas, S.: Development of a building exposure model based on UAV and 360 imagery for seismic risk assessment in Nejapa (El Salvador) , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19206, https://doi.org/10.5194/egusphere-egu26-19206, 2026.
The application of displacement time series derived from SAR Interferometry (InSAR) for tectonic strain estimation is constrained by the requirement that ground motion occurs predominantly within the east–vertical plane. Indeed, the near-polar orbit of most currently available SAR satellites makes the technique weakly sensitive to displacements in the northward direction. Since a single InSAR observation captures only the line-of-sight (LOS) projection of the displacement, data acquired from multiple viewing geometries, including at least one ascending and one descending, are required to approximately retrieve the east and vertical displacement components. To make this possible, the product between the northward displacement component and the coefficient that determines its contribution to the LOS projection is assumed to be zero. While this assumption may be acceptable when dealing with phenomena characterized by dominant east–up motion, in general, the accuracy of the estimates is suboptimal.
Under these conditions, a-priori information on the displacement direction can improve the solution. In [1], a new method, the strapdown approach, was introduced. Starting from a-priori knowledge of the displacement direction, and particularly by imposing that the vector lies within a plane, this method allows the estimation of a locally two-dimensional but globally three-dimensional solution. The possibility to vary the plane’s orientation, together with the use of an appropriate stochastic model for both the InSAR observations and the angles defining the plane, enables the method to produce a spatially variable output in terms of both direction and accuracy.
In this work, we apply the strapdown approach to highlight tectonic strain accumulation in southern Italy, specifically in the Irpinia area, characterized by high seismic hazard. We follow the one-dimensional procedure defined in [2], which focuses on detecting signs of tectonic strain accumulation by analyzing velocity variations along directions of interest, defined a-priori based on the tectonic knowledge of the area. In the absence of concomitant and spatially widespread phenomena (e.g., subsidence), these directions coincide with those along which the largest variations of velocity are expected. The one-dimensional procedure, originally applied using GNSS data, is therefore well-suited for use in combination with the strapdown approach when InSAR data are adopted as input. In this work, the proposed combined methodology is applied using time series provided by the European Ground Motion Service, considering the directions of interest initially defined in [2], which reflect the extensional tectonic regime perpendicular to the Apennine chain. Preliminary results highlight the potential of combining the strapdown approach with one-dimensional analyses of tectonic strains along known directions for seismic hazard monitoring.
[1] Brouwer, Wietske S., and Ramon Hanssen. "Estimating three-dimensional displacements with InSAR: The strapdown approach." (2023).
[2] Crespi, M., Kossobokov, V., Panza, G. F., & Peresan, A. (2020). Space-time precursory features within ground velocities and seismicity in North-Central Italy. Pure and Applied Geophysics, 177(1), 369-386.
How to cite: Giaccio, L., Belloni, V., Ravanelli, R., Lăpădat, A. M., van Leijen, F., Hanssen, R., and Crespi, M.: Combining the strapdown approach for InSAR data with one-dimensional tectonic strain analysis in the Irpinia region, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21116, https://doi.org/10.5194/egusphere-egu26-21116, 2026.
The performances of Morocco’s seismic hazard forecasts demonstrated severe shortcomings at the occurrence of the 2023 Al-Haouz earthquake (MW 6.8), evidencing the need for improved data and approaches. This study expands the Neo-Deterministic Seismic Hazard Assessment (NDSHA) to the use of the design magnitude (Mdesign) definition. We verified the approach through testing the performance of ground shaking maps computed for bedrock site conditions with respect to the 2023 Al-Haouz (MW 6.8) and the 2004 Al-Hoceima earthquakes (MW 6.4).
Using three earthquake catalogues (all truncated to 2012), we generated NDSHA ground shaking maps. To account for the Mdesign concept, earthquakes magnitudes were incremented, according to the Panza-Rugarli law, by γEMσM=0.5 (γEM=2) and 0.7 (γEM=2.8) respectively, and the predicted peak ground accelerations were compared to recorded data. The results show that the Morocco catalogue with Mdesign increment values could significantly improve the recorded ground shaking forecast for the 2023 earthquake.
The analysis demonstrates that NDSHA maps accounting for Mdesign may significantly reduce underprediction biases, especially for strong intraplate earthquakes, where the available information about past seismicity may well be incomplete and not representative of the seismogenetic potential of the region. We conclude that Mdesign is an essential prerequisite for reliable seismic hazard assessments, particularly in regions with sparse seismicity data, as it can enhance predictive capability and risk mitigation in Morocco and similar intraplate seismotectonic settings.
How to cite: Hassan, H. M., Peresan, A., ElGabry, M., Chourak, M., and Panza, G.: Improving Ground Motion Forecasting for the 2023 Al-Haouz and 2004 Al-Hoceima Earthquakes (Morocco) by using the Mdesign Concept, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18292, https://doi.org/10.5194/egusphere-egu26-18292, 2026.
In this study, we develop a deep-learning-based real-time prediction framework for ground motions and building responses from large earthquakes along the Nankai Trough, with focus on long-period (LP) ground motions (periods of 2–10 s). LP ground motions pose a serious hazard to modern society because they can shake strong high-rise buildings and the resulting damage. This study aim to rapidly predict ground motions and shaking in high-rise buildings at distant sites using near-source waveform observations.
Most machine-learning approaches to predicting LP ground motions have targeted intensity measures such as peak ground acceleration and response spectra. In contrast, Furumura and Oishi (2023) demonstrated that a time-series forecasting approach using a Temporal Convolutional Network (TCN) can predict LP ground-motion waveforms in distant plains in real time from near-source observations for shallow earthquakes off Tohoku. Building on this concept, this study aim to extend waveform-based prediction to Nankai Trough earthquakes and to predict shaking of high-rise buildings in distant plains.
The novelty of this study lies in two aspects. First, to accommodate the diversity of earthquakes along the Nankai Trough, including both shallow and deep events, we construct a TCN-Transformer model which improve arrival-time and waveform prediction across events with different apparent velocities. Second, for floor-by-floor shaking prediction from ground motions, we newly develop a TCN-PINN (Physics-Informed Neural Network) model that incorporates physics-based constraints derived from the equation of motions for governing building oscillation into loss function. This enabling physically plausible response predictions even with limited training data. Ground motions are first predicted using the TCN-Transformer model, and the results are then used as inputs to TCN-PINN models for each floor of the target building.
For the TCN-Transformer model, we trained and validated on 20 earthquakes of M5.0 or larger that occurred off the Kii Peninsula between 2008 and 2025. Waveforms recorded at the near-source F-net Fujigawa station (FUJF) were used to predict LP ground-motion waveforms at the MeSO-net Ginza station (GNZM) in the Kanto Plain, approximately 130 km away.
Next, we constructed a TCN-PINN model to predict building responses at three locations: B4F, the 13th floor, and the 21st floor, of the Central Government Building No. 2 (CG2), located 1.6 km from GNZM. This model was trained and validated using 25 earthquakes of M6 or larger that occurred off Tohoku between 2010 and 2014.
As a result, for the M6.5 earthquake on 1 April 2016 in the Nankai Trough region, the predictions successfully reproduced the arrival time, duration, and waveform envelope well. However, the overall waveform energy tended to be underestimated, indicating that future improvements is required for damage-assessment applications. For the CG2 responses, the model generally reproducing spectral-peak locations, such as predominant periods, whereas the response amplitudes were underestimated. To improve the prediction accuracy, future work will focus on refining the loss-function design to mitigate underestimation of the LP components, and will strengthen training by combining observed with synthetic scenario waveforms generated from seismic wave-propagation simulations.
How to cite: Kai, T. and Furumura, T.: Deep Learning Prediction of Long-Period Ground Motion and Building Shaking in Nankai Trough Earthquake, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9069, https://doi.org/10.5194/egusphere-egu26-9069, 2026.
Breakwaters are the critical coastal structures that protect the coastal and port areas from the devastating effects of sea waves, typhoons, and even tsunamis. Among them, Rubble Mound (RM) breakwaters are widely used due to their adaptability. However, following past major earthquakes, such as the 1995 Kobe (Japan), 1999 Kocaeli (Turkey), 2004 Indian Ocean, 2011 Great East Japan, and 2023 Kahramanmaraş (Turkey), it has been found that the stability of these structures depends not only on sea wave actions but also on seismic motions and the underlying seabed soils. As they are directly laid on marine sediments, they are vulnerable to seismic and liquefaction-induced damage. The deformation of seabed soils and breakwater components often results in settlement, lateral spreading, crest lowering, and, in severe cases, structural collapse. Such failures can significantly reduce protection against seismic and tsunami-induced wave overtopping. In seismically active coastal nations, they can greatly magnify the impact of subsequent tsunamis, turning localised failures into large-scale coastal disasters and associated socio-economic losses. Despite their global prevalence and critical role in coastal risk reduction, very limited research exists on countermeasures to enhance the seismic resilience of RM breakwaters. Thus, this study addresses this gap by experimentally investigating seismic failure mechanisms and developing innovative reinforcing techniques using 1g physical models, and then validating them through numerical modelling.
In the study, a prototype breakwater is scaled to a model scale. The conventional model consists of an RM breakwater resting on two layers of seabed (upper loose sand over lower dense sand) modelled and tested on a shake table under a sequence of earthquakes, including foreshocks (0.1g & 0.2g) and the mainshock (0.4g), in the form of sinusoidal waves at their base. Due to the liquefaction of the foundation soils beneath the breakwater and the maximum acceleration amplitude amplification at the base of the breakwater, the conventional model deformed and collapsed below mean sea level during the mainshock. To mitigate these effects, a reinforced configuration was developed, incorporating geogrid layers within the breakwater system and the interconnected geobags infilled with recycled concrete aggregates (RCA), as a replacement for conventional concrete armour units on the slope. RCAs are construction and demolition wastes; utilising them in place of concrete promotes the circular economy goals. Additionally, sheet piles were used in the seabed foundation to reduce lateral deformation during earthquakes. The effectiveness of the proposed countermeasure was assessed using parameters such as liquefaction potential, settlement, lateral displacement, and deformation patterns. Compared with the conventional model, the settlement of the reinforced breakwater was reduced by 62.7%, and lateral displacement was decreased by 60.3% during the mainshock. The model also effectively mitigated the potential for liquefaction by reducing excess pore pressure ratios and amplification ratios. The deformation patterns for the conventional and reinforced models are depicted in Figs. 1 and 2, respectively. Thus, the result demonstrated that the proposed technique significantly enhances seismic resilience and mitigation solutions for coastal infrastructure in earthquake and tsunami-prone regions.
How to cite: Pk, A. and Chaudhary, B.: Mitigation of Seismic-Induced Damage in Rubble Mound Breakwaters using Innovative Countermeasures , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12315, https://doi.org/10.5194/egusphere-egu26-12315, 2026.
The SMILE project explores the use of machine learning to generate updated building exposure layers by integrating remote sensing imagery, census data, and validated crowdsourced information. Crowdsourced data are collected through targeted initiatives involving trained students and citizens. To facilitate these activities, a web-based multimedia platform (https://smile.mi.imati.cnr.it) was developed to guide users through data collection, manage workflows, and store georeferenced information and images in a structured database, which currently includes survey forms on 4,100 buildings, mostly located in Northestern Italy.
A key goal of the study is to validate the collected data and assess their potential use to enhance existing building exposure datasets. Approximately the forms for about 400 buildings located in Udine, filled in by high school students via the platform, were reviewed by experts. Comparing expert-validated and student-collected data enabled identification of potential issues in survey design and allowed for a statistical assessment of data quality and reliability. The validation approach integrates rigorous statistical techniques, including summary statistics, cross-correlation analyses, and dissimilarity measures, with visualization methods to support the interpretation and communication of complex datasets.
We acknowledge the PRIN 2022 PNRR project SMILE “Statistical Machine Learning for Exposure development” (code P202247PK9, CUP B53D23029430001) within the European Union-NextGenerationEU program.
How to cite: Artese, M. T., Varini, E., Ciocca, G., Peresan, A., Piccoli, F., Rota, C., Kumar, R., and Scaini, C.: Validating Crowdsourced Building Data: A Statistical and Expert Approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17577, https://doi.org/10.5194/egusphere-egu26-17577, 2026.
Raising people’s disaster awareness is a prerequisite for enhancing their disaster-coping capacities. Although “disaster awareness” has long been a very common term in academic circles, disaster management communities, and even society at large, there still remains a notable lack of sufficient discussion regarding what this awareness of the general public specifically refers to, and how it can be concretely measured across different types of hazards and disasters, varied population groups, and diverse physical and socio-economic contexts. This gap is particularly acute in China. First, after reviewing the existing international understanding of the term of Public Disaster Awareness (PDA), this study newly defined this concept by drawing upon concepts of environmental awareness and environmental literacy in the field of environmental studies. Next, based on this new PDA definition, UNISDR’s terminology on public awareness of disaster, the authors’ extensive relevant research experience, and other valuable factors, this study proposed an education objective-oriented dimensional construct for PDA concept by fully incorporating UNESCO-UNEP’s classic understanding of the categories of environmental education objectives. Specifically, the proposed PDA dimensional construct comprises five specific dimensions: 1) disaster sensitivity and risk perception, 2) acquisition of disaster knowledge, 3) mastery of disaster-coping measures and skills, 4) attitudes and values, and 5) participation in disaster reduction. Subsequently, utilizing this novel PDA dimensional construct, the study developed several sets of disaster awareness measurement questionnaires that focus on people’s earthquake disasters awareness (EDA) to target different public groups in China: primary and high school students, their teachers, students’ parents, and the general public. Using these questionnaires and stratified sampling processes, the current EDA state and associated disaster education issues across several regions in China were surveyed over the past few years. Data analysis of high school students in Weinan, Shaanxi province revealed the following key findings. (i) Students’ overall EDA level was largely acceptable, but their performance in disaster sensitivity and local risk perception aspects was apparently unsatisfactory. (ii) Girls performed better than boys in attitudes, values, and participation, while boys were better in the knowledge dimension. (iii) As grade levels increased, students’ attitude and values, and participation became increasingly passive and indifferent. (iv) Extracurricular activities contributed much more to students’ EDA development than curricular education. (v) The EDA-building effects of different extracurricular activities varied; specifically, the overall effects of several activities were more significant than others, and each activity had its own distinct impact patterns across the five disaster awareness dimensions. Finally, based on these findings, education objective-specific policy recommendations for improving disaster education in local primary and high schools were provided. The novel construction of the PDA concept holds significant theoretical value for exploring both disaster awareness and disaster education. Furthermore, the central logic and specific strategies (e.g., approaches for PDA indicator development) that derived from measuring the seismic disaster awareness of China’s population have promising transferable practical implications for addressing similar issues regarding both other types of disasters and the disasters in other countries.
How to cite: Su, G., Qi, W., Zhang, T., Gao, Y., Sun, L., Wei, B., Pei, M., and Guo, X.: Public Disaster Awareness (PDA): Concept Construction and Case Measurement, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15615, https://doi.org/10.5194/egusphere-egu26-15615, 2026.
Accounting for the finite spatial extent of earthquake rupture is critical for effective regional Earthquake Early Warning (EEW), particularly for large events where point-source assumptions may fail. The Finite fault rupture Detector (FinDer) algorithm addresses this challenge by rapidly inferring the location, extent, and orientation of an ongoing earthquake fault rupture through comparison of the observed spatial distributions of high-frequency ground-motion amplitudes with pre-calculated templates derived from empirical ground motion models. Northeastern Italy, characterized by moderate-to-large seismicity primarily associated with active reverse and strike-slip faulting, represents a suitable test region for finite-fault-based EEW. We evaluate FinDer performance using a combination of real-time detections (MW < 4.5) and offline playback experiments (5.5 < MW < 6.7), acknowledging that real-time EEW timeliness is affected by telemetry latency in the current seismic station network. Results show rapid convergence toward stable event locations and magnitudes, while line-source orientation remains weakly constrained, especially for small magnitude events. Sensitivity analyses indicate that increasing station density improves the stability of source-parameter estimates, and that amplification factor-based adjustments for site effects reduce systematic biases in FinDer’s template-matching solutions. Lead times estimated from offline playback tests are also evaluated relative to macroseismic intensity thresholds corresponding to slight damage in unreinforced masonry buildings, with selected scenarios yielding non-negligible lead times. Overall, the results suggest that a properly configured FinDer-based EEW system, supported by real-time telemetry, could provide significant benefits for seismic-risk mitigation in Northeastern Italy. Nevertheless, template simplifications and the neglect of radiation-pattern effects remain major limitations, particularly for reliable strike estimation in smaller events (MW < 4.5).
How to cite: Du, F., Zuccolo, E., Parolai, S., Böse, M., and Lai, C. G.: Potential and Challenges of FinDer-Based Earthquake Early Warning in Northeastern Italy, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10240, https://doi.org/10.5194/egusphere-egu26-10240, 2026.
EEW is in operation in many places around the globe, but no country in Europe currently offers a public alert system despite significant seismic risk. Recently, the Swiss Seismological Service (SED) at ETH Zurich, in collaboration with local agencies, has rolled out public EEW systems across Central America using their internally developed algorithms and mobile phone application. The ETH-SED SeisComP EEW (ESE) system consists of two algorithms - the point source Virtual Seismologist (VS) and the Finite fault rupture detector (Finder). The mobile phone application relies on Firecloud messaging and Apple Push Notifications and is available for Android and iOS users. It has proven reliable to send low-latency alerts to several hundred of thousand users.
We are currently installing and testing the ESE system in Europe in countries where the earthquake hazard ranges from moderate (Switzerland-SED) to high (Greece-NOA, Romania-NIEP, Croatia-UniZG). Here, we present the developments undertaken over the last year in those countries and report on the algorithm performance and alert distribution for recent events. We discuss the remaining challenges and communication strategies towards public release.
This work has benefited from funding within the TRANSFORM² project, European Commission project number 101188365 (HORIZON-INFRA-2024-DEV-01-01 call); and from the Seconds Matter project, SNSF-MAPS project numbers IZ11Z0230881 and F-RO-CH-2024-0263.
How to cite: Planès, T., Clinton, J., Boese, M., Massin, F., Burgoa, B., Marmureanu, A., Anghel, M., Neagoe, C., Ene, D., Manea, E., Evangelidis, C., Boukouras, K., Zailac, K., Secanj, M., Stipcevic, J., and Dasovic, I.: Towards Public Earthquake Early Warning in Switzerland, Greece, Romania, and Croatia, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20711, https://doi.org/10.5194/egusphere-egu26-20711, 2026.
Posters on site: Wed, 6 May, 16:15–18:00 | Hall X3
In China, Yu et al. (2021) investigated the relationship between network connectivity and earthquakes using correlation coefficients between stations of multiple borehole strainmeter data and they reported that anomalies tended to increase 20 days before the earthquake. In Japan, 67 strain gauges have been installed, but the number is limited and there is a regional bias. Therefore, we decided to investigate the possibility of using the GNSS continuous observation system (GEONET) deployed by the Geospatial Information Authority of Japan (GSI) at approximately 1,300 locations throughout Japan to construct a pseudo-strain gauge consisting of four GEONET observation points to index the amount of crustal deformation. In this study, we will devise a pseudo-strainmeter using GNSS observation data and develop a method to accurately detect crustal deformation that is a precursor to M7-class earthquakes. Specifically, we analyze GNSS data from past M7-class damaging earthquakes, and investigate the effectiveness of the method for detecting earthquake precursor variations in strain with high accuracy from a case study analysis perspective. Assuming that pseudo-strain gauges exist at the diagonal intersections, we constructed an algorithm to detect anomalies in in-situ strain variation by determining the time variation of the correlation coefficient between strain and two orthogonal components at the diagonal intersections, and targeted the detection capability of earthquake related variation to the 2016 Kumamoto earthquake (M7.3). The area of analysis was the entire Kyushu region, and the spatio-temporal changes in the correlation coefficients of strain and network connectivity were investigated in detail. The results showed that the strain correlation coefficients of the N-S and E-W components at each pseudostrain station before and after the earthquake were closer to 1 the closer the stations were to the epicenter, and that the network coupling degree The increase in network coupling was confirmed at pseudo-strain stations within about 100 km of the epicenter. Seven days before the main shock, an increase in network coupling was confirmed in a linear region extending from the Hinagu-Futagawa fault zone, the epicenter of the foreshock and main shock, to Aso and Oita. Details will be reported at the time of the presentation.
How to cite: Hattori, K., Najima, Y., Yoshino, C., Noda, Y., and Fujinawa, Y.: New developments in crustal deformation research using pseudo-strain gauges with GNSS data; Test for the 2016 Kumamoto earthquake (M7.3), Japan, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19857, https://doi.org/10.5194/egusphere-egu26-19857, 2026.
Understanding how significant earthquakes prepare and initiate requires examining processes beyond tectonic loading alone. In this study, we integrate seismic, oceanic, atmospheric and ionospheric observations to investigate multi-parameter anomalies that systematically precede major earthquakes in diverse tectonic environments. Long-term seismic indicators, including seismicity pattern, reveal progressive fault locking and asperity development within rupture-prone zones. The lithospheric changes coincide with transient environmental perturbations such as sharp fluctuations in sea surface height and temperature, atmospheric pressure and temperature variability, ozone and cloud parameter anomalies and pronounced ionospheric total electron content (TEC) disturbances. The spatial overlap of these anomalies with regions of high co-seismic slip suggests that external environmental forcing, particularly transient oceanic loading and atmosphere–ionosphere coupling may amplify stresses on critically loaded fault segments. Our results highlight a consistent preparatory pattern characterized by long-term stress buildup, short-term seismic acceleration and synchronous environmental anomalies. This integrated framework underscores the importance of multi-domain monitoring systems and demonstrates the potential of coupled external–internal stress perturbations to contribute to rupture triggering in large earthquake-generating faults. By identifying cross-domain precursory signals, this approach enhances our capacity to recognize long-term and short-term indicators of impending large earthquakes, offering valuable insights for early-warning initiatives, improved hazard assessment and reducing societal risk in vulnerable regions.
How to cite: Tiwari, A., Tiwari, V. M., Mukherjee, B., Tiwari, J., and Gahalaut, V. K.: Integrated Multi-Parameter Precursory Signatures in the Preparation Phase of Large Earthquakes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1095, https://doi.org/10.5194/egusphere-egu26-1095, 2026.
In recent years, ionospheric disturbances related to earthquakes have been reported and are considered promising for short-term earthquake forecasting. However, ionospheric disturbances can also be caused by other factors, and their relationship with earthquakes is still not well understood.
In this study, we investigated the possibility to forecast short-term earthquakes using ionosonde data. We evaluated their earthquake precursory potential using Molchan's Error Diagram analysis. We also performed a statistical analysis of the ionospheric response to geomagnetic storms, a known source of ionospheric disturbances. In this analysis, we defined geomagnetic storms by Dst Index and classified into their occurrence time, magnitude, and season. We calculated the time period during which geomagnetic storms cause ionospheric anomalies. Based on these results, we removed the effects of geomagnetic storms and reevaluated the earthquake precursory potential.
Details will be shown in this presentation.
How to cite: Sasanuma, C., Song, R., Yoshino, C., Hattori, K., and Liu, J.-Y.: Assessment of Earthquake-related Ionospheric Disturbances Observed by Ionosonde, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8728, https://doi.org/10.5194/egusphere-egu26-8728, 2026.
Hydrogeochemical monitoring of groundwater is recognised as a powerful tool to investigate the preparation phases of earthquakes, particularly in tectonically active regions where fluid–rock interactions and structurally controlled fluid-flow systems may respond to crustal stress changes. However, the selection of suitable monitoring sites is a critical and often overlooked issue, as groundwater systems may display a relevant temporal variability or a limited resilience to seasonal forcing, that could mask potential seismo-hydrogeochemical signals. In this study, we propose and apply a three-step hydrogeochemical strategy designed to identify groundwater sites with the highest potential sensitivity to earthquake-related processes. Such approach was tested in the northern Marche Region (central-eastern Italy), being characterized by a moderate-to-high seismic activity in past and recent years and includes: (i) large-scale characterization of groundwater chemistry and dissolved gases, aimed at identifying dominant geochemical processes and those sites potentially influenced by deep fluid circulation; (ii) isotopic assessment (δ³⁴S–SO₄, δ¹⁸O–SO₄, δ¹¹B, ⁸⁷Sr/⁸⁶Sr, δ¹³C–TDIC) to provide insights on circulation depth and water–rock interaction pathways; (iii) high-frequency monitoring (monthly/quarterly, up to two years) to evaluate temporal stability and resilience of physico-chemical parameters, major and trace elements, and water isotopes. The integrated analysis reveals that a few sites exhibit groundwaters affected by the combination of (i) temporal stability and geochemical resilience, (ii) deep circulation and structurally controlled pathways and (iii) proximity to active seismogenic structures, making then optimal candidates for the inclusion in a long-term hydrochemistry monitoring network. By contrast, other sites, despite showing favourable characteristics are context-dependent, being affected by shallow flow paths or moderate seasonal variability, thus making them unfit for the research purposes.
The proposed methodology is scalable, reproducible, and readily transferable to other geodynamic settings. By providing a transparent, data-driven workflow for site selection, this approach strengthens the robustness of hydrogeochemical monitoring networks and enhances their capability to detect earthquake-related anomalies, thereby offering a practical framework for seismic surveillance initiatives worldwide.
How to cite: Chemeri, L., Taussi, M., Cabassi, J., Barberio, M. D., Fronzi, D., Renzulli, A., and Vaselli, O.: A three-step hydrogeochemical approach for groundwater monitoring networks in seismically active areas, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9132, https://doi.org/10.5194/egusphere-egu26-9132, 2026.
Robust Satellite Techniques (RST) applied to long, homogeneous time series of thermal infrared (TIR) satellite radiances have been used for almost three decades to detect space–time anomalies potentially related to the preparation phase of strong earthquakes. Previous multi-year investigations—often based on background datasets longer than a decade and carried out across different continents and tectonic settings—showed that over two thirds of the identified, space–time persistent anomalies fall within a predefined spatial and temporal window around earthquakes with magnitude M ≥ 4, with a false-positive rate below one third. In addition, Molchan error diagram analyses provided evidence that the observed association departs from random-guess behavior.
After comprehensive tests performed over Greece, Italy, Turkey, and Japan, we focus here on California and critically discuss the most recent advances achieved using GOES observations. Preliminary experiments based on GOES-17 TIR radiances and a four-year background (2019–2022) yielded encouraging results for M6+ earthquakes, with a gain probability of approximately 1.6 and 67% of events successfully alerted. However, the four-year limit reflects data-availability constraints linked to the operational discontinuity and subsequent decommissioning of GOES-17, while RST is known to require background datasets that are both homogeneous and statistically robust.
To increase the statistical significance of the assessment, we extend the analysis to a seven-year dataset (2019–2025) by integrating GOES-17 and GOES-18. The feasibility of this integration was preliminarily verified using the temporal overlap between the two sensors, checking for the absence of significant differences and ensuring consistency with the homogeneity requirements of RST. We finally discuss the results obtained from the extended GOES-17/18 record and their implications for short-term seismic hazard experiments.
How to cite: Colonna, R., Genzano, N., Mancusi, I., Filizzola, C., Lisi, M., Pergola, N., Nayak, K., and Tramutoli, V.: Robust Satellite Techniques for short-term seismic hazard forecast over California using a multi-year continuous GOES-17/18 TIR record, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13823, https://doi.org/10.5194/egusphere-egu26-13823, 2026.
Accurate and efficient seismic disaster risk assessment is essential for disaster prevention and emergency response, particularly in active tectonic zones characterized by complex geological and geomorphological conditions. However, existing approaches often fail to comprehensively integrate multiple influencing factors or to adequately capture regional heterogeneity. This study proposes a novel three-dimensional integrated framework for seismic risk assessment that combines subsurface structure, surface environment, and building characteristics, based on multi-source remote sensing data and detailed field investigations. The results demonstrate that fault dynamics play a dominant role in controlling seismic risk differentiation, with hanging-wall areas exhibiting a 42.6% higher comprehensive risk than footwall regions (p < 0.05). Mortality risk increases sharply within 200 m of active faults (odds ratio = 3.17, p < 0.01), reflecting the combined effects of fault properties, topography, and site conditions. Moreover, strong coupling between geomorphological factors and structural vulnerability significantly amplifies disaster impacts, as evidenced by the prevalence of vulnerable civil structures (91.31%) within MMI IX zones and the resulting pronounced spatial variability in mortality. An optimized village-level risk assessment model further achieves high predictive accuracy (R² = 0.7494), with spatial patterns closely matching observed mortality distributions. These findings highlight the critical roles of fault-related effects (hanging wall and footwall asymmetry) and ground-motion amplification mechanisms in shaping earthquake casualty patterns, providing a robust scientific basis for targeted disaster mitigation and prevention strategies in active fault zones. Future work will further incorporate InSAR-derived deformation monitoring and geotechnical investigations to refine the understanding of fault micro-mechanics and to enhance dynamic seismic risk assessment models.
How to cite: chaoxu, X.: Assessment of Seismic Disaster Risk in the Dingri Earthquake Based on Fault-Induced Ground Motion Effects, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4309, https://doi.org/10.5194/egusphere-egu26-4309, 2026.
In this work we evaluate the use of Markov-modulated Poisson Process (MMPP) in the framework of the computation of Peak Ground Acceleration (PGA) for a 475-year return period through a classical Time-Dependent Probabilistic Seismic Hazard Assessment (TD-PSHA) approach. The catalogue of Southern Spain spanning from 1970 to 2023 has been selected using several tectonic zones from the nation seismic zonation as masks for the extraction, then homogenized and declustered.
The MMPP model has been used for the computation of the seismic activity rate and has been tested with different completeness magnitudes (Mc) and number of states. Clear state transitions and coherent results (the high seismic activity rate state corresponds to periods with more high-magnitude earthquakes) can be identified for the Mw3.2 Mc with two states. A set of Ground Motion Models (GMMs) has been preselected and, using accelerometric data from the region, these GMMs have been ranked and used within a logic tree. The hazard curves (at the sites of Lorca, Murcia, Granada and Vera) and the hazard maps have been computed for each MMPP state and have been compared with other studies. The results show that higher PGA values have been obtained in the provinces of Granada, Málaga, Córdoba and Sevilla compared to previous studies. The hazard curves show high Probabilities of Exceedance (PoE) for lower PGA values in the selected sites and lower PoE for the high-end (PGA > 0.3g) of the considered PGA range when compared with other models.
We finally explored whether the proposed scheme can also use tectonic zonation information, splitting the investigated region in sub-zones (given that enough events are selected for each zone), following the approach described in Montiel-Lopez et al. (NHESS, 2025).
How to cite: Montiel, D., Peresan, A., Varini, E., Zuccolo, E., and Molina, S.: Preliminary results on MMPP applied to South-eastern Spain TD-PSHA, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20707, https://doi.org/10.5194/egusphere-egu26-20707, 2026.
Ground motion is widely recognized as a fundamental factor in triggering coseismic landslides; however, in regional-scale analyses, it is still commonly represented by a single scalar indicator (i.e. the Peak Ground Acceleration, PGA), which limits an in-depth understanding of landslide hazards. Considering the 2017 Jiuzhaigou MW 6.5 earthquake and its documented coseismic landslides as a case study, we investigate the relationship between coseismic landslides and the spatial variability of ground motion, as derived by physics- and scenario-based Neo-deterministic Seismic Hazard Assessment (NDSHA). A total of 84 peak ground motion metrics, including PGA, PGV, and PGD across different directional components and frequency bands, are computed and systematically correlated with multiple landslide characteristic parameters. The results show that (i) ground motion components in the radial and north–south directions exhibit the strongest correlation with landslide parameters; (ii) low-frequency ground motion metrics are predominantly and positively associated with landslide point density, area density, and total landslide area, whereas high-frequency metrics are more closely linked to landslide mobility; (iii) PGA- and PGD-related parameters generally outperform PGV in terms of correlation strength across all four landslide descriptors; and (iv) incorporating multiple peak ground motion parameters improves coseismic landslide susceptibility prediction by up to 8.4% compared with the commonly used USGS PGA ShakeMap. The obtained results demonstrate that no single ground motion parameter can fully capture the landslides pattern, and different ground motion parameters should be used for different landslide parameters to improve the accuracy and applicability of the regional coseismic landslide assessment.
How to cite: Wu, C., Zhang, Y., Cui, P., Romanelli, F., Peresan, A., Wei, R., and Panza, G.: Exploratory relationships between selected ground motion parameters and coseismic landslides: A case study of the 2017 Jiuzhaigou MW6.5 earthquake, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20898, https://doi.org/10.5194/egusphere-egu26-20898, 2026.
Coastal areas in the northeastern Adriatic Sea are exposed to the complex interplay of different geophysical and climate-related hazards, including tsunamis, storm surges, subsidence, and sea-level rise. Although tsunamis are rare and moderate size events in the Adriatic region, still they can have significant impacts in densely populated and highly vulnerable coastal areas. This study presents a comprehensive, scenario-based tsunami risk assessment for the coastal municipality of Lignano Sabbiadoro (Friuli Venezia Giulia, Italy), a major touristic hub characterized by flat morphology, fragile lagoon ecosystems, and marked seasonal variations of population.
The study integrates multi-scenario tsunami modelling, up to date high-resolution exposure data, and buildings vulnerability with the aim to quantify tsunami risk at the urban scale. Tsunami hazard is characterized by means of inundation modelling (water depth) performed by the NAMI DANCE software (e.g. Zaytsev et al., 2019. Sci Tsunami Haz, 38), using a refined topo-bathymetric grid at 25 m resolution. This approach overcomes the limitations of continental-scale probabilistic hazard maps and related simplified empirical relationships by explicitly accounting for local bathymetry, topography, and small-scale coastal features, resulting in highly heterogeneous and realistic inundation patterns.
Exposure for population and residential buildings is assessed at 30 m resolution, following a recently developed methodology (Badreldin et al., IJDRR 2025), to ensure consistency with the tsunami hazard scenarios resolution. The residential building stock is classified into eight typologies based on construction material, age and design code level, and building height. Population exposure is further disaggregated, according to built-up volume and weighted storey distributions, allowing for a more specific characterisation of people potentially affected by tsunami inundation. When dealing with seasonal population variability, the analysis is focused on areas with highest inundation depths (e.g. exceeding 1 m), where population occupancy is empirically estimated in low-season conditions (resident population only) and high-season conditions (full touristic occupancy). This allows us quantifying the number of people potentially affected under different seasonal scenarios and supports discussion on the critical role of tourists in the most severely impacted zones.
Structural damage is quantified using vulnerability curves for common Italian building typologies available from the literature (e.g. Del Zoppo et al., 2022, Bull Geophys Oceanogr, 63). These curves are combined with consequence models to estimate damage states, economic losses, and potential human impacts. Results indicate that most buildings would experience no or slight non-structural damage, while older, gravity-load-designed masonry mid-rise buildings emerge as the most vulnerable typology and can be potentially damaged in the areas with higher inundation depths.
Overall, the study demonstrates the added value of high-resolution, physics-based, multi-scenario tsunami risk modelling for coastal urban areas. The proposed methodology provides the basis for site-specific emergency planning, land-use management, and the development of integrated multi-hazard risk and adaptation strategies, particularly in touristic coastal regions facing increasing pressures from climate change and urban development.
How to cite: Peresan, A., Hassan, H. M., Badreldin, H., and Scaini, C.: Integrating earthquake-induced tsunami scenarios modelling and high-resolution exposure data towards risk assessment in a urban coastal area, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19854, https://doi.org/10.5194/egusphere-egu26-19854, 2026.
This study examines the relationship between ground motion parameters and building damage during the 2016 Mw 6.4 Meinong earthquake in southern Taiwan. We integrate strong-motion recordings from 599 Taiwan Strong Motion Instrumentation Program (TSMIP) stations with a georeferenced dataset of 626 damaged buildings (271 red-tagged, 355 yellow-tagged) in Tainan City. Results show that structural damage began at thresholds of ~150-175 gal for peak ground acceleration (PGA) and ~10-20 cm/s for peak ground velocity (PGV). Regression analysis indicates that PGA correlates much more strongly with building damage (r = 0.98 for red-tagged, 0.81 for yellow-tagged) than PGV (r = 0.46 and 0.26). About 70% of damaged buildings were low-rise (1-3 stories), consistent with resonance effects from short-period ground motions. Local soil liquefaction further contributed to failures in some areas with modest PGV. These findings highlight the dominant role of PGA in assessing low-rise building vulnerability, while PGV remains relevant for high-rise damage. We conclude that both parameters should be jointly considered in seismic impact assessments. This work provides the first quantitative validation of PGA and PGV against Taiwan’s updated red/yellow-tagged building damage classification, establishing a benchmark for future risk evaluation.
How to cite: Wu, Y.-M. and Song, G.-Y.: Relationship between ground motion parameters and building damage for 2016 Mw 6.4 Meinong, Taiwan earthquake, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2287, https://doi.org/10.5194/egusphere-egu26-2287, 2026.
As the most immediately impacted population, survivors’ mobility and distribution characteristics are closely linked to earthquake emergency response. Accurate population distribution and mobility data are vital foundational resources for post-disaster decision-making. With the help of mobile phone location data within the earthquake-stricken area, we explore novel rapid assessment approaches to identifying perceived impact area.
The widespread adoption of smart mobile devices in China has led to the installation of numerous third-party applications. These applications rely on push notification services enabled by Push Software Development Kits (SDKs) provided by mobile service providers. These SDKs, compliant with data security standards, collection scopes, and transmission protocols, utilize built-in functional modules to periodically collect user-authorized geolocation data. This data encompasses device identifiers, GPS coordinates, WiFi signatures, cellular base station logs, and network connectivity metadata. After encryption, these multi-source data streams inputs are aggregated into structured mobile location datasets. They can provide high-resolution insights into population mobility patterns during disasters.
At 9:05 (Beijing time) on 7 January 2025, an earthquake with magnitude Ms 6.8 hit Dingri County, Tibet Autonomous Region, which killed 126 people. We collected a mobile phone location dataset covering a 150 km radius from the epicenter, spanning 38 hours from 9:00 on 6 January to 1:00 on 8 January. It comprises 146,123 records. Each record includes four mobile location-based indicators, namely (1) Active Base Stations (base stations scanned and periodically reported by mobile devices), (2) Active Wi-Fi Hotspots (Wi-Fi hotspots scanned and periodically reported by mobile devices), (3) Mobile Devices (mobile devices that obtain services through multiple positioning methods) and (4) Wi-Fi-Connected Devices (mobile devices connected to Wi-Fi hotspots). Utilizing natural neighbor interpolation and Thiessen polygon interpolation methods, we analyzes changes in four mobile location-based indicators and their spatiotemporal distribution characteristics before and after the earthquake, summarizing crowd movement patterns and communication behaviors after the Dingri earthquake. The results indicate an uneven distribution of population and differing dynamics in mobile phone signal activity. This reflects different behavioral patterns and the potential perceived extent of the earthquake. Within 50 km of the epicenter, all four indicators showed varying degrees of decline post-earthquake, while areas beyond 100 km exhibited short-term surges, reflecting differentiated behavioral responses based on seismic impact severity. In areas experiencing strong shaking, risk avoidance behavior predominated, while in areas where shaking was noticeable but less severe, communication behavior was more prominent. Mobile data decline zones showed high spatial correlation with intensity VIII+ regions, proving their effectiveness as rapid indicators for identifying strongly affected areas. Notably, mobile location data enabled accurate identification of strongly affected zones within 30 min post-earthquake.
The research establishes a theoretical-technical framework supporting three critical post-disaster applications: (1) dynamic population distribution sensing, (2) behavioral pattern analysis of affected populations, and (3) rapid evaluation of seismic perception zones.
How to cite: Qi, W. and Li, H.: Dynamic Population Distribution and Perceived Earthquake Impact Area with Mobile Phone Location Data: a case study of the Tibet Dingri Ms 6.8 Earthquake , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13948, https://doi.org/10.5194/egusphere-egu26-13948, 2026.
Improving people 's awareness of earthquake disaster is the basis for enhancing the ability of earthquake prevention and disaster reduction of the whole society. However, existing research remains limited on temporal differences in public awareness of earthquake disasters and on the specific factors driving these changes. To examine whether public awareness of earthquake disasters changes over time following an earthquake, this study uses the Mw 7.9 Wenchuan earthquake that occurred on May 12, 2008, in Sichuan Province, China, as the research background. Based on this event, on-site surveys and return investigations were conducted at two time points—shortly after the earthquake (2008) and 16 years later (2024)—to assess earthquake disaster awareness among junior high school students, senior high school students, secondary school teachers, and parents of secondary school students in Mianzhu County, Sichuan Province, where seismic intensity reached levels VIII-XI. Based on a preliminary comparative analysis of earthquake disaster awareness questionnaires administered at the two time points, the following findings were obtained: from 2008 to 2024, earthquake disaster awareness among people of Mianzhu County, Sichuan Province exhibited both increases and decreases. Specifically, earthquake disaster awareness improved overall among adults, whereas awareness among students remained unchanged or declined, with a notable decline observed among junior high school students. These changes were reflected across the dimensions of knowledge, skills, and attitudes: (1) With respect to earthquake disaster knowledge, students showed an overall decline in their level of understanding, teachers exhibited no substantial change, and parents demonstrated an overall improvement; (2) In terms of disaster mitigation skills and understanding of government actions and measures, all four groups showed overall improvement; (3) Regarding disaster mitigation attitudes, attitudes among adults improved, whereas no noticeable change was observed among students. At the level of individual questionnaire items, these changes were manifested as follows: (i) People in the disaster-affected area showed a significant increase in their awareness of basic earthquake knowledge, fundamental government disaster mitigation policies, and earthquake avoidance precautions; (ii) Adults exhibited significant and varying degrees of improvement in their understanding of government-led earthquake prevention and disaster mitigation efforts, whereas students tended to focus primarily on school-based initiatives (e.g., disaster education, science popularization activities, and emergency drills) and remained largely unaware of other government actions; (iii) Public understanding of secondary earthquake hazards declined markedly, with particularly pronounced decreases observed for barrier lakes and epidemic outbreaks. Through this preliminary temporal comparison of earthquake disaster awareness among disaster-affected populations, key changes across different dimensions of awareness can be identified, thereby providing an empirical basis for developing region-specific and goal-oriented public education and communication strategies.
How to cite: Gao, Y., Su, G., and Qi, W.: A Preliminary Temporal Comparative Study on Earthquake Disaster Awareness among People of Mianzhu County, Sichuan Province, China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8832, https://doi.org/10.5194/egusphere-egu26-8832, 2026.
Posters virtual: Fri, 8 May, 14:00–18:00 | vPoster spot 3
EGU26-16354 | Posters virtual | VPS14
The multiple parameter disturbances and their coupling process around 2025 Dingri Mw7.1 earthquake in ChinaFri, 08 May, 14:33–14:36 (CEST) vPoster spot 3
On 7 January 2025, there took place a strong earthquake in Dingri with Mw7.1 in southern Tibet, China. Due to the complex geographical and geological conditions at this region, only a few ground-based seismic and geophysical observation stations have been installed here, but some typical anomalies have been detected before the earthquake occurrence and gave short-term and imminent prediction opinions, especially from the space-borne technologies. To reveal the whole preparation processes, multiple geophysical and geochemical observation data were collected and analyzed in this research, including regional geomagnetic field and gravity field in the lithosphere, atmospheric infrared longwave radiation (OLR) and methane gas (CH4), GNSS TEC and satellite-detected plasma and magnetic field disturbances in the ionosphere. The temporal and spatial developing characteristics of these anomalies is summarized preceding the Dingri earthquake, providing crucial support for understanding the precursory anomalies and their coupled formation mechanisms, as well as scientific basis for assessing seismic conditions in the region. The results show that, 1) Some methods provided explicit analytical predictions both before and after the earthquake, offering scientific support for regional seismic hazard assessment; 2) Pre-seismic anomalies exhibited rich development, with over 30 cumulative anomalies occurring before the earthquake, particularly showing concentrated development within the 10 days preceding the event; 3) Spatially, anomalies initially developed at long distances in the Earth-ionosphere system, and gradually converging toward the epicenter, as while the anomaly development progressively decreased in the altitude; 4) The thermal infrared and methane gas anomalies emerged during the pre-seismic phase, and fully covered the earthquake occurrence period, indicating that observations closer to the ground surface may provide more significant indicative value for the future epicenter. This seismic research demonstrates the potential of space-based Earth observation technologies to fill vast monitoring gaps in western regions of China and enhances the effectiveness of cross-layer integrated approaches. Future efforts should optimize comprehensive analytical prediction techniques by leveraging the strengths and addressing the weaknesses of different detection technologies, to improve the accuracy of spatio-temporal prediction of the three key seismic parameters.
How to cite: Zhang, X.: The multiple parameter disturbances and their coupling process around 2025 Dingri Mw7.1 earthquake in China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16354, https://doi.org/10.5194/egusphere-egu26-16354, 2026.
